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Surface Explorer

Browse, search, and visualize surface properties from the JARVIS surface database (607 entries). Surface energies, work functions, Fermi levels, VBM/CBM, and electrostatic potential profiles. Filter by formula, JID, Miller indices, and surface energy range.

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Overview

Data Source

JARVIS surfacedb — 607 surface slab entries from jarvis.db.figshare.data('surfacedb').

Endpoints

POST /surface/search — Search materials

curl -X POST "https://atomgpt.org/surface/search" \
  -H "Authorization: Bearer sk-XYZ" \
  -H "Content-Type: application/json" \
  -H "accept: application/json" \
  -d '{"formula": "Si"}'
Field Type Description
formula string Formula substring
jid string JARVIS ID (extracted from surface name)
miller string Miller index string (e.g. '110')
surf_en_min float Min surface energy
surf_en_max float Max surface energy

Response fields: idx, name, jid, miller, thickness, formula, surf_en, efermi, scf_vbm, scf_cbm, surf_vbm, surf_cbm.

GET /surface/data/{idx (integer)} — Fetch full surface record by index.

curl "https://atomgpt.org/surface/data/JVASP-1002" \
  -H "Authorization: Bearer sk-XYZ" \
  -H "accept: application/json"

Response:

{
  "idx": 42,
  "name": "Surface-JVASP-1002_miller_1_1_1_thickness_16_VASP_PBE_noDP",
  "jid": "JVASP-1002",
  "miller": "(1 1 1)",
  "thickness": "16",
  "method": "VASP PBE",
  "formula": "Si",
  "surf_en": 1.36,
  "efermi": 4.52,
  "scf_vbm": -5.73, "scf_cbm": -4.52,
  "surf_vbm": -5.73, "surf_cbm": -4.52,
  "avg_max": 8.2,
  "phi": [0.1, 0.2, ...],
  "slab": {"n_atoms": 32, "elements": ["Si"], "abc": [3.84, 3.84, 40.0], "angles": [90, 90, 90]}
}

Surface name parsed for JID, Miller indices, and thickness. phi is the electrostatic potential profile (1D array along z-axis). Surface energy in J/m².

Python Examples

import requests

response = requests.post(
    "https://atomgpt.org/surface/search",
    headers={
        "Authorization": "Bearer sk-XYZ",
        "accept": "application/json",
        "Content-Type": "application/json",
    },
    json={"formula": "Si"},
)
data = response.json()
print(f"Found {data['total']} entries")
for m in data["results"][:5]:
    print(f"  {m['jid']}: {m.get('formula', m.get('bulk_formula', ''))}")

import requests

response = requests.get(
    "https://atomgpt.org/surface/data/JVASP-1002",
    headers={"Authorization": "Bearer sk-XYZ"},
)
data = response.json()
print(f"{data['formula']} {data['miller']} surface")
print(f"  Surface energy: {data['surf_en']} J/m²")
print(f"  Work function proxy: {data['avg_max']}")
print(f"  Slab: {data['slab']['n_atoms']} atoms")

AGAPI Agent

from agapi.agents import AGAPIAgent
import os

agent = AGAPIAgent(api_key=os.environ.get("AGAPI_KEY"))
response = agent.query_sync("Show surface explorer for Silicon")
print(response)

References