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- All Subjects: chemical engineering
- Creators: Deng, Shuguang
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Description
Membrane-based technology for gas separations is currently at an emerging stage of advancement and adoption for environmental and industrial applications due to its substantial advantages like lower energy and operating costs over the conventional gas separation technologies. Unfortunately, the available polymeric (or organic) membranes suffer a trade-off between permeance and selectivity. Mixed matrix membranes (MMMs) containing two-dimensional (2D) metal-organic frameworks (MOFs) as fillers are a highly sought approach to redress this trade-off given their enhanced gas permeabilities and selectivities compared to the pure polymeric membrane. These MMMs are increasingly gaining attention by researchers due to their unique properties and wide small- and large-scale gas separation applications. However, straightforward and scalable methods for the synthesis of MOFs nanosheets have thus far been persistently elusive. This study reports the single-phase preparation, and characterization of MMMs with 2D MOFs nanosheets as fillers. The prepared MOF and the polymer matrix form the ‘dense’ MMMs which exhibit increased gas diffusion resistance, and thus improved separation abilities. The single-phase approach was more successful than the bi-phase at synthesizing the MOFs. The influence of sonication power and time on the characteristics and performance of the membranes are examined and discussed. Increasing the sonication power from 50% to 100% reduces the pore size. Additionally, the ultimate effect on the selectivity and permeance of the MMMs with different single gases is reported. Analysis of results with various gas mixers indicates further performance improvements in these MMMs could be achieved by increasing sonication time and tuning suitable membrane thicknesses. Reported results reveal that MMMs are excellent candidates for next-generation gas mixture separations, with potential applications in CO2 capture and storage, hydrogen recovery, alkene recovery from alkanes, and natural gas purification.
ContributorsNkuutu, John (Author) / Mu, Bin (Thesis director) / Shan, Bohan (Committee member) / Chemical Engineering Program (Contributor) / School of Sustainability (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Layered double hydroxides (LDHs), also known as hydrotalcite-like materials, are extensively used as precursors for the preparation of (photo-)catalysts, electrodes, magnetic materials, sorbents, etc. The synthesis typically involves the transformation to the corresponding mixed metal oxide via calcination, resulting in atomically dispersed mixed metal oxides (MMOs). This process alters the porosity of the materials, with crucial implications for the performance in many applications. Yet, the mechanisms of pore formation and collapse are poorly understood. Combining an integrated in situ and ex situ characterization approach, here we follow the evolution of porosity changes during the thermal decomposition of LDHs integrating different divalent (Mg, Ni) and trivalent (Al, Ga) metals. Variations in porous properties determined by high-resolution argon sorption are linked to the morphological and compositional changes in the samples by in situ transmission electron microscopy coupled with energy dispersive X-ray spectroscopy, which is facilitated by the synthesis of well crystallized LDHs of large crystal size. The observations are correlated with the phase changes identified by X-ray diffraction, the mass losses evidenced by thermogravimetric analysis, the structural changes determined by infrared and nuclear magnetic resonance spectroscopy, and the pore connectivity analyzed by positron annihilation spectroscopy. The findings show that the multimetallic nature of the LDH governs the size and distribution (geometry, location, and connectivity) of the mesopores developed, which is controlled by the crystallization of the MMO phase, providing key insights for the improved design of porous mixed metal oxides.
ContributorsMurty, Rohan Aditya (Author) / Deng, Shuguang (Thesis director) / Nielsen, David R. (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Metal-organic frameworks (MOFs) are a new set of porous materials comprised of metals or metal clusters bonded together in a coordination system by organic linkers. They are becoming popular for gas separations due to their abilities to be tailored toward specific applications. Zirconium MOFs in particular are known for their high stability under standard temperature and pressure due to the strength of the Zirconium-Oxygen coordination bond. However, the acid modulator needed to ensure long range order of the product also prevents complete linker deprotonation. This leads to a powder product that cannot easily be incorporated into continuous MOF membranes. This study therefore implemented a new bi-phase synthesis technique with a deprotonating agent to achieve intergrowth in UiO-66 membranes. Crystal intergrowth will allow for effective gas separations and future permeation testing. During experimentation, successful intergrown UiO-66 membranes were synthesized and characterized. The degree of intergrowth and crystal orientations varied with changing deprotonating agent concentration, modulator concentration, and ligand:modulator ratios. Further studies will focus on achieving the same results on porous substrates.
