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Catalysis Hub GraphQL API Guide
Overview
Catalysis Hub is an open-access database of DFT-calculated reaction energies and activation barriers for heterogeneous catalysis, developed at SUNCAT Center (Stanford/SLAC). It aggregates computational results from published studies, enabling researchers to search, compare, and reuse DFT data for catalyst screening and mechanism validation.
The GraphQL endpoint provides structured access to reactions, publications, and atomic structures. All data is linked to peer-reviewed publications and includes computational details (DFT code, XC functional, surface facet, coverage).
Authentication
No authentication required. Catalysis Hub is a free public service with no API keys.
GraphQL Schema
Endpoint: https://api.catalysis-hub.org/graphql
All queries use HTTP POST with a JSON query field. Responses follow the Relay connection pattern (edges/node).
Root Query Types
Query Description reactionsDFT-computed reaction energies and barriers publicationsPublished studies linked to reaction data systemsAtomic structure data (ASE Atoms objects) speciesChemical species involved in reactions
Reaction Fields
chemicalComposition, surfaceComposition, facet, reactionEnergy (eV), activationEnergy (eV), dftCode (e.g. Quantum-Espresso, VASP-5.4.4), dftFunctional (e.g. RPBE), reactants (JSON), products (JSON),
Equation
0.5O2(g) + * -> O*
Publication Fields title, authors (JSON), journal, year (Int), doi, reactions (linked Reaction list)
Core Queries
List Reactions curl -s -X POST "https://api.catalysis-hub.org/graphql" \
-H "Content-Type: application/json" -d '{"query":"{ reactions(first: 3) { edges { node { chemicalComposition reactionEnergy activationEnergy surfaceComposition } } } }"}'
{"data":{"reactions":{"edges":[
{"node":{"chemicalComposition":"Nb9Sn3","reactionEnergy":-9.687,"activationEnergy":null,"surfaceComposition":"Nb3Sn"}},
{"node":{"chemicalComposition":"Ir3V9","reactionEnergy":-8.395,"activationEnergy":null,"surfaceComposition":"V3Ir"}},
{"node":{"chemicalComposition":"Ir9Ni3","reactionEnergy":-2.005,"activationEnergy":null,"surfaceComposition":"Ir3Ni"}}
]}}}
Filter by Surface Composition curl -s -X POST "https://api.catalysis-hub.org/graphql" \
-H "Content-Type: application/json" -d '{"query":"{ reactions(first: 2, surfaceComposition: \"Pt\") { edges { node { chemicalComposition surfaceComposition facet reactionEnergy dftCode dftFunctional Equation } } } }"}'
{"data":{"reactions":{"edges":[
{"node":{"chemicalComposition":"Pt28","surfaceComposition":"Pt","facet":"100","reactionEnergy":0.856,"dftCode":"Quantum-Espresso","dftFunctional":"RPBE","Equation":"0.5N2(g) + * -> N*"}},
{"node":{"chemicalComposition":"Pt28","surfaceComposition":"Pt","facet":"100","reactionEnergy":-0.984,"dftCode":"Quantum-Espresso","dftFunctional":"RPBE","Equation":"0.5O2(g) + * -> O*"}}
]}}}
Search by Chemical Composition (partial match with ~ prefix) curl -s -X POST "https://api.catalysis-hub.org/graphql" \
-H "Content-Type: application/json" -d '{"query":"{ reactions(first: 3, chemicalComposition: \"~CO\") { edges { node { chemicalComposition reactionEnergy dftCode } } } }"}'
{"data":{"reactions":{"edges":[
{"node":{"chemicalComposition":"Co9Cr2FeMnNiO20","reactionEnergy":1.910,"dftCode":"VASP-5.4.4"}},
{"node":{"chemicalComposition":"Co9Cr2FeMnNiO20","reactionEnergy":0.648,"dftCode":"VASP-5.4.4"}},
{"node":{"chemicalComposition":"Co10CrFeMnNiO20","reactionEnergy":3.167,"dftCode":"VASP-5.4.4"}}
]}}}
Query Publications curl -s -X POST "https://api.catalysis-hub.org/graphql" \
-H "Content-Type: application/json" -d '{"query":"{ publications(first: 2, year: 2019) { edges { node { title authors journal year doi } } } }"}'
{"data":{"publications":{"edges":[
{"node":{"title":"High-Throughput Calculations of Catalytic Properties of Bimetallic Alloy Surfaces","authors":"[\"Mamun, Osman\",\"Winther, Kirsten T.\",\"Boes, Jacob R.\",\"Bligaard, Thomas\"]","journal":"Scientific Data","year":2019,"doi":"10.1038/s41597-019-0080-z"}},
{"node":{"title":"Selective high-temperature CO2 electrolysis enabled by oxidized carbon intermediates","journal":"Nature Energy","year":2019,"doi":"10.1038/s41560-019-0457-4"}}
]}}}
Rate Limits
No documented rate limits; add 200-500ms delays between requests as courtesy
Use first to limit results; pagination via cursor-based after argument
Academic Use Cases
Catalyst Screening: Compare adsorption energies across bimetallic alloy surfaces to identify candidates for target reactions (ORR, NRR, HER)DFT Validation: Cross-reference your DFT results against published values matched by surface, facet, and functionalScaling Relations: Retrieve adsorption energies across surfaces to build Bronsted-Evans-Polanyi (BEP) relationsLiterature Discovery: Find publications by year or linked reactions for citation and methodology verification
Python Example import requests
ENDPOINT = "https://api.catalysis-hub.org/graphql"
def query_catalysis_hub(query):
"""Execute a GraphQL query against Catalysis Hub."""
resp = requests.post(ENDPOINT, json={"query": query})
resp.raise_for_status()
return resp.json()["data"]
# Screen adsorption energies on Pt surfaces
data = query_catalysis_hub("""
{
reactions(first: 20, surfaceComposition: "Pt") {
edges { node { Equation facet reactionEnergy dftFunctional } }
}
}
""")
for edge in data["reactions"]["edges"]:
r = edge["node"]
print(f"{r['Equation']:<30} facet={r['facet']} E={r['reactionEnergy']:+.3f} eV")
# Publications with linked reactions
pubs = query_catalysis_hub("""
{
publications(first: 5, year: 2019) {
edges { node { title doi reactions { surfaceComposition Equation } } }
}
}
""")
for edge in pubs["publications"]["edges"]:
pub = edge["node"]
print(f"{pub['title']} | DOI: {pub['doi']} | {len(pub.get('reactions') or [])} reactions")
References 