势能作为纳米粒子聚结的描述符

IF 2.9 4区 工程技术 Q1 MULTIDISCIPLINARY SCIENCES
Panagiotis Grammatikopoulos, Aristis Damianidis, Evropi Toulkeridou
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引用次数: 0

摘要

聚结是气相合成纳米颗粒(NPs)的一个基本过程,影响着纳米颗粒的结构和合成性能。目前,在原子模拟研究中,各种度量标准被用于测量聚并程度,例如NPs质心之间形成的颈部半径、旋转半径、球度和表面积变化。这类指标的一个共同特征是,它们通常需要额外的、通常是艰苦的数据操作。在这里,引入了一个新的描述符,即初始未聚并构型和聚并构型之间的总减少势能变化(ORCiPE)。为了对描述符进行基准测试,它的定义类似于表面积的总体变化,这是一种常见且可靠的度量。当没有发生相变时,与其他指标的比较证实了ORCiPE在Au NPs聚结中的可靠性。考虑到势能是原子模拟中的标准输出属性,ORCiPE被提出作为一个有价值且方便的聚并度量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Potential Energy as Descriptor for Nanoparticle Coalescence

Potential Energy as Descriptor for Nanoparticle Coalescence

Potential Energy as Descriptor for Nanoparticle Coalescence

Coalescence is a fundamental process in gas-phase synthesis of nanoparticles (NPs), affecting their structure and resultant properties. Various metrics are currently used to measure the degree of coalescence in atomistic simulation studies, such as the radius of the neck formed between the NPs’ centers of mass, gyration radii, sphericity, and surface area changes. A common characteristic of such metrics is that they typically require additional, often painstaking, data manipulation. Here, a new descriptor is introduced, the Overall Reduced Change in Potential Energy (ORCiPE) between initially uncoalesced and coalesced configurations. To benchmark the descriptor, its definition is analogous to that of the Overall Change in Surface Area, a common and dependable metric. When no phase transition occurred, comparison with other metrics confirms the reliability of ORCiPE in coalescing Au NPs. Considering that potential energy is a standard output property in atomistic simulations, ORCiPE is proposed as a valuable and facile coalescence metric.

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来源期刊
Advanced Theory and Simulations
Advanced Theory and Simulations Multidisciplinary-Multidisciplinary
CiteScore
5.50
自引率
3.00%
发文量
221
期刊介绍: Advanced Theory and Simulations is an interdisciplinary, international, English-language journal that publishes high-quality scientific results focusing on the development and application of theoretical methods, modeling and simulation approaches in all natural science and medicine areas, including: materials, chemistry, condensed matter physics engineering, energy life science, biology, medicine atmospheric/environmental science, climate science planetary science, astronomy, cosmology method development, numerical methods, statistics
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