ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- All Subjects: chemical engineering
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
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
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
Zwitterionic polymers, due to their supurior capability of electrostatically induced hydration, have been considered as effective functionalities to alleviate bio-fouling of reverse osmosis (RO) membranes. Bulk modification of polysulfone-based matrices to improve hydrophilicity, on the other hand, is favored due to the high membrane performance, processibility, and intrinsic chlorine resistance. Here a novel synthetic method was demonstrated to prepare zwitterionic poly(arylene ether sulfone) (PAES) copolymers, which was blended with native polysulfone (PSf) to fabricate free-standing asymmetric membranes via non-solvent induced phase separation process. Both the porosity of the support layer and surface hydrophilicity increased drastically due to the incorporation of zwitterion functionalities in the rigid polysulfone matrix. The water permeance and antifouling ability of the blend membranes were both remarkably improved to 2.5 Lm−2 h−1 bar−1 and 94% of flux recovery ratio, respectively, while salt rejection remained at a high level (98%) even under the high exposure to chlorine (8,000 ppm•h). Besides the preliminary blended membrane design, for the future membrane property enhancement, this dissertation also focused on polymer structure optimizations via elucidating the fundamentals from two perspectives: 1). Synthetic reaction kinetics and mechanisms on polycondensation of PAES. Interestingly, in combination of experiments and the computational calculations by density functional theory (DFT) methods in this work, only the aryl chlorides (ArCl) monomer follows the classical second-order reaction kinetics of aromatic nucleophilic substitution (SNAr) mechanism, while the kinetics of the aryl fluorides (ArF) reaction fit a third-order rate law. The third order reaction behavior of the ArF monomer is attributed to the activation of the carbon-fluorine bond by two potassium cations (at least one bounded to phenolate), which associate as a strong three-body complex. This complex acts as the predominant reactant during the attack by the nucleophile. 2). Optimized copolymer structures were developed for controlled high molecular weight (Mw ~ 65 kDa) and zwitterionic charge content (0~100 mol%), via off-set stoichiometry during polycondensations, following with thiol-ene click reaction and ring-opening of sultone to introduce the sulfobetaine functional groups. The structure-property-morphology relationships were elucidated for better understanding atomic-level features in the charged polymers for future high-performance desalination applications.
ContributorsYang, Yi, Ph.D (Author) / Green, Matthew D (Thesis advisor) / Lin, Jerry Y.S. (Committee member) / Lind, Marylaura (Committee member) / Perreault, Francois (Committee member) / Deng, Shuguang (Committee member) / Arizona State University (Publisher)
Created2019
Description
This thesis investigated the effects of differing diameters and varying moisture content on the flowability properties of granular glass beads through use of a Freeman FT4 Powder Rheometer. These parameters were tested in order to construct an empirical model to predict flowability properties of glass beads at differing size ranges and moisture contents. The final empirical model outputted an average error of 8.73% across all tested diameters and moisture ranges.
Mohr's circles were constructed from experimentally-obtained shear stress values to quantitatively describe flowability of tested materials in terms of a flow function parameter. A high flow function value (>10) was indicative of a good flow.
By testing 120-180 µm, 120-350 µm, 180-250 µm, 250-350 µm, 430-600 µm, and 600-850 µm glass bead diameter ranges, an increase in size was seen to result in higher flow function values. The limitations of testing using the FT4 became apparent as inconsistent flow function values were obtained at 0% moisture with size ranges above 120-180 µm, or at flow function values of >21. Bead sizes larger than 430 µm showed significant standard deviation over all tested trials--when excluding size ranges above that value, the empirical model showed an average error of only 6.45%.
Wet material testing occurred at all tested glass bead size ranges using a deionized water content of 0%, 1%, 5%, 15%, and 20% by weight. The results of such testing showed a decrease in the resulting flow function parameter as more water content was added. However, this trend changed as 20% moisture content was achieved; the wet material became supersaturated, and an increase in flow function values was observed. The empirical model constructed, therefore, neglected the 20% moisture content regime.
Mohr's circles were constructed from experimentally-obtained shear stress values to quantitatively describe flowability of tested materials in terms of a flow function parameter. A high flow function value (>10) was indicative of a good flow.
By testing 120-180 µm, 120-350 µm, 180-250 µm, 250-350 µm, 430-600 µm, and 600-850 µm glass bead diameter ranges, an increase in size was seen to result in higher flow function values. The limitations of testing using the FT4 became apparent as inconsistent flow function values were obtained at 0% moisture with size ranges above 120-180 µm, or at flow function values of >21. Bead sizes larger than 430 µm showed significant standard deviation over all tested trials--when excluding size ranges above that value, the empirical model showed an average error of only 6.45%.
Wet material testing occurred at all tested glass bead size ranges using a deionized water content of 0%, 1%, 5%, 15%, and 20% by weight. The results of such testing showed a decrease in the resulting flow function parameter as more water content was added. However, this trend changed as 20% moisture content was achieved; the wet material became supersaturated, and an increase in flow function values was observed. The empirical model constructed, therefore, neglected the 20% moisture content regime.
