Code and Data: Design and Realization of High Performance Textured Lead-Free Piezoelectric Ceramics through Human-AI Collaboration
Abstract
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)
Fields of Study & Subjects
Machine Learning in Materials Science
Ferroelectric and Piezoelectric Materials
Microwave Dielectric Ceramics Synthesis
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 9 February 2026
- Language
- EN