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Accurate and efficient simulation of infrared (IR) and Raman spectra is essential for molecular identification and structural analysis. Traditional quantum chemistry methods based on the harmonic approximation neglect anharmonicity and…

Chemical Physics · Physics 2025-10-07 Shengjiao Ji , Yujin Zhang , Zihan Zou , Bin Jiang , Jun Jiang , Yi Luo , Wei Hu

The existing techniques of account for the phonon dispersion are computationally costly, while its impact on a variety of thermodynamic properties appears negligible. We develop a mathematical formalism, which allows for clear understanding…

Statistical Mechanics · Physics 2014-05-01 Roman Belousov , Mauro Prencipe

Universal machine learning interatomic potentials (uMLIPs) have emerged as powerful tools for accelerating atomistic simulations, offering scalable and efficient modeling with accuracy close to quantum calculations. However, their…

Materials Science · Physics 2025-07-17 Hendrik Kraß , Ju Huang , Seyed Mohamad Moosavi

Approximately 1.2% of the world's population has impaired voice production. As a result, automatic dysphonic voice detection has attracted considerable academic and clinical interest. However, existing methods for automated voice assessment…

Sound · Computer Science 2023-01-27 Jianwei Zhang , Julie Liss , Suren Jayasuriya , Visar Berisha

Anharmonic lattice vibrations govern the thermal dynamics in materials and present how the atoms interact and how they conduct heat. An indepth understanding of the microscopic mechanism of phonon anharmonicity in condensed systems is…

Materials Science · Physics 2021-12-30 Bin Wei , Qiyang Sun , Chen Li , Jiawang Hong

Noncentrosymmetric materials play a critical role in many important applications such as laser technology, communication systems,quantum computing, cybersecurity, and etc. However, the experimental discovery of new noncentrosymmetric…

Computational Physics · Physics 2020-06-30 Yuqi Song , Joseph Lindsay , Yong Zhao , Alireza Nasiri , Steph-Yves Louis , Jie Ling , Ming Hu , Jianjun Hu

Anharmonic phonon-phonon scattering serves a critical role in heat conduction in solids. Previous studies have identified many selection rules for possible phonon-phonon scattering channels imposed by phonon energy and momentum conservation…

Materials Science · Physics 2021-05-12 Runqing Yang , Shengying Yue , Yujie Quan , Bolin Liao

Vibrational entropy plays a central role in determining phase stability and temperature dependent behavior in materials, yet its calculation from first-principles phonon methods remains computationally demanding. In this work, we combine…

Materials Science · Physics 2026-04-28 Shivam Tripathi , Jatin Kawatra , Varun Malviya , Krishna Mehta

Phonons are ubiquitous quasiparticles in solid state systems describing the quantized vibrations of a crystal lattice. Phonons play a central role in a wide range of physical phenomena, from transport to symmetry-breaking orders, such as…

Materials Science · Physics 2025-12-04 Tiantian Zhang , Yizhou Liu , Hu Miao , Shuichi Murakami

In condensed matter physics and materials science, predicting material properties necessitates understanding intricate many-body interactions. Conventional methods such as density functional theory (DFT) and molecular dynamics (MD) often…

Materials Science · Physics 2023-11-17 Lalit Yadav

Although the tailored metal active sites and porous architectures of MOFs hold great promise for engineering challenges ranging from gas separations to catalysis, a lack of understanding of how to improve their stability limits their use in…

Materials Science · Physics 2021-06-28 Aditya Nandy , Chenru Duan , Heather J. Kulik

Hydrogen diffusion in metals and alloys plays an important role in the discovery of new materials for fuel cell and energy storage technology. While analytic models use hand-selected features that have clear physical ties to hydrogen…

Materials Science · Physics 2023-10-30 Grace M. Lu , Matthew Witman , Sapan Agarwal , Vitalie Stavila , Dallas R. Trinkle

Structural phase transitions as a function of temperature dictate the structure--functionality relationships in many technologically important materials. Harmonic Hamiltonians have proven successful in predicting the vibrational properties…

Materials Science · Physics 2019-10-09 John C. Thomas , Jonathon S. Bechtel , Anirudh Raju Natarajan , Anton Van der Ven

We present a general harmonic theory for the temperature dependence of phonon-renormalized properties of solids. Firstly, we formulate a perturbation theory in phonon-phonon interactions to calculate the phonon renormalization of physical…

Materials Science · Physics 2015-10-28 Bartomeu Monserrat , G. J. Conduit , R. J. Needs

This work provides the community with an easily executable open-source Python package designed to automize the evaluation of Interfacial Phonons (InterPhon). Its strategy of arbitrarily defining the interfacial region and periodicity…

Materials Science · Physics 2021-07-20 In Won Yeu , Gyuseung Han , Kun Hee Ye , Cheol Seong Hwang , Jung-Hae Choi

To leverage advancements in machine learning for metallic materials design and property prediction, it is crucial to develop a data-reduced representation of metal microstructures that surpasses the limitations of current physics-based…

Glasses show vibrational properties that are markedly different to those of crystals which are known as phonons. For example, excess low-frequency modes (the so-called boson peak), vibrational localization, and strong scattering of phonons…

Soft Condensed Matter · Physics 2021-01-06 Hideyuki Mizuno , Atsushi Ikeda

Topological phononics extends the foundational concepts of topological condensed matter physics to the realm of lattice vibrations and classical mechanical waves, unlocking robust, defect-immune states and phenomena beyond the reach of…

Disorder in crystals is rarely random, and instead involves local correlations whose presence and nature are hidden from conventional crystallographic probes. This hidden order can sometimes be controlled, but its importance for physical…

Materials Science · Physics 2023-10-05 Nikolaj Roth , Andrew L. Goodwin

The use of machine learning methods for accelerating the design of crystalline materials usually requires manually constructed feature vectors or complex transformation of atom coordinates to input the crystal structure, which either…

Materials Science · Physics 2018-04-10 Tian Xie , Jeffrey C. Grossman