Abstract: Road traffic is the most widespread environmental noise source in Europe, proven to affect human health and well-being adversely. Noise barriers can be a very effective way to objectively reduce the noise levels to which the population is exposed, leading to positive effects on noise perception and quality of life. In this paper, surveys were used to assess subjective noise level indicators (annoyance and quality of life) from residents of the vicinity of a highway where obsolete noise barriers were to be replaced. %HA before the barrier replacement was measured from the surveys (26.8%) and estimated based on the acoustic simulation and two existing exposure/response relationships (14.6 and 18.8% before and 13.6 and 8.3% after). The difference in the measured %HA to those calculated from the ERRs shows that those models might not estimate %HA fairly for small samples or particular situations where high Lden is reported. Noise annoyance correlated differently with the quality of life indicators: a weak link was observed with health problems, while a strong correlation was found with the comfort level to perform activities outdoors. Objective noise measurements gave LA,eq,(15 min.) reductions of 4.1dB(A) due to the new barrier, while in acoustics models, calculated as Lday, expected this reduction to be 5.2 dB(A). After replacing the noise barriers, a second survey could still not be distributed due to the unknown effect of the COVID-19 measures that are still active

Abstract: We present a computational imaging mode for large scale electron microscopy data, which retrieves a complex wave from noisy/sparse intensity recordings using a deep learning approach and subsequently reconstructs an image of the specimen from the Convolutional Neural Network (CNN) predicted exit waves. We demonstrate that an appropriate forward model in combination with open data frameworks can be used to generate large synthetic datasets for training. In combination with augmenting the data with Poisson noise corresponding to varying dose-values, we effectively eliminate overfitting issues. The U-NET[1] based architecture of the CNN is adapted to the task at hand and performs well while maintaining a relatively small size and fast performance. The validity of the approach is confirmed by comparing the reconstruction to well-established methods using simulated, as well as real electron microscopy data. The proposed method is shown to be effective particularly in the low dose range, evident by strong suppression of noise, good spatial resolution, and sensitivity to different atom types, enabling the simultaneous visualisation of light and heavy elements and making different atomic species distinguishable. Since the method acts on a very local scale and is comparatively fast it bears the potential to be used for near-real-time reconstruction during data acquisition.

Abstract: By combining statistical parameter estimation and model-order selection using a Bayesian framework, the maximum a posteriori (MAP) probability rule is proposed in this chapter as an objective and quantitative method to detect atom columns from high-resolution scanning transmission electron microscopy (HRSTEM) images. The validity and usefulness of this approach is demonstrated to both simulated and experimental annular dark-field (ADF) STEM images, but also to simultaneously acquired annular bright-field (ABF) and ADF STEM image data.

Abstract: This chapter provides an overview of statistical and quantitative methodologies that have pushed (scanning) transmission electron microscopy ((S)TEM) toward accurate and precise measurements of unknown structure parameters for understanding the relation between the structure of a material and its properties. Hereby, statistical parameter estimation theory has extensively been used which enabled not only measuring atomic column positions, but also quantifying the number of atoms, and detecting atomic columns as accurately and precisely as possible from experimental images. As a general conclusion, it can be stated that advanced statistical techniques are ideal tools to perform quantitative electron microscopy at the atomic scale. In the future, statistical methods will continue to be developed and novel quantification procedures will open up new possibilities for studying material structures at the atomic scale.

Abstract: In this chapter, the principles of detection theory are used to quantify the probability of error for atom counting from high-resolution scanning transmission electron microscopy (HRSTEM) images. Binary and multiple hypothesis testing have been investigated in order to determine the limits to the precision with which the number of atoms in a projected atomic column can be estimated. The probability of error has been calculated when using STEM images, scattering cross-sections or peak intensities as a criterion to count atoms. Based on this analysis, we conclude that scattering cross-sections perform almost equally well as images and perform better than peak intensities. Furthermore, the optimal STEM detector design can be derived for atom counting using the expression of the probability of error. We show that for very thin objects the low-angle annular dark-field (LAADF) regime is optimal and that for thicker objects the optimal inner detector angle increases.

Abstract: 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 neighboring columns, enabling the analysis of a large field of view. To provide end-users with this well-established quantification method, a user friendly program, StatSTEM, is developed which is freely available under a GNU public license. In this chapter, this efficient algorithm is applied to three different nanostructures for which the analysis of a large field of view is required.

