ucla thesis template

Thesis Statements

What is a thesis statement.

Your thesis statement is one of the most important parts of your paper.  It expresses your main argument succinctly and explains why your argument is historically significant.  Think of your thesis as a promise you make to your reader about what your paper will argue.  Then, spend the rest of your paper–each body paragraph–fulfilling that promise.

Your thesis should be between one and three sentences long and is placed at the end of your introduction.  Just because the thesis comes towards the beginning of your paper does not mean you can write it first and then forget about it.  View your thesis as a work in progress while you write your paper.  Once you are satisfied with the overall argument your paper makes, go back to your thesis and see if it captures what you have argued.  If it does not, then revise it.  Crafting a good thesis is one of the most challenging parts of the writing process, so do not expect to perfect it on the first few tries.  Successful writers revise their thesis statements again and again.

A successful thesis statement:

• makes an historical argument
• takes a position that requires defending
• is historically specific
• is focused and precise
• answers the question, “so what?”

How to write a thesis statement:

Suppose you are taking an early American history class and your professor has distributed the following essay prompt:

“Historians have debated the American Revolution’s effect on women.  Some argue that the Revolution had a positive effect because it increased women’s authority in the family.  Others argue that it had a negative effect because it excluded women from politics.  Still others argue that the Revolution changed very little for women, as they remained ensconced in the home.  Write a paper in which you pose your own answer to the question of whether the American Revolution had a positive, negative, or limited effect on women.”

Using this prompt, we will look at both weak and strong thesis statements to see how successful thesis statements work.

While this thesis does take a position, it is problematic because it simply restates the prompt.  It needs to be more specific about how  the Revolution had a limited effect on women and  why it mattered that women remained in the home.

Revised Thesis:  The Revolution wrought little political change in the lives of women because they did not gain the right to vote or run for office.  Instead, women remained firmly in the home, just as they had before the war, making their day-to-day lives look much the same.

This revision is an improvement over the first attempt because it states what standards the writer is using to measure change (the right to vote and run for office) and it shows why women remaining in the home serves as evidence of limited change (because their day-to-day lives looked the same before and after the war).  However, it still relies too heavily on the information given in the prompt, simply saying that women remained in the home.  It needs to make an argument about some element of the war’s limited effect on women.  This thesis requires further revision.

Strong Thesis: While the Revolution presented women unprecedented opportunities to participate in protest movements and manage their family’s farms and businesses, it ultimately did not offer lasting political change, excluding women from the right to vote and serve in office.

Few would argue with the idea that war brings upheaval.  Your thesis needs to be debatable:  it needs to make a claim against which someone could argue.  Your job throughout the paper is to provide evidence in support of your own case.  Here is a revised version:

Strong Thesis: The Revolution caused particular upheaval in the lives of women.  With men away at war, women took on full responsibility for running households, farms, and businesses.  As a result of their increased involvement during the war, many women were reluctant to give up their new-found responsibilities after the fighting ended.

Sexism is a vague word that can mean different things in different times and places.  In order to answer the question and make a compelling argument, this thesis needs to explain exactly what  attitudes toward women were in early America, and  how those attitudes negatively affected women in the Revolutionary period.

Strong Thesis: The Revolution had a negative impact on women because of the belief that women lacked the rational faculties of men. In a nation that was to be guided by reasonable republican citizens, women were imagined to have no place in politics and were thus firmly relegated to the home.

This thesis addresses too large of a topic for an undergraduate paper.  The terms “social,” “political,” and “economic” are too broad and vague for the writer to analyze them thoroughly in a limited number of pages.  The thesis might focus on one of those concepts, or it might narrow the emphasis to some specific features of social, political, and economic change.

Strong Thesis: The Revolution paved the way for important political changes for women.  As “Republican Mothers,” women contributed to the polity by raising future citizens and nurturing virtuous husbands.  Consequently, women played a far more important role in the new nation’s politics than they had under British rule.

This thesis is off to a strong start, but it needs to go one step further by telling the reader why changes in these three areas mattered.  How did the lives of women improve because of developments in education, law, and economics?  What were women able to do with these advantages?  Obviously the rest of the paper will answer these questions, but the thesis statement needs to give some indication of why these particular changes mattered.

