Abstract: The use of microfluidic devices in the field of plasma-liquid interaction can unlock unique possibilities to investigate the effects of plasma-generated reactive species for environmental and biomedical applications. So far, very little simulation work has been performed on microfluidic devices in contact with a plasma source. We report on the modelling and computational simulation of physical and chemical processes taking place in a novel plasma-microfluidic platform. The main production and transport pathways of reactive species both in plasma and liquid are modelled by a novel modelling approach that combines 0D chemical kinetics and 2D transport mechanisms. This combined approach, applicable to systems where the transport of chemical species occurs in unidirectional flows at high Péclet numbers, decreases calculation times considerably compared to regular 2D simulations. It takes advantage of the low computational time of the 0D reaction models while providing spatial information through multiple plug-flow simulations to yield a quasi-2D model. The gas and liquid flow profiles are simulated entirely in 2D, together with the chemical reactions and transport of key chemical species. The model correctly predicts increased transport of hydrogen peroxide into the liquid when the microfluidic opening is placed inside the plasma effluent region, as opposed to inside the plasma region itself. Furthermore, the modelled hydrogen peroxide production and transport in the microfluidic liquid differs by less than 50% compared with experimental results. To explain this discrepancy, the limits of the 0D–2D combined approach are discussed.

Abstract: The structure-property relationship at interfaces is difficult to probe for thermoelectric materials with a complex interfacial microstructure. Designing thermoelectric materials with a simple, structurally-uniform interface provides a facile way to understand how these interfaces influence the transport properties. Here, we synthesized Bi2-xSbxTe3 (x = 0, 0.1, 0.2, 0.4) nanoflakes using a hydrothermal method, and prepared Bi2-xSbxTe3 thin films with predominantly (0001) interfaces by stacking the nanoflakes through spin coating. The influence of the annealing temperature and Sb content on the (0001) interface structure was systematically investigated at atomic scale using aberration-corrected scanning transmission electron microscopy. Annealing and Sb doping facilitate atom diffusion and migration between adjacent nanoflakes along the (0001) interface. As such it enhances interfacial connectivity and improves the electrical transport properties. Interfac reactions create new interfaces that increase the scattering and the Seebeck coefficient. Due to the simultaneous optimization of electrical conductivity and Seebeck coefficient, the maximum power factor of the Bi1.8Sb0.2Te3 nanoflake films reaches 1.72 mW m(-1) K-2, which is 43% higher than that of a pure Bi2Te3 thin film.

Abstract: Fine roots mediate plant nutrient acquisition and growth. Depending on soil nutrient availability, plants can regulate fine root biomass and morphological traits to optimise nutrient acquisition. Little is known, however, about the importance of these parameters influencing forest functioning. In this study, we measured root responses to nutrient additions to gain a mechanistic understanding of plant adaptations to nutrient limitation in two tropical forests in French Guiana, differing twofold in their soil nutrient statuses. We analysed the responses of root biomass, mean root diameter (RD), specific root length (SRL), specific root area (SRA), root tissue density (RTD) and carbon (C), nitrogen (N) and phosphorus (P) concentrations in roots down to 15 cm soil depth after three years of N and P additions. At the lower-fertility site Paracou, no changes in root biomass or morphological traits were detected with either N or P addition, although P concentrations in roots increased with P addition. In the higher fertility site, Nouragues, root biomass and P concentrations in roots increased with P addition, with no changes in morphological traits. In contrast, N addition shifted root traits from acquisitive to more conservative by increasing RTD. A significant interaction between N and P in Nouragues pointed to stronger responses to P addition in the absence of N. Our results suggest that the magnitude and direction of root biomass and trait expression were regulated by soil fertility, corroborated by the response to N or P additions. At low fertility sites, we found lower plasticity in root trait expression compared to more fertile conditions, where N and P additions caused stronger and antagonistic responses. Identifying the exact role of mechanisms affecting root nutrient uptake in Amazon forests growing in different soils will be crucial to foresee if and how rapid global changes can affect their carbon allocation.

Abstract: Density functional theory is widely used to gain insights into molecule−metal surface reaction networks, which is important for a better understanding of catalysis. However, it is well-known that generalized gradient approximation (GGA)
density functionals (DFs), most often used for the study of reaction networks, struggle to correctly describe both gas-phase molecules and metal surfaces. Also, GGA DFs typically underestimate reaction barriers due to an underestimation of the selfinteraction energy. Screened hybrid GGA DFs have been shown to reduce this problem but are currently intractable for wide usage. In this work, we use a more affordable meta-GGA (mGGA) DF in combination with a nonlocal correlation DF for the first time to study and gain new insights into a catalytically important surface
reaction network, namely, CO2 hydrogenation on Cu. We show that the mGGA DF used, namely, rMS-RPBEl-rVV10, outperforms typical GGA DFs by providing similar or better predictions for metals and molecules, as well as molecule−metal surface adsorption
and activation energies. Hence, it is a better choice for constructing molecule−metal surface reaction networks.

Abstract: The electroreduction of carbon dioxide (eCO2RR) to CO using Ag nanoparticles as an electrocatalyst is promising as an industrial carbon capture and utilization (CCU) technique to mitigate CO2 emissions. Nevertheless, the long-term stability of these Ag nanoparticles has been insufficient despite initial high Faradaic efficiencies and/or partial current densities. To improve the stability, we evaluated an up-scalable and easily tunable synthesis route to deposit low-weight percentages of Ag nanoparticles (NPs) on and into the framework of a nitrogen-doped ordered mesoporous carbon (NOMC) structure. By exploiting this so-called nanoparticle confinement strategy, the nanoparticle mobility under operation is strongly reduced. As a result, particle detachment and agglomeration, two of the most pronounced electrocatalytic degradation mechanisms, are (partially) blocked and catalyst durability is improved. Several synthesis parameters, such as the anchoring agent, the weight percentage of Ag NPs, and the type of carbonaceous support material, were modified in a controlled manner to evaluate their respective impact on the overall electrochemical performance, with a strong emphasis on operational stability. The resulting powders were evaluated through electrochemical and physicochemical characterization methods, including X-ray diffraction (XRD), N2-physisorption, Inductively coupled plasma mass spectrometry (ICP-MS), scanning electron microscopy (SEM), SEM-energy-dispersive X-ray spectroscopy (SEM-EDS), high-angle annular dark field scanning transmission electron microscopy (HAADF-STEM), STEM-EDS, electron tomography, and X-ray photoelectron spectroscopy (XPS). The optimized Ag/soft-NOMC catalysts showed both a promising selectivity (∼80%) and stability compared with commercial Ag NPs while decreasing the loading of the transition metal by more than 50%. The stability of both the 5 and 10 wt % Ag/soft-NOMC catalysts showed considerable improvements by anchoring the Ag NPs on and into a NOMC framework, resulting in a 267% improvement in CO selectivity after 72 h (despite initial losses) compared to commercial Ag NPs. These results demonstrate the promising strategy of anchoring Ag NPs to improve the CO selectivity during prolonged experiments due to the reduced mobility of the Ag NPs and thus enhanced stability.

Abstract: Recent experiments have revealed that the macroscopic Kelvin equation remains surprisingly accurate even for nanoscale capillaries. This phenomenon was so far explained by the oscillatory behavior of the solid−liquid interfacial free energy. We here demonstrate thermodynamic and capillarity inconsistencies with this explanation. After revising the Kelvin equation, we ascribe its validity at nanoscale confinement to the effect of disjoining pressure.
To substantiate our hypothesis, we employed molecular dynamics simulations to evaluate interfacial heat transfer and wetting properties. Our assessments unveil a breakdown in a previously established proportionality between the work of adhesion and the Kapitza conductance at capillary heights below 1.3 nm, where the dominance of the work of adhesion shifts primarily from energy to entropy. Alternatively, the peak density of the initial water layer can effectively probe the work of adhesion. Unlike under bulk conditions, high confinement renders the work of adhesion entropically unfavorable.

Abstract: Oligomerized [Cu-O-Cu] species are reported to be efficient in promoting plasma catalytic one-step steam reforming of methane to methanol and hydrogen, achieving 6.8% CH4 conversion and 73.1% CH3OH selectivity without CO2.

Abstract: Optical hyperspectral cameras capture the spectral reflectance of materials. Since many materials behave as heterogeneous intimate mixtures with which each photon interacts differently, the relationship between spectral reflectance and material composition is very complex. Quantitative validation of spectral unmixing algorithms requires high-quality ground truth fractional abundance data, which are very difficult to obtain. In this work, we generated a comprehensive laboratory ground truth dataset of intimately mixed mineral powders. For this, five clay powders (Kaolin, Roof clay, Red clay, mixed clay, and Calcium hydroxide) were mixed homogeneously to prepare 325 samples of 60 binary, 150 ternary, 100 quaternary, and 15 quinary mixtures. Thirteen different hyperspectral sensors have been used to acquire the reflectance spectra of these mixtures in the visible, near, short, mid, and long-wavelength infrared regions (350-15385) nm. Overlaps in wavelength regions due to the operational ranges of each sensor and variations in acquisition conditions resulted in a large amount of spectral variability. Ground truth composition is given by construction, but to verify that the generated samples are sufficiently homogeneous, XRD and XRF elemental analysis is performed. We believe these data will be beneficial for validating advanced methods for nonlinear unmixing and material composition estimation, including studying spectral variability and training supervised unmixing approaches. The datasets can be downloaded from the following link: https://github.com/VisionlabHyperspectral/Multisensor_datasets.

