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1.
1.P. Larsen and M. Von Ins, Scientometrics 84, 575 (2010).
http://dx.doi.org/10.1007/s11192-010-0202-z
2.
2.R. D. Chirico, M. Frenkel, J. W. Magee, V. V. Diky, C. D. Muzny, A. F. Kazakov, K. Kroenlein, I. Abdulagatov, G. R. Hardin, W. E. Acree, J. F. Brenneke, P. L. Brown, P. T. Cummings, T. W. de Loos, D. G. Friend, A. R. H. Goodwin, L. D. Hansen, W. M. Haynes, N. Koga, A. Mandelis, K. N. Marsh, P. M. Mathias, C. McCabe, J. P. O’Connell, A. Pádua, V. Rives, C. Schick, J. P. M. Trusler, S. Vyazovkin, R. D. Weir, and J. Wu, J. Chem. Eng. Data 58, 2699 (2013).
http://dx.doi.org/10.1021/je400569s
3.
3.S. Curtarolo, G. L. W. Hart, M. B. Nardelli, N. Mingo, S. Sanvito, and O. Levy, Nat. Mater. 12, 191 (2013).
http://dx.doi.org/10.1038/nmat3568
4.
4.L. Q. Xing and W. G. J. Bunk, Giesserei 84, 20 (1997).
5.
5.D. Mu, P. Nan, J. Wang, G. Song, and W. Luo, JOM 67, 1659 (2015).
http://dx.doi.org/10.1007/s11837-015-1463-z
6.
6.O. D. Sherby and J. Wadsworth, J. Mater. Process. Technol. 117, 347 (2001).
http://dx.doi.org/10.1016/S0924-0136(01)00794-4
7.
7.G. B. Olson, Science 288, 993 (2000).
http://dx.doi.org/10.1126/science.288.5468.993
8.
8.J. W. Gibbs, Trans. Conn. Acad. Arts Sci. 2, 382 (1873).
9.
9.J. W. Gibbs, Trans. Conn. Acad. Arts Sci. 3, 108 (1876).
10.
10.J. W. Gibbs, Trans. Conn. Acad. Arts Sci. 3, 343 (1879).
11.
11.W. Hume-Rothery, J. Inst. Met. 35, 319 (1926).
12.
12.G. B. Olson, Science 277, 1237 (1997).
http://dx.doi.org/10.1126/science.277.5330.1237
13.
13.J. Van Laar, Z. Phys. Chem. 63, 216 (1908).
14.
14.J. Van Laar, Z. Phys. Chem. 64, 257 (1908).
15.
15.L. Kaufman and H. Bernstein, Computer Calculation of Phase Diagrams with Special Reference to Refractory Metals (Academic Press, Inc, 1970).
16.
16.G. B. Olson and C. J. Kuehmann, Scr. Mater. 70, 25 (2014).
http://dx.doi.org/10.1016/j.scriptamat.2013.08.032
17.
17.W. Xiong and G. B. Olson, MRS Bull. 40, 1035 (2015).
http://dx.doi.org/10.1557/mrs.2015.273
18.
18.Y.-P. Yang, J. Mater. Eng. Perform. 24, 202 (2014).
http://dx.doi.org/10.1007/s11665-014-1260-9
19.
19.G. Gou, Y. Yang, and H. Chen, Engineering 06, 936 (2014).
http://dx.doi.org/10.4236/eng.2014.613085
20.
20.G. Casalino, M. Mortello, N. Contuzzi, and F. M. C. Minutolo, Procedia CIRP 33, 434 (2015).
http://dx.doi.org/10.1016/j.procir.2015.06.099
21.
21.J. Orsborn, R. E. A. Williams, and H. Fraser, Microsc. Microanal. 21, 1089 (2015).
http://dx.doi.org/10.1017/S1431927615006236
22.
22.R. Rettig, N. C. Ritter, H. E. Helmer, S. Neumeier, and R. F. Singer, Modell. Simul. Mater. Sci. Eng. 23, 035004 (2015).
http://dx.doi.org/10.1088/0965-0393/23/3/035004
23.
23.J. Hattrick-Simpers, C. Wen, and J. Lauterbach, Catal. Lett. 145, 290 (2014).
http://dx.doi.org/10.1007/s10562-014-1442-y
24.
24.C. E. Campbell and G. B. Olson, J. Comput.-Aided Mater. Des. 7, 145 (2000).
http://dx.doi.org/10.1023/A:1011808225838
25.
25.S. Ding, Y. Liu, Y. Li, Z. Liu, S. Sohn, F. J. Walker, and J. Schroers, Nat. Mater. 13, 494 (2014).
http://dx.doi.org/10.1038/nmat3939
26.
26.A. Ludwig, R. Zarnetta, S. Hamann, A. Savan, and S. Thienhaus, Int. J. Mater. Res. 99, 1144 (2008).
http://dx.doi.org/10.3139/146.101746
27.
27.D. B. Miracle, Mater. Sci. Technol. 31, 1142 (2015).
http://dx.doi.org/10.1179/1743284714Y.0000000749
28.
28.S. V. Kalinin, B. G. Sumpter, and R. K. Archibald, Nat. Mater. 14, 973 (2015).
http://dx.doi.org/10.1038/nmat4395
29.
29.F. De Geuser, M. J. Styles, C. R. Hutchinson, and A. Deschamps, Acta Mater. 101, 1 (2015).
http://dx.doi.org/10.1016/j.actamat.2015.08.061
30.
30.M. O. McLinden, A. F. Kazakov, J. S. Brown, and P. A. Domanski, Int. J. Refrig. 38, 80 (2014).
http://dx.doi.org/10.1016/j.ijrefrig.2013.09.032
31.
31.A. F. Kazakov, M. O. McLinden, and M. Frenkel, Ind. Eng. Chem. Res. 51, 12537 (2012).
http://dx.doi.org/10.1021/ie3016126
32.
32.R. Reed, T. Tao, and N. Warnken, Acta Mater. 57, 5898 (2009).
http://dx.doi.org/10.1016/j.actamat.2009.08.018
33.
33.F. Tancret, Modell. Simul. Mater. Sci. Eng. 20, 1 (2012).
http://dx.doi.org/10.1088/0965-0393/20/4/045012
34.
34.H. K. D. H. Bhadeshia and R. Honeycombe, Steels: Microstructure and Properties (Butterworth-Heinemann, 2011).
35.
35.H. K. D. H. Bhadeshia, Stat. Anal. Data Min. 1, 296 (2009).
http://dx.doi.org/10.1002/sam.10018
36.
36.H. K. D. H. Bhadeshia, ISIJ Int. 39, 966 (1999).
http://dx.doi.org/10.2355/isijinternational.39.966
37.
37.P. Frazier and J. Wang, in Information Science for Materials Discovery and Design, edited byT. Lookman, F. J. Alexander, and K. Rajan (Springer International Publishing, Cham, 2016), pp. 45-75.
38.
38.W. Carande, A. Kazakov, C. D. Muzny, and M. Frenkel, J. Chem. Eng. Data 60, 1377 (2015).
http://dx.doi.org/10.1021/je501093v
39.
39.E. Bélisle, Z. Huang, and A. Gheribi, Databases Theory and Applications (Springer International Publishing, 2014), pp. 38-49.
40.
40.D. L. McDowell and G. B. Olson, in Scientific Modeling and Simulations, edited by S. Yip and T. Diaz de la Rubia (Springer, Netherlands, 2009), pp. 207-240.
41.
41.Z.-K. Liu and D. McDowell, Integr. Mater. Manuf. Innovations 3, 1 (2014).
http://dx.doi.org/10.1186/s40192-014-0028-2
42.
42.A. Agrawal, P. D. Deshpande, A. Cecen, G. P. Basavarsu, A. N. Choudhary, and S. R. Kalidindi, Integr. Mater. Manuf. Innovations 3, 8 (2014).
http://dx.doi.org/10.1186/2193-9772-3-8
43.
43.K. Kroenlein, V. V. Diky, C. D. Muzny, J. W. Magee, and M. Frenkel, NIST Standard Reference Database 171, NIST, 2015.
44.
44.V. V. Diky, R. D. Chirico, R. Wilhoit, Q. Dong, and M. Frenkel, J. Chem. Inf. Model. 43, 15 (2003).
http://dx.doi.org/10.1021/ci025534t
45.
45.M. Frenkel, V. V. Diky, R. D. Chirico, R. N. Goldberg, H. Heerklotz, J. E. Ladbury, D. P. Remeta, J. H. Dymond, A. R. H. Goodwin, K. N. Marsh, W. A. Wakeham, S. E. Stein, P. L. Brown, E. Königsberger, P. A. Williams, D. P. Remata, J. H. Dymond, A. R. H. Goodwin, K. N. Marsh, W. A. Wakeham, S. E. Stein, P. L. Brown, E. Konigsberger, and P. A. Williams, J. Chem. Eng. Data 56, 307 (2011).
http://dx.doi.org/10.1021/je100999j
46.
46.M. Frenkel, R. D. Chirico, V. V. Diky, P. L. Brown, J. H. Dymond, R. N. Goldberg, A. R. H. Goodwin, H. Heerklotz, E. Konigsberger, J. E. Ladbury, K. N. Marsh, D. P. Remata, S. E. Stein, W. A. Wakeham, and P. A. Williams, Pure Appl. Chem. 83, 1937 (2011).
http://dx.doi.org/10.1351/pac-rec-11-05-01
47.
47.V. V. Diky, R. D. Chirico, C. D. Muzny, A. F. Kazakov, K. Kroenlein, J. W. Magee, I. Abdulagatov, and M. Frenkel, J. Chem. Inf. Model. 53, 3418 (2013).
http://dx.doi.org/10.1021/ci4005699
48.
48.K. Kroenlein, C. D. Muzny, V. V. Diky, A. F. Kazakov, R. D. Chirico, J. W. Magee, I. Abdulagatov, and M. Frenkel, J. Chem. Inf. Model. 51, 1506 (2011).
http://dx.doi.org/10.1021/ci200096q
49.
