The role of the cryptobiome and its associated microbial community in coral reef biogeochemical cycling(2023-03) [Thesis]
Advisors: Daffonchio, Daniele; Carvalho, Susana
Committee member: Rosado, Alexandre S.Tropical coral reefs are highly productive ecosystems thriving in oligotrophic waters, a phenomenon facilitated by efficient but delicate biogeochemical cycling within reef communities. Global climate change and local stressors are driving phase shifts from coral- to non-calcifier-dominated states in reefs worldwide, substantially altering reef biogeochemical functioning. While major benthic players such as coral and macroalgae have been investigated in detail regarding carbon and nutrient dynamics, the less conspicuous “reef cryptobiome” (sensu Carvalho et al., 2019) – comprising most of reef diversity – has only recently gained attention. Autonomous Reef Monitoring Structures (ARMS) have recently been developed to sample coral reef cryptobenthic communities in a non-destructive and standardised way, allowing exploration of these often overlooked biota. Here, 16 ARMS were deployed for seven months in four distinct habitats dominated by different benthic players (i.e., four units per habitat) in a nearshore Red Sea coral reef to investigate the cryptobiome associated with proxies of varying benthic states. Two of these habitats were coral-dominated, and one each dominated by turf algae or coral rubble. To assess the biogeochemical fluxes of pioneering cryptobenthic communities, ARMS were incubated in situ prior to retrieval using customised chambers. Subsequently, 16S rRNA gene amplicon and shotgun metagenomic sequencing of the ARMS sessile (i.e., encrusting) fractions were performed to link observed fluxes with prokaryotic taxonomic and functional profiles, particularly regarding nitrogen cycling. The results show that the pioneering cryptobiome represents a significant source of inorganic nutrients and that its associated microbial communities facilitate the mineralisation and assimilation of organic matter and provide crucial genetic functional pathways for nitrogen cycling. Functional similarities among habitats suggested functional redundancy despite variation in bacterial community composition. Hence, the reef cryptobiome can be considered an important biogeochemical player in coral reefs, actively shaping the abiotic conditions within niches of the reef framework and driving the recruitment and persistence of crytobenthic and other reef organisms. As communities associated with the algae-dominated reef habitat were most distinct compositionally and biogeochemically, and as non-calcifiers are becoming more dominant in many reefs, this has implications for intensifying phase shifts in coral reefs worldwide. Future ARMS studies will also benefit from adjustment of sample processing and molecular protocols, resulting in higher sample throughput and lower costs in times of increased application of ARMS.
Analysis of the impact of outdoor air pollution in the Kingdom of Saudi Arabia on air quality.(2023-02) [Thesis]
Advisor: Stenchikov, Georgiy L.
Committee members: McCabe, Matthew; Sun, ShuyuRapid population growth, urbanization, and fossil fuel consumption have contributed to a massive decline in air quality worldwide. This phenomenon is more prevalent in developing countries, including Saudi Arabia. Even though, there are only a few published air quality studies available in the literature for Saudi Arabia. Hereby, I analyzed the annual mean concentration of common air pollutants namely particulate matter (PM2.5 and PM10), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO) in Saudi Arabia using both model predictions and observational data. I found that in general, the level of these pollutants, except CO and SO2, were higher in regions with more population density such as Makkah, Riyadh, and the Eastern provinces, hence their association with traffic-related and industrial emissions. Surprisingly, SO2 levels were higher in regions that have volcanoes in their domain instead; thus, it is more likely that the degassing of these volcanoes has indeed contributed to its emissions. I also compared the annual average levels of PM2.5, PM10, and NO2 with the World Health Organization (WHO) Global Air Quality Guidelines (AQG). I found that both PM2.5 and PM10 levels in Saudi Arabia have extremely exceeded these guidelines. Therefore, residents of Saudi Arabia are at risk of adverse health effects caused by PM pollution.
