One platform, from molecule to market
Molecular simulation, machine learning, process engineering, and techno-economics usually live in isolation. Planck connects them into one automated workflow.
Why existing computational screening falls short
Properties ≠ performance
Existing tools predict adsorption under idealized conditions, not survival through heat buildup, slow kinetics, and regeneration in a real cycle.
Viability checked too late
Water stability, thermal resilience, and supply-chain risk are usually checked after expensive campaigns. We check them first.
One method doesn't fit all physics
CO₂ capture is classical; hydrogen at metal sites is quantum. Most platforms apply a single method everywhere, sacrificing either accuracy or compute.
Flexibility is ignored
Many top materials breathe and flex under gas loading, transforming their performance. Nearly all screening tools pretend frameworks are rigid. Ours doesn't.
Limited to known materials
Database screening can only rank what has already been synthesized. The optimal material for your process may not exist yet, so we generate it.
Brute force doesn't scale
When accurate simulation is expensive, evaluating 100,000+ candidates is infeasible. A search that learns where to spend compute is missing, so we built one.
100,000 candidates in. ~50 proven winners out.
Each stage eliminates candidates before the next, more expensive one. Total compute drops by orders of magnitude.
When screening isn't enough, we search smarter and invent.
Adaptive Bayesian optimization
Rather than simulating everything, our Bayesian optimization learns which material characteristics predict performance and picks the next candidate to evaluate. Expensive simulations concentrate on the most promising regions of the space.
Materials that don't exist yet
The optimal material for your process may not exist yet. Our generative module (diffusion models over framework building blocks) proposes new structures for specific targets. Every AI-generated candidate enters the same screening pipeline.
One workflow, every capability
From molecular simulation to techno-economics, validated stage by stage over years.
- Molecular simulation of gas adsorption
- Stability prediction: water, thermal, chemical
- Quantum-accuracy methods for complex systems
- Automated structural flexibility assessment
- Integrated industrial process simulation
- Techno-economic analysis
- Generative AI for novel materials
- Adaptive Bayesian optimization
Metal-organic frameworks: crystalline sponges, designed atom by atom
MOFs are advanced porous materials (100,000+ reported structures) whose surface area and chemistry can be tuned to a specific gas and process. One gram can hide the surface area of a football pitch.
Target CO₂ capture energy
Versus 3.5-4 GJ per tonne for today's amine-based plants: about a 70% reduction.
Storage pressure
Adsorbent-based storage reaches the same capacity at a fraction of the pressure, cutting tank, compressor, and infrastructure cost.
Platform maturity
Applied in paid industrial work and validated against laboratory measurements.
See the pipeline run on your problem.
Bring a feed composition and a performance target, and we'll show you what the joint space holds.