Latest Articles for Computational Chemistry

Using machine learning to enhance the interpretability of molecular simulations.

A new dataset accelerates molecular property predictions for drug design.

This study investigates how molecules unfold under force using advanced simulations.

Investigating the benefits of non-nested data in machine learning for quantum chemistry.

Studying quantum and classical interactions in chemical processes using NEO theory.

A new method improves solvent modeling accuracy in computational studies.

LibRPA streamlines energy calculations in materials science for large systems.

ASkotch enhances kernel ridge regression efficiency for large datasets.

A software tool simplifies predictions of VOCs' behavior under sunlight exposure.

This article discusses using machine learning to speed up DFT calculations in materials science.

A novel QM/MM method enhances the study of enzymes using advanced computational techniques.

New methods enhance the study of rare molecular events.

Researchers break down complex molecules into fragments for better analysis.

Geo2Seq transforms 3D molecular structures into manageable sequences for efficient generation.

A new method enhances accuracy in calculating molecular energy differences.

New methods improve electron behavior modeling using machine learning techniques.

Researchers combine machine learning and Bayesian optimization to improve atomic structure arrangement.

Hot2Mol generates targeted molecules to disrupt harmful protein interactions.

New methods enhance analysis of complex molecular systems.

A computer model improves the study of schreibersite, a mineral linked to early life.

Study reveals efficient data sharing in ML models for battery technology.

A new method combines AI and quantum chemistry to solve complex equations efficiently.

A new method improves molecular interaction modeling using advanced charge representations.

Researchers improve predictions of standard hydrogen electrode potential using machine learning.

A new approach simplifies calculations in molecular chemistry using Slater determinants.

A new framework enhances accuracy in atomistic simulations through advanced force field optimization.

New methods enhance study of molecular behavior after light absorption.

The ACE method boosts computational efficiency in excited state calculations.

Researchers improve the RCMC method for faster and more reliable chemical reaction simulations.

A new dataset evaluates large language models for predicting material properties.

A new method improves the study of molecular interactions efficiently.

CAMP simplifies material simulations using Cartesian coordinates for better accuracy and efficiency.

MOLPIPx aids scientists in accurately modeling molecular movements using advanced techniques.

Scientists use algorithms to study how atoms change states, like liquid to ice.

Exploring the basics and significance of displaced fermionic Gaussian states in quantum mechanics.

Discover a new method enhancing molecular dynamics simulations with improved efficiency.

A new method enhances molecular dynamics simulations for speed and accuracy.

New methods are changing how scientists study electron behavior in atoms.

A new solver transforms how we calculate electron behaviors in materials.

Dive into non-covalent interactions and the S66 dataset of molecular pairs.