Strong Thesis: The Revolution had a positive impact on women because it ushered in improvements in female education, legal standing, and economic opportunity.  Progress in these three areas gave women the tools they needed to carve out lives beyond the home, laying the foundation for the cohesive feminist movement that would emerge in the mid-nineteenth century.

Thesis Checklist

When revising your thesis, check it against the following guidelines:

• Does my thesis make an historical argument?
• Does my thesis take a position that requires defending?
• Is my thesis historically specific?
• Is my thesis focused and precise?
• Does my thesis answer the question, “so what?”

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Formatting Your UCLA Thesis

Click below for the updated dissertation formatting requirements from the Graduate Division, as of March 2012.

A  LaTeX package  previously maintained (last dated known update in 2010) by John Heidemann is also available. For more information about this package, please consult the  wiki page  provided by git-hub.

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Proposing, Writing, and Filing Your Thesis or Dissertation

You’ll find the most comprehensive information about thesis and dissertation writing in published books. A range of sites, however, do provide advice that is more extensive than mere lists of the document’s components and directives to “revise” and “be concise.”

We’ve listed the most useful sites below in the following categories:

Writing Your Proposal

Resources for Proposal Writers : An annotated list of books and websites compiled by the University of Wisconsin-Madison Writing Center.

Dissertation Proposal Resources : The University of Texas at Austin has a website with real dissertation proposals from a variety of fields, which may be useful for understanding possible options for organization and other aspects; and examples of successful NSF and Fulbright proposals.

Writing Thesis and Dissertation Proposals : A detailed document for proposal writers in all disciplines, developed by Penn State’s Graduate Writing Center.

Writing and Presenting Your Thesis or Dissertation : A short, free e-book on thinking about the project, writing the proposal, completing the project, and defending it, by S. Joseph Levine of Michigan State University.

Writing Your Thesis and Dissertation

Resources for Dissertators : An annotated list of books and websites compiled by the University of Wisconsin-Madison Writing Center.

Dissertation Calculator : Enter the start date and target completion date for your dissertation, and get a timeline of research and writing milestones, which range from creating a dissertation support network to writing the abstract. Clicking on any milestone will retrieve a page of detailed advice, along with links. Developed by the University of Minnesota.

Dissertations : Resources and tips from UNC Chapel Hill’s Writing Center for their dissertation boot camp.

PhinisheD : A discussion group for people working on theses and dissertations. You will need to create an account to view posts, and a moderator must approve your registration before you can access them. Once you do have access, though, check out the posts in response to frequently asked questions on managing your dissertation, advisor, and life.

Filing Your Thesis and Dissertation

Policies and Procedures for Dissertation Thesis and Dissertation Preparation and Filing : Did you know that your left and bottom margins have to be at least 1.5 inches wide? Or that your page numbers have to be centered? Read this official UCLA manuscript preparation guide to learn more shocking (and essential) tips.

Thesis and Dissertation Meetings : Attend one of these meetings in the quarter in which you plan to file. UCLA Graduate Division and Library staff will walk you through university regulations, important dates, and the above Policies and Procedures packet.

To report a broken link, please email us at [email protected] .

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Advice for Writing a Thesis

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Thesis & Dissertation Filing Deadlines and Workshops

Winter 2024.

Electronic Thesis & Dissertation Filing Workshops These workshops will inform students about policies and procedures related to filing theses and dissertations. These sessions will cover information for both master’s and doctoral filers. All Graduate students who are filing this year are invited to attend. ~~~ Monday, February 5, 2024 10:45 AM – 12:00 PM (PT) Register Here ~~~ Tuesday, February 20, 2024 11:30 AM – 12:45 PM (PT) Register Here ~~~ Wednesday, February 28, 2024 1:30 PM – 2:45 PM (PT) Register Here ~~~ *RSVP required in order to obtain Zoom link and information.

Electronic Thesis & Dissertation Drop-In Hours Graduate students who are finalizing the formatting of their thesis or dissertation are welcome to attend a drop-in hour and receive assistance and feedback about filing and formatting requirements from APS Analysts. ~~~ Tuesday, February 13, 2024 2:30 PM – 3:30 PM (PT) Register Here ~~~ Thursday, February 22, 2024 1:00 PM – 2:00 PM (PT) Register Here ~~~ Monday, March 4, 2024 10:30 AM – 11:30 AM (PT) Register Here ~~~ *RSVP required in order to obtain Zoom link and information.

