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Topological Insulators are the best thermoelectric materials involving a sophisticated physics beyond their solid state and electronic structure. We show that exists a topological contribution to the thermoelectric effect that arise between…

Mesoscale and Nanoscale Physics · Physics 2019-04-24 Daniel Baldomir , Daniel Faílde

The rational design of two-dimensional piezoelectric materials has recently garnered great interest due to their increasing use in technological applications, including sensor technology, actuating devices, energy harvesting, and medical…

Mesoscale and Nanoscale Physics · Physics 2020-09-10 Tuğbey Kocabaş , Deniz Çakır , Cem Sevik

The understanding of methane emission and methane absorption plays a central role both in the atmosphere and on the surface of the Earth. Several important ecological processes, e.g., ebullition of methane and its natural microergodicity…

Statistics Theory · Mathematics 2015-07-21 Sándor Baran , Kinga Sikolya , Milan Stehlík

This study explores the integration of thermoelectric generators (TEGs) and phase change materials (PCMs) to enhance the efficiency of photovoltaic (PV) panels in high-temperature conditions. An AP-PM-20 Polycrystalline PV panel,…

Systems and Control · Electrical Eng. & Systems 2024-10-18 Tobechukwu Okamkpa , Joshua Okechukwu , Divine Mbachu , Chigbo Mgbemene

A first-principles based methodology for efficiently and accurately finding thermodynamically stable and metastable atomic structures is introduced and benchmarked. The approach is demonstrated for gas-phase metal-oxide clusters in…

For technical applications thermoelectric materials with a high figure of merit are desirable, and strongly correlated electron systems are very promising in this respect. Since effects of bandstructure_and_ electronic correlations play an…

Strongly Correlated Electrons · Physics 2015-05-13 K. Held , R. Arita , V. I. Anisimov , K. Kuroki

High throughput first-principles calculations, based on solving the quantum mechanical many-body problem for hundreds of materials in parallel, have been successfully applied to advance many materials-based technologies, from batteries to…

Materials Science · Physics 2023-04-28 Gabriele Losi , Omar Chehaimi , M. Clelia Righi

We demonstrate the possibility to build a thermoelectric engine using a one dimensional gas of molecules with unequal masses and hard-point interaction. Most importantly, we show that the efficiency of this engine is determined by a new…

Statistical Mechanics · Physics 2015-05-13 Jiao Wang , Giulio Casati , Tomaz Prosen , C. -H. Lai

The optimization of composition and processing to obtain materials that exhibit desirable characteristics has historically relied on a combination of scientist intuition, trial and error, and luck. We propose a methodology that can…

Machine Learning · Statistics 2017-07-20 Julia Ling , Max Hutchinson , Erin Antono , Sean Paradiso , Bryce Meredig

Thermoelectric (TE) heat pumps are a promising solid-state technology for space cooling and heating owing to their unique advantages such as environmental friendliness with no harmful refrigerants, small form factors, low noise, robustness…

Applied Physics · Physics 2024-10-15 Je-Hyeong Bahk , Thiraj D. Mohankumar , Abhishek Saini , Sarah J. Watzman

In this work, we propose a new estimation method of a Structural Equation Model. Our method is based on the EM likelihood-maximization algorithm. We show that this method provides estimators, not only of the coefficients of the model, but…

Statistics Theory · Mathematics 2015-10-02 Xavier Bry , Christian Lavergne , Myriam Tami

Databases compiled using ab-initio and symmetry-based calculations now contain tens of thousands of topological insulators and topological semimetals. This makes the application of modern machine learning methods to topological materials…

Materials Science · Physics 2020-07-01 Nikolas Claussen , B. Andrei Bernevig , Nicolas Regnault

An overall objective of energy efficiency in the built environment is to improve building and systems performances in terms of durability, comfort and economics. In order to predict, improve and meet a certain set of performance…

Computational Engineering, Finance, and Science · Computer Science 2016-06-07 A. W. M. van Schijndel

Industrial processes release substantial quantities of waste heat, which can be harvested to generate electricity. At present, the conversion of low grade waste heat to electricity relies solely on thermoelectric materials, but such…

Applied Physics · Physics 2021-01-27 Daniel Dzekan , Anja Waske , Kornelius Nielsch , Sebastian Fähler

This work builds on the previous introduction [1] of a coupled experimental-computational system devised to fully characterize the thermal behavior of complex 3D submicron electronic devices. The new system replaces the laser-based surface…

Materials Science · Physics 2007-09-13 Peter E. Raad , Pavel L. Komarov , M. Burzo

Photostriction is a phenomenon that can potentially improve the precision of light-driven actuation, the sensitivity of photodetection, and the efficiency of optical energy harvesting. However, known materials with significant…

Materials Science · Physics 2024-08-21 Zeyu Xiang , Yubi Chen , Yujie Quan , Bolin Liao

The first-principles-based effective Hamiltonian scheme provides one of the most accurate modeling technique for large-scale structures, especially for ferroelectrics. However, the parameterization of the effective Hamiltonian is…

Th$_3$Te$_4$ materials are potential candidates for commercial thermoelectric (TE) materials at high-temperature due to their superior physical properties. We incorporate the multiband Boltzmann transport equations with firstprinciples…

Materials Science · Physics 2023-01-10 Jizhu Hu Jinxin Zhong Jun Zhou

A new thermoelectric effect mechanism inspired by an autonomous Maxwell's demon [P. Strasberg, G. Schaller, T. Brandes, and M. Esposito, Phys. Rev. Lett. 110, 040601 (2013)] is proposed. In contrast to the former work where a model for…

Mesoscale and Nanoscale Physics · Physics 2020-12-07 Yugo Onishi , Naoto Nagaosa

Recent scientific advances require complex experiment design, necessitating the meticulous tuning of many experiment parameters. Tree-structured Parzen estimator (TPE) is a widely used Bayesian optimization method in recent parameter tuning…

Machine Learning · Computer Science 2025-10-01 Shuhei Watanabe
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