bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantitative measurement of doping and surface charge in a
ZnO
nanowire using in‐situ biasing and off‐axis electron holography
Authors: den Hertog Martien , Donatini Fabrice , McLeod Robert , Monroy Eva , Pernot Julien 
Published: December 2016

Semiconducting nanowires (NWs) are widely studied because the properties that stem from their three‐dimensional, nanoscale nature open new opportunities for device design. In particular ZnO NWs are widely studied for their interesting piezoelectronic properties. Though NWs can be readily grown today with increased carrier concentration due to doping, the measurement of the doping concentration at the nm scale remains challenging.
We demonstrate that state‐of‐the‐art off‐axis electron holography in combination with electrical in‐situ biasing can be used to detect active dopants and surface charges quantitatively in ZnO nanowires. The outline of the contacted NW is described in Fig. 1. We have acquired series of holograms and averaged the phase to increase signal to noise but avoid blurring due to specimen drift. The 0V bias images were used to remove contrast not related to the varying electrostatic potential and to verify the nanowire was not electrically modified during the experiment. We analyzed the depletion width in the nanowire due to an applied reverse bias to a Schottky contact on the nanowire, using a fit to the data.

Comparison of the experimental data with 3D simulations that were similarly treated indicates an
n
‐type doping level of 1x10
18
at. cm
−3
and a negative surface charge around −2.5x10
12
charges cm
−2
. Fig. 2a shows the experimental vacuum corrected phase profiles converted to potential, and a fit to the data. The extracted depletion width is indicated with a cross. The inset shows the location of the phase profile in the NW core and two symmetrically defined phase profiles obtained in vacuum on either side of the NW. The average signal in vacuum was subtracted from the NW signal and the remaining phase signal was converted to potential using a thickness of 75 nm, much smaller than the 150 nm NW diameter. In Fig. 2b the experimental and simulated depletion length is compared for 3D simulations including varying doping and surface charge quantities. We expect that the real doping is between 1 and 2x10
18
at. cm
−3
by comparison of experiment and simulation. The surface charge results in a surface depletion to a depth of 36 nm. We found an active/undepleted core thickness of 70–75 nm, providing excellent agreement between the simulated thickness of the undepleted core and the active thickness observed in the experimental data.

Off‐axis electron holography thus offers unique capabilities for quantitative analysis of active dopant concentrations and surface charges in nanostructures with nanometer‐scale spatial resolution.
Rotavirus double and triple layered viral particles: correlative characterization using electron microscopy, disc centrifuge and capillary electrophoresis
Authors: Miseur Agnes , Coppens Astrid , Chapelle Céline , Hens Christine , Blain Philippe , Delpierre Ghislain , Deschuyteneer Michel 
Published: December 2016

Rotavirus (Reoviridae) viral particles consist of capsids with 3 concentric protein layers surrounding the virus genetic material. The outer layer is composed of the VP4 and VP7 proteins, which independently elicit neutralizing antibodies and induce protective immunity.
Rotarix™, GSK live attenuated Rotavirus vaccine, was characterized by EM. The observations show that the vaccine contains both triple‐layered particles (TLPs) containing all 3 protein layers and double‐layered particles (DLPs) which lack the outer capsid proteins VP4 and VP7.

As DLPs are non‐infectious, it may be of importance to address the question of their abundance
vs
. TLPs in bulk preparations. Although such information can be obtained by EM, the method is relatively impractical for this purpose, particularly for routine analysis, as high number of particles should be observed and sized to get accurate relative abundances.

To determine the size and quantify the relative abundance of TLPs and DLPs on large populations of viral particles in bulk preparations, two size‐based, orthogonal analytical techniques were applied to detect these particles: disc centrifuge (DC) and capillary electrophoresis (CE).
To confirm the capacity of both methods to distinguish clearly the two types of capsids, TLPs and DLPs were partially purified using CsCL gradient. They were characterized by EM negative staining (Fig. 1) and cryo‐TEM (Fig. 2). Their apparent diameter difference of about 10 nm was well correlated in both techniques. The profiles obtained by DC and CE (Fig. 3) show the well‐resolved identification.

