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- All Subjects: chemical engineering
- Creators: Deng, Shuguang
Description
Excessive weight gain during pregnancy is a significant public health concern and has been the recent focus of novel, control systems-based interventions. Healthy Mom Zone (HMZ) is an intervention study that aims to develop and validate an individually tailored and intensively adaptive intervention to manage weight gain for overweight or obese pregnant women using control engineering approaches. Motivated by the needs of the HMZ, this dissertation presents how to use system identification and state estimation techniques to assist in dynamical systems modeling and further enhance the performance of the closed-loop control system for interventions.
Underreporting of energy intake (EI) has been found to be an important consideration that interferes with accurate weight control assessment and the effective use of energy balance (EB) models in an intervention setting. To better understand underreporting, a variety of estimation approaches are developed; these include back-calculating energy intake from a closed-form of the EB model, a Kalman-filter based algorithm for recursive estimation from randomly intermittent measurements in real time, and two semi-physical identification approaches that can parameterize the extent of systematic underreporting with global/local modeling techniques. Each approach is analyzed with intervention participant data and demonstrates potential of promoting the success of weight control.
In addition, substantial efforts have been devoted to develop participant-validated models and incorporate into the Hybrid Model Predictive Control (HMPC) framework for closed-loop interventions. System identification analyses from Phase I led to modifications of the measurement protocols for Phase II, from which longer and more informative data sets were collected. Participant-validated models obtained from Phase II data significantly increase predictive ability for individual behaviors and provide reliable open-loop dynamic information for HMPC implementation. The HMPC algorithm that assigns optimized dosages in response to participant real time intervention outcomes relies on a Mixed Logical Dynamical framework which can address the categorical nature of dosage components, and translates sequential decision rules and other clinical considerations into mixed-integer linear constraints. The performance of the HMPC decision algorithm was tested with participant-validated models, with the results indicating that HMPC is superior to "IF-THEN" decision rules.
Underreporting of energy intake (EI) has been found to be an important consideration that interferes with accurate weight control assessment and the effective use of energy balance (EB) models in an intervention setting. To better understand underreporting, a variety of estimation approaches are developed; these include back-calculating energy intake from a closed-form of the EB model, a Kalman-filter based algorithm for recursive estimation from randomly intermittent measurements in real time, and two semi-physical identification approaches that can parameterize the extent of systematic underreporting with global/local modeling techniques. Each approach is analyzed with intervention participant data and demonstrates potential of promoting the success of weight control.
In addition, substantial efforts have been devoted to develop participant-validated models and incorporate into the Hybrid Model Predictive Control (HMPC) framework for closed-loop interventions. System identification analyses from Phase I led to modifications of the measurement protocols for Phase II, from which longer and more informative data sets were collected. Participant-validated models obtained from Phase II data significantly increase predictive ability for individual behaviors and provide reliable open-loop dynamic information for HMPC implementation. The HMPC algorithm that assigns optimized dosages in response to participant real time intervention outcomes relies on a Mixed Logical Dynamical framework which can address the categorical nature of dosage components, and translates sequential decision rules and other clinical considerations into mixed-integer linear constraints. The performance of the HMPC decision algorithm was tested with participant-validated models, with the results indicating that HMPC is superior to "IF-THEN" decision rules.
ContributorsGuo, Penghong (Author) / Rivera, Daniel E. (Thesis advisor) / Peet, Matthew M. (Committee member) / Forzani, Erica (Committee member) / Deng, Shuguang (Committee member) / Pavlic, Theodore P. (Committee member) / Arizona State University (Publisher)
Created2018
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
The project aims at utilization of hydrothermal liquefaction (HTL) byproducts like biochar to grow microalgae. HTL is a promising method to convert wet algal biomasses into biofuels. The initial microalgae liquefaction at a temperature of 300 °C for 30 minute, converted 31.22 % of the Galdieria sulphuraria and 41.00 % of the Kirchneriella cornutum into biocrude. Upon changing the reactor from a 100 ml to a 250 ml reactor, the yield in biocrude increased to 31.48 % for G. sulphuraria and dropped to 38.05 % for K. cornutum. Further, energy recoveries based on calorific values of HTL products were seen to drop by about 5 % of the 100 ml calculated values in the larger reactor.
