Small-angle X-ray scattering simulations on a single Pt nanoparticle system: An analysis of structural characteristics

被引:0
|
作者
Chen, Jianyu [1 ]
Bi, Wenbo [1 ]
Zhang, Xingming [1 ]
Tang, Jianfeng [1 ]
Deng, Lei [1 ]
Wang, Liang [1 ,2 ]
机构
[1] Hunan Agr Univ, Sch Chem & Mat Sci, Changsha, Hunan 410128, Peoples R China
[2] Peac Inst Multiscale Sci, Chengdu 610207, Sichuan, Peoples R China
关键词
Small -angle X-ray scattering; Nanoparticles; IN-SITU; STRAIN; NANOALLOYS; PROTEINS; PROGRAM; SHAPE; SAXS; CU;
D O I
10.1016/j.commatsci.2023.112709
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Small-angle X-ray scattering (SAXS) is an operando structure characterization tool that is unique in its ability to detect diverse nano-particulate materials. Guinier approximation and form factor can efficiently extract statistically meaningful structure information such as size and morphology from SAXS data. Herein, by employing a simulation of scattering intensities via a lattice-atoms-based code, we demonstrate quantitative correlation be-tween SAXS data and the structural characteristics in real space for single Pt nanoparticle with different size and structure motifs. It is shown that, for particles with varied morphologies, the symmetry of 2D patterns strongly depend on the orientation of facets. However, the oscillation in frequencies and amplitudes of 1D profile, the azimuthally averaged and integrated 2D patterns, are not so sensitive to structure motifs. Regardless of particle shapes, the discrepancy between the actual particle sizes and evaluated values from 1D profile, obtained by utilizing the form factors or Guinier approximation, are pretty small. Such discrepancy is more apparent for smaller particles, attributed to strong size-dependence of surface constitution, especially for spheres. By conducting a detailed analysis of the correlation between real-space and reciprocal-space lattice information, this work highlights the continuous-to-discrete transition of nano-objects and paves the way to accurately deter-mining structural features from SAXS data.
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页数:12
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