Abstract: In the recent advances towards more sustainable global energy supply, H2 is a possible alternative for large scale energy storage. In this view, Liquid Organic Hydrogen Carriers (LOHC) are a class of molecules that allow for easier long term energy storage compared to conventional H2 technologies. CFD simulations were used to showcase the hydrodynamics of the dehydrogenation of a LOHC in a new reactor unit, via a cold flow mock-up study. This reactor was designed to allow for a swirling motion of the liquid carrier material, favouring the removal of H2 gas from the flow and forcing the equilibrium of the reaction towards dehydrogenation, as well as to keep the catalyst particles in motion. The CFD simulations were validated qualitatively with experimental operation of the reactor, in a system with identical dimensionless numbers (Reynolds and Stokes), in order to use less costly products during the prototyping phase.

Abstract: Pretreatment is crucial for the conversion of lignocellulose to biofuels. Unlike conventional chemical/physicochemical methods, fungal pretreatment uses white-rot fungi and mild reaction conditions. However, challenges, including substrate sterilization, long duration, and low sugar yields associated with this method, contribute to lower techno-economic performance, an aspect that has rarely been investigated. This study aimed to evaluate the feasibility of fungal pretreatment of nonsterilized poplar wood. Various factors, including inoculum types, fermentation supplements, and cultivation methods, were investigated to optimize the process. A techno-economic assessment of the optimized processes was performed at a full biorefinery scale. The scenario using nonsterilized wood as a substrate, precolonized wood as an inoculum, and a 4 week pretreatment showed a 14.5% reduction in sugar production costs (€2.15/kg) compared to using sterilized wood. Although the evaluation of nonsterilized wood pretreatment showed promising cost reductions, fungal pretreatment remained more expensive than conventional methods due to the significant capital investment required.

Abstract: Illicit drug consumption constitutes a great concern worldwide due to its increased spread and abuse, and the negative consequences exerted on society. For instance, 3,4-methylenedioxymethamphetamine (MDMA), a synthetic amphetamine-type substance, was abused by 20 million people worldwide in 2020. This psychoactive substance exerts a myriad of effects on the human body being dangerous for the consumer’s health. Besides, MDMA has been used in the treatment of some psychiatric conditions. Therefore, the development of wearable devices for MDMA sensing in biological fluids is of great importance for forensic toxicology (e.g., monitoring of patients with suspected or known MDMA consumption) as well as for therapeutic management of patients. Herein, we report the development of a wearable electrochemical platform based on a hollow microneedle (MN) array sensor for the monitoring of MDMA in the interstitial fluid by square-wave voltammetry. First, the holes of the MN array were modified with conductive pastes to devise a MN patch with a three-electrode system. Subsequently, the functionalization of the working electrode with nanomaterials enhanced MDMA detection. Thereafter, analytical parameters were evaluated exhibiting a slope of 0.05 µA µM−1 within a linear range from 1 to 50 µM and a limit of detection of 0.75 µM in artificial interstitial fluid. Importantly, critical parameters such as selectivity, piercing capability, temperature, reversibility and stability were assessed. Overall, the obtained MN sensor exhibited excellent analytical performance, making it a promising tool for MDMA tracking in interstitial fluid for individuals on probation or under therapeutic treatment.

