逆热力学:设计目标相行为的相互作用。

IF 2.9 2区 化学 Q3 CHEMISTRY, PHYSICAL
Camilla Beneduce, , , Giuseppe Mastriani, , , Petr Šulc, , , Francesco Sciortino*, , and , John Russo, 
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引用次数: 0

摘要

逆自组装的传统目标是设计相互作用,驱动粒子走向所需的目标结构。然而,实现成功的自组装还需要调整结构稳定的热力学条件。在这项工作中,我们扩展了逆设计范式,通过开发逆热力学框架来明确解决这一挑战,即设计实现特定热力学行为的相互作用势。作为朝这个方向迈出的一步,我们使用斑块状粒子混合物作为模型系统,展示了如何精确控制键合拓扑和键合能量,从而实现目标相行为的编程。特别地,我们建立了共沸脱混的设计原则,并展示了如何在任何规定的成分下创造出具有共沸性的混合物。我们的预测通过Gibbs-ensemble simulation得到了验证[Panagiotopoulos, Mol. Phys. 1987, 61, 813-826]。这些结果强调了结构设计与热力学工程耦合的必要性,并为控制多组分系统的复杂相行为提供了蓝图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Inverse Thermodynamics: Designing Interactions for Targeted Phase Behavior

The traditional goal of inverse self-assembly is to design interactions that drive particles toward a desired target structure. However, achieving successful self-assembly also requires tuning the thermodynamic conditions under which the structure is stable. In this work, we extend the inverse design paradigm to explicitly address this challenge by developing a framework for inverse thermodynamics, i.e., the design of interaction potentials that realize specific thermodynamic behavior. As a step in this direction, using patchy particle mixtures as a model system, we demonstrate how precise control over both bonding topology and bond energetics enables the programming of targeted phase behavior. In particular, we establish design principles for azeotropic demixing and show how to create mixtures that exhibit azeotropy at any prescribed composition. Our predictions are validated through Gibbs-ensemble simulations [Panagiotopoulos, Mol. Phys. 1987, 61, 813–826]. These results highlight the necessity of coupling structural design with thermodynamic engineering, and provide a blueprint for controlling complex phase behavior in multicomponent systems.

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来源期刊
CiteScore
5.80
自引率
9.10%
发文量
965
审稿时长
1.6 months
期刊介绍: An essential criterion for acceptance of research articles in the journal is that they provide new physical insight. Please refer to the New Physical Insights virtual issue on what constitutes new physical insight. Manuscripts that are essentially reporting data or applications of data are, in general, not suitable for publication in JPC B.
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