Code and Data: Design and Realization of High Performance Textured Lead-Free Piezoelectric Ceramics through Human-AI Collaboration
Code and Data: Design and Realization of High Performance Textured Lead-Free Piezoelectric Ceramics through Human-AI Collaboration
Code and data for the paper "Design and Realization of High Performance Textured Lead-Free Piezoelectric Ceramics through Human-AI Collaboration". This repository contains: LLM-based composition generation scripts using Claude 3.5 Sonnet for designing new KNN-based lead-free piezoelectric ceramics Post-hoc statistical analysis code (Leave-One-Out, Conditional Prediction, Incremental Learning) using DeepSeek-V3 via Together AI Prediction benchmarks across multiple LLMs (Claude, GPT, Gemini, DeepSeek) All pre-generated data and visualization scripts for reproducing figures in the paper and supplementary information A Google Colab notebook for one-click reproduction of all plots (no API keys required)
- Yeungnam University Korea (Republic of)
- University of Minnesota Morris United States
- Pennsylvania State University United States
- Penza State University Russian Federation
lead-free, composition optimization, materials design, Energy harvestor, AI-driven Materials Discovery, Magnetoelectric, piezoelectric ceramics, KNN, large language models, human-AI collaboration, d33
lead-free, composition optimization, materials design, Energy harvestor, AI-driven Materials Discovery, Magnetoelectric, piezoelectric ceramics, KNN, large language models, human-AI collaboration, d33
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