Coverage and Energy Analysis of T-UAV-Assisted Cellular Networks: Stochastic Geometry Approach.(2023-02) [Thesis]
Advisor: Alouini, Mohamed-Slim
Committee members: Eltawil, Ahmed; Moraga, PaulaAn unmanned aerial vehicle-mounted base station (UAV-BS), also known as an aerial base station (ABS), is a viable technology for the next 6G wireless networks due to its adaptability and affordability. Furthermore, the concept of tethered UAVs (T-UAVs), can be used to circumvent the limited network operating time of UAV-BS networks. T-UAVs are UAVs powered by a ground energy source via a tether that restrain their mobility while providing unlimited power. In this thesis, we propose systems where ABSs are deployed in user hotspots to offload the traffic and assist terrestrial base stations (TBSs). First, we propose three different scenarios based on a model of cluster pairs. We start by determining the optimal locations of T-UAVs that minimize the average pathloss for each scenario. Next, using tools from stochastic geometry and an approach of dividing the space into concentric rings and slices to quantify the locations and orientations of GSs, we analyse both coverage and energy performance for each scenario and compare their performances. We use Monte-Carlo simulations to validate our findings and provide several useful insights. For instance, we show that deploying for each pair of clusters a T-UAV that can be attached and detached from the GS is the best strategy to adopt in terms of both coverage and energy efficiency. Second, we propose a hybrid system composed of tethered and untethered UAVs (T/U-UAVs). We study the coverage performance as a function of some system parameters such as the fraction of T-UAVs that have been used, the U-UAV availability, and the radius of clusters, and we provide useful insights.
Use and Application of 2D Layered Materials-Based Memristors for Neuromorphic Computing(2023-02-01) [Thesis]
Advisor: Lanza, Mario
Committee members: Inal, Sahika; Salama, Khaled N.This work presents a step forward in the use of 2D layered materials (2DLM), specifically hexagonal boron nitride (h-BN), for the fabrication of memristors. In this study, we fabricate, characterize, and use h-BN based memristors with Ag/few-layer h-BN/Ag structure to implement a fully functioning artificial leaky integrate-and-fire neuron on hardware. The devices showed volatile resistive switching behavior with no electro-forming process required, with relatively low VSET and long endurance of beyond 1.5 million cycles. In addition, we present some of the failure mechanisms in these devices with some statistical analyses to understand the causes, as well as a statistical study of both cycle-to-cycle and device-to-device variabilities in 20 devices. Moreover, we study the use of these devices in implementing a functioning artificial leaky integrate-and-fire neuron similar to a biological neuron in the brain. We provide SPICE simulation as well as hardware implementation of the artificial neuron that are in full agreement, showing that our device could be used for such application. Additionally, we study the use of these devices as an activation function for spiking neural networks (SNNs) by providing a SPICE simulation of a fully trained network, where the artificial spiking neuron is connected to the output terminal of a crossbar array. The SPICE simulations provide a proof of concept for using h-BN based memristor for activation function for SNNs.
Synthesis and Characterization of Tetraphenylethylene-Methacrylate-Based (Co)Polymers Using Controlled Radical Polymerization(2023-01) [Thesis]
Advisor: Hadjichristidis, Nikos
Committee members: Huang, Kuo-Wei; Zhang, HuabinAggregation-induced emission (AIE) is a phenomenon with many applications, such as chemical sensors, biological probes, immunoassay markets, and active layers in fabricating organic light-emitting diodes. AIE materials in polymers can enhance the emissivity of such materials while having the benefits of polymeric materials. This thesis examines the use of AIE polymers to study the effect of structure on the properties. This is done by first synthesizing a monomer with AIE characteristics, tetraphenylethylene-methacrylate (TPEMA). Secondly, polymerizing TPEMA using free and controlled radical polymerizations. Finally, the copolymerization of TPEMA with methyl methacrylate (MMA) to understand the effect of spaced-out TPE groups in the polymer chain on the photoluminescence of the polymer. The structures of all intermediates and final products were characterized by nuclear magnetic resonance (NMR) and size exclusion chromatography (SEC). The AIE characteristics were proven and compared using the photoluminescence graphs, showing that the homopolymer had increased emission intensity than its monomer. The copolymer had higher emission intensity than TPEMA and higher normalized emission intensity than that of the homopolymer, showing the effect of structure on the photoluminescence. Both the homopolymer and the copolymer were easier to aggregate than the monomer, making it more effective to utilize the material in applications where it needs to be emissive in diluted solutions. The glass transition temperature and the tacticity of the homopolymer and copolymer were also compared. The thesis is divided into the following five chapters; 1. Introduction, where a brief background along with the scope of the thesis is provided; 2. Literature Review, where a summary of controlled radical polymerization and AIE is given; 3. Experimental Section, where the materials' detailed procedure and characterization are provided; 4. Results and Discussion, where results of successful experiments are discussed; 5. Concluding Remarks, where the results are summarized, and future work is discussed.
