Frontiers in Materials | Computational Materials Science section | New and Recent Articles https://www.frontiersin.org/journals/materials/sections/computational-materials-science RSS Feed for Computational Materials Science section in the Frontiers in Materials journal | New and Recent Articles en-us Frontiers Feed Generator,version:1 2026-05-02T19:34:41.834+00:00 60 https://www.frontiersin.org/articles/10.3389/fmats.2026.1803869 https://www.frontiersin.org/articles/10.3389/fmats.2026.1803869 <![CDATA[Microstructure-property-corrosion degradation during 475 °C aging of additively manufactured UNS S32205 duplex stainless steel: experimental and statistical assessment]]> 2026-04-30T00:00:00Z Original Research Santosh KumarV. ShamanthSeelam SrikanthRayappa Shrinivas MahaleManjunath G. AvalappaS. P. JagadishChennabasappa Hampali https://www.frontiersin.org/articles/10.3389/fmats.2026.1764787 https://www.frontiersin.org/articles/10.3389/fmats.2026.1764787 <![CDATA[Correction: Explainable AutoML models for predicting the strength of high-performance concrete using Optuna, SHAP and ensemble learning]]> 2026-04-28T00:00:00Z Correction Muhammad Salman KhanTianbo PengMuhammad Adeel KhanAsad KhanMahmood AhmadKamran AzizMohanad Muayad Sabri SabriN. S. AbdEL-Gawaad https://www.frontiersin.org/articles/10.3389/fmats.2026.1846730 https://www.frontiersin.org/articles/10.3389/fmats.2026.1846730 <![CDATA[Editorial: Digital technology for materials science and processes modelling]]> 2026-04-21T00:00:00Z Editorial Nanfu ZongTao JingKun Dou https://www.frontiersin.org/articles/10.3389/fmats.2025.1732297 https://www.frontiersin.org/articles/10.3389/fmats.2025.1732297 <![CDATA[Intelligent pavement moduli back-calculation using an SEM–transformer framework]]> 2026-01-28T00:00:00Z Original Research Guozhong WangYanqing Zhao 0.94 and MAPE < 8% across all noise cases, and shows superior performance for the base course under noisy conditions. The results demonstrate a reliable and efficient data-driven feasibility framework to support pavement structural evaluation and future digital-twin-based pavement management.]]> https://www.frontiersin.org/articles/10.3389/fmats.2025.1648653 https://www.frontiersin.org/articles/10.3389/fmats.2025.1648653 <![CDATA[Deep learning-based image classification for microstructural analysis in computational materials science]]> 2026-01-20T00:00:00Z Original Research Haiyan LiuPenghua ZhuChenyu Tan https://www.frontiersin.org/articles/10.3389/fmats.2025.1745325 https://www.frontiersin.org/articles/10.3389/fmats.2025.1745325 <![CDATA[Rapid non-contact detection of aggregate gradation based on stereo vision]]> 2026-01-08T00:00:00Z Original Research Yanzhen LiBo ZangZhiyong HuangJiaming Tang https://www.frontiersin.org/articles/10.3389/fmats.2025.1737888 https://www.frontiersin.org/articles/10.3389/fmats.2025.1737888 <![CDATA[Physics-informed neural network–transformer for dual-objective prediction and mix optimization of backfill materials]]> 2026-01-07T00:00:00Z Original Research Huizhen LiangYueying ZhangChengmi XiangShanshan FeiHan WeiBei HanAijun Zhang https://www.frontiersin.org/articles/10.3389/fmats.2025.1669229 https://www.frontiersin.org/articles/10.3389/fmats.2025.1669229 <![CDATA[Data-driven AI approaches for screening high-efficiency, stable, and lead-free perovskite photovoltaic materials: a review]]> 2026-01-06T00:00:00Z Review Beibei WangJuan WangLiping LiDengwu Wang https://www.frontiersin.org/articles/10.3389/fmats.2025.1659727 https://www.frontiersin.org/articles/10.3389/fmats.2025.1659727 <![CDATA[Modeling and design of micro-structures: focusing on functionally graded materials and future prospects]]> 2025-10-22T00:00:00Z Mini Review Tohru Hirano