Show simple item record

Machine learning for crystal identification and discovery

dc.contributor.authorSpellings, Matthew
dc.contributor.authorGlotzer, Sharon C.
dc.date.accessioned2018-05-15T20:12:27Z
dc.date.available2019-08-01T19:53:24Zen
dc.date.issued2018-06
dc.identifier.citationSpellings, Matthew; Glotzer, Sharon C. (2018). "Machine learning for crystal identification and discovery." AIChE Journal 64(6): 2198-2206.
dc.identifier.issn0001-1541
dc.identifier.issn1547-5905
dc.identifier.urihttps://hdl.handle.net/2027.42/143597
dc.publisherWiley Periodicals, Inc.
dc.subject.othercomputational
dc.subject.otherself‐assembly
dc.subject.othercrystal
dc.subject.otherdata science
dc.subject.othermachine learning
dc.titleMachine learning for crystal identification and discovery
dc.typeArticleen_US
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelChemical Engineering
dc.subject.hlbtoplevelEngineering
dc.subject.hlbtoplevelScience
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/143597/1/aic16157.pdf
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/143597/2/aic16157_am.pdf
dc.identifier.doi10.1002/aic.16157
dc.identifier.sourceAIChE Journal
dc.identifier.citedreferenceSeo 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.citedreferenceWolde 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.citedreferenceChau PL, Hardwick AJ. A new order parameter for tetrahedral configurations. Mol Phys. 1998; 93 ( 3 ): 511 – 518.
dc.identifier.citedreferenceHaji‐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.citedreferencePhillips CL, Voth GA. Discovering crystals using shape matching and machine learning. Soft Matter. 2013; 9 ( 35 ): 8552 – 8568.
dc.identifier.citedreferenceReinhart 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.citedreferenceDietz 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.citedreferenceCubuk 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.citedreferenceKeys 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.citedreferenceDzugutov M. Formation of a dodecagonal quasicrystalline phase in a simple monatomic liquid. Phys Rev Lett. 1993; 70 ( 19 ): 2924 – 2927.
dc.identifier.citedreferenceRoth J, Denton AR. Solid‐phase structures of the Dzugutov pair potential. Phys Rev E. 2000; 61 ( 6 Pt B ): 6845 – 6857.
dc.identifier.citedreferenceDempster 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.citedreferencePedregosa 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.citedreferenceSchwarz G. Estimating the dimension of a model. Ann Stat. 1978; 6 ( 2 ): 461 – 464.
dc.identifier.citedreferenceHennig C. Methods for merging Gaussian mixture components. Adv Data Anal Classif. 2010; 4 ( 1 ): 3 – 34.
dc.identifier.citedreferenceBaudry 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.citedreferencePastore 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.citedreferenceScrucca L. Identifying connected components in Gaussian finite mixture models for clustering. Comput Stat Data Anal. 2016; 93: 5 – 17.
dc.identifier.citedreferencePearson 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.citedreferenceChollet FK. 2015. Available at https://github.com/keras-team/keras
dc.identifier.citedreferenceHenzie 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.citedreferenceShevchenko EV, Talapin DV, Kotov NA, O’Brien S, Murray CB. Structural diversity in binary nanoparticle superlattices. Nature. 2006; 439 ( 7072 ): 55 – 59.
dc.identifier.citedreferenceMacfarlane RJ, Lee B, Jones MR, Harris N, Schatz GC, Mirkin CA. Nanoparticle superlattice engineering with DNA. Science. 2011; 334 ( 6053 ): 204 – 208.
dc.identifier.citedreferenceZhang 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.citedreferenceLi B, Zhou D, Han Y. Assembly and phase transitions of colloidal crystals. Nat Rev Mater. 2016; 1 ( 2 ): 15011.
dc.identifier.citedreferenceHynninen 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.citedreferenceGlaser 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.citedreferenceBatten 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.citedreferenceCosta 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.citedreferenceDamasceno PF, Engel M, Glotzer SC. Predictive self‐assembly of polyhedra into complex structures. Science. 2012; 337 ( 6093 ): 453 – 457.
dc.identifier.citedreferenceEngel 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.citedreferenceBernard EP, Krauth W. Two‐step melting in two dimensions: first‐order liquid‐hexatic transition. Phys Rev Lett. 2011; 107 ( 15 ): 155704.
dc.identifier.citedreferenceEngel 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.citedreferenceWojciechowski KW, Frenkel D. Tetratic phase in the planar hard square system? Comput Methods Sci Technol. 2004; 10 ( 2 ): 235 – 255.
dc.identifier.citedreferenceDonev 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.citedreferenceRedner GS, Hagan MF, Baskaran A. Structure and dynamics of a phase‐separating active colloidal fluid. Phys Rev Lett. 2013; 110 ( 5 ): 55701.
dc.identifier.citedreferenceSteinhardt PJ, Nelson DR, Ronchetti M. Bond‐orientational order in liquids and glasses. Phys Rev B. 1983; 28 ( 2 ): 784.
dc.identifier.citedreferencevan Duijneveldt JS, Frenkel D. Computer simulation study of free energy barriers in crystal nucleation. J Chem Phys. 1992; 96 ( 6 ): 4655 – 4668.
dc.identifier.citedreferenceYan 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.citedreferenceLechner W, Dellago C. Accurate determination of crystal structures based on averaged local bond order parameters. J Chem Phys. 2008; 129 ( 11 ): 114707.
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.