Abstract: Exposure to air pollution, such as particulate matter (PM), causes adverse health effects, particularly to the respiratory tract and cardiovascular system. PM is the collective name for all kinds of particles ranging from small particles and liquid droplets, which contain organic compounds, acids and metals, to soil or dust particles. One distinguishes PM10, PM2.5 and PM0.1, which have aerodynamic particle sizes smaller than 10, 2.5 and 0.1 µm, respectively. It is mainly the latter that is the most harmful, as PM0.1 penetrates deep into the respiratory system and carries relatively more toxic substances than the other PM fractions. Over a 15-year period, PM concentrations in European member states have fallen by about 30%. Nevertheless, the World Health Organisation (WHO) air quality guidelines, which became stricter in 2021, are exceeded in most places around the world. Particularly in cities, excessive levels of PM are measured and it is here that PM mitigation should be investigated. For this, the implementation of urban green infrastructure, including trees, shrubs, green roofs and green walls, is being looked at. Plants hinder airflow and remove PM from the air by deposition on their leaves and branches. This process is known as dry deposition. Plants can capture PM very efficiently, due to their complex structure of leaves and branches. Green walls offer significant advantages over other types of urban green infrastructure because they can grow on the huge available wall area and, because they do not hinder air circulation, as we sometimes see with trees. Green walls are believed to have a much greater, untapped potential to reduce PM pollution. However, a literature review showed that we do not know the quantitative impact of green walls and lack the tools and/or general methodology to do so. The objective of this thesis is therefore to develop a method for assessing PM removal by green walls, based on predictive models and based on relevant parameters that are experimentally determined. Computational fluid dynamics (CFD) is a numerical method to simulate airflow in complex environments such as cities. These models can also simulate the vegetation-wind interaction in detail and are interesting tools to assess the effect of green walls on PM concentrations in real environments. It is important to first study the aerodynamic effect of green walls and parameterise it correctly in CFD models. Plants decrease the wind speed and create turbulence through a combination of viscous and form drag, which are determined by the permeability (K) and drag coefficient (Cd), respectively. Wind tunnel experiments were conducted with three commonly found climbers (Hedera helix, Parthenocissus tricuspidata and Parthenocissus quinquefolia) and the variation of leaf area density was investigated for two of them. It was observed that the air resistance depended on plant species, leaf area density and wind speed. The difference between the plant species was assigned to the functional leaf size (FLS), the ratio of the largest circle within the boundaries of the leaf to the total leaf area. FLS is likely associated with other morphological characteristics of plants that, when considered collectively, provide a more comprehensive representation of leaf complexity. The pressure and velocity measurements obtained were used to optimise the permeability and drag coefficient in a CFD model. At wind speeds below 0.6 m s-1, the resistance was mainly determined by viscous drag and a larger leaf size resulted in a higher viscous drag. At wind speeds above 1.5 m s-1, form drag was dominant and the parameterised Cd decreased with increasing wind speed due to the sheltering effect of successive plant elements. The leaf area density had a significant effect on K and Cd and, is therefore an important plant parameters in CFD models. The main conclusion here is that the common practice of using a constant Cd to model the influence of plants on the air flow leads to deviations from reality. Wind tunnels are highly suitable to study the impact of green walls on PM concentration under controlled environmental conditions. For this purpose, a new wind tunnel setup was built and great attention was paid to obtaining a uniform air flow. Thus, based on CFD models, appropriate flow controllers were chosen, consisting of honeycombs and screens with different mesh sizes. New PM generation devices and measuring equipment were installed and set up appropriately. Devices were available for generating and measuring ultrafine dust (<0.1 µm, i.e. PM0.1) and fine dust (<0.3 µm, i.e. PM0.3) consisting of soot particles, and, on the other hand, fine dust with particle sizes smaller than 2.5 (PM2.5) and 10 µm (PM10) consisting of 'Arizona fine test dust'. With the new wind tunnel setup, it was possible to measure the influence of Hedera helix (common ivy), grown in a planter against a climbing aid, on the PM concentration and this was expressed by a collection efficiency, i.e. the difference in concentration in front and behind the plants normalised for the incoming concentration. The collection efficiency of H. helix depended on the particle size of the PM and wind speed. The collection efficiency decreased when the particle size increased from 0.02 to 0.2 µm and increased again for particle sizes above 0.3 µm. The collection efficiency also increased with increasing wind speed, especially for particle sizes > 0.03 µm. On the other hand, relative humidity and the type of PM (soot or dust) did not significantly affect the collection efficiency. The main objective of this study was to obtain an optimised size-resolved deposition model. Dry deposition occurs through several mechanisms, in particular gravity, diffusion, impaction and interception, and the subsequent resuspension of deposited PM back to the environment. The modelling of these mechanisms