材料信息学和可持续性——紧急案例

IF 2.4 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE DataCentric Engineering Pub Date : 2021-11-15 DOI:10.1017/dce.2021.19
H. Melia, Eric S. Muckley, J. Saal
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引用次数: 2

摘要

摘要开发变革性技术以缓解我们的全球环境和技术挑战,需要在先进材料和化学品的设计、开发和制造方面进行重大创新。为了比传统的人类直觉指导的科学方法更快地实现这一创新,我们必须过渡到以材料信息学为中心的范式,在这种范式中,利用数据科学、材料科学和人工智能之间的协同作用,实现变革,通过使用预测模型和数字双胞胎,数据驱动的发现比以往任何时候都更快。尽管材料信息学在材料和化工行业的使用正在迅速增加,但技能差距、文化阻力和数据稀疏等障碍阻碍了其广泛应用。我们讨论了材料信息学对加速技术创新的重要性,描述了当前的障碍和良好实践的例子,并就研究人员、资助机构和教育机构如何帮助加快采用21世纪急需的基于信息学的科学工具集提出了建议。
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Materials informatics and sustainability—The case for urgency
Abstract The development of transformative technologies for mitigating our global environmental and technological challenges will require significant innovation in the design, development, and manufacturing of advanced materials and chemicals. To achieve this innovation faster than what is possible by traditional human intuition-guided scientific methods, we must transition to a materials informatics-centered paradigm, in which synergies between data science, materials science, and artificial intelligence are leveraged to enable transformative, data-driven discoveries faster than ever before through the use of predictive models and digital twins. While materials informatics is experiencing rapidly increasing use across the materials and chemicals industries, broad adoption is hindered by barriers such as skill gaps, cultural resistance, and data sparsity. We discuss the importance of materials informatics for accelerating technological innovation, describe current barriers and examples of good practices, and offer suggestions for how researchers, funding agencies, and educational institutions can help accelerate the adoption of urgently needed informatics-based toolsets for science in the 21st century.
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来源期刊
DataCentric Engineering
DataCentric Engineering Engineering-General Engineering
CiteScore
5.60
自引率
0.00%
发文量
26
审稿时长
12 weeks
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