Abstract: With the rapid increase in the speed of new-generation aerospace vehicles, conventional heat-resistant aluminum alloys cannot meet the long-term service of the equipment. Therefore, the development of new high-strength heat-resistant aluminum alloys is of great strategic for the sustainable and high-quality development of industries. Al-Cu-Mg-Ag alloy is an age-hardenable heat-resistant aluminum alloy and has high strength and heat resistance. The addition of alloying elements such as Si and Sc to Al-Cu-Mg-Ag alloy introduces a competitive relationship among the σ-Al5Cu6Mg2, θ′-Al2Cu, and Ω phases. Therefore, a systematic investigation of precipitation behavior and heat resistance of Al-Cu-Mg-Ag-(Si) is essential for guiding the design of high-strength heat-resistant aluminum alloys. Combined characterization testing methods such as scanning electron microscopy, transmission electron microscopy, atom probe tomography, microhardness testing, and tensile testing with simulation calculation methods such as calculation of phase diagram, first-principles calculations, and Ab initio molecular dynamics, the effects of heat treatment processes and element content on the precipitation behavior, mechanical properties, and heat resistance of Al-Cu-Mg-Ag-(Si) alloys were systematically investigated. Furthermore, a multiple interface segregation structure was constructed at the θ′/Al interface, and a new Al-Cu-Mg-Ag-Si-Sc alloy with synergistically improved strength and heat resistance was developed. The main conclusions are as follows: (1) Based on the Kampmann-Wagner-Numerical theory, the relationship between the coarsening rate of the Ω phase and the aging process was analyzed, revealing for the first time that the critical size of Ω phase ( ) under thermal exposure temperature was the key factor determining the coarsening rate of Ω phase during long time thermal exposure heat treatment. After artificial ageing, when the size of Ω phase was smaller than the critical size , the dissolution of smaller Ω phase leaded to a rapid decrease in the number density of Ω phases, thereby reducing the heat resistance of the alloy. When the size of Ω phase was greater than or equal to the critical size , the coarsening rate of Ω phase was consistent, but a larger initial size would result in a larger final size after long-term thermal exposure. Therefore, the closer the size of Ω phase in the alloy is to the critical size under heat exposure temperature, the better the heat resistance of the alloy. (2) A concept of constructing a multiple interface segregation structure at the precipitate/matrix interface was proposed, and based on this concept, a multiple interface segregation structure containing the C/L-AlMgSiCu interfacial phase, newly discovered χ-AgMg interfacial phase, and Sc segregation layer was successfully constructed at the θ′/Al interface. The existence of the multiple interface segregation structure ensured that the designed Al-Cu-Mg-Ag-Si-Sc alloy maintains a yield strength of 400 MPa after thermal exposure at 200 C for 100 h, with a strength retention rate of 97%, creating a new record for the synergistic improvement of strength and heat resistance in aluminum alloys. In addition, combining transmission electron microscopy ex-situ/in-situ characterization with first-principles calculations, it is shown that the χ-AgMg interface phase will be destroyed due to the diffusion of the outer Ag layer during thermal exposure, and gradually dissolve into the matrix, but it can still delay the coarsening behavior of θ′-Al2Cu phase. (3) The criteria for determining whether Ω phase can precipitate are updated in Al-Cu-Mg-Ag-Si alloys with low Mg/Si ratio based on phase diagram thermodynamic calculations and multi-scale structural characterization. When W(Mg)/W(Si) > 1.4 and X(Ag)/X(Mgexcess) > 1, Ω phase can precipitate in Al-Cu-Mg-Ag-Si alloys, where X(Mgexcess) represents the atomic percentage of residual Mg elements after the formation of the AlMgSiCu quaternary precipitate phase C/L phase in the supersaturated solid solution, and the W(Mg) is the mass fraction of Mg in the supersaturated solid solution before artificial ageing. (4) The effects of alloy element content on precipitation behavior and heat resistance of Al-Cu-Mg-Ag-Si alloys were systematically analyzed. Critical conditions for the precipitation of σ-Al5Cu6Mg2 and Ω phase in Al-Cu-Mg-Ag-Si alloys are revealed. Based on calculation of phase diagram results, the conditions for precipitating σ-Al5Cu6Mg2 phase in the alloy are: ① W(Mg)/W(Si) > 1.8; ② W(Cu) > 2.7W(Mg) – 5W(Si). When W(Mg)/W(Si) < 1.8, the alloy is mainly precipitated with C/L/Q′-AlMgSiCu. When W(Cu) < 2.7W(Mg) – 5W(Si), the alloy will generate GPB zone. In addition, W(Ag)/W(Si) > 4 is the critical condition which the Ω phase can the main precipitates in Al-Cu-Mg-Ag-Si alloys. Furthermore, the correlation between precipitate types and heat resistance was summarized, showing that Al-Cu-Mg-Ag-(Si) alloys with Ω phase as the main strengthening phase are more suitable for the preparation of structures with short service time but high temperature, while Al-Cu-Mg-Ag-(Si) alloys with low Mg content and multiple segregation structures are more suitable for structures requiring long-term service at medium to high temperatures. This study, for the first time, combines calculation of phase diagram with multi-scale microstructure characterization, systematically unraveling the effects of element content on precipitation behavior, strength, and heat resistance of Al-Cu-Mg-Ag-(Si) alloys. In addition, a concept of constructing a multiple interface segregation structure at the precipitate/matrix interface was proposed to synergistically improve alloy strength and heat resistance. This work provides theoretical guidance for optimizing the composition and processing of Al-Cu-Mg-Ag-(Si) alloy and regulating the microstructure. Furthermore, it also offers new ideas and theoretical guidance for the development of novel high-strength heat-resistant alloys in other systems.

