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Related papers: Machine Learning Potentials for Hydrogen Absorptio…

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Confinement of water and methane in mesopores of hydrophobized SBA-15 is demonstrated to promote methane hydrate formation. In comparison to as-synthesized SBA-15, hydrophobization by C8 grafting accelerates the kinetics of methane storage…

The number of published Machine Learning Interatomic Potentials (MLIPs) has increased significantly in recent years. These new data-driven potential energy approximations often lack the physics-based foundations that inform many…

Materials Science · Physics 2024-04-02 Kimia Ghaffari , Salil Bavdekar , Douglas E. Spearot , Ghatu Subhash

Molten salts are promising candidates in numerous clean energy applications, where challenges in experimental methods limit knowledge of their safety-critical temperature-properties correlations. Herein, we developed and employed machine…

Chemical Physics · Physics 2024-10-24 Rajni Chahal , Luke D Gibson , Santanu Roy , Vyacheslav S Bryantsev

Machine-learning interatomic potentials (MLPs) are fast, data-driven surrogate models of atomistic systems' potential energy surfaces that can accelerate ab-initio molecular dynamics (MD) simulations by several orders of magnitude. The…

Materials Science · Physics 2024-09-23 Thomas Bischoff , Bastian Jäckl , Matthias Rupp

Hydrogen uptake in complex multicomponent alloys, including high-entropy alloys (HEAs), governs both hydrogen storage capacity and resistance to hydrogen-induced degradation. We combine high-pressure experiments, density-functional theory…

Understanding and optimizing polysulfide adsorption and conversion processes are critical to mitigating shuttle effects and sluggish redox kinetics in lithium-sulfur batteries (LSBs). Here, we introduce a machine-learning-accelerated…

Materials Science · Physics 2025-10-20 Sahil Kumar , Adithya Maurya K R , Mudit Dixit

Hydrogen bubble formation within nanoscale voids is a critical mechanism underlying the embrittlement of metallic materials, yet its atomistic origins remains elusive. Here, we present an accurate and transferable machine-learned potential…

Materials Science · Physics 2026-03-16 Yu Bao , Keke Song , Jiahui Liu , Yanzhou Wang , Yifei Ning , Penghua Ying , Ping Qian

Gas hydrates are systems of prime importance. In particular, hydrogen hydrates are potential materials of icy satellites and comets, and may be used for hydrogen storage. We explore the H2O-H2 system at pressures in the range 0-100 GPa with…

Materials Science · Physics 2014-04-01 Guang-Rui Qian , Andriy O. Lyakhov , Qiang Zhu , Artem R. Oganov , Xiao Dong

We report on the hydrogen sorption investigation of the mixed alkali cluster intercalated fulleride series NaxLi6-xC60. These compounds are isostructural to Na6C60 and Li6C60 while the cubic lattice parameter is linearly dependent on x. The…

We report results from our mini-survey for molecular hydrogen in eight high redshift damped Lyman-alpha (DLA) systems using the ESO Ultra-violet and Visible Spectrograph on the VLT. In addition, we investigate two systems using ESO public…

Astrophysics · Physics 2007-05-23 Patrick Petitjean , R. Srianand , Cédric Ledoux

Hydrogen embrittlement remains a critical challenge in structural and electronic applications of copper (Cu) but its mechanism is still not fully understood. In this study, we combine density functional theory (DFT) and bond-order potential…

Materials Science · Physics 2026-03-17 Vasileios Fotopoulos , Alexander L. Shluger

Binding energies (BEs) of adsorbates on interstellar dust grains critically control adsorption, desorption, diffusion, and surface reactivity, and therefore strongly influence astrochemical models of star- and planet-forming regions. While…

Chemical Physics · Physics 2026-02-12 Anant Vaishnav , Niels M. Mikkelsen , Mie Andersen

We present a first-principles study of geometrical structure and energetics of hydrogen adsorbed on hexagonal single-walled silicon nanotubes (SiNTs). The adsorption behaviors of hydrogen molecules in SiNTs are investigated. The binding…

Materials Science · Physics 2009-01-09 Junga Ryou , Suklyun Hong , Gunn Kim

The transport of excess protons and hydroxide ions in water underlies numerous important chemical and biological processes. Accurately simulating the associated transport mechanisms ideally requires utilizing ab initio molecular dynamics…

Chemical Physics · Physics 2023-08-15 Austin O. Atsango , Tobias Morawietz , Ondrej Marsalek , Thomas E. Markland

The hydrogen adsorption sites in MOF5 were determined using neutron powder diffraction along with first-principles calculations. The metal-oxide cluster is primarily responsible for the adsorption while the organic linker plays only a…

Materials Science · Physics 2009-11-11 T. Yildirim , M. R. Hartman

Hydrogen adsorption by the metal organic framework (MOF) structure Zn2(BDC)2(TED) is investigated using a combination of experimental and theoretical methods. By use of the nonempirical van der Waals density-functional (vdW-DF) approach, it…

Materials Science · Physics 2009-11-13 Lingzhu Kong , Valentino R. Cooper , Nour Nijem , Kunhao Li , Jing Li , Yves J. Chabal , David C. Langreth

Hydrogen is one of the few molecules which has been incarcerated in the molecular cage of C$_{60}$ and forms endohedral supramolecular complex H$_2$@C$_{60}$. In this confinement hydrogen acquires new properties. Its translational motion…

Hydrogen in metals is a significant research area with far-reaching implications, encompassing diverse fields such as hydrogen storage, metal-insulator transitions, and the recently emerging phenomenon of room-temperature ($\textit{$T_C$}$)…

Superconductivity · Physics 2023-11-30 Heejung Kim , Ina Park , J. H. Shim , D. Y. Kim

Searching for superconducting hydrides has so far largely focused on finding materials exhibiting the highest possible critical temperatures ($T_c$). This has led to a bias towards materials stabilised at very high pressures, which…

Superconductivity · Physics 2020-04-29 Michael J. Hutcheon , Alice M. Shipley , Richard J. Needs

First-principles computations are the driving force behind numerous discoveries of hydride-based superconductors, mostly at high pressures, during the last decade. Machine-learning (ML) approaches can further accelerate the future…

Superconductivity · Physics 2023-06-01 Huan Tran , Tuoc N. Vu