GreenCat
GreenCat is a catalyst discovery and optimization platform that applies physics- and mathematics-driven algorithms to identify novel catalyst formulations. The platform screens the entire periodic table for unknown catalyst options, requiring little to no prior experimental data, and has demonstrated a 40% reduction in overpotential for green hydrogen production. It serves catalyst manufacturers, pharmaceutical companies, and chemical firms seeking step-change efficiency improvements.
- Chemical Technology
- New Materials
- Clean Technology
- Software Only
- Artificial Intelligence
Funding
Founders
Founder details are not available yet.
Product
Problem
Traditional catalyst discovery relies on slow, trial-and-error experimental methods or incremental improvements to existing catalysts, often taking years and yielding only marginal gains. Even at the largest chemical firms with substantial R&D budgets, catalysts have barely changed over the last century, limiting energy efficiency, carbon intensity, and operating costs across hydrogen production, carbon capture, and pharmaceutical manufacturing.
Solution
GreenCat provides a catalyst discovery and optimization platform that applies fundamental physics and mathematics-driven algorithms to identify novel catalyst formulations in a fraction of the time compared to traditional methods. The platform screens the entire periodic table for unknown catalyst options using a proprietary global descriptor approach, requiring little to no prior experimental data. GreenCat begins by establishing comprehensive reaction networks for a given reaction system, then uses hypothetical catalyst reaction energy optimization to identify performance-determining descriptors, and finally performs descriptor-based screening with scaling relations and prediction models. The process culminates in activity comparisons and selection of final catalyst formulations engineered for stability and resistance to catalyst poisons, enabling step-change improvements rather than incremental gains.
Target Audience
Primary customers are catalyst manufacturers, pharmaceutical companies, and chemical companies across various functions and reactions, particularly those in the hydrogen economy, carbon capture and utilization, and fine chemical manufacturing sectors seeking to improve energy efficiency and reduce operating costs.
Features
- Limitless search capability that screens the entire periodic table for unknown catalyst options, unlike traditional methods limited to existing knowledge
- Zero-data discovery algorithm that works with little to no prior experimental data, eliminating the need for vast quantities of IP data
- Simulation-first approach allowing testing of hundreds of formulations before entering the lab, accelerating the discovery timeline
- Comprehensive reaction network establishment for each reaction system, ensuring all possible chemical transformation paths are accounted for before screening
- Descriptor-based screening using scaling relations and prediction models to identify specific performance-determining characteristics
- Transferable partial reaction network for activity comparisons that "sense checks" novel candidates for practical relevance and operational compatibility
- Final catalyst formulations engineered for exceptional stability and resistance to catalyst poisons for extended lifespans in continuous industrial systems
- Demonstrated case study screening 35,000 alloy candidates to identify two novel Ru-based formulations reducing overpotential by more than 40% for oxygen evolution reaction in green hydrogen production