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Dissolution of electrocatalysts during long-term and dynamic operation is a challenging problem in energy conversion and storage devices such as fuel cells and electrolyzers. To develop stable electrocatalysts, we adopt the design concept…

The 7\times7 reconstruction of the Si(111) surface represents arguably the most fascinating surface reconstruction so far observed in nature. Yet, the atomistic mechanism underpinning its formation remains unclear after it was discovered…

Materials Science · Physics 2021-05-05 Lin Hu , Bing Huang , Feng Liu

The expansiveness of compositional phase space is too vast to fully search using current theoretical tools for many emergent problems in condensed matter physics. The reliance on a deep chemical understanding is one method to identify local…

Superconductivity · Physics 2023-01-26 Lazar Novakovic , Ashkan Salamat , Keith V. Lawler

Metal surfaces have long been known to reconstruct, significantly influencing their structural and catalytic properties. Many key mechanistic aspects of these subtle transformations remain poorly understood due to limitations of previous…

Materials Science · Physics 2023-08-15 Cameron J. Owen , Yu Xie , Anders Johansson , Lixin Sun , Boris Kozinsky

Understanding and controlling nanoparticle coalescence is crucial for applications ranging from catalysis to nanodevice fabrication, yet the behavior of nanoparticles on dynamically evolving, heterogeneous substrates remains poorly…

Materials Science · Physics 2025-06-06 Cheng-Yu Chen , Duncan Burns , Peter W. Voorhees , Eric A. Stach

We construct a simple thermodynamic model to describe the melting of a supported metal nanoparticle with a spherically curved free surface both with and without surface melting. We use the model to investigate the results of recent…

Materials Science · Physics 2007-05-23 S. C. Hendy

First-row transition metal oxides and chalcogenides have been found to rival the performance of precious metal-based catalysts for the interconversion of water and O$_2$. The high lability of the first-row transition metal ions leads to…

Atomic structures of nanomaterials are inherently dynamic, continuously reshaped through interactions with chemical species and external stimuli. Such dynamics are further amplified as the size and dimensionality of nanomaterials are…

In recent years, machine learning interatomic potentials (MLIPs) have attracted significant attention as a method that enables large-scale, long-time atomistic simulations while maintaining accuracy comparable to electronic structure…

Materials Science · Physics 2025-03-27 Yuta Yoshimoto , Naoki Matsumura , Yuto Iwasaki , Hiroshi Nakao , Yasufumi Sakai

Determining the local coordination of the active site is a pre-requisite for the reliable modeling of single-atom catalysts (SACs). Obtaining such information is difficult on powder-based systems, so much emphasis is placed on density…

In this work, second-generation Car-Parrinello-based QM/MM molecular dynamics simulations of small nanoparticles of NbP, NbAs, TaAs and 1T-TaS$_2$ in water are presented. The first three materials are topological Weyl semimetals, which were…

A new mechanism for reactivity of multiply twinned gold nanoparticles resulting from their inherently strained structure provides a further explanation of the surprising catalytic activity of small gold nanoparticles. Atomic defect…

Chemical Physics · Physics 2017-07-26 Michael Walsh , Kenta Yoshida , Akihide Kuwabara , Mungo Pay , Pratibha Gai , Edward Boyes

Insight into structural and thermodynamic properties of nanoparticles is crucial for designing optimal catalysts with enhanced activity and stability. We present a semi-automated workflow for parameterizing the atomic cluster expansion…

Accurate knowledge of the atomistic transition pathways in materials and material surfaces is crucial for many material science problems. However, conventional simulation techniques used to find these transitions are extremely…

Materials Science · Physics 2026-05-01 Henry Tischler , Wenting Li , Qi Tang , Danny Perez , Thomas Vogel

Neural implicit representations have become a popular choice for modeling surfaces due to their adaptability in resolution and support for complex topology. While previous works have achieved impressive reconstruction quality by training on…

Computer Vision and Pattern Recognition · Computer Science 2024-08-12 Lu Sang , Abhishek Saroha , Maolin Gao , Daniel Cremers

The durability of passivable metals and alloys is often limited by the stability of the surface oxide film, the passive film, providing self-protection against corrosion in aggressive environments. Improving this stability requires to…

Materials Science · Physics 2019-07-26 Li Ma , Frederic Wiame , Vincent Maurice , Philippe Marcus

Simulations of Al thin film sputter depositions rely on accurate plasma and surface interaction models. Establishing the latter commonly requires a higher level of abstraction and means to dismiss the fundamental atomic fidelity. Previous…

Materials Science · Physics 2023-06-13 Tobias Gergs , Thomas Mussenbrock , Jan Trieschmann

The thousandfold increase in data-collection speed enabled by aberration-corrected optics allows us to overcome an electron microscopy paradox - how to obtain atomic-resolution chemical structure in individual nanoparticles, yet record a…

Molecular dynamics simulations are an important tool for describing the evolution of a chemical system with time. However, these simulations are inherently held back either by the prohibitive cost of accurate electronic structure theory…

Chemical Physics · Physics 2018-12-20 Michael Gastegger , Philipp Marquetand

A fundamental objective of materials modeling is identifying atomic structures that align with experimental observables. Conventional approaches for disordered materials involve sampling from thermodynamic ensembles and hoping for an…

Materials Science · Physics 2025-09-30 Tigany Zarrouk , Miguel A. Caro
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