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Articles 1111 - 1140 of 33676
Full-Text Articles in Entire DC Network
Extended S-Parameter Model Of The Power Distribution Network For Rapid Coupling Predictions, Cody Goins, Aaron Harmon, Mckennan Starkey, Kristen Donnell, Victor Khilkevich, Daryl Beetner
Extended S-Parameter Model Of The Power Distribution Network For Rapid Coupling Predictions, Cody Goins, Aaron Harmon, Mckennan Starkey, Kristen Donnell, Victor Khilkevich, Daryl Beetner
Electrical and Computer Engineering Faculty Research & Creative Works
Power and return planes are part of the power delivery network of almost all modern high frequency printed circuit boards. These power and return planes can form the basis of unintended radiated emissions from, or radiated coupling to, these boards. Predicting coupling to complex systems is a difficult problem and typically reserved for full wave simulations. Recent works have introduced segmentation approaches that are able to predict coupling to complex printed circuit board designs by using pre-rendered segments and cascading these segments through a circuit solver approach. The extended S-parameter models used by the segmentation approach currently do not include …
Radiated Susceptibility Testing Using Near-Field Scanning, Mckennan Starkey, Aaron Harmon, Cody Goins, Kristen Donnell, Victor Khilkevich, Daryl Beetner
Radiated Susceptibility Testing Using Near-Field Scanning, Mckennan Starkey, Aaron Harmon, Cody Goins, Kristen Donnell, Victor Khilkevich, Daryl Beetner
Electrical and Computer Engineering Faculty Research & Creative Works
Determining locations and components in a system responsible for radiated coupling is challenging. Methods, such as near field injection susceptibility scanning or direct power injection, can only find locations and frequencies where a component is sensitive to the near field or to an injected signal but cannot deduce if the component is well coupled to the far-field. In this paper, a method to experimentally determine the levels of radiated coupling within a target system is proposed. A near-field differential loop probe is scanned over the target device while measuring the radiated energy in a stirred-mode tent. By sweeping the near …
Graph-Based Reinforcement Learning Approach For Multi-Power-Domain Pcb Pdn Shape And Stackup Synthesis, Haran Manoharan, Hanfeng Wang, Jingnan Pan, Yuchu He, Jianmin Zhang, Xu Gao, Chulsoon Hwang
Graph-Based Reinforcement Learning Approach For Multi-Power-Domain Pcb Pdn Shape And Stackup Synthesis, Haran Manoharan, Hanfeng Wang, Jingnan Pan, Yuchu He, Jianmin Zhang, Xu Gao, Chulsoon Hwang
Electrical and Computer Engineering Faculty Research & Creative Works
Efficient power plane and stack up optimization is critical for Printed Circuit Board (PCB) Power Delivery Networks (PDNs), particularly in multi-power-domain designs with stringent DC Resistance (DCR) specifications. This work presents a novel reinforcement learning-based framework that assigns stack up layers for each power domain and iteratively refines power plane shapes to meet design constraints while ensuring non-overlapping layouts. The approach leverages Minimum Spanning Trees (MSTs) for initializing power plane shapes. It dynamically refines them using the A∗ (A-Star) algorithm with weighted pathfinding, ensuring optimal connectivity and compliance with DCR requirements. Tested extensively on multi-power-domain scenarios, the algorithm demonstrates robust …
Optimized Modeling Of Pcb Vias With Nonfunctional Pads And High-Frequency Behavior Up To 150 Ghz, Mehdi Mousavi, Kevin Cai, Chaofeng Li, Sathvika Bandi, Manish Mathew, Mehdi Khaleghi, Shameem Ahmed, Donghyun Kim
Optimized Modeling Of Pcb Vias With Nonfunctional Pads And High-Frequency Behavior Up To 150 Ghz, Mehdi Mousavi, Kevin Cai, Chaofeng Li, Sathvika Bandi, Manish Mathew, Mehdi Khaleghi, Shameem Ahmed, Donghyun Kim
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents an enhanced closed-form approach for modeling and optimizing high-frequency PCB vias, implemented in Python and validated against industry standard tools such as ADS and HFSS. The model incorporates resistance alongside inductance and capacitance to capture frequency-dependent losses and integrates non-functional pads (NFPs), demonstrating significant improvements in signal integrity by reducing reflections and enhancing return loss, particularly at 100 GHz. The methodology extends the frequency range of previous models from 100 GHz to 150 GHz, ensuring compatibility with next-generation standards like PCIe Gen 6. Validation results show insertion loss deviations under 3 dB and consistent return loss across …
Ai-Driven Traffic Scene Understanding Using Static Lidar Sensors, Elham Binshaflout, Chaima Zaghouani, Charalampos Antoniadis, Hakim Ghazzai, Nawfal Guefrachi, Ahmad Alsharoa, Sameh Najeh, Gianluca Setti
Ai-Driven Traffic Scene Understanding Using Static Lidar Sensors, Elham Binshaflout, Chaima Zaghouani, Charalampos Antoniadis, Hakim Ghazzai, Nawfal Guefrachi, Ahmad Alsharoa, Sameh Najeh, Gianluca Setti
Electrical and Computer Engineering Faculty Research & Creative Works
Traffic congestion and road safety remain critical challenges in urban environments, driving the need for more effective traffic monitoring solutions. While recent advancements in computer vision have enhanced traffic perception, the dynamic viewpoint of autonomous vehicles is often insufficient for comprehensive traffic management. To address this gap, we propose an AI-driven framework for enhanced traffic scene understanding using static LiDAR sensors at road intersections. The system collects 3D point clouds from roadside static LiDAR sensors, providing a complete view of vehicles and pedestrians. We integrate state-of-the-art 3D object detection (i.e., PV-RCNN) and instance segmentation models (i.e., PointGroup3heads) to accurately identify …
Efficient Decoupling Capacitor Impact Calculation, Faye Squires, Yifan Ding, Matthew Doyle, Matteo Cocchini, Samuel Connor, Francesco De Paulis, Albert E. Ruehli, Chulsoon Hwang, Lijun Jiang
Efficient Decoupling Capacitor Impact Calculation, Faye Squires, Yifan Ding, Matthew Doyle, Matteo Cocchini, Samuel Connor, Francesco De Paulis, Albert E. Ruehli, Chulsoon Hwang, Lijun Jiang
Electrical and Computer Engineering Faculty Research & Creative Works
Methods of optimizing decoupling capacitor placement on power distribution networks (PDNs) are often limited due to the computational complexity required to calculate the impact of connecting loads to an impedance matrix with hundreds of rows and columns. This work proposes that by removing all but one member of the impedance matrix before calculating, checking the impact of adding capacitors to the matrix can be done efficiently, and optimization methods can be viable even when requiring millions of impedance calculations.
Design Strategies For Skew Compensation In Highspeed Pcb Strip Line Interconnects, Sathvika Bandi, Reza Asadi, Zhekun Peng, Srinivas Venkataraman, Granthana Rangaswamy, Santosh Pappu, Xu Wang, Donghyun Kim
Design Strategies For Skew Compensation In Highspeed Pcb Strip Line Interconnects, Sathvika Bandi, Reza Asadi, Zhekun Peng, Srinivas Venkataraman, Granthana Rangaswamy, Santosh Pappu, Xu Wang, Donghyun Kim
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents a comprehensive analysis of the impact of intra-pair PN skew compensation in printed circuit board (PCB) strip line (SL) traces, for a high-speed 224 Gbps lane for the first time. The study investigates the effects of skew compensation placement both with and without via discontinuities. Detailed evaluations are performed in both time and frequency domains, examining critical parameters such as time-domain reflectometry (TDR), input impedance, return loss, insertion loss, and common-mode S -parameters. The findings reveal that, in a simple strip line trace without via discontinuities, the location of skew compensation has negligible influence on signal margins. …
Enhanced Continual Reinforcement Learning-Based Output Feedback Control Of Heterogeneous Quadrotors Formation, Ehsan Soleimani, S. Jagannathan
Enhanced Continual Reinforcement Learning-Based Output Feedback Control Of Heterogeneous Quadrotors Formation, Ehsan Soleimani, S. Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents a unified framework for the safe and optimal control of heterogeneous quadrotor unmanned aerial vehicles (QUAVs) in formation, enabling multitask missions without requiring precise system dynamics. To address partial state observability, a multilayer neural network (MNN) observer is designed to estimate unmeasured states. Reinforcement learning (RL) is employed for optimal control utilizing an MNN ensuring adaptability. Barrier Lyapunov Functions (BLFs) are integrated into the RL framework to enforce safety by maintaining QUAVs within predefined constraints. An enhanced continual learning (ECL) method is proposed to improve the adaptability of MNNs. This method enables effective multitask learning while mitigating …
Modeling Of Slot-Backed Microstrip Line For Emi Applications, Jongsuk Hyun, Wenchang Huang, Chulsoon Hwang
Modeling Of Slot-Backed Microstrip Line For Emi Applications, Jongsuk Hyun, Wenchang Huang, Chulsoon Hwang
Electrical and Computer Engineering Faculty Research & Creative Works
Radiated emissions from the noise-generating components in modern electronic devices are a significant concern for both electromagnetic interference and RF interference. Shielding cans are commonly used to suppress emissions from noise sources, but accurate shielding effectiveness evaluation requires a clean, well-defined radiation source that can reliably mimic real emissions for repeatable measurements. Slot-backed microstrip antennas provide a practical alternative to loop antennas, offering zero height, low parasitic radiation, and seamless printed circuit board integration. This article proposes an analytical model for estimating the magnetic dipole moment of slot-backed microstrip structures. The model captures both the discontinuity effects and radiated characteristics …
Centralized And Federated Heart Disease Classification Using Uci Dataset: A Benchmark With Interpretability Analysis, Mario Padilla Rodriguez, Eyiara Oladipo, Mohamed Nafea
Centralized And Federated Heart Disease Classification Using Uci Dataset: A Benchmark With Interpretability Analysis, Mario Padilla Rodriguez, Eyiara Oladipo, Mohamed Nafea
Electrical and Computer Engineering Faculty Research & Creative Works
Cardiovascular disease (CVD) is a leading cause of global mortality, highlighting the need for accurate diagnostic methods. This study benchmarks centralized and federated learning (FL) algorithms for heart disease binary classification using the UCI dataset, which includes 920 patient records from four hospitals in the USA, Hungary, and Switzerland. Our benchmark is supported by Shapley-value as well as Local Interpretable Model-agnostic Explanations (LIME) interpretability analyses to quantify feature importance for classification. In the centralized setup, various classification algorithms are trained on pooled data, with the Naive Bayes classifier achieving the highest test accuracy of 81.1%. Further, FL algorithms with four …
Benchmarking Deep Learning Architectures For Ecg-Based Multi-Label Heart Disease Prediction Using Mimic-Iv Database, Eyiara Oladipo, Sarwar Nazrul, Mohamed Nafea
Benchmarking Deep Learning Architectures For Ecg-Based Multi-Label Heart Disease Prediction Using Mimic-Iv Database, Eyiara Oladipo, Sarwar Nazrul, Mohamed Nafea
Electrical and Computer Engineering Faculty Research & Creative Works
Cardiovascular disease (CVD) is a leading cause of global mortality, accounting for an estimated 17.9 million deaths annually. CVD is broadly defined as a group of medical conditions influenced by modifiable or non-modifiable risk factors that affect the heart's ability to function properly. Machine learning (ML) has emerged as a powerful tool for analyzing complex medical data, aiding in early detection and accurate diagnosis of CVD and improving patient outcomes. Recent studies proposed various deep learning (DL) architectures for detecting CVD, yet there is a lack of robust benchmarks for comparing their performance on large-scale databases. In this work, we …
Corona Discharge To Touchscreen Modeling Using Nonlinear Time-Dependent Corona Streamer Propagation Model In Spice, Zhekun Peng, Daniel Szanto, Jianchi Zhou, Darryl Kostka, David Pommerenke, Daryl G. Beetner
Corona Discharge To Touchscreen Modeling Using Nonlinear Time-Dependent Corona Streamer Propagation Model In Spice, Zhekun Peng, Daniel Szanto, Jianchi Zhou, Darryl Kostka, David Pommerenke, Daryl G. Beetner
Electrical and Computer Engineering Faculty Research & Creative Works
SPICE-based methods for predicting coupling from an ESD-induced corona streamer to printed-circuit board (PCB) structures beneath a touchscreen display are evaluated in this paper. Results demonstrate that the non-linear time-dependent propagation model can capture the coupling much better than other models and accurately predict the overall current waveform.
