发表机构
Florida State University; Middle Tennessee State University; Oak Ridge National Laboratory; Louisiana State University（佛罗里达州立大学; 中田纳西州立大学; 橡树岭国家实验室; 路易斯安那州立大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究提出理论框架，揭示复杂金属合金中无序驱动的电荷转移与静电涨落遵循类高斯统计和普适qV线性相关，并通过DFT验证，为合金预测设计奠定统计物理基础。
AI 中文摘要
复杂金属合金表现出丰富的由无序驱动的电子、磁性和振动行为，这些行为源于强烈的化学无序，导致了非常规的结构-性能关系，在极端环境材料、催化、自旋电子学和热电学中具有应用前景。尽管具有技术相关性，但在化学无序合金中电荷再分布和静电涨落的微观本质仍未完全理解。在此，我们开发了一个理论框架，揭示了无序驱动的电荷转移和马德隆场涨落的普遍统计趋势。我们的解析形式表明，局部电荷转移和静电势表现出类高斯统计和普适的线性电荷-电势（qV）相关性，这些直接源于底层无序景观。我们确定了这些相关性在电子屏蔽与杂质散射相互作用中的物理起源，并展示了其统计性质如何依赖于载流子密度、无序强度和组分复杂度。我们进一步推导了控制二元和多组分合金（包括高熵材料）中qV趋势的标度关系。大超胞密度泛函理论（DFT）计算显示，对代表性金属合金的预测统计行为具有良好的定量一致性。我们的结果为将无序驱动的静电涨落纳入有效介质电子结构理论提供了一个计算高效的框架，并为复杂合金的预测性设计建立了统计物理学基础。
英文摘要
Complex metallic alloys exhibit rich disorder-driven electronic, magnetic, and vibrational behavior arising from strong chemical disorder, leading to unconventional structure-property relationships with applications in extreme-environment materials, catalysis, spintronics, and thermoelectrics. Despite their technological relevance, the microscopic nature of charge redistribution and electrostatic fluctuations in chemically disordered alloys remains incompletely understood. Here, we develop a theoretical framework that uncovers universal statistical trends of disorder-driven charge transfer and Madelung-field fluctuations. Our analytical formalism demonstrates that local charge transfer and electrostatic potentials exhibit Gaussian-like statistics and universal linear charge-potential (qV) correlations emerging directly from the underlying disorder landscape. We identify the physical origin of these correlations in the interplay between electronic screening and impurity scattering and show how their statistical properties depend on carrier density, disorder strength, and compositional complexity. We further derive scaling relations governing qV trends across binary and multicomponent alloys, including high-entropy materials. Large-supercell density-functional theory (DFT) calculations show good quantitative agreement with the predicted statistical behavior for representative metallic alloys. Our results provide a computationally efficient framework for incorporating disorder-driven electrostatic fluctuations into effective-medium electronic-structure theories and establish a statistical-physics foundation for the predictive design of complex alloys.
Comments39 pages, 59 images
