Fugacity-Driven Phase Engineering: A Predictive Gibbsian Approach for Extreme Chemical Environments

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Main Authors: Revista, Zen, CHEMISTRY, 10
Format: Recurso digital
Published: Zenodo 2025
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author Revista, Zen
CHEMISTRY, 10
author_facet Revista, Zen
CHEMISTRY, 10
contents Predicting and controlling phase behavior in extreme chemical environments is a grand challenge in materials science and chemical engineering. Traditional approaches, often relying on ideal gas assumptions or simplified activity coefficients, falter under high pressures, high temperatures, and highly reactive conditions where intermolecular interactions are significant and non-ideal effects dominate. This paper introduces a novel fugacity-driven Gibbsian approach for phase engineering, offering a robust predictive framework for such extreme environments. By focusing on fugacity, the effective partial pressure of a component in a real gas, liquid, or solid mixture, we transcend the limitations of simple pressure-based models. This method rigorously incorporates the non-ideal behavior of components through sophisticated equations of state and molecular simulation techniques, allowing for a more accurate description of chemical potential and, consequently, phase stability. We delineate a comprehensive methodology that integrates quantum mechanical calculations, density functional theory, and molecular dynamics simulations to accurately determine fugacity coefficients and understand phase transitions at an atomic level. The proposed approach facilitates the rational design of materials and processes by predicting stable phases, optimizing synthesis conditions, and identifying pathways for novel material discovery under previously inaccessible conditions. Case studies illustrating its application to high-pressure synthesis of superhard materials and the behavior of reactive fluids in supercritical conditions are discussed, demonstrating its predictive power and potential to revolutionize our understanding and manipulation of matter in extreme chemical landscapes.
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spellingShingle Fugacity-Driven Phase Engineering: A Predictive Gibbsian Approach for Extreme Chemical Environments
Revista, Zen
CHEMISTRY, 10
Predicting and controlling phase behavior in extreme chemical environments is a grand challenge in materials science and chemical engineering. Traditional approaches, often relying on ideal gas assumptions or simplified activity coefficients, falter under high pressures, high temperatures, and highly reactive conditions where intermolecular interactions are significant and non-ideal effects dominate. This paper introduces a novel fugacity-driven Gibbsian approach for phase engineering, offering a robust predictive framework for such extreme environments. By focusing on fugacity, the effective partial pressure of a component in a real gas, liquid, or solid mixture, we transcend the limitations of simple pressure-based models. This method rigorously incorporates the non-ideal behavior of components through sophisticated equations of state and molecular simulation techniques, allowing for a more accurate description of chemical potential and, consequently, phase stability. We delineate a comprehensive methodology that integrates quantum mechanical calculations, density functional theory, and molecular dynamics simulations to accurately determine fugacity coefficients and understand phase transitions at an atomic level. The proposed approach facilitates the rational design of materials and processes by predicting stable phases, optimizing synthesis conditions, and identifying pathways for novel material discovery under previously inaccessible conditions. Case studies illustrating its application to high-pressure synthesis of superhard materials and the behavior of reactive fluids in supercritical conditions are discussed, demonstrating its predictive power and potential to revolutionize our understanding and manipulation of matter in extreme chemical landscapes.
title Fugacity-Driven Phase Engineering: A Predictive Gibbsian Approach for Extreme Chemical Environments
url https://doi.org/10.5281/zenodo.17743699