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Recent Submissions

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    Field-theoretic simulations for block copolymer melts using the partial saddle-point approximation
    (MDPI, 2021) Matsen, Mark W.; Beardsley, Thomas M.
    Field-theoretic simulations (FTS) provide an efficient technique for investigating fluctuation effects in block copolymer melts with numerous advantages over traditional particle-based simulations. For systems involving two components (i.e., A and B), the field-based Hamiltonian, H_f[W_-,W_+], depends on a composition field, W_-(r), that controls the segregation of the unlike components and a pressure field, W_+(r), that enforces incompressibility. This review introduces researchers to a promising variant of FTS, in which W_-(r) fluctuates while W_+(r) tracks its mean-field value. The method is described in detail for melts of AB diblock copolymer, covering its theoretical foundation through to its numerical implementation. We then illustrate its application for neat AB diblock copolymer melts, as well as ternary blends of AB diblock copolymer with its A- and B-type parent homopolymers. The review concludes by discussing the future outlook. To help researchers to adopt the method, open-source code is provided in the Supplementary Materials that can be run on either central processing units (CPUs) or graphics processing units (GPUs).
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    Critical point of symmetric binary homopolymer blends
    (2016) Spencer, Russell K. W.; Matsen, Mark W.
    Monte Carlo field-theoretic simulations (MC-FTS) are performed on structurally symmetric binary homopolymer blends for invariant polymerization indexes of N > 10^3. It is shown that the ultraviolet (UV) divergence that plagues MC-FTS at small N can be removed by an appropriate renormalization of the Flory-Huggins interaction parameter, chi, allowing one to extract meaningful results that are independent of the wavevector cutoff. Once the divergence is taken care of, the fluctuation corrections to mean-field theory are found to be exceptionally small. In particular, the disordered-state structure function, S(k), is virtually indistinguishable from the RPA prediction, and there is a slight shift in the critical point, (chi N)_c, that roughly scales as N^-0.5. An implication of the small corrections is that previous experimental determinations of chi based on homopolymer blends should be relatively accurate.
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    Evaluating and Improving Generative Models with Feedback
    (University of Waterloo, 2026-11-05) Jiang, Dongfu
    Generative models can produce many candidate outputs for a request, but deciding which output is good, and what a model should learn next, requires feedback, a judgment of how well an output serves its task. This thesis studies how to obtain such feedback and how to use it, for evaluating generated outputs and for improving the models that produce them. The two uses place different demands on feedback. For evaluation, feedback has to agree with human judgment and explain its judgment. For training, it has to stay reliable while a model is optimized against it. The first part studies feedback for evaluation. For text, I show that feedback can be learned without a reference output, by training an evaluator on error analyses so that it locates and explains each error in a response, and its scores agree with human ratings nearly as well as GPT-4 used as a judge. For images and videos, I collect pairwise human votes on an open platform, use them to rank generative models, and release them as a benchmark on which the best multimodal judge tested agrees with people about half the time, so human preferences remain the reference for this content. The second part studies feedback for improving models, where agreement with people on fixed outputs is not enough. A policy trained against the learned text evaluator learned to refuse rather than answer, raising its reward while its accuracy fell. For code, I synthesize tests for tens of thousands of programming problems and turn execution results into preferences and rewards, which improve both Best-of-N selection and reinforcement learning. For agents that use tools over several turns, I build a reinforcement-learning framework that runs tools inside the training loop, train agents in six domains, and examine two choices in the feedback they receive. Rewarding tool use raises tool calls without necessarily raising task performance, and how much of a tool's output the policy reads can change the result. Across these studies, feedback that evaluates fixed outputs well can behave differently once a model is trained against it, so a training reward needs a measure it does not see, tracked while the model is optimized.
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    Determining the role of fluid flow on lens biomechanics
    (University of Waterloo, 2026-11-05) Gorla, Shilpa
    The vertebrate crystalline lens is a highly specialized, avascular, and transparent structure whose primary function is to change shape to refract incident light onto the retina. With increasing age, however, the lens undergoes progressive compaction of the fiber cells and crosslinking of the structural proteins, causing it to lose its elasticity. This age-dependent decline in lens ability to change shape is called presbyopia, an ocular condition affecting approximately 2 billion people worldwide. The lens of the eye relies on a specialized microcirculatory system (MCS) to maintain transparency, nutrient supply, and volume homeostasis in the absence of a blood supply. Given that the MCS plays an essential role in volume homeostasis and there is an age-related decline in the function of MCS, modulating the components of the MCS with agonists and antagonists offers a powerful approach to understanding the precise mechanism of presbyopia and identifying novel therapeutic targets for presbyopia. Using chickens, which can deform their lenses to induce shape changes and naturally develop age-related presbyopia, this study investigated the following objectives: 1. To determine the effect of modulators of aquaporin 0 (AQP0) and sodium-potassium ATPase (NKA) pumps on the lens biomechanics. 2. To determine whether TRPV1 and TRPV4 are present in the chicken crystalline lens and how modulating them affects lens biomechanics and protein expression. 3. To determine the temperature-dependent role of the lens microcirculatory system (MCS) in regulating lens biomechanics. We found that the chicken model is a robust model for investigating lens biomechanical regulation by the MCS. At room temperature, modulating AQP0, water channels altered lens hydrostatic pressure, whereas NKA modulation affected biomechanics only when ionic or volume homeostasis was disturbed. Western blot analysis confirmed the presence of protein expression of both mechanosensitive TRPV1 and TRPV4 channels in chicken lens tissue, mirroring mammalian expression patterns. TRPV4 modulation altered lens biomechanics exclusively at the physiological temperatures, whereas AQP0 and NKA modulation produced no biomechanical effect at the physiological temperature, highlighting temperature-dependent regulation of the lens microcirculatory system.
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    Universality between experiment and simulation of a diblock copolymer melt
    (American Physical Society, 2016) Beardsley, Thomas M.; Matsen, Mark W.
    The equivalent behavior among analogous block copolymer systems involving chemically distinct molecules or mathematically different models has long hinted at an underlying universality, but only recently has it been rigorously demonstrated by matching results from different simulations. The profound implication of universality is that simple coarse-grained models can be calibrated so as to provide quantitatively accurate predictions to experiment. Here, we provide the first compelling demonstration of this by simulating a polyisoprene-polylactide diblock copolymer melt using a previously calibrated lattice model. The simulation successfully predicts the peak in the disordered-state structure function, the position of the order-disorder transition and the latent heat of the transition in excellent quantitative agreement with experiment. This could mark a new era of precision in the field of block copolymer research.