Polaron

What Polaron does

Polaron helps materials teams transform microstructure into an objective, scalable input for decisions, reducing uncertainty, accelerating design cycles, and unlocking better performance. They build AI models to characterize and design microstructure, covering segmentation, quantitative analysis, 3D reconstruction, and design. The platform converts raw 2D or 3D images into objective, pixel-accurate representations of material structure, identifying features like grains, phases, pores, cracks, binders, and interfaces automatically. Polaron also learns how processing choices influence microstructure and how microstructure determines performance, enabling in silico materials design and process optimization. The platform is deployed through a secure enterprise platform, built for robust, repeatable operation across teams, sites, and secure environments, with customizable workflows and expert support.

Products

• Polaron SegmentationAutomates the measurement of features, phases, and defects in microscopy data with accuracy matching or exceeding expert analysis. Identifies and quantifies features in microscopy data, turning complex microstructure into consistent, objective measurements.
• Polaron ReconstructionUnlocks 3D insights at the speed and resolution of 2D imaging, converting 2D images to 3D volumes for deeper understanding of critical properties like transport and mechanics, and better downstream modeling.
• Polaron DesignUses microstructure-derived data to explore microstructural design scenarios and guide optimization, connecting process to structure and structure to outcomes. Enables faster, evidence-driven decisions and reduces experimental iterations.
• Polaron PlatformTransforms image data into materials intelligence, connecting process, structure, and performance across R&D and production. It includes characterization and design engines, allowing for rapid model training and evaluation.

Key capabilities

• Purpose-built AI models for microstructure workflows
• Segmentation, quantitative analysis, 3D reconstruction, and design capabilities
• Automated measurement of features, phases, and defects
• 2D to 3D AI reconstruction
• Microstructure prompting to explore design candidates in silico
• Process models to predict microstructural changes across process space
• Closed-loop process optimisation to identify optimal recipes
• Rigorously validated, production ready models
• Works with standard industrial imaging modalities
• Trains models rapidly on modest, structured datasets
• Supports high-throughput batch processing
• Secure by design with customer data isolated
• Deployable across research and production workflows
• Enterprise-ready, secure-by-design platform
• Collaborative and traceable outputs
• Customisable workflows, expert supported
• State-of-the-art image segmentation
• Scalable data-driven workflows
• GPU accelerated simulations
• Microstructure-derived parameterisation for physics-based models
• Reduced parameterisation burden via microstructure-grounded inputs
• Predictive models for process, structure, performance

Use cases

• Reducing uncertainty in materials decisions
• Accelerating design cycles
• Unlocking better performance in materials
• Automating measurement of features, phases, and defects
• Unlocking 3D insights from 2D imaging
• Exploring microstructural design scenarios
• Guiding optimization of materials
• Connecting process to structure and structure to outcomes
• Standardizing objective evidence for microstructure
• Accelerating data to decision in R&D, quality, and modelling workflows
• Enabling data-driven design of microstructure
• Turning microscopy images into quantitative insight
• Moving materials design in silico
• Exploring thousands of structures and process combinations virtually
• Balancing performance trade-offs (e.g., energy density, power capability, durability)
• Automated microstructure quantification at scale
• Root-cause and change analysis between conditions
• Quantifying electrode level degradation for automotive OEMs
• AI-accelerated design of next-generation battery cathode material (LMFP electrodes)
• Improving cell performance and understanding LMFP processing
• Standardizing evidence and detecting drift early in quality control
• Defining objective acceptance criteria from microstructure metrics
• Tracking microstructure distributions over time and across sites/suppliers
• Generating traceable evidence for cross-team alignment
• Improving predictive power of physics-based models with microstructure-derived parameters
• Building predictive models connecting process conditions to microstructure and performance outcomes

AI approach

Polaron builds AI models to characterize and design microstructure in materials science. Their platform uses AI for segmentation, quantitative analysis, 3D reconstruction, and design, enabling faster, evidence-driven decisions. They train models rapidly on structured datasets and offer GPU accelerated simulations.

Tech named: AI models, machine learning, AI-based algorithms, GPU accelerated simulations

Industries served

• Materials science
• Automotive
• Battery manufacturing
• Energy storage

What it says sets it apart

• Intelligence layer for materials science
• AI models built specifically for microstructure workflows
• Characterisation at a new level of fidelity
• Ability to move from observing microstructure to designing it
• Microstructure intelligence to reduce risk, accelerate decisions, and unlock performance
• More certainty with standardised, objective evidence
• Faster data to decision
• Unlocks performance with microstructure as a variable
• Deployed through a secure enterprise platform, backed by experts
• Rigorously validated, production ready models with focus on observability and validation
• Puts the power of AI in the hands of engineers
• Mission to accelerate development of critical materials for modern life
• Founded by scientists and engineers at the intersection of materials science, physics, and machine learning
• Proven in research and industry, including winning the £1M Manchester Prize for AI
• Backed by leading European deep-tech investors

Funding rounds we track

From the AI funding tracker — rounds as reported by the linked publications.