Investigating the Role of Fucosylation on the Stemness of Human CD34+ Mobilized Peripheral Blood Progenitor Cells(2023-01) [Thesis]
Advisor: Merzaban, Jasmeen
Committee members: Orlando, Valerio; Aranda, ManuelIt has been well-established that the process of stem cell homing is initially mediated by E-Selectin, a cell adhesion molecule constitutively expressed on the bone marrow vasculature. The ligand for E-selectin is a carbohydrate modification known as sialyl-Lewis X (sLex) found mainly on proteins, and it has been shown that ex vivo fucosylation of stem cells, including hematopoietic stem cells (HSCs) enhances these ligands, resulting in more efficient delivery of stem cells to their home in the bone marrow. However, the exact biological effects that fucosylation has on HSC function has not been extensively studied. In vivo mouse experiments from our lab where short-term CD34+ hematopoietic stem cells were fucosylated improved their delivery to the bone marrow but also exhibited improved longevity and apparent stemness as assessed by secondary transplantation. Therefore, to investigate the role fucosylation has on this phenotype and to uncover whether E-Selectin binding is also required alongside it to trigger molecular changes in hematopoietic stem cells, we set up in vitro cultures with CD34+ cells from GCSF-mobilized human peripheral blood (mPB-CD34+) that had been either left untreated or treated with fucosyltransferase VI (FUT6) in the presence and absence of recombinant E-selectin protein as well as the fucosylation inhibitor 2-fluorofucose (2-FF). We then performed characterization assays to assess cell cycle, signaling, differentiation, and viability using flow cytometry, western blotting, Giemsa staining, and a variety of viability assays. We found that fucosylation enhances the effects of E-Selectin binding, activating stem cell proliferation, triggering the PI3K/AKT/NFkB, P38, and EGFR pathways, induces a transient increase in pre-apoptotic cells, and may alter cell differentiation. These results uncover the role of fucosylation in hematopoietic stem cells and highlights the PI3K/AKT/NFkB pathway as a signaling route mediated by E-selectin to influence stem cell longevity.
Modelling Strategy for the Characterization and Prediction of IIFK-Based Hydrogel Stiffness for Cell Culture Applications(2023-01) [Thesis]
Advisor: Hauser, Charlotte
Committee members: Mahfouz, Magdy M.; Salama, Khaled N.Due to the similar nature 3D synthetics share with in vivo cell conditions, peptide-based hydrogels pose an attractive strategy for the culturing of stem cells. One aspect of this unique cell culturing technique is the tunability of the hydrogel’s stiffness, a quality linked to stem cell differentiation. Due to this linkage, a methodology in which specific cell lineages are achieved within IIFK hydrogel cultures is proposed. This work provides an analysis for the peptide scaffold IIFK; it characterizes the effect between different peptide and PBS concentrations over the resulting hydrogel stiffness and develops a mathematical model to further elucidate this interaction. Nine different hydrogel formulations were made (with a minimum of eleven replicates each) and each of its replicate’s stiffness (storage modulus, Pa) was measured through rheological experiments. Then, two different methods of replicate selection were conducted and various models were derived, each using either of the two replicate selection methods and incorporating a specific number of replicates in their creation. Regardless of sample selection and replicate number, the generated models show extremely high significances between IIFK hydrogel stiffness and PBS concentrations over the resulting hydrogel stiffness. Data analysis shows that for IIFK, the hydrogel stiffness bears a strong behavior that can be modeled by a full quadratic equation. However, the data also shows that the dependency of the model is strongly correlated with the datasets chosen to produce it, with number of replicates and replicate values both resulting in differences in each model’s predictive reliability (e.g., 82% vs 91%). Therefore, while this thesis demonstrates the ability to model IIFK hydrogel behaviour with high predictability ratings, it also establishes the necessity of both producing more replicates as well as selecting the best values for IIFK-based hydrogel modelling.
Lignin-based membrane fabrication for liquids separation(2023-01) [Thesis]
Advisor: Nunes, Suzana Pereira
Committee members: Hong, Pei-Ying; AlSulaiman, Dana Z.A sustainable industry is an essential part of the kingdom’s vision towards zero net emissions by 2060. The membrane industry commonly uses polymers from fossil sources along with solvents that are in part a concern for human health and pollution of the environment. Lignin is an abundant natural polymeric material, which could be interesting for membrane fabrication. Herein, a novel process of lignin membrane fabrication is proposed. Lignin membranes were prepared as dense and as asymmetric porous films. To avoid swelling and increase the stability in different solvents, crosslinking was performed by reacting with hexamethylene diisocyanate. The crosslinking effect was investigated from two aspects, the first aspect was varying the concentration of the crosslinker 2.5, 3.5, and 4.5 mmol g-1 of lignin to fabricate the dense films, then the reaction time was varied as 10, 15, and 30 minutes. The film’s chemical functionalization was characterized by spectroscopy and the thermal and mechanical were investigated by TGA, and the morphology of the membranes was imaged by scanning electron microscopy. To evaluate the chemical stability of the dense films and the membranes, small pieces were immersed in several organic solvents, both the dense films and the membranes displayed excellent chemical stability in all solvents for more than 48 hours. The fabricated films and membranes displayed excellent thermal, mechanical, and chemical stability due to the effective chemical modification. The performance of the membrane was tested for liquid separation with a permeance of 1.2 ±0.08 and 0.15 ±0.04 L m-2 h-1 bar-1 for pure water and methanol respectively and a MWCO in the nanofiltration range.
