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Electrocatalytic CO2 reduction technology is key to mitigating greenhouse gas emissions and the energy crisis. However, controlling the selectivity of CO2RR products at low overpotential remains a challenge. In this paper, we predicted five…

Materials Science · Physics 2024-03-05 Ran Wang , Chaozheng He , Weixing Chen , Qingquan Kong , Thomas Frauenheimac

Because of their unique and rich physical properties, transition metal dichalcogenides (TMDs) materials have attracted much interest. Many studies suggest that introducing the degree of freedom of anisotropy, which may be brought about by…

Materials Science · Physics 2025-02-11 T. T. Lin , J. W. Ma , H. C. Deng , L. Z. Liu

The microscopic structure of several amorphous substances often reveals complex patterns such as medium- or long-range order, spatial heterogeneity, and even local polycrystallinity. To capture all these features, models usually incorporate…

The $\Delta$NO two-electron density matrix (2-RDM) and energy expression are derived from a multideterminantal wave function. The approximate $\Delta$NO 2-RDM is combined with an on-top density functional and a double-counting correction to…

Chemical Physics · Physics 2022-03-14 Ismael A. Elayan , Rishabh Gupta , Joshua W. Hollett

Two-dimensional (2D) materials exhibit a wide range of remarkable phenomena, many of which owe their existence to the relativistic spin-orbit coupling (SOC) effects. To understand and predict properties of materials containing heavy…

We show that the density-matrix states of noncomposite qudit systems satisfy entropic and information relations like the subadditivity condition, strong subadditivity condition, and Araki--Lieb inequality, which characterize hidden quantum…

Quantum Physics · Physics 2016-05-04 Margarita A Man'ko , Vladimir I Man'ko

This is the second paper devoted to energetic rigidity, in which we apply our formalism to examples in two dimensions: underconstrained random regular spring networks, vertex models, and jammed packings of soft particles. Spring networks…

Soft Condensed Matter · Physics 2021-07-15 Ojan Khatib Damavandi , Varda F. Hagh , Christian D. Santangelo , M. Lisa Manning

Studying the physics of quantum correlations has gained new interest after it has become possible to measure entanglement entropies of few body systems in experiments with ultracold atomic gases. Apart from investigating trapped atom…

Quantum Physics · Physics 2020-09-22 Arkadiusz Kuroś , Anna Okopińska

We suggest two metrics for assessing the quality of atomistic configurations of disordered materials, both of which are based on quantifying the orientational distribution of neighbours around each atom in the configuration. The first…

Materials Science · Physics 2012-11-20 Matthew J. Cliffe , Andrew L. Goodwin

The theory of correlated electron systems is formulated in a form which allows to use as a reference point an ab initio band structure theory (AIBST). The theory is constructed in two steps. As a first step the total Hamiltonian is…

Strongly Correlated Electrons · Physics 2007-05-23 Igor Sandalov , Borje Johansson , Olle Eriksson

Electronic and topological properties of materials are derived from the interplay between crystalline symmetry and dimensionality. Simultaneously introducing 'forbidden' symmetries via quasiperiodic ordering with low-dimensionality into a…

Materials Science · Physics 2022-06-01 Jeffrey D. Cain , Amin Azizi , Matthias Conrad , Sinéad M. Griffin , Alex Zettl

Research on strongly correlated electron systems faces a fundamental challenge due to the complex nature of intrinsic many-body correlations. A key strategy to address this challenge lies in advancing experimental methods that can directly…

Strongly Correlated Electrons · Physics 2026-03-31 Yuehua Su , Guoya Zhang , Chao Zhang , Dezhong Cao

Ab initio calculation of the electronic properties of materials is a major challenge for solid state theory. Whereas the experience of forty years has proven density functional theory (DFT) in a suitable, e.g. local approximation (LDA) to…

Strongly Correlated Electrons · Physics 2009-11-13 K. Held , O. K. Andersen , M. Feldbacher , A. Yamasaki , Y. -F. Yang

We report electrical conductivity $\sigma$ measurements on a range of two-dimensional electron gases (2DEGs) of varying linear extent. Intriguingly, at low temperatures ($T$) and low carrier density ($n_{\mathrm{s}}$) we find the behavior…

Mesoscale and Nanoscale Physics · Physics 2016-05-25 Dirk Backes , Richard Hall , Michael Pepper , Harvey Beere , David Ritchie , Vijay Narayan

We investigate the space distribution of carrier density and the compressibility of two-dimensional (2D) electron systems by using the local density approximation. The strong correlation is simulated by the local exchange and correlation…

Strongly Correlated Electrons · Physics 2009-11-07 Junren Shi , X. C. Xie

This paper reviews the new highly interdisciplinary research field studying the behavior of condensed matter systems exposed to radiation. The paper highlights several relevant examples of recent advances in the field and provides a roadmap…

Area laws describe how entanglement entropy scales and thus provide important necessary conditions for efficient quantum many-body simulation, but they do not, by themselves, yield a direct measure of computational complexity. Here we…

Quantum Physics · Physics 2026-04-28 Anna O. Schouten , David A. Mazziotti

This document provides detailed descriptions of data acquisition and data analysis in support of the accompanying Article, cond-mat/0610721: Observation of the two-channel Kondo effect. Some of the most intriguing problems in solid state…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 R. M. Potok , I. G. Rau , Hadas Shtrikman , Yuval Oreg , D. Goldhaber-Gordon

Machine learning (ML) models for electronic structure typically rely on large datasets generated by computationally expensive Kohn-Sham density functional theory calculations, as it is not known a priori which portions of the data are…

The electron density of a molecule or material has recently received major attention as a target quantity of machine-learning models. A natural choice to construct a model that yields transferable and linear-scaling predictions is to…

Chemical Physics · Physics 2022-06-29 Andrea Grisafi , Alan M. Lewis , Mariana Rossi , Michele Ceriotti