Abstract: Humanity feels the urge of shifting to a sustainable society more than at any other time in its history. Electrification of chemical industry plays a key role in this transition. The possibility of producing fertilizers from air using renewable electricity, and simultaneously, no greenhouse gas emission, resulted in an increasing interest toward plasma technology as a solution for electrification of a part of the chemical industry in the past few years. Additionally, the activation of nitrogen molecules by vibrational and electronic excitation reactions in plasma can lead to an energy-efficient process. Last but not least, the modularity (fast on/off characteristic) of plasma technology makes it capable of using intermittent renewable electricity on site for the production of fertilizers using air. All these advantages offered by plasma technology make it a potential solution for the on-site production of fertilizers in small and decentralized plants using air and renewable electricity, which leads to a considerable reduction in fertilizer production and transportation costs. However, industrialization of plasma-based NF suffers from several challenges, including challenges of plasma catalysis for the selective production of desired species, the high energy cost of plasma-based NF compared to current industrial processes, and the design and development of scaled up and energy-efficient plasma reactors for industrial purposes. In the framework of this thesis we have tried to add to the state-of-the-art (SOTA) in plasma-based NOx production and deal with its limitations using a combination of experimental and modelling work.

Abstract: Indoor air pollution affects the global population, especially in developed countries where people spend around 90% of their time indoors. The recent pandemic exacerbated the exposure by relying on indoor spaces and a teleworking lifestyle. VOCs are a group of indoor air pollutants with harmful effects on human health at low concentrations. It is widespread that plants can remove indoor VOCs. To this day, research has combined principles of phytoremediation, biofiltration, and bioremediation into a holistic and sustainable technology called botanical biofiltration. Overall, it is sustained that its main advantage is the capacity to break down and biodegrade pollutants using low energy input. This differs from traditional systems that transfer VOCs to another phase. Furthermore, it offers additional benefits like decreased indoor air health costs, enhanced work productivity, and well-being. However, many disparities exist within the field regarding the role of plants, substrate, and phyllosphere bacteria. Yet their role has been theorized; its stability is poorly known for an engineering approach. Previous research has not addressed the bioaugmentation of the phyllosphere to increase the performance, which could boost the system. Moreover, most experiments have studied passive potted plant systems at a lab scale using small chambers, making it difficult to extrapolate findings into tangible parameters to engineer the technology. Active systems are believed to be more efficient yet require more maintenance and knowledge expertise; besides, the impact of the active flow on the long term is not fully understood. Besides, modeling the system has been oversimplified, limiting the understanding and optimization. This review sheds light on the field’s gains and gaps, like concepts, experiments, and modeling. We believe that embracing a multidisciplinary approach encompassing experiments, multiphysics modeling, microbial community analysis, and coworking with the indoor air sector will enable the optimization of the technology and facilitate its adoption.

Abstract: This study investigates the distribution of ultrasound (US) energy in a batch system for solutions with viscosity ranging from 1 to approximately 3000 mPas. Sonication was performed using horn type configurations operating at 20-30 kHz and rated power capacity of 50 or 200 W. Two different tip diameters (3 or 7 mm) and two insertion depths (35 or 25 mm) within vessels of different sizes ( approximate to 60 or 130 ml) were utilized. Additionally, a special conical tip design was employed. For each experimental setup, the calorimetric efficiency was estimated, the cavitationally active regions were visualized using the sonochemiluminescence (SCL) method and bubble cluster formation inside the vessel was macroscopically observed using a high speed camera (HSC). In the viscosity range tested, the calorimetry results showed that the efficiency and continuous operation of the device depend on both the rated power and the horn tip diameter. The ratio between electrical and calorimetric power input remained consistently around 40 to 50% across the different configurations for water, but for the 123.2 mPas solution exhibited significant variation ranging from 40 to 85%. Moreover, the power density in the smaller reactor was found to be nearly double compared to the larger one. The SCL analysis showed multiple cavitationally active zones in all setups, and the zones intensity decreased considerably with increase of the solutions viscosity. The results for the cone tip were not conclusive, but can be used as the basis for further investigation. The current research highlights the importance of thoroughly understanding the impact of each design parameter, and of establishing characterization methodologies to assist in the future development of scaled-up, commercial applications.

