Florio Giuseppe, Giordano Stefano, Puglisi Giuseppe
Department of Civil, Environmental, Land, Building Engineering and Chemistry (DICATECh), Polytechnic University of Bari, Via Orabona 4, 70125 Bari, Italy.
INFN, Section of Bari, 70126 Bari, Italy.
Entropy (Basel). 2024 Dec 18;26(12):1109. doi: 10.3390/e26121109.
Multi-stable behavior at the microscopic length-scale is fundamental for phase transformation phenomena observed in many materials. These phenomena can be driven not only by external mechanical forces but are also crucially influenced by disorder and thermal fluctuations. Disorder, arising from structural defects or fluctuations in external stimuli, disrupts the homogeneity of the material and can significantly alter the system's response, often leading to the suppression of cooperativity in the phase transition. Temperature can further introduce novel effects, modifying energy barriers and transition rates. The study of the effects of fluctuations requires the use of a framework that naturally incorporates the interaction of the system with the environment, such as Statistical Mechanics to account for the role of temperature. In the case of complex phenomena induced by disorder, advanced methods such as the replica method (to derive analytical formulas) or refined numerical methods based, for instance, on Monte Carlo techniques, may be needed. In particular, employing models that incorporate the main features of the physical system under investigation and allow for analytical results that can be compared with experimental data is of paramount importance for describing many realistic physical phenomena, which are often studied while neglecting the critical effect of randomness or by utilizing numerical techniques. Additionally, it is fundamental to efficiently derive the macroscopic material behavior from microscale properties, rather than relying solely on phenomenological approaches. In this perspective, we focus on a paradigmatic model that includes both nearest-neighbor interactions with multi-stable (elastic) energy terms and linear long-range interactions, capable of ensuring the presence of an ordered phase. Specifically, to study the effect of environmental noise on the control of the system, we include random fluctuation in external forces. We numerically analyze, on a small-size system, how the interplay of temperature and disorder can significantly alter the system's phase transition behavior. Moreover, by mapping the model onto a modified version of the Random Field Ising Model, we utilize the replica method approach in the thermodynamic limit to justify the numerical results through analytical insights.
微观长度尺度上的多稳态行为是许多材料中观察到的相变现象的基础。这些现象不仅可以由外部机械力驱动,还受到无序和热涨落的关键影响。由结构缺陷或外部刺激的涨落引起的无序会破坏材料的均匀性,并能显著改变系统的响应,常常导致相变中协同性的抑制。温度可以进一步引入新的效应,改变能垒和转变速率。对涨落效应的研究需要使用一个自然包含系统与环境相互作用的框架,比如统计力学来解释温度的作用。对于由无序引起的复杂现象,可能需要先进的方法,如复本方法(用于推导解析公式)或基于例如蒙特卡罗技术的精细数值方法。特别地,采用包含所研究物理系统主要特征并能得到可与实验数据比较的解析结果的模型,对于描述许多现实物理现象至关重要,这些现象在研究时常常忽略随机性的关键影响或仅利用数值技术。此外,从微观尺度性质高效推导宏观材料行为,而不是仅仅依赖唯象方法,这一点至关重要。从这个角度出发,我们关注一个典型模型,它既包括具有多稳态(弹性)能量项的最近邻相互作用,也包括线性长程相互作用,能够确保有序相的存在。具体而言,为了研究环境噪声对系统控制的影响,我们在外部力中引入随机涨落。我们在一个小尺寸系统上进行数值分析,研究温度和无序的相互作用如何能显著改变系统的相变行为。此外,通过将该模型映射到随机场伊辛模型的一个修改版本上,我们在热力学极限下利用复本方法通过解析见解来验证数值结果。