Abstract: Metal–organic framework (MOF)-74 is known for its effectiveness in selectively capturing carbon dioxide (CO2). Especially the Zn and Cu versions of MOF-74 show high efficiency of this material for CO2. However, the activation of this MOF, which is a crucial step for its utilization, is so far not well understood. Here, we are closing the knowledge gap by examining the activation using, for the first time in the MOF, three-dimensional electron diffraction (3DED) during in situ heating. The use of state-of-the-art direct electron detectors enables rapid acquisition and minimal exposure times, therefore minimizing beam damage to the very electron beam-sensitive MOF material. The activation process of Zn-MOF-74 and Cu-MOF-74 is systematically studied in situ, proving the creation of open metal sites. Differences in thermal stability between Zn-MOF-74 and Cu-MOF-74 are attributed to the strength of the metal–oxygen bonds and Jahn–Teller distortions. In the case of Zn-MOF-74, we observe previously unknown remaining electrostatic potentials inside the MOF pores, which indicate the presence of remaining atoms that might impede gas flow throughout the structure when using the MOF for absorption purposes. We believe our study exemplifies the significance of employing advanced characterization techniques to enhance our material understanding, which is a crucial step for unlocking the full potential of MOFs in various applications.

Abstract: Regenerative life support systems (RLSS) will play a vital role in achieving self-sufficiency during long-distance space travel. Urine conversion into a liquid nitrate-based fertilizer is a key process in most RLSS. This study describes the effects of simulated microgravity (SMG) on Comamonas testosteroni, Nitrosomonas europaea, Nitrobacter winogradskyi and a tripartite culture of the three, in the context of nitrogen recovery for the Micro-Ecological Life Support System Alternative (MELiSSA). Rotary cell culture systems (RCCS) and random positioning machines (RPM) were used as SMG analogues. The transcriptional responses of the cultures were elucidated. For CO2-producing C. testosteroni and the tripartite culture, a PermaLifeTM PL-70 cell culture bag mounted on an in-house 3D-printed holder was applied to eliminate air bubble formation during SMG cultivation. Gene expression changes indicated that the fluid dynamics in SMG caused nutrient and O2 limitation. Genes involved in urea hydrolysis and nitrification were minimally affected, while denitrification-related gene expression was increased. The findings highlight potential challenges for nitrogen recovery in space.

Abstract: The European BorderSens project leverages voltammetric sensors, developed with end-users' input, to rapidly and accurately detect illicit drugs. By embracing practicalities and validation, this technology has the potential to combat the illicit drug problem.

Abstract: In Europe, NACE codes are used for the official classification of sectors, however, the circular economy is not sufficiently captured in this classification. Therefore, this paper improves previous attempts for defining circular activities and jobs by web scraping techniques applied to each company in Belgium. We analyze their first, second, and third official NACE codes and compare these to the NACE codes they should have been allocated to according to the web scraping data. Subsequently, we calculate circularity scores for every sector to construct an indicator for the number of circular companies and jobs. The results show that the number of circular companies is lower than the baseline from official statistics when we only consider the companies' first and main NACE code. The estimates are higher than the baseline when we also take the second and third NACE codes into account and the estimated number of circular jobs is far higher than the baseline. This research upgrades previous classifications of circular sectors and demonstrates how web scraping and novel data might improve our understanding and capacity to build data. Based on the results in this paper, we recommend a uniform data collection such as reporting standards, and an inclusion of all circular strategies in sectoral classifications.

Abstract: Plasma medicine has attracted tremendous interest in a variety of medical conditions, ranging from wound healing to antimicrobial applications, even in cancer treatment, through the interactions of cold atmospheric plasma (CAP) and various biological tissues directly or indirectly. The underlying mechanisms of CAP treatment are still poorly understood although the oxidative effects of CAP with amino acids, peptides, and proteins have been explored experimentally. In this study, machine learning (ML) technology is introduced to efficiently unveil the interaction mechanisms of amino acids and reactive oxygen species (ROS) in seconds based on the data obtained from the reactive molecular dynamics (MD) simulations, which are performed to probe the interaction of five types of amino acids with various ROS on the timescale of hundreds of picoseconds but with the huge computational load of several days. The oxidative reactions typically start with H-abstraction, and the details of the breaking and formation of chemical bonds are revealed; the modification types, such as nitrosylation, hydroxylation, and carbonylation, can be observed. The dose effects of ROS are also investigated by varying the number of ROS in the simulation box, indicating agreement with the experimental observation. To overcome the limits of timescales and the size of molecular systems in reactive MD simulations, a deep neural network (DNN) with five hidden layers is constructed according to the reaction data and employed to predict the type of oxidative modification and the probability of occurrence only in seconds as the dose of ROS varies. The well-trained DNN can effectively and accurately predict the oxidative processes and productions, which greatly improves the computational efficiency by almost ten orders of magnitude compared with the reactive MD simulation. This study shows the great potential of ML technology to efficiently unveil the underpinning mechanisms in plasma medicine based on the data from reactive MD simulations or experimental measurements. In this study, since reactive molecular dynamics simulation can currently only describe interactions between a few hundred atoms in a few hundred picoseconds, deep neural networks (DNN) are introduced to enhance the simulation results by predicting more data efficiently. image

