CIF21 DIBBS: EI: The Local Spectroscopy Data Infrastructure (LSDI)

传统的经验性和一次一次的材料测试不太可能满足化学和材料研究的创新需求，使新兴行业能够及时应对能源、国家安全、医疗保健等领域的挑战。从历史上看，新材料的探索既缓慢又昂贵，从概念到商业化平均需要18年时间。该项目确定了一项重大的科学挑战--通过光谱学对材料和化学体系进行表征--通过积累、组织和自动化实验和计算资源和数据，可以极大地加强和扩大材料研究。目前，由于没有资源可以有效地完成这些任务，大量的时间被投入到光谱数据的解释和理解上。该项目使从事光谱领域工作的材料研究人员和化学家能够访问现有参数和光谱的可搜索数据库，以便进行比较和自动识别，并处理各种数据要素--生产、管理、分析、传播和共享。由此产生的数据资源有助于更广泛的材料、化学和工程界的网络基础设施，并有可能在科学和工业中催化新材料的发现和材料和化学系统的创新使用。本地光谱数据基础设施(LSDI)项目的目标是建立第一个基于良好基准的计算光谱的计算本地原子环境光谱数据库，以使公众能够获得用于快速表征材料的在线资源，以加速材料的开发和优化。随着涉及缺陷、界面和表面的纳米工程的新技术的进步，确定材料中的局部原子环境变得越来越重要。光谱技术--包括X射线近边吸收光谱(XANES)、扩展X射线吸收精细结构(EXAFS)、电子能量损失谱(EELS)和核磁共振(NMR)--已经成为阐明材料中原子尺度的化学结构、电子性质和量子现象的基本表征工具。越来越需要一种通用资源，通过利用计算方法的最新进展来填充由固态X射线吸收和核磁共振光谱及相关参数组成的交互式数据库，从而帮助所有研究人员，包括非专业人员进行光谱分配。该项目包括：(1)为XAS/核磁共振谱的第一原理计算建立可靠的基准工作流程；(2)数据生成、管理和存储；(3)开发自动化光谱分析算法；(4)通过材料项目传播；(5)通过新的材料数据云(MDCloud)环境与社区进行动态互动。该项目开发的数据基础设施将使研究人员能够通过互联网访问现有参数和光谱的可搜索数据库，以便进行比较、自动识别，以及用于模拟与各种结构和化学假说相关的光谱的计算资源。LSDI为材料、化学和工程界的网络基础设施做出贡献，并支持在光谱方法、材料和化学系统的基础理解方面取得进展。该系统催化新材料的发现，并支持材料和化学系统在科学和工业中的创新使用，这与材料基因组计划的目标一致。该奖项由先进网络基础设施部颁发，由NSF工程局(土木、机械和制造创新部)和NSF数学和物理科学部(化学部和材料研究部)联合支持。

Traditional empirical and 'one-at-a-time' materials testing is unlikely to meet the innovation needs in chemical and materials research, to enable emerging industries to address challenges in energy, national security, healthcare, and other areas in a timely manner. Historically, novel materials exploration has been slow and expensive, taking on average 18 years from concept to commercialization. This project has identified a major scientific challenge - characterization of materials and chemical systems via spectroscopy - that can greatly enhance and expand materials research through accumulation, organization, and automation of both experimental and computational resources and data. Currently, a large amount of time is invested in the interpretation and understanding of spectroscopic data, since no resource for efficiently accomplishing these tasks is available. This project allows materials researchers and chemists working in the spectroscopic field to access a searchable database of existing parameters and spectra for comparative, automated identification, and to address the full range of data elements -- production, curation, analysis, dissemination and sharing. The resulting data resource contributes to the cyberinfrastructure of the broader materials, chemistry, and engineering community, and has the potential to catalyze the discovery of new materials and the innovative use of materials and chemical systems in science and industry. The goal of the Local Spectroscopy Data Infrastructure (LSDI) project is to establish the first computational local atomic environment spectroscopy database, based on well-benchmarked computational spectra, to enable a publicly available, online resource for rapid material characterization, to accelerate materials development and optimization. Through novel technological advancements involving nanoscale engineering of defects, interfaces and surfaces, it has become increasingly important to determine the local atomic environments in materials. Spectroscopic techniques - including X-Ray Absorption Near Edge Spectroscopy (XANES), Extended X-Ray Absorption Fine Structure (EXAFS), Electron Energy Loss Spectroscopy (EELS), and Nuclear Magnetic Resonance (NMR) - have become essential characterization tools in elucidating atomic-scale chemical structure, electronic properties, and quantum phenomena in materials. There is a growing need for a general-use resource to help make spectral assignments for all researchers, including non- specialists, by capitalizing on recent advances in computational methods to populate an interactive database consisting of solid-state X-ray absorption and NMR spectra and associated parameters. This project includes: (i) creation of robust, benchmarked workflows for first-principles calculation of XAS/NMR spectra; (ii) data generation, curation and storage; (iii) development of automated spectral analysis algorithms; (iv) dissemination through the Materials Project; and (v) dynamic interaction with the community through the new Materials Data Cloud (MDCloud) environment. The data infrastructure developed by this project will allow a researcher who has recorded an experimental spectrum, such as by NMR, XANES or XAFS, of a solid-state material - even one with a disordered or non-crystalline structure - to access through the internet a searchable database of existing parameters and spectra for comparative, automated identification, along with a computational resource for simulating the spectra associated with various structural and chemical hypotheses. The LSDI contributes to the cyberinfrastructure of the materials, chemistry, and engineering communities, and supports advances in the fundamental understanding of spectroscopic methods, materials and chemical systems. The system catalyzes the discovery of new materials, and supports innovative use of materials and chemical systems in science and industry, consistent with the goals of the Materials Genome Initiative.This award by the Advanced Cyberinfrastructure Division is jointly supported by the NSF Engineering Directorate (Division of Civil, Mechanical & Manufacturing Innovation) and the NSF Directorate for Mathematical & Physical Sciences (Division of Chemistry and Division of Materials Research).