npj Computational Materials

Article	Citations
Electron-mediated anharmonicity and its role in the Raman spectrum of graphene	642
Networking autonomous material exploration systems through transfer learning	325
Dynamical phase-field model of cavity electromagnonic systems	286
Strain and ligand effects in the 1-D limit: reactivity of steps	261
Sparse representation for machine learning the properties of defects in 2D materials	199
Active learning of effective Hamiltonian for super-large-scale atomic structures	186
Multiscale kinetic model of ethylene oligomerization in Ni-NU-1000 metal-organic framework	164
Insights into oxygen diffusion in rare earth disilicate environmental barrier coatings	162
FALCON: fast active learning for machine learning potentials in atomistic and ab initio molecular dynamics simulations	128
Structure and properties of graphullerene: a semiconducting two-dimensional C60 crystal	120
Active learning to overcome exponential-wall problem for effective structure prediction of chemical-disordered materials	119
Accurate piezoelectric tensor prediction with equivariant attention tensor graph neural network	119
Exploring the role of nonlocal Coulomb interactions in perovskite transition metal oxides	118
Making atomistic materials calculations accessible with the AiiDAlab Quantum ESPRESSO app	113
Probing multi-dimensional composition spaces in search of strong metallic alloys	113
cmtj: Simulation package for analysis of multilayer spintronic devices	109
SA-GAT-SR: self-adaptable graph attention networks with symbolic regression for high-fidelity material property prediction	108
AI-assisted rapid crystal structure generation towards a target local environment	107
Crosslinking degree variations enable programming and controlling soft fracture via sideways cracking	100
Bayesian optimization acquisition functions for accelerated search of cluster expansion convex hull of multi-component alloys	100
Facilitated the discovery of new γ/γ′ Co-based superalloys by combining first-principles and machine learning	99
Prediction of intrinsic multiferroicity and large valley polarization in a layered Janus material	97
Ultra-fast interpretable machine-learning potentials	96
Origin of suppressed ferroelectricity in κ-Ga2O3: interplay between polarization and lattice domain walls	94
Dynamical mean field theory for real materials on a quantum computer	93

JARVIS-Leaderboard: a large scale benchmark of materials design methods	91
Identifying the ground state structures of point defects in solids	91
First principles methodology for studying magnetotransport in narrow gap semiconductors with ZrTe5 example	90
Vibrationally resolved optical excitations of the nitrogen-vacancy center in diamond	89
Machine learning-aided first-principles calculations of redox potentials	88
Quantum anomalous hall effect in collinear antiferromagnetism	87
Advancing organic photovoltaic materials by machine learning-driven design with polymer-unit fingerprints	87
Accelerated identification of equilibrium structures of multicomponent inorganic crystals using machine learning potentials	87
Author Correction: Active learning for accelerated design of layered materials	87
Machine learning enhanced analysis of EBSD data for texture representation	86
A critical examination of robustness and generalizability of machine learning prediction of materials properties	86
RadonPy: automated physical property calculation using all-atom classical molecular dynamics simulations for polymer informatics	84
Ultrafast laser-driven topological spin textures on a 2D magnet	84
MatSciBERT: A materials domain language model for text mining and information extraction	84
Machine learning surrogate for 3D phase-field modeling of ferroelectric tip-induced electrical switching	80
Known Unknowns: Out-of-Distribution Property Prediction in Materials and Molecules	80
Machine-learning guided search for phonon-mediated superconductivity in boron and carbon compounds	78
Combined study of phase transitions in the P2-type NaXNi1/3Mn2/3O2 cathode material: experimental, ab-initio and multiphase-field results	76
From electrons to phase diagrams with machine learning potentials using pyiron based automated workflows	75
Accelerating electron diffraction analysis using graph neural networks and attention mechanisms	74
Revealing the evolution of order in materials microstructures using multi-modal computer vision	73
Electro-chemo-mechanical modelling of structural battery composite full cells	72
Tunable sliding ferroelectricity and magnetoelectric coupling in two-dimensional multiferroic MnSe materials	72
High-throughput parameter estimation from experimental data using Bayesian Inference with accelerated sampling	72
High-speed and low-power molecular dynamics processing unit (MDPU) with ab initio accuracy	70
Raman signatures of single point defects in hexagonal boron nitride quantum emitters	70
Machine learning-enabled atomistic insights into phase boundary engineering of solid-solution ferroelectrics	70
High-throughput discovery of fluoride-ion conductors via a decoupled, dynamic, and iterative (DDI) framework	70
Graph atomic cluster expansion for foundational machine learning interatomic potentials	70
Combining feature-based approaches with graph neural networks and symbolic regression for synergistic performance and interpretability	68
A machine learning approach to designing and understanding tough, degradable polyamides	68
Tracking perovskite crystallization via deep learning-based feature detection on 2D X-ray scattering data	67
Machine vision-based detections of transparent chemical vessels toward the safe automation of material synthesis	66
From Corpus to Innovation: Advancing Organic Solar Cell Design with Large Language Models	66
Machine learning revealed giant thermal conductivity reduction by strong phonon localization in two-angle disordered twisted multilayer graphene	66
Discovering novel lead-free solder alloy by multi-objective Bayesian active learning with experimental uncertainty	66
Benchmarking universal machine learning interatomic potentials for supported nanoparticles: decoupling energy accuracy from structural exploration	66
First principles study of dielectric properties of ferroelectric perovskite oxides with extended Hubbard interactions	66
Prediction of the Cu oxidation state from EELS and XAS spectra using supervised machine learning	64
Enhancing the efficiency of time-dependent density functional theory calculations of dynamic response properties	64
Comment on “Machine learning enhanced analysis of EBSD data for texture representation”	62
A process-synergistic active learning framework for high-strength Al-Si alloys design	62
Agent-based multimodal information extraction for nanomaterials	62
Data-driven low-rank approximation for the electron-hole kernel and acceleration of time-dependent GW calculations	62
Element mapping-based Bayesian optimization framework enabling direct materials design: a case study on NASICON-type cathode materials	61
Author Correction: Characterization of domain distributions by second harmonic generation in ferroelectrics	61
Computational morphogenesis for liquid crystal elastomer metamaterial	61
Machine learning on multiple topological materials datasets	61
Approaches for handling high-dimensional cluster expansions of ionic systems	61
Theory of non-Hermitian topological whispering gallery	61

Lanthanide molecular nanomagnets as probabilistic bits	60
High-throughput discovery of perturbation-induced topological magnons	60
Magnons from time-dependent density-functional perturbation theory and nonempirical Hubbard functionals	60
Machine-learning-accelerated mechanistic exploration of interface modification in lithium metal anode	60
Author Correction: High-throughput study of the anomalous Hall effect	60
Deep learning approaches for instantaneous laser absorptance prediction in additive manufacturing	59
High-entropy solid electrolytes discovery: a dual-stage machine learning framework bridging atomic configurations and ionic transport properties	59
Leveraging active learning-enhanced machine-learned interatomic potential for efficient infrared spectra prediction	59
Transition state structure detection with machine learningś	58
Promising ferroelectric metal EuAuBi with switchable giant shift current	58
Flat topological nodal lines in heavy-fermion compound CeCoGe3	58
Prediction of protected band edge states and dielectric tunable quasiparticle and excitonic properties of monolayer MoSi2N4	58
High-throughput materials exploration system for the anomalous Hall effect using combinatorial experiments and machine learning	57
High-accuracy physical property prediction for pure organics via molecular representation learning: bridging data to discovery	56
Photoinduced ferroelectric phase transition triggering photocatalytic water splitting	56
Accurate and efficient band-gap predictions for metal halide perovskites at finite temperature	55
Pushing charge equilibration-based machine learning potentials to their limits	54
Effect of exchange-correlation functionals on the estimation of migration barriers in battery materials	54
Magnetic wallpaper Dirac fermions and topological magnetic Dirac insulators	54
Integrated modeling to control vaporization-induced composition change during additive manufacturing of nickel-based superalloys	54
Elucidation of molecular-level charge transport in an organic amorphous system	54
Ab initio dynamical mean field theory with natural orbitals renormalization group impurity solver	54
Minimal crystallographic descriptors of sorption properties in hypothetical MOFs and role in sequential learning optimization	53
Electronic structure prediction of medium and high entropy alloys across composition space	53
Optimizing casting process using a combination of small data machine learning and phase-field simulations	53
A classical equation that accounts for observations of non-Arrhenius and cryogenic grain boundary migration	52
MOFBuilder: automated end-to-end modeling of MOF dynamics for high-throughput screening	52
Deep convolutional neural networks to restore single-shot electron microscopy images	52
Predicting the synthesizability of crystalline inorganic materials from the data of known material compositions	52
A machine learning method to quantitatively predict alpha phase morphology in additively manufactured Ti-6Al-4V	51
Accelerating superconductor discovery through tempered deep learning of the electron-phonon spectral function	51
Prediction of ambient pressure conventional superconductivity above 80 K in hydride compounds	51
Exploring superionic conduction in lithium oxyhalide solid electrolytes considering composition and structural factors	51
Deep material network via a quilting strategy: visualization for explainability and recursive training for improved accuracy	51
XGBoost model for electrocaloric temperature change prediction in ceramics	51
Unified generalized universal equation of states for magnetic Co, Cr, Fe, Mn and Ni: an approach for non-collinear atomistic modelling	50
Author Correction: Physics guided deep learning for generative design of crystal materials with symmetry constraints	49
Robust Wannierization including magnetization and spin-orbit coupling via projectability disentanglement	49
Finding the semantic similarity in single-particle diffraction images using self-supervised contrastive projection learning	49
Concurrent multi-peak Bragg coherent x-ray diffraction imaging of 3D nanocrystal lattice displacement via global optimization	49
Dynamics of lattice disorder in perovskite materials, polarization nanoclusters and ferroelectric domain wall structures	48
Data-driven discovery of methane hydrate promoters	48
PID3Net: a deep learning approach for single-shot coherent X-ray diffraction imaging of dynamic phenomena	48
Origin of the insulating phase and metal-insulator transition in the organic molecular solid κ-(BEDT-TTF)2Cu2(CN)3	48
Scalable foundation interatomic potentials via message-passing pruning and graph partitioning	47
Physically interpretable interatomic potentials via symbolic regression and reinforcement learning	47
Modeling of ultrafast X-ray induced magnetization dynamics in magnetic multilayer systems	47
A dynamic Bayesian optimized active recommender system for curiosity-driven partially Human-in-the-loop automated experiments	47
Unveiling hydrogen chemical states in supersaturated amorphous alumina via machine learning-driven atomistic modeling	47
An NV− center in magnesium oxide as a spin qubit for hybrid quantum technologies	47
General invariance and equilibrium conditions for lattice dynamics in 1D, 2D, and 3D materials	47
Automated phase mapping of high-throughput X-ray diffraction data encoded with domain-specific materials science knowledge	47
Optimal pre-train/fine-tune strategies for accurate material property predictions	47
Autonomous fabrication of tailored defect structures in 2D materials using machine learning-enabled scanning transmission electron microscopy	46
Unsupervised deep denoising for four-dimensional scanning transmission electron microscopy	46
Discovery of new high-pressure phases – integrating high-throughput DFT simulations, graph neural networks, and active learning	45
A computational framework for guiding the MOCVD-growth of wafer-scale 2D materials	45
Machine learning-assisted high-throughput screening of superlattice-like O-PCM thin films	45
Unraveling dislocation-based strengthening in refractory multi-principal element alloys	45
Superior printed parts using history and augmented machine learning	45
A database of experimentally measured lithium solid electrolyte conductivities evaluated with machine learning	45
SLM-MATRIX: a multi-agent trajectory reasoning and verification framework for enhancing language models in materials data extraction	45
Accelerating multiscale electronic stopping power predictions with time-dependent density functional theory and machine learning	45
Unraveling charge effects on interface reactions and dendrite growth in lithium metal anode	44
EMFF-2025: a general neural network potential for energetic materials with C, H, N, and O elements	44
Evolution-guided Bayesian optimization for constrained multi-objective optimization in self-driving labs	44
nNPipe: a neural network pipeline for automated analysis of morphologically diverse catalyst systems	44
Tunable Schottky barriers and magnetoelectric coupling driven by ferroelectric polarization reversal of MnI3/In2Se3 multiferroic heterostructures	43
Rational design of large anomalous Nernst effect in Dirac semimetals	43
AIMATDESIGN: knowledge-augmented reinforcement learning for inverse materials design under data scarcity	43
Atomistic simulation assisted error-inclusive Bayesian machine learning for probabilistically unraveling the mechanical properties of solidified metals	43
Explainable machine learning-enabled dual-objective design of γ' phase characteristic parameters in γ'-strengthened Co-based superalloys	42
Learning atomic forces from uncertainty-calibrated adversarial attacks	42
Application of machine learning to assess the influence of microstructure on twin nucleation in Mg alloys	42
Attention-based functional-group coarse-graining: a deep learning framework for molecular prediction and design	42
Efficient simulations of charge density waves in the transition metal Dichalcogenide TiSe2	42
No ground truth needed: unsupervised sinogram inpainting for nanoparticle electron tomography (UsiNet) to correct missing wedges	41
The dual role of 90° domain walls in ferroelectric switching of Hf0.5Zr0.5O2 thin films: Insights from phase-field simulations	41
Enabling dynamic 3D coherent diffraction imaging via adaptive latent space tuning of generative autoencoders	41
Transferable equivariant graph neural networks for the Hamiltonians of molecules and solids	41

Dynamic mesophase transition induces anomalous suppressed and anisotropic phonon thermal transport	41
PredPotS: web tool for predicting one-electron standard reduction potentials for organic molecules in aqueous phase	40
Infrared markers of topological phase transitions in quantum spin Hall insulators	40
Molecular descriptors for high-throughput virtual screening of fluorescence emitters with inverted singlet-triplet energy gaps	40
Endless Dirac nodal lines in kagome-metal Ni3In2S2	39
Computational screening of sodium solid electrolytes through unsupervised learning	39
From ultrathin to bulk: decoding thickness-unrestricted ferroelectricity in Y:HfO2 via first-principles	39
Fast prediction of anharmonic vibrational spectra for complex organic molecules	39
Ferroelectric order in hybrid organic-inorganic perovskite NH4PbI3 with non-polar molecules and small tolerance factor	39
Inverse design of metal–organic frameworks for C2H4/C2H6 separation	39
Targeted materials discovery using Bayesian algorithm execution	38
Understanding phase transitions of α-quartz under dynamic compression conditions by machine-learning driven atomistic simulations	38
DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules	38
Uncovering material deformations via machine learning combined with four-dimensional scanning transmission electron microscopy	38
Learning from models: high-dimensional analyses on the performance of machine learning interatomic potentials	38
Collecting diverse near-optimal samples via nested Thompson sampling	38
Efficient first-principles electronic transport approach to complex band structure materials: the case of n-type Mg3Sb2	38
The NOMAD Artificial-Intelligence Toolkit: turning materials-science data into knowledge and understanding	37
Bidirectional mechanical switching window in ferroelectric thin films predicted by first-principle-based simulations	37
Obtaining auxetic and isotropic metamaterials in counterintuitive design spaces: an automated optimization approach and experimental characterization	37
Crystal structure prediction at finite temperatures	37
Ab initio theory of the nonequilibrium adsorption energy	37
Generalized first-principles prediction of hydrogen para-equilibrium thermodynamics in metal hydrides	37
Bayesian Optimization of Grain-Boundary Segregation in High-Entropy Alloys	36
Finite-temperature screw dislocation core structures and dynamics in α-titanium	36
Machine learning guided high-throughput search of non-oxide garnets	36
Exploring parameter dependence of atomic minima with implicit differentiation	36
High-throughput exfoliation of multiferroic ternary oxide monolayers with high transition temperature and giant spin splitting	36
The impact of ionic anharmonicity on superconductivity in metal-stuffed B-C clathrates	36
AI-enabled Lorentz microscopy for quantitative imaging of nanoscale magnetic spin textures	36
Solids that are also liquids: elastic tensors of superionic materials	35
Reply to: An explanation for the Rule of Four in Inorganic Materials	35
Perturbative solution of fermionic sign problem in quantum Monte Carlo computations	35
Kohn–Sham time-dependent density functional theory with Tamm–Dancoff approximation on massively parallel GPUs	35
The properties, thermodynamics and application prospects of diamanes	35
Non-adiabatic approximations in time-dependent density functional theory: progress and prospects	35
‘Interaction annealing’ to determine effective quantized valence and orbital structure: an illustration with ferro-orbital order in WTe2	35
Physics and chemistry from parsimonious representations: image analysis via invariant variational autoencoders	35
Small dataset machine-learning approach for efficient design space exploration: engineering ZnTe-based high-entropy alloys for water splitting	34
Computational discovery of ultra-strong, stable, and lightweight refractory multi-principal element alloys. Part I: design principles and rapid down-selection	34
Machine learning for exploring small polaron configurational space	34
Accurate and efficient molecular dynamics based on machine learning and non von Neumann architecture	34
Angular relational knowledge distillation of machine learning interatomic potentials for scalable catalyst exploration	34
Anisotropic Dzyaloshinskii-Moriya interaction protected by D2d crystal symmetry in two-dimensional ternary compounds	34
Machine learning assisted screening of two dimensional chalcogenide ferromagnetic materials with Dzyaloshinskii Moriya interaction	34
Dielectric properties of disordered crystalline materials: a computational case study on hexagonal ice	33
Simple arithmetic operation in latent space can generate a novel three-dimensional graph metamaterials	33
Intrinsic hard magnetism and thermal stability of a ThMn12-type permanent magnet	32
Accurate screening of functional materials with machine-learning potential and transfer-learned regressions: Heusler alloy benchmark	32
Towards atom-level understanding of metal oxide catalysts for the oxygen evolution reaction with machine learning	32
Advancing first-principles dielectric property prediction of complex microwave materials: an elemental-unit decomposition approach	32
Modeling the effects of salt concentration on aqueous and organic electrolytes	32
Active learning potentials for first-principles phase diagrams using replica-exchange nested sampling	32
Chemical foundation model-guided design of high ionic conductivity electrolyte formulations	32
A multi-fidelity machine learning approach to high throughput materials screening	32
Accelerating phase field simulations through a hybrid adaptive Fourier neural operator with U-net backbone	31
Chemical bonding dictates alloying effect on inherent mechanical strength and plastic deformation mechanism in CoNiCr multicomponent alloy	31
Trajectory sampling and finite-size effects in first-principles stopping power calculations	31
Efficient equivariant model for machine learning interatomic potentials	31
Machine-learning structural reconstructions for accelerated point defect calculations	31
Designing architected materials for mechanical compression via simulation, deep learning, and experimentation	31
An efficient forgetting-aware fine-tuning framework for pretrained universal machine-learning interatomic potentials	31
Towards understanding structure–property relations in materials with interpretable deep learning	31
Technical review: Time-dependent density functional theory for attosecond physics ranging from gas-phase to solids	31
Higher-order equivariant neural networks for charge density prediction in materials	31
Machine-learned interatomic potentials for transition metal dichalcogenide Mo1−xWxS2−2ySe2y alloys	30
Multi-plane denoising diffusion-based dimensionality expansion for 2D-to-3D reconstruction of microstructures with harmonized sampling	30
Exploring high thermal conductivity polymers via interpretable machine learning with physical descriptors	30
Giant multiphononic effects in a perovskite oxide	30
Large language models design sequence-defined macromolecules via evolutionary optimization	30
Linking atomic structural defects to mesoscale properties in crystalline solids using graph neural networks	30
Author Correction: Polarization switching of HfO2 ferroelectric in bulk and electrode/ferroelectric/electrode heterostructure	29
An autonomous robotic module for efficient surface tension measurements of formulations	29
Physics-informed GCN-LSTM framework for long-term forecasting of 2D and 3D microstructure evolution	29
Accelerating crystal structure search through active learning with neural networks for rapid relaxations	29
Primitive to conventional geometry projection for efficient phonon transport calculations	29
Toward high entropy material discovery for energy applications using computational and machine learning methods	29
The Bell-Evans-Polanyi relation for hydrogen evolution reaction from first-principles	29
CALPHAD-based cross-system knowledge transfer for rapid discovery of high-performance Al–Mg–Zn alloys	29
Electron-phonon physics at the exascale: a hybrid MPI-GPU-OpenMP framework for scalable Wannier interpolation	29
Investigating contact-limited scaling in sub-15-nm TMD FETs from first-principles	29
X-ray scattering tensor tomography based finite element modelling of heterogeneous materials	29
Coexistence of superconductivity and topological phase in kagome metals ANb3Bi5 (A = K, Rb, Cs)	29
Compositional complexity buffers free-volume sensitivity and serrated flow in metallic glasses	29
Rapid high-fidelity quantum simulations using multi-step nonlinear autoregression and graph embeddings	29
Phase-field modeling of coupled bulk photovoltaic effect and ferroelectric domain manipulation at ultrafast timescales	29
Electronic correlation in nearly free electron metals with beyond-DFT methods	29
Unsupervised density-based method for analyzing ion mobility in crystalline solid-state electrolytes	28
Discovery of materials for solar thermochemical hydrogen combining machine learning, computational chemistry, experiments and system simulations	28
Machine learning Hubbard parameters with equivariant neural networks	28
Coherent and semicoherent α/β interfaces in titanium: structure, thermodynamics, migration	28
Analytical and numerical modeling of optical second harmonic generation in anisotropic crystals using ♯SHAARP package	28
JAX-BTE: a GPU-accelerated differentiable solver for phonon Boltzmann transport equations	28
The best thermoelectrics revisited in the quantum limit	28
Platinum-based catalysts for oxygen reduction reaction simulated with a quantum computer	28