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Related papers: Precursor-Dependent Energetics as a Predictive Pri…

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BaTiO3 (BTO) is one of the most interesting classes of perovskite materials. The present study has been complied to explore some physical properties such as mechanical, vibrational, thermo-physical, and temperature dependent thermodynamic…

Materials Science · Physics 2025-12-11 Arpon Chakraborty , M. N. H. Liton , M. S. I. Sarker , M. M. Rahman , M. K. R. Khan

Controlling the polymorph formation in organic semiconductor thin films by the choice of substrate and deposition temperature is a key factor for targeted device performance. Small molecular semiconductors such as the quadrupolar…

Materials Science · Physics 2022-07-22 Frank Balzer , Tobias Breuer , Gregor Witte , Manuela Schiek

Zn(imidazolate)$_2$ metal-organic frameworks (MOFs) exhibit a remarkable degree of polymorphism. Because of their promising industrial applications, many research groups have investigated phase transitions, phase diagram and relative…

Materials Science · Physics 2026-05-01 Emilio Méndez , Rocio Semino

Recent experiments have shown that the striking structure formation in dewetting films of evaporating colloidal nanoparticle suspensions occurs in an ultrathin `postcursor' layer that is left behind by a mesoscopic dewetting front. Various…

Soft Condensed Matter · Physics 2010-02-04 A. J. Archer , M. J. Robbins , U. Thiele

Atomic layer deposition (ALD) is a promising technique to functionalize particle surfaces for energy applications including energy storage, catalysis, and decarbonization. In this work, we present a set of models of ALD particle coating to…

Materials Science · Physics 2024-12-04 Angel Yanguas-Gil , Jeffrey W. Elam

Aluminum oxide thin films were deposited on silicon substrates under different deposition conditions using pulse pressure metal organic chemical vapour deposition (PP-MOCVD). The current study investigates into the growth mechanism of the…

Materials Science · Physics 2016-08-23 Hari Murthy , S. S Miya , Susan Krumdieck

The use of deep learning methods for modeling fluid flow has drawn a lot of attention in the past few years. In situations where conventional numerical approaches can be computationally expensive, these techniques have shown promise in…

The multivariable theory of nucleation [J. Chem. Phys. 124, 124512 (2006)] is applied to the problem of vapor bubbles formation in pure liquids. The presented self-consistent macroscopic theory of this process employs thermodynamics…

Soft Condensed Matter · Physics 2012-05-03 Nikolay V. Alekseechkin

Multimodal molecular representation learning, which jointly models molecular graphs and their textual descriptions, enhances predictive accuracy and interpretability by enabling more robust and reliable predictions of drug toxicity,…

Machine Learning · Computer Science 2025-10-21 Yingxu Wang , Kunyu Zhang , Jiaxin Huang , Nan Yin , Siwei Liu , Eran Segal

Vapor deposition on polycrystalline films can lead to staggering levels of compressive stress, exceeding even the yield strength of the films. Mysteriously, a significant part of this stress has a reversible nature: it disappears when the…

Materials Science · Physics 2016-03-23 Amirmehdi Saedi , Marcel J. Rost

Synthesis prediction is a key accelerator for the rapid design of advanced materials. However, determining synthesis variables such as the choice of precursor materials is challenging for inorganic materials because the sequence of…

Materials Science · Physics 2023-06-13 Tanjin He , Haoyan Huo , Christopher J. Bartel , Zheren Wang , Kevin Cruse , Gerbrand Ceder

Predictions of nuclear properties far from measured data are inherently imprecise because of uncertainties in our knowledge of nuclear forces and in our treatment of quantum many-body effects in strongly-interacting systems. While the model…

Nuclear Theory · Physics 2022-09-14 Rodrigo Navarro Perez , Nicolas Schunck

Molecular generative models often assume meaningful latent geometry, but apparent property predictability can reflect sequence-level shortcuts rather than chemical organization. We study this issue in an unsupervised autoregressive…

Machine Learning · Computer Science 2026-05-08 Zakaria Elabid , Jan Andrzejewski , Bartosz Brzoza , Attila Cangi

Due to the lack of phase information, determining the physical parameters of multilayer thin films from measured neutron and X-ray reflectivity curves is, on a fundamental level, an underdetermined inverse problem. This so-called phase…

Predicting phase stabilities of crystal polymorphs is central to computational materials science and chemistry. Such predictions are challenging because they first require searching for potential energy minima and then performing arduous…

Materials Science · Physics 2020-07-15 Aleks Reinhardt , Chris J. Pickard , Bingqing Cheng

Ultra-lean premixed hydrogen combustion is a possible solution to decarbonize industry, while limiting flame temperatures and thus nitrous oxide emissions. These lean hydrogen/air flames experience strong preferential diffusion effects,…

Computational Physics · Physics 2025-08-13 Stijn N. J. Schepers , Jeroen A. van Oijen

Atomistic control of phase boundaries is crucial for optimizing the functional properties of solid-solution ferroelectrics, yet their microstructural mechanisms remain elusive. Here, we harness machine-learning-driven molecular dynamics to…

Materials Science · Physics 2025-05-09 Weiru Wen , Fan-Da Zeng , Ben Xu , Bi Ke , Zhipeng Xing , Hao-Cheng Thong , Ke Wang

Electron beam induced deposition with tungsten hexacarbonyl W(CO)6 as precursors leads to granular deposits with varying compositions of tungsten, carbon and oxygen. Depending on the deposition conditions, the deposits are insulating or…

Materials Science · Physics 2015-03-20 Kaliappan Muthukumar , Roser Valenti , Harald O. Jeschke

This paper presents a mechanically bistable mechanism of the compressed pre-curved beam. A governing equation is proposed which can be used to predict and explain the bistability of the compressed pre-curved beam. FE simulations and…

Applied Physics · Physics 2022-11-02 Fan Liu , Zian Jia , Xihang Jiang , Lifeng Wang

Denoising Diffusion models have shown remarkable performance in generating diverse, high quality images from text. Numerous techniques have been proposed on top of or in alignment with models like Stable Diffusion and Imagen that generate…

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