In addition, further confirmation was obtained by incubation of the preparations with EDTA, to remove the calcium required for VP7 protein stabilisation and thus to convert TLPs into DLPs [
1
]. The shift from TLPs to DLPs is clearly visible with CE (not shown), DC and also EM (Fig. 4).

Dynamic Light Scattering (DLS) was also evaluated and works fine with the partially purified samples of either TLPs or DLPs. The shift from TLPs to DLPs by this method is clearly observable as well (not shown). However, DLS does not allow distinguishing clearly the two populations of capsids in real samples with mixed TLPs and DLPs.
These orthogonal structural and sizing analysis methods can therefore be combined to assess and measure accurately DLPs/TLPs ratio. They thus provide a tool to understand the possible link of this ratio with the immunological potency of vaccine preparations.
Intracellular Organization in Cochlear Inner Hair Cells by
3D
Electron Microscopy
Authors: Fleck Roland , Vizay‐Barrena Gema , Bullen Anewn 
Published: December 2016

The ways in which cell architecture is modelled to meet cell function is a poorly understood facet of cell biology. However, the compartmentalization of mutually exclusive reactions in different regions of cells by membrane‐enclosed organelles or by self‐assembling macromolecular complexes is a basic mechanism of life. Fluorescent tags can display proteins confined to compartments in living cells, but provides no glimpse of the underlying ultrastructure. The electron microscope has the resolution to display cellular ultrastructure. Transmission electron microscopy (TEM) tomography of thin slices (~100‐300nm depth) can reveal complex subcellular cellular ultrastructure. Serial Block Face Scanning Electron Microscopy (SBFSEM) can provide ultrastructural resolution throughout a much longer (μm to mm) sample depth, enabling quantitative analysis of ultrastructural features throughout the length of most complex cells.
We have studied the cytoarchitecture of a cell with highly specialised organisation, the cochlear inner hair cell (IHC), using multiple hierarchies of 3D electron microscopy analyses. We have shown that synaptic terminal distribution on the IHC surface correlates with cell shape, and the distribution of a highly organised network of membranes and mitochondria encompassing the infranuclear region of the cell. Structural linkages between organelles that underlie this organisation were identified by high resolution imaging. Together these techniques have the potential for clarifying functionally specialised cytoarchitecture of other cell types. Strategies employed to improve data quality will be discussed.
Accurate and fast electron microscopy simulations using the open source
MULTEM
program
Authors: Lobato Ivan , Van Aert Sandra , Verbeeck Johan 
Published: December 2016

The most practical method for TEM image simulations is the multislice method, which is known to be an accurate numerical procedure for solving the quantum mechanical electron‐specimen interaction. Although most simulation codes treat the scattering process as purely elastic and coherent, inelastic scattering cannot be neglected and it has to be included in realistic simulations. Inelastic phonon scattering is often incorporated by using the frozen phonon model [1, 2] and the electronic excitations by using the density matrix approach [3, 4]. Nowadays, new computer technologies allow us to perform large TEM calculations with inclusion of accurate approximations of the electron‐specimen interaction in an acceptable amount of time.
A general overview of the MULTEM program along with a number of examples has been reported in [5]. In this work we present a new version of the open source MULTEM program, which adds key features including a graphical user interface, tapering truncation of the atomic potential, CPU multithreading, single/double precision calculations, STEM simulations using experimental detector sensitivities, ISTEM simulations, EFTEM simulations, STEM‐EELS simulations along with other improvements in the algorithms. A screenshot of the user interface is shown in Fig. 1. This figure shows the main available options of the program. In Fig. 2, a simulated HRTEM image and ED pattern of an isolated gold nanoparticle of 21127 atoms are shown. In these simulations, plane‐wave illumination is assumed with the following electron microscope setting: acceleration voltage (300 keV), spherical aberration (0.002 mm), defocus (19.8 Å), defocus spread (30 Å) and beam divergence angle (0.1 mrad). A numerical real space grid of 4096x4096 pixels has been used. The frozen atom simulation is performed by using the Einstein model with 200 configurations, slice thickness of 0.5Å and the three‐dimensional rms displacements of all the atoms are set to 0.085Å. For the HRTEM simulation, the spatial and temporal incoherences are included by applying the partially coherent microscope transfer function to each exit wave of the frozen atom. A multislice simulation of each frozen atom configuration only took 2.6 s on a Nvidia GeForce GTX TITAN GPU card.

The MULTEM's C++ classes, Matlab mex functions and the GUI are available in the GitHub repository
https://github.com/Ivanlh20/MULTEM
.
Combined EELS‐EDX analysis of nanoscale memristive NbOx and AlOx layers
Authors: Strobel Julian , Hansen Mirko , Haberfehlner Georg , Kothleitner Gerald , Ziegler Martin , Kohlstedt Hermann , Kienle Lorenz 
Published: December 2016

Memristive devices – electronic components that can change their resistance depending on their history of operation – offer a new approach in various fields of digital computing. [1] This advancement in information technology is being pursued in order to satisfy the ever increasing need for computing power on the one hand and to enable the imitation of neuronal networks like the hippocampus on the other. The conductive properties in memristive devices are typically governed by atomistic effects like cation or anion movement: the change of resistance state is dependent on the nanoscopic layout. The mechanisms, however, behind a non‐binary, remanent, reversible and repeatable change of electrical resistance are not well understood. In this work we present the results of dedicated transmission electron microscopy (TEM) analysis involving highly precise electron energy loss spectroscopy (EELS) methods in a complex oxide multilayer stack of only about ten nanometer total thickness. The layer sequence Nb/Al/Al
2
O
3
/Nb
x
O
y
/Au (from bottom to top; Fig. 1 a) was deposited onto a Si/SiO
2
substrate. The memristive properties of such junctions were recently investigated. [2]

Combined energy dispersive X‐ray spectroscopy (EDX) and EELS experiments allow for analyses of both light and heavy metals as well as the reliable detection of oxygen. In contrast to the deposited layer sequence we observe an entire oxidation of the metallic Al and even a partial oxidation of the Nb bottom electrode. (Fig. 1 b) and Fig. 2) Furthermore, the results imply the abundant presence of oxygen vacancies apparent from the O K‐peak in the spectrum of the amorphous Al oxide layer which acts as a tunnel barrier. (Fig. 1 c) These puzzling results will be discussed in the framework of former studies on the Nb‐Al overlayer technique. [3]
Different conduction mechanisms are being discussed based on the findings and an outlook onto further research by electronic structure calculation is given. The results shed light on the fundamentals of tunnel barrier‐based memristive devices which are compatible to state‐of‐the‐art CMOS technology and were already built into integrated circuits.
SAMF
ire ‐ a smart adaptive fitting algorithm for multi‐dimensional microscopy
Authors: Ostaševičius Tomas , de la Peña Francisco , Midgley Paul 
Published: December 2016

