ChemTrend AI: Literature & Trend Mining
Natural language literature search, automated technical summaries, and quantitative trend visualization.
The trend analysis engine is preparing your workspace.
Check your network or open ChemTrend AI in a new tab. Once it loads, return here to continue.
Enter a complex chemical topic like "Photoredox catalysis in flow" to begin.
How to Use ChemTrend AI
- Enter a topic (e.g., "C–H activation") into the Natural Language Search bar.
- Review the Automated Technical Summaries for recent advances and open problems.
- Explore the Quantitative Trend Visualizations to see yield trends and solvent landscapes.
- Click "Reference Linking" citations to verify data with Grounded Source Verification.
Features That Power Your Analysis
- AI-Powered Literature Mining: Context-aware searching using Google Gemini and Search Grounding for recent literature (last 3-5 years).
- Automated Technical Summaries: Generates structured summaries covering methodologies, reaction conditions, and limitations.
- Quantitative Trend Visualization: Extracts unstructured data into line charts (Yields), bar charts (Reagent popularity), and pie charts (Solvents).
- Grounded Source Verification: Provides direct links to external journals and distinguishes grounded data from internal model knowledge.
Use Cases & Research Applications
ChemTrend AI supports researchers by turning vast literature data into visual, actionable insights.
- Methodology Optimization: Analyze catalyst and solvent trends to select the most promising conditions for your reactions.
- Review Writing: Quickly visualize the evolution of a field over the last 5 years to draft comprehensive reviews.
- Competitive Analysis: Identify trending reagents and emerging methodologies in specific sub-fields.
- Source Verification: Instantly trace AI-generated summaries back to the original publisher for citation.
ChemTrend AI FAQs
How recent is the literature data?
The system focuses on literature from the last 3-5 years to ensure you are viewing the most current trends and methodologies.
How are the charts generated?
The app extracts unstructured text data from search results (e.g., reported yields, solvent names) and structures it into interactive visualizations automatically.
Can I trust the summaries?
ChemTrend uses "Credibility Indicators" to distinguish between grounded data and general model knowledge. Always check the direct reference links provided for verification.