Solutions — Flux Materials

Matter begins with structure.

Every material property emerges from the physical organisation of matter. Flux Materials applies Matter Computing to calculate electronic, thermal, mechanical, surface, interface, device, and manufacturing behaviour through one coherent physical cascade—without fitting a separate model to every endpoint.

what the material is → what properties emerge → where it fits → what to build → how it could be made
0.237 eV
Band-gap MAE across 1,048 public materials
16 / 16
Properties below 1% error in strict and out-of-family benchmark scenarios
4.66 million
Semiconductor candidate compositions mapped through one physics-native engine
Zero
Parameters fitted to materials-property training data
Request Pilot Access Try the Materials Demo
Flux Materials · Powered by the Matter Computing Platform

The materials-development interface to the same Matter Computing engine used across chemistry and pharmacology.

Explore the platform → Read Flux Materials → Explore Flux Pharmacology → Read the Founding Principles →
What it is Public proof Readiness Available today In pilot In development Materials cascade Industries Workflow Pilot & benchmark

What is Flux Materials?

A connected physical system for materials R&D.

A useful material is never just a promising number. A semiconductor also needs suitable transport, contacts, interfaces, stability, operating conditions, and a credible route into a device. A coating must work at the correct wavelength, temperature, substrate, environment, and deposition process. A polymer must be understood in its molecular, processing, and composite state. A laboratory candidate must eventually survive fabrication and scale-up.

Flux Materials connects those questions rather than treating them as unrelated calculations. Every stage consumes the physical information produced before it.

STAGE 1

What the material is

Composition, chemical family, bonding, structural identity, lattice behaviour, oxidation state, magnetic state, and the physical primitives from which the rest of the calculation proceeds.

STAGE 2

What properties emerge

Electronic, structural, thermal, mechanical, magnetic, dielectric, transport, and spectroscopic behaviour—calculated together rather than through a separate trained model for every endpoint.

STAGE 3

What happens at the surface

Facet-dependent work function, surface termination, environment, process state, band alignment, interface dipoles, Schottky barriers, and contact compatibility.

STAGE 4

Where the material fits

Battery, semiconductor, catalyst, solar, optical, protective, polymer, composite, packaging, and thermal-management decisions evaluated within the intended operating context.

STAGE 5

What should be built

Inverse search, candidate generation, evolutionary discovery, comparison, Pareto analysis, rejection reasons, uncertainty, recommended measurements, and prototype handoff.

STAGE 6

How it could be made

Manufacturing-route compatibility, process risks, form factors, cost and lead-time scenarios, required characterization, and the path from laboratory candidate to pilot production.

STAGE 7

What you can defend

Applicability domain, evidence type, uncertainty, benchmark receipt, calculation path, limitations, and a reproducible decision packet for every result.

Why this matters. Conventional materials R&D is divided across databases, property predictors, DFT packages, specialist simulators, spreadsheets, and internal process knowledge. FluxMateria is building one connected system: one candidate identity · one physical foundation · one evidence trail · one handoff from discovery to application and scale-up.

Readiness today

Not every capability has the same validation depth. We make the distinction visible.

Validated · ships today

Published benchmark evidence within a declared scope. Suitable as a primary screening signal inside that scope.

In pilot

The workflow runs end to end and produces structured, evidence-graded output. Validation is expanding across additional families or customer datasets.

In development

Product or physics work is active, but the capability is not represented as generally available. Early outputs may be scope-capped or directional.

Future

On the roadmap and not available today. It enters the product only after its own physics and benchmark gates are satisfied.

Validated does not mean computation replaces synthesis, device fabrication, durability testing, or regulatory qualification. It means the published calculation has passed a declared benchmark within a defined applicability domain.

Validated · ships today

Production materials capabilities

Public benchmark evidence within a declared scope.

Validated

Universal Materials Engine

Complete material-property screening from one composition.
  • Band gap and electronic classification
  • Formation energy, lattice parameters, density, and structural family
  • Thermal, mechanical, magnetic, dielectric, and electronic bundles
  • Batch calculation with family-stratified evidence
  • Handoff into specialized Materials workflows
Explore the Materials Engine
Validated

Semiconductor Design

Evaluate the operating space, not a room-temperature table value.
  • Electron and hole mobility
  • Doping, temperature, and supported alloy sweeps
  • Baliga and Johnson figures of merit
  • Inverse specification search and Pareto frontiers
  • Operating-window heatmaps and export
Explore Semiconductor Design
Validated