The large amounts of high‐quality “multi‐dimensional” data generated by modern microscopes open new avenues for quantitative nano‐characterization. Quantitative analysis of spectra and images often involve fitting a model to experimental data and, indeed, the literature is rich in applications; examples include atom counting [1], time resolved microscopy [2], electron energy loss [3] and cathodoluminescence [4] spectroscopy. However, using conventional methods to fit large datasets is challenging and when applied to multi‐dimensional models, they may become ill‐suited. The dominant and most common problem is that conventional methods struggle with any non‐linearity in the model and often require an estimate of the starting parameters that are close to the true values. Here we present a Smart Adaptive Multi‐dimensional Fitting algorithm (SAMFire) designed to ease the task of fitting such data by automatically generating best estimates for the parameters as the fitting progresses. SAMFire can fit multi‐dimensional spectra, images and data of higher dimensionality and will be available in open‐source software package HyperSpy v1.0.0 [5].
SAMFire enables quantitative analysis of large multi‐dimensional datasets that would be very challenging—if not impossible—to analyse by other means. It provides multiple fitting strategies that consist of pixel selection and parameter estimation, each tailored to different data structures. Example pixel selection orders are shown in Figure 1(a) for conventional fitting algorithms and in Figure 1(b) for one of the SAMFire strategies. The “raster” order is only viable for unusually stable and constrained models. In contrast, SAMFire follows the “path of least resistance”, learned from already fitted parts of the data and hence is applicable to a much broader range of problems.
As an example of a complex electron microscopy data analysis problem that can be easily addressed with SAMFire, Figure 2 shows a single spectrum and the result of EELS elemental and bonding quantification by curve fitting from a tilt‐series of spectrum‐images of a mixed phase nanoparticle. The model consists of eleven components to accurately describe the five elements and a background. Due to the complexity of the model, the geometry of the particle and the low signal‐to‐noise‐ratio, the outcome of fitting individual pixels was highly dependent on the starting parameters, making the analysis very challenging using conventional fitting routines. In contrast, SAMFire was able to fit the whole tilt‐series with minimal user input.
Since SAMFire enables highly sophisticated models to be fitted to large multi‐dimensional datasets significantly faster and more easily than previous algorithms, we anticipate it will become standard analysis practice, especially when quantitative analysis is required. Examples that we are currently considering include tracking motion in a time series and quantification of both light and trace elements in multiple‐domain structures.
Direct detection and electron counting ‐ A beginning of a new era for electron microscopy
Authors: Pan Ming 
Published: December 2016

Over the last decade, great progress has been made in the instrumentation of transmission electron microscopy (TEM) through the introduction of aberration correctors, electron energy monochromators, and a wide variety of TEM specimen holders designed for in‐situ applications. With these new capabilities, a wealth of advanced experimental data can be easily generated by advanced TEM systems. However, the development of a revolutionary image capture device has been lacking; this effectively makes imaging detectors the main bottleneck when striving to achieve the full potential performance of an advanced TEM.
Traditional image detectors use scintillator and optical transfer path (fiber‐coupling or lens) to convert high energy electrons to photons that are subsequently transferred to the imaging sensor to form an image. One of the disadvantages of this indirect detection approach is the loss of image resolution and sensitivity during the electron‐photon conversion and the photon transfer as additional noise sources that significantly degrade the signal‐to‐noise ratio (SNR) of the image detector.
Very recently direct detection imaging devices have been successfully developed based on technology advancement made in CMOS (complementary metal oxide semiconductor) design and manufacturing, high speed data architectures, vastly increased memory densities and speed, etc. The elimination of scintillator and subsequent optical transfer path has significantly improved the detective quantum efficiency (DQE) – a critical measure of SNR for resolution and sensitivity of an imaging device. The state‐of‐the‐art direct detection imaging device further boosts the DQE and image quality under extremely low beam conditions by electron counting at high speed (e.g. 400 fps @ 4k x 4k resolution) to eliminate the sensor readout noise and minimize the electron scattering noise. Figure 1 shows the comparison of DQE measurement at 300 kV for K2 direct detection cameras operated in electron counting (solid blue) and linear (dotted blue) mode, and scintillator/fiber optical coupled cameras (purple). It is clear that electron counting has significantly restored the DQE performance of direct detection cameras for all frequencies.

This new generation of direct detection imaging device has revolutionized the field of cryo‐electron microscopy (cryoEM) in structural biology and is starting to impact many applications in electron microscopy of materials science, for example,
in‐situ
microscopy, 4D STEM, imaging beam sensitive materials, quantitative measurement of radiation damage or quantitative electron microscopy, etc. Direct detection and electron counting are poised to advance electron microscopy into a new era.
New Opportunities in multi‐frame
STEM
Spectroscopy & Fractional Beam‐current
EELS
Authors: Jones Lewys , Varambhia Aakash , Kepaptsoglou Demie , Ramasse Quentin , Freer Robert , Azough Feridoon , Lozano‐Perez Sergio , Beanland Richard , Nellist Peter 
Published: December 2016

