Generative models as an emerging paradigm in the chemical sciences
Traditional computational approaches to design chemical species are limited by the need to
compute properties for a vast number of candidates, eg, by discriminative modeling …
compute properties for a vast number of candidates, eg, by discriminative modeling …
Knowledge-integrated machine learning for materials: lessons from gameplaying and robotics
As materials researchers increasingly embrace machine-learning (ML) methods, it is natural
to wonder what lessons can be learned from other fields undergoing similar developments …
to wonder what lessons can be learned from other fields undergoing similar developments …
Bio-based polymers with performance-advantaged properties
Bio-based compounds with unique chemical functionality can be obtained through selective
transformations of plant and other non-fossil, biogenic feedstocks for the development of …
transformations of plant and other non-fossil, biogenic feedstocks for the development of …
Recent progress and future prospects on all-organic polymer dielectrics for energy storage capacitors
With the development of advanced electronic devices and electric power systems, polymer-
based dielectric film capacitors with high energy storage capability have become particularly …
based dielectric film capacitors with high energy storage capability have become particularly …
Design of functional and sustainable polymers assisted by artificial intelligence
Artificial intelligence (AI)-based methods continue to make inroads into accelerated
materials design and development. Here, we review AI-enabled advances made in the …
materials design and development. Here, we review AI-enabled advances made in the …
Data‐driven materials science: status, challenges, and perspectives
Data‐driven science is heralded as a new paradigm in materials science. In this field, data is
the new resource, and knowledge is extracted from materials datasets that are too big or …
the new resource, and knowledge is extracted from materials datasets that are too big or …
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 …
Data-driven materials research enabled by natural language processing and information extraction
Given the emergence of data science and machine learning throughout all aspects of
society, but particularly in the scientific domain, there is increased importance placed on …
society, but particularly in the scientific domain, there is increased importance placed on …
Machine learning overcomes human bias in the discovery of self-assembling peptides
Peptide materials have a wide array of functions, from tissue engineering and surface
coatings to catalysis and sensing. Tuning the sequence of amino acids that comprise the …
coatings to catalysis and sensing. Tuning the sequence of amino acids that comprise the …
Polymer informatics: Current status and critical next steps
Artificial intelligence (AI) based approaches are beginning to impact several domains of
human life, science and technology. Polymer informatics is one such domain where AI and …
human life, science and technology. Polymer informatics is one such domain where AI and …