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  • Novel Materials Based on Poly(2-Oxazoline): Synthesis, Molecular Characterization, and Application in Drug Delivery

    Alkattan, Nedah S. (2023-06-01) [Dissertation]
    Advisor: Hadjichristidis, Nikos
    Committee members: Nunes, Suzana Pereira; Khashab, Niveen M.; Avgeropoulos, Apostolos
    Poly(2-oxazolines) (POxs) are a class of polymers that have gained significant interest in biomedical applications. POxs are mainly synthesized using living cationic ring-opening polymerization (CROP) under microwave irradiation. POxs are considered pseudo-polypeptides because they are similar to polypeptides. Nevertheless, they are more chemically stable than polypeptides due to the presence of tertiary amides. POxs The major goal of this research is to synthesize and characterize a novel well-defined amphiphilic block copolymer based on POxs. These amphiphilic block copolymers can comprise core cross-linked star polymers (CCS) or linear block copolymers. This research demonstrates and describes the synthesis of poly(2-methyl-2-oxazoline-b-poly(2,2'-(1,4-phenylene)bis-2-oxazoline)-co-(2-n-2-butyl-2-oxazoline)(PMeOx-b-P(PhenBisOx-co-ButOx) amphiphilic core cross-linked star polymers (CCS) based on POxs. The CCS polymers are synthesized via sequential CROP in two steps by synthesizing Poly(2-methyl-2-oxazoline) (PMeOx) as the living arms followed by cross-linking of the core 2, 2’-(1,4-phenylene)bis-2-oxazoline (PhenBisOx) as the cross-linker and 2-n-butyl-2-oxazoline (ButOx) as a hydrophobic monomer to form the core of the CCS polymers. In addition, this research will clarify the other kinds of amphiphilic copolymers based on aggregation-induced emission (AIE) fluorophores, tetraphenylethylene (TPE) as an initiator that have been synthesized by a combination of cationic and anionic ROP. First, the difunctional initiator TPE-(OH)2 was synthesized via McMurry coupling reaction. Then, two kinds of triblock copolymers, TPE-poly(2-methyl-2-oxazoline)-b-poly(ε-caprolactone) (TPE-(PMeOx-b-PCL)2) and TPE-poly(ε-caprolactone)-b-poly(2-methyl-2-oxazoline) (TPE-(PCL-b-PMeOx)2), were synthesized by altering the sequence of polymerization. The resulting polymers, CCS polymers and the triblock copolymers were loaded with the anticancer drug doxorubicin (DOX) and their in vitro properties, cytotoxicity, and drug release at different pH were studied. Furthermore, the resulting polymers were characterized by size exclusion chromatography (SEC), nuclear magnetic resonance (NMR), dynamic light scattering (DLS), and transmission electron microscopy (TEM). All results in this research showed that the amphiphilic block copolymers, the CCS polymers and the triblock copolymers could be suitable carriers for drug delivery systems.
  • Comprehensive Kinetic Study of Oxidative Coupling of Methane (OCM) over La2O3-based catalysts

    Wang, Haoyi (2022-12) [Dissertation]
    Advisor: Sarathy, Mani
    Committee members: Gascon, Jorge; Farooq, Aamir; Chin, Ya-Huei (Cathy)
    Oxidative coupling of methane (OCM) represents a potentially viable method to convert methane directly into more desirable products such as ethane, and ethylene. In this dissertation, a comprehensive kinetic study of oxidative coupling of methane was performed over La2O3-based catalysts. An accurate and reliable gas-phase model is critical for the entire mechanism. The gas-phase kinetics was first studied using a jet-stirred reactor without catalyst. Both experiments and simulations were conducted under various operating conditions using different gas-phase models. Quantities of interest and rate of production analyses on hydrocarbon products were also performed to evaluate the models. NUIGMech1.1 was selected as the most comprehensive model to describe the OCM gas-phase kinetics and used for the next study. Next, microkinetic analysis on La2O3-based catalysts with different dopants was performed. The Ce addition has the greatest boost over the performance. The kinetics at low conversion regimes were analyzed and correlated to the catalysts’ properties. The activation energy for methane hydrogen abstraction was estimated, with the formation rate of primary products, which suggested that the initiation reaction steps were similar for La2O3-based catalyst. A homogeneous-heterogeneous kinetic model for La2O3/CeO2 catalyst was then constructed. By applying in situ XRD, the doping of CeO2 not only enhanced catalytic performance but also improved catalyst stability from CO2 and H2O. A wide range of operating conditions was investigated experimentally and numerically, where a packed bed reactor model was constructed based on the dimensions of experimental setup and catalyst characterization. The rate of production (ROP) was also performed to identify the important reactions and prove the necessity of surface reactions for the OCM process. Laser-induced fluorescence was implemented to directly observe the presence of formaldehyde. The last section includes the implementation of in situ laser diagnosis techniques at the near-surface region to solve the existing challenges. Raman scattering was implemented to quantitate the concentration profiles of major stable species near the surface and measure the in situ local temperatures at different heights above the catalyst surface, to study the kinetics transiting from the surface edge to the near-surface gas phase and provide a new perspective in OCM kinetic studies.
  • Gaussian Blue Noise