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UCLA Electronic Theses and Dissertations

• UCLA Previously Published Works

Optimization-based Planning and Control for Robust and Dexterous Locomotion and Manipulation through Contact

• Shirai, Yuki
• Advisor(s): Hong, Dennis W.

Although robotic locomotion and manipulation have shown some remarkable progress in the real world, the current locomotion and manipulation algorithms are inefficient in performance. They often only work for relatively simple tasks such as walking and running for locomotion and pick-and-place in structured environments (e.g., factory) for manipulation. In contrast, humans can perform quite dexterous tasks through contact as contacts provide additional dexterity to interact with environments. Hence, understanding the underlying contact mechanics plays a key role in designing contact-aware planners, controllers, and estimators for locomotion and manipulation.

However, design for planners, controllers, and estimators is extremely challenging. First, the number of contact states such as making and breaking contact with environments increases dramatically as the number of contacts increases. Thus, the underlying contact dynamics become large-scale non-smooth dynamics. As a result, optimization solvers have difficulties converging due to the non-convexity of the optimization problem.

Second, it is desirable that a robot should be able to interact in unknown environments during operation, leading to generalizable locomotion and manipulation. However, robust planning with frictional interaction with uncertain physical properties is very tough as the robot might cause undesired unexpected contact events. As a result, a robot might not be able to complete its desired task.

Third, once uncertainty is quite large, it is indispensable for closed-loop controllers to stabilize locomotion and manipulation. However, the design of manipulation is quite challenging as most manipulation systems are underactuated and unobservable with potential changes in contact states and modes.

In this dissertation, we present a methodology for contact-rich locomotion and planning using trajectory optimization. We first show that the planner using graph-search planners with trajectory optimization can be beneficial for decreasing the computation complexity. Second, we describe our contact-implicit trajectory optimization for planning of multi-limbed systems for running and climbing. We use decomposition-based optimization techniques to efficiently design a trajectory for a robot subject to various complicated contact constraints such as mixed-integer constraints. Then, we present our robust and stochastic trajectory optimization algorithms for multi-contact systems. We show that our chance-constrained optimization is applicable for planning multi-limbed robots. We also propose covariance steering algorithm for contact-rich systems using a particle filter to approximate a distribution of underlying contact dynamics. Our covariance steering is able to regulate robots' states and contact states simultaneously with probabilistic guarantees. Furthermore, utilizing the underlying structure of contact-rich manipulation, we present robust bilevel trajectory optimization for pivoting manipulation under uncertain physical parameters such as friction coefficients. Our proposed framework is able to design optimal control sequences while improving the worst-case stability margin along the manipulation. Finally, we present our closed-loop controller framework for tool manipulation using visuo-tactile feedback. Our approach enables the robot to achieve tool manipulation under unexpected contact events in closed-loop control fashion with no visual feedback for partially unknown objects.

The perspectives gained from this dissertation provide better insight into developing a contact-rich planning, estimation, and control framework for dexterous locomotion and manipulation in highly unstructured environments.

Energetic Electron Losses Driven by Whistler-Mode Waves in the Inner Magnetosphere: ELFIN observations and theoretical models

