Frontiers in Materials | Computational Materials Science

Original Research

Published on 20 Aug 2026

Defect classification using the pulsed alternating current field measurement technique based on the Smoothed Pseudo Wigner-Ville distribution and principal component analysis

in Computational Materials Science

Qingxiao Kong
Lilong Lin
Xinfeng Li
Shuwei Pan
Yihuai Huang

Frontiers in Materials

doi 10.3389/fmats.2026.1894831

277 views

Original Research

Accepted on 14 Aug 2026

Phase-Stability-Guided Explainable Machine Learning for Mechanical-Property Prediction and Experimentally Supported Candidate Screening of High-Entropy Alloys

in Computational Materials Science

Derong Yuan
Delin Yuan
Xiaoyu Xu

Frontiers in Materials

198 views

Original Research

Published on 13 Aug 2026

Mesh refinement ergodicity in heterogeneous concrete fracture: a combined virtual-interface element approach

in Computational Materials Science

Gabriel Chacón
Felipe L. Rivarola
Daniel van Huyssteen
Paul Steinmann
Guillermo Etse

Frontiers in Materials

doi 10.3389/fmats.2026.1906980

448 views

Original Research

Accepted on 12 Aug 2026

Bayesian Optimization Driven Co-Regulation of Composition Design and Sintering Process Parameters for Piezoelectric Ceramics

in Computational Materials Science

Tiantian Cheng
Junfeng Luo

Frontiers in Materials

238 views

Review

Accepted on 11 Aug 2026

Machine Learning for Predicting the Glass Transition and Melting Temperatures of Polymers: Molecular Representations, Model Architectures, and Interpretability

in Computational Materials Science

Haiqian Guo
Yitian Zhang
Wei Zan
Jiejie Liu
Shuai Guo
Ayinishahan Dawuti
Xinwu Ba

Frontiers in Materials

270 views

Review

Published on 22 Jul 2026

Hot rolling in the age of artificial intelligence: towards enhanced efficiency, quality and sustainability in steel industry

in Computational Materials Science

Nanfu Zong

Frontiers in Materials

doi 10.3389/fmats.2026.1910968

790 views

Original Research

Accepted on 07 Jul 2026

A computational strategy for improving efficiency in finite element analyses with non-linear zero-thickness interface elements

in Computational Materials Science

Giovanna Xotta
Ignacio Carol
Daniel Garolera
Caterina Biscaro

Frontiers in Materials

363 views

Original Research

Published on 25 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
Nnditshedzeni Eric Maluta
Rapela Regina Maphanga

Frontiers in Materials

doi 10.3389/fmats.2026.1827271

1,273 views
1 citation

Original Research

Published on 21 May 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

doi 10.3389/fmats.2026.1815017

1,922 views
2 citations

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

1,593 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

1,628 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

1,243 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

1,149 views
1 citation

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

2,258 views
1 citation

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

4,127 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

2,107 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

2,597 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

4,414 views
1 citation

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

5,202 views
3 citations

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

4,737 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

4,614 views
4 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

3,819 views
1 citation

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

15,337 views
29 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

5,144 views
2 citations

212 articles

articles

Defect classification using the pulsed alternating current field measurement technique based on the Smoothed Pseudo Wigner-Ville distribution and principal component analysis

Phase-Stability-Guided Explainable Machine Learning for Mechanical-Property Prediction and Experimentally Supported Candidate Screening of High-Entropy Alloys

Mesh refinement ergodicity in heterogeneous concrete fracture: a combined virtual-interface element approach

Bayesian Optimization Driven Co-Regulation of Composition Design and Sintering Process Parameters for Piezoelectric Ceramics

Machine Learning for Predicting the Glass Transition and Melting Temperatures of Polymers: Molecular Representations, Model Architectures, and Interpretability

Hot rolling in the age of artificial intelligence: towards enhanced efficiency, quality and sustainability in steel industry

A computational strategy for improving efficiency in finite element analyses with non-linear zero-thickness interface elements

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

Foundation models for multimodal image data fusion in materials science

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

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

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