npj Computational Materials

Article	Citations
Author Correction: Active learning for accelerated design of layered materials	652
Multiscale modeling of ultrafast melting phenomena	408
Insights into oxygen diffusion in rare earth disilicate environmental barrier coatings	365
Quantum anomalous hall effect in collinear antiferromagnetism	214
Active learning to overcome exponential-wall problem for effective structure prediction of chemical-disordered materials	211
Active learning of effective Hamiltonian for super-large-scale atomic structures	191
Crosslinking degree variations enable programming and controlling soft fracture via sideways cracking	186
Accelerated identification of equilibrium structures of multicomponent inorganic crystals using machine learning potentials	171
Sparse representation for machine learning the properties of defects in 2D materials	143
First principles methodology for studying magnetotransport in narrow gap semiconductors with ZrTe5 example	134
Machine learning-aided first-principles calculations of redox potentials	125
Strain and ligand effects in the 1-D limit: reactivity of steps	123
Machine learning enhanced analysis of EBSD data for texture representation	122
Exploring the role of nonlocal Coulomb interactions in perovskite transition metal oxides	116
Electron-mediated anharmonicity and its role in the Raman spectrum of graphene	116
Dynamical phase-field model of cavity electromagnonic systems	116
Giant room temperature elastocaloric effect in metal-free thin-film perovskites	106
Facilitated the discovery of new γ/γ′ Co-based superalloys by combining first-principles and machine learning	106
Structure and properties of graphullerene: a semiconducting two-dimensional C60 crystal	94
Environmental screening and ligand-field effects to magnetism in CrI3 monolayer	93
Bayesian optimization acquisition functions for accelerated search of cluster expansion convex hull of multi-component alloys	92
Accurate piezoelectric tensor prediction with equivariant attention tensor graph neural network	91
Ultra-fast interpretable machine-learning potentials	90
RadonPy: automated physical property calculation using all-atom classical molecular dynamics simulations for polymer informatics	89
JARVIS-Leaderboard: a large scale benchmark of materials design methods	89

A critical examination of robustness and generalizability of machine learning prediction of materials properties	85
Understanding X-ray absorption spectra by means of descriptors and machine learning algorithms	80
Vibrationally resolved optical excitations of the nitrogen-vacancy center in diamond	79
cmtj: Simulation package for analysis of multilayer spintronic devices	79
MatSciBERT: A materials domain language model for text mining and information extraction	74
Advancing organic photovoltaic materials by machine learning-driven design with polymer-unit fingerprints	74
Identifying the ground state structures of point defects in solids	73
First principles study of dielectric properties of ferroelectric perovskite oxides with extended Hubbard interactions	72
High-throughput discovery of fluoride-ion conductors via a decoupled, dynamic, and iterative (DDI) framework	72
A machine learning approach to designing and understanding tough, degradable polyamides	70
A process-synergistic active learning framework for high-strength Al-Si alloys design	69
Author Correction: High energy barriers for edge dislocation motion in body-centered cubic high entropy alloys	68
Conversion of twisted light to twisted excitons using carbon nanotubes	68
Imaging atomic-scale chemistry from fused multi-modal electron microscopy	67
Electro-chemo-mechanical modelling of structural battery composite full cells	65
Tracking perovskite crystallization via deep learning-based feature detection on 2D X-ray scattering data	64
Machine learning revealed giant thermal conductivity reduction by strong phonon localization in two-angle disordered twisted multilayer graphene	64
Ultrafast laser-driven topological spin textures on a 2D magnet	64
Agent-based multimodal information extraction for nanomaterials	63
First-principles search of hot superconductivity in La-X-H ternary hydrides	62
A graph based approach to model charge transport in semiconducting polymers	62
Discovering novel lead-free solder alloy by multi-objective Bayesian active learning with experimental uncertainty	61
Combined study of phase transitions in the P2-type NaXNi1/3Mn2/3O2 cathode material: experimental, ab-initio and multiphase-field results	59
Prediction of the Cu oxidation state from EELS and XAS spectra using supervised machine learning	59
Tunable sliding ferroelectricity and magnetoelectric coupling in two-dimensional multiferroic MnSe materials	58
Strong electron–phonon coupling influences carrier transport and thermoelectric performances in group-IV/V elemental monolayers	58
Machine vision-based detections of transparent chemical vessels toward the safe automation of material synthesis	58
Persistent half-metallic ferromagnetism in a (111)-oriented manganite superlattice	57
High-speed and low-power molecular dynamics processing unit (MDPU) with ab initio accuracy	57
Machine learning surrogate for 3D phase-field modeling of ferroelectric tip-induced electrical switching	57
Phase-field framework with constraints and its applications to ductile fracture in polycrystals and fatigue	56
Emergence of local scaling relations in adsorption energies on high-entropy alloys	55
From electrons to phase diagrams with machine learning potentials using pyiron based automated workflows	55
Deep material network via a quilting strategy: visualization for explainability and recursive training for improved accuracy	55
A machine learning framework for damage mechanism identification from acoustic emissions in unidirectional SiC/SiC composites	55
Theory of non-Hermitian topological whispering gallery	54
Ab initio dynamical mean field theory with natural orbitals renormalization group impurity solver	53
Author Correction: Characterization of domain distributions by second harmonic generation in ferroelectrics	53
Sampling lattices in semi-grand canonical ensemble with autoregressive machine learning	53
Author Correction: High-throughput study of the anomalous Hall effect	53
Photoinduced ferroelectric phase transition triggering photocatalytic water splitting	52
Elucidation of molecular-level charge transport in an organic amorphous system	51
Approaches for handling high-dimensional cluster expansions of ionic systems	51
Comment on “Machine learning enhanced analysis of EBSD data for texture representation”	51
Machine learning on multiple topological materials datasets	51
Accurate and efficient band-gap predictions for metal halide perovskites at finite temperature	50
Prediction of ambient pressure conventional superconductivity above 80 K in hydride compounds	50
Minimal crystallographic descriptors of sorption properties in hypothetical MOFs and role in sequential learning optimization	50
Integrated modeling to control vaporization-induced composition change during additive manufacturing of nickel-based superalloys	49
Computational morphogenesis for liquid crystal elastomer metamaterial	48

Accelerating superconductor discovery through tempered deep learning of the electron-phonon spectral function	48
Magnons from time-dependent density-functional perturbation theory and nonempirical Hubbard functionals	48
Predicting elastic properties of hard-coating alloys using ab-initio and machine learning methods	48
Machine learning of superconducting critical temperature from Eliashberg theory	47
Magnetic wallpaper Dirac fermions and topological magnetic Dirac insulators	47
High-accuracy physical property prediction for pure organics via molecular representation learning: bridging data to discovery	47
Effect of exchange-correlation functionals on the estimation of migration barriers in battery materials	47
Transition state structure detection with machine learningś	46
A classical equation that accounts for observations of non-Arrhenius and cryogenic grain boundary migration	46
Data-driven low-rank approximation for the electron-hole kernel and acceleration of time-dependent GW calculations	46
High-throughput discovery of perturbation-induced topological magnons	46
Prediction of protected band edge states and dielectric tunable quasiparticle and excitonic properties of monolayer MoSi2N4	45
A machine learning method to quantitatively predict alpha phase morphology in additively manufactured Ti-6Al-4V	45
Deep convolutional neural networks to restore single-shot electron microscopy images	44
Exploring superionic conduction in lithium oxyhalide solid electrolytes considering composition and structural factors	44
Lanthanide molecular nanomagnets as probabilistic bits	44
Machine-learning-accelerated mechanistic exploration of interface modification in lithium metal anode	44
Deep learning approaches for instantaneous laser absorptance prediction in additive manufacturing	44
Optimizing casting process using a combination of small data machine learning and phase-field simulations	44
Predicting the synthesizability of crystalline inorganic materials from the data of known material compositions	44
XGBoost model for electrocaloric temperature change prediction in ceramics	44
An NV− center in magnesium oxide as a spin qubit for hybrid quantum technologies	43
Author Correction: Physics guided deep learning for generative design of crystal materials with symmetry constraints	43
Accelerating multiscale electronic stopping power predictions with time-dependent density functional theory and machine learning	43
Modeling of ultrafast X-ray induced magnetization dynamics in magnetic multilayer systems	43
A dynamic Bayesian optimized active recommender system for curiosity-driven partially Human-in-the-loop automated experiments	43
Finding the semantic similarity in single-particle diffraction images using self-supervised contrastive projection learning	43
Unveiling hydrogen chemical states in supersaturated amorphous alumina via machine learning-driven atomistic modeling	42
Dipolar spin relaxation of divacancy qubits in silicon carbide	42
Unraveling charge effects on interface reactions and dendrite growth in lithium metal anode	42
Concurrent multi-peak Bragg coherent x-ray diffraction imaging of 3D nanocrystal lattice displacement via global optimization	41
nNPipe: a neural network pipeline for automated analysis of morphologically diverse catalyst systems	41
Discovery of new high-pressure phases – integrating high-throughput DFT simulations, graph neural networks, and active learning	41
PID3Net: a deep learning approach for single-shot coherent X-ray diffraction imaging of dynamic phenomena	41
High-dimensional neural network potentials for magnetic systems using spin-dependent atom-centered symmetry functions	40
SLM-MATRIX: a multi-agent trajectory reasoning and verification framework for enhancing language models in materials data extraction	40
Computing grain boundary diagrams of thermodynamic and mechanical properties	40
A computational framework for guiding the MOCVD-growth of wafer-scale 2D materials	40
Superior printed parts using history and augmented machine learning	40
Unsupervised deep denoising for four-dimensional scanning transmission electron microscopy	40
CrysXPP: An explainable property predictor for crystalline materials	39
Dynamics of lattice disorder in perovskite materials, polarization nanoclusters and ferroelectric domain wall structures	39
General invariance and equilibrium conditions for lattice dynamics in 1D, 2D, and 3D materials	39
A database of experimentally measured lithium solid electrolyte conductivities evaluated with machine learning	39
Optimal pre-train/fine-tune strategies for accurate material property predictions	39
Evolution-guided Bayesian optimization for constrained multi-objective optimization in self-driving labs	39
Gaussian process analysis of electron energy loss spectroscopy data: multivariate reconstruction and kernel control	39
Unraveling dislocation-based strengthening in refractory multi-principal element alloys	39
Tunable Schottky barriers and magnetoelectric coupling driven by ferroelectric polarization reversal of MnI3/In2Se3 multiferroic heterostructures	39
Local and correlated studies of humidity-mediated ferroelectric thin film surface charge dynamics	38
Learning from models: high-dimensional analyses on the performance of machine learning interatomic potentials	38
Fast prediction of anharmonic vibrational spectra for complex organic molecules	38
Dynamic mesophase transition induces anomalous suppressed and anisotropic phonon thermal transport	38
How coherence is governing diffuson heat transfer in amorphous solids	37
Two-dimensional Stiefel-Whitney insulators in liganded Xenes	37
DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules	37
Computational screening of sodium solid electrolytes through unsupervised learning	37
The NOMAD Artificial-Intelligence Toolkit: turning materials-science data into knowledge and understanding	37
Crystal structure prediction at finite temperatures	37
The ferroelectric field-effect transistor with negative capacitance	37
Obtaining auxetic and isotropic metamaterials in counterintuitive design spaces: an automated optimization approach and experimental characterization	37
Endless Dirac nodal lines in kagome-metal Ni3In2S2	37
Learning atomic forces from uncertainty-calibrated adversarial attacks	36
Rational design of large anomalous Nernst effect in Dirac semimetals	36
Intriguing magnetoelectric effect in two-dimensional ferromagnetic/perovskite oxide ferroelectric heterostructure	36
No ground truth needed: unsupervised sinogram inpainting for nanoparticle electron tomography (UsiNet) to correct missing wedges	36
Enabling dynamic 3D coherent diffraction imaging via adaptive latent space tuning of generative autoencoders	36
Efficient first-principles electronic transport approach to complex band structure materials: the case of n-type Mg3Sb2	36
Atomistic simulation assisted error-inclusive Bayesian machine learning for probabilistically unraveling the mechanical properties of solidified metals	36
Transferable equivariant graph neural networks for the Hamiltonians of molecules and solids	35
Intermediate polaronic charge transport in organic crystals from a many-body first-principles approach	35
2D spontaneous valley polarization from inversion symmetric single-layer lattices	35
Ferroelectric order in hybrid organic-inorganic perovskite NH4PbI3 with non-polar molecules and small tolerance factor	35
Application of machine learning to assess the influence of microstructure on twin nucleation in Mg alloys	35
Uncovering material deformations via machine learning combined with four-dimensional scanning transmission electron microscopy	35
Targeted materials discovery using Bayesian algorithm execution	35
Understanding phase transitions of α-quartz under dynamic compression conditions by machine-learning driven atomistic simulations	35
Ferroelectricity coexisted with p-orbital ferromagnetism and metallicity in two-dimensional metal oxynitrides	35
Coarse-grained molecular dynamics integrated with convolutional neural network for comparing shapes of temperature sensitive bottlebrushes	34
Advancing first-principles dielectric property prediction of complex microwave materials: an elemental-unit decomposition approach	34

Inverse design of metal–organic frameworks for C2H4/C2H6 separation	34
Machine learning guided high-throughput search of non-oxide garnets	34
Ab initio theory of the nonequilibrium adsorption energy	34
Efficient simulations of charge density waves in the transition metal Dichalcogenide TiSe2	34
Solids that are also liquids: elastic tensors of superionic materials	34
Full-spin-wave-scaled stochastic micromagnetism for mesh-independent simulations of ferromagnetic resonance and reversal	34
Technical review: Time-dependent density functional theory for attosecond physics ranging from gas-phase to solids	33
Trajectory sampling and finite-size effects in first-principles stopping power calculations	33
Giant multiphononic effects in a perovskite oxide	33
Integration of resonant band with asymmetry in ferroelectric tunnel junctions	33
Simple arithmetic operation in latent space can generate a novel three-dimensional graph metamaterials	33
Simulating fluid flow in complex porous materials by integrating the governing equations with deep-layered machines	33
Exploring parameter dependence of atomic minima with implicit differentiation	33
Machine-learned interatomic potentials for transition metal dichalcogenide Mo1−xWxS2−2ySe2y alloys	33
Computational discovery of ultra-strong, stable, and lightweight refractory multi-principal element alloys. Part I: design principles and rapid down-selection	33
Efficient equivariant model for machine learning interatomic potentials	33
Linking atomic structural defects to mesoscale properties in crystalline solids using graph neural networks	33
Design of soft magnetic materials	33
Perturbative solution of fermionic sign problem in quantum Monte Carlo computations	33
Towards atom-level understanding of metal oxide catalysts for the oxygen evolution reaction with machine learning	32
Large language models design sequence-defined macromolecules via evolutionary optimization	32
Machine learning assisted screening of two dimensional chalcogenide ferromagnetic materials with Dzyaloshinskii Moriya interaction	32
Quantum point defects in 2D materials - the QPOD database	32
Machine-learning structural reconstructions for accelerated point defect calculations	32
Non-adiabatic approximations in time-dependent density functional theory: progress and prospects	32
Machine learning for exploring small polaron configurational space	32
Kohn–Sham time-dependent density functional theory with Tamm–Dancoff approximation on massively parallel GPUs	31
Bidirectional mechanical switching window in ferroelectric thin films predicted by first-principle-based simulations	31
Intrinsic hard magnetism and thermal stability of a ThMn12-type permanent magnet	31
Designing architected materials for mechanical compression via simulation, deep learning, and experimentation	31
Higher-order equivariant neural networks for charge density prediction in materials	31
Towards understanding structure–property relations in materials with interpretable deep learning	31
Multi-plane denoising diffusion-based dimensionality expansion for 2D-to-3D reconstruction of microstructures with harmonized sampling	31
Finite-temperature screw dislocation core structures and dynamics in α-titanium	31
Machine learning on properties of multiscale multisource hydroxyapatite nanoparticles datasets with different morphologies and sizes	31
Modeling the effects of salt concentration on aqueous and organic electrolytes	31
The Bell-Evans-Polanyi relation for hydrogen evolution reaction from first-principles	31
Physics and chemistry from parsimonious representations: image analysis via invariant variational autoencoders	30
Exploring high thermal conductivity polymers via interpretable machine learning with physical descriptors	30
Anisotropic Dzyaloshinskii-Moriya interaction protected by D2d crystal symmetry in two-dimensional ternary compounds	30
AI-enabled Lorentz microscopy for quantitative imaging of nanoscale magnetic spin textures	30
Accelerating phase field simulations through a hybrid adaptive Fourier neural operator with U-net backbone	30
Fragile topological band in the checkerboard antiferromagnetic monolayer FeSe	30
Accurate and efficient molecular dynamics based on machine learning and non von Neumann architecture	30
Phase-field modeling of coupled bulk photovoltaic effect and ferroelectric domain manipulation at ultrafast timescales	29
X-ray scattering tensor tomography based finite element modelling of heterogeneous materials	29
Atomistic Line Graph Neural Network for improved materials property predictions	29
Rapid high-fidelity quantum simulations using multi-step nonlinear autoregression and graph embeddings	29
A multi-fidelity machine learning approach to high throughput materials screening	29
Computational synthesis of substrates by crystal cleavage	29
Electronic correlation in nearly free electron metals with beyond-DFT methods	29
Small dataset machine-learning approach for efficient design space exploration: engineering ZnTe-based high-entropy alloys for water splitting	29
Platinum-based catalysts for oxygen reduction reaction simulated with a quantum computer	28
Analytical and numerical modeling of optical second harmonic generation in anisotropic crystals using ♯SHAARP package	28
Visualizing temperature-dependent phase stability in high entropy alloys	28
JAX-BTE: a GPU-accelerated differentiable solver for phonon Boltzmann transport equations	28
Point-defect-driven flattened polar phonon bands in fluorite ferroelectrics	28
A rule-free workflow for the automated generation of databases from scientific literature	28
Magnetic Moment Tensor Potentials for collinear spin-polarized materials reproduce different magnetic states of bcc Fe	28
Author Correction: Polarization switching of HfO2 ferroelectric in bulk and electrode/ferroelectric/electrode heterostructure	28
Primitive to conventional geometry projection for efficient phonon transport calculations	28
Coherent and semicoherent α/β interfaces in titanium: structure, thermodynamics, migration	28
Candidate ferroelectrics via ab initio high-throughput screening of polar materials	28
Development of the reactive force field and silicon dry/wet oxidation process modeling	27
Machine learning Hubbard parameters with equivariant neural networks	27
Enabling rapid X-ray CT characterisation for additive manufacturing using CAD models and deep learning-based reconstruction	27
Discovery of materials for solar thermochemical hydrogen combining machine learning, computational chemistry, experiments and system simulations	27
Understanding and tuning negative longitudinal piezoelectricity in hafnia	27
Glass transition temperature prediction of disordered molecular solids	27
Magnetic order in the computational 2D materials database (C2DB) from high throughput spin spiral calculations	26
Coexistence of superconductivity and topological phase in kagome metals ANb3Bi5 (A = K, Rb, Cs)	26
The best thermoelectrics revisited in the quantum limit	26
Resonant tunneling in disordered borophene nanoribbons with line defects	26
Rapid and flexible segmentation of electron microscopy data using few-shot machine learning	26
Relativistic domain-wall dynamics in van der Waals antiferromagnet MnPS3	26
Accelerating crystal structure search through active learning with neural networks for rapid relaxations	26
Topology-optimized thermal metamaterials traversing full-parameter anisotropic space	26
Recent advances and applications of deep learning methods in materials science	26
Predicting electronic screening for fast Koopmans spectral functional calculations	25
Enhancing transferability of machine learning-based polarizability models in condensed-phase systems via atomic polarizability constraint	25
Nanoscale confinement of phonon flow and heat transport	25
Effect of spin-orbit coupling on the high harmonics from the topological Dirac semimetal Na3Bi	25
Machine learning-driven synthesis of TiZrNbHfTaC5 high-entropy carbide	25
Ferroelectricity at the extreme thickness limit in the archetypal antiferroelectric PbZrO3	25
Mechanism of keyhole pore formation in metal additive manufacturing	25
Predicting column heights and elemental composition in experimental transmission electron microscopy images of high-entropy oxides using deep learning	25
Missed ferroelectricity in methylammonium lead iodide	25
Virtual melting and cyclic transformations between amorphous Si, Si I, and Si IV in a shear band at room temperature	24
High-throughput screening of 2D materials identifies p-type monolayer WS2 as potential ultra-high mobility semiconductor	24
High pressure suppression of plasticity due to an overabundance of shear embryo formation	24
Deep learning potential model of displacement damage in hafnium oxide ferroelectric films	24
Representations of molecules and materials for interpolation of quantum-mechanical simulations via machine learning	24
Data-driven Bayesian model-based prediction of fatigue crack nucleation in Ni-based superalloys	24
Symmetric carbon tetramers forming spin qubits in hexagonal boron nitride	24
Principal component analysis enables the design of deep learning potential precisely capturing LLZO phase transitions	24