Abstract: The vibrational properties of 2H-TaSe_2-xS_x (0≤x≤2) single crystals were probed using Raman spectroscopy and density functional theory calculations. The end members revealed two out of four symmetry-predicted Raman active modes, together with the pronounced two-phonon structure, attributable to the enhanced electron-phonon coupling. Additional peaks become observable due to crystallographic disorder for the doped samples. The evolution of the E₂g² mode Fano parameter reveals that the disorder has a weak impact on electron-phonon coupling, which is also supported by the persistence of two-phonon structure in doped samples. As such, this research provides thorough insights into the lattice properties, the effects of crystallographic disorder on Raman spectra, and the interplay of this disorder with the electron-phonon coupling in 2H-TaSe_2-xS_x compounds.

Abstract: The design of high‐performance structural thin films consistently seeks to achieve a delicate equilibrium by balancing outstanding mechanical properties like yield strength, ductility, and substrate adhesion, which are often mutually exclusive. Metallic glasses (MGs) with their amorphous structure have superior strength, but usually poor ductility with catastrophic failure induced by shear bands (SBs) formation. Herein, we introduce an innovative approach by synthesizing MGs characterized by large and tunable mechanical properties, pioneering a nanoengineering design based on the control of nanoscale chemical/structural heterogeneities. This is realized through a simplified model Zr 24 Cu 76 /Zr 61 Cu 39 , fully amorphous nanocomposite with controlled nanoscale periodicity ( Λ , from 400 down to 5 nm), local chemistry, and glass–glass interfaces, while focusing in‐depth on the SB nucleation/propagation processes. The nanolaminates enable a fine control of the mechanical properties, and an onset of crack formation/percolation (>1.9 and 3.3%, respectively) far above the monolithic counterparts. Moreover, we show that SB propagation induces large chemical intermixing, enabling a brittle‐to‐ductile transition when Λ  ≤ 50 nm, reaching remarkably large plastic deformation of 16% in compression and yield strength ≈2 GPa. Overall, the nanoengineered control of local heterogeneities leads to ultimate and tunable mechanical properties opening up a new approach for strong and ductile materials.

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: A thorough and quantitative understanding of the fate of excitons in covalent–organic frameworks (COFs) after photoexcitation is essential for their augmented optoelectronic and photocatalytic applications via precise structure tuning. The synthesis of a library of COFs having identical chemical backbone with impeded conjugation, but varied morphology and surface topography to study the effect of these physical properties on the photophysics of the materials is herein reported. The variation of crystallite size and surface topography substantified different aggregation pattern in the COFs, which leads to disparities in their photoexcitation and relaxation properties. Depending on aggregation, an inverse correlation between bulk luminescence decay time and exciton binding energy of the materials is perceived. Further transient absorption spectroscopic analysis confirms the presence of highly localized, immobile, Frenkel excitons (of diameter 0.3–0.5 nm) via an absence of annihilation at high density, most likely induced by structural torsion of the COF skeletons, which in turn preferentially relaxes via long‐lived (nanosecond to microsecond) excimer formation (in femtosecond scale) over direct emission. These insights underpin the importance of structural and topological design of COFs for their targeted use in photocatalysis.

Abstract: Even at low temperatures, metal nanoparticles (NPs) possess atomic dynamics that are key for their properties but challenging to elucidate. Recent experimental advances allow obtaining atomic‐resolution snapshots of the NPs in realistic regimes, but data acquisition limitations hinder the experimental reconstruction of the atomic dynamics present within them. Molecular simulations have the advantage that these allow directly tracking the motion of atoms over time. However, these typically start from ideal/perfect NP structures and, suffering from sampling limits, provide results that are often dependent on the initial/putative structure and remain purely indicative. Here, by combining state‐of‐the‐art experimental and computational approaches, how it is possible to tackle the limitations of both approaches and resolve the atomistic dynamics present in metal NPs in realistic conditions is demonstrated. Annular dark‐field scanning transmission electron microscopy enables the acquisition of ten high‐resolution images of an Au NP at intervals of 0.6 s. These are used to reconstruct atomistic 3D models of the real NP used to run ten independent molecular dynamics simulations. Machine learning analyses of the simulation trajectories allows resolving the real‐time atomic dynamics present within the NP. This provides a robust combined experimental/computational approach to characterize the structural dynamics of metal NPs in realistic conditions.

Abstract: Non-native species invasions are one of the most impactful drivers of biodiversity and ecosystem services loss worldwide. One aspect of plant species invasion, which is only recently starting to be recognized as a determinant of invasion success, is the symbiosis between plant and mycorrhizal fungi. Here, I focus on anthropogenic disturbance in mountain ecosystems and its impact on plant communities and mycorrhizal fungi to answer how these communities are impacted by disturbance and whether non-native plants can benefit to establish and spread. To this end I used a combination of different approaches: 1) repeated surveys of plants and arbuscular mycorrhizal fungi along disturbed roadsides in the mountains of Norway, 2) combining a global dataset of native and non-native plants along mountain roads with a database associating plants with their mycorrhizal types, and 3) an in-situ experiment measuring non-native plant success and changes in fungal community following different types of disturbances. Through these methods, I could assess the effects of anthropogenic disturbance on mycorrhizal symbiosis and non-native plant species at multiple scales and resolutions. We found that road disturbance has a globally consistent effect on mycorrhizal types in mountain systems, as plants associated with arbuscular mycorrhizal (AM) fungi were more abundant following disturbance. Conversely, vegetation associated with either ectomycorrhizal (EcM) or ericoid mycorrhizal (ErM) fungi was less abundant in disturbed sites. In the regional study, AM fungi were most abundant and diverse in the roots of plant communities affected by road disturbance. Non-native plants were also restricted to these disturbed sites. The experimental results showed that physical disturbance and nutrient addition have negative effects on EcM fungi and positive effects on fungal pathogens, and facilitate non-native plant success. Our results show that anthropogenic disturbance does have an effect on mycorrhizal fungi that in turn impacts the distribution of plant species in disturbed mountain systems. The resulting shift in mycorrhizal fungi benefiting AM fungi and AM plant species could have implications for non-native plant invasions. Indeed, we know that non-native plants predominantly form associations with AM fungi. Therefore, anthropogenic disturbance can facilitate non-native plant success through disruption of the native fungal communities, and especially so in high elevation and cold climate regions which are naturally less dominated by AM plants. I believe this highlights the importance of mycorrhizal symbiosis in understanding plant invasions and emphasizes the importance of monitoring sources of anthropogenic disturbance in mountains to prevent future establishment of non-native plants.

Abstract: Recent observations made by the authors revealed the activation of stress induced amorphization and sliding at grain boundary in olivine [1], a mechanism which is expected to play a pivotal role in the viscosity drop at the lithosphere-asthenosphere boundary and the brittle -ductile transition in the lithospheric mantle. However, there is a lack of information in the literature regarding the intrinsic mechanical properties and the elementary deformation mechanisms of this material, especially at time scales relevant for geodynamics. In the present work, amorphous olivine films were obtained by pulsed laser deposition (PLD). The mechanical response including the rate dependent behavior are investigated using a tension -on -chip (TOC) method developed at UCLouvain allowing to perform creep/relaxation tests on thin films at extremely low strain rates. In the present work, strain rate down to 10-12 s- 1 was reached which is unique. High strain rate sensitivity of 0.054 is observed together with the activation of relaxation at the very early stage of deformation. Furthermore, digital image correlation (DIC), used for the first time on films deformed by TOC, reveals local strain heterogeneities. The relationship between such heterogeneities, the high strain rate sensitivity and the effect of the electron beam in the scanning electron microscope is discussed and compared to the literature.

