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Articles 301 - 330 of 6056

Full-Text Articles in Physical Sciences and Mathematics

Advances In Bioelectrode Design For Developing Electrochemical Biosensors, Nabajyoti Kalita, Sudarshan Gogoi, Shelley D. Minteer, Pranab Goswami Jan 2023

Advances In Bioelectrode Design For Developing Electrochemical Biosensors, Nabajyoti Kalita, Sudarshan Gogoi, Shelley D. Minteer, Pranab Goswami

Chemistry Faculty Research & Creative Works

The critical performance factors such as selectivity, sensitivity, operational and storage stability, and response time of electrochemical biosensors are governed mainly by the function of their key component, the bioelectrode. Suitable design and fabrication strategies of the bioelectrode interface are essential for realizing the requisite performance of the biosensors for their practical utility. A multifaceted attempt to achieve this goal is visible from the vast literature exploring effective strategies for preparing, immobilizing, and stabilizing biorecognition elements on the electrode surface and efficient transduction of biochemical signals into electrical ones (i.e., current, voltage, and impedance) through the bioelectrode interface with the …

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Continual Reinforcement Learning Formulation For Zero-Sum Game-Based Constrained Optimal Tracking, Behzad Farzanegan, Sarangapani Jagannathan Jan 2023

Continual Reinforcement Learning Formulation For Zero-Sum Game-Based Constrained Optimal Tracking, Behzad Farzanegan, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This study provides a novel reinforcement learning-based optimal tracking control of partially uncertain nonlinear discrete-time (DT) systems with state constraints using zero-sum game (ZSG) formulation. To address optimal tracking, a novel augmented system consisting of tracking error and its integral value, along with an uncertain desired trajectory, is constructed. A barrier function (BF) with a tradeoff factor is incorporated into the cost function to keep the state trajectories to remain within a compact set and to balance safety with optimality. Next, by using the modified value functional, the ZSG formulation is introduced wherein an actor–critic neural network (NN) framework is …

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Securing The Transportation Of Tomorrow: Enabling Self-Healing Intelligent Transportation, Elanor Jackson, Sahra Sedigh Sarvestani Jan 2023

Securing The Transportation Of Tomorrow: Enabling Self-Healing Intelligent Transportation, Elanor Jackson, Sahra Sedigh Sarvestani

Electrical and Computer Engineering Faculty Research & Creative Works

The safety of autonomous vehicles relies on dependable and secure infrastructure for intelligent transportation. The doctoral research described in this paper aims to enable self-healing and survivability of the intelligent transportation systems required for autonomous vehicles (AV-ITS). The proposed approach is comprised of four major elements: qualitative and quantitative modeling of the AV-ITS, stochastic analysis to capture and quantify interdependencies, mitigation of disruptions, and validation of efficacy of the self-healing process. This paper describes the overall methodology and presents preliminary results, including an agent-based model for detection of and recovery from disruptions to the AV-ITS.

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Personalizing Student Graduation Paths Using Expressed Student Interests, Nicolas Dobbins, Ali R. Hurson, Sahra Sedigh Jan 2023

Personalizing Student Graduation Paths Using Expressed Student Interests, Nicolas Dobbins, Ali R. Hurson, Sahra Sedigh

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes an intelligent recommendation approach to facilitate personalized education and help students in planning their path to graduation. The goal is to identify a path that aligns with a student's interests and career goals and approaches optimality with respect to one or more criteria, such as time-to-graduation or credit hours taken. The approach is illustrated and verified through application to undergraduate curricula at the Missouri University of Science and Technology.

