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  1. Abstract

    Large language models (LLMs) have demonstrated tremendous capabilities in solving complex tasks, from quantitative reasoning to understanding natural language. However, LLMs sometimes suffer from confabulations (or hallucinations), which can result in them making plausible but incorrect statements1,2. This hinders the use of current large models in scientific discovery. Here we introduce FunSearch (short for searching in the function space), an evolutionary procedure based on pairing a pretrained LLM with a systematic evaluator. We demonstrate the effectiveness of this approach to surpass the best-known results in important problems, pushing the boundary of existing LLM-based approaches3. Applying FunSearch to a central problem in extremal combinatorics—the cap set problem—we discover new constructions of large cap sets going beyond the best-known ones, both in finite dimensional and asymptotic cases. This shows that it is possible to make discoveries for established open problems using LLMs. We showcase the generality of FunSearch by applying it to an algorithmic problem, online bin packing, finding new heuristics that improve on widely used baselines. In contrast to most computer search approaches, FunSearch searches for programs that describe how to solve a problem, rather than what the solution is. Beyond being an effective and scalable strategy, discovered programs tend to be more interpretable than raw solutions, enabling feedback loops between domain experts and FunSearch, and the deployment of such programs in real-world applications.

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    Free, publicly-accessible full text available January 18, 2025
  2. Abstract Understanding and controlling the development of deformation twins is paramount for engineering strong and stable hexagonal close-packed (HCP) Mg alloys. Actual twins are often irregular in boundary morphology and twin crystallography, deviating from the classical picture commonly used in theory and simulation. In this work, the elastic strains and stresses around irregular twins are examined both experimentally and computationally to gain insight into how twins develop and the microstructural features that influence their development. A nanoprecession electron diffraction (N-PED) technique is used to measure the elastic strains within and around a $$\left\{ {10\overline{1}2} \right\}$$ 10 1 ¯ 2 tensile twin in AZ31B Mg alloy with nm scale resolution. A full-field elasto-viscoplastic fast Fourier transform (EVP-FFT) crystal plasticity model of the same sub-grain and irregular twin structure is employed to understand and interpret the measured elastic strain fields. The calculations predict spatially resolved elastic strain fields in good agreement with the measurement, as well as all the stress components and the dislocation density fields generated by the twin, which are not easily obtainable from the experiment. The model calculations find that neighboring twins, several twin thicknesses apart, have little influence on the twin-tip micromechanical fields. Furthermore, this work reveals that irregularity in the twin-tip shape has a negligible effect on the development of the elastic strains around and inside the twin. Importantly, the major contributor to these micromechanical fields is the alignment of the twinning shear direction with the twin boundary. 
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  3. Application of polycrystalline hexagonal close packed (HCP) metals in engineering designs has been constrained by their anisotropic responses due to twinning and limited plasticity. In deformation, twins most often initiate at grain boundaries (GBs), and thicken and propagate across the grain. In this work, the GB twin embryos in Mg and Mg alloys, and the conditions that influence their propagation are investigated. Using a micromechanical crystal plasticity model, the role of embryo shape on the driving forces prevailing at the embryo boundaries that could support its expansion is studied. The modeled embryos are either planar, extending more in the shear direction than normal to the twin plane, or equiaxed. Results show that the thinner the embryo, the greater the driving forces for both thickening and forward propagation. Alloys with low prismatic-to-basal critical resolved shear stress (CRSS) ratios promote embryo thickening and large CRSS values for the slip mode that primarily accommodates the twin shear encourage propagation. The neighboring grains with orientations that enable local accommodation of the embryo twin shear by pyramidal slip promote forward propagation but have little effect on thickening. When two like embryos lie along the same GB, their paired interaction promotes forward propagation but hinders thickening. 
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  4. Abstract The vertebrate brain consists of diverse neuronal types, classified by distinct anatomy and function, along with divergent transcriptomes and proteomes. Defining the cell-type specific neuroproteomes is important for understanding the development and functional organization of neural circuits. This task remains challenging in complex tissue, due to suboptimal protein isolation techniques that often result in loss of cell-type specific information and incomplete capture of subcellular compartments. Here, we develop a genetically targeted proximity labeling approach to identify cell-type specific subcellular proteomes in the mouse brain, confirmed by imaging, electron microscopy, and mass spectrometry. We virally express subcellular-localized APEX2 to map the proteome of direct and indirect pathway spiny projection neurons in the striatum. The workflow provides sufficient depth to uncover changes in the proteome of striatal neurons following chemogenetic activation of Gα q -coupled signaling cascades. This method enables flexible, cell-type specific quantitative profiling of subcellular proteome snapshots in the mouse brain. 
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