Machine learning for crystal identification and discovery
dc.contributor.author | Spellings, Matthew | |
dc.contributor.author | Glotzer, Sharon C. | |
dc.date.accessioned | 2018-05-15T20:12:27Z | |
dc.date.available | 2019-08-01T19:53:24Z | en |
dc.date.issued | 2018-06 | |
dc.identifier.citation | Spellings, Matthew; Glotzer, Sharon C. (2018). "Machine learning for crystal identification and discovery." AIChE Journal 64(6): 2198-2206. | |
dc.identifier.issn | 0001-1541 | |
dc.identifier.issn | 1547-5905 | |
dc.identifier.uri | https://hdl.handle.net/2027.42/143597 | |
dc.publisher | Wiley Periodicals, Inc. | |
dc.subject.other | computational | |
dc.subject.other | self‐assembly | |
dc.subject.other | crystal | |
dc.subject.other | data science | |
dc.subject.other | machine learning | |
dc.title | Machine learning for crystal identification and discovery | |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | |
dc.subject.hlbsecondlevel | Chemical Engineering | |
dc.subject.hlbtoplevel | Engineering | |
dc.subject.hlbtoplevel | Science | |
dc.description.peerreviewed | Peer Reviewed | |
dc.description.bitstreamurl | https://deepblue.lib.umich.edu/bitstream/2027.42/143597/1/aic16157.pdf | |
dc.description.bitstreamurl | https://deepblue.lib.umich.edu/bitstream/2027.42/143597/2/aic16157_am.pdf | |
dc.identifier.doi | 10.1002/aic.16157 | |
dc.identifier.source | AIChE Journal | |
dc.identifier.citedreference | Seo D, Yoo CI, Chung IS, Park SM, Ryu S, Song H. Shape adjustment between multiply twinned and single‐crystalline polyhedral gold nanocrystals: decahedra, icosahedra, and truncated tetrahedra. J Phys Chem C. 2008; 112 ( 7 ): 2469 – 2475. | |
dc.identifier.citedreference | Wolde PRT, Ruiz‐Montero MJ, Frenkel D. Numerical calculation of the rate of crystal nucleation in a Lennard‐Jones system at moderate undercooling. J Chem Phys. 1996; 104 ( 24 ): 9932 – 9947. doi: 10.1063/1.471721. | |
dc.identifier.citedreference | Chau PL, Hardwick AJ. A new order parameter for tetrahedral configurations. Mol Phys. 1998; 93 ( 3 ): 511 – 518. | |
dc.identifier.citedreference | Haji‐Akbari A, Engel M, Keys AS, Zheng X, Petschek RG, Palffy‐Muhoray P, Glotzer SC. Disordered, quasicrystalline and crystalline phases of densely packed tetrahedra. Nature. 2009; 462 ( 7274 ): 773 – 777. | |
dc.identifier.citedreference | Phillips CL, Voth GA. Discovering crystals using shape matching and machine learning. Soft Matter. 2013; 9 ( 35 ): 8552 – 8568. | |
dc.identifier.citedreference | Reinhart WF, Long AW, Howard MP, Ferguson AL, Panagiotopoulos AZ. Machine learning for autonomous crystal structure identification. Soft Matter. 2017; 13 ( 27 ): 4733 – 4745. | |
dc.identifier.citedreference | Dietz C, Kretz T, Thoma MH. Machine‐learning approach for local classification of crystalline structures in multiphase systems. Phys Rev E. 2017; 96 ( 1 ): 011301. | |
dc.identifier.citedreference | Cubuk ED, Schoenholz SS, Rieser JM, Malone BD, Rottler J, Durian DJ, Kaxiras E, Liu AJ. Identifying structural flow defects in disordered solids using machine‐learning methods. Phys Rev Lett. 2015; 114 ( 10 ): 108001. | |
dc.identifier.citedreference | Keys AS, Iacovella CR, Glotzer SC. Characterizing structure through shape matching and applications to self‐assembly. Annu Rev Condens Matter Phys. 2011; 2 ( 1 ): 263 – 285. | |
dc.identifier.citedreference | Dzugutov M. Formation of a dodecagonal quasicrystalline phase in a simple monatomic liquid. Phys Rev Lett. 1993; 70 ( 19 ): 2924 – 2927. | |
dc.identifier.citedreference | Roth J, Denton AR. Solid‐phase structures of the Dzugutov pair potential. Phys Rev E. 2000; 61 ( 6 Pt B ): 6845 – 6857. | |
dc.identifier.citedreference | Dempster AP, Laird NM, Rubin DB. Maximum likelihood from incomplete data via the EM algorithm. J R Stat Soc Ser B. 1977; 39 ( 1 ): 1 – 38. | |
dc.identifier.citedreference | Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, Blondel M, Prettenhofer P, Weiss R, Dubourg V, Vanderplas J, Passos A, Cournapeau D, Brucher M, Perrot M, Duchesnay E. Scikit‐learn: machine learning in Python. J Mach Learning Res. 2011; 12: 2825 – 2830. | |
dc.identifier.citedreference | Schwarz G. Estimating the dimension of a model. Ann Stat. 1978; 6 ( 2 ): 461 – 464. | |
dc.identifier.citedreference | Hennig C. Methods for merging Gaussian mixture components. Adv Data Anal Classif. 2010; 4 ( 1 ): 3 – 34. | |
dc.identifier.citedreference | Baudry JP, Raftery AE, Celeux G, Lo K, Gottardo R. Combining mixture components for clustering. J Comput Graph Stat. 2010; 19 ( 2 ): 332 – 353. | |
