npj Computational Materials

Article	Citations
Author Correction: Active learning for accelerated design of layered materials	713
Multiscale modeling of ultrafast melting phenomena	435
Dynamical phase-field model of cavity electromagnonic systems	409
Ultra-fast interpretable machine-learning potentials	233
Active learning to overcome exponential-wall problem for effective structure prediction of chemical-disordered materials	233
Understanding X-ray absorption spectra by means of descriptors and machine learning algorithms	213
First principles methodology for studying magnetotransport in narrow gap semiconductors with ZrTe5 example	205
Facilitated the discovery of new γ/γ′ Co-based superalloys by combining first-principles and machine learning	185
Vibrationally resolved optical excitations of the nitrogen-vacancy center in diamond	149
Prediction of intrinsic multiferroicity and large valley polarization in a layered Janus material	140
Environmental screening and ligand-field effects to magnetism in CrI3 monolayer	136
cmtj: Simulation package for analysis of multilayer spintronic devices	128
Accelerated identification of equilibrium structures of multicomponent inorganic crystals using machine learning potentials	125
Machine learning-aided first-principles calculations of redox potentials	125
Advancing organic photovoltaic materials by machine learning-driven design with polymer-unit fingerprints	123
Electron-mediated anharmonicity and its role in the Raman spectrum of graphene	112
Structure and properties of graphullerene: a semiconducting two-dimensional C60 crystal	106
Accurate piezoelectric tensor prediction with equivariant attention tensor graph neural network	103
A critical examination of robustness and generalizability of machine learning prediction of materials properties	99
Quantum anomalous hall effect in collinear antiferromagnetism	99
Insights into oxygen diffusion in rare earth disilicate environmental barrier coatings	95
Machine learning enhanced analysis of EBSD data for texture representation	94
Bayesian optimization acquisition functions for accelerated search of cluster expansion convex hull of multi-component alloys	92
RadonPy: automated physical property calculation using all-atom classical molecular dynamics simulations for polymer informatics	92
Identifying the ground state structures of point defects in solids	83

Crosslinking degree variations enable programming and controlling soft fracture via sideways cracking	83
MatSciBERT: A materials domain language model for text mining and information extraction	82
JARVIS-Leaderboard: a large scale benchmark of materials design methods	81
Exploring the role of nonlocal Coulomb interactions in perovskite transition metal oxides	80
Sparse representation for machine learning the properties of defects in 2D materials	79
Strain and ligand effects in the 1-D limit: reactivity of steps	79
Active learning of effective Hamiltonian for super-large-scale atomic structures	79
Imaging atomic-scale chemistry from fused multi-modal electron microscopy	77
Electro-chemo-mechanical modelling of structural battery composite full cells	74
Machine learning revealed giant thermal conductivity reduction by strong phonon localization in two-angle disordered twisted multilayer graphene	72
Agent-based multimodal information extraction for nanomaterials	72
A process-synergistic active learning framework for high-strength Al-Si alloys design	71
Conversion of twisted light to twisted excitons using carbon nanotubes	71
Emergence of local scaling relations in adsorption energies on high-entropy alloys	70
High-throughput discovery of fluoride-ion conductors via a decoupled, dynamic, and iterative (DDI) framework	68
First principles study of dielectric properties of ferroelectric perovskite oxides with extended Hubbard interactions	68
A machine learning approach to designing and understanding tough, degradable polyamides	67
First-principles search of hot superconductivity in La-X-H ternary hydrides	67
Machine learning surrogate for 3D phase-field modeling of ferroelectric tip-induced electrical switching	67
Machine vision-based detections of transparent chemical vessels toward the safe automation of material synthesis	67
Combined study of phase transitions in the P2-type NaXNi1/3Mn2/3O2 cathode material: experimental, ab-initio and multiphase-field results	67
Discovering novel lead-free solder alloy by multi-objective Bayesian active learning with experimental uncertainty	65
Tracking perovskite crystallization via deep learning-based feature detection on 2D X-ray scattering data	64
Phase-field framework with constraints and its applications to ductile fracture in polycrystals and fatigue	64
Prediction of the Cu oxidation state from EELS and XAS spectra using supervised machine learning	64
Ultrafast laser-driven topological spin textures on a 2D magnet	63
A graph based approach to model charge transport in semiconducting polymers	62
From electrons to phase diagrams with machine learning potentials using pyiron based automated workflows	61
Tunable sliding ferroelectricity and magnetoelectric coupling in two-dimensional multiferroic MnSe materials	61
Persistent half-metallic ferromagnetism in a (111)-oriented manganite superlattice	60
High-speed and low-power molecular dynamics processing unit (MDPU) with ab initio accuracy	60
Elucidation of molecular-level charge transport in an organic amorphous system	59
Machine learning on multiple topological materials datasets	59
Comment on “Machine learning enhanced analysis of EBSD data for texture representation”	59
Photoinduced ferroelectric phase transition triggering photocatalytic water splitting	58
High-throughput materials exploration system for the anomalous Hall effect using combinatorial experiments and machine learning	58
Sampling lattices in semi-grand canonical ensemble with autoregressive machine learning	58
Author Correction: High-throughput study of the anomalous Hall effect	58
Author Correction: Characterization of domain distributions by second harmonic generation in ferroelectrics	58
Ab initio dynamical mean field theory with natural orbitals renormalization group impurity solver	57
Pushing charge equilibration-based machine learning potentials to their limits	57
Machine-learning-accelerated mechanistic exploration of interface modification in lithium metal anode	56
Magnetic wallpaper Dirac fermions and topological magnetic Dirac insulators	56
High-accuracy physical property prediction for pure organics via molecular representation learning: bridging data to discovery	56
Accelerating superconductor discovery through tempered deep learning of the electron-phonon spectral function	55
Transition state structure detection with machine learningś	54
High-throughput discovery of perturbation-induced topological magnons	53
Data-driven low-rank approximation for the electron-hole kernel and acceleration of time-dependent GW calculations	53
Theory of non-Hermitian topological whispering gallery	53
Integrated modeling to control vaporization-induced composition change during additive manufacturing of nickel-based superalloys	53

Optimizing casting process using a combination of small data machine learning and phase-field simulations	52
Predicting the synthesizability of crystalline inorganic materials from the data of known material compositions	52
A machine learning method to quantitatively predict alpha phase morphology in additively manufactured Ti-6Al-4V	51
Machine learning of superconducting critical temperature from Eliashberg theory	51
Magnons from time-dependent density-functional perturbation theory and nonempirical Hubbard functionals	51
Deep convolutional neural networks to restore single-shot electron microscopy images	51
Approaches for handling high-dimensional cluster expansions of ionic systems	50
Computational morphogenesis for liquid crystal elastomer metamaterial	49
Predicting elastic properties of hard-coating alloys using ab-initio and machine learning methods	49
Deep material network via a quilting strategy: visualization for explainability and recursive training for improved accuracy	48
Prediction of ambient pressure conventional superconductivity above 80 K in hydride compounds	48
Prediction of protected band edge states and dielectric tunable quasiparticle and excitonic properties of monolayer MoSi2N4	48
A classical equation that accounts for observations of non-Arrhenius and cryogenic grain boundary migration	48
Effect of exchange-correlation functionals on the estimation of migration barriers in battery materials	47
Accurate and efficient band-gap predictions for metal halide perovskites at finite temperature	47
Minimal crystallographic descriptors of sorption properties in hypothetical MOFs and role in sequential learning optimization	47
Lanthanide molecular nanomagnets as probabilistic bits	47
Exploring superionic conduction in lithium oxyhalide solid electrolytes considering composition and structural factors	47
Deep learning approaches for instantaneous laser absorptance prediction in additive manufacturing	47
PID3Net: a deep learning approach for single-shot coherent X-ray diffraction imaging of dynamic phenomena	46
Optimal pre-train/fine-tune strategies for accurate material property predictions	46
Unveiling hydrogen chemical states in supersaturated amorphous alumina via machine learning-driven atomistic modeling	46
XGBoost model for electrocaloric temperature change prediction in ceramics	46
SLM-MATRIX: a multi-agent trajectory reasoning and verification framework for enhancing language models in materials data extraction	46
An NV− center in magnesium oxide as a spin qubit for hybrid quantum technologies	46
Modeling of ultrafast X-ray induced magnetization dynamics in magnetic multilayer systems	45
High-dimensional neural network potentials for magnetic systems using spin-dependent atom-centered symmetry functions	45
Superior printed parts using history and augmented machine learning	45
A dynamic Bayesian optimized active recommender system for curiosity-driven partially Human-in-the-loop automated experiments	45
A computational framework for guiding the MOCVD-growth of wafer-scale 2D materials	45
Discovery of new high-pressure phases – integrating high-throughput DFT simulations, graph neural networks, and active learning	45
Author Correction: Physics guided deep learning for generative design of crystal materials with symmetry constraints	45
Tunable Schottky barriers and magnetoelectric coupling driven by ferroelectric polarization reversal of MnI3/In2Se3 multiferroic heterostructures	45
CrysXPP: An explainable property predictor for crystalline materials	44
Dynamics of lattice disorder in perovskite materials, polarization nanoclusters and ferroelectric domain wall structures	44
Dipolar spin relaxation of divacancy qubits in silicon carbide	44
General invariance and equilibrium conditions for lattice dynamics in 1D, 2D, and 3D materials	44
Concurrent multi-peak Bragg coherent x-ray diffraction imaging of 3D nanocrystal lattice displacement via global optimization	43
Unraveling dislocation-based strengthening in refractory multi-principal element alloys	43
Finding the semantic similarity in single-particle diffraction images using self-supervised contrastive projection learning	43
Accelerating multiscale electronic stopping power predictions with time-dependent density functional theory and machine learning	43
Computing grain boundary diagrams of thermodynamic and mechanical properties	42
Unraveling charge effects on interface reactions and dendrite growth in lithium metal anode	42
nNPipe: a neural network pipeline for automated analysis of morphologically diverse catalyst systems	42
Unsupervised deep denoising for four-dimensional scanning transmission electron microscopy	42
Evolution-guided Bayesian optimization for constrained multi-objective optimization in self-driving labs	42
Fast prediction of anharmonic vibrational spectra for complex organic molecules	42
A database of experimentally measured lithium solid electrolyte conductivities evaluated with machine learning	42
The ferroelectric field-effect transistor with negative capacitance	41
Transferable equivariant graph neural networks for the Hamiltonians of molecules and solids	41
Obtaining auxetic and isotropic metamaterials in counterintuitive design spaces: an automated optimization approach and experimental characterization	41
Two-dimensional Stiefel-Whitney insulators in liganded Xenes	41
DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules	41
Understanding phase transitions of α-quartz under dynamic compression conditions by machine-learning driven atomistic simulations	40
No ground truth needed: unsupervised sinogram inpainting for nanoparticle electron tomography (UsiNet) to correct missing wedges	40
Enabling dynamic 3D coherent diffraction imaging via adaptive latent space tuning of generative autoencoders	40
Atomistic simulation assisted error-inclusive Bayesian machine learning for probabilistically unraveling the mechanical properties of solidified metals	40
The NOMAD Artificial-Intelligence Toolkit: turning materials-science data into knowledge and understanding	40
Dynamic mesophase transition induces anomalous suppressed and anisotropic phonon thermal transport	40
Efficient simulations of charge density waves in the transition metal Dichalcogenide TiSe2	39
Inverse design of metal–organic frameworks for C2H4/C2H6 separation	39
Application of machine learning to assess the influence of microstructure on twin nucleation in Mg alloys	39
Intriguing magnetoelectric effect in two-dimensional ferromagnetic/perovskite oxide ferroelectric heterostructure	39
Learning from models: high-dimensional analyses on the performance of machine learning interatomic potentials	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
Coarse-grained molecular dynamics integrated with convolutional neural network for comparing shapes of temperature sensitive bottlebrushes	38
Intermediate polaronic charge transport in organic crystals from a many-body first-principles approach	38
Learning atomic forces from uncertainty-calibrated adversarial attacks	38
Efficient first-principles electronic transport approach to complex band structure materials: the case of n-type Mg3Sb2	38
2D spontaneous valley polarization from inversion symmetric single-layer lattices	37
Targeted materials discovery using Bayesian algorithm execution	37
Crystal structure prediction at finite temperatures	37
Computational screening of sodium solid electrolytes through unsupervised learning	37
Local and correlated studies of humidity-mediated ferroelectric thin film surface charge dynamics	37
Ferroelectricity coexisted with p-orbital ferromagnetism and metallicity in two-dimensional metal oxynitrides	37
Endless Dirac nodal lines in kagome-metal Ni3In2S2	37
Ferroelectric order in hybrid organic-inorganic perovskite NH4PbI3 with non-polar molecules and small tolerance factor	37
Machine learning guided high-throughput search of non-oxide garnets	36
How coherence is governing diffuson heat transfer in amorphous solids	36

Anisotropic Dzyaloshinskii-Moriya interaction protected by D2d crystal symmetry in two-dimensional ternary compounds	36
Giant multiphononic effects in a perovskite oxide	36
Exploring parameter dependence of atomic minima with implicit differentiation	36
Advancing first-principles dielectric property prediction of complex microwave materials: an elemental-unit decomposition approach	36
Higher-order equivariant neural networks for charge density prediction in materials	36
Machine-learned interatomic potentials for transition metal dichalcogenide Mo1−xWxS2−2ySe2y alloys	36
Machine learning for exploring small polaron configurational space	35
Efficient equivariant model for machine learning interatomic potentials	35
Large language models design sequence-defined macromolecules via evolutionary optimization	35
Finite-temperature screw dislocation core structures and dynamics in α-titanium	35
Solids that are also liquids: elastic tensors of superionic materials	35
Integration of resonant band with asymmetry in ferroelectric tunnel junctions	35
Simple arithmetic operation in latent space can generate a novel three-dimensional graph metamaterials	35
Non-adiabatic approximations in time-dependent density functional theory: progress and prospects	35
Kohn–Sham time-dependent density functional theory with Tamm–Dancoff approximation on massively parallel GPUs	34
Full-spin-wave-scaled stochastic micromagnetism for mesh-independent simulations of ferromagnetic resonance and reversal	34
Small dataset machine-learning approach for efficient design space exploration: engineering ZnTe-based high-entropy alloys for water splitting	34
Design of soft magnetic materials	34
Ab initio theory of the nonequilibrium adsorption energy	34
Linking atomic structural defects to mesoscale properties in crystalline solids using graph neural networks	34
Fragile topological band in the checkerboard antiferromagnetic monolayer FeSe	34
Perturbative solution of fermionic sign problem in quantum Monte Carlo computations	34
AI-enabled Lorentz microscopy for quantitative imaging of nanoscale magnetic spin textures	33
Designing architected materials for mechanical compression via simulation, deep learning, and experimentation	33
Bidirectional mechanical switching window in ferroelectric thin films predicted by first-principle-based simulations	33
Physics and chemistry from parsimonious representations: image analysis via invariant variational autoencoders	33
Technical review: Time-dependent density functional theory for attosecond physics ranging from gas-phase to solids	33
Towards understanding structure–property relations in materials with interpretable deep learning	33
Modeling the effects of salt concentration on aqueous and organic electrolytes	33
Machine learning assisted screening of two dimensional chalcogenide ferromagnetic materials with Dzyaloshinskii Moriya interaction	33
Computational discovery of ultra-strong, stable, and lightweight refractory multi-principal element alloys. Part I: design principles and rapid down-selection	33
Exploring high thermal conductivity polymers via interpretable machine learning with physical descriptors	33
Trajectory sampling and finite-size effects in first-principles stopping power calculations	33
Multi-plane denoising diffusion-based dimensionality expansion for 2D-to-3D reconstruction of microstructures with harmonized sampling	33
Machine-learning structural reconstructions for accelerated point defect calculations	33
Chemical foundation model-guided design of high ionic conductivity electrolyte formulations	33
Accelerating phase field simulations through a hybrid adaptive Fourier neural operator with U-net backbone	32
Accurate and efficient molecular dynamics based on machine learning and non von Neumann architecture	32
A multi-fidelity machine learning approach to high throughput materials screening	32
Intrinsic hard magnetism and thermal stability of a ThMn12-type permanent magnet	31
The Bell-Evans-Polanyi relation for hydrogen evolution reaction from first-principles	31
The best thermoelectrics revisited in the quantum limit	31
Towards atom-level understanding of metal oxide catalysts for the oxygen evolution reaction with machine learning	31
Atomistic Line Graph Neural Network for improved materials property predictions	31
Enabling rapid X-ray CT characterisation for additive manufacturing using CAD models and deep learning-based reconstruction	31
Quantum point defects in 2D materials - the QPOD database	31
Rapid high-fidelity quantum simulations using multi-step nonlinear autoregression and graph embeddings	30
Phase-field modeling of coupled bulk photovoltaic effect and ferroelectric domain manipulation at ultrafast timescales	30
Resonant tunneling in disordered borophene nanoribbons with line defects	30
Primitive to conventional geometry projection for efficient phonon transport calculations	30
Development of the reactive force field and silicon dry/wet oxidation process modeling	30
Coexistence of superconductivity and topological phase in kagome metals ANb3Bi5 (A = K, Rb, Cs)	29
Magnetic Moment Tensor Potentials for collinear spin-polarized materials reproduce different magnetic states of bcc Fe	29
Author Correction: Polarization switching of HfO2 ferroelectric in bulk and electrode/ferroelectric/electrode heterostructure	29
X-ray scattering tensor tomography based finite element modelling of heterogeneous materials	29
Machine learning Hubbard parameters with equivariant neural networks	29
Platinum-based catalysts for oxygen reduction reaction simulated with a quantum computer	29
Relativistic domain-wall dynamics in van der Waals antiferromagnet MnPS3	29
Point-defect-driven flattened polar phonon bands in fluorite ferroelectrics	29
Discovery of materials for solar thermochemical hydrogen combining machine learning, computational chemistry, experiments and system simulations	28
Digitalizing metallic materials from image segmentation to multiscale solutions via physics informed operator learning	28
Electronic correlation in nearly free electron metals with beyond-DFT methods	28
Candidate ferroelectrics via ab initio high-throughput screening of polar materials	28
Shaping freeform nanophotonic devices with geometric neural parameterization	28
Analytical and numerical modeling of optical second harmonic generation in anisotropic crystals using ♯SHAARP package	28
JAX-BTE: a GPU-accelerated differentiable solver for phonon Boltzmann transport equations	28
Coherent and semicoherent α/β interfaces in titanium: structure, thermodynamics, migration	28
Recent advances and applications of deep learning methods in materials science	28
Glass transition temperature prediction of disordered molecular solids	28
Topology-optimized thermal metamaterials traversing full-parameter anisotropic space	27
Rapid and flexible segmentation of electron microscopy data using few-shot machine learning	27
Understanding and tuning negative longitudinal piezoelectricity in hafnia	27
Mechanism of keyhole pore formation in metal additive manufacturing	27
A rule-free workflow for the automated generation of databases from scientific literature	27
Accelerating crystal structure search through active learning with neural networks for rapid relaxations	27
Magnetic order in the computational 2D materials database (C2DB) from high throughput spin spiral calculations	27
Predicting electronic screening for fast Koopmans spectral functional calculations	27
Enhancing transferability of machine learning-based polarizability models in condensed-phase systems via atomic polarizability constraint	26
Factorial design analytics on effects of material parameter uncertainties in multiphysics modeling of additive manufacturing	26
Predicting column heights and elemental composition in experimental transmission electron microscopy images of high-entropy oxides using deep learning	26
Principal component analysis enables the design of deep learning potential precisely capturing LLZO phase transitions	26
Self-supervised probabilistic models for exploring shape memory alloys	26
Realistic magnetic thermodynamics by local quantization of a semiclassical Heisenberg model	26
Electronic Moment Tensor Potentials include both electronic and vibrational degrees of freedom	26
Light-induced above-room-temperature Chern insulators in group-IV Xenes	26
Deep learning potential model of displacement damage in hafnium oxide ferroelectric films	26
Ferroelectricity at the extreme thickness limit in the archetypal antiferroelectric PbZrO3	26
Automated generation of structure datasets for machine learning potentials and alloys	26
Sub-bandgap charge harvesting and energy up-conversion in metal halide perovskites: ab initio quantum dynamics	26
An interleaved physics-based deep-learning framework as a new cycle jumping approach for microstructurally small fatigue crack growth simulations	26
Nanoscale confinement of phonon flow and heat transport	25
Missed ferroelectricity in methylammonium lead iodide	25
Effect of spin-orbit coupling on the high harmonics from the topological Dirac semimetal Na3Bi	25
Virtual melting and cyclic transformations between amorphous Si, Si I, and Si IV in a shear band at room temperature	25
Representations of molecules and materials for interpolation of quantum-mechanical simulations via machine learning	25