Abstract: We provide a comprehensive analysis of the prominent tight-binding (TB) models for transition metal dichalcogenides (TMDs) available in the literature. We inspect the construction of these TB models, discuss their parameterization used and conduct a thorough comparison of their effectiveness in capturing important electronic properties. Based on these insights, we propose a novel TB model for TMDs designed for enhanced computational efficiency. Utilizing MoS2 as a representative case, we explain why specific models offer a more accurate description. Our primary aim is to assist researchers in choosing the most appropriate TB model for their calculations on TMDs.

Abstract: We present an investigation of the microstructure changes in V2O3 as it goes through its inherent structural phase transition. Using V2O3 films with a well-defined crystal structure deposited by reactive magnetron sputtering on r-plane Al2O3 substrates, we study the phase coexistence region and its impact on the surface roughness of the films and the magnetic properties of overlying Ni magnetic layers in V2O3/Ni hybrid magnetic heterostructures. The simultaneous presence of two phases in V2O3 during its structural phase transition was identified with high resolution x-ray diffraction and led to an increase in surface roughness observed using x-ray reflectivity. The roughness reaches its maximum at the midpoint of the transition. In V2O3/Ni hybrid heterostructures, we find a concomitant increase in the coercivity of the magnetic layer correlated with the increased roughness of the V2O3 surface. The chemical homogeneity of the V2O3 is confirmed through transmission electron microscopy analysis. High-angle annular dark field imaging and electron energy loss spectroscopy reveal an atomically flat interface between Al2O3 and V2O3, as well as a sharp interface between V2O3 and Ni.

Abstract: We investigate the coupling factor phi( mu) that quantifies the magnetic flux phi per magnetic moment mu of a point-like magnetic dipole that couples to a superconducting quantum interference device (SQUID). Representing the dipole by a tiny current-carrying (Amperian) loop, the reciprocity of mutual inductances of SQUID and Amperian loop provides an elegant way of calculating phi(mu)(r,e(mu)) vs. position r and orientation e(mu) of the dipole anywhere in space from the magnetic field B-J(r) produced by a supercurrent circulating in the SQUID loop. We use numerical simulations based on London and Ginzburg-Landau theory to calculate phi (mu) from the supercurrent density distributions in various superconducting loop geometries. We treat the far-field regime ( r greater than or similar to a= inner size of the SQUID loop) with the dipole placed on (oriented along) the symmetry axis of circular or square shaped loops. We compare expressions for phi (mu) from simple filamentary loop models with simulation results for loops with finite width w (outer size A > alpha), thickness d and London penetration depth lambda(L )and show that for thin ( d << alpha ) and narrow (w < alpha) loops the introduction of an effective loop size a(eff) in the filamentary loop-model expressions results in good agreement with simulations. For a dipole placed right in the center of the loop, simulations provide an expression phi(mu)(a,A,d,lambda(L)) that covers a wide parameter range. In the near-field regime (dipole centered at small distance z above one SQUID arm) only coupling to a single strip representing the SQUID arm has to be considered. For this case, we compare simulations with an analytical expression derived for a homogeneous current density distribution, which yields excellent agreement for lambda(L)>w,d . Moreover, we analyze the improvement of phi(mu) provided by the introduction of a narrow constriction in the SQUID arm below the magnetic dipole.

Abstract: We explored the potential of plasma-based In-Situ Resource Utilization (ISRU) for Mars through the conversion of Martian atmosphere (~96% CO2, 2% N2, and 2% Ar) into life-sustaining chemicals. As the Martian surface pressure is about 1% of the Earth’s surface pressure, it is an ideal environment for plasma-based gas conversion using microwave reactors. At 1000 W and 10 Ln/min (normal liters per minute), we produced ~76 g/h of O2 and ~3 g/h of NOx using a 2.45 GHz waveguided reactor at 25 mbar, which is ~3.5 times Mars ambient pressure. The energy cost required to produce O2 was ~0.013 kWh/g, which is very promising compared to recently concluded MOXIE experiments on the Mars surface. This marks a crucial step towards realizing the extension of human exploration.

