GUSTAVO ARIEL SCHWARTZ POMERANIEC-rekin lankidetzan egindako argitalpenak (10)

2024

  1. A glimpse inside materials: Polymer structure – Glass transition temperature relationship as observed by a trained artificial intelligence

    Computational Materials Science, Vol. 236

  2. Transfer learning-driven artificial intelligence model for glass transition temperature estimation of molecular glass formers mixtures

    Computational Materials Science, Vol. 238

2023

  1. Characterising the glass transition temperature-structure relationship through a recurrent neural network

    Journal of Non-Crystalline Solids: X, Vol. 18

2022

  1. Approaching Polymer Dynamics Combining Artificial Neural Networks and Elastically Collective Nonlinear Langevin Equation

    Polymers, Vol. 14, Núm. 8

  2. Estimating glass transition temperature and related dynamics of molecular glass formers combining artificial neural networks and disordered systems theory

    Journal of Non-Crystalline Solids: X, Vol. 15

  3. MAPPING THE NETWORKED CONTEXT OF COPERNICUS, MICHELANGELO, AND DELLA MIRANDOLA IN WIKIPEDIA

    Advances in Complex Systems, Vol. 25, Núm. 5-6

2021

  1. Mapping Chemical Structure-Glass Transition Temperature Relationship through Artificial Intelligence

    Macromolecules, Vol. 54, Núm. 4, pp. 1811-1817

2020

  1. From chemical structure to quantitative polymer properties prediction through convolutional neural networks

    Polymer, Vol. 193

  2. Localizing and quantifying the intra-monomer contributions to the glass transition temperature using artificial neural networks

    Polymer, Vol. 203

2017

  1. Water diffusion and hydrolysis effect on the structure and dynamics of epoxy-anhydride networks

    Polymer Degradation and Stability, Vol. 143, pp. 57-63