Estimation of Petrophysical Properties from Thin Sections Using 2D to 3D Reconstruction of Confocal Laser Scanning Microscopy Images.(2022-12) [Thesis]
Advisor: Vahrenkamp, Volker
Committee members: Hoteit, Hussein; Westphal, HildegardPetrophysical properties are fundamental to understanding fluid flow processes in hydrocarbon reservoirs. Special Core Analysis (SCAL) routinely used in industry are time-consuming, expensive, and often destructive. Alternatively, easily available thin section data is lacking the representation of pore space in 3D, which is a requisite for generating pore network models (PNM) and computing petrophysical properties. In this study, these challenges were addressed using a numerical SCAL workflow that employs pore volume reconstruction from thin section images obtained from confocal laser scanning microscopy (CLSM). A key objective is to investigate methods capable of 2D to 3D reconstruction, to obtain PNM used for the estimation of transport properties. Representative thin sections from a well-known Middle-Eastern carbonate formation were used to obtain CLSM images. The thin-sections were specially prepared by spiking the resin with UV dye, enabling high-resolution imaging. The grayscale images obtained from CLSM were preprocessed and segmented into binary images. Generative Adversarial Networks (GAN) and Two-Point Statistics (TPS) were applied, and PNM were extracted from these binary datasets. Porosity, Permeability, and Mercury Injection Porosimetry (MIP) on the corresponding core plugs were conducted and an assessment of the properties computed from the PNM obtained from the reconstructed 3D pore volume is presented. Moreover, the results from the artificial pore networks were corroborated using 3D confocal images of etched pore casts (PCE). The results showed that based on visual inspection only, GAN outperformed TPS in mimicking the 3D distribution of pore scale heterogeneity, additionally, GAN and PCE outperformed the results of MIP obtained by TPS on the Skeletal-Oolitic facies, without providing a major improvement on more heterogeneous samples. All methods captured successfully the porosity while absolute permeability was not captured. Formation resistivity factor and thermal conductivity showcased their strong correlation with porosity. The study thus provides valuable insights into the application of 2D to 3D reconstruction to obtain pore network models of heterogeneous carbonate rocks for petrophysical characterization for quick decision. The study addresses the following important questions: 1) how legacy thin sections can be leveraged to petrophysically characterize reservoir rocks 2) how reliable are 2D to 3D reconstruction methods when predicting petrophysical properties of carbonates.
Perovskite/Silicon tandem solar cells: the trilogy of properties, performance, and stability(2022-12) [Thesis]
Advisor: De Wolf, Stefaan
Committee members: Laquai, Frédéric; Fatayer, ShadiWith the rapid increase in energy demand and the rise of CO2 levels due to traditional energy production from fossil fuels, it is critical to the transition to a sustainable and renewable energy sources. Recently, photovoltaic technology has been raised as a promising alternative to fossil fuel energy production. Solar cells, predominately crystalline silicon technology, are currently 3.6% of electricity production. To maintain this progress, coupling the perovskite and silicon in tandem devices has enormous potential to increase the efficiency of solar energy production, where perovskite solar cells emerged as a promising technology. Textured silicon solar cells are a well-established technology; keeping the advantage of this technology, it is crucial to employ the perovskite to be a compatible top cell for silicon-based tandems. Here, we optimize the silicon bottom cell by understanding the influence of temperature, time, and etchant concentration on the optical properties and performance of the device. Then, we investigate the impact of the textured silicon on the optoelectronic properties of perovskite. Using hyperspectral imaging, we demonstrate that different texturing substrates influence the PL of perovskite, which is associated with the thickness of the perovskite. Lastly, we explored the delamination of the devices due to the weak adhesion between C60/SnO2 after the deposition of IZO and MgF2, which was found to be caused by the deposition conditions. The high temperature and power density caused a weak adhesion between C60/SnO2. Overall, these findings will help to alter the design of Perovskite/Silicon tandem devices to accelerate the commercialization of tandem technology.
