Machine learning for glass science and engineering: A review
The design of new glasses is often plagued by poorly efficient Edisonian “trial-and-error” discovery approaches. As an alternative route, the Materials Genome Initiative has largely popularized new approaches relying on artificial intelligence and machine learning for accelerating the discovery and...
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| Veröffentlicht in: | Journal of non-crystalline solids Jg. 557; H. C; S. 119419 |
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| Hauptverfasser: | , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Netherlands
Elsevier B.V
01.04.2021
Elsevier |
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| ISSN: | 0022-3093, 1873-4812 |
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| Abstract | The design of new glasses is often plagued by poorly efficient Edisonian “trial-and-error” discovery approaches. As an alternative route, the Materials Genome Initiative has largely popularized new approaches relying on artificial intelligence and machine learning for accelerating the discovery and optimization of novel, advanced materials. Here, we review some recent progress in adopting machine learning to accelerate the design of new glasses with tailored properties.
•We review some recent progress in machine learning applied to glass science.•We provide an introduction to common machine learning techniques.•We highlight the benefits of “physics-informed machine learning.”•We show how machine learning and physics-based modeling can be used in synergy.•We discuss some potential future directions in the use of machine learning in glass science. |
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| AbstractList | The design of new glasses is often plagued by poorly efficient Edisonian “trial-and-error” discovery approaches. As an alternative route, the Materials Genome Initiative has largely popularized new approaches relying on artificial intelligence and machine learning for accelerating the discovery and optimization of novel, advanced materials. Here, we review some recent progress in adopting machine learning to accelerate the design of new glasses with tailored properties.
•We review some recent progress in machine learning applied to glass science.•We provide an introduction to common machine learning techniques.•We highlight the benefits of “physics-informed machine learning.”•We show how machine learning and physics-based modeling can be used in synergy.•We discuss some potential future directions in the use of machine learning in glass science. |
| ArticleNumber | 119419 |
| Author | Xu, Xinyi Liu, Han Yang, Kai Fu, Zipeng Bauchy, Mathieu |
| Author_xml | – sequence: 1 givenname: Han surname: Liu fullname: Liu, Han organization: Physics of Amorphous and Inorganic Solids Laboratory (PARISlab), Department of Civil and Environmental Engineering, University of California, Los Angeles, CA 90095, USA – sequence: 2 givenname: Zipeng surname: Fu fullname: Fu, Zipeng organization: Physics of Amorphous and Inorganic Solids Laboratory (PARISlab), Department of Civil and Environmental Engineering, University of California, Los Angeles, CA 90095, USA – sequence: 3 givenname: Kai surname: Yang fullname: Yang, Kai organization: Physics of Amorphous and Inorganic Solids Laboratory (PARISlab), Department of Civil and Environmental Engineering, University of California, Los Angeles, CA 90095, USA – sequence: 4 givenname: Xinyi surname: Xu fullname: Xu, Xinyi organization: Physics of Amorphous and Inorganic Solids Laboratory (PARISlab), Department of Civil and Environmental Engineering, University of California, Los Angeles, CA 90095, USA – sequence: 5 givenname: Mathieu orcidid: 0000-0003-4600-0631 surname: Bauchy fullname: Bauchy, Mathieu email: bauchy@ucla.edu organization: Physics of Amorphous and Inorganic Solids Laboratory (PARISlab), Department of Civil and Environmental Engineering, University of California, Los Angeles, CA 90095, USA |
| BackLink | https://www.osti.gov/biblio/1809420$$D View this record in Osti.gov |
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| Cites_doi | 10.1021/acs.jpcb.6b02144 10.1038/nphys3644 10.1063/1.4886421 10.1016/j.jnoncrysol.2018.04.063 10.1103/PhysRevLett.114.108001 10.2109/jcersj.110.1103 10.1016/j.patrec.2004.09.007 10.1016/j.jnucmat.2005.06.023 10.1016/j.jnoncrysol.2004.07.081 10.1016/j.jnoncrysol.2018.11.019 10.1111/j.2517-6161.1996.tb02080.x 10.1023/A:1009715923555 10.1126/science.aaa8415 10.1103/PhysRevB.95.094203 10.1039/c0an00387e 10.2320/jinstmet1952.64.3_177 10.1103/PhysRevLett.122.028001 10.1038/s41529-019-0094-1 10.21809/rilemtechlett.2017.35 10.1016/0022-3093(82)90297-6 10.1063/1.4998611 10.1016/j.jnoncrysol.2009.01.022 10.1111/j.1551-2916.2007.01945.x 10.1016/0022-3093(79)90033-4 10.1096/fasebj.1.5.3315805 10.1016/j.jnoncrysol.2016.06.023 10.1016/j.patrec.2009.09.011 10.1145/331499.331504 10.1111/jace.16082 10.1021/acs.jpcb.7b04535 10.1016/S0254-0584(02)00331-0 10.1111/j.1467-9868.2005.00503.x 10.4310/SII.2009.v2.n3.a8 10.1111/ijag.12087 10.1109/79.180705 10.1016/S0169-7439(99)00026-X 10.1016/j.commatsci.2016.07.041 10.1103/PhysRevLett.105.115503 10.1111/j.1151-2916.1978.tb09222.x 10.1209/0295-5075/82/17001 10.1021/acs.jpcb.6b11371 10.1063/1.342716 10.1083/jcb.200611141 10.1126/science.aai8830 10.1038/44565 10.1080/00401706.1970.10488634 10.1016/j.actamat.2018.08.022 10.1016/S0004-3702(03)00055-9 10.2320/jinstmet1952.65.8_680 10.1080/00031305.1992.10475879 10.1016/j.enconman.2013.03.004 10.1111/ijag.12058 10.1016/S0031-3203(02)00060-2 10.1021/acs.chemmater.6b01054 10.2139/ssrn.332382 10.1214/aos/1013203451 10.1016/0025-5408(84)90094-1 10.1080/00031305.1988.10475524 10.1103/PhysRevLett.114.125502 10.1016/j.jnoncrysol.2019.03.033 10.1111/j.1151-2916.1985.tb09656.x 10.1016/S1352-2310(97)00447-0 10.1103/PhysRevB.97.054303 10.1109/TNN.2005.845141 10.1016/j.commatsci.2018.12.004 10.1016/j.jnoncrysol.2006.12.005 10.1146/annurev.cs.04.060190.002221 10.3389/fmats.2017.00002 10.1162/neco.1989.1.3.295 10.1063/1.5023707 10.1111/jace.15122 10.1016/j.cossms.2017.09.001 10.1073/pnas.1703927114 10.1016/0022-3093(89)90582-6 10.1016/j.jnoncrysol.2018.02.023 10.1038/nmeth.3968 10.1021/acs.langmuir.6b00359 |
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| Keywords | Structural signature Artificial neuron network Composition-property relationship Molecular dynamics simulation Bayesian optimization |
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| References | Lutsko (bb0435) 1989; 65 Liu, Fu, Li, Sabri, Bauchy (bb0550) 2019; 1902 Yang, Xu, Yang, Cook, Ramos, Bauchy (bb0385) 2019; 1901 Chrisley (bb0165) 2003; 149 Bengio, Grandvalet (bb0280) 2004; 5 Rowe, Csányi, Alfè, Michaelides (bb0565) 2018; 97 Inaba, Oda, Morinaga (bb0465) 2001; 65 Cassar, de Carvalho, Zanotto (bb0185) 2018; 159 Shewchuk (bb0605) 1994 Sussman, Schoenholz, Cubuk, Liu (bb0540) 2017; 114 Duda, Hart, Stork (bb0135) 2012 Hastie, Rosset, Zhu, Zou (bb0305) 2009; 2 Motulsky, Ransnas (bb0205) 1987; 1 Hwa, Hsieh, Liu (bb0445) 2003; 78 Priven, Mazurin (bb0160) 2008; 39–40 Onbaşlı, Tandia, Mauro (bb0090) 2018 Jain, Murty, Flynn (bb0145) 1999; 31 Härdle (bb0210) 1990 Liaw, Wiener (bb0245) 2002; vol. 2 Lee, Seung (bb0360) 1999; 401 Draper, Smith (bb0130) 2014 Shelby (bb0505) 1985; 68 Du (bb0075) 2015 Jain (bb0315) 2010; 31 Bartók, Kermode, Bernstein, Csányi (bb0555) 2018; 8 Seber, Lee (bb0195) 2012 Rouxel (bb0440) 2007; 90 Liu, Zhang, Krishnan, Smedskjaer, Ryan, Gin, Bauchy (bb0170) 2019 Yang, Yang, Xu, Hoover, Smedskjaer, Bauchy (bb0060) 2019; 514 Oey, Frederiksen, Mascaraque, Youngman, Balonis, Smedskjaer, Bauchy, Sant (bb0420) 2019; 505 Altman (bb0215) 1992; 46 Anoop Krishnan, Mangalathu, Smedskjaer, Tandia, Burton, Bauchy (bb0180) 2018; 487 Cumming, Fidler, Vaux (bb0150) 2007; 177 Sundararaman, Huang, Ispas, Kob (bb0585) 2018; 148 Liu, Du, Krishnan, Li, Bauchy (bb0025) 2018 Simonyan, Zisserman (bb0105) 2014 Hush, Horne (bb0125) 1993; 10 Varshneya (bb0020) 1993 Frazier, Wang (bb0610) 2016 Lever, Krzywinski, Altman (bb0275) 2016; 13 Mauro, Tandia, Vargheese, Mauro, Smedskjaer (bb0055) 2016; 28 Tibshirani (bb0290) 1996; 58 Ma, Davidson, Still, Ivancic, Schoenholz, Liu, Yodh (bb0545) 2019; 122 Mauro (bb0030) 2018; 22 Wang, Anoop Krishnan, Wang, Smedskjaer, Mauro, Bauchy (bb0590) 2018; 498 Rocherulle, Ecolivet, Poulain, Verdier, Laurent (bb0475) 1989; 108 Schoenholz, Cubuk, Sussman, Kaxiras, Liu (bb0525) 2016; 12 Hellström, Behler (bb0570) 2018 Mauro, Zanotto (bb0010) 2014; 5 Vienna, Neeway, Ryan, Kerisit (bb0390) 2018; 2 Barlow (bb0140) 1989; 1 Tong (bb0225) 1990 Mascaraque, Bauchy, Fierro, Rzoska, Bockowski, Smedskjaer (bb0430) 2017; 121 Burges (bb0240) 1998; 2 Friedman (bb0250) 2001; 29 Rasmussen, Williams (bb0220) 2008 Sugimura, Inaba, Abe, Morinaga (bb0485) 2002; 110 Rui, Wunsch (bb0310) 2005; 16 Zou, Hastie (bb0285) 2005; 67 Cubuk, Schoenholz, Rieser, Malone, Rottler, Durian, Kaxiras, Liu (bb0535) 2015; 114 Mauro, Philip, Vaughn, Pambianchi (bb0005) 2014; 5 Bauchy (bb0035) 2019; 159 Pignatelli, Kumar, Bauchy, Sant (bb0410) 2016; 32 Bishop (bb0120) 2006 Khalid, Khalil, Nasreen (bb0345) 2014 Bauchy (bb0575) 2014; 141 Oey, Kumar, Pignatelli, Yu, Neithalath, Bullard, Bauchy, Sant (bb0405) 2017; 100 Likas, Vlassis, Verbeek (bb0325) 2003; 36 Lee Rodgers, Nicewander (bb0380) 1988; 42 Yamane, Okuyama (bb0480) 1982; 52 Bradley, Fayyad (bb0340) 1998 Li, Yuan (bb0365) 2005; 26 Mauro (bb0040) 2011; 90 Aragones, Gilboa, Postlewaite, Schmeidler (bb0270) 2002 Zanotto, Coutinho (bb0015) 2004; 347 Bauchy, Qomi, Bichara, Ulm, Pellenq (bb0520) 2015; 114 Li, Song, Yang, Krishnan, Wang, Smedskjaer, Mauro, Sant, Balonis, Bauchy (bb0085) 2017; 147 Deringer, Csányi (bb0560) 2017; 95 Carré, Ispas, Horbach, Kob (bb0595) 2016; 124 Bholowalia (bb0335) 2014; 105 Bansal, Doremus (bb0500) 2013 Yasui, Utsuno (bb0495) 1993 Mohiuddin, Mao, Jain (bb0235) 1996; 29 Pomerantsev (bb0175) 1999; 49 Wang, Venkatesh, Judd (bb0265) 1994; vol. 6 Ecolivet, Verdier (bb0455) 1984; 19 Alpaydin (bb0100) 2014 Tsugawa, Yatabe, Hirose, Matsumoto (bb0115) 1979; vol. 2 Lookman, Alexander, Rajan (bb0190) 2015 Kodinariya, Makwana (bb0330) 2013; 1 Oey, Hsiao, Callagon, Wang, Pignatelli, Bauchy, Sant (bb0415) 2017; 2 Bishnoi, Singh, Ravinder, Bauchy, Gosvami, Kodamana, Krishnan (bb0230) 2019 Wu, Zhu, Wu, Ding (bb0110) 2014; vol. 26 Madhulatha (bb0320) 2012 Russell, Russell, Norvig (bb0095) 2010 Eagan, Swearekgen (bb0450) 1978; 61 Frugier, Martin, Ribet, Advocat, Gin (bb0400) 2005; 346 Huang, Kieffer (bb0080) 2015 Cubuk, Schoenholz, Kaxiras, Liu (bb0530) 2016; 120 Jolliffe (bb0355) 2005 Weigel, Le Losq, Vialla, Dupas, Clément, Neuville, Rufflé (bb0470) 2016; 447 van der Maaten, Postma, van den Herik (bb0370) 2009 Subbotin (bb0200) 1967; 1 Binder, Kob (bb0070) 2005 Mitchell, Buchanan, DeJong, Dietterich, Rosenbloom, Waibel (bb0155) 1990; 4 Phillips (bb0045) 1979; 34 Li, Tang, Wu, Liu (bb0395) 2013; 70 Carré, Horbach, Ispas, Kob (bb0600) 2008; 82 Balabin, Lomakina (bb0260) 2011; 136 Hoerl, Kennard (bb0295) 1970; 12 Cristianini, Shawe-Taylor (bb0255) 2000 Inaba, Todaka, Ohta, Morinaga (bb0460) 2000; 64 Gross, Tomozawa, Koike (bb0490) 2009; 355 Gardner, Dorling (bb0300) 1998; 32 Jordan, Mitchell (bb0350) 2015; 349 Deng, Du (bb0580) 2019 Smedskjaer, Mauro, Yue (bb0050) 2010; 105 Cubuk, Ivancic, Schoenholz, Strickland, Basu, Davidson, Fontaine, Hor, Huang, Jiang, Keim, Koshigan, Lefever, Liu, Ma, Magagnosc, Morrow, Ortiz, Rieser, Shavit, Still, Xu, Zhang, Nordstrom, Arratia, Carpick, Durian, Fakhraai, Jerolmack, Lee, Li, Riggleman, Turner, Yodh, Gianola, Liu (bb0510) 2017; 358 (bb0065) 2015 Brauer, Rüssel, Kraft (bb0375) 2007; 353 Philipps, Stoffel, Dronskowski, Conradt (bb0515) 2017; 4 Mascaraque, Bauchy, Smedskjaer (bb0425) 2017; 121 Mauro (10.1016/j.jnoncrysol.2019.04.039_bb0010) 2014; 5 Hellström (10.1016/j.jnoncrysol.2019.04.039_bb0570) 2018 Varshneya (10.1016/j.jnoncrysol.2019.04.039_bb0020) 1993 Cubuk (10.1016/j.jnoncrysol.2019.04.039_bb0510) 2017; 358 Jain (10.1016/j.jnoncrysol.2019.04.039_bb0145) 1999; 31 Tibshirani (10.1016/j.jnoncrysol.2019.04.039_bb0290) 1996; 58 Eagan (10.1016/j.jnoncrysol.2019.04.039_bb0450) 1978; 61 Vienna (10.1016/j.jnoncrysol.2019.04.039_bb0390) 2018; 2 Khalid (10.1016/j.jnoncrysol.2019.04.039_bb0345) 2014 Motulsky (10.1016/j.jnoncrysol.2019.04.039_bb0205) 1987; 1 Alpaydin (10.1016/j.jnoncrysol.2019.04.039_bb0100) 2014 van der Maaten (10.1016/j.jnoncrysol.2019.04.039_bb0370) Chrisley (10.1016/j.jnoncrysol.2019.04.039_bb0165) 2003; 149 Oey (10.1016/j.jnoncrysol.2019.04.039_bb0405) 2017; 100 Mauro (10.1016/j.jnoncrysol.2019.04.039_bb0055) 2016; 28 Jordan (10.1016/j.jnoncrysol.2019.04.039_bb0350) 2015; 349 Smedskjaer (10.1016/j.jnoncrysol.2019.04.039_bb0050) 2010; 105 Tsugawa (10.1016/j.jnoncrysol.2019.04.039_bb0115) 1979; vol. 2 Hwa (10.1016/j.jnoncrysol.2019.04.039_bb0445) 2003; 78 Philipps (10.1016/j.jnoncrysol.2019.04.039_bb0515) 2017; 4 Onbaşlı (10.1016/j.jnoncrysol.2019.04.039_bb0090) 2018 Bartók (10.1016/j.jnoncrysol.2019.04.039_bb0555) 2018; 8 Oey (10.1016/j.jnoncrysol.2019.04.039_bb0415) 2017; 2 Deringer (10.1016/j.jnoncrysol.2019.04.039_bb0560) 2017; 95 Mascaraque (10.1016/j.jnoncrysol.2019.04.039_bb0430) 2017; 121 Li (10.1016/j.jnoncrysol.2019.04.039_bb0365) 2005; 26 Wang (10.1016/j.jnoncrysol.2019.04.039_bb0590) 2018; 498 Bradley (10.1016/j.jnoncrysol.2019.04.039_bb0340) 1998 Li (10.1016/j.jnoncrysol.2019.04.039_bb0085) 2017; 147 Liu (10.1016/j.jnoncrysol.2019.04.039_bb0025) 2018 Jolliffe (10.1016/j.jnoncrysol.2019.04.039_bb0355) 2005 Carré (10.1016/j.jnoncrysol.2019.04.039_bb0595) 2016; 124 Yasui (10.1016/j.jnoncrysol.2019.04.039_bb0495) 1993 Burges (10.1016/j.jnoncrysol.2019.04.039_bb0240) 1998; 2 Lee Rodgers (10.1016/j.jnoncrysol.2019.04.039_bb0380) 1988; 42 Rui (10.1016/j.jnoncrysol.2019.04.039_bb0310) 2005; 16 Bengio (10.1016/j.jnoncrysol.2019.04.039_bb0280) 2004; 5 Madhulatha (10.1016/j.jnoncrysol.2019.04.039_bb0320) Mohiuddin (10.1016/j.jnoncrysol.2019.04.039_bb0235) 1996; 29 Friedman (10.1016/j.jnoncrysol.2019.04.039_bb0250) 2001; 29 Pignatelli (10.1016/j.jnoncrysol.2019.04.039_bb0410) 2016; 32 Bishnoi (10.1016/j.jnoncrysol.2019.04.039_bb0230) Hastie (10.1016/j.jnoncrysol.2019.04.039_bb0305) 2009; 2 Seber (10.1016/j.jnoncrysol.2019.04.039_bb0195) 2012 Liu (10.1016/j.jnoncrysol.2019.04.039_bb0550) 2019; 1902 Zou (10.1016/j.jnoncrysol.2019.04.039_bb0285) 2005; 67 Zanotto (10.1016/j.jnoncrysol.2019.04.039_bb0015) 2004; 347 Tong (10.1016/j.jnoncrysol.2019.04.039_bb0225) 1990 Bauchy (10.1016/j.jnoncrysol.2019.04.039_bb0520) 2015; 114 Phillips (10.1016/j.jnoncrysol.2019.04.039_bb0045) 1979; 34 Draper (10.1016/j.jnoncrysol.2019.04.039_bb0130) 2014 Bishop (10.1016/j.jnoncrysol.2019.04.039_bb0120) 2006 (10.1016/j.jnoncrysol.2019.04.039_bb0065) 2015 Subbotin (10.1016/j.jnoncrysol.2019.04.039_bb0200) 1967; 1 Simonyan (10.1016/j.jnoncrysol.2019.04.039_bb0105) Anoop Krishnan (10.1016/j.jnoncrysol.2019.04.039_bb0180) 2018; 487 Sugimura (10.1016/j.jnoncrysol.2019.04.039_bb0485) 2002; 110 Mitchell (10.1016/j.jnoncrysol.2019.04.039_bb0155) 1990; 4 Rocherulle (10.1016/j.jnoncrysol.2019.04.039_bb0475) 1989; 108 Rowe (10.1016/j.jnoncrysol.2019.04.039_bb0565) 2018; 97 Lutsko (10.1016/j.jnoncrysol.2019.04.039_bb0435) 1989; 65 Cristianini (10.1016/j.jnoncrysol.2019.04.039_bb0255) 2000 Yang (10.1016/j.jnoncrysol.2019.04.039_bb0060) 2019; 514 Lever (10.1016/j.jnoncrysol.2019.04.039_bb0275) 2016; 13 Priven (10.1016/j.jnoncrysol.2019.04.039_bb0160) 2008; 39–40 Sundararaman (10.1016/j.jnoncrysol.2019.04.039_bb0585) 2018; 148 Cubuk (10.1016/j.jnoncrysol.2019.04.039_bb0535) 2015; 114 Härdle (10.1016/j.jnoncrysol.2019.04.039_bb0210) 1990 Rouxel (10.1016/j.jnoncrysol.2019.04.039_bb0440) 2007; 90 Altman (10.1016/j.jnoncrysol.2019.04.039_bb0215) 1992; 46 Mauro (10.1016/j.jnoncrysol.2019.04.039_bb0040) 2011; 90 Frugier (10.1016/j.jnoncrysol.2019.04.039_bb0400) 2005; 346 Frazier (10.1016/j.jnoncrysol.2019.04.039_bb0610) 2016 Cassar (10.1016/j.jnoncrysol.2019.04.039_bb0185) 2018; 159 Gross (10.1016/j.jnoncrysol.2019.04.039_bb0490) 2009; 355 Lee (10.1016/j.jnoncrysol.2019.04.039_bb0360) 1999; 401 Barlow (10.1016/j.jnoncrysol.2019.04.039_bb0140) 1989; 1 Hoerl (10.1016/j.jnoncrysol.2019.04.039_bb0295) 1970; 12 Bauchy (10.1016/j.jnoncrysol.2019.04.039_bb0035) 2019; 159 Jain (10.1016/j.jnoncrysol.2019.04.039_bb0315) 2010; 31 Wu (10.1016/j.jnoncrysol.2019.04.039_bb0110) 2014; vol. 26 Brauer (10.1016/j.jnoncrysol.2019.04.039_bb0375) 2007; 353 Cumming (10.1016/j.jnoncrysol.2019.04.039_bb0150) 2007; 177 Wang (10.1016/j.jnoncrysol.2019.04.039_bb0265) 1994; vol. 6 Bholowalia (10.1016/j.jnoncrysol.2019.04.039_bb0335) 2014; 105 Inaba (10.1016/j.jnoncrysol.2019.04.039_bb0465) 2001; 65 Bansal (10.1016/j.jnoncrysol.2019.04.039_bb0500) 2013 Aragones (10.1016/j.jnoncrysol.2019.04.039_bb0270) 2002 Yamane (10.1016/j.jnoncrysol.2019.04.039_bb0480) 1982; 52 Russell (10.1016/j.jnoncrysol.2019.04.039_bb0095) 2010 Rasmussen (10.1016/j.jnoncrysol.2019.04.039_bb0220) 2008 Shewchuk (10.1016/j.jnoncrysol.2019.04.039_bb0605) Duda (10.1016/j.jnoncrysol.2019.04.039_bb0135) 2012 Shelby (10.1016/j.jnoncrysol.2019.04.039_bb0505) 1985; 68 Binder (10.1016/j.jnoncrysol.2019.04.039_bb0070) 2005 Kodinariya (10.1016/j.jnoncrysol.2019.04.039_bb0330) 2013; 1 Sussman (10.1016/j.jnoncrysol.2019.04.039_bb0540) 2017; 114 Li (10.1016/j.jnoncrysol.2019.04.039_bb0395) 2013; 70 Huang (10.1016/j.jnoncrysol.2019.04.039_bb0080) 2015 Likas (10.1016/j.jnoncrysol.2019.04.039_bb0325) 2003; 36 Mascaraque (10.1016/j.jnoncrysol.2019.04.039_bb0425) 2017; 121 Hush (10.1016/j.jnoncrysol.2019.04.039_bb0125) 1993; 10 Balabin (10.1016/j.jnoncrysol.2019.04.039_bb0260) 2011; 136 Du (10.1016/j.jnoncrysol.2019.04.039_bb0075) 2015 Carré (10.1016/j.jnoncrysol.2019.04.039_bb0600) 2008; 82 Bauchy (10.1016/j.jnoncrysol.2019.04.039_bb0575) 2014; 141 Deng (10.1016/j.jnoncrysol.2019.04.039_bb0580) 2019 Ma (10.1016/j.jnoncrysol.2019.04.039_bb0545) 2019; 122 Mauro (10.1016/j.jnoncrysol.2019.04.039_bb0030) 2018; 22 Liaw (10.1016/j.jnoncrysol.2019.04.039_bb0245) 2002; vol. 2 Schoenholz (10.1016/j.jnoncrysol.2019.04.039_bb0525) 2016; 12 Cubuk (10.1016/j.jnoncrysol.2019.04.039_bb0530) 2016; 120 Lookman (10.1016/j.jnoncrysol.2019.04.039_bb0190) 2015 Weigel (10.1016/j.jnoncrysol.2019.04.039_bb0470) 2016; 447 Inaba (10.1016/j.jnoncrysol.2019.04.039_bb0460) 2000; 64 Gardner (10.1016/j.jnoncrysol.2019.04.039_bb0300) 1998; 32 Liu (10.1016/j.jnoncrysol.2019.04.039_bb0170) 2019 Yang (10.1016/j.jnoncrysol.2019.04.039_bb0385) 2019; 1901 Oey (10.1016/j.jnoncrysol.2019.04.039_bb0420) 2019; 505 Ecolivet (10.1016/j.jnoncrysol.2019.04.039_bb0455) 1984; 19 Mauro (10.1016/j.jnoncrysol.2019.04.039_bb0005) 2014; 5 Pomerantsev (10.1016/j.jnoncrysol.2019.04.039_bb0175) 1999; 49 |
| References_xml | – volume: 105 year: 2010 ident: bb0050 article-title: Prediction of glass hardness using temperature-dependent constraint theory publication-title: Phys. Rev. Lett. – year: 2015 ident: bb0190 article-title: Information Science for Materials Discovery and Design – year: 2015 ident: bb0065 publication-title: Molecular Dynamics Simulations of Disordered Materials – volume: 1 start-page: 41 year: 1967 end-page: 45 ident: bb0200 article-title: Piecewise-polynomial (spline) interpolation publication-title: Mathemat. Notes Acad. Sci. USSR – volume: 8 year: 2018 ident: bb0555 article-title: Machine learning a general-purpose interatomic potential for silicon publication-title: Phys. Rev. X – volume: 105 start-page: 17 year: 2014 end-page: 24 ident: bb0335 article-title: EBK-means: a clustering technique based on elbow method and K-means in WSN publication-title: Int. J. Comput. Appl. – volume: 19 start-page: 227 year: 1984 end-page: 231 ident: bb0455 article-title: Proprietes elastiques et indices de refraction de verres azotes publication-title: Mater. Res. Bull. – volume: 353 start-page: 263 year: 2007 end-page: 270 ident: bb0375 article-title: Solubility of glasses in the system P2O5–CaO–MgO–Na2O–TiO2: experimental and modeling using artificial neural networks publication-title: J. Non-Cryst. Solids – volume: 52 start-page: 217 year: 1982 end-page: 226 ident: bb0480 article-title: Coordination number of aluminum ions in alkali-free alumino-silicate glasses publication-title: J. Non-Cryst. Solids – volume: 2 start-page: 67 year: 2017 end-page: 73 ident: bb0415 article-title: Rate controls on silicate dissolution in cementitious environments publication-title: RILEM Tech. Lett. – volume: 4 year: 2017 ident: bb0515 article-title: Experimental and theoretical investigation of the elastic moduli of silicate glasses and crystals publication-title: Front. Mater. – volume: 49 start-page: 41 year: 1999 end-page: 48 ident: bb0175 article-title: Confidence intervals for nonlinear regression extrapolation publication-title: Chemom. Intell. Lab. Syst. – year: 1990 ident: bb0225 article-title: The Multivariate Normal Distribution – year: 2006 ident: bb0120 article-title: Pattern Recognition and Machine Learning – volume: vol. 6 start-page: 303 year: 1994 end-page: 310 ident: bb0265 article-title: Optimal stopping and effective machine complexity in learning publication-title: Advances in Neural Information Processing Systems – volume: 121 start-page: 9063 year: 2017 end-page: 9072 ident: bb0430 article-title: Dissolution kinetics of hot compressed oxide glasses publication-title: J. Phys. Chem. B – volume: 29 start-page: 31 year: 1996 end-page: 44 ident: bb0235 article-title: Artificial neural networks: a tutorial publication-title: Computer – volume: vol. 2 start-page: 18 year: 2002 end-page: 22 ident: bb0245 article-title: Classification and Regression by randomForest – volume: 1 start-page: 295 year: 1989 end-page: 311 ident: bb0140 article-title: Unsupervised learning publication-title: Neural Comput. – volume: 12 start-page: 55 year: 1970 end-page: 67 ident: bb0295 article-title: Ridge regression: biased estimation for nonorthogonal problems publication-title: Technometrics – volume: 90 start-page: 31 year: 2011 end-page: 37 ident: bb0040 article-title: Topological constraint theory of glass publication-title: Am. Ceram. Soc. Bull. – volume: 401 start-page: 788 year: 1999 end-page: 791 ident: bb0360 article-title: Learning the parts of objects by non-negative matrix factorization publication-title: Nature – volume: 1901 start-page: 1 year: 2019 end-page: 20 ident: bb0385 article-title: Prediction of silicate Glasses' stiffness by high-throughput molecular dynamics simulations and machine learning publication-title: Cond-Mat, Phys. – year: 2014 ident: bb0130 article-title: Applied Regression Analysis – volume: 349 start-page: 255 year: 2015 end-page: 260 ident: bb0350 article-title: Machine learning: trends, perspectives, and prospects publication-title: Science – start-page: 1 year: 2018 end-page: 20 ident: bb0570 article-title: Neural network potentials in materials Modeling publication-title: Handbook of Materials Modeling – volume: 114 year: 2015 ident: bb0535 article-title: Identifying structural flow defects in disordered solids using machine-learning methods publication-title: Phys. Rev. Lett. – volume: 39–40 start-page: 145 year: 2008 end-page: 150 ident: bb0160 article-title: Glass property databases: their history, present state, and prospects for further development publication-title: Adv. Mater. Res. – year: 1990 ident: bb0210 article-title: Applied Nonparametric Regression – volume: 498 start-page: 294 year: 2018 end-page: 304 ident: bb0590 article-title: A new transferable interatomic potential for molecular dynamics simulations of borosilicate glasses publication-title: J. Non-Cryst. Solids – volume: 31 start-page: 651 year: 2010 end-page: 666 ident: bb0315 article-title: Data clustering: 50 years beyond K-means publication-title: Pattern Recogn. Lett. – year: 2012 ident: bb0195 article-title: Linear Regression Analysis – volume: 110 start-page: 1103 year: 2002 end-page: 1106 ident: bb0485 article-title: Compositional dependence of mechanical properties in auminosilicate, borate and phosphate glasses publication-title: J. Ceram. Soc. Jpn. – volume: 358 start-page: 1033 year: 2017 end-page: 1037 ident: bb0510 article-title: Structure-property relationships from universal signatures of plasticity in disordered solids publication-title: Science – year: 2000 ident: bb0255 publication-title: An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods – volume: 147 year: 2017 ident: bb0085 article-title: Cooling rate effects in sodium silicate glasses: bridging the gap between molecular