MatterSpace Use Cases
Generation, not discovery.
Describe what should exist.
MatterSpace generates novel candidates — materials, drugs, chips, algorithms, biological interventions — that satisfy physical constraints by construction.
Not screening. Not filtering. Not predicting. Generating valid candidates from target specifications. Every output is physically realizable.
Case Studies
What MatterSpace has generated
From blind rediscovery of known catalysts to novel battery materials — real generation results across materials science and beyond.
Blind Rediscovery of SAA Catalysts
Rediscovered Re₁@Ni, Ir₁@Ni catalysts
MatterSpace generated single-atom alloy catalysts across 23 dopant elements and 600 candidates — matching known optimal SAA configurations without any prior knowledge of the targets. Structural match within half an angstrom.
Battery Cathode Discovery
Novel cathode candidates generated
Generated stable lithium-ion cathode materials with target voltage and capacity profiles. Constraint enforcement ensured thermodynamic stability and ionic conductivity at every step of the generation process.
Green Hydrogen Catalyst Optimization
Catalyst candidates for HER/OER
Generated catalyst compositions optimized for hydrogen evolution and oxygen evolution reactions. Multi-objective scoring across overpotential, stability, and earth-abundance constraints.
Drug Candidate Generation
Coming Soon
Generating small molecules that satisfy binding affinity, selectivity, and ADMET constraints simultaneously. Physics-grounded navigation of chemical space replaces brute-force virtual screening.
Chip Topology Optimization
Coming Soon
Generating semiconductor layouts that satisfy thermal, power, and area constraints by construction. Design-rule enforcement during generation eliminates costly post-layout iterations.
Matrix Algorithm Discovery
Coming Soon
Generating novel matrix multiplication algorithms that minimize arithmetic complexity while preserving numerical stability. Landscape navigation discovers non-obvious computational shortcuts.
How It Works
The generation pipeline
From target specification to validated candidates. Every stage is observable, every constraint enforced during generation.
Adaptive Dynamics Controller
Four physics modes fire in real time based on gradient state and exploration history. Local refinement, stochastic exploration, barrier crossing, and rapid stabilization — orchestrated automatically.
Constraint Enforcement
Physical constraints are enforced during generation, not after. Bond lengths, coordination numbers, symmetry groups, and charge neutrality validated at every step. Every output is valid by construction.
Domain Packs
Field-specific force fields, physical constraints, objective functions, and sampling strategies. The core engine is domain-agnostic — domain packs supply the science for each application.
Candidate Validation
Multi-tier validation pipeline. Fast filters eliminate non-viable candidates. Relaxation confirms local stability. Property prediction scores against objectives. High-fidelity verification on top candidates.
Sub-Engines
One architecture. Five domains.
The core engine is domain-agnostic. Domain packs supply the physics, constraints, and objectives for each field. Lattice is available now. Four more are in development.
Lattice
Materials & Energy
Crystal structures, alloys, catalysts, battery cathodes, superconductors, photovoltaics. 10 domain packs covering the most important classes of functional materials.
Available NowPharma
Drug Discovery
Molecular generation guided by binding energy landscapes. Constraint-aware synthesis ensures drug-likeness, solubility, and ADMET compliance.
Coming SoonTessera
Chip Design
Semiconductor architecture, photonic layout, and circuit topology optimization. Design-rule landscapes produce physically valid, manufacturable configurations.
Coming SoonAlgo
Algorithm Discovery
Matrix n-rank algorithm search and computational optimization. Novel algorithmic structures discovered by navigating solution landscapes under complexity and correctness constraints.
Coming SoonLongevity
Biological Interventions
Partial epigenetic reprogramming target discovery. Navigates the Yamanaka factor landscape to identify safe, reversible rejuvenation interventions grounded in cellular biology constraints.
Coming SoonStart generating with MatterSpace
Describe what should exist. MatterSpace creates it. Lattice is available now for materials discovery. Talk to us about early access to Pharma, Tessera, Algo, and Longevity.