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Related papers: InterPhon: Ab initio Interface Phonon Calculations…

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We introduce and model a three-dimensional (3D) atomic-scale phononic metamaterial producing two-path phonon interference antiresonances to control the heat flux spectrum. We show that a crystal plane partially embedded with defect-atom…

Mesoscale and Nanoscale Physics · Physics 2014-05-22 Haoxue Han , Lyudmila G. Potyomina , Alexandre A. Darinskii , Sebastian Volz , Yuriy A. Kosevich

Phonon decoherence determines the characteristic timescales over which coherent lattice vibrations decay, making it a crucial process for understanding the non-equilibrium dynamics of crystal lattices after excitation by a pump pulse. Here,…

Strongly Correlated Electrons · Physics 2025-02-04 Yiming Pan , Christoph Emeis , Stephan Jauernik , Michael Bauer , Fabio Caruso

Phonon anharmonicity is ubiquitous in real materials and is crucial for understanding thermal properties and phase stability. In this work, we show that anharmonic phonon modes can be obtained by maximizing their vibration stability during…

Materials Science · Physics 2026-05-15 Wenjing Li , Yong Lu , Fawei Zheng

Relying on the anharmonic special displacement method, we introduce an ab initio quasistatic polymorphous framework to describe local disorder, anharmonicity, and electron-phonon coupling in superionic conductors. Using the example of cubic…

New and upgraded radio interferometers produce data at massive rates and will require significant improvements in analysis techniques to reach their promised levels of performance in a routine manner. Until these techniques are fully…

Instrumentation and Methods for Astrophysics · Physics 2012-06-29 Peter K. G. Williams , Casey J. Law , Geoffrey C. Bower

The calculation of potential energy surfaces for quantum dynamics can be a time consuming task -- especially when a high level of theory for the electronic structure calculation is required. We propose an adaptive interpolation algorithm…

Chemical Physics · Physics 2016-08-24 Markus Kowalewski , Elisabeth Larsson , Alfa Heryudono

Parameter-free calculations of lattice dynamics from first principles have achieved significant progress in the past decades, with a wealth of applications in thermodynamics, phase transitions, and transport properties of materials. Current…

Materials Science · Physics 2025-08-05 Changpeng Lin , Jian Han , Ben Xu , Nicola Marzari

Interfaces between materials play a crucial role in the performance of most devices. However, predicting the structure of a material interface is computationally demanding due to the vast configuration space, which requires evaluating an…

Materials Science · Physics 2025-08-12 Ned Thaddeus Taylor , Joe Pitfield , Francis Huw Davies , Steven Paul Hepplestone

We theoretically study the phonon mediated intersurface electron-electron interactions on the pseudo two-dimensional metallic states at the two surfaces of a three-dimensional topological insulator. From a model of a three-dimensional…

Mesoscale and Nanoscale Physics · Physics 2014-01-15 Tetsuro Habe

We present an accurate interatomic potential for graphene, constructed using the Gaussian Approximation Potential (GAP) machine learning methodology. This GAP model obtains a faithful representation of a density functional theory (DFT)…

Materials Science · Physics 2018-02-14 Patrick Rowe , Gábor Csányi , Dario Alfè , Angelos Michaelides

We describe a new approach to compute the electron-phonon self-energy and carrier mobilities in semiconductors. Our implementation does not require a localized basis set to interpolate the electron-phonon matrix elements, with the advantage…

Artificial intelligence (AI) has revolutionized software development, shifting from task-specific codes (Software 1.0) to neural network-based approaches (Software 2.0). However, applying this transition in engineering software presents…

Mobile robots operating indoors must be prepared to navigate challenging scenes that contain transparent surfaces. This paper proposes a novel method for the fusion of acoustic and visual sensing modalities through implicit neural…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Advaith V. Sethuraman , Onur Bagoren , Harikrishnan Seetharaman , Dalton Richardson , Joseph Taylor , Katherine A. Skinner

We present a method for dimensionally adaptive sparse trigonometric interpolation of multidimensional periodic functions belonging to a smoothness class of finite order. This method targets applications where periodicity must be preserved…

Numerical Analysis · Mathematics 2020-08-28 Zack Morrow , Miroslav Stoyanov

A method based on the Gibbs' adsorption isotherm is developed to calculate the decrease in interfacial free energy resulting from solute segregation at an internal interface, built on measured concentration profiles. Utilizing atom-probe…

Materials Science · Physics 2020-03-04 Ivan Blum , Sung-Il Baik , Mercouri G. Kanatzidis , David N. Seidman

Interfaces impede heat flow in micro/nanostructured systems. Conventional theories for interfacial thermal transport were derived based on bulk phonon properties of the materials making up the interface without explicitly considering the…

A Materials Project based open-source Python tool, MPInterfaces, has been developed to automate the high-throughput computational screening and study of interfacial systems. The framework encompasses creation and manipulation of interface…

The coupling between electrons and phonons in solids plays a central role in describing many phenomena, including superconductivity and thermoelecric transport. Calculations of this coupling are exceedingly demanding as they necessitate…

Materials Science · Physics 2020-09-16 Anderson S. Chaves , Alex Antonelli , Daniel T. Larson , Efthimios Kaxiras

We present a computational protocol, based on density matrix perturbation theory, to obtain non-adiabatic, frequency-dependent electron-phonon self-energies for molecules and solids. Our approach enables the evaluation of electron-phonon…

Materials Science · Physics 2023-05-09 Han Yang , Marco Govoni , Arpan Kundu , Giulia Galli

We present an equivariant neural network for predicting vibrational and phonon modes of molecules and periodic crystals, respectively. These predictions are made by evaluating the second derivative Hessian matrices of the learned energy…

Disordered Systems and Neural Networks · Physics 2024-03-19 Shiang Fang , Mario Geiger , Joseph G. Checkelsky , Tess Smidt