was described by \citet{Zhang2001} and \citet{Petroff2010}. The data obtained from the wind tunnel experiments allowed validating these deposition models. It was for the first time that deposition of real PM on green walls was studied. The different PM deposition mechanisms were found to be strongly dependent on particle size and wind speed. The models of \citet{Zhang2001} and \citet{Petroff2010} each matched PM concentration measurements for only certain particle sizes. Therefore, a combination of the two models was investigated and the root mean square error was lower by on average 3.5% (PM < 0.03 µm) and 46% (PM > 0.03 µm) compared to the original models at wind speeds greater than 1.5 m s-1. For wind speeds less than 1.5 m s-1, the optimised model did not differ from the original models. The optimised model was able to meet the imposed criteria for air quality models, where a correct model exhibits low deviation from measurements ('normalised mean square error' < 1.5), low bias ('fractional bias' between -0.3 and 0.3) and high R2. In comparison, the R$2$ of the optimised model was 0.57, while that of Zhang et al. (2001) and Petroff et al. (2010) was 0.23 and 0.31, respectively. The optimised model was however characterised by a high scatter, with the fraction of modeled results located within a factor of two of the measurements being lower than 50. A model study with a green façade oriented parallel to the incoming airflow showed that deposition by interception and impaction reduced remarkably, but that the orientation had no effect on deposition by Brownian diffusion. A promising green wall form for PM mitigation is the living wall system (LWS). LWS consist of supporting structures with substrate to grow plants in and can be planted with a variety of plant species. This allows to select plant species with optimal characteristics to achieve PM deposition. These characteristics refer to the macro- and microstructure of the leaves, and research has been conducted mainly on these. On the other hand, the influence of the supporting structure and substrate on PM concentrations has rarely been studied. With the new wind tunnel setup, LWS from different manufacturers were tested for their ability to capture PM. The setups were subjected for three hours to an air flow with a low PM concentration (resuspension phase) and then for three hours to an air flow to which additional PM was added (deposition phase). Some setups were able to decrease the PM concentration during both phases, while others just caused the concentration to increase. Some systems were able to reduce particulate matter concentration during both phases, namely LWS consisting of planters (-2% and -4% for PM0.1 and PM2.5, respectively) and textile cloths (-23% and -5% for PM0.1 and PM2.5, respectively). While other systems actually resulted in an increase in concentration especially LWS existing textile fabrics consisting of geotextiles (+11% for both PM fractions) and with moss as substrate (+2% and +5% for PM0.1 and PM2.5, respectively). This highlights the importance of careful selection of suspension systems to reduce particulate matter concentrations. Further research is therefore needed on the materials used in these systems in relation to their particulate content, as well as on plant development in these systems. In addition to air measurements, measurements were taken of the amount of PM deposited on the leaves and suspension system of LWS. This allowed the difference in PM resuspension and deposition between plant species to be investigated. The amount of deposited particulate matter was determined based on 'saturation isothermal remanent magnetisation' (SIRM), a measure of magnetisable particulate matter. This was possible because the added 'Arizona fine test dust' contained iron oxide. However, no significant difference was observed between the SIRM values measured before the wind tunnel experiment, after resuspension and after deposition. This suggested that the iron oxide content in the Arizona fine test dust was too low to measure a significant difference in the SIRM values on leaves after three hours. The plant species did give rise to different SIRM values ranging between 5 and 260 µ A. In particular, SIRM values above 26 µ A were observed for the plant species that were grouped due to their significantly higher accumulation of PM. 'Specific leaf area' (SLA), specifically the ratio of the one-sided 'fresh' leaf area to its dry mass, was the significant leaf characteristic. SLA correlated with leaf complexity. In particular, plant species with elongated leaves were characterized by low SLA, high FLS and high complexity and showed significantly higher SIRM values. Finally, the optimised size-resolved deposition model was also tested in an urban model to get an idea of the impact of a green wall on PM concentrations in a so-called 'street canyon'. These are narrow streets with high buildings on both sides, making air pollution more persistent. To this end, an ideal scenario was tested in which a green wall was introduced along both sides of the street over a length of about 270 m. The model result showed a decrease in PM2.5 and PM10 of 46 ± 12% and 52 ± 14%. This result is of course for a very optimal scenario where the green wall covers the entire building façades. Since this is not feasible in reality, other ways of promoting contact between green walls and polluted air can be explored. The insights obtained illustrate that the use of climbing plants can be a cost-effective and environmentally friendly solution to reduce PM concentrations. Moreover, the findings showed that models can be used to investigate the impact of green walls on PM levels. These findings fit within the broader context of designing healthy and sustainable urban environments and developing innovative solutions based on solid scientific knowledge.