dynamics simulations and experiments publication-title: J. Chem. Phys. – year: 1993 ident: bb0020 article-title: Fundamentals of Inorganic Glasses – volume: 346 start-page: 194 year: 2005 end-page: 207 ident: bb0400 article-title: The effect of composition on the leaching of three nuclear waste glasses: R7T7, AVM and VRZ publication-title: J. Nucl. Mater. – volume: 159 start-page: 95 year: 2019 end-page: 102 ident: bb0035 article-title: Deciphering the atomic genome of glasses by topological constraint theory and molecular dynamics: a review publication-title: Comput. Mater. Sci. – start-page: 45 year: 2016 end-page: 75 ident: bb0610 article-title: Bayesian optimization for materials design publication-title: Information Science for Materials Discovery and Design – year: 1994 ident: bb0605 article-title: An Introduction to the Conjugate Gradient Method without the Agonizing Pain – year: 2014 ident: bb0105 article-title: Very Deep Convolutional Networks for Large-Scale Image Recognition – volume: 28 start-page: 4267 year: 2016 end-page: 4277 ident: bb0055 article-title: Accelerating the design of functional glasses through modeling publication-title: Chem. Mater. – volume: 32 start-page: 4434 year: 2016 end-page: 4439 ident: bb0410 article-title: Topological control on Silicates' dissolution kinetics publication-title: Langmuir – volume: 34 start-page: 153 year: 1979 end-page: 181 ident: bb0045 article-title: Topology of covalent non-crystalline solids I: short-range order in chalcogenide alloys publication-title: J. Non-Cryst. Solids – volume: 2 year: 2018 ident: bb0390 article-title: Impacts of glass composition, pH, and temperature on glass forward dissolution rate publication-title: NPJ Mater. Degradation – start-page: 1539 year: 1993 end-page: 1544 ident: bb0495 article-title: Material Design of Glasses Based on database – INTERGLAD publication-title: Computer Aided Innovation of New Materials II – volume: 70 start-page: 139 year: 2013 end-page: 148 ident: bb0395 article-title: General models for estimating daily global solar radiation for different solar radiation zones in mainland China publication-title: Energy Convers. Manag. – volume: 1 start-page: 365 year: 1987 end-page: 374 ident: bb0205 article-title: Fitting curves to data using nonlinear regression: a practical and nonmathematical review publication-title: FASEB J. – volume: 61 start-page: 27 year: 1978 end-page: 30 ident: bb0450 article-title: Effect of composition on the mechanical properties of aluminosilicate and borosilicate glasses publication-title: J. Am. Ceram. Soc. – year: 2013 ident: bb0500 article-title: Handbook of Glass Properties – volume: 122 year: 2019 ident: bb0545 article-title: Heterogeneous activation, local structure, and softness in Supercooled colloidal liquids publication-title: Phys. Rev. Lett. – volume: 355 start-page: 563 year: 2009 end-page: 568 ident: bb0490 article-title: A glass with high crack initiation load: role of fictive temperature-independent mechanical properties publication-title: J. Non-Cryst. Solids – year: 2010 ident: bb0095 article-title: Artificial Intelligence: A Modern Approach – volume: 65 start-page: 2991 year: 1989 end-page: 2997 ident: bb0435 article-title: Generalized expressions for the calculation of elastic constants by computer simulation publication-title: J. Appl. Phys. – year: 2014 ident: bb0100 article-title: Introduction to Machine Learning – volume: 5 start-page: 313 year: 2014 end-page: 327 ident: bb0010 article-title: Two centuries of glass research: historical trends, current status, and grand challenges for the future publication-title: Int. J. Appl. Glas. Sci. – volume: 149 start-page: 131 year: 2003 end-page: 150 ident: bb0165 article-title: Embodied artificial intelligence publication-title: Artificial Intelligence – start-page: 1 year: 2018 end-page: 23 ident: bb0090 article-title: Mechanical and compositional Design of High-Strength Corning Gorilla® glass publication-title: Handbook of Materials Modeling: Applications: Current and Emerging Materials – start-page: 372 year: 2014 end-page: 378 ident: bb0345 article-title: A survey of feature selection and feature extraction techniques in machine learning publication-title: 2014 Science and Information Conference – volume: 67 start-page: 301 year: 2005 end-page: 320 ident: bb0285 article-title: Regularization and variable selection via the elastic net publication-title: J. R. Stat. Soc. – volume: 16 start-page: 645 year: 2005 end-page: 678 ident: bb0310 article-title: Survey of clustering algorithms publication-title: IEEE Trans. Neural Netw. – volume: 42 start-page: 59 year: 1988 end-page: 66 ident: bb0380 article-title: Thirteen ways to look at the correlation coefficient publication-title: Am. Stat. – volume: 347 start-page: 285 year: 2004 end-page: 288 ident: bb0015 article-title: How many non-crystalline solids can be made from all the elements of the periodic table? publication-title: J. Non-Cryst. Solids – volume: 514 start-page: 15 year: 2019 end-page: 19 ident: bb0060 article-title: Prediction of the Young's modulus of silicate glasses by topological constraint theory publication-title: J. Non-Cryst. Solids – volume: 505 start-page: 279 year: 2019 end-page: 285 ident: bb0420 article-title: The role of the network-modifier's field-strength in the chemical durability of aluminoborate glasses publication-title: J. Non-Cryst. Solids – year: 2012 ident: bb0135 article-title: Pattern Classification – volume: 12 start-page: 469 year: 2016 end-page: 471 ident: bb0525 article-title: A structural approach to relaxation in glassy liquids publication-title: Nat. Phys. – volume: vol. 26 start-page: 97 year: 2014 end-page: 107 ident: bb0110 article-title: Data mining with big data publication-title: IEEE Transactions on Knowledge and Data Engineering – volume: 90 start-page: 3019 year: 2007 end-page: 3039 ident: bb0440 article-title: Elastic properties and short-to medium-range order in glasses publication-title: J. Am. Ceram. Soc. – volume: 1902 start-page: 1 year: 2019 end-page: 18 ident: bb0550 article-title: Machine learning Forcefield for silicate glasses publication-title: Cond-Mat – volume: 100 start-page: 5521 year: 2017 end-page: 5527 ident: bb0405 article-title: Topological controls on the dissolution kinetics of glassy aluminosilicates publication-title: J. Am. Ceram. Soc. – volume: 108 start-page: 187 year: 1989 end-page: 193 ident: bb0475 article-title: Elastic moduli of oxynitride glasses: extension of Makishima and Mackenzie's theory publication-title: J. Non-Cryst. Solids – volume: 141 year: 2014 ident: bb0575 article-title: Structural, vibrational, and elastic properties of a calcium aluminosilicate glass from molecular dynamics simulations: the role of the potential publication-title: J. Chem. Phys. – volume: 1 start-page: 6 year: 2013 ident: bb0330 article-title: Review on determining number of cluster in K-means clustering publication-title: Int. J. Adv. Res. Comput. Sci. Manage. Stud. – volume: 97 year: 2018 ident: bb0565 article-title: Development of a machine learning potential for graphene publication-title: Phys. Rev. B – volume: 120 start-page: 6139 year: 2016 end-page: 6146 ident: bb0530 article-title: Structural properties of defects in glassy liquids publication-title: J. Phys. Chem. B – volume: 32 start-page: 2627 year: 1998 end-page: 2636 ident: bb0300 article-title: Artificial neural networks (the multilayer perceptron)—a review of applications in the atmospheric sciences publication-title: Atmos. Environ. – volume: 78 start-page: 105 year: 2003 end-page: 110 ident: bb0445 article-title: Elastic moduli of low-silica calcium alumino-silicate glasses publication-title: Mater. Chem. Phys. – volume: 447 start-page: 267 year: 2016 end-page: 272 ident: bb0470 article-title: Elastic moduli of XAlSiO4 aluminosilicate glasses: effects of charge-balancing cations publication-title: J. Non-Cryst. Solids – year: 2005 ident: bb0355 article-title: Principal component analysis publication-title: Encyclopedia of Statistics in Behavioral Science – volume: 68 start-page: 155 year: 1985 end-page: 158 ident: bb0505 article-title: Formation and properties of