Machine learning-based structure–property predictions in silica aerogels

Soft Matter, vol. 17, pp. 7350–7358

Abstract

= 0.973. Furthermore, the same ANN is subsequently inverted for predicting the input parameters for reconstructing a DLCA model network of silica aerogels, for a given desired target fractal dimension. There, it is shown that the fractal dimension is not a unique characteristic defining the network structure of silica aerogels, and the same fractal dimension can be obtained for different sets of DLCA input parameters. However, the problem of non-uniqueness is solved by using a guided gradient descent approach for predictive modelling purposes within certain bounds of the input parameter-space. Model DLCA structures are generated from the constrained and unconstrained inversion, and are compared against several parameters, amongst them, the pore-size distributions. The constrained inversion of the ANN is shown to predict the DLCA model parameters for a desired fractal dimension within an error of 2%.

Authors 5

1. Rasul Abdusalamov corresponding Aachen Department of Continuum Mechanics

   RWTH Aachen University

   Affiliation as printed

   Aachen

   Department of Continuum Mechanics

   Germany

   RWTH Aachen University

   Department of Continuum Mechanics, RWTH Aachen University, Aachen, Germany

2. Prakul Pandit

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

   Affiliation as printed

   Cologne

   Department of Aerogels and Aerogel Composites

   German Aerospace Center

   Germany

   Institute of Materials Research

   Department of Aerogels and Aerogel Composites, Institute of Materials Research, German Aerospace Center, Cologne, Germany

3. Barbara Milow

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

   Affiliation as printed

   Cologne

   Department of Aerogels and Aerogel Composites

   German Aerospace Center

   Germany

   Institute of Materials Research

   Department of Aerogels and Aerogel Composites, Institute of Materials Research, German Aerospace Center, Cologne, Germany

4. Mikhail Itskov Aachen Department of Continuum Mechanics

   RWTH Aachen University

   Affiliation as printed

   Aachen

   Department of Continuum Mechanics

   Germany

   RWTH Aachen University

   Department of Continuum Mechanics, RWTH Aachen University, Aachen, Germany

5. Ameya Rege corresponding

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

   Affiliation as printed

   Cologne

   Department of Aerogels and Aerogel Composites

   German Aerospace Center

   Germany

   Institute of Materials Research

   Department of Aerogels and Aerogel Composites, Institute of Materials Research, German Aerospace Center, Cologne, Germany