Abstract: The interface heat transfer of two layers induced by van der Waals (vdW) contacts is theoretically investigated, based on first-principles calculations at low temperatures. The results suggest that out-of-plane acoustic phonons with low frequencies dominate the interface thermal transport due to the vdW interaction. The interface thermal conductivity is proportional to the cubic of temperature at very low temperatures, but becomes linearly proportional to temperature as temperature increases. We show that manipulating the strain alters vdW coupling, leading to increased interfacial thermal conductivity at the interface. Our findings provide valuable insights into the interface heat transport in vdW heterostructures and support further design and optimization of electronic and optoelectronic nanodevices based on vdW contacts. The heat transfer induced by van der Waals contacts is dominated by ZA phonons. The interface thermal conductivity is proportional to the cubic of temperature, but becomes linearly proportional to temperature as temperature increases.

Abstract: Molecular dynamics simulations are essential for a better understanding of dissociative chemisorption on metal surfaces, which is often the rate-controlling step in heterogeneous and plasma catalysis. The workhorse quasi-classical trajectory approach ubiquitous in molecular dynamics is able to accurately predict reactivity only for high translational and low vibrational energies. In contrast, catalytically relevant conditions generally involve low translational and elevated vibrational energies. Existing quantum dynamics approaches are intractable or approximate as a result of the large number of degrees of freedom present in molecule−metal surface reactions. Here, we extend a ring polymer molecular dynamics approach to fully include, for the first time, the degrees of freedom of a moving metal surface. With this approach, experimental sticking probabilities for the dissociative chemisorption of methane on Pt(111) are reproduced for a large range of translational and vibrational energies by including nuclear quantum effects and employing full-dimensional simulations.

Abstract: The basal plane of graphene can function as a selective barrier that is permeable to protons but impermeable to all ions and gases, stimulating its use in applications such as membranes, catalysis and isotope separation. Protons can chemically adsorb on graphene and hydrogenate it, inducing a conductor–insulator transition that has been explored intensively in graphene electronic devices. However, both processes face energy barriersand various strategies have been proposed to accelerate proton transport, for example by introducing vacancies, incorporating catalytic metalsor chemically functionalizing the lattice. But these techniques can compromise other properties, such as ion selectivity or mechanical stability. Here we show that independent control of the electric field,<italic>E</italic>, at around 1 V nm⁻¹, and charge-carrier density,<italic>n</italic>, at around 1 × 10¹⁴ cm⁻², in double-gated graphene allows the decoupling of proton transport from lattice hydrogenation and can thereby accelerate proton transport such that it approaches the limiting electrolyte current for our devices. Proton transport and hydrogenation can be driven selectively with precision and robustness, enabling proton-based logic and memory graphene devices that have on–off ratios spanning orders of magnitude. Our results show that field effects can accelerate and decouple electrochemical processes in double-gated 2D crystals and demonstrate the possibility of mapping such processes as a function of<italic>E</italic>and<italic>n</italic>, which is a new technique for the study of 2D electrode–electrolyte interfaces.

Abstract: Metal halide perovskite (MHP) quantum dots (QDs) offer immense potential for several areas of photonics research due to their easy and low-cost fabrication and excellent optoelectronic properties. However, practical applications of MHP QDs are limited by their poor stability and, in particular, their tendency to aggregate. Here, we develop a two-step double-solvent strategy to grow and confine CsPbBr3 QDs within the three-dimensional (3D) cavities of a mesoporous SBA-16 silica scaffold (CsPbBr3@SBA-16). Strong confinement and separation of the MHP QDs lead to a relatively uniform size distribution, narrow luminescence, and good ambient stability over 2 months. In addition, the CsPbBr3@SBA-16 presents a high activity and stability for visible-light-driven photocatalytic toluene C(sp(3))-H bond activation to produce benzaldehyde with similar to 730 mu mol g(-1) h(-1) yield rate and near-unity selectivity. Similarly, the structural stability of CsPbBr3@SBA-16 QDs is superior to that of both pure CsPbBr3 QDs and those confined in MCM-41 with 1D channels.