ContributorsKleppe, Cameron (Author) / Emady, Heather (Thesis advisor) / Marvi, Hamidreza (Committee member) / Deng, Shuguang (Committee member) / Arizona State University (Publisher)
Created2019
Description
Mixed-ionic electronic conducting (MIEC) oxides have drawn much attention from researchers because of their potential in high temperature separation processes. Among many materials available, perovskite type and fluorite type oxides are the most studied for their excellent oxygen ion transport property. These oxides not only can be oxygen adsorbent or O2-permeable membranes themselves, but also can be incorporated with molten carbonate to form dual-phase membranes for CO2 separation.
Oxygen sorption/desorption properties of perovskite oxides with and without oxygen vacancy were investigated first by thermogravimetric analysis (TGA) and fixed-bed experiments. The oxide with unique disorder-order phase transition during desorption exhibited an enhanced oxygen desorption rate during the TGA measurement but not in fixed-bed demonstrations. The difference in oxygen desorption rate is due to much higher oxygen partial pressure surrounding the sorbent during the fixed-bed oxygen desorption process, as revealed by X-ray diffraction (XRD) patterns of rapidly quenched samples.
Research on using perovskite oxides as CO2-permeable dual-phase membranes was subsequently conducted. Two CO2-resistant MIEC perovskite ceramics, Pr0.6Sr0.4Co0.2Fe0.8 O3-δ (PSCF) and SrFe0.9Ta0.1O3-δ (SFT) were chosen as support materials for membrane synthesis. PSCF-molten carbonate (MC) and SFT-MC membranes were prepared for CO2-O2 counter-permeation. The geometric factors for the carbonate phase and ceramic phase were used to calculate the effective carbonate and oxygen ionic conductivity in the carbonate and ceramic phase. When tested in CO2-O2 counter-permeation set-up, CO2 flux showed negligible change, but O2 flux decreased by 10-32% compared with single-component permeation. With CO2 counter-permeation, the total oxygen permeation flux is higher than that without counter-permeation.
A new concept of CO2-permselective membrane reactor for hydrogen production via steam reforming of methane (SRM) was demonstrated. The results of SRM in the membrane reactor confirm that in-situ CO2 removal effectively promotes water-gas shift conversion and thus enhances hydrogen yield. A modeling study was also conducted to assess the performance of the membrane reactor in high-pressure feed/vacuum sweep conditions, which were not carried out due to limitations in current membrane testing set-up. When 5 atm feed pressure and 10-3 atm sweep pressure were applied, the membrane reactor can produce over 99% hydrogen stream in simulation.
Oxygen sorption/desorption properties of perovskite oxides with and without oxygen vacancy were investigated first by thermogravimetric analysis (TGA) and fixed-bed experiments. The oxide with unique disorder-order phase transition during desorption exhibited an enhanced oxygen desorption rate during the TGA measurement but not in fixed-bed demonstrations. The difference in oxygen desorption rate is due to much higher oxygen partial pressure surrounding the sorbent during the fixed-bed oxygen desorption process, as revealed by X-ray diffraction (XRD) patterns of rapidly quenched samples.
Research on using perovskite oxides as CO2-permeable dual-phase membranes was subsequently conducted. Two CO2-resistant MIEC perovskite ceramics, Pr0.6Sr0.4Co0.2Fe0.8 O3-δ (PSCF) and SrFe0.9Ta0.1O3-δ (SFT) were chosen as support materials for membrane synthesis. PSCF-molten carbonate (MC) and SFT-MC membranes were prepared for CO2-O2 counter-permeation. The geometric factors for the carbonate phase and ceramic phase were used to calculate the effective carbonate and oxygen ionic conductivity in the carbonate and ceramic phase. When tested in CO2-O2 counter-permeation set-up, CO2 flux showed negligible change, but O2 flux decreased by 10-32% compared with single-component permeation. With CO2 counter-permeation, the total oxygen permeation flux is higher than that without counter-permeation.
A new concept of CO2-permselective membrane reactor for hydrogen production via steam reforming of methane (SRM) was demonstrated. The results of SRM in the membrane reactor confirm that in-situ CO2 removal effectively promotes water-gas shift conversion and thus enhances hydrogen yield. A modeling study was also conducted to assess the performance of the membrane reactor in high-pressure feed/vacuum sweep conditions, which were not carried out due to limitations in current membrane testing set-up. When 5 atm feed pressure and 10-3 atm sweep pressure were applied, the membrane reactor can produce over 99% hydrogen stream in simulation.
