Abstract: Treatment of sewage sludge with a thermal hydrolysis process (THP) followed by anaerobic digestion (AD) enables to boost biogas production and minimize residual sludge volumes. However, the reject water can cause inhibition to aerobic and anoxic ammonium-oxidizing bacteria (AerAOB & AnAOB), the two key microbial groups involved in the deammonification process. Firstly, a detailed investigation elucidated the impact of different organic fractions present in THP-AD return liquor on AerAOB and AnAOB activity. For AnAOB, soluble compounds linked to THP conditions and AD performance caused the main inhibition. Direct inhibition by dissolved organics was also observed for AerAOB, but could be overcome by treating the filtrate with extended aerobic or anaerobic incubation or with activated carbon. AerAOB additionally suffered from particulate and colloidal organics limiting the diffusion of substrates. This was resolved by improving the dewatering process through an optimized flocculant polymer dose and/or addition of coagulant polymer to better capture the large colloidal fraction, especially in case of unstable AD performance. Secondly, a new inhibition model for AerAOB included diffusion-limiting compounds based on the porter-equation, and achieved the best fit with the experimental data, highlighting that AerAOB were highly sensitive to large colloids. Overall, this paper for the first time provides separate identification of organic fractions within THP-AD filtrate causing differential types of inhibition. Moreover, it highlights the combined effect of the performance of THP, AD and dewatering on the downstream autotrophic nitrogen removal kinetics. (C) 2018 Elsevier Ltd. All rights reserved.

Abstract: The implementation of nitritation/denitritation (Nit/DNit) as alternative to nitrification/denitrification (N/DN) is driven by operational cost savings, e.g. 1.0-1.8 EUR/ton slurry treated. However, as for any biological nitrogen removal process, Nit/DNit can emit the potent greenhouse gas nitrous oxide (N2O). Challenges remain in understanding formation mechanisms and in mitigating the emissions, particularly at a low ratio of organic carbon consumption to nitrogen removal (CODrem/N-rem). In this study, the centrate (centrifuge supernatant) from anaerobic co-digestion of pig slurry was treated in a sequencing batch reactor. The process removed approximately 100% of ammonium a satisfactory nitrogen loading rate (0.4 g N/L/d), with minimum nitrite and nitrate in the effluent. Substantial N2O emission (around 17% of the ammonium nitrogen loading) was observed at the baseline operational condition (dissolved oxygen, DO, levels averaged at 0.85 mg O-2/L; CODrem/N-rem of 2.8) with similar to 68% of the total emission contributed by nitritation. Emissions increased with higher nitrite accumulation and lower organic carbon to nitrogen ratio. Yet, higher DO levels (similar to 2.2 mg O-2/L) lowered the aerobic N2O emission and weakened the dependency on nitrite concentration, suggesting a shift in N2O production pathway. The most effective N2O mitigation strategy combined intermittent patterns of aeration, anoxic feeding and anoxic carbon dosage, decreasing emission by over 99% (down to similar to 0.12% of the ammonium nitrogen loading). Without anaerobic digestion, mitigated Nit/DNit decreases the operational carbon footprint with about 80% compared to N/DN. With anaerobic digestion included, about 4 times more carbon is sequestered. In conclusion, the low CODrem/N-rem feature of Nit/DNit no longer offsets its environmental sustainability provided the process is smartly operated. (c) 2017 Elsevier Ltd. All rights reserved.

Abstract: High-rate activated sludge processes allow for the recovery of organics and energy from wastewaters. These systems are operated at a short sludge retention time and high sludge-specific loading rates, which results in a higher sludge yield and better digestibility than conventional, low-rate activated sludge. Little is known about the microbial ecology of high-rate systems. In this work, we address the need for a fundamental understanding of how high-rate microbial communities differ from low-rate communities. We investigated the high-rate and low-rate communities in a sewage treatment plant in relation to environmental and operational variables over a period of ten months. We demonstrated that (1) high-rate and low-rate communities are distinctly different in terms of richness, evenness and composition, (2) high-rate community dynamics are more variable and less shaped by deterministic factors compared to low-rate communities, (3) sub-communities of continuously core and transitional members are more shaped by deterministic factors than the continuously rare members, both in high-rate and low-rate communities, and (4) high-rate community members showed a co-occurrence pattern similar to that of low-rate community members, but were less likely to be correlated to environmental and operational variables. These findings provide a basis for further optimization of high-rate systems, in order to facilitate resource recovery from wastewater.

