Multicomponent Signal Unmixing from Nanoheterostructures: Overcoming the Traditional Challenges of Nanoscale X-ray Analysis via Machine Learning

Rossouw, David; Burdet, Pierre; Peña, Francisco de la; Ducati, Caterina; Knappett, Benjamin R.; Wheatley, Andrew E. H.; Midgley, Paul A.

doi:10.1021/acs.nanolett.5b00449

Cited by 54 publications

(41 citation statements)

References 23 publications

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“…A Pt:Fe composition of 85:15 (at%) was calculated. This composition lies within one standard deviation (3.3 at%) of the average FePt bimetallic seed composition measured previously (82.0:18.0 at% Pt:Fe) …”

Section: Resultssupporting

confidence: 85%

“…This consistency in the EDX and EELS decompositions, in addition to the general appearance of the component spectra, lent credence to their physical interpretation. Furthermore, the quantification of the EDX ICA core spectrum provided a bimetallic Pt:Fe composition which was in excellent agreement with composition measurements on the bare particle cores reported previously . If the spatially overlapping shell is not accounted for when quantifying the EDX spectra extracted from the core regions, conventional standardless Cliff–Lorimer quantification gives an iron–platinum atomic ratio of Pt:Fe = 61:39 at% in the core regions.…”

Section: Discussionsupporting

confidence: 85%

“…Having obtained what appear to be physically interpretable decompositions of the EDX and EELS spectrum images obtained simultaneously from the representative particle cluster, we now attempt to find the compositions of the bimetallic particle cores and the phase of the iron oxide shells by quantifying the unmixed component factors obtained by ICA. For the bimetallic cores, ICA has been recently used to successfully extract their composition . Here, we repeat the general methodology on these core–shell particles, which were produced in the same synthesis, but we now extend the quantification to both EDX and EELS datasets.…”

Section: Resultsmentioning

confidence: 99%

“…ICA has been applied to EDX and EELS spectrum images. More recently, the components of ICA have been used to find the composition of the bimetallic core in a core–shell nanoparticle system and the composition of gamma' precipitates in a nickel‐based superalloy . Here, we apply PCA and ICA methods to a dual EDX+EELS dataset, enabling the measurement of both core and shell compositions in core–shell heterostructures.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A New Method for Determining the Composition of Core–Shell Nanoparticles via Dual‐EDX+EELS Spectrum Imaging

Rossouw

Knappett

Wheatley

et al. 2016

Part & Part Syst Charact

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Simultaneously acquired microanalytical X‐ray and electron energy loss signals are obtained from a bimetallic core–shell nanoparticle system (FePt@Fe3O4). The signals are decomposed using independent component analysis and the extracted components are used to separately quantify the composition of the spatially overlapping core and shell phases in the nanoheterostructure. The utilization of the complementary strengths of energy dispersive X‐ray and electron energy‐loss spectroscopy microanalysis has enabled the quantification of both light and heavy elements in a single spectrum image acquisition.

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Section: Resultssupporting

confidence: 85%

Section: Discussionsupporting

confidence: 85%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A New Method for Determining the Composition of Core–Shell Nanoparticles via Dual‐EDX+EELS Spectrum Imaging

Rossouw

Knappett

Wheatley

et al. 2016

Part & Part Syst Charact

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“…Moreover,t his novel quantification procedure naturallys eparates different compounds withouti ntroducing operator bias, and is particularly effective in the presenceo fc omplex compounds, such as those developed during solution-based perovskite synthesisi np hotovoltaic devices. [25]…”

Section: Introductionmentioning

confidence: 99%

Elemental Mapping of Perovskite Solar Cells by Using Multivariate Analysis: An Insight into Degradation Processes

et al. 2016

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The technology of perovskite-based solar cells is evolving rapidly, reaching certified power conversion efficiency values now exceeding 20 %. One of the main drawbacks hindering progress in the field is the long-term stability of the cells: the mixed halide perovskites used in most devices are sensitive to humidity and degrade on a timescale varying from hours to weeks. The degradation mechanisms are poorly understood, but likely arise from combined physical and chemical modifications at the nanometer scale. The characterization of pristine and degraded materials is difficult owing to their complex chemical and physical structure and their relatively poor stability. In this work, we investigated the changes in local composition and morphology of a standard device after 2 months of air exposure in the dark, using scanning transmission electron microscopy (STEM) with nanometer resolution for imaging and analysis. Because of a state-of-the-art technique that combines STEM and energy dispersive X-ray spectroscopy (EDX), and the use of different decomposition algorithms for multivariate analysis, we highlighted the migration of elements across the interfaces between the layers comprising the device. We also noticed a morphological degradation of the hole-transporting layer (HTL), representing one of the main factors enabling the infiltration of moisture in the device, which results in reduced performance.

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Principle component analysis applied to high resolution cross sectional STEM imaging: Quantitative analysis of 2D heterostructures

Rooney¹,

Kozikov²,

Prestat³

et al. 2016

European Microscopy Congress 2016: Proceedings

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Monolayers of 2D transition metal dichalcogenides (TMDCs) provide excellent semiconducting counterparts to insulating hexagonal boron nitride (hBN) and conductive graphene.[1] Combining all three materials in a Van der Waals vertical heterostructure allows the electronic, photovoltaic and electroluminescent properties of the TMDCs to be studied.[2] Whilst transport and optoelectronic measurements can probe the properties of exotic charge carriers, and ARPES can map the bandstructure such systems, direct high resolution imaging of the buried interfaces is only possible via high resolution cross sectional (S)TEM imaging.[3] The nature of these van der Waals interfaces not only determines the carrier injection between components[4], but also affects the bandstructure of the device and its ultimate functionality[5]. Here we present a novel strategy to denoise high resolution HAADF STEM images of cross sections using principal component analysis (PCA).[6] Cross sections are fabricated in a dual‐beam FIB‐SEM instrument using the in situ lift‐out method and polished with low energy ions to achieve electron transparency.[7] Cross sections were imaged in high resolution HAADF STEM using a probe‐side aberration corrected FEI Titan G2 80–200 kV with an X‐FEG electron source. By treating each line profile perpendicular to the fringes as a signal, components associated with noise and scattering can be separated by their variance. Removing the noise components allows us to accurately determine the separation between dissimilar crystals at these unique interfaces. More widely, the approach developed here also has application in a variety of layered material systems.

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Multicomponent Signal Unmixing from Nanoheterostructures: Overcoming the Traditional Challenges of Nanoscale X-ray Analysis via Machine Learning

Cited by 54 publications

References 23 publications

A New Method for Determining the Composition of Core–Shell Nanoparticles via Dual‐EDX+EELS Spectrum Imaging

A New Method for Determining the Composition of Core–Shell Nanoparticles via Dual‐EDX+EELS Spectrum Imaging

Elemental Mapping of Perovskite Solar Cells by Using Multivariate Analysis: An Insight into Degradation Processes

Principle component analysis applied to high resolution cross sectional STEM imaging: Quantitative analysis of 2D heterostructures

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