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Explore services

Discover API services for materials science, chemistry, data processing, and more.

Explore services

Discover API services for materials science, chemistry, data processing, and more.

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Crystal Structure Prediction

Crystal Structure Prediction

17 items

Predict stable crystal structures from composition

Property Prediction

Property Prediction

16 items

Predict material or molecular properties

Structure Relaxation

Structure Relaxation

9 items

Optimize and relax atomic structures

More:ToolingGenerative DesignBenchmarksData ValidationFormat ConversionSimulationImage AnalysisModel TrainingSequence Analysis

Popular

Most used assets this week

Energy Gate Diagnostic

Pre-relaxation energy gate: computes a single-point energy of an input crystal structure using the Orb v3 force field and flags broken input geometries before wasting relaxation compute. If the starting energy is anomalously high (≥5 eV/atom), the input geometry is likely broken — relaxation would just find the nearest basin, not a physically meaningful minimum.

Jul 27

SMACT Composition Screening

CPU-only SMACT 4.0.0 wrapper for enumerating charge-neutral, electronegativity-compatible candidate compositions. Rule-based plausibility screen; not a stability or structure predictor.

Jul 31

Robocrystallographer

CPU-only, offline crystal-structure description service. Upload a CIF or POSCAR/VASP file to receive a human-readable description plus symmetry-inequivalent local environments, connectivity, warnings, and provenance. It describes the encoded structure; it does not predict stability or material properties.

Jul 31

Crystalite

is a lightweight EDM diffusion transformer for crystalline materials discovery. Generate novel crystals de novo (atom types + coordinates + lattice) or predict structures for fixed compositions (CSP). Trained on MP20; optional MPTS-52 CSP checkpoint for larger cells.

Aug 6

mCGCNN

is a dual-stream crystal graph convolutional neural network for magnetic property prediction. It augments the full crystal graph with a magnetic subgraph that encodes metal–ligand–metal exchange geometry (Goodenough–Kanamori–Anderson rules), then predicts the DFT total magnetic moment per unit cell in μB. Saturation magnetization (Ms / μ₀ Ms) is derived from that moment and the CIF cell volume. Best for ligand-bridged magnets (oxides, nitrides, and other M–X–M systems). Not recommended for elemental metals or alloys without bridging ligands — those are out of distribution for this checkpoint. Input structures must contain at least one magnetic site (transition metal, lanthanoid, or actinoid). Paper: https://arxiv.org/abs/2606.28458 Code: https://github.com/SouravMal/mCGCNN

Jul 20

elemental-indices

Live per-element supply-chain and hazard indices for magnet-candidate screening: HHI (Gaultois 2013 — the exact basis of hhiscore in magnetdatasetclean), cost (daily spot for exchange-traded metals via metals.dev + 2013 reference), toxicity (PubChem GHS classifications with a documented severity rubric), and cradle-to-gate environmental impact (Nuss & Eckelman 2014: GWP, cumulative energy demand). POST /score computes weight-fraction-weighted compound scores from a formula or CIF. Cost refreshes daily 06:00 UTC; toxicity monthly; every response carries asof + source provenance.

Jul 23

Crystal-Likeness Score (PU-CGCNN)

Predict how synthesizable an inorganic crystal is from its structure. Returns a Crystal-Likeness Score (CLscore) in [0, 1] using Jang et al.'s positive–unlabeled CGCNN ensemble — a soft prior complementary to energy-above-hull filters.

Jul 30

GGen

is a materials discovery service for proposing, relaxing, and ranking crystal structures across chemical systems. It combines symmetry-aware crystal generation with geometry optimization to help researchers explore compositions, scout element substitutions, review phase stability, and export promising candidates for follow-up simulation or analysis.

Apr 27

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Find services for your field

Chemistry

Chemistry

17 items

Chemical compounds, reactions, and molecular data

Materials Science

Materials Science

15 items

Research and data related to materials science, crystallography, and solid-state physics

Physics

Physics

13 items

Physics simulations, data, and computational tools

More:BiologyData ScienceAI & Machine LearningNeuroscienceEnergy & SustainabilityClimate & EnvironmentQuantum Computing

Latest

Recently added

Crystalite

is a lightweight EDM diffusion transformer for crystalline materials discovery. Generate novel crystals de novo (atom types + coordinates + lattice) or predict structures for fixed compositions (CSP). Trained on MP20; optional MPTS-52 CSP checkpoint for larger cells.

Aug 6

hermes-routes

Native agent-authored routes for hermes.

Aug 3

SMACT Composition Screening

CPU-only SMACT 4.0.0 wrapper for enumerating charge-neutral, electronegativity-compatible candidate compositions. Rule-based plausibility screen; not a stability or structure predictor.

Jul 31

Robocrystallographer

CPU-only, offline crystal-structure description service. Upload a CIF or POSCAR/VASP file to receive a human-readable description plus symmetry-inequivalent local environments, connectivity, warnings, and provenance. It describes the encoded structure; it does not predict stability or material properties.

Jul 31

Crystal-Likeness Score (PU-CGCNN)

Predict how synthesizable an inorganic crystal is from its structure. Returns a Crystal-Likeness Score (CLscore) in [0, 1] using Jang et al.'s positive–unlabeled CGCNN ensemble — a soft prior complementary to energy-above-hull filters.

Jul 30

Energy Gate Diagnostic

Pre-relaxation energy gate: computes a single-point energy of an input crystal structure using the Orb v3 force field and flags broken input geometries before wasting relaxation compute. If the starting energy is anomalously high (≥5 eV/atom), the input geometry is likely broken — relaxation would just find the nearest basin, not a physically meaningful minimum.

Jul 27

elemental-indices

Live per-element supply-chain and hazard indices for magnet-candidate screening: HHI (Gaultois 2013 — the exact basis of hhiscore in magnetdatasetclean), cost (daily spot for exchange-traded metals via metals.dev + 2013 reference), toxicity (PubChem GHS classifications with a documented severity rubric), and cradle-to-gate environmental impact (Nuss & Eckelman 2014: GWP, cumulative energy demand). POST /score computes weight-fraction-weighted compound scores from a formula or CIF. Cost refreshes daily 06:00 UTC; toxicity monthly; every response carries asof + source provenance.

Jul 23

mCGCNN

is a dual-stream crystal graph convolutional neural network for magnetic property prediction. It augments the full crystal graph with a magnetic subgraph that encodes metal–ligand–metal exchange geometry (Goodenough–Kanamori–Anderson rules), then predicts the DFT total magnetic moment per unit cell in μB. Saturation magnetization (Ms / μ₀ Ms) is derived from that moment and the CIF cell volume. Best for ligand-bridged magnets (oxides, nitrides, and other M–X–M systems). Not recommended for elemental metals or alloys without bridging ligands — those are out of distribution for this checkpoint. Input structures must contain at least one magnetic site (transition metal, lanthanoid, or actinoid). Paper: https://arxiv.org/abs/2606.28458 Code: https://github.com/SouravMal/mCGCNN

Jul 20
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