Efficient Computation of Electromagnetic Waves in Hydrocarbon Exploration Using the Improved Numerical Mode Matching (NMM) Method

In this study, we developed and improved the numerical mode matching (NMM) method which has previously been shown to be a fast and robust semi-analytical solver to investigate the propagation of electromagnetic (EM) waves in an isotropic layered medium. The applicable models, such as cylindrical waveguide, optical fiber, and borehole with earth geological formation, are generally modeled as an axisymmetric structure which is an orthogonal-plano-cylindrically layered (OPCL) medium consisting of materials stratified planarly and layered concentrically in the orthogonal directions.

In this report, several important improvements have been made to extend applications of this efficient solver to the anisotropic OCPL medium. The formulas for anisotropic media with three different diagonal elements in the cylindrical coordinate system are deduced to expand its application to more general materials. The perfectly matched layer (PML) is incorporated along the radial direction as an absorbing boundary condition (ABC) to make the NMM method more accurate and efficient for wave diffusion problems in unbounded media and applicable to scattering problems with lossless media. We manipulate the weak form of Maxwell's equations and impose the correct boundary conditions at the cylindrical axis to solve the singularity problem which is ignored by all previous researchers. The spectral element method (SEM) is introduced to more efficiently compute the eigenmodes of higher accuracy with less unknowns, achieving a faster mode matching procedure between different horizontal layers. We also prove the relationship of the field between opposite mode indices for different types of excitations, which can reduce the computational time by half. The formulas for computing EM fields excited by an electric or magnetic dipole located at any position with an arbitrary orientation are deduced. And the excitation are generalized to line and surface current sources which can extend the application of NMM to the simulations of controlled source electromagnetic techniques. Numerical simulations have demonstrated the efficiency and accuracy of this method.

Finally, the improved numerical mode matching (NMM) method is introduced to efficiently compute the electromagnetic response of the induction tool from orthogonal transverse hydraulic fractures in open or cased boreholes in hydrocarbon exploration. The hydraulic fracture is modeled as a slim circular disk which is symmetric with respect to the borehole axis and filled with electrically conductive or magnetic proppant. The NMM solver is first validated by comparing the normalized secondary field with experimental measurements and a commercial software. Then we analyze quantitatively the induction response sensitivity of the fracture with different parameters, such as length, conductivity and permeability of the filled proppant, to evaluate the effectiveness of the induction logging tool for fracture detection and mapping. Casings with different thicknesses, conductivities and permeabilities are modeled together with the fractures in boreholes to investigate their effects for fracture detection. It reveals that the normalized secondary field will not be weakened at low frequencies, ensuring the induction tool is still applicable for fracture detection, though the attenuation of electromagnetic field through the casing is significant. A hybrid approach combining the NMM method and BCGS-FFT solver based integral equation has been proposed to efficiently simulate the open or cased borehole with tilted fractures which is a non-axisymmetric model.

Growth, Characterization, and Properties of Hybrid Graphene-Carbon Nanotube Films and Related Carbon Nanostructures

Graphene, first isolated in 2004 and the subject of the 2010 Nobel Prize in physics, has generated a tremendous amount of research interest in recent years due to its incredible mechanical and electrical properties. However, difficulties in large-scale production and low as-prepared surface area have hindered commercial applications. In this dissertation, a new material is described incorporating the superior electrical properties of graphene edge planes into the high surface area framework of carbon nanotube forests using a scalable and reproducible technology.

The objectives of this research were to investigate the growth parameters and mechanisms of a graphene-carbon nanotube hybrid nanomaterial termed “graphenated carbon nanotubes” (g-CNTs), examine the applicability of g-CNT materials for applications in electrochemical capacitors (supercapacitors) and cold-cathode field emission sources, and determine materials characteristics responsible for the superior performance of g-CNTs in these applications. The growth kinetics of multi-walled carbon nanotubes (MWNTs), grown by plasma-enhanced chemical vapor deposition (PECVD), was studied in order to understand the fundamental mechanisms governing the PECVD reaction process. Activation energies and diffusivities were determined for key reaction steps and a growth model was developed in response to these findings. Differences in the reaction kinetics between CNTs grown on single-crystal silicon and polysilicon were studied to aid in the incorporation of CNTs into microelectromechanical systems (MEMS) devices. To understand processing-property relationships for g-CNT materials, a Design of Experiments (DOE) analysis was performed for the purpose of determining the importance of various input parameters on the growth of g-CNTs, finding that varying temperature alone allows the resultant material to transition from CNTs to g-CNTs and finally carbon nanosheets (CNSs): vertically oriented sheets of few-layered graphene. In addition, a phenomenological model was developed for g-CNTs. By studying variations of graphene-CNT hybrid nanomaterials by Raman spectroscopy, a linear trend was discovered between their mean crystallite size and electrochemical capacitance. Finally, a new method for the calculation of nanomaterial surface area, more accurate than the standard BET technique, was created based on atomic layer deposition (ALD) of titanium oxide (TiO2).