https://www.frontiersin.org/articles/10.3389/fmats.2025.1652484 https://www.frontiersin.org/articles/10.3389/fmats.2025.1652484 <![CDATA[Development of defect localization method for perforated carbon-fiber-reinforced plastic specimens using finite element method and graph neural network]]> 2025-09-25T00:00:00Z Original Research Keisuke NishiokaYuta KojimaToshiya SaitoKosuke KawakamiMasahito WashiyaMayu Muramatsu https://www.frontiersin.org/articles/10.3389/fmats.2025.1671753 https://www.frontiersin.org/articles/10.3389/fmats.2025.1671753 <![CDATA[Research on predicting flow stress of 7075 aluminum alloy using machine learning models]]> 2025-09-23T00:00:00Z Original Research Qiang WenZishen CaoSida YangHaoyu TanFengzhan ZhouJiantao YinTianhao WangZhuo QianGuoyou Gan https://www.frontiersin.org/articles/10.3389/fmats.2025.1635222 https://www.frontiersin.org/articles/10.3389/fmats.2025.1635222 <![CDATA[Detection of wood grain defects based on edge prior aggregation]]> 2025-08-29T00:00:00Z Original Research Weijian SunXu Cheng https://www.frontiersin.org/articles/10.3389/fmats.2025.1645227 https://www.frontiersin.org/articles/10.3389/fmats.2025.1645227 <![CDATA[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]]> 2025-08-08T00:00:00Z Review Hanxuan WangRaman KumarAshutosh PattanaikRajender KumarAli Saeed Owayez Khawaf AljaberiMayada Ahmed Abass https://www.frontiersin.org/articles/10.3389/fmats.2025.1591955 https://www.frontiersin.org/articles/10.3389/fmats.2025.1591955 <![CDATA[TiAlNb alloy interatomic potentials: comparing passive and active machine learning techniques with MTP and DeePMD]]> 2025-07-30T00:00:00Z Original Research Anju ChandranArcha SanthoshClaudio PistiddaPaul JerabekRoland C. AydinChristian J. Cyron https://www.frontiersin.org/articles/10.3389/fmats.2025.1616233 https://www.frontiersin.org/articles/10.3389/fmats.2025.1616233 <![CDATA[Enhancing phase change thermal energy storage material properties prediction with digital technologies]]> 2025-07-18T00:00:00Z Original Research Minghao YuJing LiuCheng ChenMingyue Li https://www.frontiersin.org/articles/10.3389/fmats.2025.1605771 https://www.frontiersin.org/articles/10.3389/fmats.2025.1605771 <![CDATA[Rapid mold optimization based on ultraviolet curing 3D printing technology]]> 2025-07-02T00:00:00Z Original Research Hanyu RaoXinyu BaiWen YanJie Liu https://www.frontiersin.org/articles/10.3389/fmats.2025.1599439 https://www.frontiersin.org/articles/10.3389/fmats.2025.1599439 <![CDATA[Digitized material design and performance prediction driven by high-throughput computing]]> 2025-06-06T00:00:00Z Original Research Hanhui LiJiao YangJingxu YaoChuanxin Sheng https://www.frontiersin.org/articles/10.3389/fmats.2025.1569055 https://www.frontiersin.org/articles/10.3389/fmats.2025.1569055 <![CDATA[Classification, identification, and quantitative study of defects in aluminum plates using pulsed alternating current field measurement combined with principal component analysis]]> 2025-04-14T00:00:00Z Original Research Qingxiao KongShuwei PanLilong LinXinfeng Li https://www.frontiersin.org/articles/10.3389/fmats.2025.1583615 https://www.frontiersin.org/articles/10.3389/fmats.2025.1583615 <![CDATA[Deep learning-driven medical image analysis for computational material science applications]]> 2025-04-08T00:00:00Z Original Research Li LuMingpei Liang https://www.frontiersin.org/articles/10.3389/fmats.2025.1542655 https://www.frontiersin.org/articles/10.3389/fmats.2025.1542655 <![CDATA[Explainable AutoML models for predicting the strength of high-performance concrete using Optuna, SHAP and ensemble learning]]> 2025-01-21T00:00:00Z Original Research Muhammad Salman KhanTianbo PengMuhammad Adeel KhanAsad KhanMahmood AhmadKamran AzizMohanad Muayad Sabri SabriN. S. Abd EL-Gawaad