49.M. Frenkel, R. D. Chirico, V. V. Diky, X. Yan, Q. Dong, and C. D. Muzny, J. Chem. Inf. Model. 45, 816 (2005).
http://dx.doi.org/10.1021/ci050067b
50.
50.V. V. Diky, C. D. Muzny, E. W. Lemmon, R. D. Chirico, and M. Frenkel, J. Chem. Inf. Model. 47, 1713 (2007).
http://dx.doi.org/10.1021/ci700071t
51.
51.R. D. Chirico, T. W. de Loos, J. Gmehling, A. R. H. Goodwin, S. Gupta, W. M. Haynes, K. N. Marsh, V. Rives, J. D. Olson, C. Spencer, J. F. Brennecke, and J. P. M. Trusler, Pure Appl. Chem. 84, 1785 (2012).
http://dx.doi.org/10.1351/pac-rec-11-05-02
52.
52.R. N. Hajra, R. Subramanian, H. Tripathy, A. K. Rai, and S. Saibaba, Thermochim. Acta 620, 40 (2015).
http://dx.doi.org/10.1016/j.tca.2015.10.002
53.
53.M. Premović, D. Minić, D. Manasijević, V. Ćosović, D. Živković, and I. Dervišević, Thermochim. Acta 609, 61 (2015).
http://dx.doi.org/10.1016/j.tca.2015.02.022
54.
54.R. N. Abdullaev and Y. M. Kozlovskii, Int. J. Thermophys. 36, 603 (2015).
http://dx.doi.org/10.1007/s10765-015-1839-x
55.
55.W. Zhai and B. Wei, J. Chem. Thermodyn. 86, 57 (2015).
http://dx.doi.org/10.1016/j.jct.2015.02.021
56.
56.F. Galiegue, K. Zyp, and G. Court, JSON Schema Core Definition Terminology Draft, 2013, http://tools.ietf.org/html/draft.
57.
57.D. C. Fallside and P. Walmsley, XML Schema Part 0 Primer Second Edition, W3C Recommendation, 2004, http://www.w3.org/TR/xmlschema.
58.
58.ThermoML Opener A Tool Direct Viewing ThermoML Files, 2016, http://trc.nist.gov/ThermoML_ Opener.html.
59.
59.K. A. Beauchamp, J. M. Behr, A. S. Rustenburg, C. I. Bayly, K. Kroenlein, and J. D. Chodera, J. Phys. Chem. B 119, 12912 (2015).
http://dx.doi.org/10.1021/acs.jpcb.5b06703
60.
60.K. A. Beauchamp, J. M. Behr, A. S. Rustenburg, C. I. Bayly, K. Kroenlein, and J. D. Chodera, ThermoPyL, 2016, https://github.com/choderalab/ThermoPyL.
61.
61.V. V. Diky, R. D. Chirico, A. F. Kazakov, C. D. Muzny, and M. Frenkel, J. Chem. Inf. Model. 49, 503 (2009).
http://dx.doi.org/10.1021/ci800345e
62.
62.V. V. Diky, R. D. Chirico, A. F. Kazakov, C. D. Muzny, and M. Frenkel, J. Chem. Inf. Model. 49, 2883 (2009).
http://dx.doi.org/10.1021/ci900340k
63.
63.V. V. Diky, R. D. Chirico, A. F. Kazakov, C. D. Muzny, J. W. Magee, I. Abdulagatov, J. W. Kang, K. Kroenlein, and M. Frenkel, J. Chem. Inf. Model. 51, 181 (2011).
http://dx.doi.org/10.1021/ci100373t
64.
64.V. Diky, R. D. Chirico, C. D. Muzny, A. F. Kazakov, K. Kroenlein, J. W. Magee, I. Abdulagatov, J. W. Kang, and M. Frenkel, J. Chem. Inf. Model. 52, 260 (2012).
http://dx.doi.org/10.1021/ci200456w
65.
65.V. V. Diky, R. D. Chirico, C. D. Muzny, A. F. Kazakov, K. Kroenlein, J. W. Magee, I. Abdulagatov, J. W. Kang, R. Gani, and M. Frenkel, J. Chem. Inf. Model. 53, 249 (2013).
http://dx.doi.org/10.1021/ci300470t
66.
66. Commercial products are identified only for purposes of technical description, and this implies no endorsement by NIST. Other products might be found that work equally well or better for the applications described.
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/content/aip/journal/aplmater/4/5/10.1063/1.4942634
2016-03-07
2016-12-07

Abstract

Computational capability has enabled materials design to evolve from trial-and-error towards more informed methodologies that require large amounts of data. Expert-designed tools and their underlying databases facilitate modern-day high throughput computational methods. Standard data formats and communication standards increase the impact of traditional data, and applying these technologies to a high throughput experimental design provides dense, targeted materials data that are valuable for material discovery. Integrated computational materials engineering requires both experimentally and computationally derived data. Harvesting these comprehensively requires different methods of varying degrees of automation to accommodate variety and volume. Issues of data quality persist independent of type.

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