Structure, Morphology, and Electrochemical Properties of Transition Metal Oxide, Hydroxide, and Phosphate Nanomaterials for Energy Storage

Energy storage technologies are crucial for efficient utilization of electricity. Supercapacitors and rechargeable batteries are of currently available energy storage systems. Transition metal oxides, hydroxides, and phosphates are the most intensely investigated electrode materials for supercapacitors and rechargeable batteries due to their high theoretical charge storage capacities resulted from reversible electrochemical reactions. Their insulating nature, however, causes sluggish electron transport kinetics within these electrode materials, hindering them from reaching the theoretical maximum. The conductivity of these transition metal based-electrode materials can be improved through three main approaches; nanostructuring, chemical substitution, and introducing carbon matrices. These approaches often lead to unique electrochemical properties when combined and balanced.

Ethanol-mediated solvothermal synthesis we developed is found to be highly effective for controlling size and morphology of transition metal-based electrode materials for both pseudocapacitors and batteries. The morphology and the degree of crystallinity of nickel hydroxide are systematically changed by adding various amounts glucose to the solvothermal synthesis. Nickel hydroxide produced in this manner exhibited increased pseudocapacitance, which is partially attributed to the increased surface area. Interestingly, this morphology effect on cobalt doped-nickel hydroxide is found to be more effective at low cobalt contents than at high cobalt contents in terms of improving the electrochemical performance.

Moreover, a thin layer of densely packed nickel oxide flakes on carbon paper substrate was successfully prepared via the glucose-assisted solvothermal synthesis, resulting in the improved electrode conductivity. When reduced graphene oxide was used for conductive coating on as-prepared nickel oxide electrode, the electrode conductivity was only slightly improved. This finding reveals that the influence of reduced graphene oxide coating, increasing the electrode conductivity, is not that obvious when the electrode is already highly conductive to begin with.

We were able to successfully control the interlayer spacing and reduce the particle size of layered titanium hydrogeno phosphate material using our ethanol-mediated solvothermal reaction. In layered structure, interlayer spacing is the key parameter for fast ion diffusion kinetics. The nanosized layered structure prepared via our method, however, exhibited high sodium-ion storage capacity regardless of the interlayer spacing, implying that interlayer space may not be the primary factor for sodium-ion diffusion in nanostructured materials, where many interstitials are available for sodium-ion diffusion.

Our ethanol-mediated solvothermal reaction was also effective for synthesis of NaTi2(PO4)3 nanoparticles with uniform size and morphology, well connected by a carbon nanotube network. This composite electrode exhibited high capacity, which is comparable to that in aqueous electrolyte, probably due to the uniform morphology and size where the preferable surface for sodium-ion diffusion is always available in all individual particles.

Fundamental understandings of the relationship between electrode microstructures and electrochemical properties discussed in this dissertation will be important to design high performance energy storage system applications.

Posttranscriptional Regulation of Embryonic Neurogenesis by the Exon Junction Complex

The six-layered neuron structure in the cerebral cortex is the foundation for human mental abilities. In the developing cerebral cortex, neural stem cells undergo proliferation and differentiate into intermediate progenitors and neurons, a process known as embryonic neurogenesis. Disrupted embryonic neurogenesis is the root cause of a wide range of neurodevelopmental disorders, including microcephaly and intellectual disabilities. Multiple layers of regulatory networks have been identified and extensively studied over the past decades to understand this complex but extremely crucial process of brain development. In recent years, post-transcriptional RNA regulation through RNA binding proteins has emerged as a critical regulatory nexus in embryonic neurogenesis. The exon junction complex (EJC) is a highly conserved RNA binding complex composed of four core proteins, Magoh, Rbm8a, Eif4a3, and Casc3. The EJC plays a major role in regulating RNA splicing, nuclear export, subcellular localization, translation, and nonsense mediated RNA decay. Human genetic studies have associated individual EJC components with various developmental disorders. We showed previously that haploinsufficiency of Magoh causes microcephaly and disrupted neural stem cell differentiation in mouse. However, it is unclear if other EJC core components are also required for embryonic neurogenesis. More importantly, the molecular mechanism through which the EJC regulates embryonic neurogenesis remains largely unknown. Here, we demonstrated with genetically modified mouse models that both Rbm8a and Eif4a3 are required for proper embryonic neurogenesis and the formation of a normal brain. Using transcriptome and proteomic analysis, we showed that the EJC posttranscriptionally regulates genes involved in the p53 pathway, splicing and translation regulation, as well as ribosomal biogenesis. This is the first in vivo evidence suggesting that the etiology of EJC associated neurodevelopmental diseases can be ribosomopathies. We also showed that, different from other EJC core components, depletion of Casc3 only led to mild neurogenesis defects in the mouse model. However, our data suggested that Casc3 is required for embryo viability, development progression, and is potentially a regulator of cardiac development. Together, data presented in this thesis suggests that the EJC is crucial for embryonic neurogenesis and that the EJC and its peripheral factors may regulate development in a tissue-specific manner.

