CONEXS: COllaborative NEtwork for X-ray Spectroscopy
CONEXS:X 射线光谱协作网络
基本信息
- 批准号:EP/S022058/1
- 负责人:
- 金额:$ 13.13万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Research Grant
- 财政年份:2019
- 资助国家:英国
- 起止时间:2019 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Scientific breakthroughs are strongly associated with technological developments, which enable the measurement of matter to an increased level of detail. A prime example of this is the development of femtosecond lasers, which opened up the field of ultrafast spectroscopy. This had a huge impact on our understanding of chemical reactions, biological functions and phase transitions in materials owing to their ability to probe, in real-time, the nuclear motion within these different types of systems. A modern revolution is underway in X-ray science with the emergence of tools capable of delivering high-brilliance ultrashort pulses of X-rays. The UK, through the Diamond Light source, investment into the European X-FEL and world-leading research groups are at the forefront of these experimental endeavors. Crucially, the complicated nature and high information context of X-ray spectroscopic observables means that a strong synergy between experiment and theory is required. However, despite the development of new theoretical methods, the exploitation of the high level methods remains relatively uncommon resulting in the full potential of the experiments not being realised. This status-quo is unacceptable, and overcoming it is one of the primary objectives of the COllaborative NEtwork for X-ray Spectroscopy (CONEXS), which will bring together experimentalists and theoreticians working in this area to achieve new levels of understanding. From the perspective of the computational community, direct engagement with experimentalists can highlight theoretical challenges and act as a catalyst for the development of new methods. From the experimental community, direct engagement with theoreticians will provide expertise in the new theoretical developments providing new opportunities for data analysis.
科学突破与技术发展密切相关,技术发展使物质的测量更加详细。一个很好的例子是飞秒激光器的发展,它开辟了超快光谱学领域。这对我们理解材料中的化学反应、生物功能和相变产生了巨大影响,因为它们能够实时探测这些不同类型系统中的核运动。随着能够提供高亮度超短X射线脉冲的工具的出现,X射线科学正在进行一场现代革命。英国通过钻石光源、对欧洲X-FEL的投资和世界领先的研究小组处于这些实验努力的最前沿。至关重要的是,X射线光谱观测的复杂性质和高信息背景意味着需要实验和理论之间的强大协同作用。然而,尽管新的理论方法的发展,开发的高层次的方法仍然相对罕见,导致未实现的实验的全部潜力。这种现状是不可接受的,克服它是X射线光谱学合作网络(CONEXS)的主要目标之一,它将汇集在这一领域工作的实验学家和理论家,以实现新的理解水平。从计算社区的角度来看,与实验主义者的直接接触可以突出理论挑战,并作为新方法开发的催化剂。从实验社区,与理论家的直接接触将提供新的理论发展的专业知识,为数据分析提供新的机会。
项目成果
期刊论文数量(10)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
A deep neural network for valence-to-core X-ray emission spectroscopy
- DOI:10.1080/00268976.2022.2123406
- 发表时间:2022-09
- 期刊:
- 影响因子:1.7
- 作者:T. Penfold;C. Rankine
- 通讯作者:T. Penfold;C. Rankine
Ultrafast nonadiabatic dynamics probed by nitrogen K-edge absorption spectroscopy.
- DOI:10.1039/c9cp03019k
- 发表时间:2020-02
- 期刊:
- 影响因子:0
- 作者:T. Northey;J. Norell;A. Fouda;N. Besley;M. Odelius;Thomas J Penfold
- 通讯作者:T. Northey;J. Norell;A. Fouda;N. Besley;M. Odelius;Thomas J Penfold
The Role of Structural Representation in the Performance of a Deep Neural Network for X-ray Spectroscopy
- DOI:10.3390/molecules25112715
- 发表时间:2020-06
- 期刊:
- 影响因子:4.6
- 作者:Marwah M M Madkhali-Marwah-M-M-Madkhali-93008847;C. Rankine;T. Penfold
- 通讯作者:Marwah M M Madkhali-Marwah-M-M-Madkhali-93008847;C. Rankine;T. Penfold
On the analysis of X-ray absorption spectra for polyoxometallates
- DOI:10.1016/j.cplett.2021.138893
- 发表时间:2021-07-29
- 期刊:
- 影响因子:2.8
- 作者:Falbo, E.;Rankine, C. D.;Penfold, T. J.
- 通讯作者:Penfold, T. J.
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Thomas Penfold其他文献
Hydrostatic Pressure-Induced Spectral Variation of Reichardt’s Dye: A Polarity/Pressure Dual Indicator
Reichardt 染料静水压引起的光谱变化:极性/压力双指示器
- DOI:
10.1021/acsomega.9b03880 - 发表时间:
2020 - 期刊:
- 影响因子:4.1
- 作者:
Akihisa Miyagawa;Julien Eng;Tetsuo Okada;Yoshihisa Inoue;Thomas Penfold;Gaku Fukuhara - 通讯作者:
Gaku Fukuhara
Thomas Penfold的其他文献
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{{ truncateString('Thomas Penfold', 18)}}的其他基金
UK High-End Computing Consortium for X-ray Spectroscopy (HPC-CONEXS)
英国 X 射线光谱高端计算联盟 (HPC-CONEXS)
- 批准号:
EP/X035514/1 - 财政年份:2023
- 资助金额:
$ 13.13万 - 项目类别:
Research Grant
Deep Neural Networks for Real-Time Spectroscopic Analysis
用于实时光谱分析的深度神经网络
- 批准号:
EP/W008009/1 - 财政年份:2022
- 资助金额:
$ 13.13万 - 项目类别:
Fellowship
rISC - the game of strategic molecular design for high efficiency OLEDs
rISC - 高效率 OLED 战略分子设计游戏
- 批准号:
EP/T022442/1 - 财政年份:2020
- 资助金额:
$ 13.13万 - 项目类别:
Research Grant
Understanding and Design Beyond Born-Oppenheimer using Time-Domain Vibrational Spectroscopy
使用时域振动光谱学理解和设计超越玻恩-奥本海默的理论
- 批准号:
EP/P012388/1 - 财政年份:2017
- 资助金额:
$ 13.13万 - 项目类别:
Research Grant
The Excited State Properties of Thermally Activated Delayed Fluorescence Emitters: A Computational Study Towards Molecular Design
热激活延迟荧光发射体的激发态特性:分子设计的计算研究
- 批准号:
EP/N028511/1 - 财政年份:2016
- 资助金额:
$ 13.13万 - 项目类别:
Research Grant
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