2024-08-08 アルゴンヌ国立研究所(ANL)
＜関連情報＞
- https://www.anl.gov/article/ability-to-track-nanoscale-flow-in-soft-matter-could-prove-pivotal-discovery
- https://www.pnas.org/doi/10.1073/pnas.2401162121
ソフトマターの非平衡ダイナミクスを特徴づける輸送係数アプローチ Transport coefficient approach for characterizing nonequilibrium dynamics in soft matter
HongRui He, Heyi Liang, Miaoqi Chu, +4, and Wei Chen
Proceedings of the National Academy of Sciences Published:July 23, 2024
DOI:https://doi.org/10.1073/pnas.2401162121
Significance
X-ray photon correlation spectroscopy (XPCS) is increasingly employed to probe dynamics in soft, structured materials, with applications set to grow alongside synchrotron upgrades worldwide. Existing methods often sacrifice crucial details by averaging data, obscuring complex phenomena such as relaxation and avalanches. Our approach, rooted in Langevin dynamics and avoiding averaging, extracts a microscopic <?XML:NAMESPACE PREFIX = “[default] http://www.w3.org/1998/Math/MathML” NS = “http://www.w3.org/1998/Math/MathML” />Jt that directly connects to XPCS intensity correlations. This improves our understanding of nonequilibrium dynamics by connecting microscopic insights into macroscopic properties. It opens avenues for optimizing soft materials in various fields, from advanced manufacturing to exploring natural phenomena.
Abstract
Nonequilibrium states in soft condensed matter require a systematic approach to characterize and model materials, enhancing predictability and applications. Among the tools, X-ray photon correlation spectroscopy (XPCS) provides exceptional temporal and spatial resolution to extract dynamic insight into the properties of the material. However, existing models might overlook intricate details. We introduce an approach for extracting the transport coefficient, denoted as J(t), from the XPCS studies. This coefficient is a fundamental parameter in nonequilibrium statistical mechanics and is crucial for characterizing transport processes within a system. Our method unifies the Green–Kubo formulas associated with various transport coefficients, including gradient flows, particle–particle interactions, friction matrices, and continuous noise. We achieve this by integrating the collective influence of random and systematic forces acting on the particles within the framework of a Markov chain. We initially validated this method using molecular dynamics simulations of a system subjected to changes in temperatures over time. Subsequently, we conducted further verification using experimental systems reported in the literature and known for their complex nonequilibrium characteristics. The results, including the derived J(t) and other relevant physical parameters, align with the previous observations and reveal detailed dynamical information in nonequilibrium states. This approach represents an advancement in XPCS analysis, addressing the growing demand to extract intricate nonequilibrium dynamics. Further, the methods presented are agnostic to the nature of the material system and can be potentially expanded to hard condensed matter systems.
