Accelerating Adaptive Materials Innovation for Resilient Dual-Use Steel Technologies (ADMIRE)

Purpose and goal

The project aims to deliver an AI-driven digital platform that applies physics-informed machine learning to accelerate the design and implementation of advanced dual-use steel alloys. By embedding fundamental physics principles directly into the AI models, the platform will enable high-quality predictions and rapid optimization of alloy compositions and processing routes.

Expected effects and result

The expected results are: 1. Development of a modular, physics-informed AI engine for alloy design and simulation. 2. Integration with physical modeling and empirical data in predictive workflows. 3. Establishment of an efficient architecture for the digital platform to support steel development and deployment. 4. Validation of the platform through representative civil and military use cases.

Planned approach and implementation

The project is structured around four work packages – outreach activities to the defense industry, adaptation of the digital platform for the civilian market for defense applications, validation with a defense partner, and dissemination to both defense and civilian stakeholders. Together, these work packages are designed to both deliver a validated dual-use prototype and fully prepare Ferritico for the accelerator program.