npj Computational Materials

Article	Citations
Author Correction: Active learning for accelerated design of layered materials	782
Sparse representation for machine learning the properties of defects in 2D materials	478
Prediction of intrinsic multiferroicity and large valley polarization in a layered Janus material	257
Strain and ligand effects in the 1-D limit: reactivity of steps	243
Accurate piezoelectric tensor prediction with equivariant attention tensor graph neural network	237
Active learning of effective Hamiltonian for super-large-scale atomic structures	224
Bayesian optimization acquisition functions for accelerated search of cluster expansion convex hull of multi-component alloys	200
Dynamical phase-field model of cavity electromagnonic systems	158
Accelerated identification of equilibrium structures of multicomponent inorganic crystals using machine learning potentials	144
Vibrationally resolved optical excitations of the nitrogen-vacancy center in diamond	144
First principles methodology for studying magnetotransport in narrow gap semiconductors with ZrTe5 example	143
Active learning to overcome exponential-wall problem for effective structure prediction of chemical-disordered materials	139
cmtj: Simulation package for analysis of multilayer spintronic devices	135
Structure and properties of graphullerene: a semiconducting two-dimensional C60 crystal	120
Dynamical mean field theory for real materials on a quantum computer	113
Crosslinking degree variations enable programming and controlling soft fracture via sideways cracking	112
Quantum anomalous hall effect in collinear antiferromagnetism	108
Advancing organic photovoltaic materials by machine learning-driven design with polymer-unit fingerprints	104
Multiscale modeling of ultrafast melting phenomena	104
Machine learning-aided first-principles calculations of redox potentials	98
Electron-mediated anharmonicity and its role in the Raman spectrum of graphene	94
Machine learning enhanced analysis of EBSD data for texture representation	90
Insights into oxygen diffusion in rare earth disilicate environmental barrier coatings	90
MatSciBERT: A materials domain language model for text mining and information extraction	89
A critical examination of robustness and generalizability of machine learning prediction of materials properties	87

Identifying the ground state structures of point defects in solids	86
JARVIS-Leaderboard: a large scale benchmark of materials design methods	85
RadonPy: automated physical property calculation using all-atom classical molecular dynamics simulations for polymer informatics	84
Facilitated the discovery of new γ/γ′ Co-based superalloys by combining first-principles and machine learning	83
Understanding X-ray absorption spectra by means of descriptors and machine learning algorithms	82
Exploring the role of nonlocal Coulomb interactions in perovskite transition metal oxides	79
Ultra-fast interpretable machine-learning potentials	78
Machine learning revealed giant thermal conductivity reduction by strong phonon localization in two-angle disordered twisted multilayer graphene	77
Discovering novel lead-free solder alloy by multi-objective Bayesian active learning with experimental uncertainty	75
Conversion of twisted light to twisted excitons using carbon nanotubes	75
Phase-field framework with constraints and its applications to ductile fracture in polycrystals and fatigue	75
Prediction of the Cu oxidation state from EELS and XAS spectra using supervised machine learning	75
High-speed and low-power molecular dynamics processing unit (MDPU) with ab initio accuracy	74
First-principles search of hot superconductivity in La-X-H ternary hydrides	74
Persistent half-metallic ferromagnetism in a (111)-oriented manganite superlattice	73
Machine learning surrogate for 3D phase-field modeling of ferroelectric tip-induced electrical switching	72
High-throughput discovery of fluoride-ion conductors via a decoupled, dynamic, and iterative (DDI) framework	71
Machine learning-enabled atomistic insights into phase boundary engineering of solid-solution ferroelectrics	71
A machine learning approach to designing and understanding tough, degradable polyamides	71
Known Unknowns: Out-of-Distribution Property Prediction in Materials and Molecules	70
Revealing the evolution of order in materials microstructures using multi-modal computer vision	70
From electrons to phase diagrams with machine learning potentials using pyiron based automated workflows	70
A process-synergistic active learning framework for high-strength Al-Si alloys design	69
Combined study of phase transitions in the P2-type NaXNi1/3Mn2/3O2 cathode material: experimental, ab-initio and multiphase-field results	67
Imaging atomic-scale chemistry from fused multi-modal electron microscopy	67
Electro-chemo-mechanical modelling of structural battery composite full cells	65
Agent-based multimodal information extraction for nanomaterials	63
Tracking perovskite crystallization via deep learning-based feature detection on 2D X-ray scattering data	63
Machine vision-based detections of transparent chemical vessels toward the safe automation of material synthesis	62
First principles study of dielectric properties of ferroelectric perovskite oxides with extended Hubbard interactions	62
Emergence of local scaling relations in adsorption energies on high-entropy alloys	62
Ultrafast laser-driven topological spin textures on a 2D magnet	62
Tunable sliding ferroelectricity and magnetoelectric coupling in two-dimensional multiferroic MnSe materials	62
Comment on “Machine learning enhanced analysis of EBSD data for texture representation”	61
Elucidation of molecular-level charge transport in an organic amorphous system	61
A graph based approach to model charge transport in semiconducting polymers	61
Machine learning on multiple topological materials datasets	61
Photoinduced ferroelectric phase transition triggering photocatalytic water splitting	60
Author Correction: Characterization of domain distributions by second harmonic generation in ferroelectrics	59
Author Correction: High-throughput study of the anomalous Hall effect	59
High-accuracy physical property prediction for pure organics via molecular representation learning: bridging data to discovery	59
Magnetic wallpaper Dirac fermions and topological magnetic Dirac insulators	58
Transition state structure detection with machine learningś	57
Sampling lattices in semi-grand canonical ensemble with autoregressive machine learning	57
Leveraging active learning-enhanced machine-learned interatomic potential for efficient infrared spectra prediction	57
Data-driven low-rank approximation for the electron-hole kernel and acceleration of time-dependent GW calculations	56
Accelerating superconductor discovery through tempered deep learning of the electron-phonon spectral function	56
Predicting elastic properties of hard-coating alloys using ab-initio and machine learning methods	55
Approaches for handling high-dimensional cluster expansions of ionic systems	55
Machine-learning-accelerated mechanistic exploration of interface modification in lithium metal anode	55

Magnons from time-dependent density-functional perturbation theory and nonempirical Hubbard functionals	55
Theory of non-Hermitian topological whispering gallery	55
Minimal crystallographic descriptors of sorption properties in hypothetical MOFs and role in sequential learning optimization	54
Prediction of protected band edge states and dielectric tunable quasiparticle and excitonic properties of monolayer MoSi2N4	54
Computational morphogenesis for liquid crystal elastomer metamaterial	54
Integrated modeling to control vaporization-induced composition change during additive manufacturing of nickel-based superalloys	54
Deep convolutional neural networks to restore single-shot electron microscopy images	54
High-throughput materials exploration system for the anomalous Hall effect using combinatorial experiments and machine learning	53
Lanthanide molecular nanomagnets as probabilistic bits	53
Exploring superionic conduction in lithium oxyhalide solid electrolytes considering composition and structural factors	52
High-throughput discovery of perturbation-induced topological magnons	52
Deep material network via a quilting strategy: visualization for explainability and recursive training for improved accuracy	52
Ab initio dynamical mean field theory with natural orbitals renormalization group impurity solver	51
Electronic structure prediction of medium and high entropy alloys across composition space	51
Prediction of ambient pressure conventional superconductivity above 80 K in hydride compounds	50
Machine learning of superconducting critical temperature from Eliashberg theory	50
Optimizing casting process using a combination of small data machine learning and phase-field simulations	50
XGBoost model for electrocaloric temperature change prediction in ceramics	50
Pushing charge equilibration-based machine learning potentials to their limits	50
Accurate and efficient band-gap predictions for metal halide perovskites at finite temperature	50
A machine learning method to quantitatively predict alpha phase morphology in additively manufactured Ti-6Al-4V	49
Predicting the synthesizability of crystalline inorganic materials from the data of known material compositions	49
A classical equation that accounts for observations of non-Arrhenius and cryogenic grain boundary migration	49
Deep learning approaches for instantaneous laser absorptance prediction in additive manufacturing	49
Effect of exchange-correlation functionals on the estimation of migration barriers in battery materials	49
Author Correction: Physics guided deep learning for generative design of crystal materials with symmetry constraints	48
CrysXPP: An explainable property predictor for crystalline materials	48
SLM-MATRIX: a multi-agent trajectory reasoning and verification framework for enhancing language models in materials data extraction	48
An NV− center in magnesium oxide as a spin qubit for hybrid quantum technologies	48
Unveiling hydrogen chemical states in supersaturated amorphous alumina via machine learning-driven atomistic modeling	48
Discovery of new high-pressure phases – integrating high-throughput DFT simulations, graph neural networks, and active learning	47
Finding the semantic similarity in single-particle diffraction images using self-supervised contrastive projection learning	47
A database of experimentally measured lithium solid electrolyte conductivities evaluated with machine learning	47
Concurrent multi-peak Bragg coherent x-ray diffraction imaging of 3D nanocrystal lattice displacement via global optimization	47
Accelerating multiscale electronic stopping power predictions with time-dependent density functional theory and machine learning	47
Unified generalized universal equation of states for magnetic Co, Cr, Fe, Mn and Ni: an approach for non-collinear atomistic modelling	47
Optimal pre-train/fine-tune strategies for accurate material property predictions	46
PID3Net: a deep learning approach for single-shot coherent X-ray diffraction imaging of dynamic phenomena	46
nNPipe: a neural network pipeline for automated analysis of morphologically diverse catalyst systems	45
Unraveling charge effects on interface reactions and dendrite growth in lithium metal anode	44
Unsupervised deep denoising for four-dimensional scanning transmission electron microscopy	44
Superior printed parts using history and augmented machine learning	44
General invariance and equilibrium conditions for lattice dynamics in 1D, 2D, and 3D materials	44
Modeling of ultrafast X-ray induced magnetization dynamics in magnetic multilayer systems	43
Automated phase mapping of high-throughput X-ray diffraction data encoded with domain-specific materials science knowledge	43
A dynamic Bayesian optimized active recommender system for curiosity-driven partially Human-in-the-loop automated experiments	43
Robust Wannierization including magnetization and spin-orbit coupling via projectability disentanglement	43
A computational framework for guiding the MOCVD-growth of wafer-scale 2D materials	43
EMFF-2025: a general neural network potential for energetic materials with C, H, N, and O elements	43
Evolution-guided Bayesian optimization for constrained multi-objective optimization in self-driving labs	42
Tunable Schottky barriers and magnetoelectric coupling driven by ferroelectric polarization reversal of MnI3/In2Se3 multiferroic heterostructures	42
Dipolar spin relaxation of divacancy qubits in silicon carbide	42
Unraveling dislocation-based strengthening in refractory multi-principal element alloys	42
Dynamics of lattice disorder in perovskite materials, polarization nanoclusters and ferroelectric domain wall structures	42
Fast prediction of anharmonic vibrational spectra for complex organic molecules	41
Ferroelectric order in hybrid organic-inorganic perovskite NH4PbI3 with non-polar molecules and small tolerance factor	41
Dynamic mesophase transition induces anomalous suppressed and anisotropic phonon thermal transport	41
The ferroelectric field-effect transistor with negative capacitance	40
Understanding phase transitions of α-quartz under dynamic compression conditions by machine-learning driven atomistic simulations	40
Molecular descriptors for high-throughput virtual screening of fluorescence emitters with inverted singlet-triplet energy gaps	40
Two-dimensional Stiefel-Whitney insulators in liganded Xenes	40
Enabling dynamic 3D coherent diffraction imaging via adaptive latent space tuning of generative autoencoders	40
Intermediate polaronic charge transport in organic crystals from a many-body first-principles approach	40
Crystal structure prediction at finite temperatures	40
2D spontaneous valley polarization from inversion symmetric single-layer lattices	40
Coarse-grained molecular dynamics integrated with convolutional neural network for comparing shapes of temperature sensitive bottlebrushes	40
Learning atomic forces from uncertainty-calibrated adversarial attacks	40
Atomistic simulation assisted error-inclusive Bayesian machine learning for probabilistically unraveling the mechanical properties of solidified metals	39
Attention-based functional-group coarse-graining: a deep learning framework for molecular prediction and design	39
Targeted materials discovery using Bayesian algorithm execution	39
Transferable equivariant graph neural networks for the Hamiltonians of molecules and solids	39
Rational design of large anomalous Nernst effect in Dirac semimetals	39
Uncovering material deformations via machine learning combined with four-dimensional scanning transmission electron microscopy	39
No ground truth needed: unsupervised sinogram inpainting for nanoparticle electron tomography (UsiNet) to correct missing wedges	38
Application of machine learning to assess the influence of microstructure on twin nucleation in Mg alloys	38
Infrared markers of topological phase transitions in quantum spin Hall insulators	38
Ferroelectricity coexisted with p-orbital ferromagnetism and metallicity in two-dimensional metal oxynitrides	38
Efficient first-principles electronic transport approach to complex band structure materials: the case of n-type Mg3Sb2	38
Intriguing magnetoelectric effect in two-dimensional ferromagnetic/perovskite oxide ferroelectric heterostructure	38
Efficient simulations of charge density waves in the transition metal Dichalcogenide TiSe2	38

Learning from models: high-dimensional analyses on the performance of machine learning interatomic potentials	37
Computational screening of sodium solid electrolytes through unsupervised learning	37
DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules	37
Chemical foundation model-guided design of high ionic conductivity electrolyte formulations	37
How coherence is governing diffuson heat transfer in amorphous solids	37
Endless Dirac nodal lines in kagome-metal Ni3In2S2	37
Obtaining auxetic and isotropic metamaterials in counterintuitive design spaces: an automated optimization approach and experimental characterization	37
Exploring parameter dependence of atomic minima with implicit differentiation	37
Inverse design of metal–organic frameworks for C2H4/C2H6 separation	37
The NOMAD Artificial-Intelligence Toolkit: turning materials-science data into knowledge and understanding	37
Advancing first-principles dielectric property prediction of complex microwave materials: an elemental-unit decomposition approach	37
Explainable machine learning-enabled dual-objective design of γ' phase characteristic parameters in γ'-strengthened Co-based superalloys	37
Trajectory sampling and finite-size effects in first-principles stopping power calculations	36
Exploring high thermal conductivity polymers via interpretable machine learning with physical descriptors	36
Solids that are also liquids: elastic tensors of superionic materials	36
Technical review: Time-dependent density functional theory for attosecond physics ranging from gas-phase to solids	36
Accurate and efficient molecular dynamics based on machine learning and non von Neumann architecture	36
AI-enabled Lorentz microscopy for quantitative imaging of nanoscale magnetic spin textures	36
Integration of resonant band with asymmetry in ferroelectric tunnel junctions	36
High-throughput exfoliation of multiferroic ternary oxide monolayers with high transition temperature and giant spin splitting	36
Accelerating phase field simulations through a hybrid adaptive Fourier neural operator with U-net backbone	35
Fragile topological band in the checkerboard antiferromagnetic monolayer FeSe	35
Machine-learned interatomic potentials for transition metal dichalcogenide Mo1−xWxS2−2ySe2y alloys	35
Towards atom-level understanding of metal oxide catalysts for the oxygen evolution reaction with machine learning	35
Design of soft magnetic materials	34
The Bell-Evans-Polanyi relation for hydrogen evolution reaction from first-principles	34
Physics and chemistry from parsimonious representations: image analysis via invariant variational autoencoders	34
Multi-plane denoising diffusion-based dimensionality expansion for 2D-to-3D reconstruction of microstructures with harmonized sampling	34
Modeling the effects of salt concentration on aqueous and organic electrolytes	34
A multi-fidelity machine learning approach to high throughput materials screening	34
Non-adiabatic approximations in time-dependent density functional theory: progress and prospects	33
Machine learning assisted screening of two dimensional chalcogenide ferromagnetic materials with Dzyaloshinskii Moriya interaction	33
Small dataset machine-learning approach for efficient design space exploration: engineering ZnTe-based high-entropy alloys for water splitting	33
Machine learning for exploring small polaron configurational space	33
Bidirectional mechanical switching window in ferroelectric thin films predicted by first-principle-based simulations	33
Full-spin-wave-scaled stochastic micromagnetism for mesh-independent simulations of ferromagnetic resonance and reversal	33
Ab initio theory of the nonequilibrium adsorption energy	33
Large language models design sequence-defined macromolecules via evolutionary optimization	33
Machine learning guided high-throughput search of non-oxide garnets	33
Simple arithmetic operation in latent space can generate a novel three-dimensional graph metamaterials	33
Kohn–Sham time-dependent density functional theory with Tamm–Dancoff approximation on massively parallel GPUs	32
Linking atomic structural defects to mesoscale properties in crystalline solids using graph neural networks	32
Anisotropic Dzyaloshinskii-Moriya interaction protected by D2d crystal symmetry in two-dimensional ternary compounds	32
Perturbative solution of fermionic sign problem in quantum Monte Carlo computations	31
Higher-order equivariant neural networks for charge density prediction in materials	31
Finite-temperature screw dislocation core structures and dynamics in α-titanium	31
Towards understanding structure–property relations in materials with interpretable deep learning	31
Intrinsic hard magnetism and thermal stability of a ThMn12-type permanent magnet	31
Computational discovery of ultra-strong, stable, and lightweight refractory multi-principal element alloys. Part I: design principles and rapid down-selection	31
Quantum point defects in 2D materials - the QPOD database	31
The impact of ionic anharmonicity on superconductivity in metal-stuffed B-C clathrates	31
Machine-learning structural reconstructions for accelerated point defect calculations	31
Giant multiphononic effects in a perovskite oxide	31
Rapid high-fidelity quantum simulations using multi-step nonlinear autoregression and graph embeddings	30
Understanding and tuning negative longitudinal piezoelectricity in hafnia	30
Coexistence of superconductivity and topological phase in kagome metals ANb3Bi5 (A = K, Rb, Cs)	30
Designing architected materials for mechanical compression via simulation, deep learning, and experimentation	30
Phase-field modeling of coupled bulk photovoltaic effect and ferroelectric domain manipulation at ultrafast timescales	30
Electronic correlation in nearly free electron metals with beyond-DFT methods	30
Digitalizing metallic materials from image segmentation to multiscale solutions via physics informed operator learning	30
Efficient equivariant model for machine learning interatomic potentials	30
The best thermoelectrics revisited in the quantum limit	30
Author Correction: Polarization switching of HfO2 ferroelectric in bulk and electrode/ferroelectric/electrode heterostructure	30
Shaping freeform nanophotonic devices with geometric neural parameterization	29
Primitive to conventional geometry projection for efficient phonon transport calculations	29
Magnetic Moment Tensor Potentials for collinear spin-polarized materials reproduce different magnetic states of bcc Fe	29
Discovery of materials for solar thermochemical hydrogen combining machine learning, computational chemistry, experiments and system simulations	29
A rule-free workflow for the automated generation of databases from scientific literature	29
Resonant tunneling in disordered borophene nanoribbons with line defects	29
X-ray scattering tensor tomography based finite element modelling of heterogeneous materials	29
Coherent and semicoherent α/β interfaces in titanium: structure, thermodynamics, migration	29
Analytical and numerical modeling of optical second harmonic generation in anisotropic crystals using ♯SHAARP package	29
Accelerating crystal structure search through active learning with neural networks for rapid relaxations	29
Topology-optimized thermal metamaterials traversing full-parameter anisotropic space	29
Platinum-based catalysts for oxygen reduction reaction simulated with a quantum computer	29
An autonomous robotic module for efficient surface tension measurements of formulations	28
Magnetic order in the computational 2D materials database (C2DB) from high throughput spin spiral calculations	28
Development of the reactive force field and silicon dry/wet oxidation process modeling	28
Point-defect-driven flattened polar phonon bands in fluorite ferroelectrics	28
Machine learning Hubbard parameters with equivariant neural networks	28
Relativistic domain-wall dynamics in van der Waals antiferromagnet MnPS3	28
Recent advances and applications of deep learning methods in materials science	27
Predicting electronic screening for fast Koopmans spectral functional calculations	27
An interleaved physics-based deep-learning framework as a new cycle jumping approach for microstructurally small fatigue crack growth simulations	27
Candidate ferroelectrics via ab initio high-throughput screening of polar materials	27
Mechanism of keyhole pore formation in metal additive manufacturing	27
Deep learning potential model of displacement damage in hafnium oxide ferroelectric films	27
JAX-BTE: a GPU-accelerated differentiable solver for phonon Boltzmann transport equations	27
Enabling rapid X-ray CT characterisation for additive manufacturing using CAD models and deep learning-based reconstruction	27
Sub-bandgap charge harvesting and energy up-conversion in metal halide perovskites: ab initio quantum dynamics	27
Enhancing transferability of machine learning-based polarizability models in condensed-phase systems via atomic polarizability constraint	27
High-throughput screening of 2D materials identifies p-type monolayer WS2 as potential ultra-high mobility semiconductor	26
Self-supervised probabilistic models for exploring shape memory alloys	26
Automated generation of structure datasets for machine learning potentials and alloys	26
High pressure suppression of plasticity due to an overabundance of shear embryo formation	26