As computational materials science evolves, simulating spintronic devices and 2D materials requires highly specialized AI models. My current project focuses on training BERT and GPT models to create:
1️⃣ A fine-tuned BERT-based model for understanding and processing scientific data
2️⃣ A GPT-based conversational assistant trained to assist researchers in providing insights, calculations, and relevant literature suggestions.
🧠 Technical Details
✅ Fine-Tuned BERT for 2D Materials
- Data Collection: Compiled a large corpus of scientific literature, equations, and device simulation results related to TMDs, spintronic devices, and quantum materials.
- Preprocessing & Tokenization:
- Domain adaptation
- Applied custom tokenization to recognize material-specific terms and equations.
- Fine-Tuning Approach:
- Trained for relation extraction and context-aware tagging of materials properties.
✅ AI Chat Agent – GPT for Device Simulations
- Model Adaptation: Trained GPT-3.5/4 using scientific papers, simulation logs, and experimental data.
- Knowledge Integration
