Predicting superhard materials via a machine learning informed evolutionary structure search

[1]  Cormac Toher,et al.  High-entropy high-hardness metal carbides discovered by entropy descriptors , 2018, Nature Communications.

[2]  Feng Lin,et al.  Machine Learning Directed Search for Ultraincompressible, Superhard Materials. , 2018, Journal of the American Chemical Society.

[3]  Cormac Toher,et al.  AFLOW-SYM: platform for the complete, automatic and self-consistent symmetry analysis of crystals. , 2018, Acta crystallographica. Section A, Foundations and advances.

[4]  Cormac Toher,et al.  AFLOW-ML: A RESTful API for machine-learning predictions of materials properties , 2017, Computational Materials Science.

[5]  Y. Gupta,et al.  Transformation of shock-compressed graphite to hexagonal diamond in nanoseconds , 2017, Science Advances.

[6]  Corey Oses,et al.  Machine learning modeling of superconducting critical temperature , 2017, npj Computational Materials.

[7]  Robert M. Hanson,et al.  The AFLOW Library of Crystallographic Prototypes: Part 2 , 2018, Computational Materials Science.

[8]  T. Cui,et al.  Nanotwinned diamond synthesized from multicore carbon onion , 2017 .

[9]  H. Mao,et al.  Compressed glassy carbon: An ultrastrong and elastic interpenetrating graphene network , 2017, Science Advances.

[10]  Eva Zurek,et al.  RandSpg: An open-source program for generating atomistic crystal structures with specific spacegroups , 2017, Comput. Phys. Commun..

[11]  Volker L. Deringer,et al.  Extracting Crystal Chemistry from Amorphous Carbon Structures , 2017, Chemphyschem : a European journal of chemical physics and physical chemistry.

[12]  Marco Buongiorno Nardelli,et al.  AFLUX: The LUX materials search API for the AFLOW data repositories , 2016, 1612.05130.

[13]  D. Mckenzie,et al.  Nanocrystalline hexagonal diamond formed from glassy carbon , 2016, Scientific Reports.

[14]  Marco Buongiorno Nardelli,et al.  Combining the AFLOW GIBBS and elastic libraries to efficiently and robustly screen thermomechanical properties of solids , 2016, 1611.05714.

[15]  Cormac Toher,et al.  Universal fragment descriptors for predicting properties of inorganic crystals , 2016, Nature Communications.

[16]  Roald Hoffmann,et al.  Homo Citans and Carbon Allotropes: For an Ethics of Citation , 2016, Angewandte Chemie.

[17]  E. Zurek Discovering New Materials via A Priori Crystal Structure Prediction , 2016 .

[18]  G. Pilania,et al.  Machine learning bandgaps of double perovskites , 2016, Scientific Reports.

[19]  Marco Buongiorno Nardelli,et al.  The AFLOW standard for high-throughput materials science calculations , 2015, 1506.00303.

[20]  Cormac Toher,et al.  Charting the complete elastic properties of inorganic crystalline compounds , 2015, Scientific Data.

[21]  V. Saleev,et al.  From zeolite nets to sp(3) carbon allotropes: a topology-based multiscale theoretical study. , 2015, Physical chemistry chemical physics : PCCP.

[22]  Yanchao Wang,et al.  Superhard BC(3) in cubic diamond structure. , 2015, Physical review letters.

[23]  A. Oganov,et al.  Synthesis of Ultra-incompressible sp3-Hybridized Carbon Nitride with 1:1 Stoichiometry , 2014, 1412.3755.

[24]  P. Buseck,et al.  Lonsdaleite is faulted and twinned cubic diamond and does not exist as a discrete material , 2014, Nature Communications.

[25]  Marco Buongiorno Nardelli,et al.  High-throughput computational screening of thermal conductivity, Debye temperature, and Grüneisen parameter using a quasiharmonic Debye model , 2014, 1407.7789.

[26]  Yanming Ma,et al.  Nanotwinned diamond with unprecedented hardness and stability , 2014, Nature.

[27]  A. P. Shevchenko,et al.  Applied Topological Analysis of Crystal Structures with the Program Package ToposPro , 2014 .

[28]  Marco Buongiorno Nardelli,et al.  A RESTful API for exchanging materials data in the AFLOWLIB.org consortium , 2014, 1403.2642.

[29]  Atsuto Seko,et al.  Machine learning with systematic density-functional theory calculations: Application to melting temperatures of single- and binary-component solids , 2013, 1310.1546.

[30]  Muratahan Aykol,et al.  Materials Design and Discovery with High-Throughput Density Functional Theory: The Open Quantum Materials Database (OQMD) , 2013 .

