npj Computational Materials

Article	Citations
Recent advances and applications of deep learning methods in materials science	206
On-the-fly active learning of interpretable Bayesian force fields for atomistic rare events	198
Machine learning for perovskite materials design and discovery	187
The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design	179
Theoretical prediction of high melting temperature for a Mo–Ru–Ta–W HCP multiprincipal element alloy	160
Atomistic Line Graph Neural Network for improved materials property predictions	159
Exchange-correlation functionals for band gaps of solids: benchmark, reparametrization and machine learning	156
Inverse-designed spinodoid metamaterials	148
Discovery of high-entropy ceramics via machine learning	134
Completing density functional theory by machine learning hidden messages from molecules	120
Ab initio theory of the negatively charged boron vacancy qubit in hexagonal boron nitride	118
A critical examination of compound stability predictions from machine-learned formation energies	115
Generative adversarial networks (GAN) based efficient sampling of chemical composition space for inverse design of inorganic materials	114
Complex strengthening mechanisms in the NbMoTaW multi-principal element alloy	111
Benchmarking graph neural networks for materials chemistry	110
Machine-learned interatomic potentials by active learning: amorphous and liquid hafnium dioxide	100
Machine-learning informed prediction of high-entropy solid solution formation: Beyond the Hume-Rothery rules	100
Benchmarking materials property prediction methods: the Matbench test set and Automatminer reference algorithm	97
Phase-field modeling of grain evolutions in additive manufacturing from nucleation, growth, to coarsening	95
Quantum simulations of materials on near-term quantum computers	94
Random forest machine learning models for interpretable X-ray absorption near-edge structure spectrum-property relationships	93
Understanding important features of deep learning models for segmentation of high-resolution transmission electron microscopy images	91
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	89
Multiscale computational understanding and growth of 2D materials: a review	89
Machine-learning structural and electronic properties of metal halide perovskites using a hierarchical convolutional neural network	88

Pores for thought: generative adversarial networks for stochastic reconstruction of 3D multi-phase electrode microstructures with periodic boundaries	87
Mechanism of keyhole pore formation in metal additive manufacturing	85
Two-step machine learning enables optimized nanoparticle synthesis	84
High-throughput discovery of high Curie point two-dimensional ferromagnetic materials	82
Biquadratic exchange interactions in two-dimensional magnets	81
Machine learning the Hubbard U parameter in DFT+U using Bayesian optimization	81
Fundamental electronic structure and multiatomic bonding in 13 biocompatible high-entropy alloys	78
Machine learning for accelerating the discovery of high-performance donor/acceptor pairs in non-fullerene organic solar cells	77
Machine learning in concrete science: applications, challenges, and best practices	76
Performant implementation of the atomic cluster expansion (PACE) and application to copper and silicon	76
Frequency-dependent dielectric constant prediction of polymers using machine learning	75
Machine-learned interatomic potentials for alloys and alloy phase diagrams	73
Two-dimensional Stiefel-Whitney insulators in liganded Xenes	70
Concepts of the half-valley-metal and quantum anomalous valley Hall effect	69
Deep learning framework for material design space exploration using active transfer learning and data augmentation	69
Accelerating phase-field-based microstructure evolution predictions via surrogate models trained by machine learning methods	68
Predicting aqueous stability of solid with computed Pourbaix diagram using SCAN functional	68
Symmetry-enforced Weyl phonons	68
Accelerating materials discovery using artificial intelligence, high performance computing and robotics	68
Compositionally restricted attention-based network for materials property predictions	66
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	63
Computational screening study of double transition metal carbonitrides M′2M″CNO2-MXene as catalysts for hydrogen evolution reaction	62
Accurate and scalable graph neural network force field and molecular dynamics with direct force architecture	62
High-throughput computational screening for two-dimensional magnetic materials based on experimental databases of three-dimensional compounds	61