Abstract: In this study, the uptake and elimination of ZnO and CuO nanoparticles in Daphnia magna was tested. Daphnids were exposed during 10 days to sublethal concentrations of ZnO and CuO nanoparticles and corresponding metal salts (ZnCl2 and CuCl2.2H2O), after which they were transferred to unexposed medium for another 10 days. At different times during the exposure and none-exposure, the total and internal zinc or copper concentration of the daphnids was determined and the nanoparticles were localized in the organism using electron microscopy. The exposure concentrations were characterized by measuring the dissolved, nanoparticle and aggregated fraction in the medium. The results showed that the ZnO nanoparticles quickly dissolved after addition to the medium. Contrarily, only a small fraction (corresponding to the dissolved metal salt) of the CuO nanoparticles dissolved, while most of these nanoparticles formed large aggregates. Despite an initial increase in zinc and copper concentration during the first 48 hour to 5 day exposure, the body concentration reached a plateau level that was comparable for the ZnO nanoparticles and ZnCl2, but much higher for the CuO nanoparticles (with visible aggregates accumulating in the gut) than CuCl2.2H2O. During the remaining exposure and subsequent none-exposure phase, the zinc and copper concentration decreased fast to concentrations comparable with the unexposed daphnids. The results indicate that D. magna can regulate its internal zinc and copper concentration after exposure to ZnO and CuO nanoparticles, similar as after exposure to metal salts. The combined dissolution, accumulation and toxicity results confirm that the toxicity of ZnO and CuO nanoparticles is caused by the dissolved fraction. Keywords nano; zinc; copper; dissolution; aggregation; electron microscopy

Abstract: Each ton of organic household waste that is collected, transported and composted incurs costs (€75/ton gate fee). Reducing the mass and volume of kitchen waste (
KW) at the point of collection can diminish transport requirements and associated costs, while also leading to an overall reduction in gate fees for final processing. To this end, the objective of this research was to deliver a proof of concept for the so-called “urban pre-composter”; a bioreactor for the decentralized, high-rate pre-treatment of KW, that aims at mass and volume reduction at the point of collection. Results show considerable reductions in mass (33%), volume (62%) and organic solids (32%) of real KW, while provision of structure material and separate collection of leachate was found to be unnecessary. The temperature profile, C/N ratio (12) and VS/TS ratio (0.69) indicated that a mature compost can be produced in 68  days (after pre-composting and main composting). An economic Monte Carlo simulation yielded that the urban pre-composter concept is not more expensive than the current approach, provided its cost per unit is €8,000–€14,500 over a 10-year period (OPEX and CAPEX, in 80% of the cases). The urban pre-composter is therefore a promising system for the efficient pre-treatment of organic household waste in an urban context.

Abstract: In the field of photocatalysis, the fabrication of black titania is a booming topic, as it offers a system with improved solar light harvesting properties and increased overall efficiency. The darkening of white TiO2 powders can be ascribed to surface hydroxylation, oxygen vacancies, Ti3+ centres, or a combination thereof. A handful of studies suggests these defects can be conveniently introduced by acoustic cavitation, generated during sonochemical treatment of pristine TiO2 powders. In reproducing these studies, P25 TiO2 samples were ultrasonicated for various hours with a power density of 8000 W/L, resulting in powders that indeed became gradually darker with increasing sonication time. However, HAADF–STEM revealed that extensive erosion of the sonotrode tip took place and contaminated the samples, which appeared to be the primary reason for the observed colour change. This was confirmed by UV–Vis DRS and DRIFTS, that showed no significant alteration of the catalyst surface after sonication. EPR measurements showed that only an insignificant fraction of Ti3+ centres were produced, far less than in a TiO2 sample that was chemically reduced with NaBH4. No evidence of the presence oxygen vacancies could be found. The enhanced photocatalytic activities of ultrasonicated materials reported in literature can therefore not be ascribed to the synthesis of actual black (defected) TiO2, but rather to specific changes in morphology as a result of acoustic cavitation. Also, this study underlines the importance of considering probe erosion in sonochemical catalyst synthesis, which is an unavoidable side effect that can have an important impact on the catalyst appearance, properties and performance.