Abstract: Warm plasma offers a promising route for CO2 splitting into valuable CO, yet recombination reactions of CO with oxygen, forming again CO2, have recently emerged as critical limitation. This study combines experiments and fluid dynamics + chemical kinetics modelling to comprehensively analyse the recombination reactions upon CO2 splitting in an atmospheric plasmatron. We introduce an innovative in-situ gas sampling technique, enabling 2D spatial mapping of gas product compositions and temperatures, experimentally confirming for the first time the substantial limiting effect of CO recombination reactions in the afterglow region. Our results show that the CO mole fraction at a 5 L/min flow rate drops significantly from 11.9 % at a vertical distance of z = 20 mm in the afterglow region to 8.6 % at z = 40 mm. We constructed a comprehensive 2D model that allows for spatial reaction rates analysis incorporating crucial reactions, and we validated it to kinetically elucidate this phenomenon. CO2 +M⇌O+CO+M and CO2 +O⇌CO+O2 are the dominant reactions, with the forward reactions prevailing in the plasma region and the backward reactions becoming prominent in the afterglow region. These results allow us to propose an afterglow quenching strategy for performance enhancement, which is further demonstrated through a meticulously developed plasmatron reactor with two-stage cooling. Our approach substantially increases the CO2 conversion (e.g., from 6.6 % to 19.5 % at 3 L/min flow rate) and energy efficiency (from 13.5 % to 28.5 %, again at 3 L/min) and significantly shortens the startup time (from ~ 150 s to 25 s). Our study underscores the critical role of inhibiting recombination reactions in plasma-based CO2 conversion and offers new avenues for performance enhancement.

Abstract: Using Hubbard-U-corrected density functional theory calculations, lattice Monte Carlo simulations, and spin Monte Carlo simulations, we investigate the impact of dopant clustering on the magnetic properties of WSe2 doped with period four transition metals. We use manganese (Mn) and iron (Fe) as candidate n-type dopants and vanadium (V) as the candidate p-type dopant, substituting the tungsten (W) atom in WSe2. Specifically, we determine the strength of the exchange interaction in Fe-, Mn-, and V-doped WSe2 in the presence of clustering. We show that the clusters of dopants are energetically more stable than discretely doped systems. Further, we show that in the presence of dopant clustering, the magnetic exchange interaction significantly reduces because the magnetic order in clustered WSe2 becomes more itinerant. Finally, we show that the clustering of the dopant atoms has a detrimental effect on the magnetic interaction, and to obtain an optimal Curie temperature, it is important to control the distribution of the dopant atoms.

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: 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: To support experimental research into gas conversion by warm plasmas, models should be developed to explain the experimental observations. These models need to describe all physical and chemical plasma properties in a coupled way. In this paper, we present a modelling approach to solve the complete set of assumed relevant equations, including gas flow, heat balance and species transport, coupled with a rather extensive chemistry set, consisting of 21 species, obtained by reduction of a more detailed chemistry set, consisting of 41 species. We apply this model to study the combined CO2 and CH4 conversion in the presence of O2, in a direct current atmospheric pressure glow discharge. Our model can predict the experimental trends, and can explain why higher O2 fractions result in higher CH4 conversion, namely due to the higher gas temperature, rather than just by additional chemical reactions. Indeed, our model predicts that when more O2 is added, the energy required to reach any set temperature (i.e., the enthalpy) drops, allowing the system to reach higher temperatures with similar amounts of energy. This is in turn related to the higher H2O fraction and lower H2 fraction formed in the plasma, as demonstrated by our model. Altogether, our new self-consistent model can capture the main physics and chemistry occurring in this warm plasma, which is an important step towards predictive modelling for plasma-based gas conversion.

Abstract: This study investigates the dry reformation of methane (DRM) over Ni/Al2O3 catalysts in a dielectric barrier discharge (DBD) non-thermal plasma reactor. A novel hybrid machine learning (ML) model is developed to optimize the plasma-catalytic DRM reaction with limited experimental data. To address the non-linear and complex nature of the plasma-catalytic DRM process, the hybrid ML model integrates three well-established algorithms: regression trees, support vector regression, and artificial neural networks. A genetic algorithm (GA) is then used to optimize the hyperparameters of each algorithm within the hybrid ML model. The ML model achieved excellent agreement with the experimental data, demonstrating its efficacy in accurately predicting and optimizing the DRM process. The model was subsequently used to investigate the impact of various operating parameters on the plasma-catalytic DRM performance. We found that the optimal discharge power (20 W), CO2/CH4 molar ratio (1.5), and Ni loading (7.8 wt%) resulted in the maximum energy yield at a total flow rate of
51 mL/min. Furthermore, we investigated the relative significance of each operating parameter on the performance of the plasmacatalytic DRM process. The results show that the total flow rate had the greatest influence on the conversion, with a significance exceeding 35% for each output, while the Ni loading had the least impact on the overall reaction performance. This hybrid model demonstrates a remarkable ability to extract valuable insights from limited datasets, enabling the development and optimization of more efficient and selective plasma-catalytic chemical processes.