Abstract: The development of porous metal materials with pore geometries and sizes at the nanoscale offers promising opportunities for the development of smart responsive interfaces for separation and catalytic applications and as building blocks for complex composite materials. Dealloying is an innovative technique based on selective removal of a sacrificial metal from a metal alloy to engineer surface textures and pores across significant thicknesses. Dealloyed structures may be processed over large scales and for a range of source alloys, offering unprecedented manufacturing opportunities. This review presents the operations and challenges of dealloying routes and discusses avenues for process optimizations and improvements, aiming at the development of scalable nanoporous materials. The potential of dealloyed materials for catalytic and sensing applications is expanded and benchmarked against reference materials. Future prospects and applications of dealloyed materials toward surface reactivity control and pore architecture development are highlighted.

Abstract: Phenols are considered as toxic pollutants and their discharge into the environment by industries is regulated by a concentration limit. As these limits are in the low mg L−1 to µg L−1-range, sensitive methods are necessary to detect these phenols. Here, aqueous industrial phenolic samples throughout a cleaning process were analyzed by two novel electrochemical sensors. Both the photoelectrochemical (PEC) sensor and the square wave voltammetric (SWV) sensor could successfully follow the decrease of the concentration of phenols along the industrial cleaning process. The discharge sample (μg L−1) could only be analyzed by the PEC sensor and not by the SWV sensor, as the phenolic concentration was close to the LOD of the latter. With HPLC-diode array detector (DAD) measurements, classical phenols such as phenol (PHOH), hydroquinone, resorcinol and o-cresol could be identified in the industrial samples, and their presence could be linked to the electrochemical responses. At last, the performance of the PEC and SWV sensors were compared with commercial colorimetric and chemical oxygen demand (COD) test kits. This comparison demonstrated the high sensitivity of the PEC sensor in the μg L−1 concentrated phenolic samples. Together with the identification of the redox peaks through HPLC-DAD analysis, the SWV sensor can be a powerful tool in the qualitative analysis of mg L−1 concentrated phenolic samples due to its speed, simplicity and absence of laborious sample pre-treatment steps.

Abstract: The increasing illicit production, distribution and abuse of amphetamine (AMP) poses a challenge for law enforcement worldwide. To effectively combat this issue, fast and portable tools for the on-site screening of suspicious samples are required. Electrochemical profile (EP)-based sensing of illicit drugs has proven to be a viable option for this purpose as it allows rapid voltammetric measurements via the use of disposable and low-cost graphite screen-printed electrodes (SPEs). In this work, a highly practical paraformaldehyde (PFA)-coated sensor, which unlocks the detectability of primary amines through derivatization, is developed for the on-site detection of AMP in seized drug samples. A potential interval was defined at the sole AMP peak (which is used for identification of the target analyte) to account for potential shifts due to fluctuations in concentration and temperature, which are relevant factors for on-site use. Importantly, it was found that AMP detection was not hindered by the presence of common diluents and adulterants such as caffeine, even when present in high amounts. When inter-drug differentiation is desired, a simultaneous second test with the same solution on an unmodified electrode is introduced to provide the required additional electrochemical information. Finally, the concept was validated by analyzing 30 seized AMP samples (reaching a sensitivity of 96.7 %) and comparing its performance to that of commercially available Raman and Fourier Transform Infrared (FTIR) devices.

Abstract: In the present work, the resolution and quantification of mixtures of different opiate compounds in the presence of common cutting agents using an electronic tongue (ET) is evaluated. More specifically, ternary mixtures of heroin, morphine and codeine were resolved in the presence of caffeine and paracetamol. To this aim, an array of three carbon screen-printed electrodes were modified with different ink-like solutions of graphite, cobalt (II) phthalocyanine and palladium, and their responses towards the different drugs were characterized by means of square wave voltammetry (SWV). Developed sensors showed a good performance with good linearity at the mu M level, LODs between 1.8 and 5.3 mu M for the 3 actual drugs, and relative standard deviation (RSD) ca. 2% for over 50 consecutive measurements. Next, a quantitative model that allowed the identification and quantification of the individual substances from the overlapped voltammograms was built using partial least squares regression (PLS) as the modeling tool. With this approach, quantification of the different drugs was achieved at the mu M level, with a total normalized root mean square error (NRMSE) of 0.084 for the test subset.