ContributorsClose, Emily Charlotte (Author) / Mu, Bin (Thesis director) / Shan, Bohan (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Within recent years, metal-organic frameworks, or MOF’s, have gained a lot of attention in the materials research community. These micro-porous materials are constructed of a metal oxide core and organic linkers, and have a wide-variety of applications due to their extensive material characteristic possibilities. The focus of this study is the MOF-5 material, specifically its chemical stability in air. The MOF-5 material has a large pore size of 8 Å, and aperture sizes of 15 and 12 Å. The pore size, pore functionality, and physically stable structure makes MOF-5 a desirable material. MOF-5 holds applications in gas/liquid separation, catalysis, and gas storage. The main problem with the MOF-5 material, however, is its instability in atmospheric air. This inherent instability is due to the water in air binding to the zinc-oxide core, effectively changing the material and its structure. Because of this material weakness, the MOF-5 material is difficult to be utilized in industrial applications. Through the research efforts proposed by this study, the stability of the MOF-5 powder and membrane were studied. MOF-5 powder and a MOF-5 membrane were synthesized and characterized using XRD analysis. In an attempt to improve the stability of MOF-5 in air, methyl groups were added to the organic linker in order to hinder the interaction of water with the Zn4O core. This was done by replacing the terepthalic acid organic linker with 2,5-dimethyl terephthalic acid in the powder and membrane synthesis steps. The methyl-modified MOF-5 powder was found to be stable after several days of exposure to air while the MOF-5 powder exhibited significant crystalline change. The methyl-modified membrane was found to be unstable when synthesized using the same procedure as the MOF-5 membrane.
ContributorsAnderson, Anthony David (Author) / Lin, Jerry Y.S. (Thesis director) / Ibrahim, Amr (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Adsorption equilibrium is an important metric used to assess adsorbent performance for gas mixture separation processes. Gas adsorption processes such as carbon capture are becoming more urgent as climate change and global warming accelerate. To speed up and reduce the cost of research on adsorbent materials and adsorption processes, I developed an open-source Python code that generates mixed gas adsorption equilibrium data using pure gas adsorption isotherms based on the ideal adsorbed solution theory (IAST). The major efforts of this M.S. research were placed on adding additional components to the mixture models since most other publications focused on binary gas mixtures. Generated mixed-gas equilibrium data were compared to experimentally collected data in order to validate the multicomponent IAST model and to determine the accuracy of the computer codes developed in this work. Additional mixed-gas equilibrium data were then generated and analyzed for trends in the data for humid flue gas conditions, natural gas processing conditions, and hydrogen gas purification conditions. For humid flue gas conditions, neither the analyzed Mg-MOF-74 nor the Zeolite 13X were shown to be suitable for use. For natural gas processing conditions, the Zeolite 13X was determined to be a much better candidate for use than the MIL-101. For hydrogen gas purification conditions, the Zeolite 5A was determined to be a better adsorbent for use than CD-AC due to the Zeolite 5A’s much lower adsorption of H2.
ContributorsCiha, Trevor (Author) / Deng, Shuguang (Thesis advisor) / Machas, Michael (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2022
Idiographic Models of Walking Behavior for Personalized mHealth Interventions: Some Novel Approaches
Description
This thesis presents the development of idiographic models (i.e., single subject or N = 1) of walking behavior as a means of facilitating the design of control systems to optimize mobile health (mHealth) interventions for sedentary adults. Model-on-Demand (MoD), an adaptive modeling technique, is demonstrated as an ideal method for modeling nonlinear systems with noise on a simulated continuously stirred tank reactor (CSTR). Comparing MoD to AutoRegressive with eXogenous input (ARX) estimation, MoD outperforms ARX in terms of addressing both nonlinearity and noise in the CSTR system. With the CSTR system as an initial proof of concept, MoD is then used to model individual walking behavior using intervention data from participants of HeartSteps, a walking intervention that studies the effect of within-day suggestions. Given the number of possible measured features from which to design the MoD models, as well as the number of model parameters that influence the model’s performance, optimizing MoD models through exhaustive search is infeasible.
Consequently, a discrete implementation of simultaneous perturbation stochastic approximation (DSPSA) is shown to be an efficient algorithm to find optimal models of walking behavior. Combining MoD with DSPSA, models of walking behavior were developed using participant data from Just Walk, a day-to-day walking intervention; MoD outperformed ARX models on both estimation and validation data. DSPSA was also applied to ARX modeling, highlighting the use of DSPSA to not only search over model parameters and features but also data partitioning, as DSPSA was used to evaluate models under various combinations of estimation and validation data from a single participant’s walking data. Results of this thesis point to ARX with DSPSA as a routine means for dynamic model estimation in large-scale behavioral intervention settings.
