On the Effect of Nucleation Undercooling on Phase Transformation Kinetics
Source abstract
Abstract
We carry out an extensive comparison between Johnson-Mehl-Avrami-Kolmogorov (JMAK) theory of first-order phase transformation kinetics and phase-field (PF) results of a benchmark problem on nucleation. To address the stochasticity of the problem, several hundreds of simulations are performed to establish a comprehensive, statistically-significant analysis of the coincidences and discrepancies between PF and JMAK transformation kinetics. We find that PF predictions are in excellent agreement with both classical nucleation theory and JMAK theory, as long as the original assumptions of the latter are appropriately reproduced - in particular, the constant nucleation and growth rates in an infinite domain. When deviating from these assumptions, PF results are at odds with JMAK theory. In particular, we observe that the size of the initial particle radius $r_0$ relative to the critical nucleation radius $r^*$ has a significant effect on the rate of transformation. While PF and JMAK agree when $r_0$ is sufficiently higher than $r^*$, the duration of initial transient growth stage of a particle, before it reaches a steady growth velocity, increases as $r_0/r^*\to 1$. This incubation time has a significant effect on the overall kinetics, e.g. on the Avrami exponent of the multi-particle simulations. In contrast, for the considered conditions and parameters, the effect of interface curvature upon transformation kinetics - in particular negative curvature regions appearing during particle impingement, present in PF but absent in JMAK theory - appears to be minor compared to that of $r_0/r^*$. We argue that rigorous benchmarking of phase-field models of stochastic processes (e.g. nucleation) need sufficient statistical data in order to make rigorous comparisons against ground truth theories. In these problems, analysis of probability distributions is clearly preferable to a deterministic approach.
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Research context
OpenAlex topics: Solidification and crystal growth phenomena · nanoparticles nucleation surface interactions · Microstructure and Mechanical Properties of Steels
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References (25)
Show source-provided references
1. Kolmogorov AN (1937) A study of the equation of diffusion with increase in the quantity of matter, and its application to a biological problem. Mosc Univ Bull Math 1:1–25
2. Avrami M (1939) Kinetics of phase change. I General theory. J Chem Phys 7(12):1103–1112. https://doi.org/10.1063/1.175038010.1063/1.1750380 ↗
3. Avrami M (1940) Kinetics of phase change. II Transformation-time relations for random distribution of nuclei. J Chem Phys 8(2):212–224. https://doi.org/10.1063/1.175063110.1063/1.1750631 ↗
4. Avrami M (1941) Granulation, phase change, and microstructure kinetics of phase change. III. J Chem Phys 9(2):177–184. https://doi.org/10.1063/1.175087210.1063/1.1750872 ↗
5. Johnson WA, Mehl RF (1939) Reaction kinetics in processes of nucleation and growth. American Institute of Mining and Metallurgical Engineers Technical Publication No. 1089
6. Christian JW (2002) The theory of transformations in metals and alloys, 2nd edn. Pergamon, Oxford
7. Cahn J, Hagel WC (1962) Theory of the pearlite reaction. In: Zakay VF, Aaronson HI (eds) Decomposition of austenite by diffusional processes. Wiley, New York, pp 131–196
8. Avramov I (2007) Kinetics of distribution of infections in networks. Physica A 379(2):615–620. https://doi.org/10.1016/j.physa.2007.02.00210.1016/j.physa.2007.02.002 ↗
9. Gránásy L, Rátkai L, Szállás A, Korbuly B, Tóth GI, Környei L, Pusztai T (2014) Phase-field modeling of polycrystalline solidification: from needle crystals to spherulites—a review. Metall Mater Trans A 45(4):1694–1719. https://doi.org/10.1007/s11661-013-1988-010.1007/s11661-013-1988-0 ↗
10. Jackson JL (1974) Dynamics of expanding inhibitory fields. Science 183(4123):445–446. https://doi.org/10.1126/science.183.4123.44510.1126/science.183.4123.445 ↗
11. Cahn JW (1996) The time cone method for nucleation and growth kinetics on a finite domain. Mater Res Soc Symp Proc 398:425–43710.1557/PROC-398-425 ↗
12. Balluffi RW, Allen SM, Carter WC (2005) Kinetics of materials. Wiley, Hoboken10.1002/0471749311 ↗
13. Chen L-Q (2002) Phase-field models for microstructure evolution. Annu Rev Mater Res 32(1):113–140. https://doi.org/10.1146/annurev.matsci.32.112001.13204110.1146/annurev.matsci.32.112001.132041 ↗
14. Boettinger WJ, Warren JA, Beckermann C, Karma A (2002) Phase-field simulation of solidification. Annu Rev Mater Res 32(1):163–194. https://doi.org/10.1146/annurev.matsci.32.101901.15580310.1146/annurev.matsci.32.101901.155803 ↗
15. Moelans N, Blanpain B, Wollants P (2008) An introduction to phase-field modeling of microstructure evolution. Calphad 32(2):268–294. https://doi.org/10.1016/j.calphad.2007.11.00310.1016/j.calphad.2007.11.003 ↗
16. Tourret D, Liu H, LLorca J (2022) Phase-field modeling of microstructure evolution: recent applications, perspectives and challenges. Prog Mater Sci 123:100810. https://doi.org/10.1016/j.pmatsci.2021.10081010.1016/j.pmatsci.2021.100810 ↗
17. Jou H-J, Lusk MT (1997) Comparison of Johnson–Mehl–Avrami–Kologoromov kinetics with a phase-field model for microstructural evolution driven by substructure energy. Phys Rev B 55(13):8114–8121. https://doi.org/10.1103/PhysRevB.55.811410.1103/PhysRevB.55.8114 ↗
18. Simmons JP, Wen Y, Shen C, Wang YZ (2004) Microstructural development involving nucleation and growth phenomena simulated with the phase field method. Mater Sci Eng A 365(1–2):136–143. https://doi.org/10.1016/j.msea.2003.09.01910.1016/j.msea.2003.09.019 ↗
19. Wheeler D, Keller T, DeWitt SJ, Jokisaari AM, Schwen D, Guyer JE, Aagesen LK, Heinonen OG, Tonks MR, Voorhees PW, Warren JA (2019) PFHub: the phase-field community hub. J Open Res Softw 7(1):29. https://doi.org/10.5334/jors.27610.5334/jors.276 ↗
20. Jokisaari AM, Voorhees PW, Guyer JE, Warren J, Heinonen OG (2017) Benchmark problems for numerical implementations of phase field models. Comput Mater Sci 126:139–151. https://doi.org/10.1016/j.commatsci.2016.09.02210.1016/j.commatsci.2016.09.022 ↗
21. Wu W, Montiel D, Guyer JE, Voorhees PW, Warren JA, Wheeler D, Gránásy L, Pusztai T, Heinonen OG (2021) Phase field benchmark problems for nucleation. Comput Mater Sci 193:110371. https://doi.org/10.1016/j.commatsci.2021.11037110.1016/j.commatsci.2021.110371 ↗
22. Allen SM, Cahn JW (1979) A microscopic theory for antiphase boundary motion and its application to antiphase domain coarsening. Acta Metall 27(6):1085–1095. https://doi.org/10.1016/0001-6160(79)90196-210.1016/0001-6160(79)90196-2 ↗
23. Bezanson J, Karpinski S, Shah VB, Edelman A (2012) Julia: a fast dynamic language for technical computing. arXiv:1209.5145 [cs]
24. Besard T, Foket C, De Sutter B (2018) Effective extensible programming: unleashing Julia on GPUs. IEEE Trans Parallel Distrib Syst. https://doi.org/10.1109/TPDS.2018.287206410.1109/TPDS.2018.2872064 ↗
25. Vakili S, Steinbach I, Varnik F (2017) On the numerical evaluation of local curvature for diffuse interface models of microstructure evolution. Procedia Comput Sci 108:1852–1862. https://doi.org/10.1016/j.procs.2017.05.25610.1016/j.procs.2017.05.256 ↗