Axalta Receives Three Edison Awards for Coating Technologies

Axalta Coating Systems

PHILADELPHIA, PA — Axalta Coating Systems (NYSE: AXTA) said it received three 2026 Edison Awards recognizing technologies in automotive coatings, electric vehicle safety, and manufacturing processes.

The company said its EcoNextJet vehicle color customization system and Alesta e-PRO FG Black coating for electric vehicle battery protection each received Gold awards, while its TintMaster AI platform received a Bronze award.

“Each of these technologies addresses a critical inflection point in their use,” Robert Roop, Axalta’s senior vice president and chief technology officer, said in a statement, citing vehicle customization, electric vehicle battery safety, and efforts to reduce color variability in paint manufacturing.

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The Edison Awards, established in 1987 and named after Thomas Edison, recognize innovation in product and service development, marketing, design, and sustainability, according to the program.

Axalta said EcoNextJet is a digital automotive painting system that applies customized colors and designs using drop-on-demand technology, enabling manufacturers to produce individualized vehicle finishes at scale.

The system uses jettable paints and integrates robotics and printhead technologies developed in collaboration with Dürr and Xaar, the company said.

The Alesta e-PRO FG Black coating is designed for use in electric vehicle battery systems to help limit fire propagation during thermal events, including overheating that can lead to chain reactions and temperatures exceeding 1200°C, according to Axalta.

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The company said the coating is intended to improve thermal stability and insulation performance when used as part of an original equipment manufacturer battery system.

TintMaster AI uses data and predictive models to adjust paint formulations before production, reducing variability and improving manufacturing efficiency.

Axalta said the platform can improve right-the-first-time performance by up to 29% in certain manufacturing scenarios compared with traditional methods.

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