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Abstract High‐throughput screening has become one of the major strategies for the discovery of novel functional materials. However, its effectiveness is severely limited by the lack of sufficient and diverse materials in current materials repositories such as the open quantum materials database (OQMD). Recent progress in deep learning have enabled generative strategies that learn implicit chemical rules for creating hypothetical materials with new compositions and structures. However, current materials generative models have difficulty in generating structurally diverse, chemically valid, and stable materials. Here we propose CubicGAN, a generative adversarial network (GAN) based deep neural network model for large scale generative design of novel cubic materials. When trained on 375 749 ternary materials from the OQMD database, the authors show that the model is able to not only rediscover most of the currently known cubic materials but also generate hypothetical materials of new structure prototypes. A total of 506 such materials have been verified by phonon dispersion calculation. Considering the importance of cubic materials in wide applications such as solar panels, the GAN model provides a promising approach to significantly expand existing materials repositories, enabling the discovery of new functional materials via screening. The new crystal structures discovered are freely accessible atwww.carolinamatdb.org.
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Thoughts on current trends in applied polymer/biopolymer materials for modern functional applications
We discuss current trends in developing novel synthetic polymers, biopolymers, and corresponding soft and functional hybrid nanocomposites for advanced current and future applications with an emphasis on active functional devices and functions. Among a wide variety of polymeric materials and relevant applications, we select the fields, which are close to the authors’ research interests. This selection includes strong but lightweight biopolymer composites, gel-like and porous materials for chemical and energy transport control, fast-actuating responsive materials and structures, and thin film electronic materials for chemical, physical, and biological sensing applications compatible with human and robotic interfaces.
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- Award ID(s):
- 2001968
- PAR ID:
- 10546261
- Publisher / Repository:
- NASU
- Date Published:
- Journal Name:
- Polymer journal
- Volume:
- 45
- Issue:
- 1
- ISSN:
- 1818-1724
- Page Range / eLocation ID:
- 3 to 14
- Subject(s) / Keyword(s):
- functional materials
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.15407/polymerj.45.01.003