Ms-Yolo: Infrared Object Detection For Edge Deployment Via Mobilenetv4 And Slideloss, Jiali Zhang, Thomas S. White, Haoliang Zhang, Wenqing Hu, Donald C. Wunsch, Jian Liu
Ms-Yolo: Infrared Object Detection For Edge Deployment Via Mobilenetv4 And Slideloss, Jiali Zhang, Thomas S. White, Haoliang Zhang, Wenqing Hu, Donald C. Wunsch, Jian Liu
Mathematics and Statistics Faculty Research & Creative Works
Infrared imaging has emerged as a robust solution for urban object detection under low-light and adverse weather conditions, offering significant advantages over traditional visible-light cameras. However, challenges such as class imbalance, thermal noise, and computational constraints can significantly hinder model performance in practical settings. To address these issues, we evaluate multiple YOLO variants on the FLIR ADAS V2 dataset, ultimately selecting YOLOv8 as our baseline due to its balanced accuracy and efficiency. Building on this foundation, we present MS-YOLO (MobileNetv4 and SlideLoss based on YOLO), which replaces YOLOv8's CSPDarknet backbone with the more efficient MobileNetV4, reducing computational overhead by 1.5% …
Keep Family Business Innovating: Revisit The Relationship Between Succession And Innovation From Ownership Succession, Yuan Chen, Weize Huang, Chevy-Hanqing Fang, Ling Chen
Keep Family Business Innovating: Revisit The Relationship Between Succession And Innovation From Ownership Succession, Yuan Chen, Weize Huang, Chevy-Hanqing Fang, Ling Chen
Business and Information Technology Faculty Research & Creative Works
This study examines how family owner-manager successors' ownership influences R&D investment in family businesses. Drawing on the socioemotional wealth (SEW) perspective, we theorize that successors with higher family ownership prioritize extended SEW, leading to stronger R&D investment, while those with lower family ownership prioritize restricted SEW, resulting in weaker R&D investment. Additionally, we explore how family dynamics—specifically, the number of family directors and asymmetric salary favoring family members—moderate this relationship. Our findings enhance the understanding of successor heterogeneity and its impact on innovation, offering insights for succession planning that support the long-term sustainability of family businesses.
Graphite Particles Modified By Zno Atomic Layer Deposition For Li-Ion Battery Anodes, Ahmad Helaley, Han Yu, Xinhua Liang
Graphite Particles Modified By Zno Atomic Layer Deposition For Li-Ion Battery Anodes, Ahmad Helaley, Han Yu, Xinhua Liang
Chemical and Biochemical Engineering Faculty Research & Creative Works
Graphite, with a modest specific capacity of 372 mA h g−1, is a stable material for lithium-ion battery anodes. However, its capacity is inadequate to meet the growing power demands because the formation of an irregular solid electrolyte interphase (SEI) can result in unstable performance. In this research, we used a few cycles of atomic layer deposition (ALD) to deposit ZnO on graphite particles as an anode with improved electrochemical stability. Transmission electron microscopy revealed that ZnO was in the form of nanoparticles due to the inert surface properties of graphite and only a few cycles of ALD. Electrochemical characterization …
Emulsion Liquid Membrane (Elm) Technique For Efficient Separation Of Heavy Metals From Acidic Solutions Including Phosphoric Acid: A Review, O. Karai, N. Y. Selem, K. Benabderazak, J. Mendil, H. Mazouz, M. H. Al-Dahhan
Emulsion Liquid Membrane (Elm) Technique For Efficient Separation Of Heavy Metals From Acidic Solutions Including Phosphoric Acid: A Review, O. Karai, N. Y. Selem, K. Benabderazak, J. Mendil, H. Mazouz, M. H. Al-Dahhan
Chemical and Biochemical Engineering Faculty Research & Creative Works
Heavy metal ions in aqueous and acidic solutions pose serious threats to ecosystems. Their effective removal is crucial, and emulsion liquid membrane (ELM) technology offers a promising solution. This review delves into ELM's principles, mechanisms, components, and performance indicators including stability for extracting heavy metals from acidic solutions including phosphoric acid., ELM's stability issues, such as internal phase coalescence, membrane leakage, and swelling, limit its efficiency. Thus, this review paper discusses previous research that analyzed ELM stability and heavy metal extraction efficiency from these acidic solutions. Furthermore, it assesses other techniques like Emulsion Ionic Liquid Membrane (EILM) and Pickering Emulsion …
Enhanced Cholesterol Efflux And Atherosclerosis Regression Via Ceh Gene Delivery Using Galactose-Functionalized Dendrimeric Nanoparticles, Huari Kou, Jing Wang, Paul J. Yannie, Da Huang, William J. Korzun, Genta Kakiyama, Siddhartha S. Ghosh, Hu Yang
Enhanced Cholesterol Efflux And Atherosclerosis Regression Via Ceh Gene Delivery Using Galactose-Functionalized Dendrimeric Nanoparticles, Huari Kou, Jing Wang, Paul J. Yannie, Da Huang, William J. Korzun, Genta Kakiyama, Siddhartha S. Ghosh, Hu Yang
Chemical and Biochemical Engineering Faculty Research & Creative Works
Cholesteryl ester hydrolase (CEH) is a critical enzyme in cholesterol ester hydrolysis, influencing cholesterol metabolism and efflux. This study demonstrates that CEH overexpression promotes free cholesterol efflux from macrophages, thereby reducing the lipid burden in existing atherosclerotic plaques. To enable targeted delivery, galactose-functionalized polyamidoamine (PAMAM) dendrimeric nanoparticles were utilized as nanocarriers for hepatic delivery of the CEH expression vector. The therapeutic potential of CEH plasmid-loaded dendrimeric nanoparticles was evaluated in Ldlr-/- mice. Results showed a significant reduction in total lesion area (21%) and aortic arch lesion area (23%) compared to baseline. Lesion component analysis revealed marked decreases in total cholesterol …
Characterizing Heat Transfer Performance In A Slurry Bubble Column Reactor Equipped With A Real Heat Exchanger, Dalia S. Makki, Hasan Sh Majdi, Amer A. Abdulrahman, Abbas J. Sultan, Bashar J. Kadhim, Muthanna H. Al-Dahhan
Characterizing Heat Transfer Performance In A Slurry Bubble Column Reactor Equipped With A Real Heat Exchanger, Dalia S. Makki, Hasan Sh Majdi, Amer A. Abdulrahman, Abbas J. Sultan, Bashar J. Kadhim, Muthanna H. Al-Dahhan
Chemical and Biochemical Engineering Faculty Research & Creative Works
Abstract: This study examines the impact of equipping a real heat exchanger in a slurry bubble column SBC on instantaneous and local heat transfer coefficients IHTC and LHTC, as well as the overall heat transfer coefficient U, employing advanced heat transfer techniques. The experiments were conducted in a 0.15 m inner diameter Plexiglas SBC with varying gas flowrates Ug (0.14–0.35) m/s at several radial sites along the column's diameter (±0.18, ±0.46, and ± 0.74) and three axial locations (H/D = 2, 3 and 4). To simulate the industrial Fischer–Tropsch bubble column reactor FT-BCR, a real heat exchanger consisting of 18 …
A New Deep Decoder Type Cascaded Feedforward Neural Network For Critical Heat Flux Prediction In Power Reactors, Rehan Zubair Khalid, Atta Ullah, Asifullah Khan, Mansoor Hameed Inayat, Muthanna H. Al-Dahhan
A New Deep Decoder Type Cascaded Feedforward Neural Network For Critical Heat Flux Prediction In Power Reactors, Rehan Zubair Khalid, Atta Ullah, Asifullah Khan, Mansoor Hameed Inayat, Muthanna H. Al-Dahhan
Chemical and Biochemical Engineering Faculty Research & Creative Works
Critical Heat Flux (CHF) is a fundamental parameter for ensuring the performance, reliability, safety, and economic viability of water-cooled nuclear reactors. Despite its significance, the absence of a deterministic theory for CHF prediction poses a substantial challenge in thermal engineering. Consequently, various experimental and numerical models have been developed, yet no universally accepted model comprehensively addresses the wide range of flow conditions encountered in practical applications. The accurate prediction of CHF remains a complex and critical task. This work introduces a novel Deep Decoder Type Cascaded feedforward Neural Network (DD-CFNN) to predict CHF across a broad spectrum of operating conditions. …
Experimental Investigation Of Heat Transfer Behavior In Spouted Bed Reactors Under Different Operating Conditions, Hasan A. Abdulwahab, Abbas J. Sultan, Amer A. Abdulrahman, Hasan Sh Majdi, Haydar A.S. Aljaafari, Zahraa W. Hasan, Laith S. Sabri, Bashar J. Kadhim, Jamal M. Ali, Muthanna H. Al-Dahhan
