Latest Articles for Computational Chemistry

Researchers improve simulations to better understand electrolyte behavior and interactions.

Research advances in modeling complex electron behaviors in materials are crucial.

Examining how different salts impact water movement and interactions.

Exploring energy behavior in open quantum systems through magnetization and electron count.

DiffCSP improves the efficiency of predicting crystal structures using generative models.

Evaluating the effectiveness of deep learning in molecular docking accuracy and plausibility.

Machine learning improves the accuracy of predicting crystal structures for new material development.

New method enhances molecular simulations and analysis in computational chemistry.

New automated approach enhances vibrational spectroscopy calculations for complex materials.

This study evaluates advanced GNNs for generating molecular graphs more effectively.

New methods improve understanding of ion interactions in simulations.

Researchers developed a method to create diverse 3D molecules using existing shapes.

ATM simplifies predicting binding energy for drug discovery.

A new method for efficient molecular modeling respecting physical symmetries.

A new method enhances efficiency in data collection for scientific machine learning.

TDMVCC enhances our ability to study molecular behavior over time.

Exploring a new method for precise excited state calculations in quantum systems.

New methods improve the study of molecular transitions in complex systems.

Exploring TDHF methods and quantum computing for dynamic electron system simulations.

New techniques improve energy calculations for large molecules with reduced errors.

A tool for efficient atomic interaction modeling in materials science.

Current methods using molecular fingerprints face significant limitations in drug development.

Exploring new methods for accurate simulation of quantum-classical interactions.

New algorithm improves crystal structure prediction using multi-objective strategies.

New Python library enhances low-energy structure search in materials science.

Explore how partial charges impact molecules and chemical bonds.

A new method for studying magnetic behavior in binuclear complexes is proposed.

Recent studies improve estimates of carbon monoxide adsorption energy on magnesium oxide surfaces.

Researchers develop an improved model for molecular interactions using atomic properties.

Explore how DFPT advances the study of phonons in materials.

A novel approach enhances accuracy in electron interaction energy calculations using the uniform electron gas model.

Research on HeC60 reveals important behaviors of trapped helium in fullerenes.

A new method improves predictions in materials science by considering spin currents.

New insights into transition metal fluorides improve computational predictions.

A new method improves uncertainty estimation in atomistic simulations with deep learning.

New methods improve molecular simulations through active learning and normalizing flows.

Explore how the committor aids in understanding molecular reactions.

A look into the fast reactions of cyclobutanone under light exposure.

Research uses machine learning to quickly predict properties of organic salt crystals.

Examining how cyclobutanone reacts when exposed to light.