Benchmarking the performance of Bayesian optimization across multiple experimental materials science domains	61
In silico modelling of cancer nanomedicine, across scales and transport barriers	59
Ab initio modeling of the energy landscape for screw dislocations in body-centered cubic high-entropy alloys	57
High-throughput density functional perturbation theory and machine learning predictions of infrared, piezoelectric, and dielectric responses	57
Magnetic and superconducting phase diagrams and transition temperatures predicted using text mining and machine learning	56
Giant anomalous Hall and Nernst effect in magnetic cubic Heusler compounds	56
Teaching solid mechanics to artificial intelligence—a fast solver for heterogeneous materials	55
Negative Poisson’s ratio in two-dimensional honeycomb structures	54
Explainable machine learning in materials science	54
Thermal transport and phase transitions of zirconia by on-the-fly machine-learned interatomic potentials	54
Understanding and design of metallic alloys guided by phase-field simulations	54
Machine learning assisted design of γ′-strengthened Co-base superalloys with multi-performance optimization	54
Sign-reversible valley-dependent Berry phase effects in 2D valley-half-semiconductors	52
A review of the recent progress in battery informatics	52
Application of phase-field method in rechargeable batteries	52
Predicting densities and elastic moduli of SiO2-based glasses by machine learning	52
Machine learning property prediction for organic photovoltaic devices	52
Small data machine learning in materials science	52
Restructured single parabolic band model for quick analysis in thermoelectricity	51
Representations of molecules and materials for interpolation of quantum-mechanical simulations via machine learning	51
Nanodevices engineering and spin transport properties of MnBi2Te4 monolayer	51
Magnetic Moment Tensor Potentials for collinear spin-polarized materials reproduce different magnetic states of bcc Fe	50
Theoretical dissection of superconductivity in two-dimensional honeycomb borophene oxide B2O crystal with a high stability	47
MatSciBERT: A materials domain language model for text mining and information extraction	47
Electrosorption at metal surfaces from first principles	47

Constrained crystals deep convolutional generative adversarial network for the inverse design of crystal structures	47
Computational high-throughput screening of alloy nanoclusters for electrocatalytic hydrogen evolution	46
Understanding X-ray absorption spectra by means of descriptors and machine learning algorithms	46
Stability of heterogeneous single-atom catalysts: a scaling law mapping thermodynamics to kinetics	45
Ab initio molecular dynamics and materials design for embedded phase-change memory	44
High performance Wannier interpolation of Berry curvature and related quantities with WannierBerri code	44
High-throughput predictions of metal–organic framework electronic properties: theoretical challenges, graph neural networks, and data exploration	43
Active learning of deep surrogates for PDEs: application to metasurface design	43
Active learning for the power factor prediction in diamond-like thermoelectric materials	43
Graph neural networks for an accurate and interpretable prediction of the properties of polycrystalline materials	43
Uncertainty quantification in molecular simulations with dropout neural network potentials	42
Mechanistic data-driven prediction of as-built mechanical properties in metal additive manufacturing	42
A Bayesian framework for adsorption energy prediction on bimetallic alloy catalysts	42
Anomalous Hall effect, magneto-optical properties, and nonlinear optical properties of twisted graphene systems	42
Interpretable machine-learning strategy for soft-magnetic property and thermal stability in Fe-based metallic glasses	42
Electrically and magnetically switchable nonlinear photocurrent in РТ-symmetric magnetic topological quantum materials	41
Materials property prediction for limited datasets enabled by feature selection and joint learning with MODNet	41
Electron correlation effects on exchange interactions and spin excitations in 2D van der Waals materials	41
Designing polymer nanocomposites with high energy density using machine learning	40
Damage mechanism identification in composites via machine learning and acoustic emission	40
Efficient electron extraction of SnO2 electron transport layer for lead halide perovskite solar cell	40
A general and transferable deep learning framework for predicting phase formation in materials	40
Predicting stable crystalline compounds using chemical similarity	40
Accelerated design and characterization of non-uniform cellular materials via a machine-learning based framework	40
