Probing composition distributions in nanoalloy catalysts with correlative electron microscopy

Liu, Shikai; Gow, Isla; Davies, Thomas E.; Barnes, Alexandra; Sankar, Meenakshisundaram; Gong, Xiaoxiao; Howe, Alexander G. R.; Dixon, Michael L.; Hutchings, Graham J.; Kiely, Christopher J.; He, Qian

doi:10.1039/d0ta00334d

Cited by 5 publications

(2 citation statements)

References 45 publications

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“…[ 6,7 ] Excited atoms emit characteristic X‐rays at greater depths within the interaction volume compared to SE or BSE, hence the typical spatial resolution of EDS in SEM is around 1–2 μm. [ 8 ] The interaction volume is variable and depends on sample density, atomic number ( Z ), beam energy, and sample tilt, and it can be calculated by the Monte Carlo simulation. [ 9 ]…”

Section: Theorymentioning

confidence: 99%

Experimental methods in chemical engineering: Scanning electron microscopy andX‐ray ultra‐microscopy—SEMandXuM

Davies

Bessette

et al. 2022

Can J Chem Eng

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Scanning electron microscopy (SEM) produces images at 500 000 times magnification and better than 1 nm resolution to characterize inorganic and organic solid morphology, surface topography, and crystallography. An electron beam interacts with the material and generates secondary electrons (SE) and backscattered electrons (BSE) that detectors capture. Coupled with X-ray energydispersive spectroscopy (X-EDS), SEM-EDS identifies elemental composition. X-ray ultra-microscopy (XuM) traverses particles to identify phase changes and areas of high density and voids without slicing through the solids by microtome. Although SEM instrument capability continuously evolves with higher magnification and better resolution, desktop SEMs are becoming standard in laboratories that require frequent imaging and lower magnification. Hand-held cameras (800-1500Â) have the advantage of low cost, ease of use, and better colours. SEM depth of field is better than visible light microscopy, but image stacking software has narrowed the gap between the two. Modern user interfaces mean that today's SEM instruments are easier to operate and data acquisition is faster, but operators must be able to select the right technique for the application (e.g., SE vs. BSE). Furthermore, they must understand how operating parameters like probe current, accelerating voltage, spot-diameter, convergence angle, and working distance compromise sample integrity. The number of articles the Web of Science indexes that mention SEM has grown from 1000 in 1990 to over 40 000 in 2021. A bibliometric map identified four clusters of research: mechanical properties and microstructure; nanoparticles, composites, and graphene; antibacterial and green synthesis; and adsorption and wastewater.

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Section: Theorymentioning

confidence: 99%

Experimental methods in chemical engineering: Scanning electron microscopy andX‐ray ultra‐microscopy—SEMandXuM

Davies

Bessette

et al. 2022

Can J Chem Eng

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“…Quantitative evaluation of such local compositional variations/changes is therefore crucial for better understanding of the controlled synthesis parameters and structure−property relationship of the nanoalloys under realistic operating conditions. For instance, using a correlative electron microscopy approach, Liu et al 12 have recently provided statistical insights into the size-dependent composition variation for a binary Au−Pd nanoalloy.…”

Section: ■ Introductionmentioning

confidence: 99%

Statistical Evaluation of the Solid-Solution State in Ternary Nanoalloys

et al. 2020

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Quantitative evaluation of the alloying state in nanoalloy systems is key to understanding their functional properties in a diverse range of applications spanning from catalysis and plasmonics to biomedicine and so forth. Here, we develop a method to statistically and visually represent the sub-nanometer local compositional distribution in ternary nanoparticles (NPs) in terms of ternary histograms and kernel density estimation analysis. Further descriptive statistics is performed within the mathematical framework of compositional data analysis to account for the constant-sum constraint and positivity inherent to the nature of compositional data. The approach has been demonstrated on several conceptual particle models and real systems, namely, Pd–Rh–Ru and Ag–Au–Pd NPs, utilizing experimental X-ray energy-dispersive spectroscopy (XEDS) maps acquired from a scanning transmission electron microscope. We regard this as a useful tool for extending to other well-known configurations such as uniformly mixed solid solutions, core–shell, or phase-decomposed clusters often encountered in other nanoalloy systems. Proposed solutions to overcome common problems associated with NPs such as low X-ray counting and XEDS spectral overlapping are also presented and discussed.

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STEM imaging and spectroscopy studies of Au and Au-based catalysts

Yao

Kiely

2023

Encyclopedia of Nanomaterials

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Probing composition distributions in nanoalloy catalysts with correlative electron microscopy

Abstract: A correlative electron microscopy method is introduced to statistically composition distributions among particles in nanoalloy materials, a parameter that is largely overlooked before.

Cited by 5 publications

References 45 publications

Experimental methods in chemical engineering: Scanning electron microscopy andX‐ray ultra‐microscopy—SEMandXuM

Experimental methods in chemical engineering: Scanning electron microscopy andX‐ray ultra‐microscopy—SEMandXuM

Statistical Evaluation of the Solid-Solution State in Ternary Nanoalloys

STEM imaging and spectroscopy studies of Au and Au-based catalysts

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