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Models
297
Datasets
245
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60 entries in Materials Science

Showing 48 of 60

ABC-1MADSKAILabOne million CAD-quality 3D shapes drawn from the ABC dataset — the foundation training corpus for the Make-A-Shape and WaLa generative models.CAD Geometry CorpusBrowse
aqcat25-datasetSandboxAQ13.5M DFT calculation trajectories for heterogeneous catalysis and ML potential training.Computational ChemistryBrowse
AtompackLeMaterialAtompack — Hub-hosted public atomistic ML datasets distributed in the Atompack format, part of the broader LeMaterial effort to standardise atomistic data exchange.Atomistic ML FormatBrowse
atomvison_atomistic_stm_images_2d_materials_unique_chemical_compositions_structure_v1-1foundry-mlSimulated STM images for 2D materials with unique chemical compositions — supports ML on atomic-resolution microscopy.STM ImagingBrowse
atomvison_simulated_atomistic_stem_images_2d_materials_unique_chemical_compositions_structure_bafoundry-mlSimulated STEM images for 2D materials — paired with structure metadata for training ML models on electron microscopy.STEM ImagingBrowse
ChemBenchjablonkagroupManually curated benchmark of 3,000+ chemistry and materials science questions across spectroscopy, reactivity, synthesis, and property prediction for evaluating LLMs.Chemistry BenchmarkBrowse
dataset_concrete_compressive_strengthfoundry-mlConcrete compressive-strength dataset — mix-design and test data for ML-based civil-engineering material modelling.Construction MaterialsBrowse
dataset_debyet_aflowfoundry-mlDebye temperature data from the AFLOW database — fundamental thermal-vibrational descriptor for ML materials property prediction.Thermal PropertiesBrowse
dataset_exfoliationefoundry-mlExfoliation energy dataset for 2D materials — supports ML-driven discovery of layered compounds suitable for monolayer isolation.2D MaterialsBrowse
dataset_li_conductivityfoundry-mlLithium-ion conductivity dataset for solid electrolytes — supports ML discovery of next-generation battery materials.Battery MaterialsBrowse
dataset_metallicglass_dmaxfoundry-mlMaximum glass-forming diameter (Dmax) data for bulk metallic glasses — for ML screening of casting feasibility.Metallic GlassBrowse
dataset_metallicglass_rcfoundry-mlCritical cooling rate (Rc) data for metallic glasses — supports ML prediction of glass-forming ability.Metallic GlassBrowse
dataset_metallicglass_rc_llmfoundry-mlLLM-extracted critical cooling rate data for metallic glasses — text-mined complement to the structured Rc dataset.Metallic GlassBrowse
dataset_mg_alloyfoundry-mlMagnesium alloy dataset — composition and property data for ML modelling of lightweight structural alloys.Alloy PropertiesBrowse
dataset_perovskite_asrfoundry-mlArea-specific resistance (ASR) data for perovskite electrodes — used in solid-oxide fuel cell ML modelling.Perovskite PropertiesBrowse
dataset_perovskite_conductivityfoundry-mlIonic and electronic conductivity measurements for perovskite materials — supports ML screening for solid-oxide fuel cell electrolytes.Perovskite PropertiesBrowse
dataset_perovskite_formationefoundry-mlFormation energies for perovskite compounds — supports ML screening for stability and synthesisability.Perovskite PropertiesBrowse
dataset_perovskite_habsfoundry-mlHot-air-balance (HABS) data for perovskite materials — thermal-stability characterisation supporting durability ML.Perovskite PropertiesBrowse
dataset_perovskite_stability_updatedfoundry-mlCurated perovskite stability data (updated release) for benchmarking ML models on photovoltaic-material durability prediction.Perovskite PropertiesBrowse
dataset_perovskite_tecfoundry-mlThermal expansion coefficients for perovskite materials — curated for ML thermal-property prediction.Perovskite PropertiesBrowse
dataset_rpv_ttsfoundry-mlReactor pressure-vessel (RPV) transition-temperature shift dataset — supports ML prediction of irradiation embrittlement.Reactor MaterialsBrowse
dataset_thermalcond_aflowfoundry-mlThermal conductivity values from the AFLOW database — supports ML-based screening of thermal management materials.Thermal PropertiesBrowse
dataset_thermalexp_aflowfoundry-mlThermal expansion coefficients from the AFLOW database — for ML thermal-mechanical modelling of inorganic materials.Thermal PropertiesBrowse
dielectric_constant_v1-1foundry-mlDielectric-constant values for inorganic compounds — supports ML screening of high-k materials for capacitors and devices.Dielectric PropertiesBrowse
