Fernando Lomello , Lucie Bard , Mario Maglione , Frédéric Schuster
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引用次数: 0
Abstract
Introduction
The quest to develop efficient, sustainable materials from non-critical, non-toxic resources is one of today's most formidable challenges in the current context of energy, transport, digital or healthcare transitions. In response, France launched the pioneering Priority Equipment and Research Program (PEPR) DIADEM in 2022. This innovative initiative, focused on DIscovery Acceleration for the Deployment of Emerging Materials (DIADEM), leverages Artificial Intelligence (AI) to accelerate the innovation chain from conception to realization, revolutionizing Materials Science sustainably. With a strategic emphasis on scientific synergy, PEPR DIADEM aims to expedite the discovery and development of novel materials essential for contemporary and future societal challenges. To achieve this, the program seeks to catalyze breakthroughs in areas ranging from energy efficiency to transportation, digitalization, and healthcare, covering a broad spectrum of materials from metallic alloys to functional nanostructures. Aligned with the Green Deal framework's ambitious targets, PEPR DIADEM addresses the urgent need for accelerated sustainable materials research. By utilizing cutting-edge technologies like rapid synthesis and characterization tools, automation, digital simulations, data management, AI, additive manufacturing, and thin film engineering, the program is set to significantly reshape the materials science landscape. As PEPR DIADEM embarks on its journey of innovation, it not only advances scientific knowledge but also holds the promise of addressing current global challenges and paving the way for a more sustainable and prosperous future.
期刊介绍:
Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to:
Structure and function of proteins, nucleic acids and other macromolecules
Structure and function of multi-component complexes
Protein folding, processing and degradation
Enzymology
Computational and structural studies of plant systems
Microbial Informatics
Genomics
Proteomics
Metabolomics
Algorithms and Hypothesis in Bioinformatics
Mathematical and Theoretical Biology
Computational Chemistry and Drug Discovery
Microscopy and Molecular Imaging
Nanotechnology
Systems and Synthetic Biology