• Tsai, Ethan
• Advisor(s): Angelopoulos, Vassilis

Resonant interactions between energetic radiation belt electrons and equatorially-generated whistler-mode waves are widely studied because they yield either electron acceleration or precipitation -- where electrons are scattered and lost into the Earth's atmosphere -- both of which are fundamental to space weather forecasting, which is an increasingly relevant challenge as society scales up its reliance on space technologies. This dissertation investigates the mechanisms that govern the effectiveness of electron losses from Earth's radiation belts driven by whistler-mode waves using novel electron precipitation measurements from the ELFIN CubeSats. A culmination of innovative engineering efforts and a refactored satellite operations program has allowed ELFIN to obtain over 12,500 high-quality, low-altitude electron measurements of the radiation belts. These measurements are uniquely capable of resolving the bounce loss cone, allowing us to probe the physics that drive electron precipitation in great detail. We first present a test particle simulation that directly compares ELFIN-measured electron precipitation with equatorial electron and wave measurements by the THEMIS and MMS spacecraft during magnetic conjunctions, confirming the importance of mid-high latitude wave-power. Next, we demonstrate that test particle simulations combined with an empirical wave amplitude model adequately approximate statistical ELFIN observations at the dawn, day, and dusk MLT sectors, but they significantly underestimate relativistic (>500$keV) electron losses on the nightside. To resolve this discrepancy, we additionally use quasi-linear diffusion simulation methods to find that considering wave obliquity, wave frequency, and plasma density together are required to recover the energetic portion (>100 keV) of precipitating electron spectra without overestimating the loss contributions from the quasi-linear regime (~100 keV). We conclude by presenting the ranges of wave and plasma characteristics necessary for the incorporation of accurately modeled electron loss rates into modern radiation belt models. This unlocks the potential to remotely sense equatorial wave properties using electron precipitation measurements, but also calls for future \textit{in situ} satellite experiments to more deeply understand the interconnected role of energetic electron losses in atmospheric, ionospheric, and magnetospheric dynamics.

Data-Driven Modeling and Control of Extreme Aerodynamic Flows: Super Resolution, Manifold Identification, and Phase-Amplitude Reduction

• Fukami, Kai
• Advisor(s): Taira, Kunihiko

In this thesis, we develop data-driven techniques to analyze unsteady aerodynamic flows under extremely gusty conditions for global field reconstruction, low-order modeling, and control. We first consider global field reconstruction from sparse sensors through the lens of generalized super-resolution analysis. This thesis offers a survey with comprehensive case studies of machine-learning-based super resolution for turbulent flows. Supervised machine-learning-based sparse reconstruction is then performed with vortical flows in a pump sump, an example of industrial turbulence. In addition, we establish a robust sparse reconstruction technique for situations in which the numbers and positions of sensors are changing over time, referred to as a Voronoi- tessellation-assisted convolutional neural network. We demonstrate its performance and robustness against noisy sensor measurements with a range of fluid flow examples. Defining interpolation and extrapolation conditions of machine-learning-based studies in unsteady flows is challenging due to their high-dimensionality and scale-invariant nature. For this reason, we consider nonlinear data-driven scaling of turbulent flows to reveal scale-invariant vortical structures across Reynolds numbers. This nonlinear scaling provides insights for supporting machine-learning-based studies of turbulent flows.To perform flow control leveraging the reconstructed fields from sparse sensors, we then consider constructing a control strategy of flows in a low-order subspace identified by nonlinear machine-learning-based data compression. We develop a nonlinear observable-augmented autoencoder that can incorporate physical observables in identifying a low-dimensional latent manifold. This thesis considers extreme vortex-gust airfoil interactions occurring when modern small aircraft fly in severe atmospheric conditions. Under such extreme aerodynamic situations, wings experience massive separation while exhibiting sharp and highly unsteady aerodynamic force responses. Although it is challenging to analyze the nonlinear, transient nature of extreme aerodynamics with conventional linear techniques, we reveal that the underlying physics of a collection of time-varying vortical flows in a high-dimensional space can be expressed on a low-rank manifold leveraging the present data-driven compression. It is also demonstrated that efficient control strategies can be derived at a minimal cost with the assistance of phase-amplitude reduction on the discovered manifold. These developed data-driven strategies offer a new perspective on reconstructing, modeling, and controlling a range of extremely unsteady flows.

Concrete’s Strength Prediction using Machine Learning Method

• Ouyang, Boya
• Advisor(s): Sant, Gaurav

In this study, I present a comprehensive study that addresses the complex challenge of predicting concrete strength, leveraging the power of advanced machine learning techniques. Recognizing the limitations of traditional prediction models, I have introduced innovative methodologies to enhance accuracy and interpretability in this crucial aspect of construction.

Central to my approach is the development of the Ensemble-Based Outlier Detection (EBOD) algorithm. Recognizing the detrimental impact of noisy data on model performance, I designed EBOD to integrate multiple detection algorithms, thereby significantly reducing the bias associated with single-algorithm methods. This innovation ensures that the datasets used for model training and analysis are of the highest quality, laying a solid foundation for more accurate predictive modeling.

Moving forward, I explored the capabilities of Gaussian Process Regression (GPR) in predicting concrete strength. My work with GPR is not just about prediction; it's about understanding the intricacies of the data. I optimized the GPR model to not only forecast concrete strength with remarkable accuracy but also to quantify the uncertainties associated with these predictions. This dual capability of the GPR model enriches the interpretability of the results, providing deeper insights that are invaluable for material engineering and construction management.

In my pursuit of transparency and interpretability in predictive modeling, I introduced symbolic regression into the study. I recognized the need for models that not only predict but also explain. Symbolic regression offered a solution, enabling me to construct interpretable models that shed light on the underlying physical phenomena governing concrete strength. To enhance the predictive power of these models, I incorporated advanced data augmentation techniques, such as the Synthetic Minority Over-sampling Technique (SMOTE), pushing the boundaries of prediction and understanding in unexplored domains.

A pivotal aspect of my study involved a meticulous analysis of the balance between data volume and the precision of machine learning models. I undertook a comprehensive evaluation of a vast dataset, assessing the performance of various algorithms in predicting concrete strength. This rigorous analysis highlights my commitment to not only advancing the accuracy of predictive models but also to understanding the practical challenges and limitations of employing machine learning in the field of concrete strength prediction.

Through the development of innovative algorithms, the application of advanced machine learning techniques, and a thorough analysis of extensive datasets, I aim to revolutionize the way we predict, understand, and apply concrete strength models in industrial applications, setting new benchmarks for accuracy and interpretability.

Novel Implicit Discretization and Solutions for Elastic Solids and Fluids

• Chen, Jingyu
• Advisor(s): Teran, Joseph M ;
• Kavehpour, Pirouz

Physics-based simulations are a powerful tool in both computer graphics and engineering applications. Implicit discretization is essential for accurate, stable, and efficient simulations of solids and fluids.

In this thesis, we first present a novel implicit Material Point Method (MPM) discretization of spatially varying surface energies. Our discretization is based on surface energy, enabling implicit time stepping and capturing surface gradients without explicitly resolving them as in traction-condition-based approaches. We include an implicit discretization of thermomechanical material coupling with novel particle-based enforcement of Robin boundary conditions. Lastly, we design a particle resampling approach for perfect conservations of linear and angular momentum with Affine-Particle-In-Cell (APIC) [Jiang et al. 2015].

The second part presents a novel deep-learning approach to approximate the solution of large, sparse, symmetric, positive-definite linear systems of equations. Our method is motivated by the conjugate gradients algorithm that iteratively selects search directions for minimizing the matrix norm of the approximation error. We use a deep neural network to accelerate convergence via data-driven improvement of the search direction at each iteration. We demonstrate the efficacy of our approach on discretized Poisson equations with millions of degrees of freedom. Our algorithm can reduce the linear system residual to the target tolerance in a small number of iterations, independent of the problem size, and generalize effectively to various systems beyond those encountered during training.

Finally, we present improvements to Position Based Dynamics (PBD) [Müller et al. 2007] and Extended Position Based Dynamics (XPBD) [Macklin et al. 2016] methods, which are variants of implicit time integrator. PBD/XPBD are powerful methods for the real-time simulation of elastic objects, but they do not always converge. We isolate the root cause in the approximate linearization of the nonlinear backward Euler systems utilized by XPBD. We provide two extensions to XPBD to address the non-convergence and support general hyperelastic models. The following chapter presents a novel position-based nonlinear Gauss-Seidel approach for quasistatic simulations of elastic objects. This approach retains the essential PBD feature of stable behavior with limited computational budgets and allows for convergent behavior when the budgets expand.

Seismic Risk Assessment of Spatially Distributed Levee System in the Sacramento-San Joaquin Delta

