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A first-principles phase field method for quantitatively predicting multi-composition phase separation without thermodynamic empirical parameter.

ABSTRACT: To design tailored materials, it is highly desirable to predict microstructures of alloys without empirical parameter. Phase field models (PFMs) rely on parameters adjusted to match experimental information, while first-principles methods cannot directly treat the typical length scale of 10 μm. Combining density functional theory, cluster expansion theory and potential renormalization theory, we derive the free energy as a function of compositions and construct a parameter-free PFM, which can predict microstructures in high-temperature regions of alloy phase diagrams. Applying this method to Ni-Al alloys at 1027 °C, we succeed in reproducing evolution of microstructures as a function of only compositions without thermodynamic empirical parameter. The resulting patterns including cuboidal shaped precipitations are in excellent agreement with the experimental microstructures in each region of the Ni-Al phase diagram. Our method is in principle applicable to any kind of alloys as a reliable theoretical tool to predict microstructures of new materials.

SUBMITTER: Bhattacharyya S

PROVIDER: S-EPMC6671953 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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A first-principles phase field method for quantitatively predicting multi-composition phase separation without thermodynamic empirical parameter.

Bhattacharyya Swastibrata S Sahara Ryoji R Ohno Kaoru K

Nature communications 20190801 1

To design tailored materials, it is highly desirable to predict microstructures of alloys without empirical parameter. Phase field models (PFMs) rely on parameters adjusted to match experimental information, while first-principles methods cannot directly treat the typical length scale of 10 μm. Combining density functional theory, cluster expansion theory and potential renormalization theory, we derive the free energy as a function of compositions and construct a parameter-free PFM, which can pr ...[more]

PMID: 31371706

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Project description:Intracellular bodies such as nucleoli, Cajal bodies and various signalling assemblies represent membraneless organelles, or condensates, that form via liquid-liquid phase separation (LLPS)1,2. Biomolecular interactions-particularly homotypic interactions mediated by self-associating intrinsically disordered protein regions-are thought to underlie the thermodynamic driving forces for LLPS, forming condensates that can facilitate the assembly and processing of biochemically active complexes, such as ribosomal subunits within the nucleolus. Simplified model systems3-6 have led to the concept that a single fixed saturation concentration is a defining feature of endogenous LLPS7-9, and has been suggested as a mechanism for intracellular concentration buffering2,7,8,10. However, the assumption of a fixed saturation concentration remains largely untested within living cells, in which the richly multicomponent nature of condensates could complicate this simple picture. Here we show that heterotypic multicomponent interactions dominate endogenous LLPS, and give rise to nucleoli and other condensates that do not exhibit a fixed saturation concentration. As the concentration of individual components is varied, their partition coefficients change in a manner that can be used to determine the thermodynamic free energies that underlie LLPS. We find that heterotypic interactions among protein and RNA components stabilize various archetypal intracellular condensates-including the nucleolus, Cajal bodies, stress granules and P-bodies-implying that the composition of condensates is finely tuned by the thermodynamics of the underlying biomolecular interaction network. In the context of RNA-processing condensates such as the nucleolus, this manifests in the selective exclusion of fully assembled ribonucleoprotein complexes, providing a thermodynamic basis for vectorial ribosomal RNA flux out of the nucleolus. This methodology is conceptually straightforward and readily implemented, and can be broadly used to extract thermodynamic parameters from microscopy images. These approaches pave the way for a deeper understanding of the thermodynamics of multicomponent intracellular phase behaviour and its interplay with the nonequilibrium activity that is characteristic of endogenous condensates.

Dataset Information

A first-principles phase field method for quantitatively predicting multi-composition phase separation without thermodynamic empirical parameter.

Publications

A first-principles phase field method for quantitatively predicting multi-composition phase separation without thermodynamic empirical parameter.

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