MaterialScienceGPT / README.md
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---
title: MaterialScienceGPT
colorFrom: purple
colorTo: yellow
sdk: gradio
sdk_version: 5.25.0
app_file: app.py
pinned: false
license: mit
short_description: 'GPT for Materials Science appplications '
---
# πŸ§ͺ Materials Science Expert Chatbot
Welcome to the **Materials Science Expert Chatbot** β€” an AI-powered assistant specialized in helping you choose the **best materials for specific applications**.
This chatbot is powered by the **Groq API (LLaMA 3.1-8B)** and is tailored to only respond to **Materials Science-related queries**.
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πŸ§‘β€πŸ”¬ Built For
Highschool Student
Chemistry & Physics enthusiasts
Computational Scientists
Materials scientists
Engineering students
Product designers and R&D teams
Anyone interested in smart material selection using AI
## πŸ” What Can This Chatbot Do?
- βœ… Suggest the **top 3 materials** for a given application
- βœ… Explain the **required properties** for the application
- βœ… Provide a **side-by-side comparison table** of key material properties (mechanical, thermal, chemical)
- βœ… Recommend suitable materials based on different scenarios
- ❌ Will **not respond** to unrelated questions (e.g., history, general knowledge)
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## πŸ’¬ Example Questions
You can ask things like:
- *What are the best corrosion-resistant materials for marine environments (e.g., desalination)?*
- *Which materials are ideal for solar panel coatings and desert heat management?*
- *What materials are used for aerospace structures in extreme climates?*
- *What advanced materials are used in electric vehicles and batteries in the UAE?*
- *How can one leverage AI/ML techniques in Materials Science?*
The bot will return a clean, structured comparison of the best material options along with their justifications.
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## πŸš€ How to Use
1. Type your question in the textbox (e.g., β€œBest materials for aerospace applications”)
2. Click **Submit** (orange button) or press **Enter**
3. View the expert response including a **materials comparison table**
4. Browse popular questions for inspiration
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## 🧠 Powered By
- **[Groq API](https://groq.com/)** – Ultra-fast inference using LLaMA 3.1-8B
- **[Gradio](https://gradio.app/)** – Beautiful and interactive UI
- **Python** – Backend glue and logic
- Optionally expandable with:
- CSV/PDF table downloads
- CIF/3D material structure viewing
- AI/ML integration for predictive material selection
---
## πŸ” Environment Variables
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference