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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。共同主编为陈立东研究员，中国科学院上海硅酸盐研究所研究员高性能陶瓷与超微结构国家重点实验室主任。
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，... 【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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Efficient first-principles electronic transport approach to complex band structure materials: the case of n-type Mg3Sb2
Zhen Li, Patrizio Graziosi & Neophytos Neophytou
npj Computational Materials 10: 9 (2024); Published online: 06 Jan 2024
Editorial Summary
First-principles electronic transport approach: Efficiency, robustness, and flexibility
Transport parameters are crucial for novel material deployment in a variety of technological applications, including solar cells, solid-sta... |
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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 Materials10: 1 (2024)
Editorial Summary
Structure-aware graph neural network: Enhanced prediction of material properties
Accurate materials property prediction using crystal structure occupies a pri... |
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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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