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: Digital disconnection has emerged as a concept describing the actions people take to limit their digital connectivity to enhance their well-being. To date, evidence on its effectiveness is mixed, leading to calls for greater consideration of why, how, when, and for whom digital disconnection works. This article responds to these calls, presenting a framework that differentiates four key harms that contribute to experiences of digital ill-being (time displacement, interference, role blurring, and exposure effects). Using these four harms as a starting point, the framework explains: (1) why people are motivated to digitally disconnect; (2) how specific disconnection strategies (i.e., placing limits on time, access, channels, and contents, interactions and features) may help them; and for whom (3) and under which conditions (when) these strategies can be effective.

Abstract: Activated carbon (AC) materials from renewable sources are widely used in electrochemical applications due to their well‐known high surface area. However, their application as electrode material in double‐layer electrochemical devices may be limited due to their relatively low electrical conductivity and lightweight. To overcome these limitations, the incorporation of pseudocapacitance metal oxide nanoparticles is an optimum approach. These nanoparticles can provide a second energy storage mechanism to the composite, mitigating the loss of surface area associated with their incorporation. As a result, the composite material is endowed with increased conductivity and higher density, making it more suitable for practical implementation in real devices. In this study, we have incorporated a fine dispersion of 1 % of MnO clusters into a highly porous activated carbon synthesized from walnut shells (WAC). The high‐resolution electron microscopy studies, combined with their related analytical techniques, allow us to determine the presence of the cluster within the matrix carbon precisely. The resulting MnO@WAC composite demonstrated significantly improved capacitive behavior compared with the WAC material, with increased volumetric capacitance and higher charge retention at higher current densities. The composite‘s electrochemical performance suggests its potential as a promising electrode material for supercapacitors, addressing drawbacks associated with traditional AC materials.

Abstract: Extension professionals are expected to help disseminate agricultural technologies, information, knowledge and skills to farmers. In order to develop valuable and long-lasting extension services, it is essential to understand the methods of extension that farmers find most beneficial. This understanding helps adopt improved practices, overcome barriers, provide targeted interventions and continuously improve agricultural extension programs. Thus, assessing factors affecting farmers' choice of agricultural extension methods is essential for developing extension methods that comply with farmers' needs and socio-economic conditions. Therefore, we analyzed the factors affecting farmers' preferences in extension methods, using cross-sectional data collected from 300 households in two sample districts and 16 Kebelles in Ethiopia between September 2019 and March 2020. Four extension methods, including training, demonstration, office visits and phone calls were considered as outcome variables. We fitted a multivariate probit model to estimate the factors that influence farmers' choice of extension methods. The results of the study showed that the number of dependents in the household head, formal education and membership of Idir (an informal insurance program a community or group runs to meet emergencies) were negatively associated with farmers' choices to participate in different extension methods compared to no extension. On the other hand, the sex of the household head, farm experience, participation in non-farm activities, monetary loan access, owning a mobile phone, radio access and membership of cooperatives were found to have a statistically significant positive impact on farmers' choices of extension methods. Based on these findings, the government and the concerned stakeholders should take farmers' socio-economic and institutional traits into account when selecting and commissioning agricultural extension methods. This could help to develop contextually relevant extension strategies that are more likely to be chosen and appreciated by farmers. Furthermore, such strategies can aid policymakers in designing extension programs that cater to farmers' needs and concerns. In conclusion, farmers' socio-economic and institutional affiliation should be taken into consideration when selecting agricultural extension methods.

Abstract: In this paper, a methodology is presented to count the number of atoms in heterogeneous nanoparticles based on the combination of multiple annular dark field scanning transmission electron microscopy (ADF STEM) images. The different non-overlapping annular detector collection regions are selected based on the principles of optimal statistical experiment design for the atom-counting problem. To count the number of atoms, the total intensities of scattered electrons for each atomic column, the so-called scattering cross-sections, are simultaneously compared with simulated library values for the different detector regions by minimising the squared differences. The performance of the method is evaluated for simulated Ni@Pt and Au@Ag core-shell nanoparticles. Our approach turns out to be a dose efficient alternative for the investigation of beam-sensitive heterogeneous materials as compared to the combination of ADF STEM and energy dispersive X-ray spectroscopy.

Abstract: The development of compact, low power, charge-neutral propulsion sources is of significant recent interest due to the rising application of micro-scale satellite platforms. Among such sources, radio frequency (rf) electrothermal microthrusters present an attractive option due to their scalability, reliability, and tunable control of power coupling to the propellant. For micropropulsion applications, where available power is limited, it is of particular importance to understand how electrical power can be transferred to the propellant efficiently, a process that is underpinned by the plasma sheath dynamics. In this work, two-dimensional fluid/Monte Carlo simulations are employed to investigate the effects of applied voltage frequency on the electron, ion, and neutral heating in an rf capacitively coupled plasma microthruster operating in argon. Variations in the electron and argon ion densities and power deposition, and their consequent effect on neutral-gas heating, are investigated with relation to the phase-averaged and phase-resolved sheath dynamics for rf voltage frequencies of 6-108 MHz at 450 V. Driving voltage frequencies above 40.68 MHz exhibit enhanced volumetric ionization from bulk electrons at the expense of the ion heating efficiency. Lower driving voltage frequencies below 13.56 MHz exhibit more efficient ionization due to secondary electrons and an increasing fraction of rf power deposition into ions. Thermal efficiencies are improved by a factor of 2.5 at 6 MHz as compared to the more traditional 13.56 MHz, indicating a favorable operating regime for low power satellite applications.