calcium Aluminosilicate glasses publication-title: J. Am. Ceram. Soc. – year: 2019 ident: bb0170 article-title: Physics-informed machine learning: predicting the stage I dissolution kinetics of silicate glasses publication-title: NPJ Mater. Degradation – year: 2012 ident: bb0320 article-title: An Overview on Clustering Methods – year: 2008 ident: bb0220 article-title: Gaussian Processes for Machine Learning, 3. Print – volume: 114 year: 2015 ident: bb0520 article-title: Rigidity transition in materials: hardness is driven by weak atomic constraints publication-title: Phys. Rev. Lett. – year: 2005 ident: bb0070 article-title: Glassy Materials and Disordered Solids: An Introduction to their Statistical Mechanics – start-page: 87 year: 2015 end-page: 112 ident: bb0080 article-title: Challenges in Modeling mixed ionic-covalent glass formers publication-title: Molecular Dynamics Simulations of Disordered Materials – volume: 31 start-page: 264 year: 1999 end-page: 323 ident: bb0145 article-title: Data clustering: a review publication-title: ACM Comput. Surv. – volume: 36 start-page: 451 year: 2003 end-page: 461 ident: bb0325 article-title: The global k-means clustering algorithm publication-title: Pattern Recogn. – volume: 82 year: 2008 ident: bb0600 article-title: New fitting scheme to obtain effective potential from car-Parrinello molecular-dynamics simulations: application to silica publication-title: EPL – volume: 5 start-page: 1089 year: 2004 end-page: 1105 ident: bb0280 article-title: No unbiased estimator of the variance of K-fold cross-validation publication-title: J. Mach. Learn. Res. – year: 2019 ident: bb0230 article-title: Predicting Young's Modulus of Glasses with Sparse Datasets Using Machine Learning – volume: vol. 2 start-page: 893 year: 1979 end-page: 895 ident: bb0115 article-title: An automobile with artificial intelligence publication-title: Proceedings of the 6th International Joint Conference on Artificial Intelligence – year: 2002 ident: bb0270 article-title: Accuracy vs. simplicity: a complex trade-off publication-title: SSRN Electron. J. – volume: 13 start-page: 703 year: 2016 end-page: 704 ident: bb0275 article-title: Model selection and overfitting: points of significance publication-title: Nat. Methods – volume: 2 start-page: 349 year: 2009 end-page: 360 ident: bb0305 article-title: Multi-class AdaBoost publication-title: Stat. Interface. – volume: 58 start-page: 267 year: 1996 end-page: 288 ident: bb0290 article-title: Regression shrinkage and selection via the Lasso publication-title: J. R. Stat. Soc. Ser. B Methodol. – year: 2009 ident: bb0370 article-title: Dimensionality Reduction: A Comparative Review – start-page: 157 year: 2015 end-page: 180 ident: bb0075 article-title: Challenges in molecular dynamics simulations of multicomponent oxide glasses publication-title: Molecular Dynamics Simulations of Disordered Materials – volume: 65 start-page: 680 year: 2001 end-page: 687 ident: bb0465 article-title: Equation for estimating the thermal diffusivity, specific heat and thermal conductivity of oxide glasses publication-title: J. Jpn. Inst. Metals – volume: 4 start-page: 417 year: 1990 end-page: 433 ident: bb0155 article-title: Machine learning publication-title: Ann. Rev. Comput. Sci. – volume: 148 year: 2018 ident: bb0585 article-title: New optimization scheme to obtain interaction potentials for oxide glasses publication-title: J. Chem. Phys. – volume: 46 start-page: 175 year: 1992 end-page: 185 ident: bb0215 article-title: An introduction to kernel and nearest-neighbor nonparametric regression publication-title: Am. Stat. – volume: 64 start-page: 177 year: 2000 end-page: 183 ident: bb0460 article-title: Equation for estimating the young’s Modulus, shear Modulus and Vickers hardness of Aluminosilicate glasses publication-title: J. Jpn. Inst. Metals – volume: 10 start-page: 8 year: 1993 end-page: 39 ident: bb0125 article-title: Progress in supervised neural networks publication-title: IEEE Signal Process. Mag. – volume: 26 start-page: 527 year: 2005 end-page: 532 ident: bb0365 article-title: 2D-LDA: a statistical linear discriminant analysis for image matrix publication-title: Pattern Recogn. Lett. – start-page: 91 year: 1998 end-page: 99 ident: bb0340 article-title: Refining Initial Points for K-Means Clustering – volume: 159 start-page: 249 year: 2018 end-page: 256 ident: bb0185 article-title: Predicting glass transition temperatures using neural networks publication-title: Acta Mater. – volume: 29 start-page: 1189 year: 2001 end-page: 1232 ident: bb0250 article-title: Greedy function approximation: a gradient boosting machine publication-title: Ann. Stat. – year: 2019 ident: bb0580 article-title: Development of boron oxide potentials for computer simulations of multicomponent oxide glasses publication-title: J. Am. Ceram. Soc. – volume: 121 start-page: 1139 year: 2017 end-page: 1147 ident: bb0425 article-title: Correlating the network topology of oxide glasses with their chemical durability publication-title: J. Phys. Chem. B – volume: 22 start-page: 58 year: 2018 end-page: 64 ident: bb0030 article-title: Decoding the glass genome publication-title: Curr. Opinion Solid State Mater. Sci. – volume: 95 year: 2017 ident: bb0560 article-title: Machine learning based interatomic potential for amorphous carbon publication-title: Phys. Rev. B – volume: 2 start-page: 121 year: 1998 end-page: 167 ident: bb0240 article-title: A tutorial on support vector machines for pattern recognition publication-title: Data Min. Knowl. Disc. – volume: 114 start-page: 10601 year: 2017 end-page: 10605 ident: bb0540 article-title: Disconnecting structure and dynamics in glassy thin films publication-title: PNAS – volume: 487 start-page: 37 year: 2018 end-page: 45 ident: bb0180 article-title: Predicting the dissolution kinetics of silicate glasses using machine learning publication-title: J. Non-Cryst. Solids – volume: 177 start-page: 7 year: 2007 end-page: 11 ident: bb0150 article-title: Error bars in experimental biology publication-title: J. Cell Biol. – volume: 136 start-page: 1703 year: 2011 end-page: 1712 ident: bb0260 article-title: Support vector machine regression (SVR/LS-SVM)—an alternative to neural networks (ANN) for analytical chemistry? Comparison of nonlinear methods on near infrared (NIR) spectroscopy data publication-title: Analyst – volume: 124 start-page: 323 year: 2016 end-page: 334 ident: bb0595 article-title: Developing empirical potentials from ab initio simulations: the case of amorphous silica publication-title: Comput. Mater. Sci. – volume: 5 start-page: 2 year: 2014 end-page: 15 ident: bb0005 article-title: Glass science in the United States: current status and future directions publication-title: Int. J. Appl. Glas. Sci. – year: 2018 ident: bb0025 article-title: Topological optimization of cementitious binders: advances and challenges publication-title: Cem. Concr. Compos. – volume: 120 start-page: 6139 year: 2016 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0530 article-title: Structural properties of defects in glassy liquids publication-title: J. Phys. Chem. B doi: 10.1021/acs.jpcb.6b02144 – volume: 12 start-page: 469 year: 2016 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0525 article-title: A structural approach to relaxation in glassy liquids publication-title: Nat. Phys. doi: 10.1038/nphys3644 – volume: 141 year: 2014 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0575 article-title: Structural, vibrational, and elastic properties of a calcium aluminosilicate glass from molecular dynamics simulations: the role of the potential publication-title: J. Chem. Phys. doi: 10.1063/1.4886421 – volume: 498 start-page: 294 year: 2018 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0590 article-title: A new transferable interatomic potential for molecular dynamics simulations of borosilicate glasses publication-title: J. Non-Cryst. Solids doi: 10.1016/j.jnoncrysol.2018.04.063 – volume: 114 year: 2015 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0535 article-title: Identifying structural flow defects in disordered solids using machine-learning methods publication-title: Phys. Rev. Lett. doi: 