cond-mat.mtrl-sci

Papers

• Deciphering Acoustic Emission with Machine Learning (2024)
  D\'enes Berta et al.
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• AtomWorld: A Benchmark for Evaluating Spatial Reasoning in Large Language Models on Crystalline Materials (2026)
  Taoyuze Lv et al.
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• MiAD: Mirage Atom Diffusion for De Novo Crystal Generation (2026)
  Andrey Okhotin et al.
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• FluxNet: Learning Capacity-Constrained Local Transport Operators for Conservative and Bounded PDE Surrogates (2026)
  Zishuo Lan et al.
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• Non-normal spectral signatures of instability in neural network training dynamics (2026)
  Souvik Ghosh
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• Sensing Intelligence as a Trainable Metamaterial Property (2026)
  Kyungmi Na et al.
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• Harnessing AtomisticSkills for Agentic Atomistic Research (2026)
  Bowen Deng et al.
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• Reinforcement Learning for Laser Additive Manufacturing Scan-Order Optimisation: A Bilevel Proxy--FEA Diagnostic Framework for Reward and World-Model Diagnosis (2026)
  Xian Wu et al.
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• Machine Learning Multiscale Interactions (2026)
  \`Alex Sol\'e et al.
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• UNATE: UNsupervised ATomic Embedding for crystal structures property prediction (2026)
  Laura Sol\`a-Garcia et al.
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• AutoDFT: A Closed-Loop Multi-Agent Framework for Autonomous DFT Calculations (2026)
  Penghui Yang et al.
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• MatFormBench: A Benchmarking Evaluation Framework for Target-Driven Materials Formulation (2026)
  Linhan Wu et al.
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• AtomComposer: Discovering Chemical Space from First Principles with Reinforcement Learning (2026)
  Bjarke Hastrup et al.
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• LEIA: Learned Environment for Interactive Architected Materials (2026)
  Haiqian Yang et al.
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• Sustainable Metal-Organic Framework Water Harvesters in the Artificial Intelligence Era (2026)
  Reid A. Coyle (Department of Chemistry et al.
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• What drives performance in molecular MPNNs? An operator-level factorial benchmark (2026)
  Panyu Jiao et al.
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