Abstract: This Special Issue, entitled “Plasma Medicine Technologies”, covers the latest remarkable developments in the field of plasma bioscience and medicine. Plasma medicine is an interdisciplinary field that combines the principles of plasma physics, material science, bioscience, and medicine, towards the development of therapeutic strategies. A study on plasma medicine has yielded the development of new treatment opportunities in medical and dental sciences. An important aspect of this issue is the presentation of research underlying new therapeutic methods that are useful in medicine, dentistry, sterilization, and, in the current scenario, that challenge perspectives in biomedical sciences. This issue is focused on basic research on the characterization of the bioplasma sources applicable to living cells, especially to the human body, and fundamental research on the mutual interactions between bioplasma and organic–inorganic liquids, and bio or nanomaterials.

Abstract: This thesis provides three potential ways to enhance the nitrogen removal efficiency of mainstream partial nitritation/anammox (PN/A), a key technology to enable energy-positive sewage treatment. In Chapter 1, the typical technologies to promote nitrogen removal efficiency are summarized. In Chapters 2 and 3, the concept ‘winter bioaugmentation with stored summer surplus sludge’ is proposed. Applying that, a cost-effective sludge preservation strategy is required. Preserving PN/A biomass without cooling and redox adjustment proved to be the cost-effective strategy. The reactivation of these stored sludges was also tested in low-temperature systems (15 and 10℃). Respectively 56% and 41% of granules activity compared to pre-storage activity (after Arrhenius-based temperature correction) could be recovered within a month (41% and 32% for flocs activity). In the end, the stored AnAOB bioaugmentation was successfully validated in the lab (20℃). In Chapter 4, a return-sludge nursery concept, applying the sidestream nitritation and blending the resulting effluent with mainstream effluent to achieve an intermediate temperature and nitrogen concentrations, is proposed. That led to a 33 – 36% increase in nitrogen removal efficiency. Arrhenius’ expectations (10 ℃ higher temperature, θ = 1.09) could only explain 49-51% of the activity increase in the nursery reactor, pointing to the role of other factors, e.g., the ~400% elevated electrical conductivity (15-16%), the 56-335% higher effluent nitrogen concentrations (12-14%), and the synergy and unknown factors (20-23%). Thus, the return-sludge biostimulation approach could also enhance nitrogen efficiency in the mainstream. In Chapter 5, the N2O emissions, linked to three typical nitrite-oxidizing bacteria (NOB) suppression strategies (low dissolved oxygen (DO) level, free ammonia (FA), and free nitrous acids (FNA) treatments) were tested in a biofilm system. A low emerged DO level (~0.60 mg O2 L-1) was effective to suppress NOB activity and decrease N2O emissions, but NOB adaptation gradually appeared after 200 days. Further NOB inhibition was successfully achieved by periodical (3 hours per week) FA (~30 mg NH3-N L-1) or FNA (~3 mg HNO2-N L-1) treatments. The FA treatment promoted N2O production, while the FNA treatment had no effect. Thus, PN/A systems should be operated at relatively low DO levels with periodical FNA treatment. In Chapter 6, the major findings proposed and the main conclusions drawn in this thesis are outlined. Beyond that, the possible design of a mainstream PN/A configuration that combined all described three technologies is demonstrated. Overall, the novel insights from this thesis potential to improve nitrogen removal efficiency in the mainstream.

