searching for research papers

A free, AI-powered research tool for scientific literature

• Seif Haridi
• Van der Waals Forces
• Critical Mass

New & Improved API for Developers

Introducing semantic reader in beta.

Stay Connected With Semantic Scholar Sign Up What Is Semantic Scholar? Semantic Scholar is a free, AI-powered research tool for scientific literature, based at the Allen Institute for AI.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Trending Articles

• Alanyl-tRNA synthetase, AARS1, is a lactate sensor and lactyltransferase that lactylates p53 and contributes to tumorigenesis. Zong Z, et al. Cell. 2024. PMID: 38653238
• Labour promotes systemic mobilisation of monocytes, T cell activation and local secretion of chemotactic factors in the intervillous space of the placenta. Vikberg S, et al. Front Immunol. 2023. PMID: 36969250 Free PMC article.
• Efficacy and safety of eco-friendly inhalers: focus on combination ipratropium bromide and albuterol in chronic obstructive pulmonary disease. Panos RJ. Int J Chron Obstruct Pulmon Dis. 2013. PMID: 23658481 Free PMC article. Review.
• Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. GBD 2021 Diseases and Injuries Collaborators. Lancet. 2024. PMID: 38642570
• Sequential CD7 CAR T-Cell Therapy and Allogeneic HSCT without GVHD Prophylaxis. Hu Y, et al. N Engl J Med. 2024. PMID: 38657244

Latest Literature

• Am Heart J (2)
• Am J Med (4)
• Arch Phys Med Rehabil (1)
• Cell Metab (4)
• Gastroenterology (8)
• J Neurosci (4)
• Nat Commun (38)
• Oncogene (1)

NCBI Literature Resources

MeSH PMC Bookshelf Disclaimer

The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.

Stand on the shoulders of giants

Google Scholar provides a simple way to broadly search for scholarly literature. From one place, you can search across many disciplines and sources: articles, theses, books, abstracts and court opinions, from academic publishers, professional societies, online repositories, universities and other web sites. Google Scholar helps you find relevant work across the world of scholarly research.

How are documents ranked?

Google Scholar aims to rank documents the way researchers do, weighing the full text of each document, where it was published, who it was written by, as well as how often and how recently it has been cited in other scholarly literature.

Features of Google Scholar

• Search all scholarly literature from one convenient place
• Explore related works, citations, authors, and publications
• Locate the complete document through your library or on the web
• Keep up with recent developments in any area of research
• Check who's citing your publications, create a public author profile

Disclaimer: Legal opinions in Google Scholar are provided for informational purposes only and should not be relied on as a substitute for legal advice from a licensed lawyer. Google does not warrant that the information is complete or accurate.

• Privacy & Terms

Reference management. Clean and simple.

Google Scholar: the ultimate guide

What is Google Scholar?

Why is google scholar better than google for finding research papers, the google scholar search results page, the first two lines: core bibliographic information, quick full text-access options, "cited by" count and other useful links, tips for searching google scholar, 1. google scholar searches are not case sensitive, 2. use keywords instead of full sentences, 3. use quotes to search for an exact match, 3. add the year to the search phrase to get articles published in a particular year, 4. use the side bar controls to adjust your search result, 5. use boolean operator to better control your searches, google scholar advanced search interface, customizing search preferences and options, using the "my library" feature in google scholar, the scope and limitations of google scholar, alternatives to google scholar, country-specific google scholar sites, frequently asked questions about google scholar, related articles.

Google Scholar (GS) is a free academic search engine that can be thought of as the academic version of Google. Rather than searching all of the indexed information on the web, it searches repositories of:

• universities
• scholarly websites

This is generally a smaller subset of the pool that Google searches. It's all done automatically, but most of the search results tend to be reliable scholarly sources.

However, Google is typically less careful about what it includes in search results than more curated, subscription-based academic databases like Scopus and Web of Science . As a result, it is important to take some time to assess the credibility of the resources linked through Google Scholar.

➡️ Take a look at our guide on the best academic databases .

One advantage of using Google Scholar is that the interface is comforting and familiar to anyone who uses Google. This lowers the learning curve of finding scholarly information .

There are a number of useful differences from a regular Google search. Google Scholar allows you to:

• copy a formatted citation in different styles including MLA and APA
• export bibliographic data (BibTeX, RIS) to use with reference management software
• explore other works have cited the listed work
• easily find full text versions of the article

Although it is free to search in Google Scholar, most of the content is not freely available. Google does its best to find copies of restricted articles in public repositories. If you are at an academic or research institution, you can also set up a library connection that allows you to see items that are available through your institution.

The Google Scholar results page differs from the Google results page in a few key ways. The search result page is, however, different and it is worth being familiar with the different pieces of information that are shown. Let's have a look at the results for the search term "machine learning.”

• The first line of each result provides the title of the document (e.g. of an article, book, chapter, or report).
• The second line provides the bibliographic information about the document, in order: the author(s), the journal or book it appears in, the year of publication, and the publisher.

Clicking on the title link will bring you to the publisher’s page where you may be able to access more information about the document. This includes the abstract and options to download the PDF.

To the far right of the entry are more direct options for obtaining the full text of the document. In this example, Google has also located a publicly available PDF of the document hosted at umich.edu . Note, that it's not guaranteed that it is the version of the article that was finally published in the journal.

Below the text snippet/abstract you can find a number of useful links.

• Cited by : the cited by link will show other articles that have cited this resource. That is a super useful feature that can help you in many ways. First, it is a good way to track the more recent research that has referenced this article, and second the fact that other researches cited this document lends greater credibility to it. But be aware that there is a lag in publication type. Therefore, an article published in 2017 will not have an extensive number of cited by results. It takes a minimum of 6 months for most articles to get published, so even if an article was using the source, the more recent article has not been published yet.
• Versions : this link will display other versions of the article or other databases where the article may be found, some of which may offer free access to the article.
• Quotation mark icon : this will display a popup with commonly used citation formats such as MLA, APA, Chicago, Harvard, and Vancouver that may be copied and pasted. Note, however, that the Google Scholar citation data is sometimes incomplete and so it is often a good idea to check this data at the source. The "cite" popup also includes links for exporting the citation data as BibTeX or RIS files that any major reference manager can import.

Pro tip: Use a reference manager like Paperpile to keep track of all your sources. Paperpile integrates with Google Scholar and many popular academic research engines and databases, so you can save references and PDFs directly to your library using the Paperpile buttons and later cite them in thousands of citation styles:

Although Google Scholar limits each search to a maximum of 1,000 results , it's still too much to explore, and you need an effective way of locating the relevant articles. Here’s a list of pro tips that will help you save time and search more effectively.

You don’t need to worry about case sensitivity when you’re using Google scholar. In other words, a search for "Machine Learning" will produce the same results as a search for "machine learning.”

Let's say your research topic is about self driving cars. For a regular Google search we might enter something like " what is the current state of the technology used for self driving cars ". In Google Scholar, you will see less than ideal results for this query .

The trick is to build a list of keywords and perform searches for them like self-driving cars, autonomous vehicles, or driverless cars. Google Scholar will assist you on that: if you start typing in the search field you will see related queries suggested by Scholar!

If you put your search phrase into quotes you can search for exact matches of that phrase in the title and the body text of the document. Without quotes, Google Scholar will treat each word separately.

This means that if you search national parks , the words will not necessarily appear together. Grouped words and exact phrases should be enclosed in quotation marks.

A search using “self-driving cars 2015,” for example, will return articles or books published in 2015.

Using the options in the left hand panel you can further restrict the search results by limiting the years covered by the search, the inclusion or exclude of patents, and you can sort the results by relevance or by date.

Searches are not case sensitive, however, there are a number of Boolean operators you can use to control the search and these must be capitalized.

• AND requires both of the words or phrases on either side to be somewhere in the record.
• NOT can be placed in front of a word or phrases to exclude results which include them.
• OR will give equal weight to results which match just one of the words or phrases on either side.

➡️ Read more about how to efficiently search online databases for academic research .

In case you got overwhelmed by the above options, here’s some illustrative examples:

Tip: Use the advanced search features in Google Scholar to narrow down your search results.

You can gain even more fine-grained control over your search by using the advanced search feature. This feature is available by clicking on the hamburger menu in the upper left and selecting the "Advanced search" menu item.

Adjusting the Google Scholar settings is not necessary for getting good results, but offers some additional customization, including the ability to enable the above-mentioned library integrations.

The settings menu is found in the hamburger menu located in the top left of the Google Scholar page. The settings are divided into five sections:

• Collections to search: by default Google scholar searches articles and includes patents, but this default can be changed if you are not interested in patents or if you wish to search case law instead.
• Bibliographic manager: you can export relevant citation data via the “Bibliography manager” subsection.
• Languages: if you wish for results to return only articles written in a specific subset of languages, you can define that here.
• Library links: as noted, Google Scholar allows you to get the Full Text of articles through your institution’s subscriptions, where available. Search for, and add, your institution here to have the relevant link included in your search results.
• Button: the Scholar Button is a Chrome extension which adds a dropdown search box to your toolbar. This allows you to search Google Scholar from any website. Moreover, if you have any text selected on the page and then click the button it will display results from a search on those words when clicked.

When signed in, Google Scholar adds some simple tools for keeping track of and organizing the articles you find. These can be useful if you are not using a full academic reference manager.

All the search results include a “save” button at the end of the bottom row of links, clicking this will add it to your "My Library".

To help you provide some structure, you can create and apply labels to the items in your library. Appended labels will appear at the end of the article titles. For example, the following article has been assigned a “RNA” label:

Within your Google Scholar library, you can also edit the metadata associated with titles. This will often be necessary as Google Scholar citation data is often faulty.

There is no official statement about how big the Scholar search index is, but unofficial estimates are in the range of about 160 million , and it is supposed to continue to grow by several million each year.

Yet, Google Scholar does not return all resources that you may get in search at you local library catalog. For example, a library database could return podcasts, videos, articles, statistics, or special collections. For now, Google Scholar has only the following publication types:

• Journal articles : articles published in journals. It's a mixture of articles from peer reviewed journals, predatory journals and pre-print archives.
• Books : links to the Google limited version of the text, when possible.
• Book chapters : chapters within a book, sometimes they are also electronically available.
• Book reviews : reviews of books, but it is not always apparent that it is a review from the search result.
• Conference proceedings : papers written as part of a conference, typically used as part of presentation at the conference.
• Court opinions .
• Patents : Google Scholar only searches patents if the option is selected in the search settings described above.

The information in Google Scholar is not cataloged by professionals. The quality of the metadata will depend heavily on the source that Google Scholar is pulling the information from. This is a much different process to how information is collected and indexed in scholarly databases such as Scopus or Web of Science .

➡️ Visit our list of the best academic databases .

