Technical institutes
A team of researchers from Dalian University of Technology has developed a new implementation of a high-accuracy two-layer Boussinesq model for fluids physics, utilizing graphics processing units (GPUs) to achieve substantial computational speedups. The model, funded by the National Natural Science Foundation of China, has been extensively optimized to align
Technical institutes
Research conducted at Hefei University of Technology has extensively reviewed the Monte Carlo (MC) simulation method, a widely used approach for quantification and propagation of uncertainties in scattering simulation of light polarization in scattering media systems. The study, funded by the National Natural Science Foundation of China, provided a thorough
Technical institutes
Researchers from Technical University Munich (TU Munich) have developed a novel framework called chemtrain-deploy, which enables the model-agnostic deployment of Machine Learning Potentials (MLPs) in LAMMPS. This framework, chemtrain-deploy, allows users to exploit the functionality of LAMMPS and perform large-scale MLP-based MD simulations on multiple GPUs. The research demonstrates the
Technical institutes
A new study on the effects of supersonic gas jet impacts on coal fragmentation has been published in the Journal of Energy Engineering. The research team, led by Zhenxing Zhou from the University of Science and Technology Beijing, investigated the mechanisms and key parameters affecting coal-breaking capacity in coal seams.
Technical institutes
Italian researchers at the Italian Institute of Technology, led by Marco De Vivo, have made a groundbreaking discovery in the field of glioma research. Their study, published in PLOS One, reveals key structural determinants of the Michaelis complex of the R132H IDH1 mutant, a crucial therapeutic target for various brain
Artificial neural networks
Burn injuries trigger substantial inflammation, complicating wound healing and potentially leading to severe systemic complications. Understanding the immune response to burns is crucial for improving treatment. Researchers from the University of Amsterdam have developed a novel approach using neural networks to predict cytokine concentrations over time and space, which can
Technical institutes
New research from Indian Institute of Technology Hyderabad has investigated the properties of electrolytes diluted with fluorinated solvents, revealing potential improvements for Li-ion battery performance. The study, supported by the Science and Engineering Research Board, employed classical molecular dynamics simulations to examine the structure and dynamics of the electrolyte at
Technical institutes
A team of scientists from the Lanzhou University of Technology in Lanzhou, People's Republic of China, has made a groundbreaking discovery regarding the dynamics of information dissemination in fractal social networks. According to a study published in the journal Communications in Nonlinear Science and Numerical Simulation, the researchers
Technical institutes
Research from Istanbul Technical University has highlighted the importance of advanced models in transitioning to green energy, with a focus on agent-based modeling (ABM) and multi-agent systems. Machine learning (ML) methods are being integrated into ABM to simulate complex energy systems, including renewable power plants, electric vehicles, and battery energy
Technical institutes
New research out of Gdansk, Poland, has shed light on the potential of integrating simulations with machine learning to refine molecular docking for flexible ligands like glycosaminoglycans (GAGs). Glycosaminoglycans are linear, negatively charged carbohydrates that modulate enzymatic activity in the extracellular matrix, posing challenges for both experimental and computational studies.
Artificial neural networks
Researchers at Purdue University have made a groundbreaking discovery in materials science, leveraging the power of graph neural networks and high-throughput density functional theory (DFT) simulations to identify 28 new high-pressure stable phases and confirm 18 pressure-induced phase transitions. This innovative approach has significantly accelerated the discovery process, which was
Artificial neural networks
New research in Chemical Physics has revealed that nuclear quantum effects play a substantial role in the structure, dynamics, and phase behavior of water. The study, conducted by researchers at the University of Vienna, employed machine-learned neural network potentials to perform large-scale path-integral molecular dynamics simulations. The findings suggest that
