Solar Cell Screening¶

Predict theoretical solar cell performance: SLME (spectroscopic limited maximum efficiency) and Shockley-Queisser limit. Uses jarvis.analysis.solarefficiency.solar.SolarEfficiency directly. Input by JID or upload absorption data.

Open App

Overview¶

Predict theoretical solar cell performance: SLME (spectroscopic limited maximum efficiency) and Shockley-Queisser limit. Uses jarvis.analysis.solarefficiency.solar.SolarEfficiency directly. Input by JID or upload absorption data.

Data Source

dft_3d + jarvis.analysis.solarefficiency

Endpoints¶

GET /solar
POST /solar/predict-jid
POST /solar/predict-data

Request Models: SolarJidRequest, SolarDataRequest

Authentication

All POST endpoints require Authorization: Bearer YOUR_TOKEN.

API Example¶

import requests

response = requests.post(
    "https://atomgpt.org/solar/predict-jid",
    headers={
        "Authorization": "Bearer sk-XYZ",
        "accept": "application/json",
        "Content-Type": "application/json",
    },
    json={"jid": "JVASP-1002"},
)
data = response.json()
print(data)

AGAPI Agent¶

from agapi.agents import AGAPIAgent
import os

agent = AGAPIAgent(api_key=os.environ.get("AGAPI_KEY"))
response = agent.query_sync("Show solar cell screening for Silicon")
print(response)

Reference¶

Comp. Mat. Sci. 259, 114063 (2025)