Google Scholar is by far the most frequently used academic search engine , but it is not the only one. Other academic search engines include:

• Science.gov
• Semantic Scholar
• scholar.google.fr : Sur les épaules d'un géant
• scholar.google.es (Google Académico): A hombros de gigantes
• scholar.google.pt (Google Académico): Sobre os ombros de gigantes
• scholar.google.de : Auf den Schultern von Riesen

➡️ Once you’ve found some research, it’s time to read it. Take a look at our guide on how to read a scientific paper .

No. Google Scholar is a bibliographic search engine rather than a bibliographic database. In order to qualify as a database Google Scholar would need to have stable identifiers for its records.

No. Google Scholar is an academic search engine, but the records found in Google Scholar are scholarly sources.

No. Google Scholar collects research papers from all over the web, including grey literature and non-peer reviewed papers and reports.

Google Scholar does not provide any full text content itself, but links to the full text article on the publisher page, which can either be open access or paywalled content. Google Scholar tries to provide links to free versions, when possible.

The easiest way to access Google scholar is by using The Google Scholar Button. This is a browser extension that allows you easily access Google Scholar from any web page. You can install it from the Chrome Webstore .

200 million monthly downloads

24 million monthly readers

3 million authors submit annually

SpringerLink - Home for all research

Discover open access.

• Publish with us

• Track your research

Featured articles and journals

Browse by subject, about springerlink.

Calls for papers

Log in for personalised recommendations.

Ageing in Place

The world’s population is ageing, and with ageing comes an increased risk of disability, multimorbidity and dementia, and an increased need for support. Older people are motivated to stay in their own homes as they age as an alternative to intramural care that is cost-beneficial and often provides...

Urban Lifelines and Supply Chains: Enhancing Resilience and Sustainability with Foundational Technologies

An urban community is an intricate network connected by a myriad of functional systems and subsystems, including civil structures, underground spaces, multi-modal transportation, telecom, energy grids, retail facilities, food systems, and healthcare facilities, all operating with unique spatial and...

Photons to Fuels: Recent Progress of Photocatalytic For CO2 Reduction and H2 Production

To address the detrimental effects of climate change, innovative and timely approaches in renewable energy and environmental chemistry are essential. Photocatalytic conversion of carbon dioxide has garnered significant attention as a viable method for carbon capture and utilization, offering the...

Trending research

Social connection and mortality in UK Biobank: a prospective cohort analysis

From clicks to consequences: a multi-method review of online grocery shopping

Highly efficient flexible structured metasurface by roll-to-roll printing for diurnal radiative cooling

Persistent cognitive slowing in post-covid patients: longitudinal study over 6 months.

Blame it on my youth: the origins of attitudes towards immigration

Creating the ICU of the future: patient-centred design to optimise recovery

Featured journals

SN Applied Sciences is now Discover Applied Sciences! We are excited to announce that SN Applied Sciences moved into our fully OA Discover journal...

Discover Sustainability is an open access journal publishing research across all fields relevant to sustainability. Average number of article...

The Journal of Epidemiology and Global Healthis an international peer reviewed journal which aims to impact global epidemiology and international...

Featured books

As part of Springer Nature, SpringerLink delivers fast access to the depth and breadth of our online collection of journals, eBooks, reference works and protocols across a vast range of subject disciplines.

SpringerLink is the reading platform of choice for hundreds of thousands of researchers worldwide. Find out how to publish your research with Springer Nature .

• Find a journal

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Download 55 million PDFs for free

Explore our top research interests.

Engineering

Anthropology

• Earth Sciences

• Computer Science

• Mathematics

• Health Sciences

Join 259 million academics and researchers

Track your impact.

Share your work with other academics, grow your audience and track your impact on your field with our robust analytics

Discover new research

Get access to millions of research papers and stay informed with the important topics around the world

Publish your work

Publish your research with fast and rigorous service through Academia.edu Publishing. Get instant worldwide dissemination of your work

Unlock the most powerful tools with Academia Premium

Work faster and smarter with advanced research discovery tools

Search the full text and citations of our millions of papers. Download groups of related papers to jumpstart your research. Save time with detailed summaries and search alerts.

• Advanced Search
• PDF Packages of 37 papers
• Summaries and Search Alerts

Share your work, track your impact, and grow your audience

Get notified when other academics mention you or cite your papers. Track your impact with in-depth analytics and network with members of your field.

• Mentions and Citations Tracking
• Advanced Analytics
• Publishing Tools

Real stories from real people

Used by academics at over 15,000 universities

Get started and find the best quality research

• Academia.edu Publishing
•   We're Hiring!
•   Help Center
• Find new research papers in:
• Cognitive Science
• Academia ©2024

🇺🇦    make metadata, not war

A comprehensive bibliographic database of the world’s scholarly literature

The world’s largest collection of open access research papers, machine access to our vast unique full text corpus, core features, indexing the world’s repositories.

We serve the global network of repositories and journals

Comprehensive data coverage

We provide both metadata and full text access to our comprehensive collection through our APIs and Datasets

Powerful services

We create powerful services for researchers, universities, and industry

Cutting-edge solutions

We research and develop innovative data-driven and AI solutions

Committed to the POSI

Cost-free PIDs for your repository

OAI identifiers are unique identifiers minted cost-free by repositories. Ensure that your repository is correctly configured, enabling the CORE OAI Resolver to redirect your identifiers to your repository landing pages.

OAI IDs provide a cost-free option for assigning Persistent Identifiers (PIDs) to your repository records. Learn more.

Who we serve?

Enabling others to create new tools and innovate using a global comprehensive collection of research papers.

“ Our partnership with CORE will provide Turnitin with vast amounts of metadata and full texts that we can ... ” Show more

Gareth Malcolm, Content Partner Manager at Turnitin

Academic institutions.

Making research more discoverable, improving metadata quality, helping to meet and monitor open access compliance.

“ CORE’s role in providing a unified search of repository content is a great tool for the researcher and ex... ” Show more

Nicola Dowson, Library Services Manager at Open University

Researchers & general public.

Tools to find, discover and explore the wealth of open access research. Free for everyone, forever.

“ With millions of research papers available across thousands of different systems, CORE provides an invalu... ” Show more

Jon Tennant, Rogue Paleontologist and Founder of the Open Science MOOC

Helping funders to analyse, audit and monitor open research and accelerate towards open science.

“ Aggregation plays an increasingly essential role in maximising the long-term benefits of open access, hel... ” Show more

Ben Johnson, Research Policy Adviser at Research England

Our services, access to raw data.

Create new and innovative solutions.

Content discovery

Find relevant research and make your research more visible.

Managing content

Manage how your research content is exposed to the world.

Companies using CORE

Gareth Malcolm

Content Partner Manager at Turnitin

Our partnership with CORE will provide Turnitin with vast amounts of metadata and full texts that we can utilise in our plagiarism detection software.

Academic institution using CORE

Kathleen Shearer

Executive Director of the Confederation of Open Access Repositories (COAR)

CORE has significantly assisted the academic institutions participating in our global network with their key mission, which is their scientific content exposure. In addition, CORE has helped our content administrators to showcase the real benefits of repositories via its added value services.

Partner projects

Ben Johnson

Research Policy Adviser

Aggregation plays an increasingly essential role in maximising the long-term benefits of open access, helping to turn the promise of a 'research commons' into a reality. The aggregation services that CORE provides therefore make a very valuable contribution to the evolving open access environment in the UK.

28 Best Academic Search Engines That make your research easier

This post may contain affiliate links that allow us to earn a commission at no expense to you. Learn more

If you’re a researcher or scholar, you know that conducting effective online research is a critical part of your job. And if you’re like most people, you’re always on the lookout for new and better ways to do it. 

I’m sure you are familiar with some research databases. But, top researchers keep an open mind and are always looking for inspiration in unexpected places. 

This article aims to give you an edge over researchers that rely mainly on Google for their entire research process.

Our list of 28 academic search engines will start with the more familiar to less.

Table of Contents

#1. Google Scholar

Google Scholar is an academic search engine that indexes the full text or metadata of scholarly literature across an array of publishing formats and disciplines.

Great for academic research, you can use Google Scholar to find articles from academic journals, conference proceedings, theses, and dissertations. The results returned by Google Scholar are typically more relevant and reliable than those from regular search engines like Google.

Tip: You can restrict your results to peer-reviewed articles only by clicking on the “Scholarly”

• Scholarly results are typically more relevant and reliable than those from regular search engines like Google.
• You can restrict your results to peer-reviewed articles only by clicking on the “Scholarly” tab.
• Google Scholar database Coverage is extensive, with approx. 200 million articles indexed.
• Abstracts are available for most articles.
• Related articles are shown, as well as the number of times an article has been cited.
• Links to full text are available for many articles.
• Abstracts are only a snippet of the full article, so you might need to do additional searching to get the full information you need.
• Not all articles are available in full text.

Google Scholar is completely free.

#2. ERIC (Education Resources Information Center) 

ERIC (short for educational resources information center) is a great academic search engine that focuses on education-related literature. It is sponsored by the U.S. Department of Education and produced by the Institute of Education Sciences. 

ERIC indexes over a million articles, reports, conference papers, and other resources on all aspects of education from early childhood to higher education. So, search results are more relevant to Education on ERIC. 

• Extensive coverage: ERIC indexes over a million articles, reports, and other resources on all aspects of education from early childhood to higher education.
• You can limit your results to peer-reviewed journals by clicking on the “Peer-Reviewed” tab.
• Great search engine for educators, as abstracts are available for most articles.

ERIC is a free online database of education-related literature. 

You might also like:

• SCI Journal: Science Journal Impact Factor
• 15 Best Websites to Download Research Papers for Free
• 11 Best Academic Writing Tools For Researchers 2024
• 10 Best Reference Management Software for Research 2024
• Academic Tools

#3. Wolfram Alpha

Wolfram Alpha is a “computational knowledge engine” that can answer factual questions posed in natural language. It can be a useful search tool. 

Type in a question like “What is the square root of 64?” or “What is the boiling point of water?” and Wolfram Alpha will give you an answer.

Wolfram Alpha can also be used to find academic articles. Just type in your keywords and Wolfram Alpha will generate a list of academic articles that match your query.

Tip: You can restrict your results to peer-reviewed journals by clicking on the “Scholarly” tab.

• Can answer factual questions posed in natural language.
• Can be used to find academic articles.
• Results are ranked by relevance.
• Results can be overwhelming, so it’s important to narrow down your search criteria as much as possible.
• The experience feels a bit more structured but it could also be a bit restrictive

Wolfram Alpha offers a few pricing options, including a “Pro” subscription that gives you access to additional features, such as the ability to create custom reports. You can also purchase individual articles or download them for offline use.