ContributorsKha, Rachael T (Author) / Rivera, Daniel E (Thesis advisor) / Deng, Shuguang (Committee member) / Muhich, Christopher (Committee member) / Arizona State University (Publisher)
Created2022
Description
Polypropylene, a non-biodegradable plastic with a higher c-c bond disassociation energy than other conventional polymers like Polyethylene (PE), is used to manufacture these three-layered masks. The amount of plastic pollution in the environment has grown tremendously, nearing million tons in a short period of time. As a result, the purpose of this study is to reduce the environmental damage caused by facemasks. This M.S. thesis offers a concise overview of various thermochemical methods employed to depolymerize plastic waste materials. It emphasizes environmentally conscious and sustainable practices, specifically focusing on solvothermal processing. This innovative approach aims to convert discarded face masks into valuable resources, including hydrocarbons suitable for jet fuel and other useful products.
The thesis provides an in-depth exploration of experimental investigations into solvothermal liquefaction techniques. Operating under specific conditions, namely, a temperature of 350°C and a reaction duration of 90 minutes, the results were notably impressive. These results included an exceptional conversion rate of 99.8%, an oil yield of 39.3%, and higher heating values (HHV) of 46.81 MJ/kg for the generated oil samples. It's worth noting that the HHV of the oil samples obtained through the solvothermal liquefaction (STL) method, at 46.82 MJ/kg, surpasses the HHV of gasoline, which stands at 43.4 MJ/kg.
The significant role of the solvent in the depolymerization process involves the dissolution and dispersion of the feedstock through solvation. This reduces the required thermal cracking temperature by enhancing mass and thermal energy transfer. While solvolysis reactions between the solvent and feedstock are limited in thermal liquefaction, the primary depolymerization process follows thermal cracking. This involves the random scission of polypropylene (PP) molecules during heat treatment, with minimal polymerization, cyclization, and radical recombination reactions occurring through free radical mechanisms.
Overall, this work demonstrates the feasibility of a highly promising technique for the effective chemical upcycling of polypropylene-based plastics into valuable resources, particularly in the context of jet fuel hydrocarbons, showcasing the comprehensive analytical methods employed to characterize the products of this innovative process.
ContributorsAkula, kapil Chandra (Author) / Deng, Shuguang (Thesis advisor) / Fini, Elham (Committee member) / Salifu, Emmanuel (Committee member) / Arizona State University (Publisher)
Created2023
Description
The objective of this research is to create a python program that can describe the adsorption breakthrough performance of direct air capture of CO2 by zeolite and other adsorbents. The purpose of creating this open-source code is because many commercial simulation software for adsorption process simulation can be extremely expensive and typically are yearly subscriptions which can be a costly expenditure for academic research labs and chemical engineers working on adsorption processes development and design. The simulation models are generated by solving the governing mass and energy transfer equations and validating the models with experimental data. The typical inputs for the adsorption process simulation include adsorption equilibrium of both CO2 and N2 on selected adsorbents, mass transfer coefficients information, adsorbent bed length and void fraction, and other physical and chemical properties of the adsorbent being tested. The outputs of the simulation package are the dimensionless CO2 concentration profile as a function of dimensionless time, which is usually used for evaluating the adsorbent performance for CO2 capture. The models created were compared to the commercial package gPROMs and they performed extremely well. The main variation between the models created and gPROMs was that the models tended to underpredict the breakpoint of experimental data and gPROMs tended to overpredict. This M.S. research is part of the major research efforts for developing an open-source adsorption process simulation package for carbon capture and conversion in Prof. Deng’s group at ASU. The ultimate goal of this research program is to reduce carbon emissions and develop a sustainable solution for a future carbon-free economy.