The origin of the lattice thermal conductivity enhancement at the ferroelectric phase transition in GeTe	40
Efficient training of ANN potentials by including atomic forces via Taylor expansion and application to water and a transition-metal oxide	40
An artificial intelligence-aided virtual screening recipe for two-dimensional materials discovery	39
Data augmentation in microscopic images for material data mining	39
Low-dimensional non-metal catalysts: principles for regulating p-orbital-dominated reactivity	39
Neural network reactive force field for C, H, N, and O systems	39
Inverse design of metasurfaces with non-local interactions	39
Automated high-throughput Wannierisation	38
Graph theory approach to determine configurations of multidentate and high coverage adsorbates for heterogeneous catalysis	37
Nanometer-size Na cluster formation in micropore of hard carbon as origin of higher-capacity Na-ion battery	37
Chemical hardness-driven interpretable machine learning approach for rapid search of photocatalysts	37
Coupling physics in machine learning to predict properties of high-temperatures alloys	37
Stabilizing mechanism of single-atom catalysts on a defective carbon surface	36
Rapid and flexible segmentation of electron microscopy data using few-shot machine learning	36
Tunable chemical complexity to control atomic diffusion in alloys	36
Topological representations of crystalline compounds for the machine-learning prediction of materials properties	35
A machine-learned interatomic potential for silica and its relation to empirical models	35
Design high-entropy carbide ceramics from machine learning	35
PRISMS-Fatigue computational framework for fatigue analysis in polycrystalline metals and alloys	34
Predicting the propensity for thermally activated β events in metallic glasses via interpretable machine learning	34
Prediction of thermoelectric performance for layered IV-V-VI semiconductors by high-throughput ab initio calculations and machine learning	33
PRISMS-PF: A general framework for phase-field modeling with a matrix-free finite element method	33
Automation of diffusion database development in multicomponent alloys from large number of experimental composition profiles	33
Pure bulk orbital and spin photocurrent in two-dimensional ferroelectric materials	33
Bimeron clusters in chiral antiferromagnets	33
Bayesian force fields from active learning for simulation of inter-dimensional transformation of stanene	33
An improved symmetry-based approach to reciprocal space path selection in band structure calculations	33
Uncertainty quantification and reduction in metal additive manufacturing	33
Machine learning and evolutionary prediction of superhard B-C-N compounds	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
Learning two-phase microstructure evolution using neural operators and autoencoder architectures	32
Efficient construction of linear models in materials modeling and applications to force constant expansions	32
Applications of quantum computing for investigations of electronic transitions in phenylsulfonyl-carbazole TADF emitters	32
Computational search for magnetic and non-magnetic 2D topological materials using unified spin–orbit spillage screening	32
Time-dependent density-functional theory molecular-dynamics study on amorphization of Sc-Sb-Te alloy under optical excitation	32
Diverse electronic and magnetic properties of CrS2 enabling strain-controlled 2D lateral heterostructure spintronic devices	32
2D spontaneous valley polarization from inversion symmetric single-layer lattices	31
Machine-learned impurity level prediction for semiconductors: the example of Cd-based chalcogenides	31
Design of two-dimensional carbon-nitride structures by tuning the nitrogen concentration	31
Accelerated discovery of a large family of quaternary chalcogenides with very low lattice thermal conductivity	31
EPIC STAR: a reliable and efficient approach for phonon- and impurity-limited charge transport calculations	31
A deep convolutional neural network for real-time full profile analysis of big powder diffraction data	30
Phase classification of multi-principal element alloys via interpretable machine learning	30
Accelerated design and discovery of perovskites with high conductivity for energy applications through machine learning	30
Diffusion of lithium ions in Lithium-argyrodite solid-state electrolytes	30
Machine learning method for tight-binding Hamiltonian parameterization from ab-initio band structure	30
Phase field modeling for the morphological and microstructural evolution of metallic materials under environmental attack	30
Cluster-formula-embedded machine learning for design of multicomponent β-Ti alloys with low Young’s modulus	29
