AI for Materials Discovery

Artificial IntelligenceUpdated Oct 5, 2026Version v1

Evidence

Public papers linked to this topic and used as evidence for gaps, timelines, and knowledge views.

83 papers

Showing 49-60 of total 83 evidence records.

Open a paper to inspect abstract, source links, and topic context.

2023OpenAlexSupporting evidence58 citations

2023OpenAlexSupporting evidence98 citations

Data-driven materials science: application of ML for predicting band gap

Soumy Prateek; Rajnish Garg; Kuldeep Kumar Saxena; V.K. Srivastav; Hitesh Vasudev; Nikhil Kumar

Jan 29, 2023Advances in Materials and Processing Technologies

2022CrossrefSupporting evidence125 citations

Data-driven discovery of 2D materials by deep generative models

Peder Lyngby; Kristian Sommer Thygesen

Nov 11, 2022npj Computational Materials

2022CrossrefSupporting evidence91 citations

Artificial Intelligence (AI) in Drugs and Pharmaceuticals

Adarsh Sahu; Jyotika Mishra; Namrata Kushwaha

Sep 1, 2022Combinatorial Chemistry & High Throughput Screening

2022OpenAlexDirectly related410 citations

Interpretable and Explainable Machine Learning for Materials Science and Chemistry

Felipe Oviedo; Juan Lavista Ferres; Tonio Buonassisi; Keith T. Butler

Jun 3, 2022Accounts of Materials Research

2022OpenAlexSupporting evidence51 citations

MaterialsAtlas.org: a materials informatics web app platform for materials discovery and survey of state-of-the-art

Jianjun Hu; Stanislav Stefanov; Yuqi Song; Sadman Sadeed Omee; Steph-Yves Louis; Edirisuriya M. Dilanga Siriwardane; Yong Zhao; Lai Wei

Apr 11, 2022npj Computational Materials

2022CrossrefDirectly related122 citations

Deep Generative Models for Materials Discovery and Machine Learning-Accelerated Innovation

Addis S. Fuhr; Bobby G. Sumpter

Mar 22, 2022Frontiers in Materials

2021OpenAlexSupporting evidence1,697 citations

Artificial intelligence: A powerful paradigm for scientific research

Yongjun Xu; Xin Liu; Xin Cao; Changping Huang; Enke Liu; Sen Qian; Xingchen Liu; Yanjun Wu; Fengliang Dong; Cheng‐Wei Qiu; Junjun Qiu; Keqin Hua; Wentao Su; Jian Wu; Huiyu Xu; Yong Han; Chenguang Fu; Zhigang Yin; Miao Liu; Ronald Roepman; Sabine Dietmann; Marko Virta; Fredrick Orori Kengara; Ze Zhang; Lifu Zhang; Taolan Zhao; Ji Dai; Jialiang Yang; Liang Lan; Ming Luo; Zhaofeng Liu; Tao An; Bin Zhang; Xiao He; Shan Cong; Xiaohong Liu; Wei Zhang; James P. Lewis; James M. Tiedje; Qi Wang; Zhulin An; Fei Wang; Libo Zhang; Tao Huang; Chuan Lü; Zhipeng Cai; Wang Fang; Jiabao Zhang

Oct 28, 2021The Innovation

2021OpenAlexSupporting evidence85 citations

Encoding the atomic structure for machine learning in materials science

Shunning Li; Yuanji Liu; Dong Chen; Yi Jiang; Zhiwei Nie; Feng Pan

Jun 18, 2021Wiley Interdisciplinary Reviews Computational Molecular Science

2021OpenAlexSupporting evidence79 citations

Computational Discovery of New 2D Materials Using Deep Learning Generative Models

Yuqi Song; Edirisuriya M. Dilanga Siriwardane; Yong Zhao; Jianjun Hu

May 14, 2021ACS Applied Materials & Interfaces

2020CrossrefSupporting evidence11 citations

Predictive Modeling of Critical Temperatures in Superconducting Materials

Natalia Sizochenko; Markus Hofmann

Dec 22, 2020Molecules

2020OpenAlexSupporting evidence697 citations

Artificial intelligence and machine learning in design of mechanical materials

Kai Guo; Zhenze Yang; Chi‐Hua Yu; Markus J. Buehler

Dec 17, 2020Materials Horizons