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Through a simulation-based study we develop a statistical model-based quantification method for atomic resolution first moment scanning transmission electron microscopy (STEM) images. This method uses the uniformly weighted least squares estimator to determine the unknown structure parameters of the images and to isolate contributions from individual atomic columns. In this way, a quantification of the projected potential per atomic column is achieved. Since the integrated projected potential of an atomic column scales linearly with the number of atoms it contains, it can serve as a basis for atom counting. The performance of atom counting from first moment STEM imaging is compared to that from traditional HAADF STEM in the presence of noise. Through this comparison, we demonstrate the advantage of first moment STEM images to attain more precise atom counts. Finally, we compare the integrated potential extracted from first-moment images of a wedge-shaped sample to those values from the bulk crystal. The excellent agreement found between these values proves the robustness of using bulk crystal simulations as a reference library. This enables atom counting for samples with different shapes by comparison with these library values., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The Bayesian genetic algorithm (BGA) is a powerful tool to reconstruct the 3D structure of mono-atomic single-crystalline metallic nanoparticles imaged using annular dark field scanning transmission electron microscopy. The number of atoms in a projected atomic column in the image is used as input to obtain an accurate and atomically precise reconstruction of the nanoparticle, taking prior knowledge and the finite precision of atom counting into account. However, as the number of parameters required to describe a nanoparticle with atomic detail rises quickly with the size of the studied particle, the computational costs of the BGA rise to prohibitively expensive levels. In this study, we investigate these computational costs and propose methods and control parameters for efficient application of the algorithm to nanoparticles of at least up to 10 nm in size., Competing Interests: Conflict of Interest. No competing interest is declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Microscopy Society of America. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid) and NMDA (N-methyl-d-aspartate) glutamate receptors are driving forces for synaptic transmission and plasticity at neocortical synapses. However, their distribution pattern in the adult rat neocortex is largely unknown and was quantified using freeze fracture replication combined with postimmunogold-labeling. Both receptors were co-localized at layer (L)4 and L5 postsynaptic densities (PSDs). At L4 dendritic shaft and spine PSDs, the number of gold grains detecting AMPA was similar, whereas at L5 shaft PSDs AMPA-receptors outnumbered those on spine PSDs. Their number was significantly higher at L5 vs. L4 PSDs. At L4 and L5 dendritic shaft PSDs, the number of gold grains detecting GluN1 was ~2-fold higher than at spine PSDs. The number of gold grains detecting the GluN1-subunit was higher for both shaft and spine PSDs in L5 vs. L4. Both receptors showed a large variability in L4 and L5. A high correlation between the number of gold grains and PSD size for both receptors and targets was observed. Both receptors were distributed over the entire PSD but showed a layer- and target-specific distribution pattern. The layer- and target-specific distribution of AMPA and GluN1 glutamate receptors partially contribute to the observed functional differences in synaptic transmission and plasticity in the neocortex., (© The Author(s) 2022. Published by Oxford University Press.)

A new methodology is presented to count the number of atoms in multimetallic nanocrystals by combining energy dispersive X-ray spectroscopy (EDX) and high angle annular dark field scanning transmission electron microscopy (HAADF STEM). For this purpose, the existence of a linear relationship between the incoherent HAADF STEM and EDX images is exploited. Next to the number of atoms for each element in the atomic columns, the method also allows quantification of the error in the obtained number of atoms, which is of importance given the noisy nature of the acquired EDX signals. Using experimental images of an Au@Ag core-shell nanorod, it is demonstrated that 3D structural information can be extracted at the atomic scale. Furthermore, simulated data of an Au@Pt core-shell nanorod show the prospect to characterize heterogeneous nanostructures with adjacent atomic numbers., (© 2022 Wiley-VCH GmbH.)

A decade ago, a statistics-based method was introduced to count the number of atoms from annular dark-field scanning transmission electron microscopy (ADF STEM) images. In the past years, this method was successfully applied to nanocrystals of arbitrary shape, size, and composition (and its high accuracy and precision has been demonstrated). However, the counting results obtained from this statistical framework are so far presented without a visualization of the actual uncertainty about this estimate. In this paper, we present three approaches that can be used to represent counting results together with their statistical error, and discuss which approach is most suited for further use based on simulations and an experimental ADF STEM image.

A small sample tilt away from a main zone axis orientation results in an elongation of the atomic columns in ADF STEM images. An often posed research question is therefore whether the ADF STEM image intensities of tilted nanomaterials should be quantified using a parametric imaging model consisting of elliptical rather than the currently used symmetrical peaks. To this purpose, simulated ADF STEM images corresponding to different amounts of sample tilt are studied using a parametric imaging model that consists of superimposed 2D elliptical Gaussian peaks on the one hand and symmetrical Gaussian peaks on the other hand. We investigate the quantification of structural parameters such as atomic column positions and scattering cross sections using both parametric imaging models. In this manner, we quantitatively study what can be gained from this elliptical model for quantitative ADF STEM, despite the increased parameter space and computational effort. Although a qualitative improvement can be achieved, no significant quantitative improvement in the estimated structure parameters is achieved by the elliptical model as compared to the symmetrical model. The decrease in scattering cross sections with increasing sample tilt is even identical for both types of parametric imaging models. This impedes direct comparison with zone axis image simulations. Nonetheless, we demonstrate how reliable atom-counting can still be achieved in the presence of small sample tilt., (Copyright © 2021 Elsevier B.V. All rights reserved.)