Discovering plasticity models without stress data	29
Quantum point defects in 2D materials - the QPOD database	29
High-dimensional neural network potentials for magnetic systems using spin-dependent atom-centered symmetry functions	29
Three-terminal Weyl complex with double surface arcs in a cubic lattice	29
A nonlinear magnonic nano-ring resonator	29
AtomSets as a hierarchical transfer learning framework for small and large materials datasets	28
AFLOW-XtalFinder: a reliable choice to identify crystalline prototypes	28

Segregation-assisted spinodal and transient spinodal phase separation at grain boundaries	28
Molecular dynamics simulation of graphene sinking during chemical vapor deposition growth on semi-molten Cu substrate	28
Uncertainty-quantified parametrically homogenized constitutive models (UQ-PHCMs) for dual-phase α/β titanium alloys	28
Deep learning for visualization and novelty detection in large X-ray diffraction datasets	28
A scheme for simulating multi-level phase change photonics materials	28
Microstructure segmentation with deep learning encoders pre-trained on a large microscopy dataset	28
Simulating Raman spectra by combining first-principles and empirical potential approaches with application to defective MoS2	27
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
Bayesian optimization with adaptive surrogate models for automated experimental design	27
Hybrid magnetorheological elastomers enable versatile soft actuators	27
Auxetic two-dimensional transition metal selenides and halides	27
Anion charge and lattice volume dependent lithium ion migration in compounds with fcc anion sublattices	27
Colossal switchable photocurrents in topological Janus transition metal dichalcogenides	27
On the mechanistic origins of maximum strength in nanocrystalline metals	27
Prediction of high thermoelectric performance in the low-dimensional metal halide Cs3Cu2I5	26
Off-the-shelf deep learning is not enough, and requires parsimony, Bayesianity, and causality	26
Radiative properties of quantum emitters in boron nitride from excited state calculations and Bayesian analysis	26
Machine learning potentials for metal-organic frameworks using an incremental learning approach	26
Accurate simulation of surfaces and interfaces of ten FCC metals and steel using Lennard–Jones potentials	26
Data-driven discovery of 2D materials by deep generative models	26
Ensemble learning-iterative training machine learning for uncertainty quantification and automated experiment in atom-resolved microscopy	26
Microscopic mechanism of unusual lattice thermal transport in TlInTe2	26
Specialising neural network potentials for accurate properties and application to the mechanical response of titanium	26
Statistics of the NiCoCr medium-entropy alloy: Novel aspects of an old puzzle	25
MaterialsAtlas.org: a materials informatics web app platform for materials discovery and survey of state-of-the-art	25
Optimal band structure for thermoelectrics with realistic scattering and bands	25
Intersystem crossing and exciton–defect coupling of spin defects in hexagonal boron nitride	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	24
High-throughput phase-field simulations and machine learning of resistive switching in resistive random-access memory	24
Tunable sliding ferroelectricity and magnetoelectric coupling in two-dimensional multiferroic MnSe materials	24
Quantum anomalous Hall effect in two-dimensional magnetic insulator heterojunctions	24
Evolutionary computing and machine learning for discovering of low-energy defect configurations	24
Flash sintering incubation kinetics	24
Super-resolving material microstructure image via deep learning for microstructure characterization and mechanical behavior analysis	24
Data-driven magneto-elastic predictions with scalable classical spin-lattice dynamics	24
Unsupervised machine learning for discovery of promising half-Heusler thermoelectric materials	24
Automated pipeline for superalloy data by text mining	24
Switchable Rashba anisotropy in layered hybrid organic–inorganic perovskite by hybrid improper ferroelectricity	24
Microstructural impacts on ionic conductivity of oxide solid electrolytes from a combined atomistic-mesoscale approach	24
In-silico synthesis of lowest-pressure high-Tc ternary superhydrides	24
Role of atomic-scale thermal fluctuations in the coercivity	24
Predicting thermoelectric properties from chemical formula with explicitly identifying dopant effects	23
Predicting lattice thermal conductivity via machine learning: a mini review	23
Inverse design of truss lattice materials with superior buckling resistance	23
