OOIR: Observatory of International Research

Papers

(The H4-Index of npj Computational Materials is 57. 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 2021-09-01 to 2025-09-01.)

Article	Citations
Author Correction: Active learning for accelerated design of layered materials	678
Multiscale modeling of ultrafast melting phenomena	424
Insights into oxygen diffusion in rare earth disilicate environmental barrier coatings	383
Sparse representation for machine learning the properties of defects in 2D materials	225
First principles methodology for studying magnetotransport in narrow gap semiconductors with ZrTe5 example	222
Strain and ligand effects in the 1-D limit: reactivity of steps	203
Machine learning enhanced analysis of EBSD data for texture representation	198
cmtj: Simulation package for analysis of multilayer spintronic devices	176
Electron-mediated anharmonicity and its role in the Raman spectrum of graphene	146
Facilitated the discovery of new γ/γ′ Co-based superalloys by combining first-principles and machine learning	138
Structure and properties of graphullerene: a semiconducting two-dimensional C60 crystal	130
Bayesian optimization acquisition functions for accelerated search of cluster expansion convex hull of multi-component alloys	126
Exploring the role of nonlocal Coulomb interactions in perovskite transition metal oxides	125
Prediction of intrinsic multiferroicity and large valley polarization in a layered Janus material	121
RadonPy: automated physical property calculation using all-atom classical molecular dynamics simulations for polymer informatics	118
Active learning to overcome exponential-wall problem for effective structure prediction of chemical-disordered materials	117
Active learning of effective Hamiltonian for super-large-scale atomic structures	116
Dynamical phase-field model of cavity electromagnonic systems	110
Accelerated identification of equilibrium structures of multicomponent inorganic crystals using machine learning potentials	98
Environmental screening and ligand-field effects to magnetism in CrI3 monolayer	97
Crosslinking degree variations enable programming and controlling soft fracture via sideways cracking	97
Advancing organic photovoltaic materials by machine learning-driven design with polymer-unit fingerprints	94
A critical examination of robustness and generalizability of machine learning prediction of materials properties	92
JARVIS-Leaderboard: a large scale benchmark of materials design methods	91
Accurate piezoelectric tensor prediction with equivariant attention tensor graph neural network	91

MatSciBERT: A materials domain language model for text mining and information extraction	87
Quantum anomalous hall effect in collinear antiferromagnetism	81
Machine learning-aided first-principles calculations of redox potentials	80
Ultra-fast interpretable machine-learning potentials	79
Identifying the ground state structures of point defects in solids	78
Vibrationally resolved optical excitations of the nitrogen-vacancy center in diamond	77
First principles study of dielectric properties of ferroelectric perovskite oxides with extended Hubbard interactions	75
Understanding X-ray absorption spectra by means of descriptors and machine learning algorithms	75
Emergence of local scaling relations in adsorption energies on high-entropy alloys	74
A process-synergistic active learning framework for high-strength Al-Si alloys design	74
A machine learning framework for damage mechanism identification from acoustic emissions in unidirectional SiC/SiC composites	73
First-principles search of hot superconductivity in La-X-H ternary hydrides	71
Combined study of phase transitions in the P2-type NaXNi1/3Mn2/3O2 cathode material: experimental, ab-initio and multiphase-field results	69
From electrons to phase diagrams with machine learning potentials using pyiron based automated workflows	69
Prediction of the Cu oxidation state from EELS and XAS spectra using supervised machine learning	68
Ultrafast laser-driven topological spin textures on a 2D magnet	68
Machine vision-based detections of transparent chemical vessels toward the safe automation of material synthesis	67
Tunable sliding ferroelectricity and magnetoelectric coupling in two-dimensional multiferroic MnSe materials	65
High-throughput discovery of fluoride-ion conductors via a decoupled, dynamic, and iterative (DDI) framework	65
Conversion of twisted light to twisted excitons using carbon nanotubes	64
Author Correction: High energy barriers for edge dislocation motion in body-centered cubic high entropy alloys	63
Machine learning surrogate for 3D phase-field modeling of ferroelectric tip-induced electrical switching	62
Imaging atomic-scale chemistry from fused multi-modal electron microscopy	62
Electro-chemo-mechanical modelling of structural battery composite full cells	61
Phase-field framework with constraints and its applications to ductile fracture in polycrystals and fatigue	61
High-speed and low-power molecular dynamics processing unit (MDPU) with ab initio accuracy	61
Agent-based multimodal information extraction for nanomaterials	60
Machine learning revealed giant thermal conductivity reduction by strong phonon localization in two-angle disordered twisted multilayer graphene	60
Tracking perovskite crystallization via deep learning-based feature detection on 2D X-ray scattering data	60
A graph based approach to model charge transport in semiconducting polymers	60
Discovering novel lead-free solder alloy by multi-objective Bayesian active learning with experimental uncertainty	58
Strong electron–phonon coupling influences carrier transport and thermoelectric performances in group-IV/V elemental monolayers	57
Persistent half-metallic ferromagnetism in a (111)-oriented manganite superlattice	57
A machine learning approach to designing and understanding tough, degradable polyamides	57