npj Computational Materials

Article	Citations
Dynamical phase-field model of cavity electromagnonic systems	671
Strain and ligand effects in the 1-D limit: reactivity of steps	347
Sparse representation for machine learning the properties of defects in 2D materials	293
Multiscale kinetic model of ethylene oligomerization in Ni-NU-1000 metal-organic framework	208
Structure and properties of graphullerene: a semiconducting two-dimensional C60 crystal	191
Active learning to overcome exponential-wall problem for effective structure prediction of chemical-disordered materials	170
Probing multi-dimensional composition spaces in search of strong metallic alloys	128
Author Correction: Active learning for accelerated design of layered materials	121
Machine learning-aided first-principles calculations of redox potentials	121
First principles methodology for studying magnetotransport in narrow gap semiconductors with ZrTe5 example	121
Origin of suppressed ferroelectricity in κ-Ga2O3: interplay between polarization and lattice domain walls	120
Dynamical mean field theory for real materials on a quantum computer	119
Vibrationally resolved optical excitations of the nitrogen-vacancy center in diamond	118
cmtj: Simulation package for analysis of multilayer spintronic devices	114
Bayesian optimization acquisition functions for accelerated search of cluster expansion convex hull of multi-component alloys	113
SA-GAT-SR: self-adaptable graph attention networks with symbolic regression for high-fidelity material property prediction	113
Crosslinking degree variations enable programming and controlling soft fracture via sideways cracking	104
Facilitated the discovery of new γ/γ′ Co-based superalloys by combining first-principles and machine learning	104
Insights into oxygen diffusion in rare earth disilicate environmental barrier coatings	103
Networking autonomous material exploration systems through transfer learning	101
Accurate piezoelectric tensor prediction with equivariant attention tensor graph neural network	99
A critical examination of robustness and generalizability of machine learning prediction of materials properties	98
Making atomistic materials calculations accessible with the AiiDAlab Quantum ESPRESSO app	95
Electron-mediated anharmonicity and its role in the Raman spectrum of graphene	94
Robust electron counting for direct electron detectors with the Back-propagation counting method	94

AI-assisted rapid crystal structure generation towards a target local environment	92
JARVIS-Leaderboard: a large scale benchmark of materials design methods	92
Unlocking 3D nanoparticle shapes from 2D high-resolution transmission electron microscopy images: a deep learning approach	92
Active learning of effective Hamiltonian for super-large-scale atomic structures	91
Ultra-fast interpretable machine-learning potentials	90
Machine learning enhanced analysis of EBSD data for texture representation	90
FALCON: fast active learning for machine learning potentials in atomistic and ab initio molecular dynamics simulations	89
Identifying the ground state structures of point defects in solids	89
Prediction of intrinsic multiferroicity and large valley polarization in a layered Janus material	88
Quantum anomalous hall effect in collinear antiferromagnetism	88
Advancing organic photovoltaic materials by machine learning-driven design with polymer-unit fingerprints	87
RadonPy: automated physical property calculation using all-atom classical molecular dynamics simulations for polymer informatics	85
Exploring the role of nonlocal Coulomb interactions in perovskite transition metal oxides	84
Machine learning surrogate for 3D phase-field modeling of ferroelectric tip-induced electrical switching	81
Accelerating electron diffraction analysis using graph neural networks and attention mechanisms	79
Revealing the evolution of order in materials microstructures using multi-modal computer vision	77
Raman signatures of single point defects in hexagonal boron nitride quantum emitters	76
Machine learning revealed giant thermal conductivity reduction by strong phonon localization in two-angle disordered twisted multilayer graphene	75
High-throughput parameter estimation from experimental data using Bayesian Inference with accelerated sampling	75
Agent-based multimodal information extraction for nanomaterials	75
High-speed and low-power molecular dynamics processing unit (MDPU) with ab initio accuracy	74
From Corpus to Innovation: Advancing Organic Solar Cell Design with Large Language Models	74
Prediction of the Cu oxidation state from EELS and XAS spectra using supervised machine learning	74
Known Unknowns: Out-of-Distribution Property Prediction in Materials and Molecules	73
From electrons to phase diagrams with machine learning potentials using pyiron based automated workflows	72
Tunable sliding ferroelectricity and magnetoelectric coupling in two-dimensional multiferroic MnSe materials	72
Discovering novel lead-free solder alloy by multi-objective Bayesian active learning with experimental uncertainty	71
