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Recent works in inverse rendering have shown promise in using multi-view images of an object to recover shape, albedo, and materials. However, the recovered components often fail to render accurately under new lighting conditions due to the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Yehonathan Litman , Or Patashnik , Kangle Deng , Aviral Agrawal , Rushikesh Zawar , Fernando De la Torre , Shubham Tulsiani

We present an information-based total-energy optimization method to produce nearly defect-free structural models of amorphous silicon. Using geometrical, structural and topological information from disordered tetrahedral networks, we have…

Disordered Systems and Neural Networks · Physics 2019-01-28 Dil K. Limbu , Raymond Atta-Fynn , Parthapratim Biswas

A solution to the inversion problem of scattering would offer aberration-free diffraction-limited 3D images without the resolution and depth-of-field limitations of lens-based tomographic systems. Powerful algorithms are increasingly being…

Functional soft materials, comprising colloidal and molecular building blocks that self-organize into complex structures as a result of their tunable interactions, enable a wide array of technological applications. Inverse methods provide…

Soft Condensed Matter · Physics 2020-04-13 Zachary M. Sherman , Michael P. Howard , Beth A. Lindquist , Ryan B. Jadrich , Thomas M. Truskett

The Sudden Approximation is applied to invert structural data on randomly corrugated surfaces from inert atom scattering intensities. Several expressions relating experimental observables to surface statistical features are derived. The…

Materials Science · Physics 2016-08-31 Daniel A. Lidar

We show that the information gained in spectroscopic experiments regarding the number and distribution of atomic environments can be used as a valuable constraint in the refinement of the atomic-scale structures of nanostructured or…

Materials Science · Physics 2015-05-14 Matthew J Cliffe , Martin T. Dove , D. A. Drabold , Andrew L. Goodwin

Amorphous silicon (a-Si) models are analyzed for structural, electronic and vibrational characteristics. Several models of various sizes have been computationally fabricated for this analysis. It is shown that a recently developed…

Disordered Systems and Neural Networks · Physics 2018-11-29 Dale Igram , Bishal Bhattarai , Parthapratim Biswas , D. A. Drabold

Metamaterials are artificially engineered structures that manipulate electromagnetic waves, having optical properties absent in natural materials. Recently, machine learning for the inverse design of metamaterials has drawn attention.…

Diffusion models have found phenomenal success as expressive priors for solving inverse problems, but their extension beyond natural images to more structured scientific domains remains limited. Motivated by applications in materials…

Computer Vision and Pattern Recognition · Computer Science 2024-10-08 Timofey Efimov , Harry Dong , Megna Shah , Jeff Simmons , Sean Donegan , Yuejie Chi

Atomic scale simulations are a key element of modern science in that they allow to understand, and even predict, complex physical or chemical phenomena on the basis of the fundamental laws of nature. Among the different existing atomic…

Materials Science · Physics 2021-07-20 Alexandre Boulle , Alain Chartier , Aurélien Debelle , Xin Jin , Jean-Paul Crocombette

Inverse design problems are common in engineering and materials science. The forward direction, i.e., computing output quantities from design parameters, typically requires running a numerical simulation, such as a FEM, as an intermediate…

Machine Learning · Computer Science 2026-02-18 Jens U. Kreber , Christian Weißenfels , Joerg Stueckler

In this paper, we present new models of germanium selenide chalcogenide glasses heavily doped with silver. The models were readily obtained with ab initio molecular dynamics and their structure agrees closely with diffraction measurements.…

Disordered Systems and Neural Networks · Physics 2009-11-11 De Nyago Tafen , D. A. Drabold , M. Mitkova

Efficiently predicting properties of porous crystalline materials has great potential to accelerate the high throughput screening process for developing new materials, as simulations carried out using first principles model are often…

Machine Learning · Computer Science 2023-11-30 Marko Petković , Pablo Romero-Marimon , Vlado Menkovski , Sofia Calero

The correct insertion of virtual objects in images of real-world scenes requires a deep understanding of the scene's lighting, geometry and materials, as well as the image formation process. While recent large-scale diffusion models have…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Ruofan Liang , Zan Gojcic , Merlin Nimier-David , David Acuna , Nandita Vijaykumar , Sanja Fidler , Zian Wang

Using molecular dynamics (MD) simulation, we investigate the mechanical response of silicon to high dose ion-irradiation. We employ a realistic and efficient model to directly simulate ion beam induced amorphization. Structural properties…

Materials Science · Physics 2009-10-31 Keith M. Beardmore , Niels Gronbech-Jensen

Deep learning has demonstrated superb efficacy in processing imaging data, yet its suitability in solving challenging inverse problems in scientific imaging has not been fully explored. Of immense interest is the determination of local…

Materials Science · Physics 2019-02-20 Nouamane Laanait , Qian He , Albina Y. Borisevich

Point defects affect material properties by altering electronic states and modifying local bonding environments. However, high-throughput first-principles simulations of point defects are costly due to large simulation cells and complex…

The classical method of determining the atomic structure of complex molecules by analyzing diffraction patterns is currently undergoing drastic developments. Modern techniques for producing extremely bright and coherent X-ray lasers allow a…

Biomolecules · Quantitative Biology 2015-10-12 Tomas Ekeberg , Stefan Engblom , Jing Liu

An ideal atomistic model of a disordered material should contradict no experiments,and should also be consistent with accurate force fields (either {\it ab initio}or empirical). We make significant progress toward jointly satisfying {\it…

Materials Science · Physics 2016-08-31 Parthapratim Biswas , De Nyago Tafen , D. A. Drabold

We present Intrinsic Image Diffusion, a generative model for appearance decomposition of indoor scenes. Given a single input view, we sample multiple possible material explanations represented as albedo, roughness, and metallic maps.…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Peter Kocsis , Vincent Sitzmann , Matthias Nießner