We present a quantitative method which allows us to reliably measure dynamic changes in the atomic structure of monatomic crystalline nanomaterials from a time series of atomic resolution annular dark field scanning transmission electron microscopy images. The approach is based on the so-called hidden Markov model and estimates the number of atoms in each atomic column of the nanomaterial in each frame of the time series. We discuss the origin of the improved performance for time series atom-counting as compared to the current state-of-the-art atom-counting procedures, and show that the so-called transition probabilities that describe the probability for an atomic column to lose or gain one or more atoms from frame to frame are particularly important. Using these transition probabilities, we show that the method can also be used to estimate the probability and cross section related to structural changes. Furthermore, we explore the possibilities for applying the method to time series recorded under variable environmental conditions. The method is shown to be promising for a reliable quantitative analysis of dynamic processes such as surface diffusion, adatom dynamics, beam effects, or in situ experiments., (Copyright © 2020 Elsevier B.V. All rights reserved.)

The cell entry mechanism of Autographa californica multiple nucleopolyhedrovirus (AcMNPV) is not fully understood. Previous studies showed that AcMNPV entered host cells primarily through clathrin-mediated endocytosis, and could efficiently infect cells via fusion with the plasma membrane after a low-pH trigger. However, whether AcMNPV enters cells via these two pathways simultaneously, and the exact manner in which AcMNPV particles are internalized into cells remains unclear. In this study, using single-virus tracking, we observed that AcMNPV particles were first captured by pre-existing clathrin-coated pits (CCP), and were then delivered to early endosomes. Population-based analysis of single-virus tracking and quantitative electron microscopy demonstrated that the majority of particles were captured by CCPs and internalized via invagination. In contrast, a minority of virus particles were not delivered to CCPs, and were internalized through direct fusion with the plasma membrane without invagination. Quantitative electron microscopy also showed that, while inhibition of CCP assembly significantly impaired viral internalization, inhibition of endosomal acidification blocked virus particles out of vesicles. Collectively, these findings demonstrated that approximately 90% of AcMNPV particles entered cells through clathrin-mediated endocytosis and 10% entered via direct fusion with the plasma membrane. This study will lead toward a better understanding of AcMNPV infection.

Studies over several decades on the organization of the CA1 hippocampus-a particularly favorable model for learning, memory and certain forms of cognition-have shown that the synaptic network in this brain region is plastic ( Fortin et al. , 2012 ). Recent evidence suggests that a number of environmental and endogenous stimuli may have a substantial effect on hippocampus-dependent cognitive function, implying enhanced synaptic plasticity in this brain region. Stimuli ( e.g. , food restriction, enriched environment, social interaction, gene-loss [knock-out animals], etc .) can trigger structural and functional plasticity ( e.g. , spine formation, increased expression of neurotrophic factors, synaptic function and neurogenesis) in the hippocampus ( Stewart et al. , 1989 ; Andrade et al. , 2002 ; Babits et al. , 2016 ). Using quantitative electron microscopy, we can study the synaptic neuropil of CA1 hippocampus in rodents during short- or long-term treatments and/or stimuli. Within the scope of this electron microscopic methodological construct, the density of various synaptic connections, the morphology and internal structure of excitatory spine synapses ( e.g. , the mean length and width of postsynaptic densities) can be quantified. Such quantitative ultrastructural measurement using high-resolution electron-microscopy may be applied to observe structural manifestations of synaptic plasticity in rodent brain tissue. The presented ultrastructural protocol may empower researchers to reveal details and synaptic changes which may not be obvious using only light microscopy. Ultrastructural data may provide substantial advances in our understanding of the changes in hippocampal synaptic architecture under different conditions., (Copyright © 2018 The Authors; exclusive licensee Bio-protocol LLC.)

Nowadays, aberration corrected transmission electron microscopy (TEM) is a popular method to characterise nanomaterials at the atomic scale. Here, atomically resolved images of nanomaterials are acquired, where the contrast depends on the illumination, imaging and detector conditions of the microscope. Visualization of light elements is possible when using low angle annular dark field (LAADF) STEM, annular bright field (ABF) STEM, integrated differential phase contrast (iDPC) STEM, negative spherical aberration imaging (NCSI) and imaging STEM (ISTEM). In this work, images of a NdGaO 3 -La 0.67 Sr 0.33 MnO 3 (NGO-LSMO) interface are quantitatively evaluated by using statistical parameter estimation theory. For imaging light elements, all techniques are providing reliable results, while the techniques based on interference contrast, NCSI and ISTEM, are less robust in terms of accuracy for extracting heavy column locations. In term of precision, sample drift and scan distortions mainly limits the STEM based techniques as compared to NCSI. Post processing techniques can, however, partially compensate for this. In order to provide an outlook to the future, simulated images of NGO, in which the unavoidable presence of Poisson noise is taken into account, are used to determine the ultimate precision. In this future counting noise limited scenario, NCSI and ISTEM imaging will provide more precise values as compared to the other techniques, which can be related to the mechanisms behind the image recording., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Aberration correction in scanning transmission electron microscopy (STEM) has greatly improved the lateral and depth resolution. When using depth sectioning, a technique during which a series of images is recorded at different defocus values, single impurity atoms can be visualised in three dimensions. In this paper, we investigate new possibilities emerging when combining depth sectioning and precise atom-counting in order to reconstruct nanosized particles in three dimensions. Although the depth resolution does not allow one to precisely locate each atom within an atomic column, it will be shown that the depth location of an atomic column as a whole can be measured precisely. In this manner, the morphology of a nanoparticle can be reconstructed in three dimensions. This will be demonstrated using simulations and experimental data of a gold nanorod., (Copyright © 2016 Elsevier B.V. All rights reserved.)