• Advisor(s): Brandenberg, Scott

The approximately 1,100 miles of levees in the Sacramento-San Joaquin Delta is critical to aquatic and terrestrial habitat, agriculture, California’s water supply and distribution system, and other infrastructure investments, and the levee system protects them from flooding and salt water intrusion. However, the levee system is threatened by a variety of hazards. Land due to oxidation of the rich Delta peat soils, and due to sea level risk act together to effectively increase the levee hydraulic loading. Consolidation of peat soils beneath levees can lead to their continued settlement over time. Delta levees are also threatened by potential sudden shocks from floods events and earthquakes. Numerous advances with greater proliferation and more sophisticated methods of risk assessments have been made since the most recent risk study of the Delta was completed. Therefore, assessing multi-hazard risks of the Delta levee system by leveraging newly available data and knowledge is of great importance for decision makers to implement improvements in response to those long-term and short-term stressors.This study primarily focuses on seismic risk assessment of Bacon Island in the central Delta. The seismic capacity, demand, spatial correlations of levee systems, and system reliability analysis are four essential components throughout the seismic risk assessment. Newly available LiDAR, bathymetry data, geotechnical site investigation results, and measurements from advanced geophysical tests significantly facilitate determining geometry, soil stratigraphy/layering, and soil property of levees. Consequently, the levee fragility functions which reflect the system seismic capacity are developed from a large number of time-series nonlinear finite element simulations using OpenSees. An overview of updated probabilistic seismic hazard analysis results for the Delta region is discussed. Moreover, an algorithm for selecting a subset of events for hazard-consistent analysis of spatially distributed infrastructures is introduced, and performed to analyze the regional probabilistic seismic hazard analysis of the Bacon Island levee system, which quantifies seismic demand of the levees. The correlation functions of capacity are derived based on field geophysical measurements and geo-statistics analysis. Furthermore, the system reliability analysis using level crossing statistics method is implemented to assess seismic risk for Bacon Island levees based on the developed levee fragility, correlation lengths, and selected event subset.

Uncertainty, portability and ancestry in polygenic scoring

• Advisor(s): Pasaniuc, Bogdan

Polygenic score (PGS) is a tool for understanding an individual's predisposition to certain diseases or complex traits based on its genetic profile. In the burgeoning era of genomic medicine, PGS has emerged as a promising tool in advancing precision healthcare, demonstrating versatile utility such as patient risk stratification, disease risk prediction, and disease subtyping. However, its real application in clinical settings is limited by its uncertainty, bias, and low portability across diverse populations. For example, an individual may receive different genetic risk reports from different providers, and the score for a non-European individual may be less accurate than for a European individual. To fully understand and partially address these limitations, I first developed a Bayesian method to quantify the uncertainty in PGS at the individual level. I find trait-specific genetic architecture such as larger polygenicity and lower heritability combined with a small training sample size will lead to large uncertainty in PGS estimate, which in turn results in unreliable patient stratification in downstream analysis. Next, I expanded this approach to encompass individuals from varied genetic ancestry backgrounds. I find that the PGS performance varied from individual to individual with genetic distance playing a key role in impacting the performance of PGS; larger genetic distance from training data correlates with higher uncertainty and lower accuracy in testing individuals. These findings highlight the necessity of integrating individual-level PGS metrics in personalized medicine and the need for increasing genetic research diversity to ensure equitable and responsible use of PGS in clinical settings.

Enhancing Tumor-Infiltrating T cells with an Exclusive Fuel Source

• Miller, Matthew Lawrence
• Advisor(s): Butte, Manish J

Solid tumors harbor immunosuppressive microenvironments that inhibit tumor-infiltrating lymphocytes (TILs) through the voracious consumption of glucose. We sought to restore TIL function by providing them with an exclusive fuel source. The glucose disaccharide cellobiose, which is a building block of cellulose, contains a β-1,4-glycosidic bond that cannot be hydrolyzed by animals (or their tumors), but fungal and bacterial organisms have evolved enzymes to catabolize cellobiose and use the resulting glucose. By equipping T cells with two proteins that enable import and hydrolysis of cellobiose, we demonstrate that supplementation of cellobiose during glucose withdrawal restores T cell cytokine production and cellular proliferation. Murine tumor growth is suppressed, and survival is prolonged. Offering exclusive access to a natural disaccharide is a new tool that augments cancer immunotherapies. Beyond cancer, this approach could be used to answer questions about the regulation of glucose metabolism across many cell types, biological processes, and diseases.

