专题:Machine Learning in Materials Science

This cluster of papers focuses on the application of materials informatics, machine learning, and high-throughput computational techniques to accelerate materials innovation. It encompasses topics such as property predictions, crystal structures, molecular dynamics, and data mining in the context of materials science and engineering.
最新文献
Prompt-Native Semantic Runtimes for Language Models: Inference-Time Semantic Governance, Provenance, Compression, and Document-Level Process Teaching

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THREE THRESHOLDS: Execution, Compression, and Confabulation in Cross-Substrate Traversals of the Space Ark

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Tokens as Computational Units in Data Science and Machine Learning: Mathematical Foundations, Transformer Architecture, Inference Economy, and Caching Systems in Foundational Models

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Architectural Distinction Note: On the Relationship Between the Crimson Hexagonal Archive and the Passioncraft Square — Crimson Hexagon Archive

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Artificial intelligence tools expand scientists’ impact but contract science’s focus

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Machine learning for phase prediction of high entropy carbide ceramics from imbalanced data

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Provenance Documentation: SEM-PROBE-2025-12 — Crimson Hexagon Archive

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Artificial intelligence-driven approaches for materials design and discovery

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unified-information-energy-paradigm-world-calculus

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Rationalizing the d-Band Model from Theory to Practice in Catalyst Design

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近5年高被引文献
Software update: The ORCA program system—Version 5.0

article Full Text OpenAlex 4246 FWCI285.5111

E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials

article Full Text OpenAlex 1558 FWCI103.8908

First-principles Phonon Calculations with Phonopy and Phono3py

article Full Text OpenAlex 1478 FWCI96.0514

Scientific discovery in the age of artificial intelligence

review Full Text OpenAlex 1474 FWCI519.4736

Submitted Publication

dataset Full Text OpenAlex 1327 FWCI0

Implementation strategies in phonopy and phono3py

review Full Text OpenAlex 1117 FWCI105.2545

Scaling deep learning for materials discovery

article Full Text OpenAlex 1071 FWCI101.0104

ProTox 3.0: a webserver for the prediction of toxicity of chemicals

article Full Text OpenAlex 1067 FWCI375.2383

Recent advances and applications of deep learning methods in materials science

article Full Text OpenAlex 1000 FWCI69.4391

ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader coverage, improved performance, API functionality and decision support

article Full Text OpenAlex 827 FWCI291.4616