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

CIF21 DIBBS:EI:本地光谱数据基础设施 (LSDI)

基本信息

  • 批准号:
    1640899
  • 负责人:
  • 金额:
    $ 394.04万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2016
  • 资助国家:
    美国
  • 起止时间:
    2016-10-01 至 2022-09-30
  • 项目状态:
    已结题

项目摘要

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).
传统的经验性和“一次一个”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,医疗保健和其他领域的挑战。 从历史上看,新材料的探索一直缓慢而昂贵,从概念到商业化平均需要18年。 该项目确定了一个重大的科学挑战-通过光谱学表征材料和化学系统-可以通过积累,组织和自动化实验和计算资源和数据来大大增强和扩展材料研究。 目前,大量的时间被投入到光谱数据的解释和理解上,因为没有有效完成这些任务的资源。该项目允许在光谱领域工作的材料研究人员和化学家访问现有参数和光谱的可搜索数据库,以进行比较,自动识别,并解决所有数据元素-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,化学和工程社区的网络基础设施,并有可能催化新材料的发现以及材料和化学系统在科学和工业中的创新使用。本地光谱数据基础设施(LSDI)项目的目标是建立第一个基于基准计算光谱的计算本地原子环境光谱数据库,以实现快速材料表征的公开在线资源,加速材料开发和优化。通过涉及缺陷、界面和表面的纳米级工程的新技术进步,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射线吸收近边光谱(XANES),扩展X射线吸收精细结构(EXAFS),电子能量损失光谱(EELS)和核磁共振(NMR)-已成为阐明材料中原子尺度化学结构,电子性质和量子现象的重要表征工具。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NMR光谱以及相关参数组成的交互式数据库,来帮助所有研究人员(包括非专业人员)进行光谱分配。该项目包括:(i)为XAS/NMR光谱的第一原理计算创建强大的基准工作流程;(ii)数据生成,管理和存储;(iii)开发自动化光谱分析算法;(iv)通过材料项目传播;(v)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记录了固态材料(即使是具有无序或非晶体结构的材料)的实验光谱(如NMR、XANES或XAFS)的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,以进行比较、自动识别,沿着用于模拟与各种结构和化学假设相关的光谱的计算资源。 LSDI为材料,化学和工程社区的网络基础设施做出了贡献,并支持光谱方法,材料和化学系统的基本理解的进步。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,与材料基因组计划的目标一致。该奖项由高级网络基础设施部颁发,由NSF工程理事会(土木,机械制造创新部)和NSF数学物理科学理事会(化学部和材料研究部)共同支持。

项目成果

期刊论文数量(11)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
The 1H T1 dispersion curve of fentanyl citrate to identify NQR parameters
使用柠檬酸芬太尼的 1H T1 离散曲线来确定 NQR 参数
  • DOI:
    10.1016/j.ssnmr.2020.101697
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    3.2
  • 作者:
    Malone, Michael W.;Espy, Michelle A.;He, Sun;Janicke, Michael T.;Williams, Robert F.
  • 通讯作者:
    Williams, Robert F.
A disordered rock salt anode for fast-charging lithium-ion batteries
  • DOI:
    10.1038/s41586-020-2637-6
  • 发表时间:
    2020-09-03
  • 期刊:
  • 影响因子:
    64.8
  • 作者:
    Liu, Haodong;Zhu, Zhuoying;Liu, Ping
  • 通讯作者:
    Liu, Ping
Enabling materials informatics for 29Si solid-state NMR of crystalline materials
为晶体材料的 29Si 固态 NMR 提供材料信息学支持
  • DOI:
    10.1038/s41524-020-0328-3
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    9.7
  • 作者:
    Sun, He;Dwaraknath, Shyam;Ling, Handong;Qu, Xiaohui;Huck, Patrick;Persson, Kristin A.;Hayes, Sophia E.
  • 通讯作者:
    Hayes, Sophia E.
Influence of Alkali Metal Cations on the Photodimerization of Bromo Cinnamates Studied by Solid-State NMR
固态核磁共振研究碱金属阳离子对溴代肉桂酸酯光二聚反应的影响
  • DOI:
    10.1021/acs.jpcc.0c09826
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Zahan, Marufa;Sun, He;Hayes, Sophia E.;Krautscheid, Harald;Haase, Jürgen;Bertmer, Marko
  • 通讯作者:
    Bertmer, Marko
Core Scientific Dataset Model: A lightweight and portable model and file format for multi-dimensional scientific data
核心科学数据集模型:多维科学数据的轻量级便携模型和文件格式
  • DOI:
    10.1371/journal.pone.0225953
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    3.7
  • 作者:
    Srivastava, Deepansh J.;Vosegaard, Thomas;Massiot, Dominique;Grandinetti, Philip J.;Ramamoorthy, Ayyalusamy
  • 通讯作者:
    Ramamoorthy, Ayyalusamy
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Kristin Persson其他文献

Becoming-with the bog born: emotional collectives in ecological fieldwork
  • DOI:
    10.1007/s11422-024-10231-5
  • 发表时间:
    2024-09-23
  • 期刊:
  • 影响因子:
    1.500
  • 作者:
    Kristin Persson;Maria Andrée;Cecilia Caiman
  • 通讯作者:
    Cecilia Caiman
Down-to-earth ecological literacy through human and nonhuman encounters in fieldwork
通过实地考察中人类和非人类的接触,培养脚踏实地的生态素养

Kristin Persson的其他文献

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{{ truncateString('Kristin Persson', 18)}}的其他基金

SI2-SSI Collaborative Research: A Computational Materials Data and Design Environment
SI2-SSI 协作研究:计算材料数据和设计环境
  • 批准号:
    1147892
  • 财政年份:
    2012
  • 资助金额:
    $ 394.04万
  • 项目类别:
    Interagency Agreement

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