    Ahmed, Abdalla G.M.; Ren, Jing; Wonka, Peter (ACM Transactions on Graphics, Association for Computing Machinery (ACM), 2022-11-30) [Article]
    Among the various approaches for producing point distributions with blue noise spectrum, we argue for an optimization framework using Gaussian kernels. We show that with a wise selection of optimization parameters, this approach attains unprecedented quality, provably surpassing the current state of the art attained by the optimal transport (BNOT) approach. Further, we show that our algorithm scales smoothly and feasibly to high dimensions while maintaining the same quality, realizing unprecedented high-quality high-dimensional blue noise sets. Finally, we show an extension to adaptive sampling.
  • Improving deep learning performance for predicting large-scale geological CO2 sequestration modeling through feature coarsening

    Yan, Bicheng; Harp, Dylan Robert; Chen, Bailian; Pawar, Rajesh J. (Scientific Reports, Springer Science and Business Media LLC, 2022-11-30) [Article]
    Physics-based reservoir simulation for fluid flow in porous media is a numerical simulation method to predict the temporal-spatial patterns of state variables (e.g. pressure p) in porous media, and usually requires prohibitively high computational expense due to its non-linearity and the large number of degrees of freedom (DoF). This work describes a deep learning (DL) workflow to predict the pressure evolution as fluid flows in large-scale 3-dimensional(3D) heterogeneous porous media. In particular, we develop an efficient feature coarsening technique to extract the most representative information and perform the training and prediction of DL at the coarse scale, and further recover the resolution at the fine scale by spatial interpolation. We validate the DL approach to predict pressure field against physics-based simulation data for a field-scale 3D geologic CO2 sequestration reservoir model. We evaluate the impact of feature coarsening on DL performance, and observe that the feature coarsening not only decreases the training time by >74% and reduces the memory consumption by >75%, but also maintains temporal error 0.63% on average. Besides, the DL workflow provides predictive efficiency with 1406 times speedup compared to physics-based numerical simulation. The key findings from this research significantly improve the training and prediction efficiency of deep learning model to deal with large-scale heterogeneous reservoir models, and thus it can also be further applied to accelerate workflows of history matching and reservoir optimization for close-loop reservoir management.
  • Enhanced Selectivity in the Electroproduction of H2O2 via F/S Dual-Doping in Metal-Free Nanofibers

    Xiang, Fei; Zhao, Xuhong; Yang, Jian; Li, Ning; Gong, Wenxiao; Liu, Yizhen; Burguete-Lopez, A.; Li, Yulan; Niu, Xiaobin; Fratalocchi, Andrea (Advanced Materials, Wiley, 2022-11-30) [Article]
    Electrocatalytic two-electron oxygen reduction (2e- ORR) to hydrogen peroxide (H2 O2 ) is attracting broad interest in diversified areas including paper manufacturing, wastewater treatment, production of liquid fuels, and public sanitation. Current efforts focus on researching low-cost, large-scale, and sustainable electrocatalysts with high activity and selectivity. Here we engineer large-scale H2 O2 electrocatalysts based on metal-free carbon fibers with a fluorine and sulfur dual-doping strategy. Optimized samples yield with a high onset potential of 0.814 V versus reversible hydrogen electrode (RHE), an almost an ideal 2e- pathway selectivity of 99.1%, outperforming most of the recent reported carbon-based or metal-based electrocatalysts. First principle theoretical computations and experiments demonstrate that the intermolecular charge transfer coupled with electron spin redistribution from fluorine and sulfur dual-doping is the crucial factor contributing to the enhanced performances in 2e- ORR. This work opens the door to the design and implementation of scalable, earth-abundant, highly selective electrocatalysts for H2 O2 production and other catalytic fields of industrial interest.

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