An AI-driven multiscale methodology to develop transparent wood as sustainable functional material by using the SSbD concept

IF 4.4 2区生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY

Computational and structural biotechnology journal Pub Date : 2024-10-18 DOI:10.1016/j.csbj.2024.10.022

Päivi Kivikytö-Reponen , Stefania Fortino , Veera Marttila , Alexey Khakalo , Kari Kolari , Antti Puisto , Daniele Nuvoli , Alberto Mariani

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引用次数: 0

Abstract

Efficient design, production, and optimization of new safe and sustainable by design materials for various industrial sectors is an on-going challenge for our society, poised to escalate in the future. Wood-based composite materials offer an attractive sustainable alternative to high impact materials such as glass and polymers and have been the focus of experimental research and development for years. Computational and AI-based materials design provides significant speed-up the development of these materials compared to traditional methods of development. However, reliable numerical models are essential for achieving this goal. The AI-TranspWood project, recently funded by the European Commission, has the ambition to develop such computational and AI-based tools in the context of transparent wood (TW), a promising composite with potential applications in various industrial fields. In this project we advance the development specifically by using an Artificial Intelligence (AI)-driven multiscale methodology.

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一种人工智能驱动的多尺度方法，利用 SSbD 概念将透明木材开发为可持续功能材料

高效设计、生产和优化用于各工业领域的安全、可持续的新型材料，是我们社会面临的一项持续挑战，而且在未来还将不断升级。木基复合材料为玻璃和聚合物等高冲击材料提供了极具吸引力的可持续替代品，多年来一直是实验研究和开发的重点。与传统开发方法相比，基于计算和人工智能的材料设计大大加快了这些材料的开发速度。然而，可靠的数值模型对于实现这一目标至关重要。最近由欧盟委员会资助的 AI-TranspWood 项目的目标是在透明木材（TW）的背景下开发这种基于计算和人工智能的工具。在本项目中，我们特别采用了人工智能（AI）驱动的多尺度方法来推进开发工作。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computational and structural biotechnology journal Biochemistry, Genetics and Molecular Biology-Biophysics

CiteScore

9.30

自引率

3.30%

发文量

540

审稿时长

6 weeks

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