Experimental Investigation Of Heat Transfer Behavior In Spouted Bed Reactors Under Different Operating Conditions, Hasan A. Abdulwahab, Abbas J. Sultan, Amer A. Abdulrahman, Hasan Sh Majdi, Haydar A.S. Aljaafari, Zahraa W. Hasan, Laith S. Sabri, Bashar J. Kadhim, Jamal M. Ali, Muthanna H. Al-Dahhan
Chemical and Biochemical Engineering Faculty Research & Creative Works
Abstract: Spouted bed reactors (SBRs) are highly valued for their effectiveness in chemical and biochemical processes due to their mixing and heat transfer capabilities. Understanding the heat transfer mechanisms in these reactors is necessary. This research delves into the heat transfer behavior of SBRs, which plays a role in enhancing their performance under operational conditions. The study conducted experiments to measure the heat transfer coefficient (HTC) at varying gas velocities (ranging from 0.32 to 0.74 m/s) at radial positions (r/R = 0, ±0.28, ±0.56, and ±0.85) and axial levels (H/D = 0.8, 2.1, and 3.5) within the spouted bed (SB) …
Tumor Microenvironment Immunomodulation By Nanoformulated Tlr 7/8 Agonist And Pi3k Delta Inhibitor Enhances Therapeutic Benefits Of Radiotherapy, Mostafa Yazdimamaghani, Oleg V. Kolupaev, Chaemin Lim, Duhyeong Hwang, Sonia J. Laurie, Charles M. Perou, Alexander V. Kabanov, Jonathan S. Serody
Tumor Microenvironment Immunomodulation By Nanoformulated Tlr 7/8 Agonist And Pi3k Delta Inhibitor Enhances Therapeutic Benefits Of Radiotherapy, Mostafa Yazdimamaghani, Oleg V. Kolupaev, Chaemin Lim, Duhyeong Hwang, Sonia J. Laurie, Charles M. Perou, Alexander V. Kabanov, Jonathan S. Serody
Chemical and Biochemical Engineering Faculty Research & Creative Works
Infiltration of immunosuppressive cells into the breast tumor microenvironment (TME) is associated with suppressed effector T cell (Teff) responses, accelerated tumor growth, and poor clinical outcomes. Previous studies from our group and others identified infiltration of immunosuppressive myeloid-derived suppressor cells (MDSCs) and regulatory T cells (Tregs) as critical contributors to immune dysfunction in the orthotopic claudin-low tumor model, limiting the efficacy of adoptive cellular therapy. However, approaches to target these cells in the TME are currently lacking. To overcome this barrier, polymeric micellular nanoparticles (PMNPs) were used for the co-delivery of small molecule drugs activating Toll-like receptors 7 and 8 …
Machine Learning Modeling For Hydrolysis Recycling Of Pet Waste, Jie Li, Lanjia Pan, Hossein Abedsoltan, Hailong Wang, Taiyang Liu, Xiangzhou Yuan, Yong Sik Ok, Yin Wang
Machine Learning Modeling For Hydrolysis Recycling Of Pet Waste, Jie Li, Lanjia Pan, Hossein Abedsoltan, Hailong Wang, Taiyang Liu, Xiangzhou Yuan, Yong Sik Ok, Yin Wang
Chemical and Biochemical Engineering Faculty Research & Creative Works
The hydrolysis of polyethylene terephthalate (PET) into terephthalic acid (TPA) can efficiently recycle waste PET, but achieving high conversion efficiency through smart reaction design remains challenging. To develop a robust and accurate machine learning (ML) model for the in-depth understanding and intelligent design of PET hydrolysis, we compiled a new dataset comprising 942 data points and comprehensive information of 44 variables involved in heating type, acid/base catalyst (ABC), organic solvent (OS), co-solvent (CS), phase transfer catalyst (PTC), and operational conditions. The developed Neural Network model demonstrated the best performance in predicting PET conversion, with a testing determination coefficient (R2 …
Mechanistic Scale-Up Of Gas-Solid Fluidized Beds Via Local Hydrodynamic Similarity, Faraj M. Zaid, Thaar M. Aljuwaya, Muthanna H. Al-Dahhan
Mechanistic Scale-Up Of Gas-Solid Fluidized Beds Via Local Hydrodynamic Similarity, Faraj M. Zaid, Thaar M. Aljuwaya, Muthanna H. Al-Dahhan
Chemical and Biochemical Engineering Faculty Research & Creative Works
This study presents a detailed experimental evaluation of a newly developed mechanistic scale-up methodology for gas-solid fluidized beds. Traditional scale-up approaches typically rely on matching global dimensionless groups, which often fail to ensure local hydrodynamic similarity. In contrast, the new mechanistic method aims to achieve scale-up by matching the radial profiles of gas holdup between geometrically similar beds at corresponding dimensionless axial positions (z/Dc). This approach is based on the premise that when gas holdup profiles align, other key hydrodynamic parameters—such as solids holdup and particle velocity—also become similar. To validate this methodology, experiments were conducted in two …
