Domain-specific Agentic AI Copilot Built for Material Scientists, Chemists, and Semiconductor Engineers
With retrieval-augmented generation on millions of scientific literature, patents, and reports,
deep scientific reasoning, large-scale materials datasets, hallucination-free insights, and real-time validation.
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Ready to design polymer materials
Specify target properties or polymer structures to discover your materials!
Research starts here
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Settings & Info
Model Architecture
AI Model: Fine-tuned Domain-specific LLMs or GPT, Gemini, Claude etc.
Post-training: Supervised fine-tuning and RLVR with RAG
Training Data: Large-scale in-house dataset
Performance Metrics
Chemical Accuracy94.2%
Synthesis Feasibility89.7%
Fine-tuning Loss0.23
Benchmarked on photoresist synthesis & polymer design tasks
Citation
Anonymous authors., "RavenLLM: LLM-Based Retrosynthetic Planning and Chemistry Discovery for Autonomous Materials Design." Under Review (2026)