Ai-designed low-add-on barrier surface treatment for film-free nonwoven substrates
Polymerize combines an AI-native materials-informatics platform with a lab-scale prototyping and testing network to co-develop low-add-on barrier surface treatments for nonwoven substrates. The service models how treatment chemistry, add-on level, and cure conditions jointly affect competing targets—barrier and stain masking versus breathability, softness, and tensile strength—then runs active-learning design of experiments to identify formulations clearing all thresholds at under €0.07/m² and 60 gsm.
Overview
Polymerize offers an AI-native materials-informatics service to co-develop low-add-on barrier surface treatments for nonwoven substrates used in film-free outercovers. Rather than supplying a fixed material, the service combines predictive modelling with lab-scale prototyping to design treatment chemistries that meet strict performance targets across a demanding multi-objective trade-off: hydrohead barrier and stain masking must be achieved without compromising breathability, softness, drape, or tensile strength—all within a hard cost ceiling of €0.07/m² and a basis weight under 60 gsm.
The service is designed for manufacturers seeking to replace film laminates with directly treated nonwovens, reducing cost, weight, and complexity while maintaining barrier performance. It is also a low-risk route to innovation: the active-learning workflow identifies the most promising candidates before any pilot-line investment.
Technical specifications
The approach models how treatment chemistry, add-on level, and cure/process conditions jointly affect the full target property set, including hydrohead barrier, stain masking, water vapour transmission rate (WVTR), air permeability, cup-crush softness, drape, noise, and machine/cross-direction tensile strength.
Key features:
- Active-learning design of experiments (DoE) identifies candidate treatments predicted to clear all thresholds simultaneously
- Explainable AI on the barrier-versus-breathability-versus-softness trade-offs
- Lab-scale prototyping on real nonwoven substrates (synthetic, natural, or hybrid)
- Characterisation across the full property set via an integrated lab network
- Reusable predictive model delivered alongside treated samples and a data pack
Target performance thresholds: barrier ~62 mbar, WVTR >2000, air permeability >5, cup-crush <50 g, tensile >2000 gf/3in, basis weight <60 gsm, cost <€0.07/m².
Technology readiness level
The service is delivered in four phases. Phase 0 scoping (2 weeks) confirms target substrates, benchmark materials, fluid set, and all performance thresholds. Phase 1 modelling and DoE (3–4 weeks) builds models linking treatment chemistry, add-on, and process to the full property set. Phase 2 lab prototyping (5–8 weeks) treats real substrates and characterises all properties, feeding results back into the models. Phase 3 down-selection (3–4 weeks) converges on one to two lead candidates that clear all must-have thresholds at target cost, and delivers samples, a data pack, and a reusable model ready for pilot-line trials.
The platform has been validated in prior programmes: in a water-based paints project, modelling 50+ ingredients against 15+ properties halved model error (16% to 8%). The service is offered at lab scale with pilot-line readiness as the defined next step.
About Polymerize
Polymerize is an AI-native platform specifically engineered to transform materials research and development. It operates as a system of intelligence that integrates a unified data foundation, domain-specific AI models, and explainable insights to accelerate the discovery, development, and scaling of new materials. By digitizing experimental workflows, the platform replaces manual, spreadsheet-based processes with a centralized, data-driven backbone. The solution features over 35 domain-guided models trained on polymers, chemicals, and advanced materials, which allow R&D teams to predict material properties, optimize formulations, and gain scientific explanations for AI-driven recommendations.
The platform serves global R&D teams across industries such as automotive, specialty chemicals, coatings, and packaging, helping them reduce failed experiments and shorten go-to-market timelines. By capturing and leveraging institutional knowledge, Polymerize enables organizations to turn years of trial-and-error into targeted innovation, ensuring that data from past experiments informs future research. Customers use the platform to achieve significant ROI through increased discovery speed and streamlined operational forecasting, with security compliance standards like SOC 2 and ISO 27001 integrated to protect sensitive intellectual property. Founded in 2020 and headquartered in Singapore, the company maintains a global presence with offices and strategic collaborations spanning Asia, Europe, and the United States.
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