Everest
| Reference number | |
| Coordinator | Alleima EMEA AB |
| Funding from Vinnova | SEK 5 486 448 |
| Project duration | November 2025 - November 2029 |
| Status | Ongoing |
| Venture | Impact Innovation Metals & Minerals - Program-specific efforts Vinnova |
| Call | Impact Innovation: Research and development projects within Techological Action Areas in the Swedish Metals and Minerals program |
Purpose and goal
The Everest project aims to minimize the capital expenditure (CAPEX) of green hydrogen production by developing AI-assisted engineering methods for key PEM water electrolyzer components. By optimizing thermally sprayed titanium layers, the project seeks to enable cost-effective, durable solutions, supporting Sweden’s transition to sustainable hydrogen and green steel.
Expected effects and result
The project expects to deliver automated artificial intelligence/machine learning (AI/ML)-based methods for rapid analysis and optimization of porous titanium layers, reducing titanium and platinum use. This will lower costs, improve raw material resilience, and accelerate the adoption of green hydrogen in hard-to-abate industries, contributing to Sweden’s climate neutrality and digitalization goals.
Planned approach and implementation
Everest will use a closed-loop, AI-driven workflow: high-throughput sample preparation, automated 3D image analysis, digital twin modeling, and Bayesian optimization of process parameters. The consortium—Alleima, Sandvik, and Uppsala University—will collaborate in work packages covering imaging, AI development, electrochemical modeling, and project management.