dc.identifier.citedreference | Pastore A, Tonellato S. A Merging Algorithm for Gaussian Mixture Components. Working Paper 2013:04; Department of Economics, University of Venice “Ca’ Foscari”. 2013; | |
dc.identifier.citedreference | Scrucca L. Identifying connected components in Gaussian finite mixture models for clustering. Comput Stat Data Anal. 2016; 93: 5 – 17. | |
dc.identifier.citedreference | Pearson K. On lines and planes of closest fit to systems of points in space. Lond Edinburgh Dublin Philos Mag J Sci. 1901; 2 ( 11 ): 559 – 572. | |
dc.identifier.citedreference | Chollet FK. 2015. Available at https://github.com/keras-team/keras | |
dc.identifier.citedreference | Henzie J, Grünwald M, Widmer‐Cooper A, Geissler PL, Yang P. Self‐assembly of uniform polyhedral silver nanocrystals into densest packings and exotic superlattices. Nat Mater. 2011; 11 ( 2 ): 131 – 137. | |
dc.identifier.citedreference | Shevchenko EV, Talapin DV, Kotov NA, O’Brien S, Murray CB. Structural diversity in binary nanoparticle superlattices. Nature. 2006; 439 ( 7072 ): 55 – 59. | |
dc.identifier.citedreference | Macfarlane RJ, Lee B, Jones MR, Harris N, Schatz GC, Mirkin CA. Nanoparticle superlattice engineering with DNA. Science. 2011; 334 ( 6053 ): 204 – 208. | |
dc.identifier.citedreference | Zhang C, Macfarlane RJ, Young KL, Choi CHJ, Hao L, Auyeung E, Liu G, Zhou X, Mirkin CA. A general approach to DNA‐programmable atom equivalents. Nat Mater. 2013; 12 ( 8 ): 741 – 746. | |
dc.identifier.citedreference | Li B, Zhou D, Han Y. Assembly and phase transitions of colloidal crystals. Nat Rev Mater. 2016; 1 ( 2 ): 15011. | |
dc.identifier.citedreference | Hynninen AP, Christova CG, van Roij R, van Blaaderen A, Dijkstra M. Prediction and observation of crystal structures of oppositely charged colloids. Physl Rev Lett. 2006; 96 ( 13 ): 138308‐1 – 138308‐4. | |
dc.identifier.citedreference | Glaser MA, Grason GM, Kamien RD, Košmrlj A, Santangelo CD, Ziherl P. Soft spheres make more mesophases. Europhys Lett (EPL). 2007; 78 ( 4 ): 46004. | |
dc.identifier.citedreference | Batten RD, Huse DA, Stillinger FH, Torquato S. Novel ground‐state crystals with controlled vacancy concentrations: from kagomé to honeycomb to stripes. Soft Matter. 2011; 7 ( 13 ): 6194. | |
dc.identifier.citedreference | Costa Campos LQ, de Souza Silva CC, Apolinario SWS. Structural phases of colloids interacting via a flat‐well potential. Phys Rev E. 2012; 86 ( 5 ): 051402‐1 – 051402‐6. | |
dc.identifier.citedreference | Damasceno PF, Engel M, Glotzer SC. Predictive self‐assembly of polyhedra into complex structures. Science. 2012; 337 ( 6093 ): 453 – 457. | |
dc.identifier.citedreference | Engel M, Damasceno PF, Phillips CL, Glotzer SC. Computational self‐assembly of a one‐component icosahedral quasicrystal. Nat Mater. 2015; 14 ( 1 ): 109 – 116. | |
dc.identifier.citedreference | Bernard EP, Krauth W. Two‐step melting in two dimensions: first‐order liquid‐hexatic transition. Phys Rev Lett. 2011; 107 ( 15 ): 155704. | |
dc.identifier.citedreference | Engel M, Anderson JA, Glotzer SC, Isobe M, Bernard EP, Krauth W. Hard‐disk equation of state: first‐order liquid‐hexatic transition in two dimensions with three simulation methods. Phys Rev E. 2013; 87 ( 4 ): 042134-1 – 042134-8. | |
dc.identifier.citedreference | Wojciechowski KW, Frenkel D. Tetratic phase in the planar hard square system? Comput Methods Sci Technol. 2004; 10 ( 2 ): 235 – 255. | |
dc.identifier.citedreference | Donev A, Burton J, Stillinger FH, Torquato S. Tetratic order in the phase behavior of a hard‐rectangle system. Phys Rev B. 2006; 73 ( 5 ): 054109. | |
dc.identifier.citedreference | Redner GS, Hagan MF, Baskaran A. Structure and dynamics of a phase‐separating active colloidal fluid. Phys Rev Lett. 2013; 110 ( 5 ): 55701. | |
dc.identifier.citedreference | Steinhardt PJ, Nelson DR, Ronchetti M. Bond‐orientational order in liquids and glasses. Phys Rev B. 1983; 28 ( 2 ): 784. | |
dc.identifier.citedreference | van Duijneveldt JS, Frenkel D. Computer simulation study of free energy barriers in crystal nucleation. J Chem Phys. 1992; 96 ( 6 ): 4655 – 4668. | |
dc.identifier.citedreference | Yan Z, Buldyrev SV, Giovambattista N, Stanley HE. Structural order for one‐scale and two‐scale potentials. Phys Rev Lett. 2005; 95 ( 13 ): 130604. | |
dc.identifier.citedreference | Lechner W, Dellago C. Accurate determination of crystal structures based on averaged local bond order parameters. J Chem Phys. 2008; 129 ( 11 ): 114707. | |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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