In this paper, we propose an algorithm to obtain a three-dimensional reconstruction of a single nanoparticle based on the method of atom counting. The location of atoms in three dimensions has been successfully performed using simulations of high-angle-annular-dark-field images from only three zone-axis projections, [110], [310] and [211], for a face-centred cubic particle. These three orientations are typically accessible by low-tilt holders often used in high-performance scanning transmission electron microscopes., (© 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.)

Recently, imaging scanning transmission electron microscopy (ISTEM) has been proposed as a promising new technique combining the advantages of conventional TEM (CTEM) and STEM (Rosenauer et al., 2014 [1]). The ability to visualize light and heavy elements together makes it a particularly interesting new, spatially incoherent imaging mode. Here, we evaluate this technique in term of precision with which atomic column locations can be measured. By using statistical parameter estimation theory, we will show that these locations can be accurately measured with a precision in the picometer range. Furthermore, a quantitative comparison is made with HAADF STEM imaging to investigate the advantages of ISTEM., (Copyright © 2016 Elsevier B.V. All rights reserved.)

An efficient model-based estimation algorithm is introduced to quantify the atomic column positions and intensities from atomic resolution (scanning) transmission electron microscopy ((S)TEM) images. This algorithm uses the least squares estimator on image segments containing individual columns fully accounting for overlap between neighbouring columns, enabling the analysis of a large field of view. For this algorithm, the accuracy and precision with which measurements for the atomic column positions and scattering cross-sections from annular dark field (ADF) STEM images can be estimated, has been investigated. The highest attainable precision is reached even for low dose images. Furthermore, the advantages of the model-based approach taking into account overlap between neighbouring columns are highlighted. This is done for the estimation of the distance between two neighbouring columns as a function of their distance and for the estimation of the scattering cross-section which is compared to the integrated intensity from a Voronoi cell. To provide end-users this well-established quantification method, a user friendly program, StatSTEM, is developed which is freely available under a GNU public license., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Precipitates and their associated strain fields significantly influence mechanical properties and, consequently, the industrial performance of aluminum alloys. In this work, we present a direct measurement of strains induced by η' and η precipitates in an Al-Zn-Mg-Cu alloy using aberration-corrected high-resolution transmission electron microscopy and quantitative strain analysis. The results demonstrate that the strain induced by precipitates in the Al-Zn-Mg-Cu alloy shows significant tensile strains perpendicular to the longitudinal direction of the precipitate discs on the side of the discs and along the longitudinal direction at both ends of the η' and η precipitates. This strain field can be described by an equivalent dislocation model, in which the lattice mismatch between the precipitate and the matrix is equivalent to a series of dislocation pairs along the precipitate/matrix interfaces., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Off-axis electron holography is a method for the transmission electron microscope (TEM) that measures the electric and magnetic properties of a specimen. The electrostatic and magnetic potentials modulate the electron wavefront phase. The error in measurement of the phase therefore determines the smallest observable changes in electric and magnetic properties. Here we explore the summation of a hologram series to reduce the phase error and thereby improve the sensitivity of electron holography. Summation of hologram series requires independent registration and correction of image drift and phase wavefront drift, the consequences of which are discussed. Optimization of the electro-optical configuration of the TEM for the double biprism configuration is examined. An analytical model of image and phase drift, composed of a combination of linear drift and Brownian random-walk, is derived and experimentally verified. The accuracy of image registration via cross-correlation and phase registration is characterized by simulated hologram series. The model of series summation errors allows the optimization of phase error as a function of exposure time and fringe carrier frequency for a target spatial resolution. An experimental example of hologram series summation is provided on WS2 fullerenes. A metric is provided to measure the object phase error from experimental results and compared to analytical predictions. The ultimate experimental object root-mean-square phase error is 0.006 rad (2π/1050) at a spatial resolution less than 0.615 nm and a total exposure time of 900 s. The ultimate phase error in vacuum adjacent to the specimen is 0.0037 rad (2π/1700). The analytical prediction of phase error differs with the experimental metrics by +7% inside the object and -5% in the vacuum, indicating that the model can provide reliable quantitative predictions., (Crown Copyright © 2014. Published by Elsevier B.V. All rights reserved.)