AI tool to predict Solar efficiency using Tanzanian minerals.Built for Microsoft Research and IBM Research Africa.
# Tanzanite-Solar-Cell-Designer-AI
The world's first AI tool to model solar cell efficiency using Tanzanian minerals to power mining communities.
##Problem Statement
In Mwanza - Tanzania , Solar power output drops by 30% during the rainy season. This causes blackouts for communities and financial losses for mini-grid operators like JUMEME. Currently solar design tools do not factor in local weather patterns or locally available minerals.
## Solution
An AI prototype that predicts solar panel efficiency based on:
1. **Mineral composition**: Hypothesis - Tanzanite+3% efficiency, High-Grade silica +2%
2. **Weather Forecast**: Rainy season reduces output
3. **Monthly Irradience**: Jun - Aug has peak sun in Mwanza
- 'Tanzanite + Aug + Sunny = 23% efficiency'
- 'Tanzanite + Apr + Rainy = 16% efficiency'
- 'High-Grade silica + Apr + Rainy = 15% efficiency'
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## How to Run
1.Open "tanzanite_ai.ipynb" in google colab
2.Run all cells
3.Change mineral, month, weather parameters to test
## Research Basis
This work is informed by:
1.UNECA. "Prospects of Africa's minerals for renewable energy technologies"
2.MDPI. " The role of transition metal oxide in perovskite solar cells"
3.arXiv. "Low-Cost perovskite solar cells from abudant materials"
## Data
- Panel cost 550w Mono: Tsh 265000-285000
[source: Jiji Tz 2026]
- Location: Mwanza TZ
- Base Efficiency: 18%
## Built For
Microsoft Research AI & IBM Research Africa Application 2026.
Author: SELEMAN MAGANGA MICHAEL - Unshakable Energy AI
## License
MIT License