Surface-limited galvanic replacement reactions of Pd, Pt, and Au onto Ag core nanoparticles through redox potential tuning

V Yadav, S Jeong, X Ye, CW Li - Chemistry of Materials, 2022 - ACS Publications
Galvanic replacement reactions (GRR) have served as a powerful synthetic strategy to
obtain hollow and morphologically complex bimetallic nanostructures. Extensive work has …

Alloying bulk-immiscible metals at the nanoscale: An XPS/STM study of bimetallic Ag-Pt/HOPG nanoparticles

AY Fedorov, AV Bukhtiyarov, MA Panafidin… - Applied Surface …, 2023 - Elsevier
The intentional tailoring of surface structure in bimetallic nanoparticles is of high interest for
academic research and industry, and many attempts have been made to improve the control …

Transfer learning aided high-throughput computational design of oxygen evolution reaction catalysts in acid conditions

S Wang, H Lin, Y Wakabayashi, LQ Zhou… - Journal of Energy …, 2023 - Elsevier
Sluggish oxygen evolution reaction (OER) in acid conditions is one of the bottlenecks that
prevent the wide adoption of proton exchange membrane water electrolyzer for green …

Surface functionalization of ZnO: Ag columnar thin films with AgAu and AgPt bimetallic alloy nanoparticles as an efficient pathway for highly sensitive gas …

A Vahl, O Lupan, D Santos-Carballal… - Journal of Materials …, 2020 - pubs.rsc.org
For a fast and reliable monitoring of hazardous environments, the discrimination and
detection of volatile organic compounds (VOCs) in the low ppm range is critically important …

High-throughput crystal structure solution using prototypes

SD Griesemer, L Ward, C Wolverton - Physical Review Materials, 2021 - APS
Databases of density functional theory (DFT) calculations, such as the Open Quantum
Materials Database (OQMD), have paved the way for accelerated materials discovery. DFT …

Machine-learning the configurational energy of multicomponent crystalline solids

AR Natarajan, A Van der Ven - npj Computational Materials, 2018 - nature.com
Abstract Machine learning tools such as neural networks and Gaussian process regression
are increasingly being implemented in the development of atomistic potentials. Here, we …

Detailed discussion on the structure of alloy nanoparticles synthesized via magnetron sputter deposition onto liquid poly (ethylene glycol)

MT Nguyen, P Pattanasattayavong… - Nanoscale …, 2024 - pubs.rsc.org
This paper is devoted to reviewing a decade of the development of vacuum sputter
deposition onto liquid poly (ethylene glycol)(PEG) to prepare metal and alloy nanoparticles …

Reversed size-dependent stabilization of ordered nanophases

J Pirart, A Front, D Rapetti… - Nature …, 2019 - nature.com
The size increase of a nanoscale material is commonly associated with the increased
stability of its ordered phases. Here we give a counterexample to this trend by considering …

[HTML][HTML] NJOY+ NCrystal: An open-source tool for creating thermal neutron scattering libraries with mixed elastic support

K Ramić, JIM Damian, T Kittelmann, DD Di Julio… - Nuclear Instruments and …, 2022 - Elsevier
In this work we present NJOY+ NCrystal, a tool to generate thermal neutron scattering
libraries with support for coherent and incoherent elastic components for crystalline solid …

The use of cluster expansions to predict the structures and properties of surfaces and nanostructured materials

L Cao, C Li, T Mueller - Journal of Chemical Information and …, 2018 - ACS Publications
The construction of cluster expansions parametrized by first-principles calculations is a
powerful tool for calculating properties of materials. In this Perspective, we discuss the …