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Implicit time integration is key to robustly simulating stiff materials and large deformations, but its performance is often dominated by repeatedly solving large linear systems. Adaptive coarsening can reduce this cost by concentrating…
Owing to the excellent catalysis properties of Ag-Au binary nanoalloy, nanostructured Ag-Au, such as Ag-Au nanoparticles and nanopillars, have been under intense investigation. To achieve high accuracy in molecular simulations of the Ag-Au…
Motivated by experimentally observed biocompatibility enhancement of nanoengineered cubic zirconia ZrO2 coatings to mesenchymal stromal cells, we have carried out computational analysis of the initial immobilization of one of known…
Concise and reliable modeling for aggregating power flexibility of distributed energy resources in active distribution networks (ADNs) is a crucial technique for coordinating transmission and distribution networks. Our recent research has…
We demonstrate how machine-learning based interatomic potentials can be used to model guest atoms in host structures. Specifically, we generate Gaussian approximation potential (GAP) models for the interaction of lithium atoms with…
The ion-bombardment induced nanopatterning of Si(001) has been simulated by atomistic simulations with and without Fe impurity. The surface contamination has been simulated by using a new force field developed for FeSi. This is a fitted…
Nanoindentation is vital for probing mechanical properties, yet traditional grid-based workflows are inefficient for targeting specific microstructural features. We present an automated nanoindentation framework that integrates machine…
Physics-based simulation is essential for developing and evaluating robot manipulation policies, particularly in scenarios involving deformable objects and complex contact interactions. However, existing simulators often struggle to balance…
Recently synthesized Porous 12-Atom-Wide Armchair Graphene Nanoribbons Nano Lett. 2024, 24, 10718-10723 exhibit tunable properties through periodic porosity, enabling precise control over their electronic, optical, thermal, and mechanical…
High-performance computing, together with a neural network model trained from data generated with first-principles methods, has greatly boosted applications of \textit{ab initio} molecular dynamics in terms of spatial and temporal scales on…
We report a novel hybrid method of simultaneous atomistic simulation of solids in critical regions (contacts surfaces, cracks areas, etc.), along with continuum modeling of other parts. The continuum is treated in terms of quasi-atoms of…
We develop and validate an interatomic potential for ruthenium based on the embedded atom method framework with the Finnis/Sinclair representation. We confirm that the new potential yields a stable hcp lattice with reasonable lattice and…
Quantum computing has shown great potential in various quantum chemical applications such as drug discovery, material design, and catalyst optimization. Although significant progress has been made in quantum simulation of simple molecules,…
Faceted shapes, such as polyhedra, are commonly found in systems of nanoscale, colloidal, and granular particles. Many interesting physical phenomena, like crystal nucleation and growth, vacancy motion, and glassy dynamics are challenging…
Advanced manufacturing (AM) technologies, such as nanoscale additive manufacturing process, enable the fabrication of nanoscale architected materials which has received great attention due to their prominent properties. However, few studies…
LiDAR-based perception is central to autonomous driving and robotics, yet raw point clouds remain highly vulnerable to noise, occlusion, and adversarial corruptions. Autoencoders offer a natural framework for denoising and reconstruction,…
Onset of vacuum arcing near a metal surface is often associated with nanoscale asperities, which may dynamically appear due to different processes ongoing in the surface and subsurface layers in the presence of high electric fields.…
We present a tight-binding potential for transition metals, carbon, and transition metal carbides, which has been optimized through a systematic fitting procedure. A minimal basis, including the s, p electrons of carbon and the d electrons…
Molecular dynamics simulation is employed to understand the thermodynamic behavior of cuboctahedron (cub) and icosahedron (ico) nanoparticles with 2-20 number of full shells. The original embedded atom method (EAM) was compared to the more…
This work presents a comprehensive benchmark of different quantisation techniques for convolutional neural networks applied to neutrino interaction recognition. Utilising simulation for a generic liquid argon time-projection chamber, models…