10.1103/PhysRevLett.114.108001 – year: 2014 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0130 – volume: 110 start-page: 1103 year: 2002 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0485 article-title: Compositional dependence of mechanical properties in auminosilicate, borate and phosphate glasses publication-title: J. Ceram. Soc. Jpn. doi: 10.2109/jcersj.110.1103 – volume: 26 start-page: 527 year: 2005 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0365 article-title: 2D-LDA: a statistical linear discriminant analysis for image matrix publication-title: Pattern Recogn. Lett. doi: 10.1016/j.patrec.2004.09.007 – volume: 346 start-page: 194 year: 2005 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0400 article-title: The effect of composition on the leaching of three nuclear waste glasses: R7T7, AVM and VRZ publication-title: J. Nucl. Mater. doi: 10.1016/j.jnucmat.2005.06.023 – volume: 347 start-page: 285 year: 2004 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0015 article-title: How many non-crystalline solids can be made from all the elements of the periodic table? publication-title: J. Non-Cryst. Solids doi: 10.1016/j.jnoncrysol.2004.07.081 – year: 2005 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0355 article-title: Principal component analysis – volume: 505 start-page: 279 year: 2019 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0420 article-title: The role of the network-modifier's field-strength in the chemical durability of aluminoborate glasses publication-title: J. Non-Cryst. Solids doi: 10.1016/j.jnoncrysol.2018.11.019 – volume: 58 start-page: 267 year: 1996 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0290 article-title: Regression shrinkage and selection via the Lasso publication-title: J. R. Stat. Soc. Ser. B Methodol. doi: 10.1111/j.2517-6161.1996.tb02080.x – volume: 2 start-page: 121 year: 1998 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0240 article-title: A tutorial on support vector machines for pattern recognition publication-title: Data Min. Knowl. Disc. doi: 10.1023/A:1009715923555 – volume: 349 start-page: 255 year: 2015 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0350 article-title: Machine learning: trends, perspectives, and prospects publication-title: Science doi: 10.1126/science.aaa8415 – volume: 95 year: 2017 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0560 article-title: Machine learning based interatomic potential for amorphous carbon publication-title: Phys. Rev. B doi: 10.1103/PhysRevB.95.094203 – volume: 136 start-page: 1703 year: 2011 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0260 article-title: Support vector machine regression (SVR/LS-SVM)—an alternative to neural networks (ANN) for analytical chemistry? Comparison of nonlinear methods on near infrared (NIR) spectroscopy data publication-title: Analyst doi: 10.1039/c0an00387e – volume: 64 start-page: 177 year: 2000 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0460 article-title: Equation for estimating the young's Modulus, shear Modulus and Vickers hardness of Aluminosilicate glasses publication-title: J. Jpn. Inst. Metals doi: 10.2320/jinstmet1952.64.3_177 – volume: 122 year: 2019 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0545 article-title: Heterogeneous activation, local structure, and softness in Supercooled colloidal liquids publication-title: Phys. Rev. Lett. doi: 10.1103/PhysRevLett.122.028001 – start-page: 1 year: 2018 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0570 article-title: Neural network potentials in materials Modeling – year: 2019 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0170 article-title: Physics-informed machine learning: predicting the stage I dissolution kinetics of silicate glasses publication-title: NPJ Mater. Degradation doi: 10.1038/s41529-019-0094-1 – volume: 2 start-page: 67 year: 2017 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0415 article-title: Rate controls on silicate dissolution in cementitious environments publication-title: RILEM Tech. Lett. doi: 10.21809/rilemtechlett.2017.35 – volume: 52 start-page: 217 year: 1982 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0480 article-title: Coordination number of aluminum ions in alkali-free alumino-silicate glasses publication-title: J. Non-Cryst. Solids doi: 10.1016/0022-3093(82)90297-6 – volume: 147 year: 2017 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0085 article-title: Cooling rate effects in sodium silicate glasses: bridging the gap between molecular dynamics simulations and experiments publication-title: J. Chem. Phys. doi: 10.1063/1.4998611 – volume: 355 start-page: 563 year: 2009 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0490 article-title: A glass with high crack initiation load: role of fictive temperature-independent mechanical properties publication-title: J. Non-Cryst. Solids doi: 10.1016/j.jnoncrysol.2009.01.022 – volume: 90 start-page: 3019 year: 2007 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0440 article-title: Elastic properties and short-to medium-range order in glasses publication-title: J. Am. Ceram. Soc. doi: 10.1111/j.1551-2916.2007.01945.x – volume: 34 start-page: 153 year: 1979 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0045 article-title: Topology of covalent non-crystalline solids I: short-range order in chalcogenide alloys publication-title: J. Non-Cryst. Solids doi: 10.1016/0022-3093(79)90033-4 – volume: 1 start-page: 365 year: 1987 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0205 article-title: Fitting curves to data using nonlinear regression: a practical and nonmathematical review publication-title: FASEB J. doi: 10.1096/fasebj.1.5.3315805 – volume: 447 start-page: 267 year: 2016 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0470 article-title: Elastic moduli of XAlSiO4 aluminosilicate glasses: effects of charge-balancing cations publication-title: J. Non-Cryst. Solids doi: 10.1016/j.jnoncrysol.2016.06.023 – volume: 31 start-page: 651 year: 2010 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0315 article-title: Data clustering: 50 years beyond K-means publication-title: Pattern Recogn. Lett. doi: 10.1016/j.patrec.2009.09.011 – volume: 31 start-page: 264 year: 1999 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0145 article-title: Data clustering: a review publication-title: ACM Comput. Surv. doi: 10.1145/331499.331504 – start-page: 91 year: 1998 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0340 – year: 2019 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0580 article-title: Development of boron oxide potentials for computer simulations of multicomponent oxide glasses publication-title: J. Am. Ceram. Soc. doi: 10.1111/jace.16082 – year: 2000 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0255 – volume: 121 start-page: 9063 year: 2017 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0430 article-title: Dissolution kinetics of hot compressed oxide glasses publication-title: J. Phys. Chem. B doi: 10.1021/acs.jpcb.7b04535 – ident: 10.1016/j.jnoncrysol.2019.04.039_bb0230 – volume: 1 start-page: 6 year: 2013 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0330 article-title: Review on determining number of cluster in K-means clustering publication-title: Int. J. Adv. Res. Comput. Sci. Manage. Stud. – volume: 1902 start-page: 1 year: 2019 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0550 article-title: Machine learning Forcefield for silicate glasses publication-title: Cond-Mat – volume: 78 start-page: 105 year: 2003 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0445 article-title: Elastic moduli of low-silica calcium alumino-silicate glasses publication-title: Mater. Chem. Phys. doi: 10.1016/S0254-0584(02)00331-0 – volume: 67 start-page: 301 year: 2005 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0285 article-title: Regularization and variable selection via the elastic net publication-title: J. R. Stat. Soc. doi: 10.1111/j.1467-9868.2005.00503.x – ident: 10.1016/j.jnoncrysol.2019.04.039_bb0320 – volume: 2 start-page: 349 year: 2009 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0305 