Organic Semiconductor Aggregates: from Molecular Designs to Device Applications

• Advisor(s): Yang, Yang

Organic semiconductors built on π-conjugated structures have attracted significant attention due to their distinctive optical, electronic, and mechanical properties. These characteristics position them as ideal materials for various electronic devices. Notably, their strong light absorption and efficient charge transport capabilities mark organic semiconductors as promising solutions for addressing the global energy crisis through solar energy conversion. However, precise control of “soft” nanostructures formed by the noncovalently aggregated organic semiconductors for achieving desired optoelectronic properties is challenging, compared to covalently or ionically inorganic semiconductors with rigid architectures. In Chapter 1, I will introduce basic structures and properties of organic semiconductors, especially on their molecular packing behavior. The structure-property relationship of organic semiconductors will be discussed in terms of device applications, such as the development of near-infrared donor and acceptor materials for organic photovoltaics. From molecular designs to device applications, in the following chapters, I will introduce the chemistry of several organic semiconductor aggregates constructed from twisted and nonplanar π-systems and their performances in various solar energy fields, such as photocatalytic hydrogen reaction, organic photovoltaics and perovskite solar cells. In Chapter 2, I will show the self-assembly of noncovalent π-stacked organic frameworks that shows a higher activity for photocatalytic hydrogen evolution. I will first introduce the background of noncovalent π-stacked organic frameworks, which are a subclass of porous materials that consist of crystalline networks formed by self-assembly of organic building blocks through π-π interactions. π-stacked organic frameworks based on spirofluorene as central units and 3-(dicyanomethylidene)indan-1-one as end groups demonstrate strong visible light absorption from 500 nm to 700 nm and high surface area (248 m2 g–1) with 1.8 nm hydrophilic micropores, rendering them well-suited for applications in photocatalysis. The fabricated π-stacked organic frameworks nanoparticles exhibit hydrogen evolution rate up to 152 mmol h-1g-1 at room temperature and 618 mmol h-1g-1 at 70 °C. Cryo-transmission electron microscopy further reveal the native morphology of these nanoparticles and the cocatalyst Pt loading status on them. In Chapter 3, I will discuss the singlet fission property of pentacene polymer and its application in organic photovoltaics. Singlet fission is a process that converts one singlet exciton into two triplet excitons while conserving spin. This exciton multiplication process has the potential to overcome the Shockley-Queisser limit of solar power conversion efficiency. Pentacene with high mobility has proved to be ideal organic semiconductors for singlet fission organic photovoltaics. Nevertheless, the cost-intensive vacuum deposition process and the propensity of molecular aggregation in the solid state to prematurely quench triplet excitons pose challenges for their application in photovoltaics. To address these issues, a pentacene polymer is engineered with pentacene units arranged orthogonally to the polymer backbone. This design facilitates the use of pentacene-based materials in organic photovoltaics as donor materials through solution processing. Rapid conversion of photoexcited singlets into triplet pairs, occurring on a picosecond time scale (495 ps) and further dissociate into two “free” triplet excitons in 9.8 µs are observed in the pentacene polymer via transient absorption spectroscopy. The resulting photovoltaic devices based on pentacene polymer and nonfullerene acceptors demonstrate 1.92% power conversion efficiency. In Chapter 4, I will focus on a helicene-based organic semiconductor and its application as electron transport layer in inverted perovskite solar cells. Electron transport layer materials based on fullerene tend to form large clusters and undergo dimerization when exposed to light, leading to a deterioration in electron transport capability and device degradation. The nonplanar geometry of helicenes proves effective in preventing such aggregation issues, thereby enhancing device stability. We have successfully synthesized a small-molecule n-type organic semiconductor utilizing [6]helicene. This compound was employed as the electron transport layer, n-doped by organic amines, in an inverted perovskite solar cell, achieving an impressive power conversion efficiency of over 16%.

Scalable and Efficient Material Point Methods on Modern Computational Platforms

• Qiu, Yuxing
• Advisor(s): Terzopoulos, Demetri

The challenge of efficiently and plausibly simulating deformable solids and fluids remains significant in the domains of Computer Graphics and Scientific Computing. This dissertation presents an in-depth exploration of physics-based simulation, with an emphasis on the Material Point Method (MPM) --- a dominant technique in this arena. Our research aims to extend the capabilities of MPM, focusing on enhancing its performance, scalability, range of applications, and integration with emerging AI technologies. We first summarize our development of optimized MPM leveraging GPU architectures. This advancement accelerates scenarios involving hundreds of millions of particles in multi-GPU computational environments. Furthermore, the thesis introduces a device-agnostic and distributed MPM framework. This system is adept at dynamically allocating workloads across multiple computing ranks, thus enabling simulations at unprecedented particle-count scales. Additionally, the dissertation examines the application of physics-based simulation, specifically MPM, in real-time contexts. It also integrates simulation with generative AI tasks. This exploration includes developing unified frameworks for simulations, image rendering, and natural language processing, showcasing the versatile applicability of MPM in tackling contemporary computational challenges.