Pro costs $5.49 and Pro Premium costs $9.99

#4. iSEEK Education 

• 15 Best Websites To Download Research Papers For Free
• 30+ Essential Software For Researchers
• 15 Best Academic Research Trend Prediction Platforms
• 15 Best Academic Networking And Collaboration Platforms

iSEEK is a search engine targeting students, teachers, administrators, and caregiver. It’s designed to be safe with editor-reviewed content.

iSEEK Education also includes a “Cited by” feature which shows you how often an article has been cited by other researchers.

• Editor-reviewed content.
• “Cited by” feature shows how often an article has been cited by other researchers.
• Limited to academic content.
• Doesn’t have the breadth of coverage that some of the other academic search engines have.

iSEEK Education is free to use.

#5. BASE (Bielefeld Academic Search Engine)

BASE is hosted at Bielefeld University in Germany and that’s where it name stems from (Bielefeld Academic Search Engine). 

Known as “one of the most comprehensive academic web search engines,” it contains over 100 million documents from 4,000 different sources. 

Users can narrow their search using the advanced search option, so regardless of whether you need a book, a review, a lecture, a video or a thesis, BASE has what you need.

BASE indexes academic articles from a variety of disciplines, including the arts, humanities, social sciences, and natural sciences.

• One of the world’s most voluminous search engines, 
• Indexes academic articles from a variety of disciplines, especially for academic web resources
• Includes an “Advanced Search” feature that lets you restrict your results to peer-reviewed journals.
• Doesn’t include abstracts for most articles.
• Doesn’t have related articles, references, cited by

BASE is free to use.

• 10 Best Reference Management Software for Research 2023
• 15 Best Academic Networking and Collaboration Platforms
• 30+ Essential Software for Researchers
• 15 Best Academic Blogging and Content Management 
• 11 Best Academic Writing Tools For Researchers

CORE is an academic search engine that focuses on open access research papers. A link to the full text PDF or complete text web page is supplied for each search result. It’s academic search engine dedicated to open access research papers.

• Focused on open access research papers.
• Links to full text PDF or complete text web page are supplied for each search result.
• Export formats include BibTeX, Endnote, RefWorks, Zotero.
• Coverage is limited to open access research papers.
• No abstracts are available for most articles.
• No related articles, references, or cited by features.

CORE is free to use.

• Best Plagiarism Checkers for Research Papers in 2024

#7. Science.gov

Science.gov is a search engine developed and managed by the United States government. It includes results from a variety of scientific databases, including NASA, EPA, USGS, and NIST. 

US students are more likely to have early exposure to this tool for scholarly research. 

• Coverage from a variety of scientific databases (200 million articles and reports).
• Links to full text are available for some articles.

Science.gov is free to use.

• 15 Best Academic Journal Discovery Platforms
• Sci Hub Review 

#8. Semantic Scholar

Semantic Scholar is a recent entrant to the field. Its goal is to provide more relevant and effective search results via artificial intelligence-powered methods that detect hidden relationships and connections between research topics.

• Powered by artificial intelligence, which enhances search results.
• Covers a large number of academic articles (approx. 40 million).
• Related articles, references, and cited by features are all included.
• Links to full text are available for most articles.

Semantic Scholar is free to use.

• 11 Best Academic Writing Tools For Researchers 
• 10 Best Reference Management Software for Research 
• 15 Best Academic Journal Discovery Platforms 

#9. RefSeek

RefSeek searches more than five billion documents, including web pages, books, encyclopedias, journals, and newspapers.

This is one of the free search engines that feels like Yahoo with a massive directory. It could be good when you are just looking for research ideas from unexpected angles. It could lead you to some other database that you might not know such as the CIA The World Factbook, which is a great reference tool.

• Searches more than five billion documents.
• The Documents tab is very focused on research papers and easy to use.
• Results can be filtered by date, type of document, and language.
• Good source for free academic articles, open access journals, and technical reports.
• The navigation and user experience is very dated even to millenials…
• It requires more than 3 clicks to dig up interesting references (which is how it could lead to you something beyond the 1st page of Google)
• The top part of the results are ALL ads (well… it’s free to use)

RefSeek is free to use.

#10. ResearchGate 

A mixture of social networking site + forum + content databases where researchers can build their profile, share research papers, and interact with one another.

Although it is not an academic search engine that goes outside of its site, ResearchGate ‘s library of works offers an excellent choice for any curious scholar.

There are more than 100 million publications available on the site from over 11 million researchers. It is possible to search by publication, data, and author, as well as to ask the researchers questions. 

• A great place to find research papers and researchers.
• Can follow other researchers and get updates when they share new papers or make changes to their profile.
• The network effect can be helpful in finding people who have expertise in a particular topic.
• Interface is not as user friendly
• Can be overwhelming when trying to find relevant papers.
• Some papers are behind a paywall.

ResearchGate is free to use.

• 15 Best Academic Research Trend Prediction Platforms 
• 25 Best Tools for Tracking Research Impact and Citations

#11. DataONE Search (formerly CiteULike) 

A social networking site for academics who want to share and discover academic articles and papers.

• A great place to find academic papers that have been shared by other academics.
• Some papers are behind a paywall

CiteULike is free to use.

#12. DataElixir 

DataElixir is deigned to help you find, understand and use data. It includes a curated list of the best open datasets, tools and resources for data science.

• Dedicated resource for finding open data sets, tools, and resources for data science.
• The website is easy to navigate.
• The content is updated regularly
• The resources are grouped by category.
• Not all of the resources are applicable to academic research.
• Some of the content is outdated.

DataElixir is free to use.

#13. LazyScholar – browser extension

LazyScholar is a free browser plugin that helps you discover free academic full texts, metrics, and instant citation and sharing links. Lazy Scholar is created Colby Vorland, a postdoctoral fellow at Indiana University.

• It can integrate with your library to find full texts even when you’re off-campus.
• Saves your history and provides an interface to find it.
• A pre-formed citation is availlable in over 900 citation styles.
• Can recommend you topics and scans new PubMed listings to suggest new papers
• Results can be a bit hit or miss

LazyScholar is free to use.

#14. CiteseerX – digital library from PenState

CiteseerX is a digital library stores and indexes research articles in Computer Science and related fields. The site has a robust search engine that allows you to filter results by date, author.

• Searches a large number of academic papers.
• Results can be filtered by date, author, and topic.
• The website is easy to use.
• You can create an account and save your searches for future reference.

CiteseerX is free to use.

• Surfer Review: Is It Worth It?
• 25 Best Tools For Tracking Research Impact And Citations

#15. The Lens – patents search 

The Lens or the Patent Lens is an online patent and scholarly literature search facility, provided by Cambia, an Australia-based non-profit organization.

• Searches for a large number of academic papers.

The price range can be free for non-profit use to $5,000 for commercial enterprise.

#16. Fatcat – wiki for bibliographic catalog 

Fatcat is an open bibliographic catalog of written works. The scope of works is somewhat flexible, with a focus on published research outputs like journal articles, pre-prints, and conference proceedings. Records are collaboratively editable, versioned, available in bulk form, and include URL-agnostic file-level metadata.

• Open source and collaborative
• You can be part of the community that is very focused on its mission
• The archival file-level metadata (verified digests and long-term copies) is a great feature.
• Could prove to be another rabbit hole
• People either love or hate the text-only interface

#17. Lexis Web – Legal database

Are you researching legal topics? You can turn to Lexis Web for any law-related questions you may have. The results are drawn from legal sites and can be filtered based on criteria such as news, blogs, government, and commercial. Additionally, users can filter results by jurisdiction, practice area, source and file format.

• Results are drawn from legal sites.
• Filters are available based on criteria such as news, blogs, government, and commercial.
• Users can filter results by jurisdiction, practice area, source and file format.
• Not all law-related questions will be answered by this search engine.
• Coverage is limited to legal sites only.

Lexis Web is free for up to three searches per day. After that, a subscription is required.

#18. Infotopia – part of the VLRC family

Infotopia touts itself as an “alternative to Google safe search.” Scholarly book results are curated by librarians, teachers, and other educational workers. Users can select from a range of topics such as art, health, and science and technology, and then see a list of resources pertaining to the topic. 

Consequently, if you aren’t able to find what you are looking for within Infotopia’s pages, you will probably find it on one of its many suggested websites.

#19. Virtual Learning Resources Center

Virtual Learning Resources Center (VLRC) is an academic search engine that features thousands of academic sites chosen by educators and librarians worldwide. Using an index generated from a research portal, university, and library internet subject guides, students and instructors can find current, authoritative information for school.

• Thousands of academic information websites indexed by it. You will also be able to get more refined results with custom Google search, which will speed up your research. 
• Many people consider VLRC as one of the best free search engines to start looking for research material. 
• TeachThought rated the Virtual LRC #3 in it’s list of 100 Search Engines For Academic Research
• More relevant to education 
• More relevant to students

Powered by Google Custom Search Engine (CSE), Jurn is a free online search engine for accessing and downloading free full-text scholarly papers. It was created by David Haden in a public open beta version in February 2009, initially for locating open access electronic journal articles in the arts and humanities.

After the indexing process was completed, a website containing additional public directories of web links to indexed publications was introduced in mid-2009. The Jurn search service and directory has been regularly modified and cleaned since then.

• A great resource for finding academic papers that are behind paywalls.
• The content is updated regularly.uren

Jurn is free to use.

#21. WorldWideScience

The Office of Scientific and Technical Information—a branch of the Office of Science within the U.S. Department of Energy—hosts the portal WorldWideScience , which has dubbed itself “The Global Science Gateway.”

Over 70 countries’ databases are used on the website. When a user enters a query, it contacts databases from all across the world and shows results in both English and translated journals and academic resources.

• Results can be filtered by language and type of resource
• Interface is easy to use
• Contains both academic journal articles and translated academic resources 
• The website can be difficult to navigate.

WorldWideScience is free to use.

#22. Google Books

A user can browse thousands of books on Google Books, from popular titles to old titles, to find pages that include their search terms. You can look through pages, read online reviews, and find out where to buy a hard copy once you find the book you are interested in.

#23. DOAJ (Directory of Open Access Journals)

DOAJ is a free search engine for scientific and scholarly materials. It is a searchable database with over 8,000 peer-reviewed research papers organized by subject. It’s one of the most comprehensive libraries of scientific and scholarly resources, with over 8,000 journals available on a variety of themes.

#24. Baidu Scholar

Baidu Xueshu (Academic) is the Chinese version for Google Scholar. IDU Scholar indexes academic papers from a variety of disciplines in both Chinese and English.

• Articles are available in full text PDF.
• Covers a variety of academic disciplines.
• No abstracts are available for most articles, but summaries are provided for some.
• A great portal that takes you to different specialized research platform
• You need to be able to read Chinese to use the site
• Since 2021 there is a rise of focus on China and the Chinese Communist Party

Baidu Scholar is free to use.

#25. PubMed Central

PubMed is a free search engine that provides references and abstracts for medical, life sciences, and biomedical topics.