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Rafid: A Lightweight Approach To Radio Frequency Interference Detection In Time Domain Using Lstm And Statistical Analysis, Luke A. Smith, Vishesh Kumar Tanwar, Maciej Jan Zawodniok, Sanjay Kumar Madria Jan 2023

Rafid: A Lightweight Approach To Radio Frequency Interference Detection In Time Domain Using Lstm And Statistical Analysis, Luke A. Smith, Vishesh Kumar Tanwar, Maciej Jan Zawodniok, Sanjay Kumar Madria

Electrical and Computer Engineering Faculty Research & Creative Works

Recently, the utilization of Radio Frequency (RF) devices has increased exponentially over numerous vertical platforms. This rise has led to an abundance of Radio Frequency Interference (RFI) continues to plague RF systems today. The continued crowding of the RF spectrum makes RFI efficient and lightweight mitigation critical. Detecting and localizing the interfering signals is the foremost step for mitigating RFI concerns. Addressing these challenges, we propose a novel and lightweight approach, namely RaFID, to detect and locate the RFI by incorporating deep neural networks (DNNs) and statistical analysis via batch-wise mean aggregation and standard deviation (SD) calculations. RaFID investigates the …

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Lifelong Deep Learning-Based Control Of Robot Manipulators, Irfan Ganie, Jagannathan Sarangapani Jan 2023

Lifelong Deep Learning-Based Control Of Robot Manipulators, Irfan Ganie, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

This study proposes a lifelong deep learning control scheme for robotic manipulators with bounded disturbances. This scheme involves the use of an online tunable deep neural network (DNN) to approximate the unknown nonlinear dynamics of the robot. The control scheme is developed by using a singular value decomposition-based direct tracking error-driven approach, which is utilized to derive the weight update laws for the DNN. To avoid catastrophic forgetting in multi-task scenarios and to ensure lifelong learning (LL), a novel online LL scheme based on elastic weight consolidation is included in the DNN weight-tuning laws. Our results demonstrate that the resulting …

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Lifelong Learning-Based Multilayer Neural Network Control Of Nonlinear Continuous-Time Strict-Feedback Systems, Irfan Ahmad Ganie, S. (Sarangapani) Jagannathan Jan 2023

Lifelong Learning-Based Multilayer Neural Network Control Of Nonlinear Continuous-Time Strict-Feedback Systems, Irfan Ahmad Ganie, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In This Paper, We Investigate Lifelong Learning (LL)-Based Tracking Control for Partially Uncertain Strict Feedback Nonlinear Systems with State Constraints, employing a Singular Value Decomposition (SVD) of the Multilayer Neural Networks (MNNs) Activation Function based Weight Tuning Scheme. the Novel SVD-Based Approach Extends the MNN Weight Tuning to (Formula Presented.) Layers. a Unique Online LL Method, based on Tracking Error, is Integrated into the MNN Weight Update Laws to Counteract Catastrophic Forgetting. to Adeptly Address Constraints for Safety Assurances, Taking into Account the Effects Caused by Disturbances, We Utilize a Time-Varying Barrier Lyapunov Function (TBLF) that Ensures a Uniformly Ultimately …

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Towards Robust Consensus For Intelligent Decision-Making In Iot Blockchain Networks, Charles Rawlins, S. (Sarangapani) Jagannathan Jan 2023

Towards Robust Consensus For Intelligent Decision-Making In Iot Blockchain Networks, Charles Rawlins, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Distributed consensus is the core aspect of blockchain protocol security design. Recent protocols like IOTA have improved concurrency and scalability over Proof-of-work (PoW) with Bitcoin but have core design decisions that are inefficient for limited devices and do not take advantage of previous network experience to reduce calculations. This work proposes the first blockchain consensus protocol based on active machine-learning decisions, called Proof-of-history (PoH). PoH is setup as a distributed reinforcement-learning task for monitoring classification and training of blockchain transactions with an inner deep classifier. Early theoretical analysis and simulations show that PoH is robust to uncoordinated byzantine attacks through …

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Improved Intelligent Ledger Construction For Realistic Iot Blockchain Networks, Charles Rawlins, S. (Sarangapani) Jagannathan Jan 2023

Improved Intelligent Ledger Construction For Realistic Iot Blockchain Networks, Charles Rawlins, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Scalability is essential for next generation blockchain technology to integrate with large mobile networks like Internet of Things (IoT). The IOTA distributed ledger protocol has combined transaction generation and verification to address this, but at the expense of increased reliance on connectivity to resolve conflicts with a novel ledger data structure. Intelligent Ledger Construction (ILC) was proposed as an auditable lightweight reinforcement-learning scheme to address this constraint with proposal of local conflict resolution with machine-learning classification. This effort presents an improved reliability reward model to enhance training for ILC and further reduce adversarial gaming and resource usage. Testing this revision …

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Skin Lesion Segmentation In Dermoscopic Images With Noisy Data, Norsang Lama, Jason Hagerty, Anand Nambisan, Ronald Joe Stanley, William Van Stoecker Jan 2023

Skin Lesion Segmentation In Dermoscopic Images With Noisy Data, Norsang Lama, Jason Hagerty, Anand Nambisan, Ronald Joe Stanley, William Van Stoecker

Electrical and Computer Engineering Faculty Research & Creative Works

We Propose a Deep Learning Approach to Segment the Skin Lesion in Dermoscopic Images. the Proposed Network Architecture Uses a Pretrained Efficient Net Model in the Encoder and Squeeze-And-Excitation Residual Structures in the Decoder. We Applied This Approach on the Publicly Available International Skin Imaging Collaboration (ISIC) 2017 Challenge Skin Lesion Segmentation Dataset. This Benchmark Dataset Has Been Widely Used in Previous Studies. We Observed Many Inaccurate or Noisy Ground Truth Labels. to Reduce Noisy Data, We Manually Sorted All Ground Truth Labels into Three Categories — Good, Mildly Noisy, and Noisy Labels. Furthermore, We Investigated the Effect of Such …

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Delivering Broadband Light Deep Into Diffusive Media, Rohin Mcintosh, Nicholas Bender, Alexey Yamilov, Arthur Goetschy, Chia Wei Hsu, Hasan Yilmaz, Hui Cao Jan 2023

Delivering Broadband Light Deep Into Diffusive Media, Rohin Mcintosh, Nicholas Bender, Alexey Yamilov, Arthur Goetschy, Chia Wei Hsu, Hasan Yilmaz, Hui Cao

Physics Faculty Research & Creative Works

Waves propagate diffusively through disordered media, such as biological tissue, clouds, and paint, due to random scattering. Recent advances in optical wavefront shaping techniques have enabled controlling coherent light propagation in multiple-scattering samples. We overcome wave diffusion to deliver optical energy into a target region of arbitrary size and shape anywhere inside a strong-scattering system. This is particularly important for applications such as photoacoustic microscopy and optogenetics, where light needs to be deposited deep into biological tissue. For monochromatic light, we previously introduced the deposition matrix (DM) Z(ω), which maps its input wavefront to the field distribution in the target …

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Scattering-Angle Dependence Of Doubly Differential Cross Sections For Ionization In Proton Collisions With Molecular Hydrogen, C. T. Plowman, K. H. Spicer, Michael Schulz, A. S. Kadyrov Jan 2023

Scattering-Angle Dependence Of Doubly Differential Cross Sections For Ionization In Proton Collisions With Molecular Hydrogen, C. T. Plowman, K. H. Spicer, Michael Schulz, A. S. Kadyrov

Physics Faculty Research & Creative Works

The wave-packet convergent close-coupling (WP-CCC) approach is applied to calculate the energy spectrum of electrons ejected in p+H2 collisions as a function of the scattering angle of the projectile. The calculations are performed for projectile energies of 75, 100, and 200 keV. At these incident energies there are many competing reaction channels that play an essential role in the collision dynamics. The target is modeled as an orientationally averaged effective one-electron system. The results are compared with available perturbative calculations and experimental data. Good agreement between the WP-CCC results and experimental data is found for small emission energies, especially when …

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Simulation Of Coherent Remission In Planar Disordered Medium, Pablo Jara-Palacios, Ho Chun Lin, Chia Wei Hsu, Hui Cao, Alexey Yamilov Jan 2023

