MatterSpace · The Universal Generation Engine for Science and Engineering
Most candidates fail before testing.
MatterSpace generates candidates in materials science and longevity workflows with scientific and engineering constraints enforced during creation, not applied as filters after the fact.
Not screening. Not filtering. Not generic prediction. MatterSpace generates valid candidates directly from target specifications.
Case Studies
Where MatterSpace removes invalid work
From blind rediscovery of known catalysts to novel battery materials, these examples show where the search budget goes directly to viable candidates.
Blind Rediscovery of SAA Catalysts
Rediscovered Re₁@Ni, Ir₁@Ni catalysts
Brute-force screening of single-atom alloy catalysts is prohibitively expensive across the full combinatorial space of dopant elements and host lattices. MatterSpace generated 600 candidates across 23 dopant elements and matched known optimal SAA configurations without prior knowledge of the targets. Structural match within half an angstrom.
Battery Cathode Discovery
Novel cathode candidates generated
High-performance battery cathodes require specific voltage and capacity profiles, but current design approaches discard over 90% of candidates on stability violations. MatterSpace generated stable lithium-ion cathode materials with thermodynamic stability and ionic conductivity enforced at every generation step.
Green Hydrogen Catalyst Optimization
Catalyst candidates for HER/OER
Green hydrogen production requires catalysts balancing overpotential, long-term stability, and earth-abundance. MatterSpace generated catalyst compositions optimized for HER/OER with multi-objective scoring across all three constraints simultaneously.
Epigenetic Reprogramming Search
Ready
Partial reprogramming efforts fail when rejuvenation comes with identity loss, unsafe dosing, or biologically implausible intervention bundles. MatterSpace Vital generates factor combinations, dosing schedules, and delivery strategies under identity-preservation and safety constraints instead of relying on blind screening.
How It Works
From target requirements to candidate set
From target specification to validated candidates. Every stage is observable, and constraints stay inside generation instead of showing up only at the rejection step.
Adaptive Dynamics Controller
The controller selects the right search strategy in real time based on landscape conditions. No manual tuning between runs.
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. Two public categories: Lattice for materials and Vital for longevity.
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.
Public Categories
One architecture. Two public categories.
The core engine is domain-agnostic. Lattice covers materials science and energy workflows. Vital covers longevity and epigenetic reprogramming workflows.
Lattice
Materials & Energy
Crystal, alloy, catalyst, electrolyte, and coating candidates for materials and energy teams. Ready for simulation or synthesis.
ReadyVital
Longevity & Epigenetic Reprogramming
Factor combinations, dosing schedules, and delivery strategies for rejuvenation, epigenetic reprogramming, and longevity workflows under safety and identity constraints.
ReadyConstraints in. Candidates out.
MatterSpace Lattice is available now for materials discovery. MatterSpace Vital is ready for longevity and epigenetic reprogramming workflows.