ContributorsWu, Han-Chun (Author) / Lin, Jerry Y.S. (Thesis advisor) / Deng, Shuguang (Committee member) / Jiao, Yang (Committee member) / Emady, Heather (Committee member) / Muhich, Christopherq (Committee member) / Arizona State University (Publisher)
Created2020
Description
Lithium-ion and lithium-metal batteries are deemed to be the choice of energy storage media for the future. However, they are not entirely safe and their performance in terms of cycle life and charging rates is sub-optimal. A majority of these issues arise from the currently used flammable polyolefinic separators and carbonate solvent based electrolytes. This work utilizes in-house developed and specific property tuned electrode-coated inorganic separators in combination with a fire-proof electrolyte to resolve the above stated concerns.Firstly, to improve the safety of the lithium-ion cell with a commercial polypropylene separator a thermally stable in-house developed electrode coated quartz silica separator is utilized. The silica separator due to its better electrolyte wettability, electrolyte uptake and lower resistance also offers better capacity retention (~ 15 %) at high rates of discharge. Subsequently, research on developing a completely safe lithium-ion battery was conducted by replacing the traditional carbonate solvent based electrolyte with a fire-proof lithium bis-fluoro sulphonyl-imide salt/tri-methyl phosphate solvent electrolyte. However, this electrolyte has a high viscosity and low separator wetting rate.
A microporous in house synthesized silicalite electrode-coated separator due to its high surface energy functionalizes the viscous fire-proof electrolyte and together they are tested in a full-cell. The intra-particle pores of the silicalite separator result in a thinner and more robust solid electrolyte interface on graphite. This results in about 20 % higher capacity retention during long term cycling when compared to the polypropylene separator used in the same full-cell.
To enable stable and fast charging lithium-metal batteries free from dendrite propagation related failure, plate shaped γ-alumina and silicalite electrode-coated separators with high tortuosity are developed and used in a lithium-metal full-cell battery, with the former separator having no intra-particle pores and the latter having them. The γ-alumina separators show improvements in dendrite propagation prevention up to 3 C-rate of charge/discharge but a loss in active lithium is seen beyond the 75th cycle. However, microporous plate-shaped silicalite separators did not show any loss in active lithium even at 3 C-rate for 100 cycles due to the homogenized lithium-ion flux at the anode, while also preventing dendrite propagation.
ContributorsRafiz, Kishen (Author) / Lin, Jerry Y.S (Thesis advisor) / Muhich, Christopher (Committee member) / Kannan, Arunachala (Committee member) / Deng, Shuguang (Committee member) / Green, Matthew (Committee member) / Arizona State University (Publisher)
Created2021
Description
Cyclical chemical looping involves the thermal reduction of metal oxide to release O2 at high temperatures, followed by its oxidation using O-containing molecules like O2, H2O, or CO2. This process is a promising method for solar thermochemical water splitting (STCH), oxygen separation, and thermochemical energy storage (TCES). The efficiency and economic viability of this process hinge on the thermodynamics of metal oxide reduction. This dissertation presents innovative methods to enhance the performance of these processes, with a specific focus on STCH and TCES by advancing thermodynamic characterization and screening of potential metal oxides, thereby reducing H2 costs.A novel CALPHAD approach, the CrossFit Compound Energy Formalism (CEF), integrates theoretical (density functional theory) and experimental (thermogravimetric) data to develop thermodynamic models for desired materials. The CrossFit-CEF was applied to BaxSr1-xFeO3-δ identifying matching thermodynamics and off-stoichiometric values to literature (~100-180 kJ/mol O2 reduction enthalpies across the BaxSr1-xFeO3-δ compositional range). Comparisons with the traditional van ‘t Hoff thermodynamic extraction technique reveal that the CrossFit-CEF method significantly outperforms conventional methods. For instance, the CEF method was employed to extract thermodynamic data for CaFexMn1-xO3-δ and identify optimal TCES CaFexMn1-xO3-δ compositions. The CrossFit-CEF method found the same thermodynamic trends on less than half the data utilized in a van ‘t Hoff approach and determined that the optimal CaFexMn1-xO3-δ composition had the minimal Fe concentration synthesized (x=0.625), achieving ~60 kJ/mol TCES.
Bayesian Inference was employed was employed to expedite data collection. When combined with the CrossFit-CEF method, Bayesian Inference assesses the likelihood that the current model accurately describes the data, providing confidence intervals for the model. This approach reduces the amount of data needed for accurate thermodynamic modeling by 50%.
Finally, the CrossFit-CEF and Bayesian methods are integrated into a system-level STCH model to optimize and accelerate materials design for specific plant operating conditions. Overall, this dissertation introduces methods that yield more accurate thermodynamic models with reduced data requirements. The time saved in data collection enables screening of more materials, expediting material identification and optimization. The materials identified through these techniques are expected to enhance chemical looping cycles, leading to increased H2 production efficiency and reduced costs.
ContributorsWilson, Steven A (Author) / Muhich, Christopher L (Thesis advisor) / Rivera, Daniel E (Committee member) / Stechel, Ellen B (Committee member) / Lin, Jerry (Committee member) / Deng, Shuguang (Committee member) / Arizona State University (Publisher)
Created2024