Simulating fluid flow in complex porous materials by integrating the governing equations with deep-layered machines	23
Temperature and composition dependent screw dislocation mobility in austenitic stainless steels from large-scale molecular dynamics	23
Extracting local nucleation fields in permanent magnets using machine learning	23
Identifying the ground state structures of point defects in solids	23
A systematic approach to generating accurate neural network potentials: the case of carbon	23
Defect-mediated Rashba engineering for optimizing electrical transport in thermoelectric BiTeI	23
Predicting synthesizable multi-functional edge reconstructions in two-dimensional transition metal dichalcogenides	23
Stone–Wales defects in hexagonal boron nitride as ultraviolet emitters	22
Identification of crystal symmetry from noisy diffraction patterns by a shape analysis and deep learning	22
Physics-informed deep learning for solving phonon Boltzmann transport equation with large temperature non-equilibrium	22
Anion order in oxysulfide perovskites: origins and implications	22
Predicting adsorption ability of adsorbents at arbitrary sites for pollutants using deep transfer learning	22
Systematic coarse-graining of epoxy resins with machine learning-informed energy renormalization	22
Field-free spin–orbit torque perpendicular magnetization switching in ultrathin nanostructures	22
Computational design for 4D printing of topology optimized multi-material active composites	22
Multifunctional antiperovskites driven by strong magnetostructural coupling	22
Structural and chemical mechanisms governing stability of inorganic Janus nanotubes	22
First-principles search of hot superconductivity in La-X-H ternary hydrides	22
Machine-learned metrics for predicting the likelihood of success in materials discovery	21
An atomistic approach for the structural and electronic properties of twisted bilayer graphene-boron nitride heterostructures	21
Viscosity in water from first-principles and deep-neural-network simulations	21
The optical tweezer of skyrmions	21
How dopants limit the ultrahigh thermal conductivity of boron arsenide: a first principles study	21
Comparing crystal structures with symmetry and geometry	21
How coherence is governing diffuson heat transfer in amorphous solids	21
Tunable spin textures in polar antiferromagnetic hybrid organic–inorganic perovskites by electric and magnetic fields	21
Composition design of high-entropy alloys with deep sets learning	21
Causal analysis of competing atomistic mechanisms in ferroelectric materials from high-resolution scanning transmission electron microscopy data	21
Artificial neural network approach for multiphase segmentation of battery electrode nano-CT images	20
Ferroelectricity coexisted with p-orbital ferromagnetism and metallicity in two-dimensional metal oxynitrides	20
High-throughput computational-experimental screening protocol for the discovery of bimetallic catalysts	20
Chiral logic computing with twisted antiferromagnetic magnon modes	20
Artificial generation of representative single Li-ion electrode particle architectures from microscopy data	20
Intersectional nanotwinned diamond-the hardest polycrystalline diamond by design	20
Three-dimensional coherent X-ray diffraction imaging via deep convolutional neural networks	20
Towards fully automated GW band structure calculations: What we can learn from 60.000 self-energy evaluations	20
Van der Waals force-induced intralayer ferroelectric-to-antiferroelectric transition via interlayer sliding in bilayer group-IV monochalcogenides	20
Uncertainty quantification and composition optimization for alloy additive manufacturing through a CALPHAD-based ICME framework	20
Switchable half-metallicity in A-type antiferromagnetic NiI2 bilayer coupled with ferroelectric In2Se3	20
Hole-doping induced ferromagnetism in 2D materials	20
Prediction of the Curie temperature considering the dependence of the phonon free energy on magnetic states	20
TransPolymer: a Transformer-based language model for polymer property predictions	20
Dynamic observation of dendrite growth on lithium metal anode during battery charging/discharging cycles	20
Comprehensive scan for nonmagnetic Weyl semimetals with nonlinear optical response	20
Perfect short-range ordered alloy with line-compound-like properties in the ZnSnN2:ZnO system	19
Strong electron–phonon coupling influences carrier transport and thermoelectric performances in group-IV/V elemental monolayers	19
Data driven discovery of conjugated polyelectrolytes for optoelectronic and photocatalytic applications	19
Coexistence of nontrivial topological properties and strong ferromagnetic fluctuations in quasi-one-dimensional A2Cr3As3	19