研究论文
A family of large language models for materials research with insights into model adaptability in continued pretraining
Dhruv Ahlawat, Vaibhav Mishra, Sourabh Singh, Mohd Zaki, Vaibhav Bihani, Hargun Singh Grover, Biswajit Mishra, Santiago Miret 等 10 位
Indian Institute of Technology Delhi Brain Physiology Lab Intel (United States) Low Income Investment Fund
来源Nature Machine Intelligence
年份2026
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学术脉络
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材料 / 化学Machine Learning in Materials Science
Block Copolymer Self-Assembly · Composite Material Mechanics
参考文献 42
Topology of the pyroxenes as a function of temperature, pressure, and composition as determined from the procrystal electron density
被引 618Robert T. Downs · American Mineralogist · 2003
Materials Science and Technology
被引 88Sabar D. Hutagalung · InTech eBooks · 2012
SMACT: Semiconducting Materials by Analogy and Chemical Theory
被引 74Daniel W. Davies, Keith T. Butler, Adam Jackson · The Journal of Open Source Software · 2019
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引用本文 3
Structured domain knowledge enables trustworthy materials science question-answering with large language models
被引 0Daegun Lee, Jiwoo Choi, Gyeong Hoon Yi · Digital Discovery · 2026
Organic Chemistry as a Catalyst for AI Innovation: Challenges, Methods, and Emerging Paradigms
被引 0Nitesh V. Chawla, Gisela A. González‐Montiel, Kehan Guo · Chemical Reviews · 2026
An AI assistant for materials scientists
被引 0Nature India · 2026
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