This paper addresses the critical challenge of tire-road contact dynamics in intelligent transportation systems, particularly for Level 4 autonomous driving. Traditional empirical models fail to accurately predict tire behavior on unstructured road s...
Understanding biomolecular function at the atomic scale requires detailed insight into the structural changes underlying dynamic processes. Vibrational infrared (IR) spectroscopy─when paired with biomolecular simulations and quantum-chemical calculat...
Cryo-EM and X-ray crystallography provide crucial experimental data for obtaining atomic-detail models of biomacromolecules. Refining these models relies on library-based stereochemical data, which, in addition to being limited to known chemical enti...
Journal of chemical information and modeling
Oct 16, 2025
Light-driven molecular nanomotors hold promise for applications in materials science and biomedicine. Significant efforts have focused on improving their efficiency, often targeting single candidate molecules. Here, we present a systematic, data-driv...
A significant amount of scholarship and funding has been dedicated to ethical and social studies of new and emerging science and technology (NEST), from nanotechnology to synthetic biology, and Artificial Intelligence. Quantum technologies comprise t...
Journal of chemical information and modeling
Sep 22, 2025
We present TeNNet-SAC (hermodynamics-mbedded eural work for egment ctivity oefficient) model, a novel machine learning framework for predicting activity coefficients in liquid mixtures using only the SMILES representations of the constituent molecule...
Journal of chemical information and modeling
Sep 10, 2025
The calculation of the highest occupied molecular orbital-lowest unoccupied molecular orbital (HOMO-LUMO) gap for chemical molecules is computationally intensive using quantum mechanics (QM) methods, while experimental determination is often costly a...
Computational methods have revolutionized NMR spectroscopy, driving significant advancements in structural biology and related fields. This review focuses on recent developments in quantum chemical and machine learning approaches for computational NM...
Journal of chemical information and modeling
Aug 27, 2025
Neural network potentials trained on quantum-mechanical data can calculate molecular interactions with relatively high speed and accuracy. However, not all neural network potentials are suitable for molecular simulations, as they might exhibit instab...
Quantum tunneling-based DNA sequencing promises to transform genomic analysis by improving long-read accuracy and enabling high-throughput sequencing, particularly the precise measurement of electrical conductance and tunneling current signatures ass...
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