Abstract: This study introduces solid-state tuning of a mesostructured cellular foam (MCF) to enhance hydrogen (H-2) storage in clathrate hydrates. Grafting of promoter-like molecules (e.g., tetrahydrofuran) at the internal surface of the MCF resulted in a substantial improvement in the kinetics of formation of binary H-2-THF clathrate hydrate. Identification of the confined hydrate as sII clathrate hydrate and enclathration of H-2 in its small cages was performed using XRD and high-pressure H-1 NMR spectroscopy respectively. Experimental findings show that modified MCF materials exhibit a similar to 1.3 times higher H-2 storage capacity as compared to non-modified MCF under the same conditions (7 MPa, 265 K, 100% pore volume saturation with a 5.56 mol% THF solution). The enhancement in H-2 storage is attributed to the hydrophobicity originating from grafting organic molecules onto pristine MCF, thereby influencing water interactions and fostering an environment conducive to H-2 enclathration. Gas uptake curves indicate an optimal tuning point for higher H-2 storage, favoring a lower density of carbon per nm(2). Furthermore, a direct correlation emerges between higher driving forces and increased H-2 storage capacity, culminating at 0.52 wt% (46.77 mmoles of H-2 per mole of H2O and 39.78% water-to-hydrate conversions) at 262 K for the modified MCF material with fewer carbons per nm(2). Notably, the substantial H-2 storage capacity achieved without energy-intensive processes underscores solid-state tuning's potential for H-2 storage in the synthesized hydrates. This study evaluated two distinct kinetic models to describe hydrate growth in MCF. The multistage kinetic model showed better predictive capabilities for experimental data and maintained a low average absolute deviation. This research provides valuable insights into augmenting H-2 storage capabilities and holds promising implications for future advancements.

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 success of colloidal semiconductor nanocrystals (NCs) in science and optoelectronics is inextricable from their surfaces. The functionalization of lead halide perovskite NCs1-5 poses a formidable challenge because of their structural lability, unlike the well-established covalent ligand capping of conventional semiconductor NCs6,7. We posited that the vast and facile molecular engineering of phospholipids as zwitterionic surfactants can deliver highly customized surface chemistries for metal halide NCs. Molecular dynamics simulations implied that ligand-NC surface affinity is primarily governed by the structure of the zwitterionic head group, particularly by the geometric fitness of the anionic and cationic moieties into the surface lattice sites, as corroborated by the nuclear magnetic resonance and Fourier-transform infrared spectroscopy data. Lattice-matched primary-ammonium phospholipids enhance the structural and colloidal integrity of hybrid organic-inorganic lead halide perovskites (FAPbBr3 and MAPbBr3 (FA, formamidinium; MA, methylammonium)) and lead-free metal halide NCs. The molecular structure of the organic ligand tail governs the long-term colloidal stability and compatibility with solvents of diverse polarity, from hydrocarbons to acetone and alcohols. These NCs exhibit photoluminescence quantum yield of more than 96% in solution and solids and minimal photoluminescence intermittency at the single particle level with an average ON fraction as high as 94%, as well as bright and high-purity (about 95%) single-photon emission. Phospholipids enhance the structural and colloidal integrity of hybrid organic-inorganic lead halide perovskites and lead-free metal halide nanocrystals, which then exhibit enhanced robustness and optical properties.

Abstract: The safe and efficient use of hydrogen energy, which is in high demand worldwide today, requires efficient hydrogen storage. Despite significant advances in hydrogen storage using carbon-based nanomaterials, including carbon nanotubes (CNTs), efforts to substantially increase the storage capacity remain less effective. In this work, we demonstrate the effect of endohedral transition metal atoms on the hydrogen storage capacity of CNTs using reactive molecular dynamics simulations. We find that an increase in the volume fraction of endohedral nickel atoms leads to an increase in the concentration of physisorbed hydrogen molecules around single-walled CNTs (SWNTs) by approximately 1.6 times compared to pure SWNTs. The obtained results provide insight into the underlying mechanisms of how endohedral transition metal atoms enhance the hydrogen storage ability of SWNTs under nearly ambient conditions.