Abstract: Pancreatic ductal adenocarcinoma (PDAC) and glioblastoma multiforme (GBM) are two of the most malignant solid tumor types with poor survival rates, which underscore the urgency of novel and efficacious treatment strategies. Within the last decade, immunotherapy has been established as a breakthrough in cancer therapy. This mainly has been driven by the clinical data and approval associated with several immune checkpoint inhibitors (e.g. anti-CTLA-4 and anti-PD-1/L1). Despite the clinical benefit in specific tumor types, these inhibitors have not yet fulfilled their promise in low immunogenic tumors such as PDAC and GBM. Oxidative stress in cancer cells due to elevated reactive oxygen species (ROS) and an inability to balance intracellular redox state has recently been highlighted as promising target for anticancer treatment strategies with possible immunogenic effects. In this PhD dissertation, I investigated novel oxidative stress-mediated treatment approaches to target PDAC and GBM and to enhance immunogenicity by inducing immunogenic cell death (ICD). In the first part of this thesis (chapter 2), I reviewed the mechanistic responses of cancer cells towards different oxidative stress-inducing treatment strategies and their immunomodulating effects. The resulting literature demonstrated that different exogenous and endogenous ROS-inducing therapies show direct and indirect immunomodulating effects, which can be either immunostimulatory or immunosuppressive. One of the indirect immunostimulatory effects of the ROS-mediating therapies is the capacity of inducing immunogenic cell death (ICD) in tumor cells, which can increase the immunogenicity and consequently can trigger an antitumoral immune response. In chapter 3, I investigated a novel exogenous ROS-inducing treatment method, namely cold atmospheric plasma, to determine the therapeutic and ICD-inducing effects in PDAC, in vitro. I revealed that plasma-treated PBS (pPBS) has the potential to induce ICD in pancreatic cancer cells (PCCs) and to reduce the immunosuppressive tumor microenvironment (TME) by attacking the tumor supportive pancreatic stellate cells (PSCs). Although the cell death induced in PSCs was non-immunogenic as seen by the lack of danger-associated molecular patterns (DAMPs) emission and DC activation, I showed that pPBS could disrupt the physical barrier and lower the immunosuppressive secretion profile (lower TGF-β) of PSCs. In contrast, DAMPs were released by PCCs after treatment with pPBS which resulted in activation and maturation of DCs and a more immunostimulatory secretion profile (higher TNF-α, IFN-γ). Hence, indirect plasma treatment via pPBS has the potential to enhance immunogenicity in PDAC by triggering ICD and by attacking the immunosuppressive PSCs. Tumor cells can evolve adaptation mechanisms to protect themselves against intrinsic oxidative stress by upregulation of pro-survival molecules and their antioxidant defense system to maintain the redox balance. As such, tumor cells can become resistant towards exogenous ROS-inducing therapies, like plasma. Dual targeting of the redox balance of tumor cells by increasing exogenous levels of ROS and inhibiting the antioxidant defense system can maximally exploit ROS-mediated cell death mechanisms as therapeutic anticancer strategy. In this regard, cold atmospheric plasma was combined with auranofin, a thioredoxin reductase inhibitor, in GBM (chapter 4). A synergistic effect was shown after this combination treatment in 2D and 3D, however, in 3D only high concentrations of auranofin synergized with plasma treatment. I confirmed a ROS-mediated response after combination treatment, which was able to induce distinct cell death mechanisms, specifically apoptosis and ferroptosis. Additionally, the auranofin and plasma combined treatment strategy induced cell death, which resulted in an increased release of DAMPs. Together with the observed DC maturation, these results indicates the potential increase in immunogenicity, though, the phagocytotic capacity of DCs was inhibited by auranofin. In chapter 5, I evaluated this promising oxidative stress combination therapy in GBM, in vivo. A decrease in tumor kinetics and an increased survival in GBM-bearing mice was observed when auranofin was sequentially combined with direct plasma treatment. No T cell infiltration was observed after auranofin monotherapy. However, further characterization of the TME after the combination therapy is necessary to provide more insight in the immunogenic effects in vivo. In conclusion, this PhD dissertation comprises novel and important therapeutic and immunogenic insights in cold atmospheric plasma and auranofin as promising oxidative stress-mediated treatment strategies for low immunogenic tumors, like PDAC and GBM. These preclinical results provide a solid basis for future research towards combinations with immunotherapeutic approaches.