article-title: Multi-class AdaBoost publication-title: Stat. Interface. doi: 10.4310/SII.2009.v2.n3.a8 – volume: 5 start-page: 313 year: 2014 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0010 article-title: Two centuries of glass research: historical trends, current status, and grand challenges for the future publication-title: Int. J. Appl. Glas. Sci. doi: 10.1111/ijag.12087 – year: 2015 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0190 – year: 2014 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0100 – volume: 29 start-page: 31 year: 1996 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0235 article-title: Artificial neural networks: a tutorial publication-title: Computer – start-page: 87 year: 2015 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0080 article-title: Challenges in Modeling mixed ionic-covalent glass formers – volume: 10 start-page: 8 year: 1993 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0125 article-title: Progress in supervised neural networks publication-title: IEEE Signal Process. Mag. doi: 10.1109/79.180705 – volume: 49 start-page: 41 year: 1999 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0175 article-title: Confidence intervals for nonlinear regression extrapolation publication-title: Chemom. Intell. Lab. Syst. doi: 10.1016/S0169-7439(99)00026-X – year: 2008 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0220 – year: 1990 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0210 – volume: 124 start-page: 323 year: 2016 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0595 article-title: Developing empirical potentials from ab initio simulations: the case of amorphous silica publication-title: Comput. Mater. Sci. doi: 10.1016/j.commatsci.2016.07.041 – volume: 90 start-page: 31 year: 2011 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0040 article-title: Topological constraint theory of glass publication-title: Am. Ceram. Soc. Bull. – volume: vol. 2 start-page: 18 year: 2002 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0245 – volume: 105 year: 2010 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0050 article-title: Prediction of glass hardness using temperature-dependent constraint theory publication-title: Phys. Rev. Lett. doi: 10.1103/PhysRevLett.105.115503 – volume: vol. 2 start-page: 893 year: 1979 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0115 article-title: An automobile with artificial intelligence – volume: 61 start-page: 27 year: 1978 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0450 article-title: Effect of composition on the mechanical properties of aluminosilicate and borosilicate glasses publication-title: J. Am. Ceram. Soc. doi: 10.1111/j.1151-2916.1978.tb09222.x – volume: 1901 start-page: 1 year: 2019 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0385 article-title: Prediction of silicate Glasses' stiffness by high-throughput molecular dynamics simulations and machine learning publication-title: Cond-Mat, Phys. – ident: 10.1016/j.jnoncrysol.2019.04.039_bb0105 – volume: 82 year: 2008 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0600 article-title: New fitting scheme to obtain effective potential from car-Parrinello molecular-dynamics simulations: application to silica publication-title: EPL doi: 10.1209/0295-5075/82/17001 – year: 2012 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0135 – year: 2013 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0500 – volume: 121 start-page: 1139 year: 2017 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0425 article-title: Correlating the network topology of oxide glasses with their chemical durability publication-title: J. Phys. Chem. B doi: 10.1021/acs.jpcb.6b11371 – volume: 65 start-page: 2991 year: 1989 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0435 article-title: Generalized expressions for the calculation of elastic constants by computer simulation publication-title: J. Appl. Phys. doi: 10.1063/1.342716 – volume: 177 start-page: 7 year: 2007 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0150 article-title: Error bars in experimental biology publication-title: J. Cell Biol. doi: 10.1083/jcb.200611141 – year: 2005 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0070 – ident: 10.1016/j.jnoncrysol.2019.04.039_bb0605 – volume: 358 start-page: 1033 year: 2017 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0510 article-title: Structure-property relationships from universal signatures of plasticity in disordered solids publication-title: Science doi: 10.1126/science.aai8830 – volume: 401 start-page: 788 year: 1999 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0360 article-title: Learning the parts of objects by non-negative matrix factorization publication-title: Nature doi: 10.1038/44565 – volume: 12 start-page: 55 year: 1970 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0295 article-title: Ridge regression: biased estimation for nonorthogonal problems publication-title: Technometrics doi: 10.1080/00401706.1970.10488634 – volume: 159 start-page: 249 year: 2018 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0185 article-title: Predicting glass transition temperatures using neural networks publication-title: Acta Mater. doi: 10.1016/j.actamat.2018.08.022 – year: 2006 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0120 – volume: 5 start-page: 1089 year: 2004 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0280 article-title: No unbiased estimator of the variance of K-fold cross-validation publication-title: J. Mach. Learn. Res. – year: 2015 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0065 – volume: 149 start-page: 131 year: 2003 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0165 article-title: Embodied artificial intelligence publication-title: Artificial Intelligence doi: 10.1016/S0004-3702(03)00055-9 – volume: 65 start-page: 680 year: 2001 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0465 article-title: Equation for estimating the thermal diffusivity, specific heat and thermal conductivity of oxide glasses publication-title: J. Jpn. Inst. Metals doi: 10.2320/jinstmet1952.65.8_680 – volume: 46 start-page: 175 year: 1992 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0215 article-title: An introduction to kernel and nearest-neighbor nonparametric regression publication-title: Am. Stat. doi: 10.1080/00031305.1992.10475879 – volume: 70 start-page: 139 year: 2013 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0395 article-title: General models for estimating daily global solar radiation for different solar radiation zones in mainland China publication-title: Energy Convers. Manag. doi: 10.1016/j.enconman.2013.03.004 – start-page: 1 year: 2018 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0090 article-title: Mechanical and compositional Design of High-Strength Corning Gorilla® glass – volume: 5 start-page: 2 year: 2014 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0005 article-title: Glass science in the United States: current status and future directions publication-title: Int. J. Appl. Glas. Sci. doi: 10.1111/ijag.12058 – volume: 2 year: 2018 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0390 article-title: Impacts of glass composition, pH, and temperature on glass forward dissolution rate publication-title: NPJ Mater. Degradation – start-page: 1539 year: 1993 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0495 article-title: Material Design of Glasses Based on database – INTERGLAD – volume: 36 start-page: 451 year: 2003 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0325 article-title: The global k-means clustering algorithm publication-title: Pattern Recogn. doi: 10.1016/S0031-3203(02)00060-2 – start-page: 372 year: 2014 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0345 article-title: A survey of feature selection and feature extraction techniques in machine learning – year: 1990 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0225 – volume: 28 start-page: 4267 year: 2016 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0055 article-title: Accelerating the design of functional glasses through modeling publication-title: Chem. Mater. doi: 10.1021/acs.chemmater.6b01054 – year: 2002 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0270 article-title: Accuracy vs. simplicity: a complex trade-off publication-title: SSRN Electron. J. doi: 10.2139/ssrn.332382 – volume: 29 start-page: 1189 year: 2001 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0250 article-title: Greedy function approximation: a gradient boosting machine publication-title: Ann. Stat. doi: 10.1214/aos/1013203451 – volume: 19 start-page: 227 year: 1984 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0455 article-title: Proprietes elastiques et indices de refraction de verres azotes publication-title: Mater. Res. Bull. doi: 10.1016/0025-5408(84)90094-1 – volume: vol. 6 start-page: 303 year: 1994 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0265 article-title: Optimal stopping and effective machine complexity in learning – volume: 42 start-page: 59 year: 1988 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0380 article-title: Thirteen ways to look at the correlation coefficient publication-title: Am. Stat. doi: 10.1080/00031305.1988.10475524 – volume: 114 year: 2015 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0520 article-title: Rigidity transition in materials: hardness is driven by weak atomic constraints publication-title: Phys. Rev. Lett. doi: 10.1103/PhysRevLett.114.125502 – volume: 514 start-page: 15 year: 2019 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0060 article-title: Prediction of the Young's modulus of silicate glasses by topological constraint theory publication-title: J. Non-Cryst. Solids doi: 10.1016/j.jnoncrysol.2019.03.033 – volume: 68 start-page: 155 year: 1985 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0505 article-title: Formation and properties of calcium Aluminosilicate glasses publication-title: J. Am. Ceram. Soc. doi: 10.1111/j.1151-2916.1985.tb09656.x – year: 2018 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0025 article-title: Topological optimization of cementitious binders: advances and challenges publication-title: Cem. Concr. Compos. – volume: 32 start-page: 2627 year: 1998 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0300 article-title: Artificial neural networks (the multilayer perceptron)—a review of applications in the atmospheric sciences publication-title: Atmos. Environ. doi: 10.1016/S1352-2310(97)00447-0 – year: 2012 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0195 – volume: 97 year: 2018 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0565 article-title: Development of a machine learning potential for graphene publication-title: Phys. Rev. B doi: 10.1103/PhysRevB.97.054303 – volume: 16 start-page: 645 year: 2005 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0310 article-title: Survey of clustering algorithms publication-title: IEEE Trans. Neural Netw. doi: 10.1109/TNN.2005.845141 – volume: 159 start-page: 95 year: 2019 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0035 article-title: Deciphering the atomic genome of glasses by topological constraint theory and molecular dynamics: a review publication-title: Comput. Mater. Sci. doi: 10.1016/j.commatsci.2018.12.004 – volume: 1 start-page: 41 year: 1967 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0200 article-title: Piecewise-polynomial (spline) interpolation publication-title: Mathemat. Notes Acad. Sci. USSR – volume: 353 start-page: 263 year: 2007 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0375 article-title: Solubility of glasses in the system P2O5–CaO–MgO–Na2O–TiO2: experimental and modeling using artificial neural networks publication-title: J. Non-Cryst. Solids doi: 10.1016/j.jnoncrysol.2006.12.005 – volume: vol. 26 start-page: 97 year: 2014 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0110 article-title: Data mining with big data – year: 2010 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0095 – volume: 4 start-page: 417 year: 1990 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0155 article-title: Machine learning publication-title: Ann. Rev. Comput. Sci. doi: 10.1146/annurev.cs.04.060190.002221 – volume: 39–40 start-page: 145 year: 2008 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0160 article-title: Glass property databases: their history, present state, and prospects for further development publication-title: Adv. Mater. Res. – year: 1993 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0020 – volume: 4 year: 2017 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0515 article-title: Experimental and theoretical investigation of the elastic moduli of silicate glasses and crystals publication-title: Front. Mater. doi: 10.3389/fmats.2017.00002 – start-page: 157 year: 2015 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0075 article-title: Challenges in molecular dynamics simulations of multicomponent oxide glasses – volume: 1 start-page: 295 year: 1989 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0140 article-title: Unsupervised learning publication-title: Neural Comput. doi: 10.1162/neco.1989.1.3.295 – volume: 148 year: 2018 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0585 article-title: New optimization scheme to obtain interaction potentials for oxide glasses publication-title: J. Chem. Phys. doi: 10.1063/1.5023707 – ident: 10.1016/j.jnoncrysol.2019.04.039_bb0370 – volume: 100 start-page: 5521 year: 2017 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0405 article-title: Topological controls on the dissolution kinetics of glassy aluminosilicates publication-title: J. Am. Ceram. Soc. doi: 10.1111/jace.15122 – volume: 22 start-page: 58 year: 2018 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0030 article-title: Decoding the glass genome publication-title: Curr. Opinion Solid State Mater. Sci. doi: 10.1016/j.cossms.2017.09.001 – volume: 114 start-page: 10601 year: 2017 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0540 article-title: Disconnecting structure and dynamics in glassy thin films publication-title: PNAS doi: 10.1073/pnas.1703927114 – start-page: 45 year: 2016 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0610 article-title: Bayesian optimization for materials design – volume: 8 year: 2018 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0555 article-title: Machine learning a general-purpose interatomic potential for silicon publication-title: Phys. Rev. X – volume: 108 start-page: 187 year: 1989 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0475 article-title: Elastic moduli of oxynitride glasses: extension of Makishima and Mackenzie's theory publication-title: J. Non-Cryst. Solids doi: 10.1016/0022-3093(89)90582-6 – volume: 487 start-page: 37 year: 2018 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0180 article-title: Predicting the dissolution kinetics of silicate glasses using machine learning publication-title: J. Non-Cryst. Solids doi: 10.1016/j.jnoncrysol.2018.02.023 – volume: 13 start-page: 703 year: 2016 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0275 article-title: Model selection and overfitting: points of significance publication-title: Nat. Methods doi: 10.1038/nmeth.3968 – volume: 32 start-page: 4434 year: 2016 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0410 article-title: Topological control on Silicates' dissolution kinetics publication-title: Langmuir doi: 10.1021/acs.langmuir.6b00359 – volume: 105 start-page: 17 year: 2014 ident: 10.1016/j.jnoncrysol.2019.04.039_bb0335 article-title: EBK-means: a clustering technique based on elbow method and K-means in WSN publication-title: Int. J. Comput. Appl. |
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| Snippet | The design of new glasses is often plagued by poorly efficient Edisonian “trial-and-error” discovery approaches. As an alternative route, the Materials Genome... |
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| SubjectTerms | Artificial neuron network Bayesian optimization Composition-property relationship Molecular dynamics simulation Structural signature |
| Title | Machine learning for glass science and engineering: A review |
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