Simulation Of Coherent Remission In Planar Disordered Medium, Pablo Jara-Palacios, Ho Chun Lin, Chia Wei Hsu, Hui Cao, Alexey Yamilov

Physics Faculty Research & Creative Works

Waves remitted from a scattering medium carry information that can be used for non-invasive imaging and sensing. Such techniques are usually limited by a low photon budget. Recent progress in optical wavefront shaping has enabled coherent control with an order-of-magnitude enhancement of remission [1]. This experimental study necessitated increasingly demanding numerical simulations. Extending this line of research requires more sophisticated computational techniques capable of simulating multiple instances of even larger systems. Here, we demonstrate that remission geometry can be efficiently simulated using a novel open-source software package [2] Maxwell's Equations Solver with Thousands of Inputs (MESTI). To verify its numerical …

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Rate-Monotonic Scheduler For Lora-Based Smart Space Monitoring System, Preti Kumari, Hari Prabhat Gupta, Sajal K. Das, Rahul Bansal Jan 2023

Rate-Monotonic Scheduler For Lora-Based Smart Space Monitoring System, Preti Kumari, Hari Prabhat Gupta, Sajal K. Das, Rahul Bansal

Computer Science Faculty Research & Creative Works

Smart spaces system equipped with sensors to collect data that can be used to generate insights about its environmental conditions. Those collected data is then transmitted to the applications to enhance the comfort, quality of life, and security of the space. Long Range (LoRa) technology provides long distance coverage and consumes low energy which makes it suitable for smart space application. There are six virtual channels to transmit data in LoRa, however network faces the interference problem when nodes transmitted data at the same time. The interference problem makes LoRa less suitable for time-critical applications. To mitigate the interference problem, …

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Environmentally-Aware And Energy-Efficient Multi-Drone Coordination And Networking For Disaster Response, Chengyi Qu, Francesco Betti Sorbelli, Rounak Singh, Prasad Calyam, Sajal K. Das Jan 2023

Environmentally-Aware And Energy-Efficient Multi-Drone Coordination And Networking For Disaster Response, Chengyi Qu, Francesco Betti Sorbelli, Rounak Singh, Prasad Calyam, Sajal K. Das

Computer Science Faculty Research & Creative Works

In a Disaster Response Management (DRM) Scenario, Communication and Coordination Are Limited, and Absence of Related Infrastructure Hinders Situational Awareness. Unmanned Aerial Vehicles (UAVs) or Drones Provide New Capabilities for DRM to Address These Barriers. However, There is a Dearth of Works that Address Multiple Heterogeneous Drones Collaboratively Working Together to Form a Flying Ad-Hoc Network (FANET) with Air-To-Air and Air-To-Ground Links that Are Impacted By: (I) Environmental Obstacles, (Ii) Wind, and (Iii) Limited Battery Capacities. in This Paper, We Present a Novel Environmentally-Aware and Energy-Efficient Multi-Drone Coordination and Networking Scheme that Features a Reinforcement Learning (RL) based Location Prediction …

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Deep Meta Q-Learning Based Multi-Task Offloading In Edge-Cloud Systems, Nelson Sharma, Aswini Ghosh, Rajiv Misra, Sajal K. Das Jan 2023

Deep Meta Q-Learning Based Multi-Task Offloading In Edge-Cloud Systems, Nelson Sharma, Aswini Ghosh, Rajiv Misra, Sajal K. Das

Computer Science Faculty Research & Creative Works

Resource-Constrained Edge Devices Can Not Efficiently Handle the Explosive Growth of Mobile Data and the Increasing Computational Demand of Modern-Day User Applications. Task Offloading Allows the Migration of Complex Tasks from User Devices to the Remote Edge-Cloud Servers Thereby Reducing their Computational Burden and Energy Consumption While Also Improving the Efficiency of Task Processing. However, Obtaining the Optimal Offloading Strategy in a Multi-Task Offloading Decision-Making Process is an NP-Hard Problem. Existing Deep Learning Techniques with Slow Learning Rates and Weak Adaptability Are Not Suitable for Dynamic Multi-User Scenarios. in This Article, We Propose a Novel Deep Meta-Reinforcement Learning-Based Approach to …