Ultraviolet micro light-emitting diode and color-conversion for white-light communication(2022-11-29) [Thesis]
Advisor: Ooi, Boon S.
Committee members: Ohkawa, Kazuhiro; Ng, Tien Khee; Mohammed, Omar F.Visible-light communication (VLC) has several advantages over the commonly used radio frequency (RF) spectrum, including high bandwidth and low crosstalk. These features have become of more significance, especially as the proliferation of wireless devices increases and causes spectrum crowding. The white light in VLC systems is typically obtained from blue/violet light-emitting diodes (LEDs) and phosphors partially converting blue light into longer wavelength colors spanning the visible-light band. One phosphor that is frequently used is cerium-doped yttrium aluminum garnet (YAG). However, YAG suffers from a low color-rendering index (CRI) and high correlated color temperature (CCT). Lead halide perovskites provide an alternative to YAG and have been extensively utilized for optoelectronic devices owing to their tunable bandgap and high photoluminescence quantum yield (PLQY). However, their drawbacks, e.g., lead toxicity and instability, hinder their widespread application. Herein, in order to take advantage of a high-performance lead-free tin-based halide perovskite phosphor that has a high absolute PLQY of near unity and a wide spectral emission ranging from 500 to 700 nm, we fabricated ultraviolet (UV) micro light-emitting diodes (micro-LEDs) with a peak wavelength at 365 nm to match the peak of the photoluminescence excitation (PLE) spectra of the material to obtain strong yellow-spectrum emission. Together with a blue LED, white light was obtained with a CRI of 84.9 and 4115-K CCT. Despite the long PL lifetime of the perovskite material, which is in the order of μs, a net data rate of 1.5 Mb/s was achieved using orthogonal frequency-division multiplexing (OFDM) with adaptive bit and power loading to take advantage of the exceptionally high PLQY of the phosphor to improve the data throughput of the VLC system using higher modulation orders. Furthermore, through improvements to the nanostructure of lead-free tin-based halide perovskite phosphor and the use of excitation sources with a higher power, the data rate is expected to be even higher. The lead-free nature of this material, along with its wide spectrum and high conversion efficiency, makes it a promising alternative to conventional toxic perovskite-based phosphors. As the first demonstration of VLC links using lead-free perovskite, this study paves the way for safer, more sustainable VLC systems.
Predicting Reaction Yield in C_N Cross-coupling Using Machine Learning(2022-11-29) [Thesis]
Advisor: Gao, Xin
Committee members: Cavallo, Luigi; Han, YuThe catalysis reaction performance, such as yield, is very crucial in organic chemistry. And predicting the reaction yield is still very challenging. In this thesis, machine learning is used to predict the reaction yield in a C–N cross-coupling approach. The reaction data are from the high-throughput experimental data with four variables: reactants, Pd catalysts, additives, and bases. Each reaction data will give the corresponding yield. The data are from the literature, which has been uploaded. The total data number used in machine learning is 7910. The method mainly consists of four steps. First, load the csv data and import modules. Second, encode data with molecular fingerprint or one-hot encoding. The data will be normalized if there is need. Third, split the dataset into train and test set with the size ratio of 7/3 or 8/2. Fourth, use six machine learning models to learn the data and evaluate their performance. Then, compare the prediction yield of the test set. The accuracy in prediction (RMSE value and R-squared) and running time will be considered for evaluation. By comparing the RMSE and R-squared values of different models, we can decide which one has better performance and better fitting results. Improved reaction performance, or high-performance catalysts and their characteristics may be obtained.
DISCOVERING SEAGRASS BLUE CARBON RESOURCES IN THE RED SEA BY GREEN TURTLE Chelonia mydas TRACKING(2022-11-27) [Thesis]
Advisor: Duarte, Carlos M.