Characterizing The Transient Emission Of Particles And Gases From A Single Puff Of Electronic Cigarette Smoke, Kashala Fabrice Kapiamba, Steven Achterberg, Ta Chun Lin, Philip D. Whitefield, Yue-Wern Huang, Yang Wang
Characterizing The Transient Emission Of Particles And Gases From A Single Puff Of Electronic Cigarette Smoke, Kashala Fabrice Kapiamba, Steven Achterberg, Ta Chun Lin, Philip D. Whitefield, Yue-Wern Huang, Yang Wang
Chemistry Faculty Research & Creative Works
This study employed high-time-resolution systems to examine the transient properties of aerosols and gases emitted from electronic cigarette (EC) puffs. Using a fast aerosol sizer, we measured particle size distributions (PSDs) across various EC brands (JUUL, VUSE, VOOPOO), revealing sizes ranging from 5 to 1000 nm at concentrations of 107 to 1010 cm-3. Most aerosols were found to be in the ultrafine range (below 100 nm), with JUUL-, VUSE-, and VOOPOO-producing aerosols with geometric mean sizes of 19.9, 47.3, and 29.4 nm, respectively. Applying the International Commission on Radiological Protection (ICRP) deposition model and assuming no further evolution of aerosols …
Instantaneous Hydrolysis Of Methyl Paraoxon Nerve Agent Simulant Is Catalyzed By Nontoxic Aminoguanidine Imines, Emmanuel Kingsley Darkwah, Puspa Aryal, Chi Zhang, Charles B. Musgrave, William A. Goddard, V. Prakash Reddy
Instantaneous Hydrolysis Of Methyl Paraoxon Nerve Agent Simulant Is Catalyzed By Nontoxic Aminoguanidine Imines, Emmanuel Kingsley Darkwah, Puspa Aryal, Chi Zhang, Charles B. Musgrave, William A. Goddard, V. Prakash Reddy
Chemistry Faculty Research & Creative Works
Exposure to organophosphate-based nerve agents and pesticides poses health and security threats to civilians, soldiers, and first responders. Thus, there is a need to develop effective decontamination agents that are nonhazardous to human health. To address this, we demonstrate that instantaneous hydrolysis of methyl paraoxon (Me-POX), a nerve agent simulant, can be achieved in the presence of aminoguanidine imines at pH 10: ● the pyridine-4-aldehyde aminoguanidine-imine (1) and ● the 2,3-butanedione aminoguanidine-imine (2). The hydrolysis of Me-POX under these conditions is substantially faster than that of the state-of-the-art decontaminating agent, Dekon-139 (2,3-butanedione oxime, potassium salt). Furthermore, Dekon-139 shows adverse effects …
Pla-Based Bone Tissue Engineering Scaffolds Incorporating Hydroxyapatite And Bioactive Glass Using Digital Light Processing, Engin Gepek, Fateme Fayyazbakhsh, Lev Suliandziga, Vadym Mochalin, Osman Iyibilgin, Yue-Wern Huang, Ming C. Leu
Pla-Based Bone Tissue Engineering Scaffolds Incorporating Hydroxyapatite And Bioactive Glass Using Digital Light Processing, Engin Gepek, Fateme Fayyazbakhsh, Lev Suliandziga, Vadym Mochalin, Osman Iyibilgin, Yue-Wern Huang, Ming C. Leu
Chemistry Faculty Research & Creative Works
Bone tissue engineering (BTE) aims to repair bone defects using biocompatible materials with tailored geometries and pore structures, providing appropriate mechanical support and control over biodegradation kinetics to promote bone growth. In this study, we utilized digital light processing (DLP) 3D printing to fabricate scaffolds with varying pore sizes using polymer–ceramic slurries composed of polylactic acid (PLA) as the main polymer matrix, incorporated with hydroxyapatite (HA) and bioactive borate glass (BBG) at various ratios. We studied the effect of composition on rheological behavior, printability, mechanical properties, bioactivity, degradation rate, and biocompatibility. While HA increased viscosity and reduced printing accuracy, it …
Tricatalytic Organocatalyst-Enzyme Hybrid Cascade For Improving Complete Oxidation Of Glucose To Carbon Dioxide, Adam Milam, Rokas Gerulskis, Jose Intano, Shelley D. Minteer
Tricatalytic Organocatalyst-Enzyme Hybrid Cascade For Improving Complete Oxidation Of Glucose To Carbon Dioxide, Adam Milam, Rokas Gerulskis, Jose Intano, Shelley D. Minteer
Chemistry Faculty Research & Creative Works
Advancing energy harvesting is crucial for the development of wearable and implantable technologies. Given the high concentration of complex fuels, such as glucose, in biological fluids, biofuel cells present a promising avenue for exploration. However, glucose fuel cells that have been published to date typically catalyze only one or two of the maximum 12 oxidation steps for glucose, resulting in low energy density. Although known multienzyme cascades, which are sequential biochemical reactions where multiple enzymes work in tandem to convert a substrate into a final product, have addressed this inefficiency, they come with several trade-offs, such as reduced power density …
Enhanced Biofuel Cells Based On A Hybrid Enzymatic/Bimetallic Composite For Complete Lactate Catalytic Electrooxidation, Jefferson Honorio Franco, João Victor Bonaldo, Shelley D. Minteer, Adalgisa R. De Andrade
Enhanced Biofuel Cells Based On A Hybrid Enzymatic/Bimetallic Composite For Complete Lactate Catalytic Electrooxidation, Jefferson Honorio Franco, João Victor Bonaldo, Shelley D. Minteer, Adalgisa R. De Andrade
Chemistry Faculty Research & Creative Works
We describe complete lactate electrooxidation in an enzymatic biofuel cell that combines the catalytic action of the bimetallic composite Ru@Pt-CNT and the enzyme oxalate oxidase (OxOx). The Ru@Pt-CNT/OxOx hybrid electrode was 2.0-fold more catalytically active than the electrode containing the bimetallic composite only. During chronoamperometric experiments, the hybrid electrode achieved a 35% higher maximum current density (2.65 ± 0.15 mA cm-2) than the Ru@Pt-CNT electrode. Electrochemical impedance spectroscopy showed that the hybrid electrode had lower charge transfer resistance than the Ru@Pt-CNT electrode, confirming that OxOx had a high affinity for lactate during the bioelectrocatalytic reaction on the electrode …
Mechanical And Thermal Characterization Of Additively Manufactured Carbon/Nylon 12 And Carbon/Peek Composites, Matik Heskin, Bradley Deuser, Thomas P. Schuman, K. Chandrashekhara, John Bayldon, Jeff Degrange, Steven Patterson, Neiko Levenhagen
Mechanical And Thermal Characterization Of Additively Manufactured Carbon/Nylon 12 And Carbon/Peek Composites, Matik Heskin, Bradley Deuser, Thomas P. Schuman, K. Chandrashekhara, John Bayldon, Jeff Degrange, Steven Patterson, Neiko Levenhagen
Chemistry Faculty Research & Creative Works
This study explores additive manufacturing of carbon fiber-reinforced thermoplastic composites using the Composite-Based Additive Manufacturing (CBAM) process. Carbon/Nylon 12 and Carbon/PEEK composites were fabricated and evaluated through mechanical (compression, tensile, flexural, and impact) and thermal (DSC and TGA) tests. Carbon/PEEK exhibited superior mechanical performance, with 97.5% higher tensile strength, 79.8% higher elastic modulus, and 59.6% higher flexural strength compared to Carbon/Nylon 12. Thermal testing showed that Carbon/PEEK had higher thermal stability, beginning degradation at 350 °C versus 298 °C for Carbon/Nylon. These results indicate that CBAM-fabricated Carbon/PEEK composites are suitable for applications requiring high strength and temperature resistance.
A New Paradigm For The Supramolecular Structure Of Laterally Offset Diarenes: Polymorphs Ii Of Para-Substituted Acetophenone Azines, Yp.Ph.(Me)C.N.N.C(Me).Ph.Yp (Y = Cl, Br, Ch3), Harmeet Bhoday, Kaidi Yang, Steven P. Kelley, Rainer Glaser
A New Paradigm For The Supramolecular Structure Of Laterally Offset Diarenes: Polymorphs Ii Of Para-Substituted Acetophenone Azines, Yp.Ph.(Me)C.N.N.C(Me).Ph.Yp (Y = Cl, Br, Ch3), Harmeet Bhoday, Kaidi Yang, Steven P. Kelley, Rainer Glaser
Chemistry Faculty Research & Creative Works
The crystal structures of polymorphs II of acetophenone azines YpPhRCNNCRPhYp with R = CH3 and Y = Cl (1M), Br (2M), and CH3 (8M) are discussed. The azine molecules in polymorphs II are Ci-symmetric with trans-azine moieties and conrotatory phenyl twists. Polymorphs 1M-I and 2M-I contain C2-symmetric enantiomers with pronounced azine twists and disrotatory phenyl twists and allow for strong lateral double T-contacts. The three polymorphs II exemplify the new Paradigm IV for the supramolecular architectures of "laterally offset diarenes" and result in "shiplap/flat" idioteloamphiphile monolayers. Intralayer lateral attraction is provided by edge-to-face arene-arene contacts …