Deep reinforcement learning for microstructural optimisation of silica aerogels

Scientific Reports, vol. 14, pp. 1511

Abstract

Silica aerogels are being extensively studied for aerospace and transportation applications due to their diverse multifunctional properties. While their microstructural features dictate their thermal, mechanical, and acoustic properties, their accurate characterisation remains challenging due to their nanoporous morphology and the stochastic nature of gelation. In this work, a deep reinforcement learning (DRL) framework is presented to optimise silica aerogel microstructures modelled with the diffusion-limited cluster-cluster aggregation (DLCA) algorithm. For faster computations, two environments consisting of DLCA surrogate models are tested with the DRL framework for inverse microstructure design. The DRL framework is shown to effectively optimise the microstructure morphology, wherein the error of the material properties achieved is dependent upon the complexity of the environment. However, in all cases, with adequate training of the DRL agent, material microstructures with desired properties can be achieved by the framework. Thus, the methodology provides a resource-efficient means to design aerogels, offering computational advantages over experimental iterations or direct numerical solutions.

Authors 4

1. Prakul Pandit corresponding

   Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)

   Affiliation as printed

   Department of Aerogels and Aerogel Composites, Institute of Materials Research, German Aerospace Center, Linder Höhe, 51147, Cologne, NRW, Germany. prakul.pandit@dlr.de

   Department of Aerogels and Aerogel Composites, Institute of Materials Research, German Aerospace Center, Linder Höhe, 51147, Cologne, NRW, Germany

2. Rasul Abdusalamov corresponding Aachen Department of Continuum Mechanics

   RWTH Aachen University

   Affiliation as printed

   Department of Continuum Mechanics, RWTH Aachen University, Eilfschornsteinstr. 18, 52062, Aachen, NRW, Germany. abdusalamov@km.rwth-aachen.de

   Department of Continuum Mechanics, RWTH Aachen University, Eilfschornsteinstr. 18, 52062, Aachen, NRW, Germany

3. Mikhail Itskov Aachen Department of Continuum Mechanics

   RWTH Aachen University

   Affiliation as printed

   Department of Continuum Mechanics, RWTH Aachen University, Eilfschornsteinstr. 18, 52062, Aachen, NRW, Germany

4. Ameya Rege

   Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) · Keele University

   Affiliation as printed

   Department of Aerogels and Aerogel Composites, Institute of Materials Research, German Aerospace Center, Linder Höhe, 51147, Cologne, NRW, Germany

   School of Computer Science and Mathematics, Keele University, Keele, Staffordshire, ST5 5BG, UK