Compositional fluctuations and polymorph selection in crystallization of model soft colloids

Understanding polymorph selection in atomic and molecular systems and its control through thermodynamic conditions and external factors (such as seed characteristics) is fundamental to the design of targeted materials and holds great significance in materials sciences. In this work, using Monte Carlo simulations on the Gaussian core model and hard-core Yukawa colloidal systems, we investigated the control of polymorph selection and explored the underlying mechanisms by tuning thermodynamic parameters. We demonstrate that by carefully modifying the free energy landscape to render the globally stable face-centered cubic (FCC) phase metastable with respect to the body-centered cubic (BCC) phase, the polymorphic identity of particles transitions from FCC-dominated to BCC-dominated via an intermediate regime where both phases nucleate-either selectively or competitively-giving rise to a critical-like composition fluctuation of the growing solid-like cluster during the nucleation process. We further probed the critical solid-like cluster compositions, especially in the vicinity of the fluid-BCC-FCC triple point, where the three phases coexist, and observed an interpenetrating arrangement of FCC- and BCC-like particles rather than a commonly observed non-classical core-shell-like two-step nucleation scenario. In addition, we developed a supervised machine learning approach based on structural descriptors derived from persistent homology, a topological data analysis method, to uncover the polymorph selection signatures encoded in local structural fluctuations of the metastable fluid. We believe that the insights gained from this work have the potential to add to the ongoing efforts to control crystallization pathways to obtain the desired functional material.

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Publication Details

Journal
The Journal of Chemical Physics
Published
2025-12-17
DOI
https://doi.org/10.1063/5.0289735
Primary Topic
Topological and Geometric Data Analysis
Type
article
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article

Compositional fluctuations and polymorph selection in crystallization of model soft colloids

Mantu Santra, Debasish Koner, Gadha Ramesh, Rakesh S. Singh et al.
The Journal of Chemical Physics
Topological and Geometric Data Analysis
article

Compositional fluctuations and polymorph selection in crystallization of model soft colloids

Mantu Santra, Debasish Koner, Gadha Ramesh, Rakesh S. Singh, A Kumari
article en

Abstract

Understanding polymorph selection in atomic and molecular systems and its control through thermodynamic conditions and external factors (such as seed characteristics) is fundamental to the design of targeted materials and holds great significance in materials sciences. In this work, using Monte Carlo simulations on the Gaussian core model and hard-core Yukawa colloidal systems, we investigated the control of polymorph selection and explored the underlying mechanisms by tuning thermodynamic parameters. We demonstrate that by carefully modifying the free energy landscape to render the globally stable face-centered cubic (FCC) phase metastable with respect to the body-centered cubic (BCC) phase, the polymorphic identity of particles transitions from FCC-dominated to BCC-dominated via an intermediate regime where both phases nucleate-either selectively or competitively-giving rise to a critical-like composition fluctuation of the growing solid-like cluster during the nucleation process. We further probed the critical solid-like cluster compositions, especially in the vicinity of the fluid-BCC-FCC triple point, where the three phases coexist, and observed an interpenetrating arrangement of FCC- and BCC-like particles rather than a commonly observed non-classical core-shell-like two-step nucleation scenario. In addition, we developed a supervised machine learning approach based on structural descriptors derived from persistent homology, a topological data analysis method, to uncover the polymorph selection signatures encoded in local structural fluctuations of the metastable fluid. We believe that the insights gained from this work have the potential to add to the ongoing efforts to control crystallization pathways to obtain the desired functional material.

The Journal of Chemical PhysicsVol. 163(23)
Indian Institute of Technology Goa (IN), Indian Institute of Science Education and Research, Tirupati (IN), Indian Institute of Technology Hyderabad (IN)
Openalex Percentile: Top 60%
Topological and Geometric Data Analysis
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