Materials intelligence platform
LATTICE connects scientific evidence, generative and predictive models, physics-based simulation, engineering constraints, and experimental feedback to accelerate materials development for terrestrial and space infrastructure.
Point of view
Search broadly. Score cheaply. Escalate selectively. Verify against physics. Learn from every experiment.
LATTICE coordinates models, solvers, databases and experiments inside one evidence-driven learning loop.
Core platform
The permanent operating core. LATTICE starts from an engineering objective, traverses evidence and design space, then selects candidates for progressively stronger simulation and experiment based on evidence and decision value.
Parse mission requirements, search literature and patents, retrieve known materials, extract evidence, ingest structures and contract the candidate universe before higher-fidelity computation.
Explore structures, formulations, interfaces and architectures with manufacturability, cost, environment and mission constraints inside the design loop.
Use independent critics, deterministic checks, fit-for-domain simulation, uncertainty analysis and experiment planning—then reconcile measurements and failures into the next cycle.
One visual grammar across the platform: DISCOVER brings evidence into an inspectable design space; DESIGN turns objectives into material architectures; VERIFY advances candidates through progressively stronger evidence.
Closed-loop architecture
Computational and experimental effort rises with evidence depth and decision value.
LATTICE architecture
Materials libraries
Libraries are reusable domain packs of data, descriptors, constraints, evaluators, simulation hooks and validation templates.
Featured design space
Applications
Filter by mission need rather than project name. Each context maps back to concrete materials questions and evidence requirements.
Choose a project card to see the relevant material libraries, target properties, and the evidence gate LATTICE should apply.
Mission walkthroughs
Two research missions show how the same LATTICE loop adapts to different material families, mission objectives and validation pathways.
Research workspace
The embedded workspace carries mission requirements, candidate records, evidence lineage, validation logic and structured research actions in one continuous environment.
Evidence discipline
Every consequential value must preserve its evidence state, provenance, method or model, conditions, uncertainty and version. Human authority remains explicit for qualification and safety-critical decisions.
Dataset, publication, patent, experimental record, model and version stay attached to the candidate.
Confidence ranges, evidence depth, research questions and operating conditions remain visible in the decision record.
Inputs, model/tool versions, solver settings, data versions, outputs and validation state are traceable.
Every completed test and research outcome enriches the next search, design and validation cycle.
Material selection, qualification, hazardous tests and engineering baselines remain reviewable human decisions.
Generated candidates carry a GEN evidence state until stronger evidence is attached through prediction, simulation or measurement.
Research & evidence
Research pathways connect source literature, engineering context, candidate records and validation logic to the materials decisions they support.
MOF, zeolite and allied sorbent families connect adsorption behavior, regeneration, cycling and cartridge-level engineering.
Explore research pathway →PCM systems, thermal interfaces, conductive networks and containment architectures connect material choice to system heat flow and cycling.
Explore research pathway →Material class, geometry, alignment, chemistry, fill and environment form a reusable design space for transport, thermal, sensing, tribology and photonics.
Explore research pathway →eurus Intelligence Foundry
LATTICE is the materials intelligence specialist inside the eurus Intelligence Foundry—a human-governed system for assembling models, deterministic tools, simulation, experiments and evidence workflows around technical objectives.
Build with LATTICE
Use LATTICE for a bounded engineering problem, a research collaboration, or early workspace access.