Microscopic Phase-Field Modeling
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arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866914119854063616 |
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| author | Jin, Jaehyeok Reichman, David R. |
| author_facet | Jin, Jaehyeok Reichman, David R. |
| contents | Phase-field methods offer a versatile computational framework for simulating large-scale morphological evolution. However, the applicability and predictability of phase-field models are inherently limited by their ad hoc nature, and there is currently no version of this approach that enables truly first-principles predictive modeling of large-scale non-equilibrium processes. Here, we present a bottom-up framework that provides a route to the construction of mesoscopic phase-field models entirely based on atomistic information. Leveraging molecular coarse-graining, we describe the formulation of an order parameter-based free energy functional appropriate for a phase-field description via the enhanced sampling of rare events. We demonstrate our approach on ice nucleation dynamics, achieving a spatiotemporal scale-up of nearly $10^8$ times compared to the microscopic model. Our framework offers a unique approach for incorporating atomistic details into mesoscopic models and systematically bridges the gap between microscopic particle-based simulations and field-theoretic models. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2410_08180 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Microscopic Phase-Field Modeling Jin, Jaehyeok Reichman, David R. Materials Science Soft Condensed Matter Statistical Mechanics Chemical Physics Phase-field methods offer a versatile computational framework for simulating large-scale morphological evolution. However, the applicability and predictability of phase-field models are inherently limited by their ad hoc nature, and there is currently no version of this approach that enables truly first-principles predictive modeling of large-scale non-equilibrium processes. Here, we present a bottom-up framework that provides a route to the construction of mesoscopic phase-field models entirely based on atomistic information. Leveraging molecular coarse-graining, we describe the formulation of an order parameter-based free energy functional appropriate for a phase-field description via the enhanced sampling of rare events. We demonstrate our approach on ice nucleation dynamics, achieving a spatiotemporal scale-up of nearly $10^8$ times compared to the microscopic model. Our framework offers a unique approach for incorporating atomistic details into mesoscopic models and systematically bridges the gap between microscopic particle-based simulations and field-theoretic models. |
| title | Microscopic Phase-Field Modeling |
| topic | Materials Science Soft Condensed Matter Statistical Mechanics Chemical Physics |
| url | https://arxiv.org/abs/2410.08180 |