Abstract: Electron ptychography provides highly sensitive, dose efficient phase images which can be corrected for aberrations after the data has been acquired. This is crucial when very precise quantification is required, such as with sensitivity to charge transfer due to bonding. Drift can now be essentially eliminated as a major impediment to focused probe ptychography, which benefits from the availability of easily interpretable simultaneous Z-contrast imaging. However challenges have remained when quantifying the ptychographic phases of atomic sites. The phase response of a single atom has a negative halo which can cause atoms to reduce in phase when brought closer together. When unaccounted for, as in integrating methods of quantification, this effect can completely obscure the effects of charge transfer. Here we provide a new method of quantification that overcomes this challenge, at least for 2D materials, and is robust to experimental parameters such as noise, sample tilt.

Abstract: We report a study of scattering dynamics in crystals employing momentum-resolved scanning transmission
electron microscopy under varying illumination conditions. As we perform successive changes of the probe
focus, multiple real-space signals are obtained in dependence of the shape of the incident electron wave.
With support from extensive simulations, each signal is shown to be characterised by an optimum focus for
which the contrast is maximum and which differs among different signals. For instance, a systematic focus
mismatch is found between images formed by high-angle scattering, being sensitive to thickness and chemical
composition, and the first moment in diffraction space, being sensitive to electric fields. It follows that a single
recording at one specific probe focus is usually insufficient to characterise materials comprehensively. Most
importantly, we demonstrate in experiment and simulation that the second moment (

Abstract: In this second part of a series we attempt to construct an empirical model that can mimick all experimental observations made regarding the role of an alternative interleaved scan pattern in STEM imaging on the beam damage in a specific zeolite sample. We make use of a 2D diffusion model that describes the dissipation of the deposited beam energy in the sequence of probe positions that are visited during the scan pattern. The diffusion process allows for the concept of trying to ‘outrun’ the beam damage by carefully tuning the dwell time and distance between consecutively visited probe positions. We add a non linear function to include a threshold effect and evaluate the accumulated damage in each part of the image as a function of scan pattern details. Together, these ingredients are able to describe qualitatively all aspects of the experimental data and provide us with a model that could guide a further optimisation towards even lower beam damage without lowering the applied electron dose. We deliberately remain vague on what is diffusing here which avoids introducing too many sample specific details. This provides hope that the model can be applied also in sample classes that were not yet studied in such great detail by adjusting higher level parameters: a sample dependent diffusion constant and damage threshold.

Abstract: This paper investigates the possible benefits for counting atoms of different chemical nature when analysing multiple 2D scanning transmission electron microscopy (STEM) images resulting from independent annular dark field (ADF) detector regimes. To reach this goal, the principles of statistical detection theory are used to quantify the probability of error when determining the number of atoms in atomic columns consisting of multiple types of elements. In order to apply this theory, atom-counting is formulated as a statistical hypothesis test, where each hypothesis corresponds to a specific number of atoms of each atom type in an atomic column. The probability of error, which is limited by the unavoidable presence of electron counting noise, can then be computed from scattering-cross sections extracted from multiple ADF STEM images. Minimisation of the probability of error as a function of the inner and outer angles of a specified number of independent ADF collection regimes results in optimal experimental designs. Based on simulations of spherical Au@Ag and Au@Pt core–shell nanoparticles, we investigate how the combination of two non-overlapping detector regimes helps to improve the probability of error when unscrambling two types of atoms. In particular, the combination of a narrow low angle ADF detector with a detector formed by the remaining annular collection regime is found to be optimal. The benefit is more significant if the atomic number Z difference becomes larger. In
addition, we show the benefit of subdividing the detector regime into three collection areas for heterogeneous nanostructures based on a structure consisting of three types of elements, e.g., a mixture of Au, Ag and Al atoms. Finally, these results are compared with the probability of error resulting when one would ultimately use a pixelated 4D STEM detector and how this could help to further reduce the incident electron dose.

Abstract: Advanced materials often consist of multiple elements which are arranged in a complicated structure. Quantitative scanning transmission electron microscopy is useful to determine the composition and thickness of nanostructures at the atomic scale. However, significant difficulties remain to quantify mixed columns by comparing the resulting atomic resolution images and spectroscopy data with multislice simulations where dynamic scattering needs to be taken into account. The combination of the computationally intensive nature of these simulations and the enormous amount of possible mixed column configurations for a given composition indeed severely hamper the quantification process. To overcome these challenges, we here report the development of an incoherent non-linear method for the fast prediction of ADF-EDX scattering cross-sections of mixed columns under channelling conditions. We first explain the origin of the ADF and EDX incoherence from scattering physics suggesting a linear dependence between those two signals in the case of a high-angle ADF detector. Taking EDX as a perfect incoherent reference mode, we quantitatively examine the ADF longitudinal incoherence under different microscope conditions using multislice simulations. Based on incoherent imaging, the atomic lensing model previously developed for ADF is now expanded to EDX, which yields ADF-EDX scattering cross-section predictions in good agreement with multislice simulations for mixed columns in a core–shell nanoparticle and a high entropy alloy. The fast and accurate prediction of ADF-EDX scattering cross-sections opens up new opportunities to explore the wide range of ordering possibilities of heterogeneous materials with multiple elements.

