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| 期刊介绍 |
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| 《npj 计算材料学》是在线出版、完全开放获取的国际学术期刊。发表结合计算模拟与设计的材料学一流的研究成果。本刊由中国科学院上海硅酸盐研究所与英国自然出版集团（Nature Publishing Group，NPG）以伙伴关系合作出版。 主编为陈龙庆博士，美国宾州州立大学材料科学与工程系、工程科学与力学系、数学系的杰出教授。共同主编为陈立东博士，中国科学院上海硅酸盐研究所研究员，中国科学院院士，亚太材料科学院院士。 办刊目的与报道范围《npj 计算材料学》是在线出版、完全开放获取的国际学术期刊，发表各... 【查看详细】 |
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Peculiar band geometry induced giant shift current in ferroelectric SnTe monolayer
Gan Jin & Lixin He
npj Computational Materials 10: 23 (2024); Published online: 29 January 2024
Editorial Summary
Giant Photocurrent Effect in Two-Dimensional Ferroelectric SnTe: driven by the Monopole Quantum Potential Fields Arising from Peculiar Band Structures.
The Bulk Photovoltaic Effect (BPVE) is a phenomenon in which light-induced electrical current or voltage is generated in non-centrosymmetric... |
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Full-landscape selection rules of electrons and phonons and temperature-induced effects in 2D silicon and germanium allotropes
Le Shu, Yujie Xia, Ben Li, Lei Peng, Hezhu Shao, Zengxu Wang, Yan Ce, Heyuan Zhu & Hao Zhang
npj Computational Materials 10: 2 (2024); Published online: 02 January 2024
Editorial Summary
Electrons and phonons scattering: Importance of selection rules
The search for materials with a high thermoelectric figure of merit (zT) has attracted lots of attention for centur... |
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Structure-aware graph neural network based deep transfer learning framework for enhanced predictive analytics on diverse materials datasets
Vishu Gupta, Kamal Choudhary, Brian DeCost, Francesca Tavazza, Carelyn Campbell, Wei-keng Liao, Alok Choudhary & Ankit Agrawal
npj Computational Materials 10: 1 (2024)
Editorial Summary
Structure-aware graph neural network: Enhanced prediction of material properties
Accurate materials property prediction using crystal structure occupies a p... |
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Obtaining auxetic and isotropic metamaterials in counterintuitive design spaces: an automated optimization approach and experimental characterization
Timon Meier, Runxuan Li, Stefanos Mavrikos, Brian Blankenship, Zacharias Vangelatos, M. Erden Yildizdag & Costas P. Grigoropoulos
npj Computational Materials 10: 3 (2023)
Editorial Summary
Theoretical Design of Metamaterials with Unique Mechanical Properties
The design of mechanical materials with tailored properties has been subject of signif... |
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Atomistic fracture in bcc iron revealed by active learning of Gaussian approximation potential
Lei Zhang, Gábor Csányi, Erik van der Giessen & Francesco Maresca
npj Computational Materials 9: 217 (2023); Published online: 08 Dec 2023
Editorial Summary
Crack-tip deformation mechanism in bcc iron: dislocation emission VS. cleavage? Active learning interatomic potential!
The prediction of atomistic fracture mechanisms in body-centred cubic (bcc) iron is essential for understanding its... |
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