Abstract: Restoration of drained peatlands through rewetting has recently emerged as a prevailing strategy to mitigate excessive greenhouse gas emissions and re-establish the vital carbon sequestration capacity of peatlands. Rewetting can help to restore vegetation communities and biodiversity, while still allowing for extensive agricultural management such as paludiculture. Belowground processes governing carbon fluxes and greenhouse gas dynamics are mediated by a complex network of microbial communities and processes. Our understanding of this complexity and its multi-factorial controls in rewetted peatlands is limited. Here, we summarize the research regarding the role of soil microbial communities and functions in driving carbon and nutrient cycling in rewetted peatlands including the use of molecular biology techniques in understanding biogeochemical processes linked to greenhouse gas fluxes. We emphasize that rapidly advancing molecular biology approaches, such as high-throughput sequencing, are powerful tools helping to elucidate the dynamics of key biogeochemical processes when combined with isotope tracing and greenhouse gas measuring techniques. Insights gained from the gathered studies can help inform efficient monitoring practices for rewetted peatlands and the development of climate-smart restoration and management strategies.

Abstract: Tropical rainforests host an exceptional biodiversity and play a fundamental role in the regulation of global climatic cycles. Soil fungi and bacteria are key players in the transformation and processing of nutrients in terrestrial ecosystems while having an essential role as tree mutualists or antagonists. Still, there are gaps in our understanding of the main variables driving soil microbes on these forests and it is unclear how future climate change scenarios may impact soil microbes and further affect the ecosystem. In this thesis, we first explored the drivers of the microbial community composition in two pristine forests in French Guiana by using amplicon DNA sequencing. The neighboring tree species were found to be a crucial factor influencing the fungal and bacterial community composition at our sites regardless of the season. Additionally, within the environmental factors explored, soil moisture, phosphorus (P) and nitrogen (N) availability were consistently the main soil properties controlling the composition of soil microbial communities. Secondly, as increased nutrient deposition due to anthropogenic activities are expected to affect tropical forests ecosystems N and P availability, a factorial N and P nutrient addition experiment in the same sites was used to assess the effects of changes in the soil nutrient stoichiometry on the soil microbial communities. These results showed that after 3 years of nutrient additions, the bacterial and fungal community composition was affected by both the N and P additions. Besides, the fungal community composition had a stronger response to the nutrient addition, especially when P was added. Moreover, when the nutrient addition effect was assessed in bacteria and fungi with different life strategies, we found different nutrient optima between them. Furthermore, to study the effect of the connection to an existing mycorrhizal mycelium on tree seedlings, I established a mycelium exclusion experiment. Interestingly, we could not detect an effect of the mycorrhizal mycelium exclusion on the seedling N uptake, performance, or fungal community composition in roots after one year. All together this work provides a deeper understanding of the factors influencing the soil microbial communities on these lowland tropical forests, demonstrating that the tree community composition exerts a higher influence on the soil microbial community composition than previously expected. Moreover, our results show that the fungal and bacterial community composition and its relationship with trees in the vicinity is highly dependent on the ecosystem nutrient availability.

Abstract: Acoustic plasmons in graphene exhibit strong confinement induced by a proximate metal surface and hybridize with phonons of transition metal dichalcogenides (TMDs) when these materials are combined in a van der Waals heterostructure, thus forming screened graphene plasmon-phonon polaritons (SGPPPs), a type of acoustic mode. While SGPPPs are shown to be very sensitive to the dielectric properties of the environment, enhancing the SGPPPs coupling strength in realistic heterostructures is still challenging. Here we employ the quantum electrostatic heterostructure model, which builds upon the density functional theory calculations for monolayers, to show that the use of a metal as a substrate for graphene-TMD heterostructures (i) vigorously enhances the coupling strength between acoustic plasmons and the TMD phonons, and (ii) markedly improves the sensitivity of the plasmon wavelength on the structural details of the host platform in real space, thus allowing one to use the effect of environmental screening on acoustic plasmons to probe the structure and composition of a van der Waals heterostructure down to the monolayer resolution.

