Frontiers in Materials | Computational Materials Science

Original Research

Published on 08 May 2026

Digital modeling approach for optimizing steel materials production in sports equipment manufacturing using artificial intelligence and high-throughput computational techniques

in Computational Materials Science

Wenzhao Wu
Yue Zhang

Frontiers in Materials

doi 10.3389/fmats.2026.1765832

256 views

Original Research

Accepted on 04 May 2026

First-principles investigation of NaX(Mn,Ti)O2 cathode material for rechargeable sodium-ion batteries

in Computational Materials Science

Tshifhiwa Steven Ranwaha
Ratshilumela steve Dima
Nditshedzeni eric Maluta
Rapela Regina Maphanga

Frontiers in Materials

100 views

Original Research

Published on 30 Apr 2026

Microstructure-property-corrosion degradation during 475 °C aging of additively manufactured UNS S32205 duplex stainless steel: experimental and statistical assessment

in Computational Materials Science

Santosh Kumar
V. Shamanth
Seelam Srikanth
Rayappa Shrinivas Mahale
Manjunath G. Avalappa
S. P. Jagadish
Chennabasappa Hampali

Frontiers in Materials

doi 10.3389/fmats.2026.1803869

503 views

Correction

Published on 28 Apr 2026

Correction: Explainable AutoML models for predicting the strength of high-performance concrete using Optuna, SHAP and ensemble learning

in Computational Materials Science

Muhammad Salman Khan
Tianbo Peng
Muhammad Adeel Khan
Asad Khan
Mahmood Ahmad
Kamran Aziz
Mohanad Muayad Sabri Sabri
N. S. AbdEL-Gawaad

Frontiers in Materials

doi 10.3389/fmats.2026.1764787

378 views

Editorial

Published on 21 Apr 2026

Editorial: Digital technology for materials science and processes modelling

in Computational Materials Science

Nanfu Zong
Tao Jing
Kun Dou

Frontiers in Materials

doi 10.3389/fmats.2026.1846730

494 views

Original Research

Accepted on 13 Apr 2026

Foundation Models for Multimodal Image Data Fusion in Materials Science

in Computational Materials Science

Ali Riza Durmaz
James D. Lamb
McLean P. Echlin
Tresa M. Pollock

Frontiers in Materials

238 views

Original Research

Published on 28 Jan 2026

Intelligent pavement moduli back-calculation using an SEM–transformer framework

in Computational Materials Science

Guozhong Wang
Yanqing Zhao

Frontiers in Materials

doi 10.3389/fmats.2025.1732297

1,264 views

Original Research

Published on 20 Jan 2026

Deep learning-based image classification for microstructural analysis in computational materials science

in Computational Materials Science

Haiyan Liu
Penghua Zhu
Chenyu Tan

Frontiers in Materials

doi 10.3389/fmats.2025.1648653

2,311 views

Original Research

Published on 08 Jan 2026

Rapid non-contact detection of aggregate gradation based on stereo vision

in Computational Materials Science

Yanzhen Li
Bo Zang
Zhiyong Huang
Jiaming Tang

Frontiers in Materials

doi 10.3389/fmats.2025.1745325

1,056 views

Original Research

Published on 07 Jan 2026

Physics-informed neural network–transformer for dual-objective prediction and mix optimization of backfill materials

in Computational Materials Science

Huizhen Liang
Yueying Zhang
Chengmi Xiang
Shanshan Fei
Han Wei
Bei Han
Aijun Zhang

Frontiers in Materials

doi 10.3389/fmats.2025.1737888

1,346 views

Review

Published on 06 Jan 2026

Data-driven AI approaches for screening high-efficiency, stable, and lead-free perovskite photovoltaic materials: a review

in Computational Materials Science

Beibei Wang
Juan Wang
Liping Li
Dengwu Wang

Frontiers in Materials

doi 10.3389/fmats.2025.1669229

1,867 views

Mini Review

Published on 22 Oct 2025

Modeling and design of micro-structures: focusing on functionally graded materials and future prospects

in Computational Materials Science

Tohru Hirano

Frontiers in Materials

doi 10.3389/fmats.2025.1659727

3,544 views
1 citation

Original Research

Published on 25 Sep 2025

Development of defect localization method for perforated carbon-fiber-reinforced plastic specimens using finite element method and graph neural network

in Computational Materials Science

Keisuke Nishioka
Yuta Kojima
Toshiya Saito
Kosuke Kawakami
Masahito Washiya
Mayu Muramatsu

Frontiers in Materials

doi 10.3389/fmats.2025.1652484

3,073 views
1 citation

Original Research

Published on 23 Sep 2025

Research on predicting flow stress of 7075 aluminum alloy using machine learning models

in Computational Materials Science

Qiang Wen
Zishen Cao
Sida Yang
Haoyu Tan
Fengzhan Zhou
Jiantao Yin
Tianhao Wang
Zhuo Qian
Guoyou Gan

Frontiers in Materials

doi 10.3389/fmats.2025.1671753

3,077 views
3 citations

Original Research

Published on 29 Aug 2025

Detection of wood grain defects based on edge prior aggregation

in Computational Materials Science

Weijian Sun
Xu Cheng

Frontiers in Materials

doi 10.3389/fmats.2025.1635222

2,663 views

Review

Published on 08 Aug 2025

Computational methods and artificial intelligence-based modeling of magnesium alloys: a systematic review of machine learning, deep learning, and data-driven design and optimization approaches

in Computational Materials Science

Hanxuan Wang
Raman Kumar
Ashutosh Pattanaik
Rajender Kumar
Ali Saeed Owayez Khawaf Aljaberi
Mayada Ahmed Abass

