Q
Qiang Zhu
Researcher at University of Nevada, Las Vegas
Publications - 129
Citations - 7046
Qiang Zhu is an academic researcher from University of Nevada, Las Vegas. The author has contributed to research in topics: Crystal structure prediction & Ab initio. The author has an hindex of 35, co-authored 119 publications receiving 5404 citations. Previous affiliations of Qiang Zhu include State University of New York System & Stony Brook University.
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New developments in evolutionary structure prediction algorithm USPEX
TL;DR: It is shown how to generate randomly symmetric structures, and how to introduce 'smart' variation operators, learning about preferable local environments, that substantially improve the efficiency of the evolutionary algorithm USPEX and allow reliable prediction of structures with up to ∼200 atoms in the unit cell.
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Semimetallic Two-Dimensional Boron Allotrope with Massless Dirac Fermions
Xiang-Feng Zhou,Xiang-Feng Zhou,Xiao Dong,Xiao Dong,Artem R. Oganov,Artem R. Oganov,Artem R. Oganov,Qiang Zhu,Yongjun Tian,Hui-Tian Wang,Hui-Tian Wang +10 more
TL;DR: In this paper, a novel 2D boron structure with nonzero thickness was proposed based on an ab initio evolutionary structure search, which is considerably lower in energy than the recently proposed $\ensuremath{\alpha}$-sheet structure and its analogues.
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Phagraphene: A Low-Energy Graphene Allotrope Composed of 5-6-7 Carbon Rings with Distorted Dirac Cones.
Zhenhai Wang,Xiang-Feng Zhou,Xiaoming Zhang,Qiang Zhu,Huafeng Dong,Mingwen Zhao,Artem R. Oganov +6 more
TL;DR: The electronic structure of phagraphene has distorted Dirac cones, which are lower in energy than most of the predicted 2D carbon allotropes due to its sp(2)-binding features and density of atomic packing comparable to graphene.
Journal ArticleDOI
Report on the sixth blind test of organic crystal-structure prediction methods
Anthony M. Reilly,Richard I. Cooper,Claire S. Adjiman,Saswata Bhattacharya,A. Daniel Boese,Jan Gerit Brandenburg,Peter J. Bygrave,Rita Bylsma,J.E. Campbell,Roberto Car,David H. Case,Renu Chadha,Jason C. Cole,Katherine Cosburn,Katherine Cosburn,Herma M. Cuppen,Farren Curtis,Farren Curtis,Graeme M. Day,Robert A. DiStasio,Robert A. DiStasio,Alexander Dzyabchenko,Bouke P. van Eijck,Dennis M. Elking,Joost A. van den Ende,Julio C. Facelli,Marta B. Ferraro,Laszlo Fusti-Molnar,Christina-Anna Gatsiou,Thomas S. Gee,René de Gelder,Luca M. Ghiringhelli,Hitoshi Goto,Stefan Grimme,Rui Guo,D. W. M. Hofmann,Johannes Hoja,Rebecca K. Hylton,Luca Iuzzolino,Wojciech Jankiewicz,Daniël T. de Jong,John Kendrick,Niek J. J. de Klerk,Hsin-Yu Ko,L. N. Kuleshova,Xiayue Li,Xiayue Li,Sanjaya Lohani,Frank J. J. Leusen,Albert M. Lund,Albert M. Lund,Jian Lv,Yanming Ma,Noa Marom,Noa Marom,Artëm E. Masunov,Patrick McCabe,David P. McMahon,Hugo Meekes,Michael P. Metz,Alston J. Misquitta,Sharmarke Mohamed,Bartomeu Monserrat,Richard J. Needs,Marcus A. Neumann,Jonas Nyman,Shigeaki Obata,Harald Oberhofer,Artem R. Oganov,Anita M. Orendt,Gabriel Ignacio Pagola,Constantinos C. Pantelides,Chris J. Pickard,Chris J. Pickard,Rafał Podeszwa,Louise S. Price,Sarah L. Price,Angeles Pulido,Murray G. Read,Karsten Reuter,Elia Schneider,Christoph Schober,Gregory P. Shields,Pawanpreet Singh,Isaac J. Sugden,Krzysztof Szalewicz,Christopher R. Taylor,Alexandre Tkatchenko,Alexandre Tkatchenko,Mark E. Tuckerman,Mark E. Tuckerman,Mark E. Tuckerman,Francesca Vacarro,Francesca Vacarro,Manolis Vasileiadis,Álvaro Vázquez-Mayagoitia,Leslie Vogt,Yanchao Wang,Rona E. Watson,Gilles A. de Wijs,Jack Yang,Qiang Zhu,Colin R. Groom +102 more
TL;DR: The results of the sixth blind test of organic crystal structure prediction methods are presented and discussed, highlighting progress for salts, hydrates and bulky flexible molecules, as well as on-going challenges.
Journal ArticleDOI
Structure prediction drives materials discovery
Artem R. Oganov,Artem R. Oganov,Artem R. Oganov,Chris J. Pickard,Chris J. Pickard,Qiang Zhu,Richard J. Needs +6 more
TL;DR: This Review discusses structure prediction methods, examining their potential for the study of different materials systems, and presents examples of computationally driven discoveries of new materials — including superhard materials, superconductors and organic materials — that will enable new technologies.