Surface & Contact

Design the interface the device will actually have.
  • Facet and termination sweeps
  • Environment- and process-aware work function
  • Band alignment and interface dipoles
  • Schottky barriers and contact-pair comparison
  • Experimental-source provenance
Explore Surface & Contact
Validated / pilot

Battery Electrochemistry

Make cathode decisions in battery terms.
  • Voltage, capacity, transport, and fast-charge signals
  • Electrolyte, coating, and interface fit
  • Degradation and cycle-life risks
  • Uncertainty and out-of-domain warnings
  • Recommended experiments and prototype handoff
Explore Battery Electrochemistry
Validated / pilot

Catalyst Scoring

Evaluate the catalytic system, not a single adsorption number.
  • Industrial catalyst families and multi-objective scoring
  • Elementary steps and activation barriers
  • Microkinetics and rate-limiting-step analysis
  • Operating conditions and inverse catalyst discovery
  • Cost, toxicity, and supply-chain signals
Explore Catalyst Scoring
Validated by technique

Spectroscopy & Characterization

Predict the signature before committing the sample.
  • UV–Vis, IR, Raman, and NMR
  • Peak assignment and confidence indicators
  • Predicted-versus-experimental comparison
  • Exportable spectra and assignment tables
  • Technique- and material-class-specific support
Explore Spectroscopy
In pilot

Search, design, and connected workflows

End-to-end workflows with validation expanding across additional material families and real customer decisions.

In pilot

Inverse Search

Stop searching. Start specifying.
  • Target ranges and hard constraints
  • Required and excluded elements
  • Operating conditions and weighted trade-offs
  • Ranked candidates and near-miss explanations
  • Pareto frontiers and exportable shortlists
Explore Inverse Search
In pilot

Materials Design Studio

Turn a specification into candidate compositions.
  • Hard and soft constraints
  • Candidate generation, repair, and lineage
  • Physics-derived evaluation and Pareto ranking
  • Rejection reasons and shortlist export
  • Optional GPU lattice-dynamics validation for finalists
Explore Design Studio
In pilot

Evolutionary Discovery

Run a discovery campaign, not a single query.
  • Multiple weighted objectives
  • Thousands of candidates per generation
  • Family-aware crossover and mutation
  • Diversity preservation and candidate lineage
  • Stability gates and survivor promotion
Explore Evolutionary Discovery
Expanding

Connected Materials Workflows

One candidate can move through the platform without losing its identity.
  • One immutable candidate identity
  • One versioned calculation record
  • One evidence vocabulary
  • One applicability-domain record
  • One decision packet and downstream handoff

Warnings, uncertainty, evidence, and provenance remain attached as the candidate moves between modules.

In development

From property calculation to complete industrial workflows

The next generation of Flux Materials turns the current physics engine into application-specific studios. These are active development programs, not current general-production claims.

In development

Solar Device Studio

From promising absorber to prototype-ready stack.

Planned decisions

  • Compare complete absorber, front-contact, back-contact, passivation, and architecture choices
  • Identify electronic mismatch, interface, and passivation risks
  • Balance efficiency potential, stability, cost, criticality, and manufacturability
  • Rank prototype priority and recommend measurements that reduce uncertainty
  • Generate an exportable prototype build packet
The earliest external form will be an evidence-graded Solar Stack Readiness workflow. PCE, degradation, recombination, lifetime, and defect outputs remain labelled according to their individual validation depth.
In development

Coatings & Thin-Film Studio

Design the complete stack, not merely the coating material.

Optical Stack

  • Anti-reflective coatings, reflectors, filters, and transparent conductors
  • Reflectance, transmittance, absorption, thickness, and layer ordering
  • Wavelength, angle, substrate, temperature, and deposition conditions
  • Manufacturing handoff

Protective System

  • Corrosion, wear, thermal, moisture/gas barrier, and insulation screening
  • Layer and process compatibility
  • Adhesion and degradation risk
  • Recommended characterization and test plans
Optical and protective workflows advance independently. A validated optical calculation cannot lend credibility to an unvalidated lifetime or corrosion claim.
In development

Manufacturing & Scale-Up Advisor

Turn a candidate into a credible route to production.

Planned outputs

  • Compatible and incompatible manufacturing routes
  • Primary and fallback processes and form-factor suitability
  • Process risks, setup burden, tolerance, finish, yield, and scrap assumptions
  • Geography- and volume-specific cost ranges and lead-time scenarios
  • Characterization requirements and pilot-to-production milestones
  • Synthesis, coating, or deposition links where relevant
Economic outputs will be dated, sourced scenarios rather than false-precision point estimates. Process compatibility and commercial attractiveness remain separate unless combined through a visible scoring model.
In development

Polymer & Composite Studio

Screen molecular choices and material architectures together.