Abstract: Nowadays, the burning of fossil fuels, particularly petroleum, natural gas, and coal, meets the rising need for power and fuels for automobiles and industries. This has given rise to ecological and climate challenges. This thesis explores these issues from three distinct perspectives: (i) experimental, (ii) computational, and (iii) process simulation, with a focus on studying CO2 as an alternative and economically viable raw material. Firstly, the experimental study is focused on the synthesis, characterization, and testing of novel catalysts for electroreduction of CO2 and oxalic acid, an intermediate product of CO2. Electrocatalysts based on Cu supported by citrus (orange and lemon) peel biomass are prepared. These catalysts exhibit activity in the electrochemical reduction of CO2, emphasizing the effectiveness of biomasses, particularly orange peels, as environmentally friendly precursors for sustainable and efficient electrocatalysts. In addition, graphitic carbon nitrides/TiO2 nanotubes (g-C3N4/TiNT) composites are prepared for the electrocatalytic reduction of oxalic acid to glycolic acid, revealing superior electrocatalytic properties compared to pristine TiNT. Characterization by X-ray diffraction, X-ray photoelectron spectroscopy, and scanning electronic microscopy were performed for all the prepared electrocatalysts. Delving into the reduction of CO2 on Cu catalysts, a computational study about the synthesis of methanol on Cu(111) surface is performed by using the Vienna Ab initio Simulation Package. A systematic study is carried out to define the activation energies of the elementary reactions by using mGGA DF. Consequently, it is shown that the rate-controlling step is CH3O* hydrogenation and the formate pathway on Cu(111) proceeds through the HCOOH* intermediate. Finally, the process simulation, performed by using the software Aspen Plus 11 from AspenTech Inc., is based on the comparison of a catalytic (oxidation of ethylene glycol) and an electrocatalytic process (CO2 electroreduction chain) to synthesize glycolic acid. An economic analysis of the operational and investment costs reveals that the catalytic process is more cost-effective due to the current instability of electrocatalysts and proton exchange membranes, resulting in increased maintenance costs and, consequently, higher prices for the product.

Abstract: Background This study explores the repurposing of Auranofin (AF), an anti-rheumatic drug, for treating non-small cell lung cancer (NSCLC) adenocarcinoma and pancreatic ductal adenocarcinoma (PDAC). Drug repurposing in oncology offers a cost-effective and time-efficient approach to developing new cancer therapies. Our research focuses on evaluating AF's selective cytotoxicity against cancer cells, identifying RNAseq-based biomarkers to predict AF response, and finding the most effective co-therapeutic agents for combination with AF. Methods Our investigation employed a comprehensive drug screening of AF in combination with eleven anticancer agents in cancerous PDAC and NSCLC patient-derived organoids (n = 7), and non-cancerous pulmonary organoids (n = 2). Additionally, we conducted RNA sequencing to identify potential biomarkers for AF sensitivity and experimented with various drug combinations to optimize AF's therapeutic efficacy. Results The results revealed that AF demonstrates a preferential cytotoxic effect on NSCLC and PDAC cancer cells at clinically relevant concentrations below 1 µM, sparing normal epithelial cells. We identified Carbonic Anhydrase 12 (CA12) as a significant RNAseq-based biomarker, closely associated with the NF-κB survival signaling pathway, which is crucial in cancer cell response to oxidative stress. Our findings suggest that cancer cells with low CA12 expression are more susceptible to AF treatment. Furthermore, the combination of AF with the AKT inhibitor MK2206 was found to be particularly effective, exhibiting potent and selective cytotoxic synergy, especially in tumor organoid models classified as intermediate responders to AF, without adverse effects on healthy organoids. Conclusion Our research offers valuable insights into the use of AF for treating NSCLC and PDAC. It highlights AF's cancer cell selectivity, establishes CA12 as a predictive biomarker for AF sensitivity, and underscores the enhanced efficacy of AF when combined with MK2206 and other therapeutics. These findings pave the way for further exploration of AF in cancer treatment, particularly in identifying patient populations most likely to benefit from its use and in optimizing combination therapies for improved patient outcomes.

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: 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.