Large-scale Integration of Experimental and Computational Data for 2D Materials
Technical University of Denmark（丹麦技术大学）；University of South Florida（南佛罗里达大学）；Drexel University（德雷塞尔大学）；Aarhus University（奥胡斯大学）；École Polytechnique Fédérale de Lausanne (EPFL)（洛桑联邦理工学院）；National University of Singapore（新加坡国立大学）；Universität zu Köln（科隆大学）
Mohammad A. Akhound, Tara M. Boland, Mikkel O. Sauer, Matthias Batzill, Moses A. Bokinala, Stela Canulescu, Yury Gogotsi, Philip Hofmann, Andras Kis, Jiong Lu, … 展开作者
Mohammad A. Akhound, Tara M. Boland, Mikkel O. Sauer, Matthias Batzill, Moses A. Bokinala, Stela Canulescu, Yury Gogotsi, Philip Hofmann, Andras Kis, Jiong Lu, Thomas Michely, Søren Raza, Wencai Ren, Joshua A. Robinson, Zdenek Sofer, Jing H. Teng, Søren Ulstrup, Meng Zhao, Xiaoxu Zhao, Jens J. Mortensen, Thomas Olsen, Kristian S. Thygesen
The past decade has seen rapid growth in the number of experimentally realized two-dimensional (2D) materials with diverse chemical and physical properties. However, information on their crystal structure, synthesis routes, and measured or predicted properties, remains scattered across thousands of publications. Here we consolidate this fragmented knowledge by establishing X2DB - an open infrastructure that integrates experimental and computational data on 2D materials. Using extensive literature mining and direct community uploads, we identify 370 unique 2D materials that have been realized in monolayer or few-layer form, and link them to their digital counterparts in computational databases, enabling consistent ab initio characterization of their properties across monolayer, bilayer and bulk forms. We describe the structure and content of the database highlighting its support for community uploads, illustrate how it can be used to generate new scientific insight and introduce a hierarchical classification of the known set of 2D materials. Our work provides a foundation for the integration and cross-fertilization of experimental and theoretical knowledge, opening new avenues for data-driven, predictive synthesis of novel 2D materials.
Reliable Density Functional Theory Predictions of Bandgaps for Materials
Shanghai University（上海大学）；University of Technology Sydney（悉尼科技大学）；Materials Genome Institute, Shanghai University（上海大学材料基因组研究院）；ANU Supercomputer Facility（澳大利亚国立大学超级计算设施）；University of New South Wales (Canberra)（新南威尔士大学（堪培拉））
Atomically-precise synthesis and simultaneous integration of 2D transition metal dichalcogenides enabled by nano-confinement
Beijing National Center for Condensed Matter Physics and Institute of Physics, Chinese Academy of Sciences（中国科学院物理研究所）；School of Physical Sciences, University of Chinese Academy of Sciences（中国科学院大学物理科学学院）；Suzhou Laboratory（苏州实验室）；Institute of Technology for Carbon Neutrality, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences（中国科学院深圳先进技术研究院碳中和技术研究所）；Frontier Institute of Science and Technology, Xi’an Jiaotong University（西安交通大学前沿科学中心）；Department of Engineering Mechanics and Center for Nano and Micro Mechanics, Tsinghua University（清华大学工程力学系微纳力学与微系统教育部重点实验室）；Faculty of Materials Science and Energy Engineering, Shenzhen University of Advanced Technology（深圳先进材料能源学院）
Complex Workflow Management and Integration of Distributed Computing Resources by Science Gateway Portal for Molecular Dynamics Simulations in Materials Science
A comment on "The Computational 2D Materials Database: high-throughput modeling and discovery of atomically thin crystals"
最近，Sten Haastrup，Mikkel Strange，Mohnish Pandey，Thorsten Deilmann，Per S Schmidt，Nicki F Hinsche，Morten N Gjerding，Daniele Torelli，Peter M Larsen，Anders C Riis-Jensen，Jakob Gath，Karsten W Jacobsen，Jens Jrgen Mortensen，Thomas Olsen和Kristian S Thygesen [2D Mater. 5（2018）042002]介绍了计算二维材料数据库（C2 DB），该数据库组织了分布在30多种不同晶体结构中的约1500种二维材料的各种结构，热力学，弹性，电子，磁性和光学性质。不幸的是，这项工作在弹性和机械稳定性测试领域存在严重和根本性的缺陷，这使得它不可靠。
Reproducibility in Computational Materials Science: Lessons from 'A General-Purpose Machine Learning Framework for Predicting Properties of Inorganic Materials'
University of Toronto（多伦多大学）；Argonne National Laboratory（阿贡国家实验室）
Simplified Silicon Nitride Nanomembrane Circuits for van der Waals Integration
Leibniz Institute for Solid State and Materials Research Dresden (IFW Dresden)（德累斯顿莱布尼茨固体与材料研究所）；Dresden University of Technology（德累斯顿工业大学）；University of Naples Federico II（那不勒斯费德里科二世大学）；National Institute of Advanced Industrial Science and Technology (AIST)（产业技术综合研究所）
Efficient technique for computational design of thermoelectric materials
高效的热电材料是非常需要的，并且寻找它们的探索已经加强，因为它们可能是化石能源的有前途的替代品。在这里，我们提出了一个一般的第一性原理方法来预测，在多组分系统中，有效的热电化合物。该方法结合了稳健的进化算法，Pareto多目标优化，密度泛函理论和Boltzmann半经典计算的热电效率。为了测试我们的整体框架的性能和可靠性，我们使用众所周知的系统Bi $_2$ Te $_3$ -Sb $_2$ Te $_3$。
A Materials Map Integrating Experimental and Computational Data via Graph-Based Machine Learning for Enhanced Materials Discovery
Frontier research Institute for Interdisciplinary Sciences, Tohoku University（东北大学跨学科前沿研究所）；Advanced Institute for Materials Research (WPI-AIMR), Tohoku University（东北大学材料前沿研究所（WPI-AIMR））
Emerging electro-optic molecular crystals for optoelectronic integration
Core Electronics Technology Research Institute (CETRI), National Institute of Advanced Industrial Science and Technology (AIST)（中央电子技术研发所，产业技术综合研究所）；Photonics-Electronics Integration Research Center (PEIRC), National Institute of Advanced Industrial Science and Technology (AIST)（光子-电子集成研究中心，产业技术综合研究所）
Massive Discovery of Low-Dimensional Materials from Universal Computational Strategy
Nanoscience Center, Department of Physics, University of Jyväskylä（于韦斯屈莱大学）；Department of Physics, Chalmers University of Technology（查尔姆斯理工大学）；Microelectronics Research Unit, Faculty of Information Technology and Electrical Engineering, University of Oulu（奥卢大学）
Computational Design of Stable and Highly Ion-conductive Materials using Multi-objective Bayesian Optimization: Case Studies on Diffusion of Oxygen and Lithium
Impressive computational acceleration by using machine learning for 2-dimensional super-lubricant materials discovery
University of Technology Sydney（悉尼科技大学）；University of North Carolina（北卡罗来纳大学）；Commonwealth Scientific and Industrial Research Organization（澳大利亚联邦科学与工业研究组织）；Monash University（莫纳什大学）；La Trobe University（拉筹伯大学）；The University of Nottingham（诺丁汉大学）；The University of Queensland（昆士兰大学）；Flinders University（弗林德斯大学）
Light-matter interactions in layered materials and heterostructures: from moiré physics and magneto-optical effects to ultrafast dynamics and hybrid meta-photonics
Integration of 2D Materials in Radial van der Waals Heterostructure Metasurfaces
Ludwig-Maximilians-Universität München（慕尼黑大学）；Politecnico di Milano（米兰理工大学）；Universidade Federal de Pernambuco（伯南布哥联邦大学）；IFN-CNR, Istituto di Fotonica e Nanotecnologie（意大利国家研究委员会光子学与纳米技术研究所）