Abstract: Sulfur hexafluoride (SF6), as a man-made gas, is widely used in power industry, semiconductor industry and metal-processing industry. However, SF6 is a greenhouse gas and its global warming potential is 23500 times that of CO2. Besides, SF6 is very stable, with a lifetime in the atmosphere for more than one thousand years. Under natural conditions, only the ultraviolet light can make it slowly decomposed. Thus, the emission of SF6 has a great threat to the environment. In recent years, with the development of our national economy, the use of SF6 increased dramatically. And 90% of the SF6 emissions come from the power industry. In the meantime, the emission of SF6 exists a ‘hysteresis effect’, as many of the SF6-gas insulation equipment will retire in next decades, the emission of SF6 may increase sharply, and this may put great pressure on the environment. Therefore, it’s necessary to make efforts in controlling and treating the SF6 emission. Among the SF6 abatement technologies, the non-thermal plasma(NTP) represented by the dielectric barrier discharge(DBD) can effectively degrade SF6 and is suitable for large-scale industry applications. However, its energy efficiency still gets room for improvement and this kind of method has a defect that it’s hard to regulate the degradation by-products. Therefore, this paper proposed the combination of the packed bed reactor and the DBD technology to form a packed DBD discharge system for SF6 degradation, so that to further improve the energy efficiency and regulate the selectivity of by-products. By experiment and simulation research, the following innovations have been achieved: (1) Based on the packed bed DBD platform, the power parameter and gas-phase parameters of SF6 degradation were studied. It was found that the discharge process was significantly enhanced with the addition of packing particles, and the discharge energy efficiency was improved. The increase of input voltage can obviously increase the degradation rate, but reduces the energy efficiency. The increase of SF6 initial concentration and gas flow rate can improve the energy efficiency, but reduce the degradation rate. Therefore, both degradation rate and energy efficiency should be considered in deciding basic experimental conditions. (2) Active gases, such as O2, H2O and NH3, could effectively promote the degradation rate of SF6, and changed the product selectivity. In our packed bed DBD system, O2 and H2O have the optimal concentration conditions, which are 2% and 1%, respectively. The addition of O2 can promote the generation of S-O-F products, and inhibit the selectivity of SO2, while the addition of H2O had the opposite effects. In addition, the synergistic degradation of NH3 and SF6 will produce solid products, such as NH3HF, NH4HF2 and elemental S. For gaseous products, the increase of NH3 will lead to the generation of SO2 in the final degradation products and inhibit the generation of S-O-F products. (3) Different kinds of packing materials have great impacts on the degradation system in the discharge parameters, degradation rate and energy efficiency, as well as the products distribution. In the experiment, we compared the degradation results in three systems: glass beads packing, γ-Al2O3 packing and no-packing system. The packing of glass beads effectively improved the discharge voltage amplitude and discharge power, while had a limited effect on the equivalent capacitance of the dielectric. Besides, γ-Al2O3 packing had little effect on voltage amplitude, but obviously increased the equivalent capacitance of the dielectric. Furthermore, the degradation rate and energy efficiency in γ-Al2O3 system was higher than that of glass bead system. For products selectivity, γ-Al2O3 system was more desirable, where S-O-F type of product selectivity was suppressed and the SO2 selectivity increased significantly. By contrast, the glass beads system hardly affected the product selectivity. This results are presumably due to the relatively high dielectric constant of γ-Al2O3 particles and γ-Al2O3 itself may act as a reactant or a catalyst participating in the degradation reactions. (4) The size and status of the packing particles also have significant effects on the degradation process. The systems packed with 1, 2 and 4mm γ-Al2O3 particles for SF6 degradation were compared, and the 2mm system had the best performance, which may because the 2mm system had a good balance between the active contact area and the gas residence time. In addition, the packing pellets suffered from a hydration process slightly reduced the discharge parameters in the γ-Al2O3 packing system and significantly reduced the degradation rate was, which may because the H2O molecules pre-occupied the active sites on the γ-Al2O3 surface and reduced the discharge process. (5) Based on density functional theory (DFT), the degradation process of SF6 in the packed bed DBD system was studied at atomic scale. It was found that the SF6 can occur a physical adsorption at AlⅢ active sites on γ-Al2O3 surface. The activation barrier for the first degradation step of SF6 on γ-Al2O3 surface is much lower than in gas phase, which proved that the SF6 molecule is activated on the γ-Al2O3 surface. In addition, the plasma may affect the γ-Al2O3 surface to generate excess electrons or external electric fields. This two effects can change the adsorbed SF6 molecules from physical adsorption to chemisorption, together with an obvious stretching of S-F bonds, indicating that the plasma surface effects prmote the activation and decomposition of SF6 molecules. Furthermore, the stepwise degradation process of SF6 on γ-Al2O3 surface were investigated. The influence of radicals produced by plasma on the degradation process was analyzed. It was found that via Eley–Rideal (ER) reactions, high-energy radicals could effectively reduce the activation barriers and promote the surface reactions. Finally, the degradation mechanism of SF6 molecules in the packed bed plasma system was summarized, which may provide a theoretical basis for the study of harmless degradation of SF6. Keywords: SF6; Packed Bed DBD; Discharge Parameters; Products Analysis; Degradation Mechanism

Abstract: The discovery of antibiotics represented one of the greatest breakthroughs in medicine. Their success combined with an increasing intensive use is apparently bound to be also their undoing. This is due to the development of acquired antibiotic resistance, leading to inefficient antibiotherapy and even to the impossibility of treatment and death. The development and spread of antibiotic resistance are fueled by the widespread presence of trace levels of antibiotics residue, in various media, from environment to aliments. One of the solutions is the rigorous monitoring of the levels of antibiotics, which in term requires an almost constant development of new, more accessible analytical methods, especially screening methods, capable of decentralized analysis. In this direction, the electrochemical detection of antibiotics represents a very viable alternative. In this context, the aim of this thesis was to develop new electrochemical methods for the detection of antibiotics by employing and expanding on several strategies, like biomimetic sensors and electrochemical fingerprinting. Five studies were described in this thesis, that can be roughly divided in three categories, based on the analytical strategy employed. The first group is represented by direct electrochemical methods. The second group focuses on the use of biomimetic elements, molecularly imprinted polymers and aptamers. The hyphenation of electrochemical methods with other analytical methods was explored in the last group. In the last study, included in this group, the singlet oxygen-based photoelectrochemical approach was used for the detection of a phenolic antibiotic, rifampicin. The originality of the thesis consists in the testing and development of new approaches to various strategies used in electrochemical detection, revealing new insights in the field of electrochemical detection of antibiotics. The complex electrochemical fingerprint and the mechanism of the electrochemical oxidation were created and investigated, respectively, for the antibiotic vancomycin. New sensitive nanoplatforms were prepared by employing and combining new protocols. Additionally, important contributions were brought through the study involving the singlet oxygen-based detection of rifampicin. We demonstrated how a photocatalyst can exhibit analyte selectivity by strongly interacting with a complex phenolic compound, rifampicin. Summing up, the studies presented in this thesis will have an important impact in the field of electrochemical detection of antibiotics.