If you’re studying anything related to healthcare or science, this site is perfect. PublicMed Central is operated by the National Center for Biotechnology Information, a division of the U.S. National Library of Medicine. It contains more than 3 million full-text journal articles. 

It’s similar to PubMed Health, which focuses on health-related research and includes abstracts and citations to over 26 million articles.

#26. MEDLINE®

MEDLINE® is a paid subscription database for life sciences and biomedicine that includes more than 28 million citations to journal articles. For finding reliable, carefully chosen health information, Medline Plus provides a powerful search tool and even a dictionary.

• A great database for life sciences and biomedicine.
• Contains more than 28 million references to journal articles.
• References can be filtered by date, type of document, and language.
• The database is expensive to access.
• Some people find it difficult to navigate and find what they are looking for.

MEDLINE is not free to use ( pricing information ).

Defunct Academic Search Engines 

#27. microsoft academic  .

Microsoft Academic

Microsoft Academic Search seemed to be a failure from the beginning. It ended in 2012, then re-launched in 2016 as Microsoft Academic. It provides the researcher with the opportunity to search academic publications,

Microsoft Academic used to be the second-largest academic search engine after Google Scholar. Microsoft Academic provides a wealth of data for free, but Microsoft has announced that it will shut Microsoft Academic down in by 2022. 

#28. Scizzle

Designed to help researchers stay on top of the literature by setting up email alerts, based on key terms, for newspapers.

Unfortunately, academic search engines come and go. These are two that are no longer available.

Final Thoughts

There are many academic search engines that can help researchers and scholars find the information they need. This list provides a variety of options, starting with more familiar engines and moving on to less well-known ones. 

Keeping an open mind and exploring different sources is essential for conducting effective online research. With so much information at our fingertips, it’s important to make sure we’re using the best tools available to us.

Tell us in the comment below which academic search engine have you not heard of? Which database do you think we should add? What database do your professional societies use? What are the most useful academic websites for research in your opinion?

There is more.

Check out our other articles on the Best Academic Tools Series for Research below.

• Learn how to get more done with these Academic Writing Tools  
• Learn how to proofread your work with these Proofreading Tools
• Learn how to broaden your research landscape with these Academic Search Engines
• Learn how to manage multiple research projects with these Project Management Tools
• Learn how to run effective survey research with these Survey Tools for Research
• Learn how get more insights from important conversations and interviews with Transcription Tools
• Learn how to manage the ever-growing list of references with these Reference Management Software
• Learn how to double your productivity with literature reviews with these AI-Based Summary Generators
• Learn how to build and develop your audience with these Academic Social Network Sites
• Learn how to make sure your content is original and trustworthy with these Plagiarism Checkers
• Learn how to talk about your work effectively with these Science Communication Tools

10 thoughts on “28 Best Academic Search Engines That make your research easier”

Thank you so much Joannah..I have found this information useful to me as librarian in an academic library

You are welcome! We are happy to hear that!

Thank You Team, for providing a comprehensive list of academic search engines that can help make research easier for students and scholars. The variety of search engines included offers a range of options for finding scholarly articles, journals, and other academic resources. The article also provides a brief summary of each search engine’s features, which helps in determining which one is the best fit for a specific research topic. Overall, this article is a valuable resource for anyone looking for a quick and easy way to access a wealth of academic information.

Thank you for taking the time to share your feedback with us. We are delighted to hear that you found our list of academic search engines helpful in making research easier for students and scholars. We understand the importance of having a variety of options when it comes to finding scholarly articles, journals, and other academic resources, and we strive to provide a comprehensive list of resources to meet those needs.

We are glad that you found the brief summary of each search engine’s features helpful in determining which one is the best fit for a specific research topic. Our goal is to make it easy for our readers to access valuable academic information and we’re glad that we were able to achieve that for you.

We appreciate your support and thank you for your kind words. We will continue to provide valuable resources for students and researchers in the future. Please let us know if you have any further questions or suggestions.

No more questions Thank You

I cannot thank you enough!!! thanks alot 🙂

Typography animation is a technique that combines text and motion to create visually engaging and dynamic animations. It involves animating individual letters, words, or phrases in various ways to convey a message, evoke emotions, or enhance the visual impact of a design or video. – Typography Animation Techniques Tools and Online Software {43}

Hi Joannah! Here’s another one you may want to add! Expontum ( https://www.expontum.com/ ) – Helps researchers quickly find knowledge gaps and identify what research projects have been completed before. Thanks!

Expontum – Helps researchers quickly find knowledge gaps and identify what research projects have been completed before. Expontum is free, open access, and available to all globally with no paid versions of the site. Automated processes scan research article information 24/7 so this website is constantly updating. By looking at over 35 million research publications (240 million by the end of 2023), the site has 146 million tagged research subjects and 122 million tagged research attributes. Learn more about methodology and sources on the Expontum About Page ( https://www.expontum.com/about.php )

Hey Ryan, I clicked and checked your site and thought it was very relevant to our reader. Thank you for sharing. And, we will be reviewing your site soon.

Sounds good! Thanks, Joannah!

Leave a Comment Cancel reply

Save my name, email, and website in this browser for the next time I comment.

We maintain and update science journals and scientific metrics. Scientific metrics data are aggregated from publicly available sources. Please note that we do NOT publish research papers on this platform. We do NOT accept any manuscript.

2012-2024 © scijournal.org

Where to find peer reviewed articles for research

This is our ultimate guide to helping you get familiar with your research field and find peer reviewed articles in the Web of Science™. It forms part of our Research Smarter series. 

Finding relevant research and journal articles in your field is critical to a successful research project. Unfortunately, it can be one of the hardest, most time-consuming challenges for academics.

This blog outlines how you can leverage the Web of Science citation network to complete an in-depth, comprehensive search for literature. We share insights about how you can find a research paper and quickly assess its impact. We also explain how to create alerts to keep track of new papers in your field – whether you’re new to the topic or about to embark on a literature review.

• Choosing research databases for your search
• Where to find peer reviewed articles? Master the keyword search
• Filter your results and analyze for trends
• Explore the citation network
• Save your searches and set up alerts for new journal articles

1. Choosing research databases for your search

The myriad search engines, research databases and data repositories all differ in reliability, relevancy and organization of data. This can make it tricky to navigate and assess what’s best for your research at hand.

The Web of Science stands out the most powerful and trusted citation database. It helps you connect ideas and advance scientific research across all fields and disciplines. This is made possible with best-in-class publication and citation data for confident discovery and assessment of journal articles. The Web of Science is also publisher-neutral, carefully-curated by a team of expert editors and consists of 19 different research databases.

The Web of Science Core Collection™ is the single most authoritative source for how to find research articles, discover top authors , and relevant journals . It only includes journals that have met rigorous quality and impact criteria, and it captures billions of cited references from globally significant journals, books and proceedings ( check out its coverage ). Researchers and organizations use this research database regularly to track ideas across disciplines and time.

Explore the Web of Science Core Collection

We recommend spending time exploring the Core Collection specifically because its advanced citation network features are unparalleled. If you are looking to do an exhaustive search of a specific field, you might want to switch to one of the field-specific databases like MEDLINE and INSPEC. You can also select “All databases” from the drop-down box on the main search page. This will cover all research databases your institution subscribes to. IF you are still unsure about where to find scholarly journal articles, you can learn more in our Quick Reference Guide, here, or try it out today.

“We recommend spending time exploring the Core Collection specifically because its advanced citation network features are unparalleled.”

2. Where to find peer reviewed articles? Master the keyword search

A great deal of care and consideration is needed to find peer review articles for research. It starts with your keyword search.

Your chosen keywords or search phrases cannot be too inclusive or limiting. They also require constant iteration as you become more familiar with your research field. Watch this video on search tips to learn more:

It’s worth noting that a repeated keyword search in the same Web of Science database will retrieve almost identical results every time, save for newly-indexed research. Not all research databases do this. If you are conducting a literature review and require a reproducible keyword search, it is best to steer clear of certain databases. For example, a research database that lacks overall transparency or frequently changes its search algorithm may be detrimental to your research.

3. Filter your search results and analyze trends

Group, rank and analyze the research articles in your search results to optimize the relevancy and efficiency of your efforts. In the Web of Science, researchers can cut through the data in a number of creative ways. This will help you when you’re stuck wondering where to find peer reviewed articles, journals and authors. The filter and refine tools , as well as the Analyze Results feature, are all at your disposal for this.

“Group, rank and analyze the research papers in your search results to optimize the relevancy and efficiency of your efforts.”

Filter and Refine tools in the Web of Science

You can opt for basic filter and refine tools in the Web of Science. These include subject category, publication date and open access within your search results. You can also filter by highly-cited research and hot research papers. A hot paper is a journal article that has accumulated rapid and significant numbers of citations over a short period of time.

The Analyze Results tool does much of this and more. It provides an interactive visualization of your results by the most prolific author, institution and funding agency, for example. This, combined, will help you understand trends across your field.

4. Explore the citation network

Keyword searches are essentially an a priori view of the literature. Citation-based searching, on the other hand, leads to “systematic serendipity”. This term was used by Eugene Garfield, the founder of Web of Science. New scientific developments are linked to the global sphere of human knowledge through the citation network. The constantly evolving connections link ideas and lead to systematic serendipity, allowing for all sorts of surprising discoveries.

Exploring the citation network helps you to:

• Identify a seminal research paper in any field. Pay attention to the number of times a journal article is cited to achieve this.
• Track the advancement of research as it progresses over time by analyzing the research papers that cite the original source. This will also help you catch retractions and corrections to research.
• Track the evolution of a research paper backward in time by tracking the work that a particular journal article cites.
• View related references. A research paper may share citations with another piece of work (calculated from bibliographic coupling). That means it’s likely discussing a similar topic.

Visualizing the history discoveries in the citation network

The Web of Science Core Collection indexes every piece of content cover-to-cover. This creates a complete and certain view of more than 115 years of the highest-quality journal articles. The depth of coverage enables you to uncover the historical trail of a research paper in your field. By doing so, it helps you visualize how discoveries unfold through time. You can also learn where they might branch off into new areas of research.  Achieve this in your search by ordering your result set by date of publication.

As PhD student Rachel Ragnhild Carlson (Stanford University) recently wrote in a column for Nature: [1]

”As a PhD student, I’ve learnt to rely not just on my Web of Science research but on numerous conversations with seasoned experts. And I make sure that my reading includes literature from previous decades, which often doesn’t rise to the top of a web search. This practice is reinforced by mentors in my lab, who often find research gems by filtering explicitly for studies greater than ten years old.”

5. Save your search and set up alerts for new journal articles

Save time and keep abreast of new journal articles in your field by saving your searches and setting up email alerts . This means you can return to your search at any time. You can also stay up-to-date about a new research paper included in your search result. This will help you find an article more easily in the future. Head over to Web of Science to try it out today.

