UK High-End Computing Consortium for X-ray Spectroscopy (HPC-CONEXS)
UK High-End Computing Consortium for X-ray Spectroscopy (HPC-CONEXS)
批准号:
EP/X035514/1
负责人:
Thomas Penfold
金额:
$47.38万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --
中文摘要
点击翻译按钮获取中文摘要
英文摘要
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. Since 2019, the COllaborative NEtwork for X-ray Spectroscopy (CONEXS, EP/S022058/1) has established a strong community of over 600 researchers in the area of X-ray spectroscopy, with a primary focus ofnurturing a strong synergy between experiment and theory. Through providing access to state-of-the-art computing facilities, the UK High-End Computing Consortium for X-ray Spectroscopy (HPC-CONEXS) will develop computational tools to advance the detailed analysis of experimental data. It will also provide resources and training for both experts and non-experts to further enhance the synergy between experiment and theory ensuring maximum impact from the UK's research and investment in this area.
期刊论文(7)
专著(0)
科研奖励(0)
会议论文
Uncertainty quantification of spectral predictions using deep neural networks.
使用深度神经网络对光谱预测的不确定性进行量化。
DOI:
10.1039/d3cc01988h
发表时间:
2023
期刊:
Chemical communications (Cambridge, England)
影响因子:
--
作者:
[Verma S]
通讯作者:
Verma S
Towards the automated extraction of structural information from X-ray absorption spectra
从 X 射线吸收光谱中自动提取结构信息
DOI:
10.1039/d3dd00101f
发表时间:
2023
期刊:
Digital Discovery
影响因子:
--
作者:
[David T]
通讯作者:
David T
Partial Density of States Representation for Accurate Deep Neural Network Predictions of X-ray Spectra
X 射线光谱精确深度神经网络预测的部分态密度表示
DOI:
10.26434/chemrxiv-2024-bbrgt
发表时间:
2024
期刊:
影响因子:
--
作者:
[Middleton C]
通讯作者:
Middleton C
Deep Neural Networks for Real-Time Spectroscopic Analysis
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批准号:EP/W008009/1
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项目类别:Fellowship
-
资助金额:$146.4万
-
财政年份:2022
-
负责人:Thomas Penfold
-
依托单位:
rISC - the game of strategic molecular design for high efficiency OLEDs
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批准号:EP/T022442/1
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项目类别:Research Grant
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资助金额:$44.77万
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财政年份:2020
-
负责人:Thomas Penfold
-
依托单位:
CONEXS: COllaborative NEtwork for X-ray Spectroscopy
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批准号:EP/S022058/1
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项目类别:Research Grant
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资助金额:$13.13万
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财政年份:2019
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负责人:Thomas Penfold
-
依托单位:
Understanding and Design Beyond Born-Oppenheimer using Time-Domain Vibrational Spectroscopy
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批准号:EP/P012388/1
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项目类别:Research Grant
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资助金额:$32.93万
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财政年份:2017
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负责人:Thomas Penfold
-
依托单位:
The Excited State Properties of Thermally Activated Delayed Fluorescence Emitters: A Computational Study Towards Molecular Design
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批准号:EP/N028511/1
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项目类别:Research Grant
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资助金额:$10.97万
-
财政年份:2016
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负责人:Thomas Penfold
-
依托单位:
国内基金
海外基金
真菌特异的内吞作用相关蛋白End3发挥作用的结构研究
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批准号:32000859
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项目类别:青年科学基金项目
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资助金额:24.0万元
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批准年份:2020
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负责人:王冬立
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依托单位:
从PBMC-β-END-μ-阿片受体途径探讨华蟾素治疗癌痛的外周机制
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批准号:81173612
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项目类别:面上项目
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资助金额:58.0万元
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批准年份:2011
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负责人:陈涛
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依托单位:
研究EB1(End-Binding protein 1)的癌基因特性及作用机制
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批准号:30672361
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项目类别:面上项目
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资助金额:24.0万元
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批准年份:2006
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负责人:徐宁志
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依托单位: