Of the emerging photovoltaic technologies, perovskite solar cells (PSCs) are arguably among the most promising candidates for commercialization. Worldwide interest has prompted researchers to produce tens of thousands of studies on the topic, making PSCs one of the most active research topics of the past decade. Unfortunately, the rapid output of a substantial number of publications has made the traditional literature review process and research plans cumbersome tasks for both the novice and expert. In...

The standard approach to analyzing brain electrical activity is to examine the spectral density function (SDF) and identify frequency bands, defined apriori, that have the most substantial relative contributions to the overall variance of the signal. However, a limitation of this approach is that the precise frequency and bandwidth of oscillations are not uniform across cognitive demands. Thus, these bands should not be arbitrarily set in any analysis. To overcome this limitation, we propose three...

Soot prediction from combustion systems is still a major challenge in high-fidelity simulations of reactive flows, especially in turbulent conditions. Among the critical aspects, due to its slow characteristic formation times, soot sensitivity to strain rate and turbulence-chemistry interaction models for combustion closure can be found. Starting from the laminar problem, Soot Formation (SF) and Soot Formation Oxidation (SFO) counterflow flames are studied, allowing assessment of the roles of the different underlying phenomena concurring at...

Physical entanglement in polymer melt are the basis of our understanding for rheological response of polymer melts and they strongly influence crystallization kinetics and, retrospectively, the resultant mechanical properties of the material. It is known that by increasing the molar mass of the polymeric material it enhances the resultant mechanical properties, ultimately changing a commodity plastic into an engineering polymer. However, considering that the molar mass between entanglements is an intrinsic property of a polymer,...

With video data dominating the internet traffic, it is crucial to develop automated models that can analyze and understand what humans do in videos. Such models must solve tasks such as action classification, temporal activity localization, spatiotemporal action detection, and video captioning. This dissertation aims to identify the challenges hindering the progress in human action understanding and propose novel solutions to overcome these challenges. We identify three challenges: (i) the lack of tools to systematically...

Neural Networks are powerful tools used in Machine Learning to solve complex problems across many domains, including biological classification, self-driving cars, and automated management of distributed systems. However, practitioners' trust in Neural Network models is limited by their inability to answer important questions about their behavior, such as whether they will perform correctly or if they can be entrusted with private data. One major issue with Neural Networks is their "black-box" nature, which makes it...

Transportation produces about 25% of the global CO2 emissions, with gasoline and diesel light-duty vehicles being responsible for nearly half the transportation sector energy use. The reduction of emissions from transportation is an enormous challenge. While electrification is on the horizon, around 70% of the world’s vehicles are expected to be non-electric by 2050. One pragmatic way of tackling the emissions is to optimize the systems employed in the over 1 billion vehicles on the...

With 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...

Fractional diffusion equations have played an increasingly important role in ex- plaining long-range interactions, nonlocal dynamics and anomalous diffusion, pro- viding effective means of describing the memory and hereditary properties of such processes. This dissertation explores the uncertainty propagation in space fractional diffusion equations in one and multiple dimensions with variable diffusivity and order parameters. This is achieved by:(i) deploying accurate numerical schemes of the forward problem, and (ii) employing uncertainty quantifications tools that accelerate...

It 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...

Rapid 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...

The success of Generative Adversarial Networks (GANs) has resulted in unprecedented quality both for image generation and manipulation. Recent state-of-the-art GANs (e.g., the StyleGAN series) have demonstrated outstanding results in photo-realistic image generation. In this dissertation, we explore the latent space properties, including image manipulation, extraction of 3D properties, and performing various weakly supervised and unsupervised downstream tasks using StyleGAN and its derivative architectures. First, we study the images' projection into StyleGAN's latent space and...

