OOIR: Observatory of International Research

Papers

(The H4-Index of Journal of Chemical Physics is 61. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-04-01 to 2024-04-01.)

Article	Citations
The ORCA quantum chemistry program package	1926
Scalable molecular dynamics on CPU and GPU architectures with NAMD	1533
CP2K: An electronic structure and molecular dynamics software package - Quickstep: Efficient and accurate electronic structure calculations	1376
Quantum ESPRESSO toward the exascale	797
Recent developments in the general atomic and molecular electronic structure system	723
TURBOMOLE: Modular program suite for ab initio quantum-chemical and condensed-matter simulations	616
The Molpro quantum chemistry package	603
Software for the frontiers of quantum chemistry: An overview of developments in the Q-Chem 5 package	523
PSI4 1.4: Open-source software for high-throughput quantum chemistry	436
NWChem: Past, present, and future	418
Recent developments in the PySCF program package	392
Coupled-cluster techniques for computational chemistry: The CFOUR program package	364
TRAVIS—A free analyzer for trajectories from molecular simulation	343
r2SCAN-3c: A “Swiss army knife” composite electronic-structure method	295
Modern quantum chemistry with [Open]Molcas	278
Heterogeneous parallelization and acceleration of molecular dynamics simulations in GROMACS	273
Siesta: Recent developments and applications	228
Numerically “exact” approach to open quantum dynamics: The hierarchical equations of motion (HEOM)	218
A fast and high-quality charge model for the next generation general AMBER force field	195
The DIRAC code for relativistic molecular calculations	189
CHARMM-GUI supports the Amber force fields	175
OrbNet: Deep learning for quantum chemistry using symmetry-adapted atomic-orbital features	149
Plasmonic hot electrons for sensing, photodetection, and solar energy applications: A perspective	142
An accurate and transferable machine learning potential for carbon	138
The CRYSTAL code, 1976–2020 and beyond, a long story	131

Pressure control using stochastic cell rescaling	113
Perspective on integrating machine learning into computational chemistry and materials science	109
Conformational transition of SARS-CoV-2 spike glycoprotein between its closed and open states	105
Solvation at metal/water interfaces: An ab initio molecular dynamics benchmark of common computational approaches	101
Coarse graining molecular dynamics with graph neural networks	100
The ONETEP linear-scaling density functional theory program	91
Δ -machine learning for potential energy surfaces: A PIP approach to bring a DFT-based PES to CCSD(T) level of theory	90
Liquid–liquid transition and polyamorphism	88
ReSpect: Relativistic spectroscopy DFT program package	88
TeraChem: Accelerating electronic structure and ab initio molecular dynamics with graphical processing units	86
From orbitals to observables and back	85
The physics of active polymers and filaments	85
Variational and diffusion quantum Monte Carlo calculations with the CASINO code	83
Simple model for the electric field and spatial distribution of ions in a microdroplet	83
Combined multiplet theory and experiment for the Fe 2p and 3p XPS of FeO and Fe2O3	81
QMCPACK: Advances in the development, efficiency, and application of auxiliary field and real-space variational and diffusion quantum Monte Carlo	81
Intermolecular interactions in optical cavities: An ab initio QED study	81
On the origin of ground-state vacuum-field catalysis: Equilibrium consideration	81
Generalized correlation-based dynamical network analysis: a new high-performance approach for identifying allosteric communications in molecular dynamics trajectories	76
Optical properties of charged excitons in two-dimensional semiconductors	76
Polaritonic normal modes in transition state theory	75
Peptide Gaussian accelerated molecular dynamics (Pep-GaMD): Enhanced sampling and free energy and kinetics calculations of peptide binding	74
Characterization of charge carrier behavior in photocatalysis using transient absorption spectroscopy	72
r2SCAN-D4: Dispersion corrected meta-generalized gradient approximation for general chemical applications	70
Diffusion with resetting in a logarithmic potential	69
Operator learning for predicting multiscale bubble growth dynamics	69
Committee neural network potentials control generalization errors and enable active learning	69
Descriptors representing two- and three-body atomic distributions and their effects on the accuracy of machine-learned inter-atomic potentials	68
GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations	67
e T 1.0: An open source electronic structure program with emphasis on coupled cluster and multilevel methods	67
Dyson-orbital concepts for description of electrons in molecules	66
An improved chain of spheres for exchange algorithm	65
Fitting potential energy surfaces with fundamental invariant neural network. II. Generating fundamental invariants for molecular systems with up to ten atoms	65
Reproducibility of cavity-enhanced chemical reaction rates in the vibrational strong coupling regime	64
Predicting molecular dipole moments by combining atomic partial charges and atomic dipoles	64
A practical guide to biologically relevant molecular simulations with charge scaling for electronic polarization	62
When do short-range atomistic machine-learning models fall short?	61