Abstract: To understand the structure–property relationship of nanostructures, reliably quantifying parameters, such as the number of atoms along the projection direction, is important. Advanced statistical methodologies have made it possible to count the number of atoms for monotype crystalline nanoparticles from a single ADF STEM image. Recent developments enable one to simultaneously acquire multiple ADF STEM images. Here, we present an extended statistics-based method for atom counting from a combination of multiple statistically independent ADF STEM images reconstructed from non-overlapping annular detector collection regions which improves the accuracy and allows one to retrieve precise atom-counts, especially for images acquired with low electron doses and multiple element structures.

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: Quantification of annular dark field (ADF) scanning transmission electron microscopy (STEM) images in terms
of composition or thickness often relies on probe-position integrated scattering cross sections (PPISCS). In
order to compare experimental PPISCS with theoretically predicted ones, expensive simulations are needed for
a given specimen, zone axis orientation, and a variety of microscope settings. The computation time of such
simulations can be in the order of hours using a single GPU card. ADF STEM simulations can be efficiently
parallelized using multiple GPUs, as the calculation of each pixel is independent of other pixels. However, most
research groups do not have the necessary hardware, and, in the best-case scenario, the simulation time will
only be reduced proportionally to the number of GPUs used. In this manuscript, we use a learning approach and
present a densely connected neural network that is able to perform real-time ADF STEM PPISCS predictions as
a function of atomic column thickness for most common face-centered cubic (fcc) crystals (i.e., Al, Cu, Pd, Ag,
Pt, Au and Pb) along [100] and [111] zone axis orientations, root-mean-square displacements, and microscope
parameters. The proposed architecture is parameter efficient and yields accurate predictions for the PPISCS
values for a wide range of input parameters that are commonly used for aberration-corrected transmission
electron microscopes.

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: 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: Four dimensional scanning transmission electron microscopy (4D STEM) records the scattering of electrons in a material in great detail. The benefits offered by 4D STEM are substantial, with the wealth of data it provides facilitating for instance high precision, high electron dose efficiency phase imaging via centre of mass or ptychography based analysis. However the requirement for a 2D image of the scattering to be recorded at each probe position has long placed a severe bottleneck on the speed at which 4D STEM can be performed. Recent advances in camera technology have greatly reduced this bottleneck, with the detection efficiency of direct electron detectors being especially well suited to the technique. However even the fastest frame driven pixelated detectors still significantly limit the scan speed which can be used in 4D STEM, making the resulting data susceptible to drift and hampering its use for low dose beam sensitive applications. Here we report the development of the use of an event driven Timepix3 direct electron camera that allows us to overcome this bottleneck and achieve 4D STEM dwell times down to 100 ns; orders of magnitude faster than what has been possible with frame based readout. We characterize the detector for different acceleration voltages and show that the method is especially well suited for low dose imaging and promises rich datasets without compromising dwell time when compared to conventional STEM imaging.

Abstract: 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.

Abstract: In computed tomography, the reconstruction is typically obtained on a voxel grid. In this work, however, we propose a mesh-based reconstruction method. For tomographic problems, 3D meshes have mostly been studied to simulate data acquisition, but not for reconstruction, for which a 3D mesh means the inverse process of estimating shapes from projections. In this paper, we propose a differentiable forward model for 3D meshes that bridge the gap between the forward model for 3D surfaces and optimization. We view the forward projection as a rendering process, and make it differentiable by extending recent work in differentiable rendering. We use the proposed forward model to reconstruct 3D shapes directly from projections. Experimental results for single-object problems show that the proposed method outperforms traditional voxel-based methods on noisy simulated data. We also apply the proposed method on electron tomography images of nanoparticles to demonstrate the applicability of the method on real data.