Abstract: In the biogeochemical flows on Earth, the reactive nitrogen (Nr) level has three times surpassed the safe boundary. The severe transgression of this boundary goes against sustainable planetary development. The modern food production process excessively relies on synthetic Nr fertilizers from the Haber– Bosch process. However, the massive loss of valuable nitrogen resources (i.e., 78-89%) from agriculture has been causing severe nitrogen cascade. Besides, the domestic wastewater in some local areas is discharged without proper treatment, making it a nonnegligible source of Nr pollution for local water bodies. Anthropogenic activities keep pumping out Nr pollution via point-source and non-point-source (NPS) emissions. Compared to the NPS emissions, point sources give visible and identified waste streams. It is vital to intervene the nitrogen cascade from point sources and facilitate humanity back to the safe Nr boundary. The collected and collectible Nr streams from food production, waste management, and recycling secondary raw materials can be used as waste-based fertilizers for agricultural cultivation. Besides the well-investigated recovery of inorganic Nr, organic Nr accounts for a massive Nr proportion on the Earth. Proper handling and treatment make these useful organic fertilizers for soil-based cultivation. However, these organic Nr fertilizers cannot directly apply to fertigation or hydroponic cultivation systems, and further biological conversion via nitrogen mineralization and nitrification to nitrate is essential. Besides the direct Nr cycling, the indirect Nr cycling ‘over the atmosphere’ should also be considered. In this way, the nitrogen cycle can be completed via converting the waste Nr back to nitrogen gas (i.e., Nr removal) and then synthesizing into Nr again. The municipal wastewater treatment plants receive a vast amount of low-strength Nr wastewater (mainly as ammonium) daily. Compared to the conventional nitrification/denitrification process, partial nitritation/anammox (PN/A) is considered a resource- and cost-effective technology for wastewater with a low COD/N ratio. Moreover, the novel autotrophic denitratation/anammox process could be a good Nr removal process for wastewater containing both ammonium and nitrate. This Ph.D. thesis aimed to develop Nr recovery, conversion, and removal bioreactor strategies for different types of waste streams and biomass. Nr recovery was investigated on high-strength Nr waste streams for fertigation or hydroponic applications in Chapters 2 and 3. On the other hand, Nr removal was studied on the medium- to low-strength Nr waste streams in Chapters 4 and 5. In Chapter 2, a novel mineralization and nitrification system was proposed, producing nutrient solutions from solid organic fertilizers for hydroponic systems. Batch tests showed that aerobic incubation at 35°C could realize the NO₃⁻-N production efficiency above 90% from a novel microbial fertilizer. Subsequently, in the stirred tank bioreactor test, NO₃⁻-N production efficiency stabilized in a range of 44-51% under the influent loading rate of 400 mg TN L⁻¹ d⁻¹ at a 5-day HRT. Using Ca(OH)₂ and Mg(OH)₂ as pH control reagents generated the nutrient solutions with different P, Ca, and Mg nutrient levels. After modeling the nutrient balancing process, the proportion of organic-sourced NO₃⁻-N in the Hoagland nutrient solution (HNS) of Ca(OH)₂ scenario was 92.7%, while only 37.4% in the Mg(OH)₂ scenario. Compared to commercial scenarios, the total costs of the organic-sourced HNS can be cost-competitive for hydroponic cultivation. In Chapter 3, the Nr recovery as nitrate (NO₃⁻-N) from diluted human urine (around 670 mg N L⁻¹) was explored in a trickling filter (TF) for the first time. A novel concept of in-situ integrating the TF system into hydroponic systems was proposed as meaningful progress towards sustainable agriculture. The difference between synthetic and real urine in nitrification efficiency was found to be negligible. The full nitrification of alkalinized real urine was realized in the pH-controlled TF by calcium hydroxide (Ca(OH)₂) at around pH 6. The TF could handle different urine collection batches and maintain relatively stable nitrification performance, with NO₃⁻-N production efficiency and rate of 88±3% and 136±4 mg N L⁻¹ d⁻¹, respectively. The optimal HLR to realize this nitrification performance was 2 m³ m⁻² h⁻¹, with energy consumption of 1.8 kWh electricity kg⁻¹ NO₃⁻-N production. Ca(OH)₂, as a cheap base, its triple advantages on urine alkalinization, full nitrification, and macronutrient supplementation were successfully demonstrated in our proposed concept. In Chapter 4, towards more sustainable wastewater treatment, the feasibility of one-stage partial nitritation/anammox (PN/A) was investigated in three parallel packed-bed trickling filters (TFs), with three types of carrier materials of different specific surface areas. Synthetic wastewater containing 100-250 mg NH₄⁺-N L⁻¹ was tested to mimic medium-strength household waste streams after carbon removal. Interestingly, the cheap carrier based on expanded clay achieved similar rates as commercially used plastic carrier materials. The top passive ventilation combined with an optimum hydraulic loading rate of 1.8 m³ m⁻² h⁻¹ could reach approximately 60% total nitrogen (TN) removal at a rate of 300 mg N L⁻¹ d⁻¹. A relatively low NO₃⁻-N production (13%) via PN/A was achieved in TFs. Most of the TN removal took place in the top compartment, where anammox activity was the highest. Energy consumption estimation (0.78 kWh electricity g⁻¹ N removed) suggested that the proposed process could be a suitable low-cost alternative for nitrogen removal. In Chapter 5, coupling sulfur-driven denitratation (SDN) with anammox was proposed to treat the wastewater containing both NO₃⁻-N and NH₄⁺-N, like the secondary effluents of mainstream PN/A processes. To explore the feasibility of sufficient and stable NO₂⁻-N accumulation via SDN in the long term, the effects of pH setpoints, residual NO₃⁻-N level, and biomass-specific NO₃⁻-N loading rate (BSNLR) were investigated. Alternating the pH setpoints between 7.0 and 8.5 could temporarily stimulate the NO₂⁻-N accumulation. Both the residual NO₃⁻-N and BSNLR showed highly positive correlations with the NO₂⁻-N accumulation efficiency. Under the control of pH 8.5, 1.0±0.8 mg NO₃⁻-N L⁻¹ and 150±42 mg NO₃⁻-N g⁻¹ VSS d⁻¹, SDN could produce 6.4±1.0 mg NO₂⁻-N L⁻¹ in the short term. Thiobacillus members may play a crucial role in managing the NO₂⁻-N accumulation, but the reduction of abundance and possible adaptation significantly impaired the efficacy of control strategies in the long run. Overall, novel technologies have been proposed to sustainably convert Nr in waste streams and biomass. The decision for Nr recovery versus removal and synthesis should be based on specific cases with the best environmental, economic, and human-health sustainability. In the future, the Nr management concepts should be further improved to make the nitrogen cycle more sustainable with higher resource use efficiency and less Nr emissions to the environment. Although the thesis is mainly focused on limited types of Nr waste streams, it pointed out the direction of sustainable Nr management and could facilitate the Nr back to the safe boundary in the long run.

Abstract: Exposure to volatile organic compounds (VOCs) remains a major public health concern. Indoor VOC concentrations typically far exceed outdoor levels due to a variety of emission sources and the stringent insulation measures that are imposed today. Many attempts have been made to use photocatalysis for indoor air purification. In an ideal situation, photocatalysis is capable of complete mineralization of VOCs to H2O and CO2, without any byproduct formation. Moreover, the process can take place at standard atmospheric conditions, i.e. ambient temperature and atmospheric pressure. However, successful exploitation is still impeded due to low conversion efficiency, significant pressure loss (and hence a high energy consumption) and byproduct formation. In the first part of this thesis an attempt was made to tackles these problems by designing a novel type of photocatalytic (PCO) reactor. The PCO device consists of a cylindrical vessel filled with TiO2-coated glass tubes and equipped with UV fluorescence lamps. It was investigated in terms of fluid dynamics, coating properties, UV-light distribution and photocatalytic activity. Experimental data was later used to develop and calibrate a Multiphysics model. The model proved to be a useful tool for designing and upscaling the PCO reactor. Consequently, an optimized prototype reactor was constructed and tested according the CEN-EN-16846-1 standard for VOC removal. Although the prototype showed promising results for lab-scale conditions, it struggled with byproduct formation when purifying ppb-level VOCs. In the second part of this thesis, activated carbon adsorption was investigated in order to combine it with photocatalysis. Activated carbon fiber was opted for its fast kinetics, high adsorption capacity and thermo-electrical regeneration. The filter was studied in detail regarding the adsorption of polar and apolar VOCs at indoor air concentration levels and regeneration capabilities. Experimental data was used to develop a Multiphysics model for activated carbon adsorption as well. Consequently, a novel type of ACF filter was developed using the Multiphysics model, which was equipped with electrodes in the tips of the pleats for effective thermal regeneration. In the last part, the combination of both ACF and PCO was studied using a realistic case study. Based on the Multiphysics model, the feasibility of a so-called hybrid air purification device could be investigated. The Multiphysics model shows promising results for this hybrid PCO-ACF system and hence, a demo setup was constructed for future research.

Abstract: Scaling down the size of transistors has been a trend for several decades which has led to improved transistor performance, increased transistor density and hence the overall computation power of IC chips. The trend slowed in recent years due to reliability and power consumption issues at the nanoscale. Hence strain is introduced into transistor channels that has beneficial effects on improving the mobility of charge carriers, providing an alternative pathway for enhancing transistor performance. Therefore, monitoring strain is vital for the semiconductor industry. With the recent trend of decreasing device dimensions (FinFETS ~ 10-20nm) and strain modulation being used throughout, industry needs a reliable and fast method as quality control or defect characterisation. Such a universal strain measurement method does not exist, and one relies on a combination of quantitative in-line methods and complex off-line approaches. In this thesis, I investigated TEM and Raman spectroscopy-based methodologies for strain measurement. In terms of TEM methodologies, advancements are made for the STEM moiré imaging, targeting strain spatial resolution enhancement. I introduce advanced quadrature demodulation and phase stepping interferometry applied to STEM moiré that greatly enhances the spatial resolution while providing enhanced field of view and sensitivity for strain measurement. We introduce ways to reduce scan distortions in strain maps using an alternative scan strategy called “Block scanning” and the non-linear regression applied for strain extraction. Prospects for 3D strain analysis using high-resolution tomography is also investigated which gives direct access for the full second order strain tensors calculation. Finally, we compare strain measurements from TEM techniques with inline techniques like Raman spectroscopy. Raman stress measurement involves sensitive identification of the TO and LO phonon peaks. Raman spectrum of strained Ge transistor channel consists of strongly overlapping peaks within the spectral resolution of the spectrometer. Hence, the process of deconvolution of the two peaks is rather challenging. Hence, we explore new polarisation geometries like radially polarised incoming light which was shown to ease the deconvolution problem resulting in improved precision for Raman stress–strain measurements.