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Density Functional Theory (DFT) is one of the most widely used methods for "ab initio" calculations of the structure of atoms, molecules, crystals, surfaces, and their interactions. Unfortunately, the customary introduction to DFT is often…

Physics Education · Physics 2010-12-07 Nathan Argaman , Guy Makov

Although the melting temperature, $T_{m}$, of a solid can be calculated based on first-principles molecular dynamics (FP-MD) simulations, systematic assessments of the accuracy of the resulting values have not yet been reported. FP-MD…

Materials Science · Physics 2024-12-10 Koun Shirai , Hiroyoshi Momida , Kazunori Sato , Sangil Hyun

Electron energy-loss spectroscopy (EELS) coupled with scanning transmission electron microscopy (STEM) is a powerful technique to determine materials composition and bonding with high spatial resolution. Noise is often a limitation…

Instrumentation and Detectors · Physics 2025-05-21 Yifan Wang , Mai Tan , Carlos Fernandez-Granda , Peter A. Crozier

We extend the ideas of using AdS/CFT to calculate energy loss of extended defects in strongly coupled systems to general holographic metrics. We find the equations of motion governing uniformly moving defects of various dimension and…

High Energy Physics - Theory · Physics 2013-05-30 John F. Fuini , Andreas Karch

Machine learning thermodynamic perturbation theory (MLPT) is a promising approach to compute finite temperature properties when the goal is to compare several different levels of ab initio theory and/or to apply highly expensive…

A first-principles method, based on density functional perturbation theory, is presented for computing the leading order tunability of high-dielectric-constant materials.

Materials Science · Physics 2007-05-23 K. M. Rabe

Quantum dots (QDs) are good model systems for fundamental studies of mesoscopic transport phenomena using thermoelectric effects because of their small size, electrostatically tunable properties and thermoelectric response characteristics…

Mesoscale and Nanoscale Physics · Physics 2016-11-16 Artis Svilans , Martin Leijnse , Heiner Linke

Modern laboratory techniques like ultrafast laser excitation and shock compression can bring matter into highly nonequilibrium states with complex structural transformation, metallization and dissociation dynamics. To understand and model…

Computational Physics · Physics 2022-05-24 Qiyu Zeng , Bo Chen , Xiaoxiang Yu , Shen Zhang , Dongdong Kang , Han Wang , Jiayu Dai

We establish large deviation principles (LDPs) for empirical measures associated with a sequence of Gibbs distributions on $n$-particle configurations, each of which is defined in terms of an inverse temperature $% \beta_n$ and an energy…

Probability · Mathematics 2020-01-07 Paul Dupuis , Vaios Laschos , Kavita Ramanan

Using transient grating spectroscopy (TGS) we measure the thermal diffusivity of tungsten exposed to different levels of 20 MeV self-ion irradiation. Damage as low as 3.2 x 10^-4 displacements per atom (dpa) causes a measurable reduction in…

Materials Science · Physics 2020-02-05 Abdallah Reza , Hongbing Yu , Kenichiro Mizohata , Felix Hofmann

Detectors based upon the noble elements, especially liquid xenon as well as liquid argon, as both single- and dual-phase types, require reconstruction of the energies of interacting particles, both in the field of direct detection of dark…

Interacting defect systems are ubiquitous in materials under realistic scenarios, yet gaining an atomic-level understanding of these systems from a computational perspective is challenging - it often demands substantial resources due to the…

Materials Science · Physics 2024-03-21 Hao Yu

In order to keep track of the operational state of power grid, the world's largest sensor systems, smart grid, was built by deploying hundreds of millions of smart meters. Such system makes it possible to discover and make quick response to…

Machine Learning · Computer Science 2019-07-10 Jiangteng Li , Fei Wang

We studied deep levels (DLs) in p-type CdMnTe by photo-Hall effect spectroscopy with enhanced illumination. We showed that the mobility of minority and majority carriers can be deduced directly from the spectra by using proper wavelength…

Materials Science · Physics 2018-07-25 A. Musiienko , R. Grill , P. Moravec , P. Fochuk , I. Vasylchenko , H. Elhadidy , L. Šedivý

Material-based two-level systems (TLSs), appearing as defects in low-temperature devices including superconducting qubits and photon detectors, are difficult to characterize. In this study we apply a uniform dc-electric field across a film…

Lithium superionic conductors (LSCs) are of major importance as solid electrolytes for next-generation all-solid-state lithium-ion batteries. While $ab$ $initio$ molecular dynamics have been extensively applied to study these materials,…

The energetically optimal position of lattice defects on intrinsically curved surfaces is a complex function of shape parameters. For open surfaces, a simple condition predicts the critical size for which a central disclination yields lower…

Soft Condensed Matter · Physics 2023-08-09 Siddhansh Agarwal , Sascha Hilgenfeldt

We present an improved method to calculate defect formation energies that overcomes the band-gap problem of Kohn-Sham density-functional theory (DFT) and reduces the self-interaction error of the local-density approximation (LDA) to DFT. We…

Materials Science · Physics 2009-11-13 Patrick Rinke , Anderson Janotti , Matthias Scheffler , Chris G. Van de Walle

The basic properties of point defects (atomic geometry, the position of charge-transfer levels, and formation energies) on the (110) surface of GaAs, GaP, and InP have been calculated employing density-functional theory. Based on these…

Materials Science · Physics 2007-05-23 G. Schwarz , J. Neugebauer , M. Scheffler

Scattering of carriers with ionized impurities governs charge transport in doped semiconductors. However, electron interactions with ionized impurities cannot be fully described with quantitative first-principles calculations, so their…

Materials Science · Physics 2021-10-12 I-Te Lu , Jin-Jian Zhou , Jinsoo Park , Marco Bernardi
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