AI Tool Center
Six AI tools covering the full materials science research workflow
Material Workbench
AI-powered browser computing for materials science
LLM-driven computation platform running entirely in browser using Pyodide. Natural language to code, parameter protection, real-time monitoring, and project management.
- Natural language to code
- Browser-based Pyodide
- Parameter lock protection
- Real-time monitoring
- Multi-domain support
AI Code Generator
AI-powered materials science code generation & Paper2Code
Describe your requirement in plain language — AI generates production-ready materials science code, detects bugs, and can even extract algorithms directly from paper text.
- Natural language to code
- Auto bug detection & fix
- Multi-language support
- Paper2Code mode
OpenDraft
AI-assisted academic writing for SCI journals
Intelligently organize research ideas, auto-generate introductions and literature reviews, polish academic expression, and provide Chinese–English translation.
- Auto-generate introduction
- Literature review drafting
- Academic language polishing
- CN ↔ EN translation
PicAxe
Upload any figure — AI writes the caption & results
Upload XRD, SEM, TEM, XPS or electrochemical figures — AI identifies the chart type, analyses data features, and outputs SCI-standard figure captions and results text.
- Identifies multiple figure types
- SCI-standard caption output
- Results text generation
- Copy-paste ready
LAMMPS AI Lab
Natural-language-driven molecular dynamics simulation
Describe your simulation in plain language → AI generates LAMMPS scripts → cloud execution → real-time visualization → AI interprets results. No coding required.
- Natural language to script
- Cloud parallel computing
- Real-time visualization
- AI analysis report
Introduction Finder
Nature / Science-style introductions & full paper drafts
Paste your Methods, Results or Conclusions — AI writes a Nature/Science-quality introduction. Also supports multi-turn research discussion, full paper draft generation, and DFT/MD/ML calculation recommendations.
- Nature / Science intro generation
- Multi-turn research discussion
- Full paper draft (Sections 2–5)
- DFT/MD/ML calculation recommendations