Abstract: This dissertation focuses on the materials and techniques used by the Brussels artists Michael Sweerts (1618-1664) and Michaelina Wautier (1614-1689). It tries to answer the following research questions: 1.Did 17th-century Brussels-based artists use idiosyncratic painting materials and techniques, and can their work be distinguished from paintings created in other artistic centers based on these materials and techniques? 2.How did Sweerts and Wautier influence each other’s work? In order to answer the research questions, a selection of relevant and representative paintings from Sweerts’ and Wautier’s oeuvre has been studied with MA-XRF scanning and microscopic examination. The results are discussed in volume 2 of this dissertation, and form the basis upon which the chapters in volume 1 are built. MA-XRF scanning is a non-destructive imaging technique based on the technique of X-ray fluorescence (XRF). The technique allows for the collection of elemental information about the materials present in a work of art. The work presented in this dissertation has shed more light on the working methods of Sweerts and Wautier. It has shown they both showed an openness and willingness to continue learning and developing as an artist. Wautier did not feel constrained to work only in one genre and apparently carried on developing her skills throughout her career, as evidenced by Flower Garland with Butterfly. She might have trained with a specialized artist to master their idiosyncratic working methods and this diverse genre. This suggests that Wautier had an interest in art education. Sweerts too had a passion for art education: he was involved in the drawing academy of Camillo Pamphilj in Rome, and later established his own academy for life drawing in Brussels. Sweerts’ work clearly shows the influence of his Italian contemporaries. Whilst living in Rome, he adapted his working methods to local customs such as working on brightly colored grounds. Wautier’s oeuvre shows that she was open to explore different genres and that she took inspiration from her contemporaries, including Theodoor van Loon and Daniël Seghers. In doing so, she furthered the development of different genres as she added original elements to her compositions. It is the conclusion of this dissertation that Michaelina Wautier can thus be considered one of the innovative artists of mid-17th-century Flemish painting, who inspired other artists in the Low Countries, including Michael Sweerts.

Abstract: MicroRNAs (miRNAs) are small oligonucleotides (18-25 bases) that play a key role in epigenetic regulation. Since the discovery of miRNAs in 1993, their role in biological processes has been extensively investigated. By now, it has been evidenced that monitoring and detection of miRNAs can improve (early) disease diagnosis. The existing diagnostic approaches have limitations such as the need for complex multistep protocols for sample preparation, analysis, data interpretation, high cost of equipment, the need for highly qualified personnel, and high laboratory standards. As opposed to this, point-of-care biosensors and chips aim to facilitate the procedure and avoid sending samples into centralized laboratories, which saves time, reduces the chance of sample degradation, and enables analysis of patient samples in remote areas, directly at home or primary and secondary care facilities (i.e. general practitioners and specialists). The latter is essential for therapy assessment and follow-up monitoring of patients with chronic diseases and cancer. Nevertheless, the development of such sensors is lagging compared to the projections of 10 – 20 years ago, mainly due to insufficient sensitivity, poor reproducibility, and the complexity of the sensors’ design reported in the research literature. This motivates the development of new detection strategies and technologies such as photoelectrochemical sensors that combine the best features of different sensing approaches. The primary concern when developing detection technologies for miRNA is the need for a highly sensitive and selective platform. This thesis explores a novel photoelectrochemical (PEC) method that is distinctive owing to its sensitive nature and simple and robust design. Firstly, we focused on the usage of recently emerging commercial gold-sputtered electrode systems for the detection of short nucleic acid with enzymatic amplification. Importantly, cleaning such electrodes is a challenge since the standard procedures known for regular disk electrodes such as polishing cannot be employed here, since it will damage the protective layer on the electrode. However, the electrodes can be washed and pretreated chemically and/or electrochemically. Thus, a procedure to effectively clean and modify the gold-sputtered electrode has been developed, resulting in high-performance gold-sputtered nucleic acid sensors. Next, the usage of molecular photosensitizers as an alternative to enzymatic amplification has been evaluated. We took advantage of the singlet oxygen production by photosensitizers upon photoexcitation, leading to a photocurrent response due to the singlet oxygen-induced (electro)chemical conversions. Following the demonstration of the detection strategy, the analytical performance of the sensing system was evaluated using magnetic beads-based nucleic acid assay on disposable electrode platforms, with a focus to enhance the sensitivity and robustness of the technique in detecting complementary nucleic acid targets. Following the fundamental evaluation of the singlet oxygen-based PEC detection of nucleic acids, we further optimized the assay and measurement parameters and employed the sensing strategy for a polymerase chain reaction-free (PCR-free) quantification of miRNAs related to prostate cancer. By successfully detecting and quantifying low-picomolar range concentrations (< 10 pM) in plasma samples from prostate cancer patients, we successfully showed the applicability of the novel sensing strategy. We have also compared and positioned the performance of our developed PEC strategy with an existing state-of-art technique, i.e. electrochemiluminescence (ECL). Our PEC strategy performed on par with ECL, both yielding low-picomolar detection limits in serum matrices, however quicker and cheaper than ECL. Owing to the versatility of this PEC technique, the final study explored its multiplexing capability. As a starting point in this branch of the research, we have investigated two possible ways for multiplexing. To perform multiple measurements at the same time, constructing calibration plots and quantifying unknown miRNA concentrations in patient samples at the same time, we have developed a high-throughput detection with 96X multi-channel electrode systems and in-house designed and constructed 96XLED illumination sources. Secondly, to detect more than one target miRNA in a single measurement, intra-vial multiplexing where the samples were analyzed for different targets in one vial was also explored. Altogether, this thesis presents the fundamentals, development and application of a novel PEC strategy for detecting short (< 25 bases) nucleic acid sequences, in particular, miRNA. With an aim to serve as a distinctive technique to function as a clinical testing platform without any need for PCR, this work adds value to the development of nucleic acid-based sensors for miRNAs and other short-stranded nucleic acid biomarkers, and benefits in the early detection of diseases like cancer.