Abstract: We explore the effect of thickness, magnetization direction, strain, and gating on the topological quantum phase transition of a thin-film magnetic topological insulator. Reducing the film thickness to the ultrathin regime couples the edge states on the two surfaces, opening a gap known as the hybridization gap, and causing a phase transition from a topological insulator to a normal insulator (NI). An out-of-plane/in-plane magnetization of size proportional to the hybridization gap triggers a phase transition from a normal insulator state to a quantum anomalous Hall (QAH)/semimetal state. A magnetization tilt by angle 0 from the out-of-plane axis influences the topological phase transition in a way that for sufficiently large 0, no phase transition from NI to QAH can be observed regardless of the sample thickness or magnetization, and for 0 close to pi /2 the system transits to a semimetal phase. Furthermore, we demonstrate that compressive/tensile strain can be used to decrease/increase the magnetization threshold for the topological phase transition. Finally, we reveal the effect of a vertical potential acting on the film, be it due to the substrate or applied gating, which breaks inversion symmetry and raises the magnetization threshold for the transition from NI to QAH state.

Abstract: Cu is one of the most promising materials as an electrocatalyst for the nitrate reduction reaction (NO3RR) to ammonia, a reaction that can simultaneously remove nitrates from wastewater and produce ammonia, a high-value commodity chemical. However, a rational approach to catalyst design is lacking, limiting efficient catalyst optimization. In this work, we propose a way to synthesize monodisperse, polycrystalline Cu NPs with small variances in size by changing the carbon chain length of the phosphonic acid-based ligand. Cu NPs with 8.3, 10.0, and 11.9 nm diameters are successfully synthesized, and high-resolution electron microscopy and tomography are used to characterize these NPs in depth. By isolating Cu NP size as a parameter, we can unequivocally establish its effect on electrochemical performance for the NO3RR to ammonia under optimal operating conditions for the catalyst (0.1 M KOH electrolyte at -1.25 V vs RHE, as established in the first phase). The smallest Cu NPs (8.3 nm with a TDPA ligand) perform best, achieving Faradaic efficiencies (FEs) of 85.4% and absolute current densities of similar to 250 mA cm(-2), with increasing current densities and constant FEs as the particle size decreases. To allow for a rational approach to Cu-based catalyst design from a stability perspective, this work completed a first study of the main degradation pathway that the Cu NPs undergo during NO3RR. High-resolution electron microscopy and tomography are used to characterize the particles at various stages of the reaction. The NPs undergo agglomeration, pulverization, and particle detachment due to the reaction, starting at a particle size of 8.3 nm and progressively getting smaller, but leveling off, until a NP size of 2.6 nm is reached after 2 h of electrolysis. This decrease in NP size goes paired with a decrease in FE from 83% after the first 15 min to 74% after 2 h at -0.75 V vs RHE, despite the increase in active surface area. These insights into the most prominent degradation mechanisms allow for rational adjustments to future catalysts to combat these changes; for example, by embedding NPs in a tailored support, morphological degradation could be impeded. Therefore, these insights allow for a rational approach to the improvement of the stability of Cu-based catalysts for the NO3RR, a very important but often an overlooked aspect of catalyst design.

Abstract: The illicit drug market has been constantly evolving in the last decades, with a significant rise in counterfeit medicines posing serious public health risks. Benzodiazepines (BZDs) such as alprazolam (generally sold under the brand name Xanax), have particularly become the target of counterfeiting efforts due to their addictive nature and upsurge of unregulated designer BZDs. These counterfeit versions frequently resemble legitimate products but contain harmful adulterants or other potent illicit substances. Few methods have been developed to tackle counterfeit pills, usually limited to accurate and sophisticated laboratory equipment. This study explores the feasibility of combining electrochemical fingerprinting with data analysis to overcome the limitations of traditional methods. First, the electrochemical behavior of selected BZDs is studied, and analytical parameters such as pH are optimized. Then, the electroanalysis of common adulterants and illicit drugs is addressed and integrated into a user-friendly app, including a flowchart system. The proposed electrochemical strategy enables the detection of counterfeit Xanax by identifying the presence or absence of alprazolam. It also allows determination of the alprazolam content within a pill while meeting the fundamental requirements of the end users. This study represents an on-site methodology to address the growing challenges posed by BZDs, easily transferable to counterfeit medicines from other drug groups.

Abstract: The emerging reductive catalytic fractionation biorefinery which is currently under development aims to convert woody biomass efficiently into high-value products. Despite its potential, the environmental consequences of its implementation are not well known. Therefore, a forward-looking consequential life cycle assessment examines greenhouse gas emissions associated with its products (pulp, phenolic monomers, and oligomers) compared to alternative market options. Findings indicate that current greenhouse gas emissions exceed those of the existing alternatives, with by-products and the gaseous waste stream as major contributors. Process adaption to (i) produce higher-valued products (bleached pulps, phenols, and propylene) and (ii) incinerate gaseous waste stream for energy are proposed, potentially reducing emissions by up to 50 %, outperforming alternative options. Compared to land-based transportation, waterways can increase feedstock availability by up to 1000 km without an increase in emissions. In conclusion, the consequential approach provides valuable insights for enhancing and optimizing the environmental performance of the process.

