相关论文: Exploring the impacts of conformer selection metho…
The primary target of this paper is to present novel compounds in view of their possible use as oxidizers in propulsion applications using molecular modeling calculations and supersonic flow simulations. Carbon-based heterocyclic compounds…
Electron capture processes for low energy Ar9+ ions colliding on Ar2 dimer targets are investigated, focusing attention on charge sharing as a function of molecule orientation and impact parameter. A preference in charge-asymmetric…
The interpretation of defect models heavily relies on software metrics that are used to construct them. However, such software metrics are often correlated to defect models. Prior work often uses feature selection techniques to remove…
This study evaluates the uncertainty in nanodosimetric calculations caused by variations in interaction cross sections within Monte Carlo Track Structure (MCTS) simulation codes. Nanodosimetry relies on accurately simulating particle…
We use an independent electron model with semi-classical approximation to electron dynamics to investigate differential cross sections for electron emission in fast collisions of protons with ammonia molecules. An effective potential model…
We report on the development of an original mesoscopic lattice model to predict structural, dynamical and capacitive properties of carbon-carbon supercapacitors. The model uses input from molecular simulations, such as free energy profiles…
To perform recognition, molecules must locate and specifically bind their targets within a noisy biochemical environment with many look-alikes. Molecular recognition processes, especially the induced-fit mechanism, are known to involve…
Current instance segmentation models achieve high performance on average predictions, but lack principled uncertainty quantification: their outputs are not calibrated, and there is no guarantee that a predicted mask is close to the ground…
Protein function does not solely depend on structure but often relies on dynamical transitions between distinct conformations. Despite this fact, our ability to characterize or predict protein dynamics is substantially less developed…
The quantitative structure-activity relationship (QSAR) regression model is a commonly used technique for predicting biological activities of compounds using their molecular descriptors. Predictions from QSAR models can help, for example,…
Accurate prediction of pure component physiochemical properties is crucial for process integration, multiscale modeling, and optimization. In this work, an enhanced framework for pure component property prediction by using explainable…
This paper presents a quantitative analysis of the impact of inelastic collisions with atoms in a crystalline environment on the channeling efficiency and intensity of the channeling radiation for high-energy electrons and positrons passing…
Hybrid quantum/molecular mechanics models (QM/MM methods) are widely used in material and molecular simulations when MM models do not provide sufficient accuracy but pure QM models are computationally prohibitive. Adaptive QM/MM coupling…
Extracting consistent statistics between relevant free-energy minima of a molecular system is essential for physics, chemistry and biology. Molecular dynamics (MD) simulations can aid in this task but are computationally expensive,…
Finding low-energy molecular conformers is challenging due to the high dimensionality of the search space and the computational cost of accurate quantum chemical methods for determining conformer structures and energies. Here, we combine…
Bolted joints are critical in engineering for maintaining structural integrity and reliability. Accurate prediction of parameters influencing their function and behavior is essential for optimal performance. Traditional methods often fail…
The Poisson-Boltzmann equation is a widely used model to study the electrostatics in molecular solvation. Its numerical solution using a boundary integral formulation requires a mesh on the molecular surface only, yielding accurate…
It is now possible to conduct large scale perturbation screens with complex readout modalities, such as different molecular profiles or high content cell images. While these open the way for systematic dissection of causal cell circuits,…
Machine-learning techniques are essential in modern collider research, yet their probabilistic outputs often lack calibrated uncertainty estimates and finite-sample guarantees, limiting their direct use in statistical inference and…
We study swelling and structural properties of ionic microgel suspensions within a comprehensive coarse-grained model that combines the polymeric and colloidal natures of microgels as permeable, compressible, charged spheres governed by…