Electron energy‐loss spectroscopy (EELS) and energy‐dispersive x‐ray spectroscopy (EDX) are two of the most common means of chemical analysis in the scanning transmission electron microscope (STEM). While the instrumentation hardware has progressed markedly in recent years, the way that microscopists operate these spectrometers has changed very little. In general small areas are scanned just using coarse pixilation, slow scan‐speeds and high beam‐currents. Finally, once acquired these chemical signals are usually expressed in only relative or arbitrary units. This stands in stark contrast with modern best‐practice in STEM imaging, where wider fields of view are surveyed utilising multi‐frame acquisitions, faster scan speeds, finer pixel sampling and lower electron doses. More recently it has also become common place to express STEM image data in units of fractional‐beam‐current facilitating direct comparison with simulation.
We will present EELS and EDX results where best‐practice techniques from STEM imaging have been repurposed to improve chemical map quality. Multi‐frame spectrum‐image data were recorded with simultaneous EELS and EDX spectra, before using non‐rigid data registration [1] in the spatial domain, Figure 1. This not only reduces scan‐distortion but also unlocks tools such as; digital super‐resolution, strain mapping performed directly on chemical maps, and the digital accumulation of weak signals such as those from monochromated EELS. We also present an ‘equal fixed‐dose’ fractionation study where sample damage was reduced drastically using a fast‐scanning multi frame approach compared with its single scan equivalent.
EELS spectrum data fidelity was improved by energy‐drift tracking and correction [2,3]. After this, the limiting performance in multi‐frame spectra becomes the spectral‐noise and was found to depend strongly on the quality of the available dark‐reference, Figure 2. To mitigate this artefact, separate dark‐references and full‐beam gain‐references were recorded along with wholly un‐processed experimental spectra. Further improvement in the noise performance was released by stepping the EELS spectra in energy between each scan before un‐stepping them in post‐processing [4]. Dark‐correction was performed offline before dividing by the gain‐reference to finally express the EELS spectra in terms of fractional beam current [5].
It is expected that leveraging all these individually small improvements collectively will deliver more precise chemical maps while minimising sample damage and experimental time overheads.
Defect Investigation by Atomic‐Resolution
STEM
of
III
‐V Horizontal Nanowires grown via Template‐Assisted Selective area Epitaxy
Authors: Bologna Nicolas , Knoedler Moritz , Borg Mattias , Cutaia Davide , Erni Rolf , Riel Heike , Marta Rossel D. 
Published: December 2016

Scaling of silicon microelectronics is reaching fundamental physical limitations related in particular to the power consumption. A possible solution is represented by III‐V semiconductors integrated on Si which have much higher electron mobility and injection velocity. The possibility to grow III‐V nan‐owires allows also the creation of new transistor concepts for Tunnel Field‐Effect Transistors [1], which could lead to an increase in the efficiency of the circuits by reducing the supply voltage and thus the power consumption.
The growth of III‐V nanowires by Template Assisted Selective Epitaxy (TASE) (Fig. 1a) [2] has enabled the direct integration of heterostructures on Si (100) for TFET applications. The performance of the de‐vice may however be affected by the presence of defects (twins, dislocations, stacking faults, anti‐phase boundaries) along the nanowire since every single discontinuity in the crystal can lead to a mod‐ification in the electrical properties of the material. The understanding, control and suppression of such defects have always been a very challenging task and a crucial point to obtain well performing devices.
Here, we report the investigation of different III‐V compounds, by means of atomic‐resolution STEM, starting from GaAs homostructures to InAs‐GaSb heterostructures (Fig.1b), allowing detailed charac‐terization of defects, strains and compositions. We make use of the large degree of freedom of growth parameters in the TASE technique (temperature, V/III ratio, molar flux of precursors) to prepare nan‐owire samples (Fig.1b) with the aim to find the right parameters combination to reduce the defects density. Our analysis confirms a process‐dependent defect density in nanowires and shows that de‐fect‐free nanowires can be indeed obtained by optimizing the growth conditions (Fig.2).