Committee members: Afifi, Abdulakader M.; Johnson, Maggie D.Seagrass is a valuable and important habitat, providing services such as coastal protection, supporting fisheries, and carbon sequestration. However, it is challenging to map accurately, as remote sensing has limits to how deep in the water column it can penetrate, and uncertainties such as distinguishing between algae and seagrass. Seagrass can exist at depths of theoretically 90 m deep in ultraoligotrophic waters, meaning that there is much of this habitat that cannot be mapped by remote sensing. Green turtles are an ideal candidate to help find seagrass blue carbon resources in the Red Sea. They go through an ontogenetic dietary shift to become almost completely herbivorous, and have a high fidelity to foraging sites. In this study we aim to assess the use of green turtles Chelonia mydas in discovering seagrass blue carbon. We use telemetry from 53 turtles tagged over 2018, 2019, and 2021 to map their foraging areas. 50 out of the 53 (94.34%) foraging sites had not been visited by previous seagrass studies in the Red Sea. We visited 18 locations in 14 of these foraging sites to ground truth them, and all 14 foraging sites (100%) had seagrass present. Comparatively, 18 out of 30 sites where seagrass was indicated by the remote sensing-based Allen Coral Atlas showed no seagrass. The turtles were seen to favour travelling shorter distances, thus it will be necessary to expand the area of tagging in order to achieve complete coverage of the Red Sea. Approximately 1/3 of the visited sites were deeper than 8 m, and so out of range of remote sensing, showing that considerable blue carbon resources may be discovered with the use of turtles. Samples were taken for carbon stock estimation from the ground truthed sites. A mean carbon stock of 4.89 ± 0.83 kg Corg m-2 was estimated for 1 m depth sediment. In the future it is important to develop methods for mapping the surface areas of the deep and inaccessible seagrass habitats that the turtles discover.
Morphological and compositional control of a Zeolitic Imidazolate Framework for catalytic applications(2022-11-27) [Thesis]
Advisor: Han, Yu
Committee members: Lai, Zhiping; Huang, Kuo-WeiThe structures of metal-organic frameworks (MOFs) are highly tunable, which allows their properties to be regulated by varying the types of metal ions and organic linkers. As one of the most widely studied MOFs, ZIF-8 (ZIF: zeolite imidazolate framework) has demonstrated fascinating properties for separation and catalysis applications. However, there is a lack of studies on the morphological and compositional control of ZIF-8 crystals. In this thesis, we systematically investigate the effect of solvents (water and methanol) and metal sources (nitrate and acetate) on the properties of ZIF-8 and the efficiency of doping additional metals into ZIF-8. We found that the product obtained from nitrate and water had a broad crystal size distribution. When using nitrate and methanol, the size of product was not uniform while when using acetate and methanol, the doping amount is low. Interestingly, uniform ZIF-8 crystal with high Ni doping (up to 1.96%) can be obtained by using the combination of water and acetate. In addition, the developed water-based synthesis is environmentally friendly, efficient, and easy to scale up. A gram-level product can be obtained at room temperature for just 1 h, which fits the principle of green chemistry. Besides, compared with pristine ZIF-8, Ni-ZIF-8 shows a significantly enhanced catalytic conversion rate in the Knowevenagel reaction. Finally, a polymetallic ZIF-8 was synthesized using the same method since all single metallic ions doped ZIF-8 contribute to improving the catalytic activity. However, because the crystal size reaches the micrometer level and there is a slight decrease in the content of Ni, the reaction activity did not outperform that of 25%Ni-ZIF-8.
Gas Sensing Performance of Lu2CF2 MXene Monolayer Evaluated by Density Functional Theory and the Nonequilibrium Green’s Function Formalism(2022-11-23) [Thesis]
Advisor: Schwingenschlögl, Udo
Committee members: Laquai, Frédéric; Bagci, HakanThe effect of toxic gas on the environment, notably climate change, as well as public and individual health is severe. The gas sensor is therefore one of the most important technologies in our daily life. Metal oxides have been utilized as sensing materials for a long time, but their high operating temperature restricts their employment in a variety of applications. In contrast, MXenes, two-dimensional transition metal carbides, carbonitrides, or nitrides, attract attention due to their unusual material properties with a high surface-to-volume ratio and chemical stability are potential choices. They can be synthesized through the chemical exfoliation of MAX phases with their irreducible properties. Lu2CF2 is a unique MXenes family member. Using density functional theory with van der Waals dispersion correction, the application potential of the 2D MXene Lu2CF2 for gaseous pollutant sensing (CO, CO2, NO, NO2, NH3, H2S, and SO2) is studied. Distances and adsorption sites are determined. In addition to applying widely used theoretical approaches (adsorption energy, charge transfer, adsorption distance recovery time, and ionization energy) to evaluate gas sensing properties, the non-equilibrium Green's function formalism is used to calculate the current–voltage characteristics before and after gas adsorption. NO2 is chemisorbed with significant adsorption energies and apparent charge transfer, and NH3 is only weakly chemisorbed on the monolayer. (CO, CO2, H2S, and SO2) are physisorbed. The results indicate that the Lu2CF2 monolayer can detect SO2 with excellent performance as a gas sensor (high sensitivity, high selectivity, and rapid recovery time). Moreover, Non-equilibrium Green’s function calculations demonstrate large resistivity variations when SO2 molecules is adsorbed on the monolayer. Adsorption of (CO, H2S, and NH3). The adsorption of NH3 and SO2 molecules lowers the ionization energy of the monolayer considerably, indicating that it can be employed as an optical gas sensor for NH3 and SO2 detection. NO induces a magnetic moment in Lu2CF2, indicating that it could be used as a magnetic NO gas sensor. The sensing method provided symmetry-breaking structural distortions without changing the band gap.
Predicting Protein Functions From Interactions Using Neural Networks and Ontologies(2022-11-22) [Thesis]
Advisor: Hoehndorf, Robert
Committee members: Arold, Stefan T.; Moshkov, MikhailTo understand the process of life, it is crucial for us to study proteins and their functions. Proteins execute (almost) all cellular activities, and their functions are standardized by Gene Ontology (GO). The amount of discovered protein sequences grows rapidly as a consequence of the fast rate of development of technologies in gene sequencing. In UniProtKB, there are more than 200 million proteins. Still, less than 1% of the proteins in the UniProtKB database are experimentally GO-annotated, which is the result of the exorbitant cost of biological experiments. To minimize the large gap, developing an efficient and effective method for automatic protein function prediction (AFP) is essential. Many approaches have been proposed to solve the AFP problem. Still, these methods suffer from limitations in the way the knowledge of the domain is presented and what type of knowledge is included. In this work, we formulate the task of AFP as an entailment problem and exploit the structure of the related knowledge in a set and reusable framework. To achieve this goal, we construct a knowledge base of formal GO axioms and protein-protein interactions to use as background knowledge for AFP. Our experiments show that the approach proposed here, which allows for ontology awareness, improves results for AFP of proteins; they also show the importance of including protein-protein interactions for predicting the functions of proteins.
Commercial chemical vapor-deposited hexagonal boron nitride: how far is it from mechanically exfoliated-like quality?(2022-11-10) [Thesis]
Advisor: Lanza, Mario
Committee members: Zhang, Xixiang; Li, Xiaohang; Anthopoulos, Thomas D.Two-dimensional (2D) layered hexagonal boron nitride (h-BN) has become a very popular material in nanoelectronics in recent years because of its extraordinary chemical stability and thermal conductivity . Recently, h-BN is also commonly used as a dielectric material , and research in this area is still in its early stages. The commonly used methods for fabricating h-BN include mechanical exfoliation and chemical vapor deposition (CVD). CVD is a recognized industry-compatible method for producing large-area h-BN. However, studies have shown that multilayer h-BN grown by CVD is polycrystalline and contains multiple local defects . These defects and inhomogeneity cannot be avoided and lead to small amounts of atom-wide amorphous regions that have weak dielectric strength . Although the general characteristics of h-BN prepared by these two fabrication methods can be learned from different works in the literature, it is difficult to study the quality of h-BN without systematically comparing the differences between the two growth methods under the same experimental conditions and with large number of samples. This also makes it difficult for researchers to choose the best-quality h-BN. In this work, the morphological characteristics and electrical properties of mechanically exfoliated h-BN and CVD-grown h-BN from different sources have been compared under different conditions. Commercially available h-BN flakes mechanically exfoliated from NIMS h-BN bulk crystal show no leakage current at electrical fields up to 25.9 MV/cm, and above this applied electrical force, the size of the conductive spots is extremely small (1.99 ± 1.81 nm2). On the contrary, “monolayer” CVD-grown h-BN samples from Graphene Supermarket were shown to be amorphous in ~20% of their area, which makes them appear discontinuous from an electrical point of view, plus they contain large thickness fluctuations up to 6 layers. Moreover, in nanoelectronic measurements collected with a conductive atomic force microscope (CAFM) working in vacuum, mechanically exfoliated h-BN showed better electrical homogeneity and presented later dielectric breakdown compared to the h-BN samples fabricated by the CVD method.
