Discover Materials

ISSN：2730-7727

ESSN：2730-7727

所属分区：2区

出版地：Switzerland

研究方向：materials-

Discover Materials英文简介

Discover Materials is part of the Discover journal series committed to providing a streamlined submission process, rapid review and publication, and a high level of author service at every stage. It is a broad, open access journal publishing research from across all fields of materials research.

Discover Materials covers all areas where materials are activators for innovation and disruption, providing cutting-edge research findings to researchers, academicians, students, and engineers. It considers the whole value chain, ranging from fundamental and applied research to the synthesis, characterisation, modelling and application of materials.

Moreover, we especially welcome papers connected to so-called ‘green materials’, which offer unique properties including natural abundance, low toxicity, economically affordable and versatility in terms of physical and chemical properties. They are the activators of an eco-sustainable economy serving all innovation sectors. Indeed, they can be applied in numerous scientific and technological applications including energy, electronics, building, construction and infrastructure, materials science and engineering applications and pollution management and technology. For instance, biomass-based materials can be developed as a source for biodiesel and bioethanol production, and transformed into advanced functionalized materials for applications such as the transformation of chitin into chitosan which can be further used for biomedicine, biomaterials and tissue engineering applications. Green materials for electronics are also a key vector concerning the integration of novel devices on conformable, flexible substrates with free-of-form surfaces for innovative product development. We also welcome new developments grounded on Artificial Intelligence to model, design and simulate materials and to gain new insights into materials by discovering new patterns and relations in the data.

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