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Machine learning enables polymer cloud-point engineering via inverse design | npj Computational Materials
Nature
Inverse design is an outstanding challenge in disordered systems with multiple length scales such as polymers, particularly when designing...
59 months ago
Applications of Machine Learning to Design Polymer-Based Dielectrics
AZoM
Polymer-based dielectrics are widely used in different electrical and electronic devices like capacitors, power transmission cables,...
31 months ago
Sizing up feature descriptors for macromolecular machine learning with polymeric biomaterials | npj Computational ...
Nature
It has proved challenging to represent the behavior of polymeric macromolecules as machine learning features for biomaterial interaction...
12 months ago
Artificial intelligence driven design of catalysts and materials for ring opening polymerization using a domain-specific ...
Nature
Advances in machine learning (ML) and automated experimentation are poised to vastly accelerate research in polymer science.
12 months ago
Two-step machine learning enables optimized nanoparticle synthesis | npj Computational Materials
Nature
In materials science, the discovery of recipes that yield nanomaterials with defined optical properties is costly and time-consuming.
38 months ago
How machine learning can help select capping layers to suppress perovskite degradation
Nature
Environmental stability of perovskite solar cells (PSCs) has been improved by trial-and-error exploration of thin low-dimensional (LD)...
46 months ago
Materials informatics approach using domain modelling for exploring structure–property relationships of polymers ...
Nature
In the development of polymer materials, it is an important issue to explore the complex relationships between domain structure and physical...
24 months ago