npj Computational Materials

Article	Citations
Author Correction: Active learning for accelerated design of layered materials	752
Dynamical phase-field model of cavity electromagnonic systems	447
Active learning to overcome exponential-wall problem for effective structure prediction of chemical-disordered materials	435
Sparse representation for machine learning the properties of defects in 2D materials	245
First principles methodology for studying magnetotransport in narrow gap semiconductors with ZrTe5 example	238
Crosslinking degree variations enable programming and controlling soft fracture via sideways cracking	224
Quantum anomalous hall effect in collinear antiferromagnetism	214
RadonPy: automated physical property calculation using all-atom classical molecular dynamics simulations for polymer informatics	191
Machine learning-aided first-principles calculations of redox potentials	151
MatSciBERT: A materials domain language model for text mining and information extraction	143
Prediction of intrinsic multiferroicity and large valley polarization in a layered Janus material	141
Electron-mediated anharmonicity and its role in the Raman spectrum of graphene	134
Strain and ligand effects in the 1-D limit: reactivity of steps	133
Facilitated the discovery of new γ/γ′ Co-based superalloys by combining first-principles and machine learning	129
Accurate piezoelectric tensor prediction with equivariant attention tensor graph neural network	129
Advancing organic photovoltaic materials by machine learning-driven design with polymer-unit fingerprints	113
Bayesian optimization acquisition functions for accelerated search of cluster expansion convex hull of multi-component alloys	110
Active learning of effective Hamiltonian for super-large-scale atomic structures	108
Vibrationally resolved optical excitations of the nitrogen-vacancy center in diamond	105
Structure and properties of graphullerene: a semiconducting two-dimensional C60 crystal	102
cmtj: Simulation package for analysis of multilayer spintronic devices	99
Multiscale modeling of ultrafast melting phenomena	97
Insights into oxygen diffusion in rare earth disilicate environmental barrier coatings	93
Dynamical mean field theory for real materials on a quantum computer	88
Ultra-fast interpretable machine-learning potentials	86

A critical examination of robustness and generalizability of machine learning prediction of materials properties	85
JARVIS-Leaderboard: a large scale benchmark of materials design methods	84
Machine learning enhanced analysis of EBSD data for texture representation	84
Accelerated identification of equilibrium structures of multicomponent inorganic crystals using machine learning potentials	83
Exploring the role of nonlocal Coulomb interactions in perovskite transition metal oxides	82
Understanding X-ray absorption spectra by means of descriptors and machine learning algorithms	80
Identifying the ground state structures of point defects in solids	79
Machine learning revealed giant thermal conductivity reduction by strong phonon localization in two-angle disordered twisted multilayer graphene	75
Conversion of twisted light to twisted excitons using carbon nanotubes	75
First principles study of dielectric properties of ferroelectric perovskite oxides with extended Hubbard interactions	74
Machine vision-based detections of transparent chemical vessels toward the safe automation of material synthesis	74
A machine learning approach to designing and understanding tough, degradable polyamides	73
High-throughput discovery of fluoride-ion conductors via a decoupled, dynamic, and iterative (DDI) framework	71
Persistent half-metallic ferromagnetism in a (111)-oriented manganite superlattice	71
Machine learning surrogate for 3D phase-field modeling of ferroelectric tip-induced electrical switching	70
Tracking perovskite crystallization via deep learning-based feature detection on 2D X-ray scattering data	70
Agent-based multimodal information extraction for nanomaterials	70
Prediction of the Cu oxidation state from EELS and XAS spectra using supervised machine learning	69
First-principles search of hot superconductivity in La-X-H ternary hydrides	67
Phase-field framework with constraints and its applications to ductile fracture in polycrystals and fatigue	66
From electrons to phase diagrams with machine learning potentials using pyiron based automated workflows	66
Combined study of phase transitions in the P2-type NaXNi1/3Mn2/3O2 cathode material: experimental, ab-initio and multiphase-field results	66
Ultrafast laser-driven topological spin textures on a 2D magnet	66
Emergence of local scaling relations in adsorption energies on high-entropy alloys	65
Tunable sliding ferroelectricity and magnetoelectric coupling in two-dimensional multiferroic MnSe materials	65
Discovering novel lead-free solder alloy by multi-objective Bayesian active learning with experimental uncertainty	64
A graph based approach to model charge transport in semiconducting polymers	63
Imaging atomic-scale chemistry from fused multi-modal electron microscopy	63
A process-synergistic active learning framework for high-strength Al-Si alloys design	63
High-speed and low-power molecular dynamics processing unit (MDPU) with ab initio accuracy	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
Electro-chemo-mechanical modelling of structural battery composite full cells	61
Machine learning on multiple topological materials datasets	61
Photoinduced ferroelectric phase transition triggering photocatalytic water splitting	61
Author Correction: High-throughput study of the anomalous Hall effect	60
Author Correction: Characterization of domain distributions by second harmonic generation in ferroelectrics	60
High-throughput materials exploration system for the anomalous Hall effect using combinatorial experiments and machine learning	59
Magnetic wallpaper Dirac fermions and topological magnetic Dirac insulators	58
High-accuracy physical property prediction for pure organics via molecular representation learning: bridging data to discovery	58
Theory of non-Hermitian topological whispering gallery	58
Magnons from time-dependent density-functional perturbation theory and nonempirical Hubbard functionals	57
Transition state structure detection with machine learningś	57
Accelerating superconductor discovery through tempered deep learning of the electron-phonon spectral function	56
Sampling lattices in semi-grand canonical ensemble with autoregressive machine learning	56
Data-driven low-rank approximation for the electron-hole kernel and acceleration of time-dependent GW calculations	56
Lanthanide molecular nanomagnets as probabilistic bits	55
Prediction of ambient pressure conventional superconductivity above 80 K in hydride compounds	55
Machine learning of superconducting critical temperature from Eliashberg theory	55
Machine-learning-accelerated mechanistic exploration of interface modification in lithium metal anode	53

Pushing charge equilibration-based machine learning potentials to their limits	53
Deep learning approaches for instantaneous laser absorptance prediction in additive manufacturing	53
High-throughput discovery of perturbation-induced topological magnons	52
Integrated modeling to control vaporization-induced composition change during additive manufacturing of nickel-based superalloys	52
XGBoost model for electrocaloric temperature change prediction in ceramics	52
Leveraging active learning-enhanced machine-learned interatomic potential for efficient infrared spectra prediction	51
Deep convolutional neural networks to restore single-shot electron microscopy images	51
Ab initio dynamical mean field theory with natural orbitals renormalization group impurity solver	51
Deep material network via a quilting strategy: visualization for explainability and recursive training for improved accuracy	50
Approaches for handling high-dimensional cluster expansions of ionic systems	50
Predicting elastic properties of hard-coating alloys using ab-initio and machine learning methods	50
Minimal crystallographic descriptors of sorption properties in hypothetical MOFs and role in sequential learning optimization	50
Predicting the synthesizability of crystalline inorganic materials from the data of known material compositions	50
Prediction of protected band edge states and dielectric tunable quasiparticle and excitonic properties of monolayer MoSi2N4	50
A classical equation that accounts for observations of non-Arrhenius and cryogenic grain boundary migration	50
A machine learning method to quantitatively predict alpha phase morphology in additively manufactured Ti-6Al-4V	50
Accurate and efficient band-gap predictions for metal halide perovskites at finite temperature	50
Optimizing casting process using a combination of small data machine learning and phase-field simulations	49
Exploring superionic conduction in lithium oxyhalide solid electrolytes considering composition and structural factors	48
Unveiling hydrogen chemical states in supersaturated amorphous alumina via machine learning-driven atomistic modeling	48
Computational morphogenesis for liquid crystal elastomer metamaterial	48
Effect of exchange-correlation functionals on the estimation of migration barriers in battery materials	48
Optimal pre-train/fine-tune strategies for accurate material property predictions	48
Author Correction: Physics guided deep learning for generative design of crystal materials with symmetry constraints	47
An NV− center in magnesium oxide as a spin qubit for hybrid quantum technologies	47
SLM-MATRIX: a multi-agent trajectory reasoning and verification framework for enhancing language models in materials data extraction	47
PID3Net: a deep learning approach for single-shot coherent X-ray diffraction imaging of dynamic phenomena	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
Concurrent multi-peak Bragg coherent x-ray diffraction imaging of 3D nanocrystal lattice displacement via global optimization	46
Finding the semantic similarity in single-particle diffraction images using self-supervised contrastive projection learning	46
Discovery of new high-pressure phases – integrating high-throughput DFT simulations, graph neural networks, and active learning	46
Tunable Schottky barriers and magnetoelectric coupling driven by ferroelectric polarization reversal of MnI3/In2Se3 multiferroic heterostructures	45
Unified generalized universal equation of states for magnetic Co, Cr, Fe, Mn and Ni: an approach for non-collinear atomistic modelling	45
Dipolar spin relaxation of divacancy qubits in silicon carbide	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	45
Dynamics of lattice disorder in perovskite materials, polarization nanoclusters and ferroelectric domain wall structures	45
A database of experimentally measured lithium solid electrolyte conductivities evaluated with machine learning	44
A computational framework for guiding the MOCVD-growth of wafer-scale 2D materials	44
Unraveling dislocation-based strengthening in refractory multi-principal element alloys	44
General invariance and equilibrium conditions for lattice dynamics in 1D, 2D, and 3D materials	44
Superior printed parts using history and augmented machine learning	43
Evolution-guided Bayesian optimization for constrained multi-objective optimization in self-driving labs	43
Unsupervised deep denoising for four-dimensional scanning transmission electron microscopy	43
nNPipe: a neural network pipeline for automated analysis of morphologically diverse catalyst systems	43
Dynamic mesophase transition induces anomalous suppressed and anisotropic phonon thermal transport	42
CrysXPP: An explainable property predictor for crystalline materials	42
Rational design of large anomalous Nernst effect in Dirac semimetals	42
Ferroelectric order in hybrid organic-inorganic perovskite NH4PbI3 with non-polar molecules and small tolerance factor	42
Endless Dirac nodal lines in kagome-metal Ni3In2S2	42
Coarse-grained molecular dynamics integrated with convolutional neural network for comparing shapes of temperature sensitive bottlebrushes	42
No ground truth needed: unsupervised sinogram inpainting for nanoparticle electron tomography (UsiNet) to correct missing wedges	42
Learning from models: high-dimensional analyses on the performance of machine learning interatomic potentials	41
Efficient simulations of charge density waves in the transition metal Dichalcogenide TiSe2	41
Enabling dynamic 3D coherent diffraction imaging via adaptive latent space tuning of generative autoencoders	41
The NOMAD Artificial-Intelligence Toolkit: turning materials-science data into knowledge and understanding	40
2D spontaneous valley polarization from inversion symmetric single-layer lattices	40
Obtaining auxetic and isotropic metamaterials in counterintuitive design spaces: an automated optimization approach and experimental characterization	40
Crystal structure prediction at finite temperatures	40
Uncovering material deformations via machine learning combined with four-dimensional scanning transmission electron microscopy	40
Atomistic simulation assisted error-inclusive Bayesian machine learning for probabilistically unraveling the mechanical properties of solidified metals	40
Understanding phase transitions of α-quartz under dynamic compression conditions by machine-learning driven atomistic simulations	39
Learning atomic forces from uncertainty-calibrated adversarial attacks	39
Efficient first-principles electronic transport approach to complex band structure materials: the case of n-type Mg3Sb2	39
Intriguing magnetoelectric effect in two-dimensional ferromagnetic/perovskite oxide ferroelectric heterostructure	39
Fast prediction of anharmonic vibrational spectra for complex organic molecules	39
Targeted materials discovery using Bayesian algorithm execution	39
Intermediate polaronic charge transport in organic crystals from a many-body first-principles approach	38
Explainable machine learning-enabled dual-objective design of γ' phase characteristic parameters in γ'-strengthened Co-based superalloys	38
Molecular descriptors for high-throughput virtual screening of fluorescence emitters with inverted singlet-triplet energy gaps	38
How coherence is governing diffuson heat transfer in amorphous solids	38
Transferable equivariant graph neural networks for the Hamiltonians of molecules and solids	37
Two-dimensional Stiefel-Whitney insulators in liganded Xenes	37
Application of machine learning to assess the influence of microstructure on twin nucleation in Mg alloys	37
Ferroelectricity coexisted with p-orbital ferromagnetism and metallicity in two-dimensional metal oxynitrides	37
Inverse design of metal–organic frameworks for C2H4/C2H6 separation	37
DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules	37
Infrared markers of topological phase transitions in quantum spin Hall insulators	37
Computational screening of sodium solid electrolytes through unsupervised learning	37

The ferroelectric field-effect transistor with negative capacitance	37
Advancing first-principles dielectric property prediction of complex microwave materials: an elemental-unit decomposition approach	36
Simple arithmetic operation in latent space can generate a novel three-dimensional graph metamaterials	36
Perturbative solution of fermionic sign problem in quantum Monte Carlo computations	36
Machine learning guided high-throughput search of non-oxide garnets	36
Solids that are also liquids: elastic tensors of superionic materials	36
Giant multiphononic effects in a perovskite oxide	36
Exploring parameter dependence of atomic minima with implicit differentiation	36
Ab initio theory of the nonequilibrium adsorption energy	36
Full-spin-wave-scaled stochastic micromagnetism for mesh-independent simulations of ferromagnetic resonance and reversal	35
Integration of resonant band with asymmetry in ferroelectric tunnel junctions	35
Designing architected materials for mechanical compression via simulation, deep learning, and experimentation	35
Anisotropic Dzyaloshinskii-Moriya interaction protected by D2d crystal symmetry in two-dimensional ternary compounds	35
Towards atom-level understanding of metal oxide catalysts for the oxygen evolution reaction with machine learning	35
Multi-plane denoising diffusion-based dimensionality expansion for 2D-to-3D reconstruction of microstructures with harmonized sampling	35
The Bell-Evans-Polanyi relation for hydrogen evolution reaction from first-principles	35
Bidirectional mechanical switching window in ferroelectric thin films predicted by first-principle-based simulations	34
Technical review: Time-dependent density functional theory for attosecond physics ranging from gas-phase to solids	34
Machine-learning structural reconstructions for accelerated point defect calculations	34
Physics and chemistry from parsimonious representations: image analysis via invariant variational autoencoders	34
Kohn–Sham time-dependent density functional theory with Tamm–Dancoff approximation on massively parallel GPUs	34
AI-enabled Lorentz microscopy for quantitative imaging of nanoscale magnetic spin textures	34
Trajectory sampling and finite-size effects in first-principles stopping power calculations	34
Chemical foundation model-guided design of high ionic conductivity electrolyte formulations	34
Modeling the effects of salt concentration on aqueous and organic electrolytes	34
Large language models design sequence-defined macromolecules via evolutionary optimization	33
Exploring high thermal conductivity polymers via interpretable machine learning with physical descriptors	33
Machine-learned interatomic potentials for transition metal dichalcogenide Mo1−xWxS2−2ySe2y alloys	33
Design of soft magnetic materials	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
Non-adiabatic approximations in time-dependent density functional theory: progress and prospects	33
Higher-order equivariant neural networks for charge density prediction in materials	33
Fragile topological band in the checkerboard antiferromagnetic monolayer FeSe	33
Machine learning for exploring small polaron configurational space	33
Accurate and efficient molecular dynamics based on machine learning and non von Neumann architecture	32
Accelerating phase field simulations through a hybrid adaptive Fourier neural operator with U-net backbone	32
Linking atomic structural defects to mesoscale properties in crystalline solids using graph neural networks	32
Towards understanding structure–property relations in materials with interpretable deep learning	32
Quantum point defects in 2D materials - the QPOD database	32
Efficient equivariant model for machine learning interatomic potentials	32
Rapid high-fidelity quantum simulations using multi-step nonlinear autoregression and graph embeddings	31
A multi-fidelity machine learning approach to high throughput materials screening	31
Computational discovery of ultra-strong, stable, and lightweight refractory multi-principal element alloys. Part I: design principles and rapid down-selection	31
Primitive to conventional geometry projection for efficient phonon transport calculations	31
Finite-temperature screw dislocation core structures and dynamics in α-titanium	31
Intrinsic hard magnetism and thermal stability of a ThMn12-type permanent magnet	31
Atomistic Line Graph Neural Network for improved materials property predictions	31
Point-defect-driven flattened polar phonon bands in fluorite ferroelectrics	30
Author Correction: Polarization switching of HfO2 ferroelectric in bulk and electrode/ferroelectric/electrode heterostructure	30
JAX-BTE: a GPU-accelerated differentiable solver for phonon Boltzmann transport equations	30
Discovery of materials for solar thermochemical hydrogen combining machine learning, computational chemistry, experiments and system simulations	30
Digitalizing metallic materials from image segmentation to multiscale solutions via physics informed operator learning	30
Accelerating crystal structure search through active learning with neural networks for rapid relaxations	30
Coexistence of superconductivity and topological phase in kagome metals ANb3Bi5 (A = K, Rb, Cs)	30
Phase-field modeling of coupled bulk photovoltaic effect and ferroelectric domain manipulation at ultrafast timescales	30
Platinum-based catalysts for oxygen reduction reaction simulated with a quantum computer	30
Shaping freeform nanophotonic devices with geometric neural parameterization	30
Candidate ferroelectrics via ab initio high-throughput screening of polar materials	29
Relativistic domain-wall dynamics in van der Waals antiferromagnet MnPS3	29
The best thermoelectrics revisited in the quantum limit	29
Magnetic order in the computational 2D materials database (C2DB) from high throughput spin spiral calculations	29
Understanding and tuning negative longitudinal piezoelectricity in hafnia	29
X-ray scattering tensor tomography based finite element modelling of heterogeneous materials	28
Development of the reactive force field and silicon dry/wet oxidation process modeling	28
Rapid and flexible segmentation of electron microscopy data using few-shot machine learning	28
Electronic correlation in nearly free electron metals with beyond-DFT methods	28
Enabling rapid X-ray CT characterisation for additive manufacturing using CAD models and deep learning-based reconstruction	28
Coherent and semicoherent α/β interfaces in titanium: structure, thermodynamics, migration	28
Magnetic Moment Tensor Potentials for collinear spin-polarized materials reproduce different magnetic states of bcc Fe	28
Analytical and numerical modeling of optical second harmonic generation in anisotropic crystals using ♯SHAARP package	28
Glass transition temperature prediction of disordered molecular solids	28
A rule-free workflow for the automated generation of databases from scientific literature	28
Topology-optimized thermal metamaterials traversing full-parameter anisotropic space	28
Resonant tunneling in disordered borophene nanoribbons with line defects	28
Recent advances and applications of deep learning methods in materials science	27
Realistic magnetic thermodynamics by local quantization of a semiclassical Heisenberg model	27
Machine learning Hubbard parameters with equivariant neural networks	27
Predicting electronic screening for fast Koopmans spectral functional calculations	27
Virtual melting and cyclic transformations between amorphous Si, Si I, and Si IV in a shear band at room temperature	27
Mechanism of keyhole pore formation in metal additive manufacturing	27
Enhancing transferability of machine learning-based polarizability models in condensed-phase systems via atomic polarizability constraint	27
Machine learning-driven synthesis of TiZrNbHfTaC5 high-entropy carbide	26
An interleaved physics-based deep-learning framework as a new cycle jumping approach for microstructurally small fatigue crack growth simulations	26
Self-supervised probabilistic models for exploring shape memory alloys	26
Factorial design analytics on effects of material parameter uncertainties in multiphysics modeling of additive manufacturing	26
Enhancing electrocaloric effects of KNN-based ceramics by phase- and ion-configurational entropy regulation based on phase-field modeling	26
Sub-bandgap charge harvesting and energy up-conversion in metal halide perovskites: ab initio quantum dynamics	26
Principal component analysis enables the design of deep learning potential precisely capturing LLZO phase transitions	26
Ferroelectricity at the extreme thickness limit in the archetypal antiferroelectric PbZrO3	26
Deep learning potential model of displacement damage in hafnium oxide ferroelectric films	26
Predicting column heights and elemental composition in experimental transmission electron microscopy images of high-entropy oxides using deep learning	26
Electronic Moment Tensor Potentials include both electronic and vibrational degrees of freedom	26
Leveraging unlabeled SEM datasets with self-supervised learning for enhanced particle segmentation	26
Symmetric carbon tetramers forming spin qubits in hexagonal boron nitride	26