Abstract: Nutrient circularity is an emerging concept that seeks to address the environmental problems and nutrient losses caused by agriculture and food consumption. The implementation of circular nutrient technologies and practices (CNTPs), that recover, reuse, and recycle nutrients from agricultural and urban waste is an important policy objective. Yet, which policies govern the adoption of CNTPs is not well defined. This study presents the first systematic review of impact evaluations of policy measures that aim to improve nutrient circularity regulating components of the biological cycle of the circular economy, particularly focusing on bioaccessible nutrients. The key CNTPs that were subject to existing impact evaluations were identified. CNTPs were categorized into nutrient circularity themes, with manure management emerging as a prominent focus. The reviewed studies implemented several methods to assess the impacts of policies on various dependent variables, associated with nutrient circularity. Economic simulation models and linear programming were the most prevalent methods for impact evaluation. Policy measures were labeled as either enabling or not-enabling nutrient circularity based on whether they sufficiently promoted nutrient circularity through facilitating the adoption of CNTPs, and controlling for soil, water and air health, preventing its contamination. It is concluded that incentive policies, harmonizing market support, tax incentives, and technological advancements, as well as coherence of local, national and cross-country legislation prove indispensable in steering the economic feasibility and sustainability of CNTPs, offering a promising avenue for progress and a transformative shift towards nutrient circularity.

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: Graphene oxide (GO) is one of the most promising candidates for next generation of atomically thin membranes. Nevertheless, one of the major issues for real world application of GO membranes is their undesirable swelling in an aqueous environment. Recently, we demonstrated that generation of H3O+ and OH- ions (e.g., with an external electric field) in the interlayer gallery could impart aqueous stability to the layered GO membranes (A. Gogoi, ACS Appl. Mater. Interfaces, 2022, 14, 34946). This, however, compromises the water flux through the membrane. In this study, we report on reducing the GO nanosheets as a solution to this issue. With the reduction of the GO nanosheets, the water flux through the layered GO membrane initially increases and then decreases again beyond a certain degree of reduction. Here, two key factors are at play. Firstly, the instability of the H-bond network between water molecules and the GO nanosheets, which increases the water flux. Secondly, the pore size reduction in the interlayer gallery of the membranes, which decreases the water flux. We also observe a significant improvement in the salt rejection of the membranes, due to the dissociation of water molecules in the interlayer gallery. In particular, for the case of 10% water dissociation, the water flux through the membranes can be enhanced without altering its selectivity. This is an encouraging observation as it breaks the traditional tradeoff between water flux and salt rejection of a membrane.

Abstract: Oxocarbons, known for over two centuries, have recently revealed a long-awaited facet: two-dimensional crystalline structures. Employing an intelligent global optimization algorithm (IGOA) alongside densityfunctional calculations, we unearthed a quasi -flat oxocarbon (C 6 0 6 ), featuring an oxygen -decorated hole, and a novel 3D-borocarbon. Comparative analyses with recently synthesized isostructures, such as 2D -porous carbon nitride (C 6 N 6 ) and 2D -porous boroxine (B 6 0 6 ), highlight the unique attributes of these compounds. All structures share a common stoichiometry of X 6 Y 6 (which we call COF-66), where X = B, C, and Y = B, N, O (with X not equal Y), exhibiting a 2D -crystalline structure, except for borocarbon C 6 B 6 , which forms a 3D crystal. In our comprehensive study, we conducted a detailed exploration of the electronic structure of X 6 Y 6 compounds, scrutinizing their thermodynamic properties and systematically evaluating phonon stability criteria. With expansive surface areas, diverse pore sizes, biocompatibility, pi-conjugation, and distinctive photoelectric properties, these structures, belonging to the covalent organic framework (COF) family, present enticing prospects for fundamental research and hold potential for biosensing applications.

Abstract: Electronic devices that work in the quantum regime often employ hybrid nanostructures to bring about a nonlinear behaviour. The nonlinearity that these can provide has proven to be useful, in particular, for applications in quantum computation. Here we present a hybrid device that acts as a capacitor with a nonlinear charge-voltage relation. The device consists of a nanowire placed between the plates of a coplanar capacitor, with a co-parallel alignment. At low temperatures, due to the finite density of states on the nanowire, the charge distribution in the capacitor is uneven and energy-dependent, resulting in a charge-dependent effective capacitance. We study this system analytically and numerically, and show that the nonlinearity of the capacitance is significant enough to be utilized in circuit quantum electrodynamics. The resulting nonlinearity can be switched on, modulated, and switched off by an external potential, thus making this capacitive device highly versatile for uses in quantum computation.

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: 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: The interplay between a magnetic field and the Coulomb potential from a charged vacancy on the electron states in graphene is investigated within the tight-binding model. The Coulomb potential removes locally Landau level degeneracy, while the vacancy introduces a satellite level next to the normal Landau level. These satellite levels are found throughout the positive-energy region, but in the negative-energy region, they turn into atomic collapse resonances. Crossings between Landau levels with different angular quantum number m are found. Unlike the point impurity system in which an anticrossing occurs between Landau levels of the same m, in this work anticrossing is found between the normal Landau level and the vacancy-induced level. The atomic collapse resonance hybridizes with the Landau levels. The charge at which the lowest Landau level m = -1, N = 1 crosses E = 0 increases with enhancing magnetic field. A Landau level scaling anomaly occurs when the charge is larger than the critical charge beta 0.6 and this critical charge is independent of the magnetic field.