In this dissertation, three different coupled systems of volume integral and hydrodynamic equations are formulated to analyze electromagnetic scattering from composite plasmonic structures consisting of dielectrics, metals, or semiconductors. First coupled system of volume integral and hydrodynamic equations is formulated to describe the electromagnetic interactions on nanostructures consisting of metallic and dielectric parts. The hydrodynamic equation is enforced in metallic parts while the volume integral equation is enforced in both metallic and dielectric parts. This...

Free-space optical communication (FSO) has been proposed as an attractive alternative to radio frequency communication in the sense that it provides wide bandwidth and high capacity without requirement of license. However, the scalability of FSO link is limited by pointing error, atmospheric turbulence, and loss. Especially, when it comes to the FSO link between moving platforms, it is imperative works to analyze the statistical channel model considering accurate pointing errors and atmospheric turbulence at the...

Challenging drilling applications and fluctuating oil prices have created a new emphasis on developing innovative technology to enhance safety and reduce cost. During drilling operations, an estimate of the rock strength is usually derived from monitoring downhole drilling forces. Recent advances in downhole measurement technologies allow for accurately estimating these forces at the drill bit, thus reconstructing the rock strength along the well as a 1D-profile. This dissertation presents a novel in-cutter force sensing technology...

This thesis considers the reconstruction of subsurface models from seismic observations, a well-known high-dimensional and ill-posed problem. As a first regularization to such a problem, a reduction of the parameters' space is considered following a truncated Discrete Cosine Transform (DCT). This helps regularizing the seismic inverse problem and alleviates its computational complexity. A second regularization based on Laplace priors as a way of accounting for sparsity in the model is further proposed to enhance the...

History matching is a critical process used for calibrating simulation models and assessing subsurface uncertainties. This common technique aims to align the reservoir models with the observed data. However, achieving this goal is often challenging due to the non uniqueness of the solution, underlying subsurface uncertainties, and usually the high computational cost of simulations. The traditional approach is often based on trial and error, which is exhaustive and labor-intensive. Some analytical and numerical proxies combined...

With the lithium demand sharply increasing, mainly due to the fast development of electric vehicles, the lithium extraction from salt lake brines attracts a massive attention. However, the challenge of highly separating Li+ over Mg2+ from salt lakes retards the exploitation of this natural treasure. Nanofiltration (NF) is considered a promising technology to fulfillthe vital challenge due to its advantages of low energy consumption and low footprint. However, current NF membranes suffer from low selectivity....

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...

Aggregation-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...

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...

The rise of atmospheric CO2 is a threat to many ecosystems, including coral reefs. Rising sea surface temperatures are known to interfere on coral health and cause extensive worldwide mortality. In the Red Sea, coral reefs are spread across 18 degrees of latitude, resulting in a temperature gradient with maximum monthly mean sea surface temperatures ranging from around 33 °C in the south to 27°C in the north. Such gradients can lead to adaptations to...

Organic solvent nanofiltration (OSN) is a membrane-based technique that separate molecules ranging between 100–2000 g mol–1. OSN has emerged as a promising alternative for applications in the petrochemical industry. Most OSN membranes are either integrally skinned asymmetric (ISA) or thin-film composites (TFC). Interfacially polymerized TFC membranes have been identified as potential OSN membranes with separation at a molecular level. Recent research showed the limitation of interfacially polymerized and commercial membranes for non-polar solvent nanofiltration, which...

Deep generative models are deep learning-based methods that are optimized to synthesize samples of a given distribution. During the past years, they have attracted a lot of interest from the research community, and the developed tools now enjoy many practical applications in content creation and editing. In computer vision, such models are typically built for images, videos, and 3D objects. Recently, there has emerged a paradigm of neural fields, which unifies the representations of such...

This thesis tackles the geometric modeling of quad meshes for fabrication-aware design, with a focus on introducing planarity to the structural elements for efficient manufacturing in architectural practice. Many architectural structures can be computationally represented by quad meshes which obey various constraints. These constraints concern planarity of faces, planarity of vertex stars, configuration of supporting structures, static equilibrium and others. This thesis draws attention to novel methods of computing such constrained quad meshes. A new...