Artificial intelligence allowing data-driven prediction of physicochemical properties of polymers is rapidly emerging as a powerful tool for advancing material science. Here, we developed a methodology to use polymer adsorption data as predictable data by analyzing causal relationships between polymer properties and experimental results instead of using big polymer data.
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© 2022 The Royal Society of Chemistry.
All Science Journal Classification (ASJC) codes
- Electronic, Optical and Magnetic Materials
- Ceramics and Composites
- Surfaces, Coatings and Films
- Metals and Alloys
- Materials Chemistry