diffusion_v1-4foundry-mlDiffusion-coefficient dataset for inorganic systems — supports ML modelling of solid-state ion transport and electrolyte design.Diffusion CoefficientsBrowse
direct_electron_detectorceleritas_xs_simulated_readout_images_electron_counting_model_v1-1foundry-mlSimulated readout images from a Celeritas XS direct-electron detector — training data for electron-counting models in cryo-EM and STEM.Electron MicroscopyBrowse
double_perovskite_bandgap_v1-1foundry-mlComputed band gaps for double-perovskite compounds — supports ML-based screening for photovoltaic and optoelectronic applications.Electronic StructureBrowse
elastic_tensor_v1-1foundry-mlElastic tensor data for inorganic materials — supports ML prediction of bulk and shear moduli.Mechanical PropertiesBrowse
electromigration_v1-1foundry-mlElectromigration data for interconnect materials — supports ML prediction of failure rates in microelectronic devices.Failure MechanismsBrowse
elwood_md_v1-2foundry-mlElwood molecular-dynamics simulation set — trajectory and energy data for ML molecular-property prediction.Molecular DynamicsBrowse
excess-propertiesmist-modelsExcess-property dataset for binary/ternary chemical mixtures — used to fine-tune MIST mixtures models on thermodynamic deviations from ideal mixing.Mixture PropertiesBrowse
foundry_aflow_band_gaps_v1-1foundry-mlBand-gap values from the AFLOW high-throughput materials database, formatted for ML model training and evaluation.Electronic StructureBrowse
foundry_mp_band_gaps_v1-1foundry-mlBand-gap values curated from the Materials Project for ML benchmarking on inorganic electronic structure.Electronic StructureBrowse
foundry_oqmd_band_gaps_v1-1foundry-mlBand-gap values from the Open Quantum Materials Database (OQMD), prepared for ML benchmarking on inorganic crystal electronic structure.Electronic StructureBrowse
foundry_osdb_v1-1foundry-mlOrganic Semiconductor Database (OSDB) curated for ML — supports property prediction and screening of organic optoelectronic materials.Organic SemiconductorsBrowse
foundry_stan_segmentation_v1-1foundry-mlSegmentation dataset (STAN) for materials microscopy images — supports ML feature extraction from electron-microscopy data.Microscopy SegmentationBrowse
heusler_magnetization_v1-1foundry-mlMagnetisation data for Heusler-alloy compounds — supports ML discovery of half-metallic and magnetocaloric materials.Magnetic PropertiesBrowse
LeMat-BulkLeMaterialPrimary bulk materials database aggregating 1M+ crystal structures with DFT-computed formation energies, band gaps, and elastic properties for materials discovery.Materials ScienceBrowse
LeMat-Bulk-DFT-HullLeMaterialDFT convex hull reference data for materials stability analysis.Materials ScienceBrowse
LeMat-Bulk-DFT-Hull-AllLeMaterialComplete DFT convex hull dataset for bulk materials discovery.Materials ScienceBrowse
LeMat-Bulk-MLIP-Formation-EnergiesLeMaterialFormation energies for LeMat-Bulk computed with multiple ML interatomic potentials (MLIPs) — used to benchmark MLIPs and to derive MLIP-based stability estimates.Materials ScienceBrowse
LeMat-Bulk-MLIP-HullLeMaterialConvex hull data for bulk materials from MLIP calculations.Materials ScienceBrowse
LeMat-BulkUniqueLeMaterialDeduplicated companion to LeMat-Bulk — unique inorganic crystal structures aggregated across source databases, intended as a curated training set for generative materials models.Materials ScienceBrowse
LeMat-GenBench-embeddingsLeMaterialPrecomputed embeddings for the LeMat-GenBench benchmark — drop-in features for evaluating generative materials models on crystal-structure prediction and downstream tasks.Materials EmbeddingsBrowse
LeMat-RhoLeMaterialLeMat-Rho — ~69,000 inorganic crystal structures computed at the r2SCAN meta-GGA level in VASP, with charge densities, Bader charges, forces, stresses, and energies for ML training and electronic-structure analysis.Materials ScienceBrowse
LeMat-SynthLeMaterialLeMat-Synth — curated dataset of materials synthesis procedures and conditions, supporting work on synthesizability prediction and synthesis-route generation.Materials SynthesisBrowse
LeMat-Synth-PapersLeMaterialLeMat-Synth-Papers — curated corpus of materials synthesis literature, intended for training and evaluating models that extract synthesis procedures and recipes from text.Materials LiteratureBrowse
LeMat-TrajLeMaterialLarge-scale molecular dynamics trajectory dataset for training machine learning interatomic potentials across diverse bulk material compositions.Materials ScienceBrowse

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