Polymer Property Estimation

  • Defined thermoplastic families and binary copolymers
  • Tg, Tm, density, solubility parameter, and supported thermal/processing properties
  • Molecular weight, tacticity, crystallinity, temperature, humidity, and processing state

Composite Micromechanics

  • Fibre-reinforced and particulate composites
  • Matrix, reinforcement, orientation, aspect ratio, and volume fraction
  • Interface assumptions, environmental conditions, and supported micromechanical methods
Polymer estimation and composite micromechanics use separate contracts and evidence. General formulations, cure chemistry, adhesives, ageing, fatigue, fracture, and regulatory claims remain outside the first release.
Research development

Advanced Packaging & Thermal Management

Find the thermal bottleneck before building the package.

Phase-one vertical slice

  • Layered die–TIM–heat-spreader representation
  • Through-plane and supported anisotropic thermal conductivity
  • Explicit interface resistance
  • Temperature and power-density inputs
  • Layer and total resistance and bottleneck identification
  • Comparison of thermal-interface materials
  • Unit- and condition-preserving decision packet
Warpage, moisture, thermal cycling, fatigue, delamination, interconnect failure, and full package reliability remain separate research programs and are not implied by the initial thermal calculation.
Future

The longer materials roadmap

Capabilities under exploration beyond the current specialty-studio program.

Package reliability

Full thermomechanical, moisture, cycling, fatigue, delamination, and interconnect reliability.

Hydrogen & fuel cells

Electrocatalysts, membranes, storage materials, interfaces, and durability workflows.

Functional ceramics

Electronic, dielectric, thermal, structural, and high-temperature ceramic systems.

Defects & degradation

Wider defect, recombination, corrosion, diffusion, ageing, and degradation physics.

Wider material classes

Broader amorphous, MOF, organic-semiconductor, and polymer chemistry coverage.

Multiscale reliability

Propagation from material properties to component behaviour and system-level reliability.

Future capabilities are not available today. Each enters the product only after its own implementation, physics, benchmark, evidence, and release gates are satisfied.

The materials cascade

From formula to industrial decision. Each phase carries its own readiness tier.

1Material identityComposition · structure · bonding contextValidated
Composition normalizationStructural-family classificationBonding and oxidation contextMagnetic and electronic classificationCrystal and lattice descriptors
2Core material propertiesElectronic · structural · thermal · mechanical · magneticValidated by scope
Band gapFormation energyLattice parametersDensityElastic and bulk propertiesHardnessThermal conductivityThermal expansionMelting behaviourMagnetic propertiesDielectric behaviourSpectroscopy
3Transport, surfaces, and interfacesOperating conditions · contacts · boundariesValidated / pilot
Electron and hole mobilityDoping and temperature responseAlloy-composition responseWork functionFacet and termination effectsBand alignmentInterface dipolesContact barriers
4Current application workflowsIndustry-specific decision layersValidated / pilot
Battery ElectrochemistrySemiconductor DesignSurface & ContactCatalyst ScoringInverse Search
5Candidate design and discoverySpecification · generation · optimizationIn pilot
Materials Design StudioEvolutionary DiscoveryMulti-objective optimizationPareto analysisCandidate lineageGPU stability validation
6Next industry studiosDevice · coating · manufacturing · polymer · packagingIn development
Solar Device StudioCoatings & Thin-Film StudioManufacturing & Scale-Up AdvisorPolymer & Composite StudioAdvanced Packaging & Thermal Management
7Prototype and manufacturing handoffFrom recommendation to actionPilot / development
Candidate recommendationRejection reasonsPriority measurementsPrototype packetProcess-route comparisonScale-up plan
8Evidence and assuranceScope · uncertainty · provenance · reproducibilityAvailable & expanding
Applicability domainEvidence typeUncertaintyVersioned calculationsBenchmark receiptsProvenanceImmutable decision packetsBlind-validation programs

Proof on public benchmarks

Physics-native accuracy at screening throughput.

Universal materials characterization
16 / 16

Every strict and out-of-family result below 1%

The universal benchmark evaluates a 16-property characterization path across strict and out-of-family scenarios, with millisecond-scale evaluation.

Explore materials benchmarks →
Band-gap prediction
0.237 eV

MAE across 1,048 materials

One fixed composition-based predictor evaluated across metals, semiconductors, and insulators, with no band-gap training split and no fitted band-gap parameters.

See the band-gap benchmark →
Semiconductor transport
6.2% / 4.4%

Electron / hole mobility MAPE

Continuous evaluation across material family, five decades of doping, temperature from 77–500 K, and supported ternary-alloy compositions.

Explore Semiconductor Design →
Surfaces and contacts
0.063 eV

MAE across 35 experimental interface stacks

Work function, band alignment, interface dipole, and Schottky-barrier workflows with surface and operating conditions as explicit inputs.

Explore Surface & Contact →
Battery electrochemistry
0.149 V

Calibrated holdout voltage MAE

A battery-native screening and prototype-handoff workflow. The current evidence supports screening and triage, not replacement of laboratory validation.

Explore Battery Electrochemistry →
Candidate-space exploration
4,662,588

Semiconductor compositions mapped

A generated candidate universe evaluated through one physics-native engine. Candidate count is not a claim that every composition is stable or synthesizable.

Read the Atlas case study →
Explore All Materials BenchmarksSubmit a Blind Benchmark

One platform, multiple industries

The same physical foundation becomes a different decision workflow in each industrial context.

Semiconductors & electronics

Band gaps, transport, contacts, interfaces, power-device figures of merit, packaging, and thermal management.

Energy storage

Battery-native screening, transport, interfaces, coatings, degradation signals, uncertainty, and prototype handoff.

Renewable energy

Solar absorbers, contact stacks, protective layers, photoelectrodes, and manufacturing readiness.

Optics & photonics

Thin-film optical stacks, reflectors, filters, transparent conductors, sensors, imaging systems, and laser components.

Chemicals & catalysis

Catalyst cycles, operating windows, surfaces, coatings, polymers, process compatibility, and candidate discovery.

Aerospace & automotive

Composites, protective coatings, thermal barriers, power electronics, structural materials, and manufacturing routes.

Industrial manufacturing

Process selection, form-factor compatibility, cost and lead-time scenarios, characterization, and scale-up planning.

Polymers, packaging & consumer materials

Polymer properties, composite architectures, barrier systems, thermal behaviour, processing, and sustainability screening.

Not a property database. Not one more surrogate model.

Flux Materials is designed to compute broadly before teams simulate or test deeply.

Materials databases

Fast retrieval of materials already known, but limited when the candidate has not already been measured, computed, or indexed.

Machine-learning models

Fast after training, but dependent on labelled data, representation choices, and the chemical space already encountered. Different properties usually require different models.

DFT & numerical simulation

Powerful and indispensable for deep analysis, but too expensive to place inside every interactive screen, search, optimization loop, and early engineering decision.

Flux Materials

  • Novel compositions evaluated immediately
  • Entire candidate spaces screened
  • No per-library retraining
  • Versioned and reproducible results
  • Evidence and limitations declared
  • Discovery connected to prototype and manufacturing

Workflow: from material to defensible decision

One connected path instead of a chain of disconnected files and vendor tools.

1

Input

Composition, library, imported candidate, or target specification.

2

Profile

Supported electronic, structural, thermal, mechanical, magnetic, transport, and surface properties.

3

Contextualize

Evaluate the candidate inside the relevant application and operating conditions.

4

Compare

Rank against objectives, constraints, uncertainty, and rejection reasons.

5

Design

Generate candidates, evolve a population, alter a stack, or select the next measurement.

6

Hand off

Prototype packet, characterization plan, manufacturing route, or deep-simulation shortlist.

7

Decide

Export a reproducible packet with versions, evidence, uncertainty, and limitations.

Bring us the materials decision your current stack cannot answer.

Bring a composition library, semiconductor target, device stack, coating problem, target property profile, or manufacturing constraint. We will define the scope before the run and state which capabilities are validated, in pilot, or experimental.

Pilot program

Run Flux Materials on your actual candidates and operating conditions.

Request Pilot Access

Blind benchmark

Provide a held-back dataset and an agreed metric. The protocol and evaluation criteria are frozen before prediction.

Submit a Blind Benchmark

Interactive demo

Enter a public composition and inspect a live, timestamped verification run.

Try the Materials Demo
Flux Materials · Powered by the Matter Computing Platform

The materials-development interface to the same Matter Computing engine used across chemistry and pharmacology. One physical basis. Domain-specific expression. Evidence-bound use.

Explore the platform → Read Flux Materials → Explore Flux Pharmacology → Read the Founding Principles →