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FAIR data enabling new horizons for materials research
The prosperity and lifestyle of our society are very much governed by achievements in
condensed matter physics, chemistry and materials science, because new products for …
condensed matter physics, chemistry and materials science, because new products for …
A systematic review of machine learning methods applied to fuel cells in performance evaluation, durability prediction, and application monitoring
W Ming, P Sun, Z Zhang, W Qiu, J Du, X Li… - International Journal of …, 2023 - Elsevier
A fuel cell is a power generation device that directly converts chemical energy into electrical
energy through chemical reactions; fuel cells are widely used in aerospace, electric vehicle …
energy through chemical reactions; fuel cells are widely used in aerospace, electric vehicle …
Review of machine learning for hydrodynamics, transport, and reactions in multiphase flows and reactors
Artificial intelligence (AI), machine learning (ML), and data science are leading to a
promising transformative paradigm. ML, especially deep learning and physics-informed ML …
promising transformative paradigm. ML, especially deep learning and physics-informed ML …
Unsupervised learning methods for molecular simulation data
Unsupervised learning is becoming an essential tool to analyze the increasingly large
amounts of data produced by atomistic and molecular simulations, in material science, solid …
amounts of data produced by atomistic and molecular simulations, in material science, solid …
Molecular characterization of polymer networks
Polymer networks are complex systems consisting of molecular components. Whereas the
properties of the individual components are typically well understood by most chemists …
properties of the individual components are typically well understood by most chemists …
Emerging trends in machine learning: a polymer perspective
In the last five years, there has been tremendous growth in machine learning and artificial
intelligence as applied to polymer science. Here, we highlight the unique challenges …
intelligence as applied to polymer science. Here, we highlight the unique challenges …
[HTML][HTML] Unleashing the power of artificial intelligence in materials design
The integration of artificial intelligence (AI) algorithms in materials design is revolutionizing
the field of materials engineering thanks to their power to predict material properties, design …
the field of materials engineering thanks to their power to predict material properties, design …
Emerging materials intelligence ecosystems propelled by machine learning
The age of cognitive computing and artificial intelligence (AI) is just dawning. Inspired by its
successes and promises, several AI ecosystems are blossoming, many of them within the …
successes and promises, several AI ecosystems are blossoming, many of them within the …
[HTML][HTML] Machine-learning predictions of polymer properties with Polymer Genome
Polymer Genome is a web-based machine-learning capability to perform near-
instantaneous predictions of a variety of polymer properties. The prediction models are …
instantaneous predictions of a variety of polymer properties. The prediction models are …
Machine-Learning-Guided Discovery of 19F MRI Agents Enabled by Automated Copolymer Synthesis
M Reis, F Gusev, NG Taylor, SH Chung… - Journal of the …, 2021 - ACS Publications
Modern polymer science suffers from the curse of multidimensionality. The large chemical
space imposed by including combinations of monomers into a statistical copolymer …
space imposed by including combinations of monomers into a statistical copolymer …