“Everyone should set up email alerts with keywords for PubMed, Web of Science, etc. Those keyword lists will evolve and be fine-tuned over time. However, it really helps to get an idea of recent publications.” Thorbjörn Sievert , PhD student, University of Jyväskylä

[1] Ragnhild Carlson, R. 2020 ‘How Trump’s embattled environment agency prepared me for a PhD’, Nature 579, 458

Related posts

Clarivate welcomes the barcelona declaration on open research information.

Demonstrating socioeconomic impact – a historical perspective of ancient wisdom and modern challenges

Unlocking U.K. research excellence: Key insights from the Research Professional News Live summit

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• J Med Libr Assoc
• v.106(4); 2018 Oct

A systematic approach to searching: an efficient and complete method to develop literature searches

Associated data.

Creating search strategies for systematic reviews, finding the best balance between sensitivity and specificity, and translating search strategies between databases is challenging. Several methods describe standards for systematic search strategies, but a consistent approach for creating an exhaustive search strategy has not yet been fully described in enough detail to be fully replicable. The authors have established a method that describes step by step the process of developing a systematic search strategy as needed in the systematic review. This method describes how single-line search strategies can be prepared in a text document by typing search syntax (such as field codes, parentheses, and Boolean operators) before copying and pasting search terms (keywords and free-text synonyms) that are found in the thesaurus. To help ensure term completeness, we developed a novel optimization technique that is mainly based on comparing the results retrieved by thesaurus terms with those retrieved by the free-text search words to identify potentially relevant candidate search terms. Macros in Microsoft Word have been developed to convert syntaxes between databases and interfaces almost automatically. This method helps information specialists in developing librarian-mediated searches for systematic reviews as well as medical and health care practitioners who are searching for evidence to answer clinical questions. The described method can be used to create complex and comprehensive search strategies for different databases and interfaces, such as those that are needed when searching for relevant references for systematic reviews, and will assist both information specialists and practitioners when they are searching the biomedical literature.

INTRODUCTION

Librarians and information specialists are often involved in the process of preparing and completing systematic reviews (SRs), where one of their main tasks is to identify relevant references to include in the review [ 1 ]. Although several recommendations for the process of searching have been published [ 2 – 6 ], none describe the development of a systematic search strategy from start to finish.

Traditional methods of SR search strategy development and execution are highly time consuming, reportedly requiring up to 100 hours or more [ 7 , 8 ]. The authors wanted to develop systematic and exhaustive search strategies more efficiently, while preserving the high sensitivity that SR search strategies necessitate. In this article, we describe the method developed at Erasmus University Medical Center (MC) and demonstrate its use through an example search. The efficiency of the search method and outcome of 73 searches that have resulted in published reviews are described in a separate article [ 9 ].

As we aimed to describe the creation of systematic searches in full detail, the method starts at a basic level with the analysis of the research question and the creation of search terms. Readers who are new to SR searching are advised to follow all steps described. More experienced searchers can consider the basic steps to be existing knowledge that will already be part of their normal workflow, although step 4 probably differs from general practice. Experienced searchers will gain the most from reading about the novelties in the method as described in steps 10–13 and comparing the examples given in the supplementary appendix to their own practice.

CREATING A SYSTEMATIC SEARCH STRATEGY

Our methodology for planning and creating a multi-database search strategy consists of the following steps:

• Determine a clear and focused question
• Describe the articles that can answer the question
• Decide which key concepts address the different elements of the question
• Decide which elements should be used for the best results
• Choose an appropriate database and interface to start with
• Document the search process in a text document
• Identify appropriate index terms in the thesaurus of the first database
• Identify synonyms in the thesaurus
• Add variations in search terms
• Use database-appropriate syntax, with parentheses, Boolean operators, and field codes
• Optimize the search
• Evaluate the initial results
• Check for errors
• Translate to other databases
• Test and reiterate

Each step in the process is reflected by an example search described in the supplementary appendix .

1. Determine a clear and focused question

A systematic search can best be applied to a well-defined and precise research or clinical question. Questions that are too broad or too vague cannot be answered easily in a systematic way and will generally result in an overwhelming number of search results. On the other hand, a question that is too specific will result into too few or even zero search results. Various papers describe this process in more detail [ 10 – 12 ].

2. Describe the articles that can answer the question

Although not all clinical or research questions can be answered in the literature, the next step is to presume that the answer can indeed be found in published studies. A good starting point for a search is hypothesizing what the research that can answer the question would look like. These hypothetical (when possible, combined with known) articles can be used as guidance for constructing the search strategy.

3. Decide which key concepts address the different elements of the question

Key concepts are the topics or components that the desired articles should address, such as diseases or conditions, actions, substances, settings, domains (e.g., therapy, diagnosis, etiology), or study types. Key concepts from the research question can be grouped to create elements in the search strategy.

Elements in a search strategy do not necessarily follow the patient, intervention, comparison, outcome (PICO) structure or any other related structure. Using the PICO or another similar framework as guidance can be helpful to consider, especially in the inclusion and exclusion review stage of the SR, but this is not necessary for good search strategy development [ 13 – 15 ]. Sometimes concepts from different parts of the PICO structure can be grouped together into one search element, such as when the desired outcome is frequently described in a certain study type.

4. Decide which elements should be used for the best results

Not all elements of a research question should necessarily be used in the search strategy. Some elements are less important than others or may unnecessarily complicate or restrict a search strategy. Adding an element to a search strategy increases the chance of missing relevant references. Therefore, the number of elements in a search strategy should remain as low as possible to optimize recall.

Using the schema in Figure 1 , elements can be ordered by their specificity and importance to determine the best search approach. Whether an element is more specific or more general can be measured objectively by the number of hits retrieved in a database when searching for a key term representing that element. Depending on the research question, certain elements are more important than others. If articles (hypothetically or known) exist that can answer the question but lack a certain element in their titles, abstracts, or keywords, that element is unimportant to the question. An element can also be unimportant because of expected bias or an overlap with another element.

Schema for determining the optimal order of elements

Bias in elements

The choice of elements in a search strategy can introduce bias through use of overly specific terminology or terms often associated with positive outcomes. For the question “does prolonged breastfeeding improve intelligence outcomes in children?,” searching specifically for the element of duration will introduce bias, as articles that find a positive effect of prolonged breastfeeding will be much more likely to mention time factors in their titles or abstracts.

Overlapping elements

Elements in a question sometimes overlap in their meaning. Sometimes certain therapies are interventions for one specific disease. The Lichtenstein technique, for example, is a repair method for inguinal hernias. There is no need to include an element of “inguinal hernias” to a search for the effectiveness of the Lichtenstein therapy. Likewise, sometimes certain diseases are only found in certain populations. Adding such an overlapping element could lead to missing relevant references.

The elements to use in a search strategy can be found in the plot of elements in Figure 1 , by following the top row from left to right. For this method, we recommend starting with the most important and specific elements. Then, continue with more general and important elements until the number of results is acceptable for screening. Determining how many results are acceptable for screening is often a matter of negotiation with the SR team.

5. Choose an appropriate database and interface to start with

Important factors for choosing databases to use are the coverage and the presence of a thesaurus. For medically oriented searches, the coverage and recall of Embase, which includes the MEDLINE database, are superior to those of MEDLINE [ 16 ]. Each of these two databases has its own thesaurus with its own unique definitions and structure. Because of the complexity of the Embase thesaurus, Emtree, which contains much more specific thesaurus terms than the MEDLINE Medical Subject Headings (MeSH) thesaurus, translation from Emtree to MeSH is easier than the other way around. Therefore, we recommend starting in Embase.

MEDLINE and Embase are available through many different vendors and interfaces. The choice of an interface and primary database is often determined by the searcher’s accessibility. For our method, an interface that allows searching with proximity operators is desirable, and full functionality of the thesaurus, including explosion of narrower terms, is crucial. We recommend developing a personal workflow that always starts with one specific database and interface.

6. Document the search process in a text document

We advise designing and creating the complete search strategies in a log document, instead of directly in the database itself, to register the steps taken and to make searches accountable and reproducible. The developed search strategies can be copied and pasted into the desired databases from the log document. This way, the searcher is in control of the whole process. Any change to the search strategy should be done in the log document, assuring that the search strategy in the log is always the most recent.

7. Identify appropriate index terms in the thesaurus of the first database

Searches should start by identifying appropriate thesaurus terms for the desired elements. The thesaurus of the database is searched for matching index terms for each key concept. We advise restricting the initial terms to the most important and most relevant terms. Later in the process, more general terms can be added in the optimization process, in which the effect on the number of hits, and thus the desirability of adding these terms, can be evaluated more easily.

Several factors can complicate the identification of thesaurus terms. Sometimes, one thesaurus term is found that exactly describes a specific element. In contrast, especially in more general elements, multiple thesaurus terms can be found to describe one element. If no relevant thesaurus terms have been found for an element, free-text terms can be used, and possible thesaurus terms found in the resulting references can be added later (step 11).

Sometimes, no distinct thesaurus term is available for a specific key concept that describes the concept in enough detail. In Emtree, one thesaurus term often combines two or more elements. The easiest solution for combining these terms for a sensitive search is to use such a thesaurus term in all elements where it is relevant. Examples are given in the supplementary appendix .

8. Identify synonyms in the thesaurus

Most thesauri offer a list of synonyms on their term details page (named Synonyms in Emtree and Entry Terms in MeSH). To create a sensitive search strategy for SRs, these terms need to be searched as free-text keywords in the title and abstract fields, in addition to searching their associated thesaurus terms.

The Emtree thesaurus contains more synonyms (300,000) than MeSH does (220,000) [ 17 ]. The difference in number of terms is even higher considering that many synonyms in MeSH are permuted terms (i.e., inversions of phrases using commas).

Thesaurus terms are ordered in a tree structure. When searching for a more general thesaurus term, the more specific (narrower) terms in the branches below that term will also be searched (this is frequently referred to as “exploding” a thesaurus term). However, to perform a sensitive search, all relevant variations of the narrower terms must be searched as free-text keywords in the title or abstract, in addition to relying on the exploded thesaurus term. Thus, all articles that describe a certain narrower topic in their titles and abstracts will already be retrieved before MeSH terms are added.

9. Add variations in search terms (e.g., truncation, spelling differences, abbreviations, opposites)

Truncation allows a searcher to search for words beginning with the same word stem. A search for therap* will, thus, retrieve therapy, therapies, therapeutic, and all other words starting with “therap.” Do not truncate a word stem that is too short. Also, limitations of interfaces should be taken into account, especially in PubMed, where the number of search term variations that can be found by truncation is limited to 600.

Databases contain references to articles using both standard British and American English spellings. Both need to be searched as free-text terms in the title and abstract. Alternatively, many interfaces offer a certain code to replace zero or one characters, allowing a search for “pediatric” or “paediatric” as “p?ediatric.” Table 1 provides a detailed description of the syntax for different interfaces.

Field codes in five most used interfaces for biomedical literature searching

Searching for abbreviations can identify extra, relevant references and retrieve more irrelevant ones. The search can be more focused by combining the abbreviation with an important word that is relevant to its meaning or by using the Boolean “NOT” to exclude frequently observed, clearly irrelevant results. We advise that searchers do not exclude all possible irrelevant meanings, as it is very time consuming to identify all the variations, it will result in unnecessarily complicated search strategies, and it may lead to erroneously narrowing the search and, thereby, reduce recall.

Searching partial abbreviations can be useful for retrieving relevant references. For example, it is very likely that an article would mention osteoarthritis (OA) early in the abstract, replacing all further occurrences of osteoarthritis with OA . Therefore, it may not contain the phrase “hip osteoarthritis” but only “hip oa.”

It is also important to search for the opposites of search terms to avoid bias. When searching for “disease recurrence,” articles about “disease free” may be relevant as well. When the desired outcome is survival , articles about mortality may be relevant.

10. Use database-appropriate syntax, with parentheses, Boolean operators, and field codes

Different interfaces require different syntaxes, the special set of rules and symbols unique to each database that define how a correctly constructed search operates. Common syntax components include the use of parentheses and Boolean operators such as “AND,” “OR,” and “NOT,” which are available in all major interfaces. An overview of different syntaxes for four major interfaces for bibliographic medical databases (PubMed, Ovid, EBSCOhost, Embase.com, and ProQuest) is shown in Table 1 .

Creating the appropriate syntax for each database, in combination with the selected terms as described in steps 7–9, can be challenging. Following the method outlined below simplifies the process:

• Create single-line queries in a text document (not combining multiple record sets), which allows immediate checking of the relevance of retrieved references and efficient optimization.
• Type the syntax (Boolean operators, parentheses, and field codes) before adding terms, which reduces the chance that errors are made in the syntax, especially in the number of parentheses.
• Use predefined proximity structures including parentheses, such as (() ADJ3 ()) in Ovid, that can be reused in the query when necessary.
• Use thesaurus terms separately from free-text terms of each element. Start an element with all thesaurus terms (using “OR”) and follow with the free-text terms. This allows the unique optimization methods as described in step 11.
• When adding terms to an existing search strategy, pay close attention to the position of the cursor. Make sure to place it appropriately either in the thesaurus terms section, in the title/abstract section, or as an addition (broadening) to an existing proximity search.

The supplementary appendix explains the method of building a query in more detail, step by step for different interfaces: PubMed, Ovid, EBSCOhost, Embase.com, and ProQuest. This method results in a basic search strategy designed to retrieve some relevant references upon which a more thorough search strategy can be built with optimization such as described in step 11.

11. Optimize the search

The most important question when performing a systematic search is whether all (or most) potentially relevant articles have been retrieved by the search strategy. This is also the most difficult question to answer, since it is unknown which and how many articles are relevant. It is, therefore, wise first to broaden the initial search strategy, making the search more sensitive, and then check if new relevant articles are found by comparing the set results (i.e., search for Strategy #2 NOT Strategy #1 to see the unique results).

A search strategy should be tested for completeness. Therefore, it is necessary to identify extra, possibly relevant search terms and add them to the test search in an OR relationship with the already used search terms. A good place to start, and a well-known strategy, is scanning the top retrieved articles when sorted by relevance, looking for additional relevant synonyms that could be added to the search strategy.

We have developed a unique optimization method that has not been described before in the literature. This method often adds valuable extra terms to our search strategy and, therefore, extra, relevant references to our search results. Extra synonyms can be found in articles that have been assigned a certain set of thesaurus terms but that lack synonyms in the title and/or abstract that are already present in the current search strategy. Searching for thesaurus terms NOT free-text terms will help identify missed free-text terms in the title or abstract. Searching for free-text terms NOT thesaurus terms will help identify missed thesaurus terms. If this is done repeatedly for each element, leaving the rest of the query unchanged, this method will help add numerous relevant terms to the query. These steps are explained in detail for five different search platforms in the supplementary appendix .

12. Evaluate the initial results

The results should now contain relevant references. If the interface allows relevance ranking, use that in the evaluation. If you know some relevant references that should be included in the research, search for those references specifically; for example, combine a specific (first) author name with a page number and the publication year. Check whether those references are retrieved by the search. If the known relevant references are not retrieved by the search, adapt the search so that they are. If it is unclear which element should be adapted to retrieve a certain article, combine that article with each element separately.

Different outcomes are desired for different types of research questions. For instance, in the case of clinical question answering, the researcher will not be satisfied with many references that contain a lot of irrelevant references. A clinical search should be rather specific and is allowed to miss a relevant reference. In the case of an SR, the researchers do not want to miss any relevant reference and are willing to handle many irrelevant references to do so. The search for references to include in an SR should be very sensitive: no included reference should be missed. A search that is too specific or too sensitive for the intended goal can be adapted to become more sensitive or specific. Steps to increase sensitivity or specificity of a search strategy can be found in the supplementary appendix .

13. Check for errors

Errors might not be easily detected. Sometimes clues can be found in the number of results, either when the number of results is much higher or lower than expected or when many retrieved references are not relevant. However, the number expected is often unknown, and very sensitive search strategies will always retrieve many irrelevant articles. Each query should, therefore, be checked for errors.

One of the most frequently occurring errors is missing the Boolean operator “OR.” When no “OR” is added between two search terms, many interfaces automatically add an “AND,” which unintentionally reduces the number of results and likely misses relevant references. One good strategy to identify missing “OR”s is to go to the web page containing the full search strategy, as translated by the database, and using Ctrl-F search for “AND.” Check whether the occurrences of the “AND” operator are deliberate.

Ideally, search strategies should be checked by other information specialists [ 18 ]. The Peer Review of Electronic Search Strategies (PRESS) checklist offers good guidance for this process [ 4 ]. Apart from the syntax (especially Boolean operators and field codes) of the search strategy, it is wise to have the search terms checked by the clinician or researcher familiar with the topic. At Erasmus MC, researchers and clinicians are involved during the complete process of structuring and optimizing the search strategy. Each word is added after the combined decision of the searcher and the researcher, with the possibility of directly comparing results with and without the new term.

14. Translate to other databases

To retrieve as many relevant references as possible, one has to search multiple databases. Translation of complex and exhaustive queries between different databases can be very time consuming and cumbersome. The single-line search strategy approach detailed above allows quick translations using the find and replace method in Microsoft Word (<Ctrl-H>).

At Erasmus MC, macros based on the find-and-replace method in Microsoft Word have been developed for easy and fast translation between the most used databases for biomedical and health sciences questions. The schema that is followed for the translation between databases is shown in Figure 2 . Most databases simply follow the structure set by the Embase.com search strategy. The translation from Emtree terms to MeSH terms for MEDLINE in Ovid often identifies new terms that need to be added to the Embase.com search strategy before the translation to other databases.

Schematic representation of translation between databases used at Erasmus University Medical Center

Dotted lines represent databases that are used in less than 80% of the searches.

Using five different macros, a thoroughly optimized query in Embase.com can be relatively quickly translated into eight major databases. Basic search strategies will be created to use in many, mostly smaller, databases, because such niche databases often do not have extensive thesauri or advanced syntax options. Also, there is not much need to use extensive syntax because the number of hits and, therefore, the amount of noise in these databases is generally low. In MEDLINE (Ovid), PsycINFO (Ovid), and CINAHL (EBSCOhost), the thesaurus terms must be adapted manually, as each database has its own custom thesaurus. These macros and instructions for their installation, use, and adaptation are available at bit.ly/databasemacros.

15. Test and reiterate

Ideally, exhaustive search strategies should retrieve all references that are covered in a specific database. For SR search strategies, checking searches for their recall is advised. This can be done after included references have been determined by the authors of the systematic review. If additional papers have been identified through other non-database methods (i.e., checking references in included studies), results that were not identified by the database searches should be examined. If these results were available in the databases but not located by the search strategy, the search strategy should be adapted to try to retrieve these results, as they may contain terms that were omitted in the original search strategies. This may enable the identification of additional relevant results.

A methodology for creating exhaustive search strategies has been created that describes all steps of the search process, starting with a question and resulting in thorough search strategies in multiple databases. Many of the steps described are not new, but together, they form a strong method creating high-quality, robust searches in a relatively short time frame.

Our methodology is intended to create thoroughness for literature searches. The optimization method, as described in step 11, will identify missed synonyms or thesaurus terms, unlike any other method that largely depends on predetermined keywords and synonyms. Using this method results in a much quicker search process, compared to traditional methods, especially because of the easier translation between databases and interfaces (step 13). The method is not a guarantee for speed, since speed depends on many factors, including experience. However, by following the steps and using the tools as described above, searchers can gain confidence first and increase speed through practice.

What is new?

This method encourages searchers to start their search development process using empty syntax first and later adding the thesaurus terms and free-text synonyms. We feel this helps the searcher to focus on the search terms, instead of on the structure of the search query. The optimization method in which new terms are found in the already retrieved articles is used in some other institutes as well but has to our knowledge not been described in the literature. The macros to translate search strategies between interfaces are unique in this method.

What is different compared to common practice?

Traditionally, librarians and information specialists have focused on creating complex, multi-line (also called line-by-line) search strategies, consisting of multiple record sets, and this method is frequently advised in the literature and handbooks [ 2 , 19 – 21 ]. Our method, instead, uses single-line searches, which is critical to its success. Single-line search strategies can be easily adapted by adding or dropping a term without having to recode numbers of record sets, which would be necessary in multi-line searches. They can easily be saved in a text document and repeated by copying and pasting for search updates. Single-line search strategies also allow easy translation to other syntaxes using find-and-replace technology to update field codes and other syntax elements or using macros (step 13).

When constructing a search strategy, the searcher might experience that certain parentheses in the syntax are unnecessary, such as parentheses around all search terms in the title/abstract portion, if there is only one such term, there are double parentheses in the proximity statement, or one of the word groups exists for only one word. One might be tempted to omit those parentheses for ease of reading and management. However, during the optimization process, the searcher is likely to find extra synonyms that might consist of one word. To add those terms to the first query (with reduced parentheses) requires adding extra parentheses (meticulously placing and counting them), whereas, in the latter search, it only requires proper placement of those terms.

Many search methods highly depend on the PICO framework. Research states that often PICO or PICOS is not suitable for every question [ 22 , 23 ]. There are other acronyms than PICO—such as sample, phenomenon of interest, design, evaluation, research type (SPIDER) [ 24 ]—but each is just a variant. In our method, the most important and specific elements of a question are being analyzed for building the best search strategy.

