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AI for Materials Discovery

Artificial IntelligenceUpdated Jul 30, 2026Version v1

Knowledge Timeline Gaps (1)Evidence (40)Community (0)

Evidence

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

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All40 Core17 Supporting23 Background0

Showing 1-12 of total 40 evidence records.

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2026CrossrefSupporting evidence0 citations

Improving predictive modeling in materials science based on data augmentation approach

Mohamed Hamidi; Mohamed Loutou

Jul 10, 2026Journal of Materials Science: Materials in Engineering

2026CrossrefSupporting evidence0 citations

Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models

Paul Hagemann; Simon Müller; Janine George; Philipp Benner

Jul 6, 2026Journal of Physics: Materials

2026CrossrefDirectly related0 citations

Machine Learning in Materials Science: Data-Driven Discovery and Functional Applications

Mihail Kolev

Jul 6, 2026Encyclopedia

2026CrossrefDirectly related0 citations

Matter - AI A Multimodal AI Framework for Accelerated Materials Discovery in Physical Sciences

Prudvi Saisaran Ponduru

Jun 14, 2026International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences

2026CrossrefSupporting evidence0 citations

AI/ML Enabled High‐Throughput Design and Synthesis for Energetic Molecules

Wen Qian

May 19, 2026Materials Genome Engineering Advances

2026CrossrefDirectly related1 citations

Generative Design for Alloys: Harnessing Generative Models for Faster Discovery

Cheng Li; Yuehui Xian; Yumei Zhou; Xiangdong Ding; Jun Sun; Dezhen Xue

May 1, 2026Advanced Materials

2026CrossrefDirectly related0 citations

Multi-fidelity learning in materials informatics: methodologies, applications, and outlook

Bo Wang; Yangyang Xu; Yumei Zhou; Dezhen Xue

Mar 30, 2026Journal of Materials Informatics

2026CrossrefSupporting evidence9 citations

AI-powered open-source infrastructure for accelerating materials discovery and advanced manufacturing

Mariangeles Salas; Anand Singh; Carlos Pignataro; Lokendra Pal

Feb 17, 2026Communications Materials

2026PubMedDirectly related

Efficient and valid large molecule generation via self-supervised generative models.

Kwak D; Chowdhury MR; Yoon BJ; Qian X

Jan 1, 2026npj drug discovery

2026PubMedDirectly related

Statistical AI Enables Precise Screening of Multielement Catalysts.

Li C; Li M; Ran N; Lv Y; Zhou W; Liu J

Jan 1, 2026Journal of the American Chemical Society

2026PubMedSupporting evidence

Raw Data as the Verification Layer: Why AI-Driven Materials Discovery Needs Experimental Infrastructure.

Reeves-McLaren N

Jan 1, 2026ACS omega

2026CrossrefDirectly related25 citations

Machine Learning for Accelerating Energy Materials Discovery: Bridging Quantum Accuracy with Computational Efficiency

Kwang S. Kim

Jan 1, 2026Advanced Energy Materials

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AI for Materials Discovery — Research Evidence and Topic Memory | Kritoma