Cope Elana J, Bustamante Joana, Johnson Zöe M, Lancaster Alicia, Gurunathan Ramya, George Janine, Agne Matthias T
Department of Chemistry and Biochemistry, University of Oregon, Eugene, OR, USA.
Federal Institute for Materials Research and Testing (BAM), 12205 Berlin, Germany.
Joule. 2025 Aug 20;9(8):None. doi: 10.1016/j.joule.2025.102054.
Heat capacity, which directly relates to free energy changes and thermal transport, is fundamental to modern engineering design. Even though current computational technology provides a detailed picture of atomic vibrations, the Debye and Dulong-Petit models are still widely utilized despite being prone to lower accuracy. Modern considerations of vibrational states, anharmonicity, electronic carriers, and phase transformations could improve estimates. Herein, the physics-based vibrational + dilation + electronic (VDE) model incorporates a user-provided phonon density of states, a phonon pressure-based dilation term, and an electronic component. Phonon density of states from analytical, machine-learned, and first-principles methods are compared, thus highlighting the advantages of machine-learned technology. Heat capacity estimates for 38 diverse materials are often within 5% of experimental values between 200 and 600 K. Detailed temperature-dependent investigations are carried out for several materials, including , ZIF-8, , polyvinyl chloride (PVC), and amorphous silicon. Se is modeled through its phase transition, which further demonstrates the model's capabilities to enable engineering design and sophisticated analysis.
热容与自由能变化和热传输直接相关,是现代工程设计的基础。尽管当前的计算技术能够提供原子振动的详细图像,但德拜模型和杜隆-珀蒂模型尽管精度较低,仍被广泛使用。对振动状态、非谐性、电子载流子和相变的现代考量可以改进估算。在此,基于物理的振动+膨胀+电子(VDE)模型纳入了用户提供的声子态密度、基于声子压力的膨胀项和一个电子分量。比较了来自解析法、机器学习法和第一性原理方法的声子态密度,从而突出了机器学习技术的优势。38种不同材料的热容估算值在200至600K之间通常与实验值相差在5%以内。对几种材料进行了详细的温度相关研究,包括硒、ZIF-8、聚氯乙烯(PVC)和非晶硅。硒通过其相变进行建模,这进一步证明了该模型在支持工程设计和复杂分析方面的能力。