Volume 6, Issue 3 (September, 2026) – 13 articles | Journal of Materials Informatics

Review

LLM-driven materials knowledge extraction: multimodal parsing, ontology, and agentic systems

Shuai Yang

, ... Ying Lu

J. Mater. Inf. 2026, 6, 39. DOI: 10.20517/jmi.2026.38

Review | Available online: 30 Jul 2026

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Research Article

Deciphering the strength-ductility trade-off in (CuNiMn)-X alloys via interpretable machine learning

Fei Tan, ... Zhou Li

J. Mater. Inf. 2026, 6, 36. DOI: 10.20517/jmi.2026.14

Research Article | Available online: 24 Jun 2026

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Physics-informed machine learning framework integrating solid solution strengthening theory for accelerated hardness prediction in high-entropy alloys

Ao Gao, ... Xingjun Liu

J. Mater. Inf. 2026, 6, 44. DOI: 10.20517/jmi.2026.16

Research Article | Available online: 7 Sep 2026

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PhyMLP: an automated strategy for machine-learning potential construction via data fusion and adaptive point-sampling

Yiqun Guo, ... Wangyu Hu

J. Mater. Inf. 2026, 6, 37. DOI: 10.20517/jmi.2026.18

Research Article | Available online: 27 Jul 2026

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Machine-learning-enabled composition–process co-design of heat-resistant cast aluminum alloys with superior elevated-temperature strength

Changmei Hao, ... Han Xiao

J. Mater. Inf. 2026, 6, 38. DOI: 10.20517/jmi.2026.20

Research Article | Available online: 28 Jul 2026

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A federated learning–driven data fusion strategy for the hardenability prediction of gear steel

Chunlei Shang, ... Xinping Mao

J. Mater. Inf. 2026, 6, 41. DOI: 10.20517/jmi.2026.26

Research Article | Available online: 26 Aug 2026

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Data-driven design of high-abundance rare earth permanent magnets for low-carbon and resource-efficient production

Yuxuan Wu, ... Lu Wang

J. Mater. Inf. 2026, 6, 42. DOI: 10.20517/jmi.2026.31

Research Article | Available online: 26 Aug 2026

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Prediction of electron localization functions from superposed atomic densities for accelerated superhydride discovery

Austin Ellis

, ... Maosheng Miao

J. Mater. Inf. 2026, 6, 45. DOI: 10.20517/jmi.2026.44

Research Article | Available online: 15 Sep 2026

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Multi-activity derivative automated labeling and margin-sampling active learning for efficient determination of phase boundaries

Dingding Chen, ... Aimin Zhang

J. Mater. Inf. 2026, 6, 46. DOI: 10.20517/jmi.2026.21

Research Article | Available online: 28 Sep 2026

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Reaction-anchored generative informatics for million-scale CO₂ catalyst screening via multi-adsorbate constraints

Dongjin Tang, ... Rui Qi

J. Mater. Inf. 2026, 6, 47. DOI: 10.20517/jmi.2026.63

Research Article | Available online: 28 Sep 2026

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Integrating physical metallurgy principles and machine learning for predicting continuous cooling phase transformations in steel

Juan Yang, ... Ziyong Hou

J. Mater. Inf. 2026, 6, 48. DOI: 10.20517/jmi.2026.54

Research Article | Available online: 29 Sep 2026

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Commentary

Commentary on ten selected 2025 papers in AI for Materials Science

Yi Liu

J. Mater. Inf. 2026, 6, 43. DOI: 10.20517/jmi.2026.36

Commentary | Available online: 26 Aug 2026

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Correction

Correction: Machine learning and shap-based prediction of multifactor thermal-oxidative aging behavior in glass fiber reinforced polyamide6

Hui Zhan, ... Tongfei Shi

J. Mater. Inf. 2026, 6, 40. DOI: 10.20517/jmi.2026.66

Correction | Available online: 11 Aug 2026

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Volume

Volume 6, Issue 3 (2026) – 13 articles

Review

LLM-driven materials knowledge extraction: multimodal parsing, ontology, and agentic systems

Research Article

Deciphering the strength-ductility trade-off in (CuNiMn)-X alloys via interpretable machine learning

Physics-informed machine learning framework integrating solid solution strengthening theory for accelerated hardness prediction in high-entropy alloys

PhyMLP: an automated strategy for machine-learning potential construction via data fusion and adaptive point-sampling

Machine-learning-enabled composition–process co-design of heat-resistant cast aluminum alloys with superior elevated-temperature strength

A federated learning–driven data fusion strategy for the hardenability prediction of gear steel

Data-driven design of high-abundance rare earth permanent magnets for low-carbon and resource-efficient production

Prediction of electron localization functions from superposed atomic densities for accelerated superhydride discovery

Multi-activity derivative automated labeling and margin-sampling active learning for efficient determination of phase boundaries

Reaction-anchored generative informatics for million-scale CO₂ catalyst screening via multi-adsorbate constraints

Integrating physical metallurgy principles and machine learning for predicting continuous cooling phase transformations in steel

Commentary

Commentary on ten selected 2025 papers in AI for Materials Science

Correction

Correction: Machine learning and shap-based prediction of multifactor thermal-oxidative aging behavior in glass fiber reinforced polyamide6

Actions for 0 selected articles

Committee on Publication Ethics

Portico

Committee on Publication Ethics

Portico

Volume

Volume 6, Issue 3 (2026) – 13 articles

Review

LLM-driven materials knowledge extraction: multimodal parsing, ontology, and agentic systems

Research Article

Deciphering the strength-ductility trade-off in (CuNiMn)-X alloys via interpretable machine learning

Physics-informed machine learning framework integrating solid solution strengthening theory for accelerated hardness prediction in high-entropy alloys

PhyMLP: an automated strategy for machine-learning potential construction via data fusion and adaptive point-sampling

Machine-learning-enabled composition–process co-design of heat-resistant cast aluminum alloys with superior elevated-temperature strength

A federated learning–driven data fusion strategy for the hardenability prediction of gear steel

Data-driven design of high-abundance rare earth permanent magnets for low-carbon and resource-efficient production

Prediction of electron localization functions from superposed atomic densities for accelerated superhydride discovery

Multi-activity derivative automated labeling and margin-sampling active learning for efficient determination of phase boundaries

Reaction-anchored generative informatics for million-scale CO2 catalyst screening via multi-adsorbate constraints

Integrating physical metallurgy principles and machine learning for predicting continuous cooling phase transformations in steel

Commentary

Commentary on ten selected 2025 papers in AI for Materials Science

Correction

Correction: Machine learning and shap-based prediction of multifactor thermal-oxidative aging behavior in glass fiber reinforced polyamide6

Actions for 0 selected articles

Committee on Publication Ethics

Portico

Committee on Publication Ethics

Portico

Reaction-anchored generative informatics for million-scale CO₂ catalyst screening via multi-adsorbate constraints