Abstract: Urine nitrification is pH-sensitive due to limited alkalinity and high residual ammonium concentrations. This study aimed to investigate how the pH affects nitrogen conversion and the microbial community of urine nitrification with a pH-based feeding strategy. First, kinetic parameters for NH3, HNO2, and NO2– limitation and inhibition were determined for nitrifiers from a urine nitrification reactor. The turning point for ammonia-oxidizing bacteria (AOB), i.e., the substrate concentration at which a further increase would lead to a decrease in activity due to inhibitory effects, was at an NH3 concentration of 12 mg-N L–1, which was reached only at pH values above 7. The total nitrite turning point for nitrite-oxidizing bacteria (NOB) was pH-dependent, e.g., 18 mg-N L–1 at pH 6.3. Second, four years of data from two 120 L reactors were analyzed, showing that stable nitrification with low nitrite was most likely between pH 5.8 and 6.7. And third, six 12 L urine nitrification reactors were operated at total nitrogen concentrations of 1300 and 3600 mg-N L–1 and pH values between 2.5 and 8.5. At pH 6, the AOB Nitrosomonas europaea was found, and the NOB belonged to the genus Nitrobacter. At pH 7, nitrite accumulated, and Nitrosomonas halophila was the dominant AOB. NOB were inhibited by HNO2 accumulation. At pH 8.5, the AOB Nitrosomonas stercoris became dominant, and NH3 inhibited NOB. Without influent, the pH dropped to 2.5 due to the growth of the acid-tolerant AOB “Candidatus Nitrosacidococcus urinae”. In conclusion, pH is a decisive process control parameter for urine nitrification by influencing the selection and kinetics of nitrifiers.

Abstract: Today, illicit drugs are omnipresent in society. Clandestine markets are growing faster than ever before, record amounts of cocaine are seized in seaports and airports, while the associated violence is spiralling out of control. In addition, drug monitoring centres worldwide are warning for the increasing complexity of the drug markets, as the traditionally popular drugs are joined by countless new synthetic variants, while medical drugs are also increasingly being abused. In order to provide services confronted with illicit drug samples (police, customs, forensic scientists, first responders, …) with important information on the identity of an unknown sample, suitable analytical tests are required. While these exist for laboratory environments, on-site applicable tests are important to accelerate the decision-making process. Electrochemical sensors have all the advantages required for such on-site tests: they are fast, portable, easy-to-use and reliable. Furthermore, they are not influenced by colours, which are frequently added to drug samples to deceive the existing tests. Previous work has mainly focussed on the detection of a single drug per analysis. However, many drugs could be encountered due to the diversity of the drug markets. Therefore, this project developed electrochemical strategies for the detection of multiple drugs simultaneously. First, the electrochemical behaviour of the individual drugs was studied in different measuring conditions (assessing the influence of pH, concentration and temperature). Then, all findings and strategies were combined to detect multiple targets simultaneously. An electrochemical sensor was developed for the four most popular drugs at music festivals: cocaine, MDMA, amphetamine and ketamine. This sensor generates a so-called ‘superfingerprint’ of the sample, which is then automatically interpreted by a developed algorithm in order to produce a straightforward output. Finally, a pill analysis sensor was developed in the context of drug checking services, where a consumer can anonymously have a sample chemically analysed to obtain information on the composition, dose and potentially harmful additives. The sensor achieved an outstanding accuracy in identifying the main component and provided the option to quantify, as well as an indication on the presence of other substances in the sample. The project’s findings demonstrate the potential for electrochemistry in illicit drug detection and provide a basis for the development of new sensors, targeting other drug combinations.

Abstract: In a world increasingly reliant on alternative energy sources, the quest for efficient and secure storage solutions is paramount. This doctoral thesis explores the exciting potential of a familiar material – water – to act as a vault for next-generation energy sources like hydrogen (H2) and methane (CH4). Nature offers a solution in the form of clathrate hydrates, fascinating cage-like structures formed from water molecules that can trap these gas molecules within their framework. This research investigates on improving the formation kinetics and gas storage capabilities of clathrate hydrates utilizing porous materials and the interstitial space between non-porous materials to augment the contact between gas and water thereby catalysing the growth of hydrates and unlocking their full potential as efficient and secure energy storage reservoirs. A key outcome of this research is the formulation of an empirical correlation, offering predictive insights into CH4 hydrate phase equilibrium conditions. Innovative approaches utilizing thermally conductive beads have yielded substantial enhancements in CH4 uptake. Furthermore, the identification of optimal water content within porous materials showcases a pathway to maximize CH4 storage capacity and hydrate growth kinetics. In the domain of hydrogen storage, attention is also directed towards unstirred systems, where the integration of functionalized porous materials has demonstrated a significant improvement in the rate of hydrate formation and the overall H2 storage capacity. A noteworthy achievement of this research lies in the successful storage of H2 within confined CH4 hydrates through a gas exchange process and the preliminary results show the potential for safer and more sustainable method for H2 storage at mild thermodynamic conditions, offering promising prospects for future energy systems.