AI-POWERED MATERIALS DISCOVERY
Algorithmic iterative reticular synthesis of zeolitic imidazolate framework crystals
The discovery of crystalline reticular materials remains largely trial-and-error despite their societal importance. We introduce our algorithmic iterative reticular synthesis (AIRES) cycle, which integrates automated synthesis, image recognition, single-crystal X-ray diffraction and, crucially, customized algorithmic decision-making, to maximize distinct crystal discoveries rather than optimizing single targets. Demonstrated on zeolitic imidazolate frameworks (ZIFs), AIRES achieves twice the discovery rate of random exploration, crystallizing 10 new linkers into diverse ZIF topologies and expanding the single-linker Zn-ZIF library by one-third. By transforming reticular synthesis from an empirical process to a systematic exploration, AIRES provides a scalable and efficient blueprint for accelerating materials discovery.
Key Enterprise Impact Metrics
AIRES transforms empirical materials synthesis into a systematic, accelerated discovery process, yielding significant gains in efficiency and novel material identification.
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Required for Discovery (AIRES)
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Faster Discovery Rate
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Zn-ZIF Library Expanded
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Breakthrough Discovery Rate
2x Faster than Random ExplorationAIRES dramatically accelerates ZIF discovery, achieving twice the rate of random exploration and crystallizing 10 new linkers into diverse ZIF topologies, expanding the Zn-ZIF library by one-third.
AIRES Iterative Discovery Cycle
Automated Synthesis
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Image Recognition
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Single-Crystal X-ray Diffraction (SCXRD)
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Algorithmic Decision-Making
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Dataset Curation
| Feature | AIRES Approach | Traditional Empirical Methods |
|---|---|---|
| Objective | Maximize distinct crystal discoveries | Optimize single target (e.g., yield, property) |
| Exploration Strategy | Systematic, ML-guided decision-making, adaptive | Trial-and-error, limited cross-system learning |
| Efficiency | Twofold acceleration (700 vs 1,400 experiments) | Resource-intensive, slow discovery rate |
| Scalability | Blueprint for accelerating materials discovery | Difficult to scale due to empirical nature |
Impact Metrics for ZIF Discovery
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New Linkers Crystallized
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Distinct Topologies Discovered
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Library Expansion (%)
ZIF-A6: A Novel Structural Motif
One of the standout discoveries by AIRES is ZIF-A6, featuring an unprecedented double fes topology structure. Unlike previously reported layered ZIFs with single atomic layers, ZIF-A6 exhibits a new double-thick-layer arrangement where two layers of metal nodes are covalently bridged by 5BrIM. This represents a significant advancement in ZIF chemistry, demonstrating AIRES's ability to uncover novel structural motifs beyond typical expectations. The platform effectively guided the exploration towards this complex and previously unknown architecture.
Advanced ROI Calculator
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Estimated Annual Savings
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Researcher Hours Reclaimed Annually
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Your AIRES Implementation Roadmap
A phased approach to integrate AIRES into your enterprise R&D, ensuring a smooth transition and rapid value generation.
Phase 1: AIRES Customization & Data Integration
Tailor the AIRES platform to your specific material systems and integrate existing experimental data. Develop custom chemical descriptors and initial ML models.
Phase 2: Automated High-Throughput Screening
Deploy robotic synthesis and automated characterization (optical imaging, SCXRD) to generate new datasets guided by AIRES's decision-making algorithms.
Phase 3: Iterative Discovery & Optimization
Run iterative AIRES cycles, continuously refining ML models and exploring novel chemical spaces to maximize distinct material discoveries and optimize synthesis conditions.
Phase 4: Scalable Materials Development
Transition successful discoveries from AIRES into scalable production, using validated structures and optimized conditions for further material development and commercialization.
Ready to Accelerate Your Discovery?
Transform your materials R&D from empirical guesswork to algorithmic precision. Discover novel materials faster and more efficiently with AIRES.
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