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A modified electron beam induced deposition method using a parallel beam of electrons is developed. The method relies on the build-up of surface potential on an insulating surface exposed to an electron beam. Presence of sharp edges on the…
Two types of approaches to modeling molecular systems have demonstrated high practical efficiency. Density functional theory (DFT), the most widely used quantum chemical method, is a physical approach predicting energies and electron…
A neuroevolution potential (NEP) for the ternary $\alpha$-Fe--C--H system was developed based on a database generated from spin-polarized density functional theory (DFT) calculations, achieving empirical potential efficiency with DFT…
This work investigates the change in cell survival predicted by the local effect model (LEM) for an irradiated cell containing metal nanoparticles (MNPs) depending on the distribution of neighboring cells and the uptake of MNPs into the…
The central approximation made in classical molecular dynamics simulation of materials is the interatomic potential used to calculate the forces on the atoms. Great effort and ingenuity is required to construct viable functional forms and…
In the last years, the potential of using ionic liquids (IL)s as an environment for nanoparticle (NP) synthesis has been demonstrated and in particular, triggering NP formation in ILs by electron irradiation has been reported as a very…
Over the past decade inter-atomic potentials based on machine-learning (ML) techniques have become an indispensable tool in the atomic-scale modeling of materials. Trained on energies and forces obtained from electronic-structure…
Deep neural networks (DNNs) have been used to successfully predict molecular properties calculated based on the Kohn--Sham density functional theory (KS-DFT). Although this prediction is fast and accurate, we believe that a DNN model for…
We demonstrate that a high-dimensional neural network potential (HDNNP) can predict the lattice thermal conductivity of semiconducting materials with an accuracy comparable to that of density functional theory (DFT) calculation. After a…
Understanding the behavior of materials under irradiation is crucial for the design and safety of nuclear reactors, spacecraft, and other radiation environments. The threshold displacement energy (Ed) is a critical parameter for…
Compared with traditional fuels, emulsified fuels can improve fuel atomization and combustion, and nanoparticles as additives have the potential to enhance combustion and reduce emissions. Previous studies on micro-explosion mainly…
Fluids in nanopores are of importance for many engineering applications, including energy storage in supercapacitors, hydrocarbons recovery from unconventional sources, or water desalination. Thermodynamic properties of fluids confined in…
We determine the limit of the lowest achievable photoemitted electron temperature, and therefore the maximum achievable electron brightness, due to heating just after emission into vacuum, applicable to dense relativistic or nonrelativistic…
Machine-learning potentials are usually trained on the ground-state, Born-Oppenheimer energy surface, which depends exclusively on the atomic positions and not on the simulation temperature. This disregards the effect of thermally-excited…
Heat-based cancer treatment, so-called hyperthermia, can be used to destroy tumour cells directly or to make them more susceptible to chemotherapy or radiation therapy. To apply heat locally, iron oxide nanoparticles are injected into the…
This study explores nanoparticle-assisted electron injection as a method for controlling beam charge in laser wakefield acceleration through particle-in-cell simulations. We systematically investigate how the material (Li through Au) and…
Simulating water from first principles remains a significant computational challenge due to the slow dynamics of the underlying system. Although machine-learned interatomic potentials (MLPs) can accelerate these simulations, they often fail…
We calculate density profiles of a simple model fluid in contact with a planar surface using density functional theory (DFT), in particular for the case where there is a vapour layer intruding between the wall and the bulk liquid. We apply…
Electron-ion interactions play a central role for the energy relaxation processes and ultra-fast structure dynamics in laser-heated matter. The accurate prediction of the electron-ion energy exchange in a transient excited two-temperature…
The accurate and precise extraction of information from a modern particle physics detector, such as an electromagnetic calorimeter, may be complicated and challenging. In order to overcome the difficulties we propose processing the detector…