An AI-driven multiscale methodology to develop transparent wood as sustainable functional material by using the SSbD...

Area of Science:

• Materials Science
• Sustainable Engineering
• Computational Materials Design

Background:

• Developing safe and sustainable materials is a significant societal challenge.
• Wood-based composites offer an eco-friendly alternative to conventional materials like glass and polymers.
• Traditional material development is time-consuming; computational and AI approaches can accelerate this process.

Purpose of the Study:

• To develop advanced computational and AI-based tools for material design.
• To focus on transparent wood (TW) as a promising sustainable composite material.
• To accelerate the design, production, and optimization of TW for industrial applications.

Main Methods:

• Utilizing an Artificial Intelligence (AI)-driven multiscale methodology.
• Developing reliable numerical models for material simulation.
• Leveraging computational approaches for accelerated materials design.

Main Results:

• The AI-TranspWood project aims to create AI-driven tools for transparent wood development.
• This methodology promises to significantly speed up the creation of new sustainable materials.
• The project focuses on advancing AI-based multiscale modeling for composite materials.

Conclusions:

• The AI-TranspWood project is developing novel AI tools for sustainable material design.
• This research advances the use of AI-driven multiscale methodologies for transparent wood.
• The project contributes to faster and more efficient development of sustainable composite materials.