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Lasa: Location-Aware Scheduling Algorithm In Industrial Iot Networks With Mobile Nodes, Marco Pettorali, Francesca Righetti, Carlo Vallati, Sajal K. Das, Giuseppe Anastasi Jan 2023

Lasa: Location-Aware Scheduling Algorithm In Industrial Iot Networks With Mobile Nodes, Marco Pettorali, Francesca Righetti, Carlo Vallati, Sajal K. Das, Giuseppe Anastasi

Computer Science Faculty Research & Creative Works

The Synchronized Single-hop Multiple Gateway (SHMG) is a framework recently proposed to support mobility into 6TiSCH, the standard network architecture defined for Industrial Internet of Things (IIoT) deployments. SHMG supports industrial applications with stringent requirements by adopting the Shared-Downstream Dedicated-Upstream (SD-DU) scheduling policy, which allocates to Mobile Nodes (MNs) a set of dedicated transmission opportunities for uplink data. Such allocation is performed on all the Border Routers (BRs) of the network without considering the location of MNs. Transmission opportunities are reserved also in BRs far from the current location of the MN, resulting in a waste of resources that limits …

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Reward Maximization For Disaster Zone Monitoring With Heterogeneous Uavs, Wenzheng Xu, Chengxi Wang, Hongbin Xie, Weifa Liang, Haipeng Dai, Zichuan Xu, Ziming Wang, Bing Guo, Sajal K. Das Jan 2023

Reward Maximization For Disaster Zone Monitoring With Heterogeneous Uavs, Wenzheng Xu, Chengxi Wang, Hongbin Xie, Weifa Liang, Haipeng Dai, Zichuan Xu, Ziming Wang, Bing Guo, Sajal K. Das

Computer Science Faculty Research & Creative Works

In this paper, we study the deployment of $K$ heterogeneous UAVs to monitor Points of Interest (PoIs) in a disaster zone, where a PoI may represent a school building or an office building, in which people are trapped. A UAV can take images/videos of PoIs and send its collected information back to a nearby rescue station for decision-making. Unlike most existing studies that focused on only homogeneous UAVs, we here study the scheduling of $K$ heterogeneous UAVs, where different UAVs have different energy capacities and functionalities that lead to different monitoring qualities (monitoring rewards) of each PoI. For example, one …

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Q-Learning For Sum-Throughput Optimization In Wireless Visible-Light Uav Networks, Yuwei Long, Nan Cen Jan 2023

Q-Learning For Sum-Throughput Optimization In Wireless Visible-Light Uav Networks, Yuwei Long, Nan Cen

Computer Science Faculty Research & Creative Works

Unmanned Aerial Vehicles (UAVs) Have Been Adopted as Aerial Base Stations (ABSs) to Provide Wireless Connectivity to Ground Users in Events of Increased Network Demand, and Points-Of-Failure Infrastructure (Such as in Disasters). However, with the Existing Crowded Radio Frequency (RF) Spectrum, UAV ABSs Cannot Provide High-Data-Rate Communication Required in 5G and beyond. to Address This Challenge, Visible Light Communication (VLC) is Proposed to Be Equipped on UAVs to Take Advantage of the Flexible and On-Demand Deployment Feature of the UAV, and the High-Data-Rate Communication of the VLC. However, VLC Has Strong Alignment Requirements between Transceivers, Therefore, How to Determine the …

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The Generalized Lyapunov Function As Ao’S Potential Function: Existence In Dimensions 1 And 2, Haoyu Wang, Wenqing Hu, Xiaoliang Gan, Ping Ao Jan 2023

The Generalized Lyapunov Function As Ao’S Potential Function: Existence In Dimensions 1 And 2, Haoyu Wang, Wenqing Hu, Xiaoliang Gan, Ping Ao