A process-synergistic active learning framework for high-strength Al-Si alloys design	71
Benchmarking universal machine learning interatomic potentials for supported nanoparticles: decoupling energy accuracy from structural exploration	70
First principles study of dielectric properties of ferroelectric perovskite oxides with extended Hubbard interactions	70
DiffCrysGen: a generative diffusion model for accelerated design of inorganic crystalline materials	70
Machine learning-enabled atomistic insights into phase boundary engineering of solid-solution ferroelectrics	69
Combining feature-based approaches with graph neural networks and symbolic regression for synergistic performance and interpretability	67
A machine learning approach to designing and understanding tough, degradable polyamides	67
Combined study of phase transitions in the P2-type NaXNi1/3Mn2/3O2 cathode material: experimental, ab-initio and multiphase-field results	66
Electro-chemo-mechanical modelling of structural battery composite full cells	66
Machine-learning guided search for phonon-mediated superconductivity in boron and carbon compounds	65
Machine vision-based detections of transparent chemical vessels toward the safe automation of material synthesis	65
Comment on “Machine learning enhanced analysis of EBSD data for texture representation”	64
Enhancing the efficiency of time-dependent density functional theory calculations of dynamic response properties	64
Graph atomic cluster expansion for foundational machine learning interatomic potentials	64
Ultrafast laser-driven topological spin textures on a 2D magnet	64
Element mapping-based Bayesian optimization framework enabling direct materials design: a case study on NASICON-type cathode materials	63
Promising ferroelectric metal EuAuBi with switchable giant shift current	63
Approaches for handling high-dimensional cluster expansions of ionic systems	63
Flat topological nodal lines in heavy-fermion compound CeCoGe3	63
Data-driven low-rank approximation for the electron-hole kernel and acceleration of time-dependent GW calculations	63
Pushing charge equilibration-based machine learning potentials to their limits	63
Theory of non-Hermitian topological whispering gallery	62
Exploring superionic conduction in lithium oxyhalide solid electrolytes considering composition and structural factors	62

MOFBuilder: automated end-to-end modeling of MOF dynamics for high-throughput screening	62
Predicting the synthesizability of crystalline inorganic materials from the data of known material compositions	62
Accelerating superconductor discovery through tempered deep learning of the electron-phonon spectral function	62
Transition state structure detection with machine learningś	61
High-throughput materials exploration system for the anomalous Hall effect using combinatorial experiments and machine learning	60
Prediction of protected band edge states and dielectric tunable quasiparticle and excitonic properties of monolayer MoSi2N4	60
Author Correction: High-throughput study of the anomalous Hall effect	58
High-accuracy physical property prediction for pure organics via molecular representation learning: bridging data to discovery	58
Lanthanide molecular nanomagnets as probabilistic bits	58
Author Correction: Characterization of domain distributions by second harmonic generation in ferroelectrics	58
Magnons from time-dependent density-functional perturbation theory and nonempirical Hubbard functionals	58
Deep learning approaches for instantaneous laser absorptance prediction in additive manufacturing	56
Electronic structure prediction of medium and high entropy alloys across composition space	56
Elucidation of molecular-level charge transport in an organic amorphous system	56
Magnetic wallpaper Dirac fermions and topological magnetic Dirac insulators	56
Minimal crystallographic descriptors of sorption properties in hypothetical MOFs and role in sequential learning optimization	56
Machine learning on multiple topological materials datasets	55
Optimizing casting process using a combination of small data machine learning and phase-field simulations	55
XGBoost model for electrocaloric temperature change prediction in ceramics	55
Predicting temperature-dependent optoelectronic properties of semiconductor defects with equivariant neural networks	54
Deep convolutional neural networks to restore single-shot electron microscopy images	54
High-entropy solid electrolytes discovery: a dual-stage machine learning framework bridging atomic configurations and ionic transport properties	54
High-throughput discovery of perturbation-induced topological magnons	54
Effect of exchange-correlation functionals on the estimation of migration barriers in battery materials	54
Machine-learning-accelerated mechanistic exploration of interface modification in lithium metal anode	53
Deep material network via a quilting strategy: visualization for explainability and recursive training for improved accuracy	53
Photoinduced ferroelectric phase transition triggering photocatalytic water splitting	53
A classical equation that accounts for observations of non-Arrhenius and cryogenic grain boundary migration	52
Ab initio dynamical mean field theory with natural orbitals renormalization group impurity solver	52
Integrated modeling to control vaporization-induced composition change during additive manufacturing of nickel-based superalloys	52
Leveraging active learning-enhanced machine-learned interatomic potential for efficient infrared spectra prediction	51
A machine learning method to quantitatively predict alpha phase morphology in additively manufactured Ti-6Al-4V	51
Computational morphogenesis for liquid crystal elastomer metamaterial	51
Prediction of ambient pressure conventional superconductivity above 80 K in hydride compounds	50
Accurate and efficient band-gap predictions for metal halide perovskites at finite temperature	50
Unveiling hydrogen chemical states in supersaturated amorphous alumina via machine learning-driven atomistic modeling	49
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
Optimal pre-train/fine-tune strategies for accurate material property predictions	49
Finding the semantic similarity in single-particle diffraction images using self-supervised contrastive projection learning	49
Unified generalized universal equation of states for magnetic Co, Cr, Fe, Mn and Ni: an approach for non-collinear atomistic modelling	49
Origin of the insulating phase and metal-insulator transition in the organic molecular solid κ-(BEDT-TTF)2Cu2(CN)3	49
PID3Net: a deep learning approach for single-shot coherent X-ray diffraction imaging of dynamic phenomena	49
Discovery of new high-pressure phases – integrating high-throughput DFT simulations, graph neural networks, and active learning	48
Data-driven discovery of methane hydrate promoters	48
Superior printed parts using history and augmented machine learning	48
Physically interpretable interatomic potentials via symbolic regression and reinforcement learning	48
nNPipe: a neural network pipeline for automated analysis of morphologically diverse catalyst systems	48
Concurrent multi-peak Bragg coherent x-ray diffraction imaging of 3D nanocrystal lattice displacement via global optimization	48
Tunable Schottky barriers and magnetoelectric coupling driven by ferroelectric polarization reversal of MnI3/In2Se3 multiferroic heterostructures	47
A computational framework for guiding the MOCVD-growth of wafer-scale 2D materials	47
Evolution-guided Bayesian optimization for constrained multi-objective optimization in self-driving labs	47
SLM-MATRIX: a multi-agent trajectory reasoning and verification framework for enhancing language models in materials data extraction	47
AIMATDESIGN: knowledge-augmented reinforcement learning for inverse materials design under data scarcity	46
Modeling of ultrafast X-ray induced magnetization dynamics in magnetic multilayer systems	46
Machine learning-assisted high-throughput screening of superlattice-like O-PCM thin films	46
First-principles approach to spin excitations in noncollinear magnetic systems	46
Unsupervised deep denoising for four-dimensional scanning transmission electron microscopy	46
Prediction and tuning of altermagnetic magnon splitting in RFeO3: non-relativistic and relativistic perspectives	45
Dynamics of lattice disorder in perovskite materials, polarization nanoclusters and ferroelectric domain wall structures	45
Unraveling dislocation-based strengthening in refractory multi-principal element alloys	45
GEMDAT: a Python toolkit for site-resolved diffusion analysis in solid-state molecular dynamics	45
Scalable foundation interatomic potentials via message-passing pruning and graph partitioning	45
Unraveling charge effects on interface reactions and dendrite growth in lithium metal anode	44
Magnon shake-up: entanglement generation and sensing	44
Accelerating multiscale electronic stopping power predictions with time-dependent density functional theory and machine learning	43
An NV− center in magnesium oxide as a spin qubit for hybrid quantum technologies	43
Why is the strength of an elastomeric polymer network so low	43
Automated phase mapping of high-throughput X-ray diffraction data encoded with domain-specific materials science knowledge	42
A database of experimentally measured lithium solid electrolyte conductivities evaluated with machine learning	42
A dynamic Bayesian optimized active recommender system for curiosity-driven partially Human-in-the-loop automated experiments	42
Autonomous fabrication of tailored defect structures in 2D materials using machine learning-enabled scanning transmission electron microscopy	42
Attention-based functional-group coarse-graining: a deep learning framework for molecular prediction and design	41
Fast prediction of anharmonic vibrational spectra for complex organic molecules	41
EMFF-2025: a general neural network potential for energetic materials with C, H, N, and O elements	41
PredPotS: web tool for predicting one-electron standard reduction potentials for organic molecules in aqueous phase	41
Endless Dirac nodal lines in kagome-metal Ni3In2S2	41
Inverse design of metal–organic frameworks for C2H4/C2H6 separation	41
General invariance and equilibrium conditions for lattice dynamics in 1D, 2D, and 3D materials	41
Collecting diverse near-optimal samples via nested Thompson sampling	40

Application of machine learning to assess the influence of microstructure on twin nucleation in Mg alloys	40
The dual role of 90° domain walls in ferroelectric switching of Hf0.5Zr0.5O2 thin films: Insights from phase-field simulations	40
Rational design of large anomalous Nernst effect in Dirac semimetals	40
Enabling dynamic 3D coherent diffraction imaging via adaptive latent space tuning of generative autoencoders	40
Efficient simulations of charge density waves in the transition metal Dichalcogenide TiSe2	40
Ferroelectric order in hybrid organic-inorganic perovskite NH4PbI3 with non-polar molecules and small tolerance factor	40
Crystal structure prediction at finite temperatures	39
Infrared markers of topological phase transitions in quantum spin Hall insulators	39
Enhanced shift current in GeTe/SnSe heterostructures for bulk photovoltaic effect	39
Generalized first-principles prediction of hydrogen para-equilibrium thermodynamics in metal hydrides	38
Understanding phase transitions of α-quartz under dynamic compression conditions by machine-learning driven atomistic simulations	38
Efficient first-principles electronic transport approach to complex band structure materials: the case of n-type Mg3Sb2	38
Learning atomic forces from uncertainty-calibrated adversarial attacks	38
Targeted materials discovery using Bayesian algorithm execution	38
Computational screening of sodium solid electrolytes through unsupervised learning	37
The NOMAD Artificial-Intelligence Toolkit: turning materials-science data into knowledge and understanding	37
Learning from models: high-dimensional analyses on the performance of machine learning interatomic potentials	37
Atomistic simulation assisted error-inclusive Bayesian machine learning for probabilistically unraveling the mechanical properties of solidified metals	37
Dynamic mesophase transition induces anomalous suppressed and anisotropic phonon thermal transport	37
Magnetic and moiré proximity effects in WSe2/WSe2/CrI3 trilayers	37
Obtaining auxetic and isotropic metamaterials in counterintuitive design spaces: an automated optimization approach and experimental characterization	37
No ground truth needed: unsupervised sinogram inpainting for nanoparticle electron tomography (UsiNet) to correct missing wedges	36
From ultrathin to bulk: decoding thickness-unrestricted ferroelectricity in Y:HfO2 via first-principles	36
Explainable machine learning-enabled dual-objective design of γ' phase characteristic parameters in γ'-strengthened Co-based superalloys	36
Designing non-Van der Waals two-dimensional materials via a layer-intercalation strategy with tailorable ferroelectric, magnetic, and photocatalytic properties	36
Molecular descriptors for high-throughput virtual screening of fluorescence emitters with inverted singlet-triplet energy gaps	36
DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules	36
Transferable equivariant graph neural networks for the Hamiltonians of molecules and solids	35
Bayesian Optimization of Grain-Boundary Segregation in High-Entropy Alloys	35
Finite-temperature screw dislocation core structures and dynamics in α-titanium	35
Machine learning guided high-throughput search of non-oxide garnets	35
AI-enabled Lorentz microscopy for quantitative imaging of nanoscale magnetic spin textures	35
Ab initio theory of the nonequilibrium adsorption energy	35
Kohn–Sham time-dependent density functional theory with Tamm–Dancoff approximation on massively parallel GPUs	35
Perturbative solution of fermionic sign problem in quantum Monte Carlo computations	34
Physics and chemistry from parsimonious representations: image analysis via invariant variational autoencoders	34
Machine learning assisted screening of two dimensional chalcogenide ferromagnetic materials with Dzyaloshinskii Moriya interaction	34
Reply to: An explanation for the Rule of Four in Inorganic Materials	34
Active learning potentials for first-principles phase diagrams using replica-exchange nested sampling	33
Anisotropic Dzyaloshinskii-Moriya interaction protected by D2d crystal symmetry in two-dimensional ternary compounds	33
Trajectory sampling and finite-size effects in first-principles stopping power calculations	33
Intrinsic hard magnetism and thermal stability of a ThMn12-type permanent magnet	33
Simple arithmetic operation in latent space can generate a novel three-dimensional graph metamaterials	33
Accelerating phase field simulations through a hybrid adaptive Fourier neural operator with U-net backbone	33
Machine learning for exploring small polaron configurational space	33
Chemical foundation model-guided design of high ionic conductivity electrolyte formulations	32
Large language models design sequence-defined macromolecules via evolutionary optimization	32
Computational discovery of ultra-strong, stable, and lightweight refractory multi-principal element alloys. Part I: design principles and rapid down-selection	32
Solids that are also liquids: elastic tensors of superionic materials	32
Chemical bonding dictates alloying effect on inherent mechanical strength and plastic deformation mechanism in CoNiCr multicomponent alloy	32
Bidirectional mechanical switching window in ferroelectric thin films predicted by first-principle-based simulations	32
Technical review: Time-dependent density functional theory for attosecond physics ranging from gas-phase to solids	32
Higher-order equivariant neural networks for charge density prediction in materials	32
Enabling single-observation decomposition of multi-phase X-ray diffraction patterns via generative deep learning	32
Non-adiabatic approximations in time-dependent density functional theory: progress and prospects	32
Multi-plane denoising diffusion-based dimensionality expansion for 2D-to-3D reconstruction of microstructures with harmonized sampling	31
Towards understanding structure–property relations in materials with interpretable deep learning	31
Morphology prediction of small nanoparticles in any orientation from single electron micrographs	31
Angular relational knowledge distillation of machine learning interatomic potentials for scalable catalyst exploration	31
Machine-learning structural reconstructions for accelerated point defect calculations	31
Accurate screening of functional materials with machine-learning potential and transfer-learned regressions: Heusler alloy benchmark	31
‘Interaction annealing’ to determine effective quantized valence and orbital structure: an illustration with ferro-orbital order in WTe2	31
Guided diffusion for the discovery of new superconductors	31
The impact of ionic anharmonicity on superconductivity in metal-stuffed B-C clathrates	31
Dielectric properties of disordered crystalline materials: a computational case study on hexagonal ice	31
Efficient equivariant model for machine learning interatomic potentials	31
Linking atomic structural defects to mesoscale properties in crystalline solids using graph neural networks	30
Towards atom-level understanding of metal oxide catalysts for the oxygen evolution reaction with machine learning	30
Exploring parameter dependence of atomic minima with implicit differentiation	30
Small dataset machine-learning approach for efficient design space exploration: engineering ZnTe-based high-entropy alloys for water splitting	30
Giant multiphononic effects in a perovskite oxide	30
Advancing first-principles dielectric property prediction of complex microwave materials: an elemental-unit decomposition approach	30
The properties, thermodynamics and application prospects of diamanes	30
Achieving optimal GaN/SiC interfacial thermal conductance via ultrathin alloy interlayers for high-power device cooling	30
Machine-learned interatomic potentials for transition metal dichalcogenide Mo1−xWxS2−2ySe2y alloys	29
Modeling the effects of salt concentration on aqueous and organic electrolytes	29
Exploring high thermal conductivity polymers via interpretable machine learning with physical descriptors	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
Accelerating crystal structure search through active learning with neural networks for rapid relaxations	29
An efficient forgetting-aware fine-tuning framework for pretrained universal machine-learning interatomic potentials	29
A multi-fidelity machine learning approach to high throughput materials screening	29
The Bell-Evans-Polanyi relation for hydrogen evolution reaction from first-principles	29
An autonomous robotic module for efficient surface tension measurements of formulations	29
Electron-phonon physics at the exascale: a hybrid MPI-GPU-OpenMP framework for scalable Wannier interpolation	29
Designing architected materials for mechanical compression via simulation, deep learning, and experimentation	29
High-throughput exfoliation of multiferroic ternary oxide monolayers with high transition temperature and giant spin splitting	29
Author Correction: Polarization switching of HfO2 ferroelectric in bulk and electrode/ferroelectric/electrode heterostructure	29
CALPHAD-based cross-system knowledge transfer for rapid discovery of high-performance Al–Mg–Zn alloys	29
Rapid high-fidelity quantum simulations using multi-step nonlinear autoregression and graph embeddings	29
Platinum-based catalysts for oxygen reduction reaction simulated with a quantum computer	28
Constructing machine learning interatomic potentials with minimum amount of ab initio data	28
Machine learning Hubbard parameters with equivariant neural networks	28
Understanding and tuning negative longitudinal piezoelectricity in hafnia	28
Digitalizing metallic materials from image segmentation to multiscale solutions via physics informed operator learning	28