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What do crystals nucleate on? What is the microscopic mechanism? How can we model nucleation?

Published online by Cambridge University Press:  04 May 2016

Richard Sear*
Affiliation:
Department of Physics, University of Surrey, UK; r.sear@surrey.ac.uk
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Abstract

Crystallization is a key process in materials science, and most materials are made by processes that involve crystallization. Crystallization starts with nucleation, a process that is poorly understood for two reasons. First, nucleation occurs in contact with the typically uncharacterized surface of an impurity in the system. Second, we typically have little direct data on the microscopic mechanism of nucleation. We have a theory called classical nucleation, but when a simple application of the theory disagrees with experiment, it is unclear whether the theory is wrong, or if some feature of the surface is missing from the model. This article briefly reviews recent work on nucleation and its mechanisms. We are not alone in working with a stochastic process whose underlying mechanism is poorly understood. Engineers often have this problem and have developed powerful statistical models for stochastic processes. Surprisingly, even though they are sometimes used by materials scientists in different contexts, these are not used to model and predict nucleation behavior. We could advance the field with their use.

Type
Research Article
Copyright
Copyright © Materials Research Society 2016 

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References

Pruppacher, H.R., Klett, J.D., Microphysics of Clouds and Precipitation (Reidel Publishing, Dordrecht, The Netherlands, 1978).Google Scholar
Murray, B.J., O’Sullivan, D., Atkinson, J.D., Webb, M.E., Chem. Soc. Rev. 41, 6519 (2012).Google Scholar
Ashby, M.F., Jones, D.R.H., Engineering Materials, 4th ed. (Butterworth- Heinemann, Oxford, 2011, vol. 1).Google Scholar
Chawla, K., Composite Materials: Science and Engineering, 3rd ed. (Springer, London, 2012).Google Scholar
Gurganus, C.W., Charnawskas, J.C., Kostinski, A.B., Shaw, R.A., Phys. Rev. Lett. 113, 235701 (2014).Google Scholar
Campbell, J.M., Meldrum, F.C., Christenson, H.K., Cryst. Growth Des. 13, 1915 (2013).Google Scholar
Diao, Y., Helgeson, M.E., Myerson, A.S., Hatton, T.A., Doyle, P.S., Trout, B.L., J. Am. Chem. Soc. 133, 3756 (2011).Google Scholar
Gurganus, C., Kostinski, A.B., Shaw, R.A., J. Phys. Chem. C 117, 6195 (2013).Google Scholar
Parmar, A.S., Gottschall, P.E., Muschol, M., Biophys. Chem. 129, 224 (2007).Google Scholar
Akella, S.V., Mowitz, A., Heymann, M., Fraden, S., Cryst. Growth Des. 14, 4487 (2014).Google Scholar
Tan, L., Davis, R.M., Myerson, A.S., Trout, B.L., Cryst. Growth Des. 15, 2176 (2015).Google Scholar
Page, A.J., Sear, R.P., J. Am. Chem. Soc. 131, 17550 (2009).Google Scholar
Auer, S., Frenkel, D., J. Chem. Phys. 120, 3015 (2004).Google Scholar
Valeriani, C., Sanz, E., Frenkel, D., J. Chem. Phys. 122, 194501 (2005).Google Scholar
Filion, L., Ni, R., Frenkel, D., Dijkstra, M., J. Chem. Phys. 134, 134901 (2011).Google Scholar
Debenedetti, P.G., Metastable Liquids (Princeton University Press, Princeton, NJ, 1996).Google Scholar
Sear, R.P., J. Phys. Condens. Matter 19, 033101 (2007).Google Scholar
Sear, R.P., Int. Mat. Rev. 57, 328 (2012).Google Scholar
Sear, R.P., Phys. Rev. E 70, 021605 (2004).Google Scholar
Herbert, R.J., Murray, B.J., Whale, T.F., Dobbie, S.J., Atkinson, J.D., Atmos. Chem. Phys. 14, 8501 (2014).Google Scholar
Schwind, M., Zhdanov, V.P., Zoric, I., Kasemo, B., Nano Lett. 10, 931 (2010).Google Scholar
Laval, P., Crombez, A., Salmon, J.-B., Langmuir 25, 1836 (2009).Google Scholar
Little, L.J., Sear, R.P., Keddie, J.L., Cryst. Growth Des. 15, 5345 (2015).Google Scholar
Nielsen, M.H., Aloni, S., De Yoreo, J.J., Science 345, 1158 (2014).Google Scholar
Baumgartner, J., Dey, A., Bomans, P.H.H., Coadou, C.L., Fratzl, P., Sommerdijk, N.A.J.M., Faivre, D., Nat. Mater. 12, 310 (2013).Google Scholar
Turnbull, D., J. Chem. Phys. 18, 198 (1950).Google Scholar
Kuhs, M., Zeglinski, J., Rasmuson, O.C., Cryst. Growth Des. 14, 905 (2014).Google Scholar
Sear, R.P., CrystEngCom 16, 6506 (2014).Google Scholar
Sear, R.P., Phys. Rev. E 89, 022405 (2014).Google Scholar
Proschan, F., Technometrics, 5 (3), 375 (1963).Google Scholar
Lee, E.T., Statistical Methods for Survival Data Analysis, 2nd ed. (Wiley, Hoboken, NJ, 1992).Google Scholar
Cox, D.R., Oakes, D., Analysis of Survival Data (Chapman and Hall, London, 1984).Google Scholar
Levine, J., “Statistical Explanation of Spontaneous Freezing of Water Droplets,” National Advisory Committee for Aeronautics (NACA) Tech. Note 2234 (1950).Google Scholar
Sear, R.P., Atmos. Chem. Phys. 13, 7215 (2013).Google Scholar
Dorsch, R.G., Hacker, P.T., “Photomicrographic Investigation of Spontaneous Freezing Temperatures of Supercooled Water Droplets,” National Advisory Committee for Aeronautics (NACA) Tech. Note 2142 (1950).Google Scholar
Castillo, E., Extreme Value Theory in Engineering (Academic Press, San Diego, 1988).Google Scholar
Salam, A., Lohmann, U., Lesins, G., Atmos. Chem. Phys. 7, 3923 (2007).Google Scholar
Moore, E.B., Molinero, V., Phys. Chem. Chem. Phys. 13, 20008 (2011).Google Scholar