Biochar from HTL of G. sulphuraria at 300 °C showed 15.98 and 5.27 % of phosphorous and nitrogen, respectively. HTL products from the biomass were analyzed for major elements through ICP-OES and CHNS/O. N and P are macronutrients that can be utilized in growing microalgae. This could reduce the operational demands in growing algae like, phosphorous mined to meet annual national demand for aviation fuel. Acidic leaching of these elements as phosphates and ammoniacal nitrogen was studied. Improved leaching of 49.49 % phosphorous and 95.71 % nitrogen was observed at 40 °C and pH 2.5 over a period of 7 days into the growth media. These conditions being ideal for growth of G. sulphuraria, leaching can be done in-situ to reduce overhead cost.
Growth potential of G. sulphuraria in leached media was compared to a standard cyanidium media produced from inorganic chemicals. Initial inhibition studies were done in the leached media at 40 °C and 2-3 vol. % CO2 to observe a positive growth rate of 0.273 g L-1 day-1. Further, growth was compared to standard media with similar composition in a 96 well plate 50 μL microplate assay for 5 days. The growth rates in both media were comparable. Additionally, growth was confirmed in a 240 times larger tubular reactor in a Tissue Culture Roller drum apparatus. A better growth was observed in the leached cyanidium media as compared to the standard variant.
Biochar from HTL of G. sulphuraria at 300 °C showed 15.98 and 5.27 % of phosphorous and nitrogen, respectively. HTL products from the biomass were analyzed for major elements through ICP-OES and CHNS/O. N and P are macronutrients that can be utilized in growing microalgae. This could reduce the operational demands in growing algae like, phosphorous mined to meet annual national demand for aviation fuel. Acidic leaching of these elements as phosphates and ammoniacal nitrogen was studied. Improved leaching of 49.49 % phosphorous and 95.71 % nitrogen was observed at 40 °C and pH 2.5 over a period of 7 days into the growth media. These conditions being ideal for growth of G. sulphuraria, leaching can be done in-situ to reduce overhead cost.
Growth potential of G. sulphuraria in leached media was compared to a standard cyanidium media produced from inorganic chemicals. Initial inhibition studies were done in the leached media at 40 °C and 2-3 vol. % CO2 to observe a positive growth rate of 0.273 g L-1 day-1. Further, growth was compared to standard media with similar composition in a 96 well plate 50 μL microplate assay for 5 days. The growth rates in both media were comparable. Additionally, growth was confirmed in a 240 times larger tubular reactor in a Tissue Culture Roller drum apparatus. A better growth was observed in the leached cyanidium media as compared to the standard variant.
ContributorsMathew, Melvin (Author) / Deng, Shuguang (Thesis advisor) / Lammers, Peter J. (Committee member) / Nielsen, David R (Committee member) / Arizona State University (Publisher)
Created2017
Description
Plastic consumption has reached astronomical amounts. The issue is the single-use plastics that continue to harm the environment, degrading into microplastics that find their way into our environment. Finding sustainable, reliable, and safe methods to break down plastics is a complex but valuable endeavor. This research aims to assess the viability of using biochar as a catalyst to break down polyethylene terephthalate (PET) plastics under hydrothermal liquefaction conditions. PET is most commonly found in single-use plastic water bottles. Using glycolysis as the reaction, biochar is added and assessed based on yield and time duration of the reaction. This research suggests that temperatures of 300℃ and relatively short experimental times were enough to see the complete conversion of PET through glycolysis. Further research is necessary to determine the effectiveness of biochar as a catalyst and the potential of process industrialization to begin reducing plastic overflow.
ContributorsWyatt, Olivia (Author) / Deng, Shuguang (Thesis director) / Jin, Kailong (Committee member) / Barrett, The Honors College (Contributor) / Chemical Engineering Program (Contributor)
Created2023-05
Description
This study presents an evaluation of the predicted flow behavior and the minimum outlet diameter in a computationally simulated hopper. The flow pattern in hoppers was simulated to test three size fractions, three moisture levels of microcrystalline cellulose (MCC), and two hopper wall angles in Multiphase Flow with Interphase eXchanges (MFiX). Predictions from MFiX were then compared to current literature. As expected, the smaller size fractions with lower water content were closer to ideal funnel flow than their larger counterparts. The predicted minimum outlet diameter in simulations showed good agreement with close to ideal flowability. These findings illustrate the connection between lab flowability experiments and computational simulations. Lastly, three fluidized bed simulations were also created in MFiX with zeolite 13X to analyze the pressure and velocity within the bed. The application of flowability simulations can improve the transport of solids in processing equipment used during the production of powders.
ContributorsBuchanan, Lidija (Author) / Emady, Heather (Thesis advisor) / Muhich, Christopher (Committee member) / Deng, Shuguang (Committee member) / Arizona State University (Publisher)
Created2023
Description
Anthropogenic processes have increased the concentration of toxic Se, As and N in water. Oxo-anions of these species are poisonous to aquatic and terrestrial life. Current remediation techniques have low selectivity towards their removal. Understanding the chemistry and physics which control oxo-anion adsorption on metal oxide and the catalytic nitrate reduction to inform improved remediation technologies can be done using Density functional theory (DFT) calculations. The adsorption of selenate, selenite, and arsenate was investigated on the alumina and hematite to inform sorbent design strategies. Adsorption energies were calculated as a function of surface structure, composition, binding motif, and pH within a hybrid implicit-explicit solvation strategy. Correlations between surface property descriptors including water network structure, cationic species identity, and facet and the adsorption energies of the ions show that the surface water network controls the adsorption energy more than any other, including the cationic species of the metal-oxide. Additionally, to achieve selectivity for selenate over sulphate, differences in their electronic structure must be exploited, for example by the reduction of selenate to selenite by Ti3+ cations.
Thermochemical or electrochemical reduction pathways to convert NO3- to N2 or NH3, which are benign or value-added products, respectively are examined over single-atom electrocatalysts (SAC) in Cu. The activity and selectivity for nitrate reduction are compared with the competitive hydrogen evolution reaction (HER). Cu suppresses HER but produces toxic NO2- because of a high activation barrier for cleaving the second N-O bond. SACs provide secondary sites for reaction and break traditional linear scaling relationships. Ru-SACs selectively produce NH3 because N-O bond scission is facile, and the resulting N remains isolated on SAC sites; reacting with H+ from solvating H2O to form ammonia. Conversely, Pd-SAC forms N2 because the reduced N* atoms migrate to the Cu surface, which has a low H availability, allowing N atoms to combine to N2. This relation between N* binding preference and reduction product is demonstrated across an array of SAC elements.
Hence, the solvation effects on the surface critically alter the activity of adsorption and catalysis and the removal of toxic pollutants can be improved by altering the surface water network.
ContributorsGupta, Srishti (Author) / Muhich, Christopher L (Thesis advisor) / Singh, Arunima (Committee member) / Emady, Heather (Committee member) / Westerhoff, Paul (Committee member) / Deng, Shuguang (Committee member) / Arizona State University (Publisher)
Created2023
Description
Adsorption is fundamentally known to be a non-isothermal process; in which temperature increase is largely significant, causing fairly appreciable impacts on the processkinetics. For porous adsorbent particles like metal organic frameworks (MOFs), silica
gel, and zeolite, the resultant relative heat generated is partly distributed within the
particle, and the rest is transferred to the surrounding ambient fluid (air).
For large step changes in adsorbed phase concentration and fast adsorption rates,
especially, the isothermality of adsorption (as in some studies) is an inadequate assumption and inspires rather erroneous diffusivities of porous adsorbents. Isothermal models, in consequence, are insufficient for studying adsorption in porous adsorbents. Non-isothermal models can satisfactorily and exhaustively describe adsorption
in porous adsorbents. However, in many of the analyses done using the models, the
thermal conductivity of the adsorbent is assumed to be infinite; thus, particle temperature is taken to be fairly uniform during the process—a trend not observed for
carbon dioxide (CO2) adsorption on MOFs.
A new and detailed analysis of CO2 adsorption in a single microporous MOF-5
particle, assuming a finite effective thermal conductivity along with comprehensive
parametric studies for the models, is presented herein. A significant average temperature increase of 5K was calculated using the new model, compared to the 0.7K
obtained using the Stremming model. A corresponding increase in diffusivity from
8.17 x 10-13 to 1.72 x 10-11 m2/s was observed, indicating the limitations of both
isothermal models and models that assume constant diffusivity.
ContributorsNkuutu, John (Author) / Lin, Jerry (Thesis advisor) / Emady, Heather (Committee member) / Deng, Shuguang (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
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
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