Towards the Direct Synthesis of Gasoline-Range Hydrocarbons from Carbon Dioxide(2022-11) [Thesis]
Advisor: Gascon, Jorge
Committee members: Ruiz-Martinez, Javier; Cavallo, LuigiThe emergence of climate change led to major mitigation drives towards circular carbon economy and carbon neutrality. More specifically, an environmentally sustainable approach – stemming from reacting CO2 with green H2 – can be tailored to produce gasoline-range hydrocarbons. This would lead to further diversification from conventional energy, while also offering a valuable recycle route for CO2 emissions. This thesis successfully applied advanced chemical engineering concepts – via multifunctional heterogeneous catalysis – to directly convert CO2 into hydrocarbons, in the same reactor. The approach combined two catalysts: an In/Co bimetallic catalyst, which converted CO2 into methanol, and a Pt/Zn modified zeolite beta (BEA) catalyst, which converted methanol into hydrocarbons. High-throughput synthesis and catalytic reaction units were utilized to create and test 22 different catalysts – varying In-Co-Pt-Zn/BEA compositions and synthesis methods – in a total of 32 catalytic configurations. These catalysts were analyzed via techniques including XRD, WDXRF, BET, TGA, ICP-OES, pyridine-IR, TEM, and HAADF-STEM EDX, for further characterization and optimization. Results include the discovery of optimum catalytic configurations that led to methanol and isoparaffin selectivities upward of 70% and 60%, respectively – with minimal deactivation rates, at 300 ℃, 50 bar, and with H2/CO2 volumetric ratio of 4:1.
The Red Sea Coral Reef Cryptobiome: How do Nearby Benthic Communities Influence the Biodiversity of the Reef's Hidden Majority?(2022-11) [Thesis]
Advisor: Berumen, Michael L.
Committee members: Hong, Pei-Ying; Carvalho, SusanaMost of the reef's biodiversity remains undiscovered due to its complex tridimensional structure and the small size of the organisms that compose most of its biodiversity. To better understand the biodiversity of the major biological component of the reef environment (the cryptobiome), artificial cubic-like tools called Autonomous Reef Monitoring Structures (ARMS) were created to mimic the tridimensional nature of coral reefs. Here, I deployed 16 ARMS within four distinct benthic habitats on Tahla reef in the Red Sea (Saudi Arabia) to investigate how changes in reef habitats reflect changes in associated biodiversity of the cryptobiome. The following habitat types were selected after reef surveys and based on benthic coverage prevalence: i) Algae Pavement; ii) Rubble; iii) Plating corals; and iv) Branching corals. Habitats were located at the same depth contour (~10m), under similar exposure conditions and separated by at least 35m. The rugosity of the habitats was estimated based on the chain method, whereas monthly measurements of the physicochemical characteristics of the water were assessed by water collections (nutrients and chlorophyll a) and Conductivity-Temperature-Depth (CTD) instrument deployments (temperature, salinity). A fixed quadrat of approximately 15m2 was marked within each habitat type and four ARMS were deployed randomly within it. Units were retrieved after a period of approximately seven months for analysis of pioneer eukaryotic assemblages through traditional taxonomy identification of organisms larger than 2000μm, and through molecular metabarcoding using COI and 18S markers for the remaining ARMS fractions: sessile, 500μm-2000μm, and 106μm-500μm. To compare two distinct current methodologies to assess cryptobenthic taxa, water collections next to each ARMS unit were conducted right before retrieval. These samples were used to investigate the environmental DNA using the same COI and 18S markers. The biodiversity of the pioneer cryptobiome assemblage was analyzed through a combination of univariate and multivariate statistical methods. Overall, the habitats that showed greatest significantly distinct cryptobenthic community composition were Algae Pavement and Plating Corals, the ARMS and eDNA were defined as complementary techniques to assess the cryptofauna, and the use of a multi-marker approach increased the resolution of the cryptofauna characterization across different reef habitats.
Terrain-Based UAV Positioning: Tractable Models, Generalized Algorithms, and Analytical Results(2022-11) [Thesis]
Advisor: Alouini, Mohamed-Slim
Committee members: Gao, Xin; Eltawil, Ahmed; Trichili, AbderrahmenDeploying unmanned aerial vehicle (UAV) networks to provide coverage for outdoor users has attracted great attention during the last decade. Terrain information requires extensive attention in outdoor UAV networks, and it is one of the most important factors affecting coverage performance. Providing tractable models and common methods is necessary to generalize the terrain-based outdoor UAV positioning strategies. In this thesis, we demonstrate that UAVs can provide stable coverage for regularly moving users based on the existing local terrain reconstruction methods with UAV sampling. Next, a coarse-grained UAV deployment can be performed with a simple set of parameters that characterize the terrain features. A stochastic geometry framework can provide general analytical results for the above coarse-grained UAV networks. In addition, the UAV can avoid building blockage without prior terrain information through real-time linear-trajectory search. We proposed four algorithms related to the combinations of collecting prior terrain information and using real-time search, and then their performances are evaluated and compared in different scenarios. By adjusting the height of the UAV based on terrain information collected before networking, the performance is significantly enhanced compared to the one when no terrain information is available. The algorithm based on real-time search further improves the coverage performance by avoiding the shadow of buildings. During the execution of the real-time search algorithm, the search distance is reduced using the collected terrain information.