Abstract: Hybrid pixel direct electron detectors are gaining popularity in electron microscopy due to their excellent properties. Some commercial cameras based on this technology are relatively affordable which makes them attractive tools for experimentation especially in combination with an SEM setup. To support this, a detector characterization (Modulation Transfer Function, Detective Quantum Efficiency) of an Advacam Minipix and Advacam Advapix detector in the 15–30 keV range was made. In the current work we present images of Point Spread Function, plots of MTF/DQE curves and values of DQE(0) for these detectors. At low beam currents, the silicon detector layer behaviour should be dominant, which could make these findings transferable to any other available detector based on either Medipix2, Timepix or Timepix3 provided the same detector layer is used.

Abstract: In this paper convexity constraints are derived for a background model of electron energy loss spectra (EELS) that is linear in the fitting parameters. The model outperforms a power-law both on experimental and simulated backgrounds, especially for wide energy ranges, and thus improves elemental quantification results. Owing to the model’s linearity, the constraints can be imposed through fitting by quadratic programming. This has important advantages over conventional nonlinear power-law fitting such as high speed and a guaranteed unique solution without need for initial parameters. As such, the need for user input is significantly reduced, which is essential for unsupervised treatment of large datasets. This is demonstrated on a demanding spectrum image of a semiconductor device sample with a high number of elements over a wide energy range.

Abstract: Lignin removal plays a crucial role in the efficient bioconversion of lignocellulose to fermentable sugars. As a delignification process, fungal pretreatment has gained great interest due to its environmental friendliness and low energy consumption. In our previous study, a positive linear correlation between acid-insoluble lignin degradation and the achievable enzymatic saccharification yield has been found, hereby highlighting the importance of the close follow-up of lignin degradation during the solid-state fungal pretreatment process. However, the standard quantification of lignin, which relies on the two-step acid hydrolysis of the biomass, is highly laborious and time-consuming. Vibrational spectroscopy has been proven as a fast and easy alternative; however, it has not been extensively researched on lignocellulose subjected to solid-state fungal pretreatment. Therefore, the present study examined the suitability of near-infrared spectroscopy (NIR) for the rapid and easy assessment of lignin content in poplar wood pretreated with Phanerochaete chrysosporium. Furthermore, the predictive power of the obtained calibration model and the recently published ATR-FTIR spectroscopy-based model were compared for the first time using the same fungus-treated wood data set. PLSR was used to correlate the NIR spectra to the acid-insoluble lignin contents (19.9%-27.1%) of pretreated wood. After normalization and second derivation, a PLSR model with a good coefficient of determination (RCV2 = 0.89) and a low root mean square error (RMSECV = 0.55%) were obtained despite the heterogeneous nature of the fungal solid-state fermentation. The performance of this PLSR model was comparably good to the one obtained by ATR-FTIR (RCV2 = 0.87) while it required more extensive spectral pre-processing. In conclusion, both methods will be highly useful for the high-throughput and user-friendly monitoring of lignin degradation in a solid-state fungal pretreatment-based biorefinery concept.

Abstract: The development of compact, low power, charge-neutral propulsion sources is of significant recent interest due to the rising application of micro-scale satellite platforms. Among such sources, radio frequency (rf) electrothermal microthrusters present an attractive option due to their scalability, reliability, and tunable control of power coupling to the propellant. For micropropulsion applications, where available power is limited, it is of particular importance to understand how electrical power can be transferred to the propellant efficiently, a process that is underpinned by the plasma sheath dynamics. In this work, two-dimensional fluid/Monte Carlo simulations are employed to investigate the effects of applied voltage frequency on the electron, ion, and neutral heating in an rf capacitively coupled plasma microthruster operating in argon. Variations in the electron and argon ion densities and power deposition, and their consequent effect on neutral-gas heating, are investigated with relation to the phase-averaged and phase-resolved sheath dynamics for rf voltage frequencies of 6-108 MHz at 450 V. Driving voltage frequencies above 40.68 MHz exhibit enhanced volumetric ionization from bulk electrons at the expense of the ion heating efficiency. Lower driving voltage frequencies below 13.56 MHz exhibit more efficient ionization due to secondary electrons and an increasing fraction of rf power deposition into ions. Thermal efficiencies are improved by a factor of 2.5 at 6 MHz as compared to the more traditional 13.56 MHz, indicating a favorable operating regime for low power satellite applications.

Abstract: The diffraction patterns of crystalline materials with local order contain sharp Bragg reflections as well as highly structured diffuse scattering. In this study, we quantitatively show how the diffuse scattering in three-dimensional electron diffraction (3D ED) data is influenced by various parameters, including the data acquisition mode, the detector type and the use of an energy filter. We found that diffuse scattering data used for quantitative analysis are preferably acquired in selected area electron diffraction (SAED) mode using a CCD and an energy filter. In this study, we also show that the diffuse scattering in 3D ED data can be obtained with a quality comparable to that from single-crystal X-ray diffraction. As electron diffraction requires much smaller crystal sizes than X-ray diffraction, this opens up the possibility to investigate the local structure of many technologically relevant materials for which no crystals large enough for single-crystal X-ray diffraction are available.