Though it is generally recommended that searchers search both MEDLINE and Embase, most use MEDLINE as the starting point. It is considered the gold standard for biomedical searching, partially due to historical reasons, since it was the first of its kind, and more so now that it is freely available via the PubMed interface. Our method can be used with any database as a starting point, but we use Embase instead of MEDLINE or another database for a number of reasons. First, Embase provides both unique content and the complete content of MEDLINE. Therefore, searching Embase will be, by definition, more complete than searching MEDLINE only. Second, the number of terms in Emtree (the Embase thesaurus) is three times as high as that of MeSH (the MEDLINE thesaurus). It is easier to find MeSH terms after all relevant Emtree terms have been identified than to start with MeSH and translate to Emtree.

At Erasmus MC, the researchers sit next to the information specialist during most of the search strategy design process. This way, the researchers can deliver immediate feedback on the relevance of proposed search terms and retrieved references. The search team then combines knowledge about databases with knowledge about the research topic, which is an important condition to create the highest quality searches.

Limitations of the method

One disadvantage of single-line searches compared to multi-line search strategies is that errors are harder to recognize. However, with the methods for optimization as described (step 11), errors are recognized easily because missed synonyms and spelling errors will be identified during the process. Also problematic is that more parentheses are needed, making it more difficult for the searcher and others to assess the logic of the search strategy. However, as parentheses and field codes are typed before the search terms are added (step 10), errors in parentheses can be prevented.

Our methodology works best if used in an interface that allows proximity searching. It is recommended that searchers with access to an interface with proximity searching capabilities select one of those as the initial database to develop and optimize the search strategy. Because the PubMed interface does not allow proximity searches, phrases or Boolean “AND” combinations are required. Phrase searching complicates the process and is more specific, with the higher risk of missing relevant articles, and using Boolean “AND” combinations increases sensitivity but at an often high loss of specificity. Due to some searchers’ lack of access to expensive databases or interfaces, the freely available PubMed interface may be necessary to use, though it should never be the sole database used for an SR [ 2 , 16 , 25 ]. A limitation of our method is that it works best with subscription-based and licensed resources.

Another limitation is the customization of the macros to a specific institution’s resources. The macros for the translation between different database interfaces only work between the interfaces as described. To mitigate this, we recommend using the find-and-replace functionality of text editors like Microsoft Word to ease the translation of syntaxes between other databases. Depending on one’s institutional resources, custom macros can be developed using similar methods.

Results of the method

Whether this method results in exhaustive searches where no important article is missed is difficult to determine, because the number of relevant articles is unknown for any topic. A comparison of several parameters of 73 published reviews that were based on a search developed with this method to 258 reviews that acknowledged information specialists from other Dutch academic hospitals shows that the performance of the searches following our method is comparable to those performed in other institutes but that the time needed to develop the search strategies was much shorter than the time reported for the other reviews [ 9 ].

CONCLUSIONS

With the described method, searchers can gain confidence in their search strategies by finding many relevant words and creating exhaustive search strategies quickly. The approach can be used when performing SR searches or for other purposes such as answering clinical questions, with different expectations of the search’s precision and recall. This method, with practice, provides a stepwise approach that facilitates the search strategy development process from question clarification to final iteration and beyond.

SUPPLEMENTAL FILE

Acknowledgments.

We highly appreciate the work that was done by our former colleague Louis Volkers, who in his twenty years as an information specialist in Erasmus MC laid the basis for our method. We thank Professor Oscar Franco for reviewing earlier drafts of this article.

Stop doing your research essay wrong way!

Writing a research paper: devil in details..

Another task from a professor made you devastated and lost? Of course, because it's something that no one likes to do. Especially a young student who obviously have dozens of other important things to do. What task we are talking about? The monotonous and long, time consuming and confusing one. Yes, it's all about writing a research paper! Why students don't like it? Well, let's see.

First, the job requires a lot of time necessary for searching, reading, comparing, analyzing and then put together. Finding a topic and the data to do a research is just 30% of the task. The major part is to put everything in a proper format. For example, create a suitable and captivating research paper introduction to arouse your professor interest.

Second, it's the efforts to make everything correct and according to requirements. You don't write make a composition with your thoughts and conclusions in chaotic way. You need to make APA research paper to show your knowledge and proficiency. It takes time as well.

Third, it's the amount of workload. Looking for data, then finding the necessary parts, trying to put everything in a proper order and format. Isn't it easier just to have someone doing it for you?

Research essay: 5 steps to success!

Everyone wants to be a great student. Taking major part in college life, getting straight As, being helpful and easy-going. But what if you need help yourself? For instance, with your research essay. How to get it done and not to be exhausted? Here are some tips to help you!

• Calculate you time right. You'll never be able to finish a task overnight, so don't attempt to make a worthy writing when the deadline is tomorrow. Usually the task to write a paper is given long before the actual deadline.
• Choose the topic correctly. You won't be enjoying your work if you don't like the subject. In every task, even the most boring one, there might be something interesting for you. Be creative. Think outside the box. It might be the key to tremendous success!
• Acknowledge that it's time to give in. If you tried and then you failed, there might be other solutions. Like typing in Google "write my paper for me" and be relieved of the burden of the task.
• Divide the whole work into small tasks and steps. Let's face the truth, no one is able to compose the whole essay at one try. Little by little you'll get to the end of the task, but doing it gradually. And keep in mind the advise number 1!
• Rest! Don't stay in front of your PC until your eyes are red, brain not working, coffee not helping. Have a little walk outside, distract yourself from constant work. After that you'll be able to come back to the task with a new wave of energy.

Always check your paper.

No matter what you decide - to make the writing yourself or use professional service to do the task - keep in mind one general rule! Always check the essay to make sure there are no mistakes. There would be a possibility to make edits after you hand the paper to your professor. Look for spelling mistakes, compare the topic and content, check the format.

Human Capital Spillovers and Health: Does Living Around College Graduates Lengthen Life?

Equally educated people are healthier if they live in more educated places. Every 10 percent point increase in an area’s share of adults with a college degree is associated with a decline in all-cause mortality by 7%, controlling for individual education, demographics, and area characteristics. Area human capital is also associated with lower disease prevalence and improvements in self-reported health. The association between area education and health increased greatly between 1990 and 2010. Spatial sorting does not drive these externalities; there is little evidence that sicker people move disproportionately into less educated areas. Differences in health-related amenities, ranging from hospital quality to pollution, explain no more than 17% of the area human capital spillovers on health. Over half of the correlation between area human capital and health is a result of the correlation between area human capital and smoking and obesity. More educated areas have stricter regulations regarding smoking and more negative beliefs about smoking. These have translated over time into a population that smokes noticeably less and that is less obese, leading to increasing divergence in health outcomes by area education.

Bor and Cutler thank the National Institute for Aging, and Glaeser thanks the Taubman Center for State and Local Government for financial support. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

I have received speaking fees from organizations that organize members that invest in real estate markets, including the National Association of Real Estate Investment Managers, the Pension Real Estate Association and the Association for International Real Estate Investors.

MARC RIS BibTeΧ

Download Citation Data

Working Groups

More from nber.

In addition to working papers , the NBER disseminates affiliates’ latest findings through a range of free periodicals — the NBER Reporter , the NBER Digest , the Bulletin on Retirement and Disability , the Bulletin on Health , and the Bulletin on Entrepreneurship  — as well as online conference reports , video lectures , and interviews .

Help | Advanced Search

Computer Science > Computation and Language

Title: phi-3 technical report: a highly capable language model locally on your phone.

Abstract: We introduce phi-3-mini, a 3.8 billion parameter language model trained on 3.3 trillion tokens, whose overall performance, as measured by both academic benchmarks and internal testing, rivals that of models such as Mixtral 8x7B and GPT-3.5 (e.g., phi-3-mini achieves 69% on MMLU and 8.38 on MT-bench), despite being small enough to be deployed on a phone. The innovation lies entirely in our dataset for training, a scaled-up version of the one used for phi-2, composed of heavily filtered web data and synthetic data. The model is also further aligned for robustness, safety, and chat format. We also provide some initial parameter-scaling results with a 7B and 14B models trained for 4.8T tokens, called phi-3-small and phi-3-medium, both significantly more capable than phi-3-mini (e.g., respectively 75% and 78% on MMLU, and 8.7 and 8.9 on MT-bench).

Submission history

Access paper:.

• HTML (experimental)
• Other Formats

References & Citations

• Google Scholar
• Semantic Scholar

BibTeX formatted citation

Bibliographic and Citation Tools

Code, data and media associated with this article, recommenders and search tools.

• Institution

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs .

Suggestions or feedback?

MIT News | Massachusetts Institute of Technology

• Machine learning
• Social justice
• Black holes
• Classes and programs

Departments

• Aeronautics and Astronautics
• Brain and Cognitive Sciences
• Architecture
• Political Science
• Mechanical Engineering

Centers, Labs, & Programs

• Abdul Latif Jameel Poverty Action Lab (J-PAL)
• Picower Institute for Learning and Memory
• Lincoln Laboratory
• School of Architecture + Planning
• School of Engineering
• School of Humanities, Arts, and Social Sciences
• Sloan School of Management
• School of Science
• MIT Schwarzman College of Computing

Researchers detect a new molecule in space

Press contact :.

Previous image Next image

New research from the group of MIT Professor Brett McGuire has revealed the presence of a previously unknown molecule in space. The team's open-access paper, “ Rotational Spectrum and First Interstellar Detection of 2-Methoxyethanol Using ALMA Observations of NGC 6334I ,” appears in April 12 issue of The Astrophysical Journal Letters .

Zachary T.P. Fried , a graduate student in the McGuire group and the lead author of the publication, worked to assemble a puzzle comprised of pieces collected from across the globe, extending beyond MIT to France, Florida, Virginia, and Copenhagen, to achieve this exciting discovery. 

“Our group tries to understand what molecules are present in regions of space where stars and solar systems will eventually take shape,” explains Fried. “This allows us to piece together how chemistry evolves alongside the process of star and planet formation. We do this by looking at the rotational spectra of molecules, the unique patterns of light they give off as they tumble end-over-end in space. These patterns are fingerprints (barcodes) for molecules. To detect new molecules in space, we first must have an idea of what molecule we want to look for, then we can record its spectrum in the lab here on Earth, and then finally we look for that spectrum in space using telescopes.”

Searching for molecules in space

The McGuire Group has recently begun to utilize machine learning to suggest good target molecules to search for. In 2023, one of these machine learning models suggested the researchers target a molecule known as 2-methoxyethanol. 

“There are a number of 'methoxy' molecules in space, like dimethyl ether, methoxymethanol, ethyl methyl ether, and methyl formate, but 2-methoxyethanol would be the largest and most complex ever seen,” says Fried. To detect this molecule using radiotelescope observations, the group first needed to measure and analyze its rotational spectrum on Earth. The researchers combined experiments from the University of Lille (Lille, France), the New College of Florida (Sarasota, Florida), and the McGuire lab at MIT to measure this spectrum over a broadband region of frequencies ranging from the microwave to sub-millimeter wave regimes (approximately 8 to 500 gigahertz). 

The data gleaned from these measurements permitted a search for the molecule using Atacama Large Millimeter/submillimeter Array (ALMA) observations toward two separate star-forming regions: NGC 6334I and IRAS 16293-2422B. Members of the McGuire group analyzed these telescope observations alongside researchers at the National Radio Astronomy Observatory (Charlottesville, Virginia) and the University of Copenhagen, Denmark. 

“Ultimately, we observed 25 rotational lines of 2-methoxyethanol that lined up with the molecular signal observed toward NGC 6334I (the barcode matched!), thus resulting in a secure detection of 2-methoxyethanol in this source,” says Fried. “This allowed us to then derive physical parameters of the molecule toward NGC 6334I, such as its abundance and excitation temperature. It also enabled an investigation of the possible chemical formation pathways from known interstellar precursors.”

Looking forward

Molecular discoveries like this one help the researchers to better understand the development of molecular complexity in space during the star formation process. 2-methoxyethanol, which contains 13 atoms, is quite large for interstellar standards — as of 2021, only six species larger than 13 atoms were detected outside the solar system , many by McGuire’s group, and all of them existing as ringed structures.  

“Continued observations of large molecules and subsequent derivations of their abundances allows us to advance our knowledge of how efficiently large molecules can form and by which specific reactions they may be produced,” says Fried. “Additionally, since we detected this molecule in NGC 6334I but not in IRAS 16293-2422B, we were presented with a unique opportunity to look into how the differing physical conditions of these two sources may be affecting the chemistry that can occur.”

Share this news article on:

Related links.

• McGuire Lab
• Department of Chemistry

Related Topics

• Space, astronomy and planetary science
• Astrophysics

Related Articles

Found in space: Complex carbon-based molecules

Previous item Next item

More MIT News

Exploring the history of data-driven arguments in public life

Read full story →

Three from MIT awarded 2024 Guggenheim Fellowships

A musical life: Carlos Prieto ’59 in conversation and concert

Two from MIT awarded 2024 Paul and Daisy Soros Fellowships for New Americans

MIT Emerging Talent opens pathways for underserved global learners

The MIT Edgerton Center’s third annual showcase dazzles onlookers

• More news on MIT News homepage →

Massachusetts Institute of Technology 77 Massachusetts Avenue, Cambridge, MA, USA

• Map (opens in new window)
• Events (opens in new window)
• People (opens in new window)
• Careers (opens in new window)
• Accessibility
• Social Media Hub
• MIT on Facebook
• MIT on YouTube
• MIT on Instagram

Numbers, Facts and Trends Shaping Your World

Read our research on:

Full Topic List

Regions & Countries

• Publications
• Our Methods
• Short Reads
• Tools & Resources

Read Our Research On:

How Pew Research Center will report on generations moving forward

Journalists, researchers and the public often look at society through the lens of generation, using terms like Millennial or Gen Z to describe groups of similarly aged people. This approach can help readers see themselves in the data and assess where we are and where we’re headed as a country.

Pew Research Center has been at the forefront of generational research over the years, telling the story of Millennials as they came of age politically and as they moved more firmly into adult life . In recent years, we’ve also been eager to learn about Gen Z as the leading edge of this generation moves into adulthood.

But generational research has become a crowded arena. The field has been flooded with content that’s often sold as research but is more like clickbait or marketing mythology. There’s also been a growing chorus of criticism about generational research and generational labels in particular.

Recently, as we were preparing to embark on a major research project related to Gen Z, we decided to take a step back and consider how we can study generations in a way that aligns with our values of accuracy, rigor and providing a foundation of facts that enriches the public dialogue.

A typical generation spans 15 to 18 years. As many critics of generational research point out, there is great diversity of thought, experience and behavior within generations.

We set out on a yearlong process of assessing the landscape of generational research. We spoke with experts from outside Pew Research Center, including those who have been publicly critical of our generational analysis, to get their take on the pros and cons of this type of work. We invested in methodological testing to determine whether we could compare findings from our earlier telephone surveys to the online ones we’re conducting now. And we experimented with higher-level statistical analyses that would allow us to isolate the effect of generation.

What emerged from this process was a set of clear guidelines that will help frame our approach going forward. Many of these are principles we’ve always adhered to , but others will require us to change the way we’ve been doing things in recent years.

Here’s a short overview of how we’ll approach generational research in the future:

We’ll only do generational analysis when we have historical data that allows us to compare generations at similar stages of life. When comparing generations, it’s crucial to control for age. In other words, researchers need to look at each generation or age cohort at a similar point in the life cycle. (“Age cohort” is a fancy way of referring to a group of people who were born around the same time.)

When doing this kind of research, the question isn’t whether young adults today are different from middle-aged or older adults today. The question is whether young adults today are different from young adults at some specific point in the past.

To answer this question, it’s necessary to have data that’s been collected over a considerable amount of time – think decades. Standard surveys don’t allow for this type of analysis. We can look at differences across age groups, but we can’t compare age groups over time.

Another complication is that the surveys we conducted 20 or 30 years ago aren’t usually comparable enough to the surveys we’re doing today. Our earlier surveys were done over the phone, and we’ve since transitioned to our nationally representative online survey panel , the American Trends Panel . Our internal testing showed that on many topics, respondents answer questions differently depending on the way they’re being interviewed. So we can’t use most of our surveys from the late 1980s and early 2000s to compare Gen Z with Millennials and Gen Xers at a similar stage of life.

This means that most generational analysis we do will use datasets that have employed similar methodologies over a long period of time, such as surveys from the U.S. Census Bureau. A good example is our 2020 report on Millennial families , which used census data going back to the late 1960s. The report showed that Millennials are marrying and forming families at a much different pace than the generations that came before them.

Even when we have historical data, we will attempt to control for other factors beyond age in making generational comparisons. If we accept that there are real differences across generations, we’re basically saying that people who were born around the same time share certain attitudes or beliefs – and that their views have been influenced by external forces that uniquely shaped them during their formative years. Those forces may have been social changes, economic circumstances, technological advances or political movements.

When we see that younger adults have different views than their older counterparts, it may be driven by their demographic traits rather than the fact that they belong to a particular generation.

The tricky part is isolating those forces from events or circumstances that have affected all age groups, not just one generation. These are often called “period effects.” An example of a period effect is the Watergate scandal, which drove down trust in government among all age groups. Differences in trust across age groups in the wake of Watergate shouldn’t be attributed to the outsize impact that event had on one age group or another, because the change occurred across the board.

Changing demographics also may play a role in patterns that might at first seem like generational differences. We know that the United States has become more racially and ethnically diverse in recent decades, and that race and ethnicity are linked with certain key social and political views. When we see that younger adults have different views than their older counterparts, it may be driven by their demographic traits rather than the fact that they belong to a particular generation.

Controlling for these factors can involve complicated statistical analysis that helps determine whether the differences we see across age groups are indeed due to generation or not. This additional step adds rigor to the process. Unfortunately, it’s often absent from current discussions about Gen Z, Millennials and other generations.

When we can’t do generational analysis, we still see value in looking at differences by age and will do so where it makes sense. Age is one of the most common predictors of differences in attitudes and behaviors. And even if age gaps aren’t rooted in generational differences, they can still be illuminating. They help us understand how people across the age spectrum are responding to key trends, technological breakthroughs and historical events.

Each stage of life comes with a unique set of experiences. Young adults are often at the leading edge of changing attitudes on emerging social trends. Take views on same-sex marriage , for example, or attitudes about gender identity .

Many middle-aged adults, in turn, face the challenge of raising children while also providing care and support to their aging parents. And older adults have their own obstacles and opportunities. All of these stories – rooted in the life cycle, not in generations – are important and compelling, and we can tell them by analyzing our surveys at any given point in time.

When we do have the data to study groups of similarly aged people over time, we won’t always default to using the standard generational definitions and labels. While generational labels are simple and catchy, there are other ways to analyze age cohorts. For example, some observers have suggested grouping people by the decade in which they were born. This would create narrower cohorts in which the members may share more in common. People could also be grouped relative to their age during key historical events (such as the Great Recession or the COVID-19 pandemic) or technological innovations (like the invention of the iPhone).

By choosing not to use the standard generational labels when they’re not appropriate, we can avoid reinforcing harmful stereotypes or oversimplifying people’s complex lived experiences.

Existing generational definitions also may be too broad and arbitrary to capture differences that exist among narrower cohorts. A typical generation spans 15 to 18 years. As many critics of generational research point out, there is great diversity of thought, experience and behavior within generations. The key is to pick a lens that’s most appropriate for the research question that’s being studied. If we’re looking at political views and how they’ve shifted over time, for example, we might group people together according to the first presidential election in which they were eligible to vote.

With these considerations in mind, our audiences should not expect to see a lot of new research coming out of Pew Research Center that uses the generational lens. We’ll only talk about generations when it adds value, advances important national debates and highlights meaningful societal trends.

• Age & Generations
• Demographic Research
• Generation X
• Generation Z
• Generations
• Greatest Generation
• Methodological Research
• Millennials
• Silent Generation

Kim Parker is director of social trends research at Pew Research Center

How Teens and Parents Approach Screen Time

Who are you the art and science of measuring identity, u.s. centenarian population is projected to quadruple over the next 30 years, older workers are growing in number and earning higher wages, teens, social media and technology 2023, most popular.

1615 L St. NW, Suite 800 Washington, DC 20036 USA (+1) 202-419-4300 | Main (+1) 202-857-8562 | Fax (+1) 202-419-4372 |  Media Inquiries

Research Topics

• Coronavirus (COVID-19)
• Economy & Work
• Family & Relationships
• Gender & LGBTQ
• Immigration & Migration
• International Affairs
• Internet & Technology
• News Habits & Media
• Non-U.S. Governments
• Other Topics
• Politics & Policy
• Race & Ethnicity
• Email Newsletters

ABOUT PEW RESEARCH CENTER  Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of  The Pew Charitable Trusts .

Copyright 2024 Pew Research Center

Terms & Conditions

Privacy Policy

Cookie Settings

Reprints, Permissions & Use Policy

Search form

• About W&M Libraries
• News & Events

W&M Libraries Announces the 2024 Undergraduate Research Award Winners

The William & Mary Libraries Undergraduate Library Research Awards recognize the creative and original library research completed by William & Mary undergraduate students. Awards are given to students whose papers best illustrate exemplary use of W&M Libraries' tools and resources and the development of information-gathering skills. Four awards are granted each year in two categories: Freshman/Sophomore and Junior/Senior. 

Junior/Senior Category 

Freshman/Sophomore Category: