npj Computational Materials

Article	Citations
Recent advances and applications of deep learning methods in materials science	217
Machine learning for perovskite materials design and discovery	192
The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design	185
Atomistic Line Graph Neural Network for improved materials property predictions	171
Theoretical prediction of high melting temperature for a Mo–Ru–Ta–W HCP multiprincipal element alloy	162
Exchange-correlation functionals for band gaps of solids: benchmark, reparametrization and machine learning	158
Inverse-designed spinodoid metamaterials	152
Discovery of high-entropy ceramics via machine learning	135
Completing density functional theory by machine learning hidden messages from molecules	122
Ab initio theory of the negatively charged boron vacancy qubit in hexagonal boron nitride	120
A critical examination of compound stability predictions from machine-learned formation energies	119
Generative adversarial networks (GAN) based efficient sampling of chemical composition space for inverse design of inorganic materials	115
Benchmarking graph neural networks for materials chemistry	114
Complex strengthening mechanisms in the NbMoTaW multi-principal element alloy	113
Machine-learned interatomic potentials by active learning: amorphous and liquid hafnium dioxide	104
Machine-learning informed prediction of high-entropy solid solution formation: Beyond the Hume-Rothery rules	101
Benchmarking materials property prediction methods: the Matbench test set and Automatminer reference algorithm	99
Quantum simulations of materials on near-term quantum computers	96
Phase-field modeling of grain evolutions in additive manufacturing from nucleation, growth, to coarsening	96
Random forest machine learning models for interpretable X-ray absorption near-edge structure spectrum-property relationships	96
Understanding important features of deep learning models for segmentation of high-resolution transmission electron microscopy images	93
Machine-learning structural and electronic properties of metal halide perovskites using a hierarchical convolutional neural network	92
The electrode tortuosity factor: why the conventional tortuosity factor is not well suited for quantifying transport in porous Li-ion battery electrodes and what to use instead	90
Mechanism of keyhole pore formation in metal additive manufacturing	87
Two-step machine learning enables optimized nanoparticle synthesis	87

Pores for thought: generative adversarial networks for stochastic reconstruction of 3D multi-phase electrode microstructures with periodic boundaries	87
Machine learning the Hubbard U parameter in DFT+U using Bayesian optimization	83
High-throughput discovery of high Curie point two-dimensional ferromagnetic materials	82
Biquadratic exchange interactions in two-dimensional magnets	82
Fundamental electronic structure and multiatomic bonding in 13 biocompatible high-entropy alloys	81
Machine learning in concrete science: applications, challenges, and best practices	79
Machine learning for accelerating the discovery of high-performance donor/acceptor pairs in non-fullerene organic solar cells	78
Performant implementation of the atomic cluster expansion (PACE) and application to copper and silicon	78
Frequency-dependent dielectric constant prediction of polymers using machine learning	77
Machine-learned interatomic potentials for alloys and alloy phase diagrams	76
Accelerating materials discovery using artificial intelligence, high performance computing and robotics	73
Concepts of the half-valley-metal and quantum anomalous valley Hall effect	73
Two-dimensional Stiefel-Whitney insulators in liganded Xenes	72
Deep learning framework for material design space exploration using active transfer learning and data augmentation	71
Accelerating phase-field-based microstructure evolution predictions via surrogate models trained by machine learning methods	71
Predicting aqueous stability of solid with computed Pourbaix diagram using SCAN functional	70
Symmetry-enforced Weyl phonons	69
Compositionally restricted attention-based network for materials property predictions	68
Accurate and scalable graph neural network force field and molecular dynamics with direct force architecture	65
Predominance of non-adiabatic effects in zero-point renormalization of the electronic band gap	65
Band degeneracy enhanced thermoelectric performance in layered oxyselenides by first-principles calculations	65
In silico modelling of cancer nanomedicine, across scales and transport barriers	64
Computational screening study of double transition metal carbonitrides M′2M″CNO2-MXene as catalysts for hydrogen evolution reaction	63
Benchmarking the performance of Bayesian optimization across multiple experimental materials science domains	62
High-throughput computational screening for two-dimensional magnetic materials based on experimental databases of three-dimensional compounds	62
Explainable machine learning in materials science	60
Small data machine learning in materials science	60
Ab initio modeling of the energy landscape for screw dislocations in body-centered cubic high-entropy alloys	58
High-throughput density functional perturbation theory and machine learning predictions of infrared, piezoelectric, and dielectric responses	58
Thermal transport and phase transitions of zirconia by on-the-fly machine-learned interatomic potentials	58
Understanding and design of metallic alloys guided by phase-field simulations	57
Machine learning property prediction for organic photovoltaic devices	57
Giant anomalous Hall and Nernst effect in magnetic cubic Heusler compounds	57
Sign-reversible valley-dependent Berry phase effects in 2D valley-half-semiconductors	57
Negative Poisson’s ratio in two-dimensional honeycomb structures	56
A review of the recent progress in battery informatics	56
Machine learning assisted design of γ′-strengthened Co-base superalloys with multi-performance optimization	56
Teaching solid mechanics to artificial intelligence—a fast solver for heterogeneous materials	55
Restructured single parabolic band model for quick analysis in thermoelectricity	55
Representations of molecules and materials for interpolation of quantum-mechanical simulations via machine learning	55
MatSciBERT: A materials domain language model for text mining and information extraction	53
Application of phase-field method in rechargeable batteries	53
Nanodevices engineering and spin transport properties of MnBi2Te4 monolayer	53
Magnetic Moment Tensor Potentials for collinear spin-polarized materials reproduce different magnetic states of bcc Fe	53
Understanding X-ray absorption spectra by means of descriptors and machine learning algorithms	51
Constrained crystals deep convolutional generative adversarial network for the inverse design of crystal structures	50
Electrosorption at metal surfaces from first principles	49
Theoretical dissection of superconductivity in two-dimensional honeycomb borophene oxide B2O crystal with a high stability	48
High performance Wannier interpolation of Berry curvature and related quantities with WannierBerri code	48
Computational high-throughput screening of alloy nanoclusters for electrocatalytic hydrogen evolution	47

Graph neural networks for an accurate and interpretable prediction of the properties of polycrystalline materials	46
Stability of heterogeneous single-atom catalysts: a scaling law mapping thermodynamics to kinetics	45
Active learning for the power factor prediction in diamond-like thermoelectric materials	45
A Bayesian framework for adsorption energy prediction on bimetallic alloy catalysts	45
Efficient electron extraction of SnO2 electron transport layer for lead halide perovskite solar cell	44
High-throughput predictions of metal–organic framework electronic properties: theoretical challenges, graph neural networks, and data exploration	44
Ab initio molecular dynamics and materials design for embedded phase-change memory	44
Active learning of deep surrogates for PDEs: application to metasurface design	43
Uncertainty quantification in molecular simulations with dropout neural network potentials	43
Anomalous Hall effect, magneto-optical properties, and nonlinear optical properties of twisted graphene systems	43
Mechanistic data-driven prediction of as-built mechanical properties in metal additive manufacturing	42
Damage mechanism identification in composites via machine learning and acoustic emission	42
Interpretable machine-learning strategy for soft-magnetic property and thermal stability in Fe-based metallic glasses	42
Electron correlation effects on exchange interactions and spin excitations in 2D van der Waals materials	42
The origin of the lattice thermal conductivity enhancement at the ferroelectric phase transition in GeTe	42
Electrically and magnetically switchable nonlinear photocurrent in РТ-symmetric magnetic topological quantum materials	42
Data augmentation in microscopic images for material data mining	41
Low-dimensional non-metal catalysts: principles for regulating p-orbital-dominated reactivity	41
A general and transferable deep learning framework for predicting phase formation in materials	41
Predicting stable crystalline compounds using chemical similarity	41
An artificial intelligence-aided virtual screening recipe for two-dimensional materials discovery	41
Materials property prediction for limited datasets enabled by feature selection and joint learning with MODNet	41
Inverse design of metasurfaces with non-local interactions	40
Chemical hardness-driven interpretable machine learning approach for rapid search of photocatalysts	40
Efficient training of ANN potentials by including atomic forces via Taylor expansion and application to water and a transition-metal oxide	40
Designing polymer nanocomposites with high energy density using machine learning	40
Accelerated design and characterization of non-uniform cellular materials via a machine-learning based framework	40
Nanometer-size Na cluster formation in micropore of hard carbon as origin of higher-capacity Na-ion battery	39
Automated high-throughput Wannierisation	39
Neural network reactive force field for C, H, N, and O systems	39
A machine-learned interatomic potential for silica and its relation to empirical models	38
Graph theory approach to determine configurations of multidentate and high coverage adsorbates for heterogeneous catalysis	38
Rapid and flexible segmentation of electron microscopy data using few-shot machine learning	37
Tunable chemical complexity to control atomic diffusion in alloys	37
Coupling physics in machine learning to predict properties of high-temperatures alloys	37
Design high-entropy carbide ceramics from machine learning	37
Topological representations of crystalline compounds for the machine-learning prediction of materials properties	36
Diverse electronic and magnetic properties of CrS2 enabling strain-controlled 2D lateral heterostructure spintronic devices	36
Predicting the propensity for thermally activated β events in metallic glasses via interpretable machine learning	35
Machine learning and evolutionary prediction of superhard B-C-N compounds	35
An improved symmetry-based approach to reciprocal space path selection in band structure calculations	34
Automation of diffusion database development in multicomponent alloys from large number of experimental composition profiles	34
Prediction of thermoelectric performance for layered IV-V-VI semiconductors by high-throughput ab initio calculations and machine learning	34
Bimeron clusters in chiral antiferromagnets	34
Applications of quantum computing for investigations of electronic transitions in phenylsulfonyl-carbazole TADF emitters	34
Pure bulk orbital and spin photocurrent in two-dimensional ferroelectric materials	34
PRISMS-Fatigue computational framework for fatigue analysis in polycrystalline metals and alloys	34
Machine-learned impurity level prediction for semiconductors: the example of Cd-based chalcogenides	33
High-dimensional neural network potentials for magnetic systems using spin-dependent atom-centered symmetry functions	33
Machine learning potentials for metal-organic frameworks using an incremental learning approach	33
Accelerated design and discovery of perovskites with high conductivity for energy applications through machine learning	33
Uncertainty quantification and reduction in metal additive manufacturing	33
Learning two-phase microstructure evolution using neural operators and autoencoder architectures	33
Bayesian force fields from active learning for simulation of inter-dimensional transformation of stanene	33
Accelerated discovery of a large family of quaternary chalcogenides with very low lattice thermal conductivity	32
Time-dependent density-functional theory molecular-dynamics study on amorphization of Sc-Sb-Te alloy under optical excitation	32
Computational search for magnetic and non-magnetic 2D topological materials using unified spin–orbit spillage screening	32
Efficient construction of linear models in materials modeling and applications to force constant expansions	32
Automated crystal structure analysis based on blackbox optimisation	32
The microscopic origin of DMI in magnetic bilayers and prediction of giant DMI in new bilayers	32
2D spontaneous valley polarization from inversion symmetric single-layer lattices	31
Design of two-dimensional carbon-nitride structures by tuning the nitrogen concentration	31
Machine learning method for tight-binding Hamiltonian parameterization from ab-initio band structure	31
Data-driven discovery of 2D materials by deep generative models	31
A deep convolutional neural network for real-time full profile analysis of big powder diffraction data	31
EPIC STAR: a reliable and efficient approach for phonon- and impurity-limited charge transport calculations	31
Diffusion of lithium ions in Lithium-argyrodite solid-state electrolytes	30
Phase classification of multi-principal element alloys via interpretable machine learning	30
Quantum point defects in 2D materials - the QPOD database	30
Discovering plasticity models without stress data	30
A nonlinear magnonic nano-ring resonator	30
Hybrid magnetorheological elastomers enable versatile soft actuators	30
Phase field modeling for the morphological and microstructural evolution of metallic materials under environmental attack	30
Accurate simulation of surfaces and interfaces of ten FCC metals and steel using Lennard–Jones potentials	29
Three-terminal Weyl complex with double surface arcs in a cubic lattice	29
Microstructure segmentation with deep learning encoders pre-trained on a large microscopy dataset	29
Cluster-formula-embedded machine learning for design of multicomponent β-Ti alloys with low Young’s modulus	29
AtomSets as a hierarchical transfer learning framework for small and large materials datasets	29
Bayesian optimization with adaptive surrogate models for automated experimental design	29
A scheme for simulating multi-level phase change photonics materials	29

Segregation-assisted spinodal and transient spinodal phase separation at grain boundaries	28
On the mechanistic origins of maximum strength in nanocrystalline metals	28
Deep learning for visualization and novelty detection in large X-ray diffraction datasets	28
AFLOW-XtalFinder: a reliable choice to identify crystalline prototypes	28
Simulating Raman spectra by combining first-principles and empirical potential approaches with application to defective MoS2	28
Auxetic two-dimensional transition metal selenides and halides	28
Uncertainty-quantified parametrically homogenized constitutive models (UQ-PHCMs) for dual-phase α/β titanium alloys	28
Design rules for strong electro-optic materials	27
Machine learning of superconducting critical temperature from Eliashberg theory	27
Identifying candidate hosts for quantum defects via data mining	27
Anion charge and lattice volume dependent lithium ion migration in compounds with fcc anion sublattices	27
Ensemble learning-iterative training machine learning for uncertainty quantification and automated experiment in atom-resolved microscopy	27
Off-the-shelf deep learning is not enough, and requires parsimony, Bayesianity, and causality	27
Specialising neural network potentials for accurate properties and application to the mechanical response of titanium	27
Colossal switchable photocurrents in topological Janus transition metal dichalcogenides	27
Prediction of high thermoelectric performance in the low-dimensional metal halide Cs3Cu2I5	27
Radiative properties of quantum emitters in boron nitride from excited state calculations and Bayesian analysis	26
In-silico synthesis of lowest-pressure high-Tc ternary superhydrides	26
Microscopic mechanism of unusual lattice thermal transport in TlInTe2	26
Microstructural impacts on ionic conductivity of oxide solid electrolytes from a combined atomistic-mesoscale approach	26
Simulating fluid flow in complex porous materials by integrating the governing equations with deep-layered machines	26
Predicting thermoelectric properties from chemical formula with explicitly identifying dopant effects	25
Flash sintering incubation kinetics	25
Super-resolving material microstructure image via deep learning for microstructure characterization and mechanical behavior analysis	25
Oxygen-vacancy induced magnetic phase transitions in multiferroic thin films	25
A multiscale polymerization framework towards network structure and fracture of double-network hydrogels	25
Intersystem crossing and exciton–defect coupling of spin defects in hexagonal boron nitride	25
First-principles search of hot superconductivity in La-X-H ternary hydrides	25
Optimal band structure for thermoelectrics with realistic scattering and bands	25
Computational design for 4D printing of topology optimized multi-material active composites	25
Switchable Rashba anisotropy in layered hybrid organic–inorganic perovskite by hybrid improper ferroelectricity	25
Statistics of the NiCoCr medium-entropy alloy: Novel aspects of an old puzzle	25
Identifying the ground state structures of point defects in solids	25
MaterialsAtlas.org: a materials informatics web app platform for materials discovery and survey of state-of-the-art	25
Tunable sliding ferroelectricity and magnetoelectric coupling in two-dimensional multiferroic MnSe materials	24
Unsupervised machine learning for discovery of promising half-Heusler thermoelectric materials	24
Evolutionary computing and machine learning for discovering of low-energy defect configurations	24
Extracting local nucleation fields in permanent magnets using machine learning	24
Data-driven magneto-elastic predictions with scalable classical spin-lattice dynamics	24
Stone–Wales defects in hexagonal boron nitride as ultraviolet emitters	24
Role of atomic-scale thermal fluctuations in the coercivity	24
Predicting lattice thermal conductivity via machine learning: a mini review	24
High-throughput phase-field simulations and machine learning of resistive switching in resistive random-access memory	24
Viscosity in water from first-principles and deep-neural-network simulations	24
Quantum anomalous Hall effect in two-dimensional magnetic insulator heterojunctions	24
Automated pipeline for superalloy data by text mining	24
Predicting adsorption ability of adsorbents at arbitrary sites for pollutants using deep transfer learning	23
Identification of crystal symmetry from noisy diffraction patterns by a shape analysis and deep learning	23
Inverse design of truss lattice materials with superior buckling resistance	23
An atomistic approach for the structural and electronic properties of twisted bilayer graphene-boron nitride heterostructures	23
Defect-mediated Rashba engineering for optimizing electrical transport in thermoelectric BiTeI	23
A systematic approach to generating accurate neural network potentials: the case of carbon	23
Physics-informed deep learning for solving phonon Boltzmann transport equation with large temperature non-equilibrium	23
Field-free spin–orbit torque perpendicular magnetization switching in ultrathin nanostructures	23
Temperature and composition dependent screw dislocation mobility in austenitic stainless steels from large-scale molecular dynamics	23
Systematic coarse-graining of epoxy resins with machine learning-informed energy renormalization	23
Predicting synthesizable multi-functional edge reconstructions in two-dimensional transition metal dichalcogenides	23
Anion order in oxysulfide perovskites: origins and implications	23
Multifunctional antiperovskites driven by strong magnetostructural coupling	22
Structural and chemical mechanisms governing stability of inorganic Janus nanotubes	22
Comprehensive scan for nonmagnetic Weyl semimetals with nonlinear optical response	22
Tunable spin textures in polar antiferromagnetic hybrid organic–inorganic perovskites by electric and magnetic fields	22
Comparing crystal structures with symmetry and geometry	22
How coherence is governing diffuson heat transfer in amorphous solids	22
TransPolymer: a Transformer-based language model for polymer property predictions	22
How dopants limit the ultrahigh thermal conductivity of boron arsenide: a first principles study	22
Machine-learned metrics for predicting the likelihood of success in materials discovery	21
Artificial neural network approach for multiphase segmentation of battery electrode nano-CT images	21
The optical tweezer of skyrmions	21
Towards fully automated GW band structure calculations: What we can learn from 60.000 self-energy evaluations	21
Dynamic observation of dendrite growth on lithium metal anode during battery charging/discharging cycles	21
Composition design of high-entropy alloys with deep sets learning	21
Switchable half-metallicity in A-type antiferromagnetic NiI2 bilayer coupled with ferroelectric In2Se3	21
Causal analysis of competing atomistic mechanisms in ferroelectric materials from high-resolution scanning transmission electron microscopy data	21
Low-overhead distribution strategy for simulation and optimization of large-area metasurfaces	21
Artificial generation of representative single Li-ion electrode particle architectures from microscopy data	21
High-throughput screening of hypothetical metal-organic frameworks for thermal conductivity	21
Hole-doping induced ferromagnetism in 2D materials	21
Modelling charge transport and electro-optical characteristics of quantum dot light-emitting diodes	21
Prediction of protected band edge states and dielectric tunable quasiparticle and excitonic properties of monolayer MoSi2N4	21