Bridging the Scale Gap from Leaf to Canopy in Biosphere-Atmosphere Gas and Particle Exchanges

Terrestrial ecosystems, occupying more than 25% of the Earth's surface, can serve as

`biological valves' in regulating the anthropogenic emissions of atmospheric aerosol

particles and greenhouse gases (GHGs) as responses to their surrounding environments.

While the signicance of quantifying the exchange rates of GHGs and atmospheric

aerosol particles between the terrestrial biosphere and the atmosphere is

hardly questioned in many scientic elds, the progress in improving model predictability,

data interpretation or the combination of the two remains impeded by

the lack of precise framework elucidating their dynamic transport processes over a

wide range of spatiotemporal scales. The diculty in developing prognostic modeling

tools to quantify the source or sink strength of these atmospheric substances

can be further magnied by the fact that the climate system is also sensitive to the

feedback from terrestrial ecosystems forming the so-called `feedback cycle'. Hence,

the emergent need is to reduce uncertainties when assessing this complex and dynamic

feedback cycle that is necessary to support the decisions of mitigation and

adaptation policies associated with human activities (e.g., anthropogenic emission

controls and land use managements) under current and future climate regimes.

With the goal to improve the predictions for the biosphere-atmosphere exchange

of biologically active gases and atmospheric aerosol particles, the main focus of this

dissertation is on revising and up-scaling the biotic and abiotic transport processes

from leaf to canopy scales. The validity of previous modeling studies in determining

iv

the exchange rate of gases and particles is evaluated with detailed descriptions of their

limitations. Mechanistic-based modeling approaches along with empirical studies

across dierent scales are employed to rene the mathematical descriptions of surface

conductance responsible for gas and particle exchanges as commonly adopted by all

operational models. Specically, how variation in horizontal leaf area density within

the vegetated medium, leaf size and leaf microroughness impact the aerodynamic attributes

and thereby the ultrane particle collection eciency at the leaf/branch scale

is explored using wind tunnel experiments with interpretations by a porous media

model and a scaling analysis. A multi-layered and size-resolved second-order closure

model combined with particle

uxes and concentration measurements within and

above a forest is used to explore the particle transport processes within the canopy

sub-layer and the partitioning of particle deposition onto canopy medium and forest

oor. For gases, a modeling framework accounting for the leaf-level boundary layer

eects on the stomatal pathway for gas exchange is proposed and combined with sap

ux measurements in a wind tunnel to assess how leaf-level transpiration varies with

increasing wind speed. How exogenous environmental conditions and endogenous

soil-root-stem-leaf hydraulic and eco-physiological properties impact the above- and

below-ground water dynamics in the soil-plant system and shape plant responses

to droughts is assessed by a porous media model that accommodates the transient

water

ow within the plant vascular system and is coupled with the aforementioned

leaf-level gas exchange model and soil-root interaction model. It should be noted

that tackling all aspects of potential issues causing uncertainties in forecasting the

feedback cycle between terrestrial ecosystem and the climate is unrealistic in a single

dissertation but further research questions and opportunities based on the foundation

derived from this dissertation are also brie

y discussed.

Descending Control of Limb Movements in Drosophila melanogaster

Because the interactions between feedforward influences are inextricably linked during many motor outputs (including but not limited to walking), the contribution of descending inputs to the generation of movements is difficult to study. Here we take advantage of the relatively small number of descending neurons (DNs) in the Drosophila melanogaster model system. We first characterize the number and distribution of the DN populations, then present a novel load free preparation, which enables the study of descending control on limb movements in a context where sensory feedback can be is reduced while leaving the nervous system, musculature, and cuticle of the animal relatively intact. Lastly we use in-vivo whole cell patch clamp electrophysiology to characterize the role of individual DNs in response to specific sensory stimuli and in relationship to movement. We find that there are approximately 1100 DNs in Drosophila that are distributed across six clusters. Input from these DNs is not necessary for coordinated motor activity, which can be generated by the thoracic ganglion, but is necessary for the specific combinations of joint movements typically observed in walking. Lastly, we identify a particular cluster of DNs that are tuned to sensory stimuli and innervate the leg neuromeres. We propose that a multi-layered interaction between these DNs, other DNs, and motor circuits in the thoracic ganglia enable the diverse but well-coordinated range of motor outputs an animal might exhibit.