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Research Statements

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A research statement is used when applying for some academic faculty positions and research-intensive positions. A research statement is usually a single-spaced 1-2 page document that describes your research trajectory as a scholar, highlighting growth: from where you began to where you envision going in the next few years. Ultimately, research productivity, focus and future are the most highly scrutinized in academic faculty appointments, particularly at research-intensive universities. Tailor your research statement to the institution to which you are applying – if a university has a strong research focus, emphasize publications; if a university values teaching and research equally, consider ending with a paragraph about how your research complements your teaching and vice versa. Structures of these documents also varies by discipline. See two common structures below.

Structure One:

Introduction: The first paragraph should introduce your research interests in the context of your field, tying the research you have done so far to a distinct trajectory that will take you well into the future.

Summary Of Dissertation: This paragraph should summarize your doctoral research project. Try not to have too much language repetition across documents, such as your abstract or cover letter.

Contribution To Field And Publications: Describe the significance of your projects for your field. Detail any publications initiated from your independent doctoral or postdoctoral research. Additionally, include plans for future publications based on your thesis. Be specific about journals to which you should submit or university presses that might be interested in the book you could develop from your dissertation (if your field expects that). If you are writing a two-page research statement, this section would likely be more than one paragraph and cover your future publication plans in greater detail.

Second Project: If you are submitting a cover letter along with your research statement, then the committee may already have a paragraph describing your second project. In that case, use this space to discuss your second project in greater depth and the publication plans you envision for this project. Make sure you transition from your dissertation to your second large project smoothly – you want to give a sense of your cohesion as a scholar, but also to demonstrate your capacity to conceptualize innovative research that goes well beyond your dissertation project.

Wider Impact Of Research Agenda: Describe the broader significance of your work. What ties your research projects together? What impact do you want to make on your field? If you’re applying for a teaching-oriented institution, how would you connect your research with your teaching?

Structure Two:

25% Previous Research Experience: Describe your early work and how it solidified your interest in your field. How did these formative experiences influence your research interests and approach to research? Explain how this earlier work led to your current project(s).

25% Current Projects: Describe your dissertation/thesis project – this paragraph could be modeled on the first paragraph of your dissertation abstract since it covers all your bases: context, methodology, findings, significance. You could also mention grants/fellowships that funded the project, publications derived from this research, and publications that are currently being developed.

50% Future Work: Transition to how your current work informs your future research. Describe your next major project or projects and a realistic plan for accomplishing this work. What publications do you expect to come out of this research? The last part of the research statement should be customized to demonstrate the fit of your research agenda with the institution.

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• Dissertation & Thesis Template

As a resource for graduate students, sample Word templates are available to assist with the initial formatting of doctoral dissertations and master's theses. Students are expected to fully format their dissertation/thesis according to the   " Preparation and Submission Manual for Doctoral Dissertations and Master's Theses ".

• This template is a starting point and students may have to add or remove sections/text to accurately reflect their document and adhere to all requirements in the manual.
• Graduate Education and Postdoctoral Affairs (GEPA) does not provide technical support for any of the templates below.
• If using these templates, students must still refer to the formatting manual for full instructions.

The below templates are in Word. If you prefer to use LaTeX, here is a recommended unofficial template . We are not able to provide technical support for LaTeX.

Note: opening the Word template in Google Docs may cause auto-formatting features to be lost or auto-formatting features may appear differently.

A sample template of a co-author permission letter and cover letter from the committee chair can be found here . For complete information on submission of permission letters, please see this page and/or refer to the full Manual . 

Master’s Degree Thesis

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Doctoral Degree Dissertation

• Degree Completion
• Dissertation & Thesis Submission
• Dissertation & Thesis Manual

University of California Irvine Thesis

A LaTeX template for thesis and dissertation documents at UC Irvine.

Queries and updates should be directed to https://github.com/lotten/uci-thesis-latex .

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