Development of small-angle scattering pair distribution function analysis techniques and application to nanoparticles assemblies

Development of small-angle scattering pair distribution function analysis techniques and application to nanoparticles assemblies

by Chia-Hao Liu

About
With the improvement in synthesis method, a variety of nanoparticles (NPs) with nearly uniform distribution in size and morphology are now available to scientists. This progress opens a new opportunity of assembling these high quality nanoparticles into metamaterial - nanoparticle assemblies (NPAs). The properties of NPA depend on the interactions between constituent NPs, therefore NPA offer a distinct advantage in designing material properties that are not available in the bulk phase (crystal) or discrete phase (nanoparticle). Novel application of NPA in modern devices, such as solar cells and field effect transistors, had also been demonstrated. The spatial arrangements of NPs is the key factor to their interactions, therefore, it is crucial to characterize the structure of NPA quantitatively. The technique of diffraction plays an unique role for characterizing NPA structure, as it not only offers the structural type, which may also be obtained from imagine technique, but also yields structural information in three-dimension, such inter-particle distance and the range of structural coherence of the packing order. Traditionally, the diffraction analysis is based on crystallography and is carried out in reciprocal space. However, it has been known local structure is overlooked in this kind of crystallographic analysis, which places a challenge for have a comprehensive understanding of the NPA structure. The pair distribution function (PDF) analysis, which is powerful in probing local structures for atomic systems, serves as a promising tool for characterizing NPA structure. How- ever, the approach of using PDF analysis for NPA structure characterization has barely been explored. In this thesis, I will present the methodological developments of the PDF technique. Starting from presenting a machine-learning-assisted approach for predicting the space group of its structure from the PDF, I will be focusing on the aspect of accelerating the structure modeling steps with PDF. Next, the development of pair distribution function analysis in small-angle scattering domain sasPDF will be introduced, including software package PDFgetX3 which is aiming to facilitate the extraction of PDF from small-angle scattering data quickly. The approach of sasPDF is validated against three representative structures across different levels of structural order. Finally, the example of applying sasPDF method to identify the jamming transition signature in polymer-ligated NPA is introduced, followed by another example of discovering multiply-twinned structure from the reprogramming of DNA-ligated NPA.

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