Mathematics and Statistics Faculty Research & Creative Works

By using Ao's decomposition for stochastic dynamical systems, a new notion of potential function has been introduced by Ao and his collabora-tors recently. We show that this potential function agrees with the generalized Lyapunov function of the deterministic part of the stochastic dynamical sys-tem. We further prove the existence of Ao's potential function in dimensions 1 and 2 via the solution theory of first-order partial differential equations. Our framework reveals the equivalence between Ao's potential function and Lyapunov function, the latter being one of the most significant central notions in dynamical systems. Using this equivalence, our existence proof can also …

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Three Solutions For Discrete Anisotropic Kirchhoff-Type Problems, Martin Bohner, Giuseppe Caristi, Ahmad Ghobadi, Shapour Heidarkhani Jan 2023

Three Solutions For Discrete Anisotropic Kirchhoff-Type Problems, Martin Bohner, Giuseppe Caristi, Ahmad Ghobadi, Shapour Heidarkhani

Mathematics and Statistics Faculty Research & Creative Works

In this article, using critical point theory and variational methods, we investigate the existence of at least three solutions for a class of double eigenvalue discrete anisotropic Kirchhoff-type problems. An example is presented to demonstrate the applicability of our main theoretical findings.

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Using Catalysis To Control The Morphology And Stiffness Of Shape Memory Poly(Isocyanurate-Urethane) (Pir-Pur) Aerogels, A. B.M. Shaheen Ud Doulah, Chandana Mandal, Hojat Majedi Far, Vaibhav A. Edlabadkar, Rushi U. Soni, Stephen Y. Owusu, Nicholas Leventis, Chariklia Sotiriou-Leventis Jan 2023

Using Catalysis To Control The Morphology And Stiffness Of Shape Memory Poly(Isocyanurate-Urethane) (Pir-Pur) Aerogels, A. B.M. Shaheen Ud Doulah, Chandana Mandal, Hojat Majedi Far, Vaibhav A. Edlabadkar, Rushi U. Soni, Stephen Y. Owusu, Nicholas Leventis, Chariklia Sotiriou-Leventis

Chemistry Faculty Research & Creative Works

A large array of anhydrous metal ions were tested as catalysts in the preparation of shape memory poly(isocyanurate-urethane) (PIR-PUR) aerogels from the reaction of 1,3,5-tris(6-isocyanatohexyl)-1,3,5-triazinane-2,4,6-trione (Desmodur N3300A: a well-known isocyanurate-based aliphatic triisocyanate) and triethylene glycol (TEG) in anhydrous acetonitrile. The reaction yielded wet gels that were dried into aerogels in an autoclave with supercritical fluid CO2. The catalytic activity was mostly identified among CH3CN-soluble salts (mainly chlorides) of third-row d-block elements from iron to zinc, group 13 elements from aluminum to thallium, as well as cadmium, bismuth, and tin. Tin (119Sn) NMR indicated that the metal ion complexes with TEG, …

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Rovibrational States Calculations Of The H2o-Hcn Heterodimer With The Multiconfiguration Time Dependent Hartree Method, Hervé Tajouo Tela, Ernesto Quintas-Sánchez, Marie Lise Dubernet, Yohann Scribano, Richard Dawes, Fabien Gatti, Steve Ndengué Jan 2023

Rovibrational States Calculations Of The H2o-Hcn Heterodimer With The Multiconfiguration Time Dependent Hartree Method, Hervé Tajouo Tela, Ernesto Quintas-Sánchez, Marie Lise Dubernet, Yohann Scribano, Richard Dawes, Fabien Gatti, Steve Ndengué

Chemistry Faculty Research & Creative Works

Water and hydrogen cyanide are two of the most common species in space and the atmosphere with the ability of binding to form dimers such as H2O-HCN. In the literature, while calculations characterizing various properties of the H2O-HCN cluster (equilibrium distance, vibrational frequencies and rotational constants) have been done in the past, extensive calculations of the rovibrational states of this system using a reliable quantum dynamical approach have yet to be reported. In this work, we intend to mend that by performing the first calculation of the rovibrational states of the H2O-HCN van der …

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Nmr Study Of Co2 Capture By Butylamine And Oligopeptide Kdde In Aqueous Solution: Capture Efficiency And Gibbs Free Energy Of The Capture Reaction As A Function Of Ph**, Kaidi Yang, Joseph Schell, Fabio Gallazzi, Wei Wycoff, Rainer Glaser Jan 2023

Nmr Study Of Co2 Capture By Butylamine And Oligopeptide Kdde In Aqueous Solution: Capture Efficiency And Gibbs Free Energy Of The Capture Reaction As A Function Of Ph**, Kaidi Yang, Joseph Schell, Fabio Gallazzi, Wei Wycoff, Rainer Glaser

Chemistry Faculty Research & Creative Works

We Have Been Interested in the Development of Rubisco-Based Biomimetic Systems for Reversible CO2 Capture from Air. Our Design of the Chemical CO2 Capture and Release (CCR) System is Informed by the Understanding of the Binding of the Activator CO2 (ACO2) in Rubisco (Ribulose-1,5-Bisphosphate Carboxylase/oxygenase). the Active Site Consists of the Tetrapeptide Sequence Lys-Asp-Asp-Glu (Or KDDE) and the Lys Sidechain Amine is Responsible for the CO2 Capture Reaction. We Are Studying the Structural Chemistry and the Thermodynamics of CO2 Capture based on the Tetrapeptide CH3CO−KDDE−NH2 ("KDDE") in Aqueous …

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Electrodeposition Of Epitaxial Wide Bandgap P-Type Semiconductors And Copper Metal For Energy Conversion And Flexible Electronics, Bin Luo Jan 2023

Electrodeposition Of Epitaxial Wide Bandgap P-Type Semiconductors And Copper Metal For Energy Conversion And Flexible Electronics, Bin Luo

Doctoral Dissertations

"Epitaxial electrodeposition is a simple, low-cost technology to produce highly ordered materials on single-crystal surfaces. This research focuses on the epitaxial electrodeposition of wide bandgap p-type semiconductors and epitaxial Cu thin films via a self-assembled monolayer for energy conversion and flexible electronics. Paper I introduces the epitaxial electrodeposition of hole conducting CuSCN nanorods onto Au (111) surface, and lift-off to produce flexible and transparent foils. Highly ordered CuSCN could serve as an inorganic transport layer in various opto-electronic devices such as perovskite solar cells, LEDs, and transistors. An ordered and transparent CuSCN foil was also produced by epitaxial lift-off following …

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Near-Ir Spectroscopic Analysis Of The Primary Volatile Composition Of Long And Short-Period Comets, Younas Khan Jan 2023

Near-Ir Spectroscopic Analysis Of The Primary Volatile Composition Of Long And Short-Period Comets, Younas Khan

Doctoral Dissertations

"Comets are among the most well-preserved objects that formed in the protosolar nebula ∼4.5 Gyr ago. Hence, they are important for understanding various aspects of the formation, evolution, and habitability of the solar system. Multiple primary volatiles (molecules directly sublimating into the coma from the nucleus) emit via rovibrational transitions in the near-IR, providing opportunities to calculate their abundances. To date, only ∼50 comets have been characterized for their primary volatiles, with the short-period Jupiter-family comets (JFCs) being significantly underrepresented. In contrast, hundreds of comets have been sampled at optical/UV wavelengths, primarily for the composition of daughter species, leading to …

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Fluorination Of Rubisco-Mimetic Co2 Capture Systems. Theoretical And Experimental Studies Of Ammonium Ion Acidity Depression And Carbamylation, Brian Michael Jameson Jan 2023

Fluorination Of Rubisco-Mimetic Co2 Capture Systems. Theoretical And Experimental Studies Of Ammonium Ion Acidity Depression And Carbamylation, Brian Michael Jameson

Doctoral Dissertations

"RuBisCO-inspired CO2 capture and release (CCR) systems featuring amines have been developed for the purpose of reversable CO2 capture from air. The enzyme active site consists of the tetrapeptide sequence Lys-Asp-Asp-Glu. The Lys sidechain amine undergoes carbamylation and an Mg2+ cation stabilizes the resulting carbamate. The Na-acyl-lysinyl-aspratyl-aspartyl-glutamide (Lys-Asp-Asp-Glu, KDDE) peptide featured maximum capture at pH ≈ 10; a pH region too high for Mg2+ ions to remain in solution. This work aims to achieve pKa depression by introducing fluorine in the proximity of the lysine’s sidechain amine. A comparative analysis was made of butylamine, …

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Applied Geochemistry, Geochronology And Biostratigraphy: Case Studies From The 38th Parallel Structures In Missouri And Orange Basin, Offshore Western South Africa, Marissa Kay Spencer Jan 2023

Applied Geochemistry, Geochronology And Biostratigraphy: Case Studies From The 38th Parallel Structures In Missouri And Orange Basin, Offshore Western South Africa, Marissa Kay Spencer

Doctoral Dissertations

"The unique alignment of the Decaturville, Crooked Creek, and Weaubleau geological structures in central Missouri, three of nine known such structures along the 38th parallel in Illinois, Missouri, and Kansas, has puzzled geoscientists for decades. Research using palynology (palynomorphs and particulate organic matter) and radiometric dating of impact spherules were used to constrain age and a relationship between these enigmatic structures and infer their paleoenvironmental conditions. Novel melting damages, unique to impact, were documented in the palynomorphs in all the three structures. Early Ordovician acritarchs with melted processes correlate with 40Ar-39Ar stepwise heating age of impact spherules …

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Delivering Broadband Light Deep Into Diffusive Media, Rohin Mcintosh, Nicholas Bender, Alexey Yamilov, Arthur Goetschy, Chia Wei Hsu, Hasan Yilmaz, Hui Cao Jan 2023

Delivering Broadband Light Deep Into Diffusive Media, Rohin Mcintosh, Nicholas Bender, Alexey Yamilov, Arthur Goetschy, Chia Wei Hsu, Hasan Yilmaz, Hui Cao

Physics Faculty Research & Creative Works

Waves propagate diffusively through disordered media, such as biological tissue, clouds, and paint, due to random scattering. Recent advances in optical wavefront shaping techniques have enabled controlling coherent light propagation in multiple-scattering samples. We overcome wave diffusion to deliver optical energy into a target region of arbitrary size and shape anywhere inside a strong-scattering system. This is particularly important for applications such as photoacoustic microscopy and optogenetics, where light needs to be deposited deep into biological tissue. For monochromatic light, we previously introduced the deposition matrix (DM) Z(ω), which maps its input wavefront to the field distribution in the target …

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Cavity Induced Collective Behavior In The Polaritonic Ground State, Vasil Rokaj, Simeon I. Mistakidis, H. R. Sadeghpour Jan 2023

Cavity Induced Collective Behavior In The Polaritonic Ground State, Vasil Rokaj, Simeon I. Mistakidis, H. R. Sadeghpour

Physics Faculty Research & Creative Works

Cavity Quantum Electrodynamics Provides An Ideal Platform To Engineer And Control Light-Matter Interactions With Polariton Quasiparticles. In This Work, We Investigate Collective Phenomena In A System Of Many Particles In A Harmonic Trap Coupled To A Homogeneous Cavity Vacuum Field. The System Couples Collectively To The Cavity Field, Through Its Center Of Mass, And Collective Polariton States Emerge. The Cavity Field Mediates Pairwise Long-Range Interactions And Enhances The Effective Mass Of The Particles. This Leads To An Enhancement Of Localization In The Matter Ground State Density, Which Features A Maximum When Light And Matter Are On Resonance, And Demonstrates A …

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