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Two-dimensional (2D) materials have wide applications in superconductors, quantum, and topological materials. However, their rational design is not well established, and currently less than 6,000 experimentally synthesized 2D materials have…

Materials Science · Physics 2023-01-18 Rongzhi Dong , Yuqi Song , Edirisuriya M. D. Siriwardane , Jianjun Hu

Harnessing the wave-nature of charge carriers in solid state devices, electron optics investigates and exploits coherent phenomena, in analogy with optics and photonics. Typically, this requires complex electronic devices leveraging…

Electrides are exotic compounds in which excess electrons occupy interstitial regions of the crystal lattice and serve as anions, exhibiting exceptional properties such as low work function, high electron mobility, and strong catalytic…

Materials Science · Physics 2026-01-30 Shuo Tao , Qiang Zhu

Interdisciplinary collaboration in battery science is required for rapid evaluation of better compositions and materials. However, diverging domain vocabulary and non-compatible experimental results slow down cooperation. We critically…

Programmable structures are systems whose undeformed geometries and material property distributions are deliberately designed to achieve prescribed deformed configurations under specific loading conditions. Inflatable structures are a…

Computational Engineering, Finance, and Science · Computer Science 2025-08-19 Sara Karimi , Nikolaos N. Vlassis

Conjugated polymers are experiencing a surge of renewed interest due to their promising applications in various organic electronic devices. These include organic light-emitting diodes (OLEDs), field-effect transistors (FETs), and organic…

Materials Science · Physics 2025-09-24 Miguel Lagos , Miguel Kiwi , Rodrigo Paredes

The first part of this article centers on the fact that key features of the dynamical response of weakly-correlated materials (the alkalis, Al), have been found experimentally to differ qualitatively from simple-model behavior. In the…

Strongly Correlated Electrons · Physics 2007-05-23 Adolfo G. Eguiluz , Wei Ku

Generative models based on generative adversarial networks (GANs) and variational autoencoders (VAEs) have been widely studied in the fields of image generation, speech generation, and drug discovery, but, only a few studies have focused on…

Machine Learning · Computer Science 2019-10-28 Yoshihide Sawada , Koji Morikawa , Mikiya Fujii

In this paper, density functional theory calculations are used to explore the electronic and atomic reconstruction at interfaces between III-III/I-V oxides. In particular, at these interfaces, two dimensional electron gases (2DEGs) with…

Materials Science · Physics 2012-06-06 Valentino R. Cooper

Advances in generative artificial intelligence are transforming how metal-organic frameworks (MOFs) are designed and discovered. This Perspective introduces the shift from laborious enumeration of MOF candidates to generative approaches…

Generative model for 2D materials has shown significant promise in accelerating the material discovery process. The stability and performance of these materials are strongly influenced by their underlying symmetry. However, existing…

Materials Science · Physics 2025-09-30 Shihang Xu , Shibing Chu , Rami Mrad , Zhejun Zhang , Zhelin Li , Runxian Jiao , Yuanping Chen

The rising demand for high-performing batteries requires new technological concepts. To facilitate fast charge and discharge, hierarchically structured electrodes offer short diffusion paths in the active material. However, there are still…

Quantum-electrodynamical density-functional theory (QEDFT) provides a first-principles framework for describing materials coupled to quantized electromagnetic fields. While QEDFT has successfully captured cavity-induced modifications of…

Materials Science · Physics 2026-03-26 Benshu Fan , I-Te Lu , Michael Ruggenthaler , Angel Rubio

Porous flow-through electrodes are used as the core reactive component across electrochemical technologies. Controlling the fluid flow, species transport, and reactive environment is critical to attaining high performance. However,…

Thin films are gaining ground in photonics and optoelectronics, promising improvements in their efficiency and functionality as well as decreased material usage as compared to bulk technologies. However, proliferation of thin films would…

Optics · Physics 2021-11-12 Pyry Kivisaari , Mikko Partanen , Toufik Sadi , Jani Oksanen

Ab initio modeling of molecular electronics is nowadays routinely performed by combining the Density Functional Theory (DFT) and Nonequilibrium Green function (NEGF) techniques. This method has its roots in the current formula given by Meir…

Mesoscale and Nanoscale Physics · Physics 2009-11-11 A. P. Jauho

Predicting molecular conformations from molecular graphs is a fundamental problem in cheminformatics and drug discovery. Recently, significant progress has been achieved with machine learning approaches, especially with deep generative…

Machine Learning · Computer Science 2022-03-16 Minkai Xu , Lantao Yu , Yang Song , Chence Shi , Stefano Ermon , Jian Tang

Charge carrier mobility and recombination determine the performance of many opto-electronic devices such as solar cells, sensors and light-emitting diodes. Understanding how these parameters change as a function of material choice, charge…

Applied Physics · Physics 2025-06-30 Markus Hußner , Carsten Deibel , Roderick Charles Ian MacKenzie

The development of new battery materials, particularly novel cathode chemistries, is essential for enabling next generation energy storage technologies. In this work, we employ a multi-fidelity screening protocol combining the Energy-GNoME…

Materials Science · Physics 2026-02-11 Nada Alghamdi , Paolo de Angelis , Pietro Asinari , Eliodoro Chiavazzo

Higher loading of active electrode materials is desired in batteries, especially those based on conversion reactions, for enhanced energy density and cost efficiency. However, increasing active material loading in electrodes can cause…

Machine Learning · Computer Science 2024-12-30 Vidushi Sharma , Andy Tek , Khanh Nguyen , Max Giammona , Murtaza Zohair , Linda Sundberg , Young-Hye La