ContributorsBonelli, Xavier Berlage (Author) / Deng, Shuguang (Thesis advisor) / Andino, Jean (Committee member) / Seo, Don (Committee member) / Arizona State University (Publisher)
Created2022
Description
The objective of this research was to develop Aluminophosphate-five (AlPO4-5, AFI) zeolite adsorbents for efficient oxygen removal from a process stream to support an on-going Department of Energy (DOE) project on solar energy storage. A molecular simulation study predicted that substituted AlPO4-5 zeolite can adsorb O2 through a weak chemical bond at ambient temperature. Substituted AlPO4-5 zeolite was successfully synthesized via hydrothermal crystallization by following carefully designed procedures to tailor the zeolite for efficient O2 adsorption. Synthesized AlPO4-5 in this work included Sn/AlPO-5, Mo/AlPO-5, Pd/AlPO-5, Si/AlPO-5, Mn/AlPO-5, Ce/AlPO-5, Fe/AlPO-5, CuCe/AlPO-5, and MnSnSi/AlPO-5. While not all zeolite samples synthesized were fully characterized, selected zeolite samples were characterized by powder x-ray diffraction (XRD) for crystal structure confirmation and phase identification, and nitrogen adsorption for their pore textural properties. The Brunauer-Emmett-Teller (BET) specific surface area and pore size distribution were between 172 m2 /g - 306 m2 /g and 6Å - 9Å, respectively, for most of the zeolites synthesized. Samples of great interest to this project such as Sn/AlPO-5, Mo/AlPO-5 and MnSnSi/AlPO-5 were also characterized using x-ray photoelectron spectroscopy (XPS) and energy-dispersive x-ray spectroscopy (EDS) for elemental analysis, scanning electron microscopy (SEM) for morphology and particle size estimation, and electron paramagnetic resonance (EPR) for nature of adsorbed oxygen. Oxygen and nitrogen adsorption experiments were carried out in a 3-Flex adsorption apparatus (Micrometrics) at various temperatures (primarily at 25℃) to determine the adsorption properties of these zeolite samples as potential adsorbents for oxygen/nitrogen separation. Experiments showed that some of the zeolite samples adsorb little-to-no oxygen and nitrogen at 25℃, while other zeolites such as Sn/AlPO-5, Mo/AlPO-5, and MnSnSi/AlPO-5 adsorb decent but inconsistent amounts of oxygen with the highest observed values of about 0.47 mmol/ g, 0.56 mmol/g, and 0.84 mmol/ g respectively. The inconsistency in adsorption is currently attributed to non-uniform doping of the zeolites, and these findings validate that some substituted AlPO4-5 zeolites are promising adsorbents. However, more investigations are needed to verify the causes of this inconsistency to develop a successful AlPO4-5 zeolite-based adsorbent for oxygen/nitrogen separation.
ContributorsBuyinza, Allan Smith (Author) / Deng, Shuguang (Thesis advisor) / Varman, Arul M (Committee member) / Jin, Kailong (Committee member) / Arizona State University (Publisher)
Created2021
Description
Physical inactivity is a major contributor to chronic illnesses and mortality globally. However, most interventions to address it rely on static, aggregate models that overlook idiographic (i.e., individual-level) dynamics, limiting intervention effectiveness. Leveraging mobile technology and control systems engineering principles, this dissertation provides a novel, comprehensive framework for personalized behavioral interventions that have been tested experimentally under the Control Optimization Trial (COT) paradigm. Through careful design of experiments, elaborate signal processing and model estimation, and judicious formulation of behavior intervention optimization as a control system problem, this dissertation develops tools to overcome challenges faced in the large-scale dissemination of mobile health (mHealth) interventions. A novel Three-Degrees-of-Freedom Kalman Filter-based Hybrid Model Predictive Control (3DoF-KF HMPC) controller is formulated for physical activity interventions and evaluated in a clinical trial, demonstrating its effectiveness. Furthermore, this dissertation expands on understanding the underlying dynamics influencing behavior change. Engineering principles are applied to develop a conceptual approach to generate dynamic hypotheses and translate these into first-principle dynamic models. The generated models are used in concert with system identification principles to enhance the design of experiments that yield dynamically informative data sets for behavioral medicine applications. Additionally, sophisticated search, filtering, and model estimation algorithms are applied to optimize and personalize model structures and estimate dynamic models that account for nonlinearities and “Just-in-Time” (JIT; moments of need, receptivity, and opportunity) context in behavior change systems. In addition, the pervasive issue of data missingness in interventions is addressed by integrating system identification principles with a Bayesian inference model-based technique for data imputation. The findings in this dissertation extend beyond physical activity, offering insights for promoting healthy behaviors in other applications, such as smoking cessation and weight management. The integration of control systems engineering in behavioral medicine research, as demonstrated in this dissertation, offers broad impacts by advancing the field's understanding of behavior change dynamics, enhancing accessibility to personalized behavioral health interventions, and improving patient outcomes. This research has the potential to radically improve behavioral interventions, increase affordability and accessibility, inspire interdisciplinary collaboration, and provide behavioral scientists with tools capable of addressing societal challenges in mHealth and preventive medicine.
ContributorsEl Mistiri, Mohamed (Author) / Rivera, Daniel E. (Thesis advisor) / Deng, Shuguang (Committee member) / Muhich, Christopher (Committee member) / Pavlic, Theodore P. (Committee member) / Zhang, Wenlong (Committee member) / Arizona State University (Publisher)
Created2024