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Finding new superconductors with a high critical temperature ($T_c$) has been a challenging task due to computational and experimental costs. We present a diffusion model inspired by the computer vision community to generate new…

Superconductivity · Physics 2023-07-28 Daniel Wines , Tian Xie , Kamal Choudhary

Recent interest in structure solution and refinement using electron diffraction (ED) has been fuelled by its inherent advantages when applied to crystals of sub-micron size, as well as a better sensitivity to light elements. Currently, data…

Computational Physics · Physics 2022-08-23 Anton Cleverley , Richard Beanland

Transmission electron diffraction is a powerful and versatile structural probe for the characterization of a broad range of materials, from nanocrystalline thin films to single crystals. With recent developments in fast electron detectors…

Materials Science · Physics 2021-10-06 Jian-Min Zuo , Renliang Yuan , Yu-Tsun Shao , Haw-Wen Hsiao , Saran Pidaparthy , Yang Hu , Qun Yang , Jiong Zhang

This report extends our recent progress in tackling a challenging 3D inverse scattering problem governed by the Helmholtz equation. Our target application is to reconstruct dielectric constants, electric conductivities and shapes of front…

Colloidal self-assembly -- the spontaneous organization of colloids into ordered structures -- has been considered key to produce next-generation materials. However, the present-day staggering variety of colloidal building blocks and the…

Soft Condensed Matter · Physics 2021-06-29 Gabriele Maria Coli , Emanuele Boattini , Laura Filion , Marjolein Dijkstra

Singlet fission has emerged as one of the most exciting phenomena known to improve the efficiencies of different types of solar cells and has found uses in diverse optoelectronic applications. The range of available singlet fission…

Generative machine learning models have revolutionized material discovery by capturing complex structure-property relationships, yet extending these approaches to the inverse design of three-dimensional metamaterials remains limited by…

Computational Engineering, Finance, and Science · Computer Science 2026-04-27 Li Zheng , Siddhant Kumar , Dennis M. Kochmann

We introduce Diffusion Active Learning, a novel approach that combines generative diffusion modeling with data-driven sequential experimental design to adaptively acquire data for inverse problems. Although broadly applicable, we focus on…

Machine Learning · Computer Science 2025-04-07 Luis Barba , Johannes Kirschner , Tomas Aidukas , Manuel Guizar-Sicairos , Benjamín Béjar

The revolution in materials in the past century was built on a knowledge of the atomic arrangements and the structure-property relationship. The sine qua non for obtaining quantitative structural information is single crystal…

Computational Physics · Physics 2023-12-27 Gabe Guo , Judah Goldfeder , Ling Lan , Aniv Ray , Albert Hanming Yang , Boyuan Chen , Simon JL Billinge , Hod Lipson

We demonstrate a motion-free intensity diffraction tomography technique that enables direct inversion of 3D phase and absorption from intensity-only measurements for weakly scattering samples. We derive a novel linear forward model,…

Image and Video Processing · Electrical Eng. & Systems 2018-06-26 Ruilong Ling , Waleed Tahir , Hsing-Ying Lin , Hakho Lee , Lei Tian

Hydrogenation of amorphous silicon (a-Si:H) is critical for reducing defect densities, passivating mid-gap states and surfaces, and improving photoconductivity in silicon-based electro-optical devices. Modelling the atomic scale structure…

Waveform inversion is theoretically a powerful tool to reconstruct subsurface structures, but a usually encountered problem is that accurate sources are very rare, causing the computation unstable and divergent. This challenging problem,…

Geophysics · Physics 2024-07-12 Han Yu

Amorphous (disordered) materials are solids that have shown great potential in various domains, including energy storage, thermal management, and advanced materials. Unlike crystalline materials that can be described by unit cells…

Machine Learning · Computer Science 2026-05-01 Yan Lin , Jilin Hu , N. M. Anoop Krishnan , Morten M. Smedskjaer

Crystalline materials, with symmetrical and periodic structures, exhibit a wide spectrum of properties and have been widely used in numerous applications across electronics, energy, and beyond. For crystalline materials discovery,…

Computational Engineering, Finance, and Science · Computer Science 2026-02-11 Zhenzhong Wang , Haowei Hua , Wanyu Lin , Ming Yang , Kay Chen Tan

An inversion method for time-resolved data from ultrafast experiments is introduced, based on forward-optimisation in a trajectory basis. The method is applied to experimental data from x-ray scattering of the photochemical ring-opening…

Chemical Physics · Physics 2024-10-28 Kyle Acheson , Adam Kirrander

Amorphous carbon (a-C) materials have diverse interesting and useful properties, but the understanding of their atomic-scale structures is still incomplete. Here, we report on extensive atomistic simulations of the deposition and growth of…

Materials Science · Physics 2020-11-05 Miguel A. Caro , Gábor Csányi , Tomi Laurila , Volker L. Deringer

We discuss a novel approach that allows to obtain effective potentials from ab initio trajectories. Our method consists in fitting the weighted radial distribution functions obtained from the ab initio data with the ones obtained from…

Disordered Systems and Neural Networks · Physics 2018-02-28 Antoine Carre , Simona Ispas , Jurgen Horbach , Walter Kob

In an expansion of a previous study [1], we apply inverse design methods to produce two-dimensional plasma metamaterial devices with realistic plasma elements which incorporate quartz envelopes, collisionality (loss), non-uniform density…

Applied Physics · Physics 2022-10-31 Jesse A Rodriguez , Mark A. Cappelli

The structural evolution of laser-excited systems of gold has previously been measured through ultrafast MeV electron diffraction. However, there has been a long-standing inability of atomistic simulations to provide a consistent picture of…

Materials Science · Physics 2024-06-19 J. M. Molina , T. G. White

Negative refraction is known to occur in materials that simultaneously possess a negative electric permittivity and magnetic permeability; hence they are termed negative index materials. However, there are no known natural materials that…