Abstract: This study reports the impact of film microstructure and composition on the Young’s modulus and residual stress in nanocrystalline diamond (NCD) thin films ( thick) grown on silicon substrates using a linear antenna microwave plasma-enhanced chemical vapor deposition (CVD) system. Combining laser acoustic wave spectroscopy to determine the elastic properties with simple wafer curvature measurements, a straightforward method to determine the intrinsic stress in NCD films is presented. Two deposition parameters are varied: (1) the substrate temperature from 400 °C to 900 °C, and (2) the [P]/[C] ratio from 0 ppm to 8090 ppm in the H2/CH4/CO2/PH3 diamond CVD plasma. The introduction of PH3 induces a transition in the morphology of the diamond film, shifting from NCD with larger grains to ultra-NCD with a smaller grain size, concurrently resulting in a decrease in Young’s modulus. Results show that the highest Young’s modulus of (113050) GPa for the undoped NCD deposited at 800 °C is comparable to single crystal diamond, indicating that NCD with excellent mechanical properties is achievable with our process for thin diamond films. Based on the film stress results, we propose the origins of tensile intrinsic stress in the diamond films. In NCD, the tensile intrinsic stress is attributed to larger grain size, while in ultra-NCD films the tensile intrinsic stress is due to grain boundaries and impurities.

Abstract: Transport measurements are readily used to probe different phases in disordered topological insulators (TIs), where determining topological invariants explicitly is challenging. On that note, universal conductance fluctuations (UCF) theory asserts the conductance G for an ensemble has a Gaussian distribution, and that standard deviation 8G depends solely on the symmetries and dimensions of the system. Using a real-space tight -binding Hamiltonian on a system with Anderson disorder, we explore conductance fluctuations in a thin Bi2Se3 film and demonstrate the agreement of their behavior with UCF hypotheses. We further show that magnetic field applied out-of-plane breaks the time -reversal symmetry and transforms the system's Wigner-Dyson class from root symplectic to unitary, increasing 8G by 2. Finally, we reveal that while Bi2Se3 is a strong TI, weak TI and metallic phases can be stabilized in presence of strain and disorder, and detected by monitoring the conductance fluctuations.

Abstract: The global challenge posed by increasing levels of greenhouse gases and the associated detrimental impacts of global warming necessitate a strategic shift from traditional fossil fuel-based energy systems to more sustainable, renewable, and circular energy and material solutions. Consequently, the potential of photoactive nanoparticles, particularly those that harness light-driven processes, has captured extensive scientific interest as a viable approach to mitigating energy and environmental challenges on a global scale. Although, the adoption of solar light based solutions in the chemical industry has been very less due to sluggish reaction rates and its cascading effects on its economics. The primary focus of this dissertation is the study of plasmonic metal nanoparticles and metal oxide nanoparticles, emphasizing their applications in light-driven energy conversion. The distinctive properties of plasmonic materials, especially surface plasmon resonance (SPR), are pivotal in these applications. SPR involves the oscillation of electron clouds at the surface of nanoparticles when resonating with incident electromagnetic radiation, significantly enhancing solar radiation absorption. This feature is crucial for addressing the limitations of semiconductor photocatalysts like TiO2, which typically exhibit restricted absorption of solar irradiation. The objective of this dissertation is to further optimize the plasmonic enhancement mechanisms by strategically tuning the interactions between plasmonic nanoparticles and TiO2. This is achieved through the development of core-shell nanostructures and the self-assembly of supraparticles, designed to enhance plasmonic photocatalytic systems. The dissertation begins by elucidating the basic concepts and ideations behind the construction of these nanostructures and their roles in enhancing plasmonic photocatalysis, focusing on mechanisms such as near-electric field enhancement, electron transfer, and enhanced photon absorption. To achieve these objectives, modified synthesis techniques were developed to fabricate novel Au@TiO2 core-shell structures with precisely controlled TiO2 shell thickness and self-assembled Au-TiO2 supraparticles with variable sizes. The thesis further delves into the structural characterization of these synthesized nanoparticles, introducing both basic and advanced electron microscopy techniques. For the specific applications of these structures, it was found that Au@TiO2 core-shell nanoparticles with an optimal 4nm TiO2 shell thickness show significant enhancement in the hydrogen evolution reaction. Additionally, the largest Au-TiO2 supraparticles demonstrate superior efficacy in hydrogen peroxide generation. This work not only deepens the scientific understanding of plasmonic materials but also contributes to the development of renewable energy materials.