[31]  Kristin A. Persson,et al.  Commentary: The Materials Project: A materials genome approach to accelerating materials innovation , 2013 .

[32]  Yanming Ma,et al.  First-principles structural design of superhard materials. , 2013, The Journal of chemical physics.

[33]  Svetlozar Nestorov,et al.  The Computational Materials Repository , 2012, Computing in Science & Engineering.

[34]  Yuejian Wang,et al.  Crystal structure of graphite under room-temperature compression and decompression , 2012, Scientific Reports.

[35]  Bo Xu,et al.  Microscopic theory of hardness and design of novel superhard crystals , 2012 .

[36]  Marco Buongiorno Nardelli,et al.  AFLOWLIB.ORG: A distributed materials properties repository from high-throughput ab initio calculations , 2012 .

[37]  S. Curtarolo,et al.  AFLOW: An automatic framework for high-throughput materials discovery , 2012, 1308.5715.

[38]  David C. Lonie,et al.  Identifying duplicate crystal structures: XtalComp, an open-source solution , 2012, Comput. Phys. Commun..

[39]  S. Leoni,et al.  Superhard s p3 carbon allotropes with odd and even ring topologies , 2011, 1206.5379.

[40]  David C. Lonie,et al.  XtalOpt version r9: An open-source evolutionary algorithm for crystal structure prediction , 2011, Comput. Phys. Commun..

[41]  Dianzhong Li,et al.  Modeling hardness of polycrystalline materials and bulk metallic glasses , 2011 .

[42]  Dianzhong Li,et al.  Hardness of T-carbon: Density functional theory calculations , 2011, 1108.2570.

[43]  Zhou Yu,et al.  Lonsdaleite – A material stronger and stiffer than diamond , 2011 .

[44]  A. Oganov,et al.  Evolutionary search for superhard materials: Methodology and applications to forms of carbon and TiO2 , 2011, 1105.1729.

[45]  G. Su,et al.  T-carbon: a novel carbon allotrope. , 2011, Physical review letters.

[46]  David C. Lonie,et al.  XtalOpt: An open-source evolutionary algorithm for crystal structure prediction , 2011, Comput. Phys. Commun..

[47]  F. Gao,et al.  Microscopic models of hardness , 2010 .

[48]  R. Needs,et al.  Hypothetical low-energy chiral framework structure of group 14 elements , 2010 .

[49]  Hui Wang,et al.  Superhard monoclinic polymorph of carbon. , 2009, Physical review letters.

[50]  Yanming Ma,et al.  Rhombohedral superhard structure of BC2N , 2009 .

[51]  Yi Zhang,et al.  Harder than diamond: superior indentation strength of wurtzite BN and lonsdaleite. , 2009, Physical review letters.

[52]  Fangfang Zhang,et al.  Electronegativity identification of novel superhard materials. , 2008, Physical review letters.

[53]  Jirí Vackár,et al.  Hardness of covalent and ionic crystals: first-principle calculations. , 2006, Physical review letters.

[54]  Peter J. Eng,et al.  Bonding Changes in Compressed Superhard Graphite , 2003, Science.

[55]  Siyuan Zhang,et al.  Hardness of covalent crystals. , 2003, Physical review letters.

[56]  Vadim V. Brazhkin,et al.  Harder than diamond: Dreams and reality , 2002 .

[57]  J. Friedman Greedy function approximation: A gradient boosting machine. , 2001 .

[58]  Y. Vohra,et al.  Electrical and mechanical properties of C70 fullerene and graphite under high pressures studied using designer diamond anvils. , 2000, Physical review letters.

[59]  David M. Teter,et al.  Computational Alchemy: The Search for New Superhard Materials , 1998 .

[60]  Burke,et al.  Generalized Gradient Approximation Made Simple. , 1996, Physical review letters.

[61]  Hafner,et al.  Ab initio molecular dynamics for liquid metals. , 1995, Physical review. B, Condensed matter.

[62]  Blöchl,et al.  Projector augmented-wave method. , 1994, Physical review. B, Condensed matter.

[63]  A. Liu,et al.  Prediction of New Low Compressibility Solids , 1989, Science.

[64]  I. D. Brown,et al.  The inorganic crystal structure data base , 1983, J. Chem. Inf. Comput. Sci..

[65]  Eva Zurek,et al.  XtalOpt version r11: An open-source evolutionary algorithm for crystal structure prediction , 2018, Comput. Phys. Commun..

[66]  Michael Sung,et al.  Carbon nitride and other speculative superhard materials , 1996 .