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Metamaterial thermal energy devices obtained from transformation optics have recently attracted wide attention due to their vast potential in energy storage, thermal harvesting or heat manipulation. However, these devices usually require…

Piezoelectric materials are widely used in all kinds of industries such as electric cigarette lighters, diesel engines and x-ray shutters. However, discovering high-performance and environmentally friendly (e.g. lead-free) piezoelectric…

Materials Science · Physics 2022-02-09 Jeffrey Hu , Yuqi Song

The discovery of new superconducting materials, particularly those exhibiting high critical temperature ($T_c$), has been a vibrant area of study within the field of condensed matter physics. Conventional approaches primarily rely on…

Superconductivity · Physics 2025-05-14 Xiao-Qi Han , Zhenfeng Ouyang , Peng-Jie Guo , Hao Sun , Ze-Feng Gao , Zhong-Yi Lu

Thermal properties of nanomaterials are crucial to not only improving our fundamental understanding of condensed matter systems, but also to developing novel materials for applications spanning research and industry. Since quantum effects…

Quantum Physics · Physics 2022-08-26 Connor Powers , Lindsay Bassman Oftelie , Daan Camps , Wibe A. de Jong

The discovery of novel materials for thermoelectric energy conversion has potential to be accelerated by data-driven screening combined with high-throughput calculations. One way to increase the efficacy of successfully choosing a candidate…

The present theoretical study focuses on the structural, electronic and thermoelectric properties of PbTe, PbSe and their ternary alloys PbSe$_{x}$Te$_{1-x}$, using the density functional theory (DFT) by the full potential linearised…

Materials Science · Physics 2025-12-29 M. Kaid Slimane , B. N. Brahmi , M. Bouchenaki , S. Bekhechi

Traditional entropy-based methods - such as cross-entropy loss in classification problems - have long been essential tools for representing the information uncertainty and physical disorder in data and for developing artificial intelligence…

Machine Learning · Computer Science 2026-01-06 Shun Wang , Shun-Li Shang , Zi-Kui Liu , Wenrui Hao

Electronic-structure theory is a strong pillar of materials science. Many different computer codes that employ different approaches are used by the community to solve various scientific problems. Still, the precision of different packages…

Thermoelectric performance is of interest for numerous applications such as waste heat recovery and solid state energy conversion, and will be seen to be closely connected to topological insulator behavior. In this context we here report…

Materials Science · Physics 2015-01-26 Hongliang Shi , David Parker , Mao-Hua Du , David J. Singh

Nanostructured materials have emerged as an alternative to enhance the figure of merit (ZT) of thermoelectric (TE) devices. Graphene exhibits a high electrical conductivity (in-plane) that is necessary for a high ZT; however, this effect is…

Organic molecular crystals are ideally placed to become next-generation piezoelectric materials due to their diverse chemistries that can be used to engineer tailor-made solid-state assemblies. Using crystal engineering principles, and…

Materials Science · Physics 2024-12-11 Shubham Vishnoi , Geetu Kumari , Robert Guest , Pierre-André Cazade , Sarah Guerin

We develop a first-principles framework for evaluating the fundamental length scales of superconductivity, namely the coherence length $\xi_0$ and the magnetic penetration depth $\lambda_\mathrm{L}$, within superconducting density…

Superconductivity · Physics 2026-03-06 Mitsuaki Kawamura , Takuya Nomoto , Niklas Witt , Ryotaro Arita

The effective mass of charge carriers is a fundamental descriptor of the electronic structure of materials, and can be used to assess performance in electronics applications, or to screen for thermoelectrics and transparent conductors.…

Materials Science · Physics 2025-12-02 Szymon Błazucki , Junfeng Qiao , Nicola Marzari

Accurate prediction of the thermal and electrical conductivities of materials under extremely high temperatures is essential in high-energy-density physics. These properties govern processes such as stellar core dynamics, planetary magnetic…

Plasma Physics · Physics 2025-10-14 Qianrui Liu , Xiantu He , Mohan Chen

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

Finite temperature disordered solid solutions and magnetic materials are difficult to study directly using first principles calculations, due to the large unit cells and many independent samples that are required. In this work, we develop a…

Materials Science · Physics 2019-05-22 Kevin F. Garrity

Metal-insulator transition (MIT) materials are a useful platform for emerging microelectronic, optoelectronic, and neuromorphic devices, but their discovery is hindered by the high computational cost of electronic structure modeling, the…

Scientific progress increasingly depends on synthesizing knowledge across vast literature, yet most experimental data remains trapped in semi-structured formats that resist systematic extraction and analysis. Here, we present MatSKRAFT, a…

Information Retrieval · Computer Science 2025-09-15 Kausik Hira , Mohd Zaki , Mausam , N. M. Anoop Krishnan

In this work, we present an atomistic first-principles framework for modeling the low-temperature electronic and transport properties of disordered two-dimensional (2D) materials with randomly distributed point defects (impurities). The…

Mesoscale and Nanoscale Physics · Physics 2020-02-11 Kristen Kaasbjerg

We present a machine learning (ML) method for efficient computation of vibrational thermal expectation values of physical properties from first principles. Our approach is based on the non-perturbative frozen phonon formulation in which…

Materials Science · Physics 2026-03-16 Niraj Aryal , Sheng Zhang , Weiguo Yin , Gia-Wei Chern