Frontiers in Materials

doi 10.3389/fmats.2025.1645227

8,476 views
11 citations

Original Research

Published on 30 Jul 2025

TiAlNb alloy interatomic potentials: comparing passive and active machine learning techniques with MTP and DeePMD

in Computational Materials Science

Anju Chandran
Archa Santhosh
Claudio Pistidda
Paul Jerabek
Roland C. Aydin
Christian J. Cyron

Frontiers in Materials

doi 10.3389/fmats.2025.1591955

3,209 views

Original Research

Published on 18 Jul 2025

Enhancing phase change thermal energy storage material properties prediction with digital technologies

in Computational Materials Science

Minghao Yu
Jing Liu
Cheng Chen
Mingyue Li

Frontiers in Materials

doi 10.3389/fmats.2025.1616233

2,972 views

Original Research

Published on 02 Jul 2025

Rapid mold optimization based on ultraviolet curing 3D printing technology

in Computational Materials Science

Hanyu Rao
Xinyu Bai
Wen Yan
Jie Liu

Frontiers in Materials

doi 10.3389/fmats.2025.1605771

2,556 views
1 citation

Original Research

Published on 06 Jun 2025

Digitized material design and performance prediction driven by high-throughput computing

in Computational Materials Science

Hanhui Li
Jiao Yang
Jingxu Yao
Chuanxin Sheng

Frontiers in Materials

doi 10.3389/fmats.2025.1599439

4,561 views
2 citations

Original Research

Published on 14 Apr 2025

Classification, identification, and quantitative study of defects in aluminum plates using pulsed alternating current field measurement combined with principal component analysis

in Computational Materials Science

Qingxiao Kong
Shuwei Pan
Lilong Lin
Xinfeng Li

Frontiers in Materials

doi 10.3389/fmats.2025.1569055

2,077 views

Original Research

Published on 08 Apr 2025

Deep learning-driven medical image analysis for computational material science applications

in Computational Materials Science

Li Lu
Mingpei Liang

Frontiers in Materials

doi 10.3389/fmats.2025.1583615

6,881 views
5 citations

Original Research

Published on 21 Jan 2025

Explainable AutoML models for predicting the strength of high-performance concrete using Optuna, SHAP and ensemble learning

in Computational Materials Science

Muhammad Salman Khan
Tianbo Peng
Muhammad Adeel Khan
Asad Khan
Mahmood Ahmad
Kamran Aziz
Mohanad Muayad Sabri Sabri
N. S. Abd EL-Gawaad

Frontiers in Materials

doi 10.3389/fmats.2025.1542655

4,355 views
19 citations

Original Research

Published on 11 Dec 2024

Influence of microstructure on the wettability of tobacco leaves: a theoretical model and quantitative analysis

in Computational Materials Science

Jinxin Tie
Binfeng Shen
Yuehui Qiao
Wei Zhao
Ronghua Xu
Miao Wang
Kecheng Li
Jie Qian

Frontiers in Materials

doi 10.3389/fmats.2024.1485713

2,621 views
1 citation

205 articles

articles

Digital modeling approach for optimizing steel materials production in sports equipment manufacturing using artificial intelligence and high-throughput computational techniques

First-principles investigation of NaX(Mn,Ti)O2 cathode material for rechargeable sodium-ion batteries

Microstructure-property-corrosion degradation during 475 °C aging of additively manufactured UNS S32205 duplex stainless steel: experimental and statistical assessment

Correction: Explainable AutoML models for predicting the strength of high-performance concrete using Optuna, SHAP and ensemble learning

Editorial: Digital technology for materials science and processes modelling

Foundation Models for Multimodal Image Data Fusion in Materials Science

Intelligent pavement moduli back-calculation using an SEM–transformer framework

Deep learning-based image classification for microstructural analysis in computational materials science

Rapid non-contact detection of aggregate gradation based on stereo vision

Physics-informed neural network–transformer for dual-objective prediction and mix optimization of backfill materials

Data-driven AI approaches for screening high-efficiency, stable, and lead-free perovskite photovoltaic materials: a review

Modeling and design of micro-structures: focusing on functionally graded materials and future prospects

Development of defect localization method for perforated carbon-fiber-reinforced plastic specimens using finite element method and graph neural network

Research on predicting flow stress of 7075 aluminum alloy using machine learning models

Detection of wood grain defects based on edge prior aggregation

Computational methods and artificial intelligence-based modeling of magnesium alloys: a systematic review of machine learning, deep learning, and data-driven design and optimization approaches

TiAlNb alloy interatomic potentials: comparing passive and active machine learning techniques with MTP and DeePMD

Enhancing phase change thermal energy storage material properties prediction with digital technologies

Rapid mold optimization based on ultraviolet curing 3D printing technology

Digitized material design and performance prediction driven by high-throughput computing

Classification, identification, and quantitative study of defects in aluminum plates using pulsed alternating current field measurement combined with principal component analysis

Deep learning-driven medical image analysis for computational material science applications

Explainable AutoML models for predicting the strength of high-performance concrete using Optuna, SHAP and ensemble learning

Influence of microstructure on the wettability of tobacco leaves: a theoretical model and quantitative analysis