Abstract: Photocatalytic acetaldehyde degradation exhibits satisfactory performance only at relatively low acetaldehyde flow rates, predominately below 10 × 10-3 mL/min, leaving ample room for improvement. Therefore, it is necessary to prepare more efficient photocatalysts for acetaldehyde degradation. Moreover, the impact of the interaction strength between the titania surface and surface water on the photocatalytic acetaldehyde efficiency is poorly understood. To address these issues, in this work a series of (0 0 1)-faceted anatase titania samples with various surface properties and structures were synthesized via a solvothermal method and tested at high acetaldehyde flow rates under UV light irradiation. With increasing solvothermal time, the pore volume, surface area, and the abundance of surface OH groups all increased, while the crystallite size decreased. These were all identified to be beneficial to promote the degradation performance. When the solvothermal temperature was 180 ℃ and the reaction time was 5 h, the prepared sample displayed the most efficient performance at 19.25× 10-3 mL/min of acetaldehyde (conversion of (74 ± 1)% versus (29 ± 1)% for P25), and achieved a 100 % conversion at 16 × 10-3 mL/min. A weaker interaction strength between surface water and the titania surface was found to improve the acetaldehyde adsorption capacity, thereby promoting the acetaldehyde degradation efficiency. The stability of the best performing sample was tested over 48 h, demonstrating a highly stable performance with no signs of deactivation. Even at a relative humidity of 30 %, the acetaldehyde conversion retains 82% of its efficiency in a dry atmosphere, highlighting its potential in practical applications.

Abstract: Supercapacitive biofuel cells' (SBFCs) most recent advancements are herein disclosed. In conventional SBFCs the biocomponent is employed as the pseudocapacitive component, while in self-charging biodevices it also works as the biocatalyst. The performance of different types of SBFCs are summarized according to the categorization based on the biocatalyst employed: supercapacitive microbial fuel cells (sMFCs), supercapacitive biophotovoltaics (SBPV) and supercapacitive enzymatic fuel cells (s-EFCs). SBFCs could be considered as promising 'alternative' energy devices (low-cost, environmentally friendly, and technically undemanding electric power sources etc.) being suitable for powering a new generation of miniaturized electronic applications.

Abstract: Using state-of-the-art simulation methods, we optimized the performance of nanoscale superconducting scanning probe tips for advanced spatial imaging of magnetic fields. The systematic studies of the tips’ static properties as a function of the tilted magnetic field, geometric parameters, and material parameters were carried out. The sensitivity of different superconducting quantum interference devices (SQUIDs) to the magnetic field emanating from the magnetic nanoparticle, where the location of a magnetic nanoparticle is considered below the primary loop's center, was examined as a function of the primary and secondary loop dimensions. The main objective of the research was to characterize and optimize the performance of a nano-sized SQUID-on-tip (SOT) device. Optimal SOT sensitivity was sought, for different loop sizes, arm linewidth, and lead dimensions. Moreover, we revealed that a constriction in the loop arms of the SOT can substantially improve the sensitivity of the device. Finally, the properties of the theta-SOT device were examined in the presence of in-plane and out-of-plane magnetic field components, enabling nanoscale imaging of 3D distributions of the magnetic field. Altogether, the obtained results deliver an engineering solution for the optimum performance of the SOT device in desired conditions.

Abstract: In this theoretical study, we assess the impact of a graphene capping layer on the resistivity of defective, extremely scaled interconnects. We investigate the effect of graphene capping on the electronic transport in ultrascaled interconnects, in the presence of grain boundary defects in the metal layer. We compare the results obtained using our quantum mechanical model to a simple parallel-conductor model and find that the parallel-conductor model does not capture the effect of the graphene cap correctly. At 0.5 nm metal thickness, the parallel-conductor model underestimates the conductivity by 3.0% to 4.0% for single-sided and double sided graphene capping, respectively.