Suppr超能文献

具有亚皮米空间分辨率的超快扩展X射线吸收精细结构的结构分析:应用于自旋交叉配合物。

Structural analysis of ultrafast extended x-ray absorption fine structure with subpicometer spatial resolution: application to spin crossover complexes.

作者信息

Gawelda W, Pham V-T, van der Veen R M, Grolimund D, Abela R, Chergui M, Bressler C

机构信息

Ecole Polytechnique Fédérale de Lausanne, Laboratoire de Spectroscopie Ultrarapide, Institut des Sciences et Ingénierie Chimiques, CH-1015 Lausanne-Dorigny, Switzerland.

出版信息

J Chem Phys. 2009 Mar 28;130(12):124520. doi: 10.1063/1.3081884.

Abstract

We present a novel analysis of time-resolved extended x-ray absorption fine structure (EXAFS) spectra based on the fitting of the experimental transients obtained from optical pump/x-ray probe experiments. We apply it to the analysis of picosecond EXAFS data on aqueous Fe(II)(bpy)(3), which undergoes a light induced conversion from its low-spin (LS) ground state to the short-lived (tau approximately 650 ps) excited high-spin (HS) state. A series of EXAFS spectra were simulated for a collection of possible HS structures from which the ground state fit spectrum was subtracted to generate transient difference absorption (TA) spectra. These are then compared with the experimental TA spectrum using a least-squares statistical analysis to derive the structural change. This approach reduces the number of required parameters by cancellation in the differences. It also delivers a unique solution for both the fractional population and the extracted excited state structure. We thus obtain a value of the Fe-N bond elongation in the HS state with subpicometer precision (0.203+/-0.008 A).

摘要

我们基于对光泵浦/ X射线探测实验获得的实验瞬态进行拟合,提出了一种对时间分辨扩展X射线吸收精细结构(EXAFS)光谱的新颖分析方法。我们将其应用于对水溶液中[Fe(II)(bpy)(3)]²⁺的皮秒级EXAFS数据的分析,该物质经历了从其低自旋(LS)基态到短寿命(τ约650皮秒)激发高自旋(HS)态的光诱导转换。针对一系列可能的HS结构模拟了一系列EXAFS光谱,从中减去基态拟合光谱以生成瞬态差分吸收(TA)光谱。然后使用最小二乘统计分析将这些光谱与实验TA光谱进行比较,以得出结构变化。这种方法通过在差异中进行抵消来减少所需参数的数量。它还为分数布居和提取的激发态结构提供了唯一的解决方案。因此,我们以亚皮米精度(0.203±0.008 Å)获得了HS态下Fe-N键伸长的值。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验