ADAM: Accelerated Design of Architectural Materials

Coordinator: Laurent ORGEAS

3SR – Laboratoire Sols, Solides, Structures, Risques
(UMR 5521 Univ. Grenoble Alpes/CNRS/Grenoble INP)

Keywords: architectural materials, 3D-4D printing, 3D-4D imaging, design by artificial intelligence, thermal and hygro-mechanical properties

With a growing demand for multifunctional materials with optimized properties, the usual approach to materials design which optimizes their chemistry and nanostructure is interesting but reaches its limits. To overcome them, a complementary approach proves relevant and consists of taking advantage of the higher scale, the mesostructure, in which the architecture of the material can be controlled by hybridization and/or optimization of the geometry. This approach requires the use of innovative materials development and shaping processes, such as 3D or 4D printing.

By taking advantage of recent advances in artificial intelligence and data mining, the ADAM (Accelerated Design of Architectural Materials) project aims to discover new architectural materials:

  • with mesostructures optimized for increased multifunctional properties,
  • which represent real breakthroughs with regard to existing material solutions,
  • by accelerating this design process by a factor of ten.

The overall proof of concept will be highlighted with three printed architectural materials, in line with the major issues of energy transition and climate change. They are of particular interest in the field of energy, the transport of goods and people and even health.

For the first two architectural systems, metallic, we will optimize their shaping, their mesostructures and their thermal (conductive and radiative) and mechanical (elastoplastic) properties by coupling:

  • 3D imaging in real time on an instrumented additive manufacturing device,
  • 3D in situ imaging in real time during the deformation of the produced architectures,
  • advanced digital modeling in materials science and structural optimization,
  • techniques from data mining and artificial intelligence.

The third system will be a hydrophilic bio-sourced system developed by printing and optimized to achieve new hygromorphic properties.