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Articles 421 - 450 of 7311

Full-Text Articles in Physical Sciences and Mathematics

Dynamic Anomaly Threshold Based Malicious Behavior Detection In Lora-Assisted Industrial Iot, Subir Halder, Amrita Ghosal, Thomas Newe, Sajal K. Das Jan 2025

Dynamic Anomaly Threshold Based Malicious Behavior Detection In Lora-Assisted Industrial Iot, Subir Halder, Amrita Ghosal, Thomas Newe, Sajal K. Das

Computer Science Faculty Research & Creative Works

Smart manufacturing, powered by Long Range (LoRa) communication-assisted Industrial Internet of Things (IIoT), offers significant benefits but also incurs security concerns due to device compromise. In addition, various application scenarios and inherent heterogeneity of IIoT devices induce significant challenges for reliable behavior detection of compromised devices. While existing work is mostly on detecting compromised devices and there exists limited work on modeling system behavior, an open question is how to model the per-device behavior in an IIoT deployment and how behavioral changes can be automatically adapted in different scenarios. This paper proposes Misbehav, a novel self-learning device behavior anomaly detection …

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Securing Federated Learning From Distributed Backdoor Attacks Via Maximal Clique And Dynamic Reputation System, Priyesh Ranjan, Ashish Gupta, Sajal K. Das Jan 2025

Securing Federated Learning From Distributed Backdoor Attacks Via Maximal Clique And Dynamic Reputation System, Priyesh Ranjan, Ashish Gupta, Sajal K. Das

Computer Science Faculty Research & Creative Works

Federated Learning (FL) is a distributed learning paradigm that leverages the computational strength of local devices to collaboratively train a model. The clients train the local model on their respective devices and submit the weight updates to the server for aggregation. This paradigm allows the clients to experience diverse data without sharing their local data with other participants or the server. However, FL is susceptible to backdoor attackers that deliberately train the model on altered data, essentially trying to get favor on a specific subtask separated from the main task. In this work, we focus on powerful backdoor attackers who …

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Iterative Recommendations Based On Monte Carlo Sampling And Trust Estimation In Multi-Stage Vehicular Traffic Routing Games, Doris E.M. Brown, Venkata Sriram Siddhardh Nadendla, Sajal K. Das Jan 2025

Iterative Recommendations Based On Monte Carlo Sampling And Trust Estimation In Multi-Stage Vehicular Traffic Routing Games, Doris E.M. Brown, Venkata Sriram Siddhardh Nadendla, Sajal K. Das

Computer Science Faculty Research & Creative Works

The shortest-time route recommendations offered by modern navigation systems fuel selfish routing in urban vehicular traffic networks and are therefore one of the main reasons for the growth of congestion. In contrast, intelligent transportation systems (ITS) prefer to steer driver-vehicle systems (DVS) toward system-optimal route recommendations, which are primarily designed to mitigate network congestion. However, due to misalignment in motives, drivers may exhibit a lack of trust in the ITS. This paper models the interaction between a DVS and an ITS as a novel, multi-stage routing game where the DVS exhibits dynamics in its trust towards the recommendations of the …

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Smartsla: Enabling Quality Of Service In Blockchain-Enabled Iot Networks, Kyle M. Whitlatch, Asad Waqar Malik, Sanjay Madria Jan 2025

Smartsla: Enabling Quality Of Service In Blockchain-Enabled Iot Networks, Kyle M. Whitlatch, Asad Waqar Malik, Sanjay Madria

Computer Science Faculty Research & Creative Works

The significant advancement in Internet of Things (IoT) adoption has enabled Multi-access Edge Computing (MEC) to mitigate IoT sensors limited computational, transmission power constraints, and data distribution overhead. However, integrating MEC with the IoT ecosystem poses several challenges, resulting in integrity issues with the MECs, impacting their capacity to effectively serve users seeking data generated by IoT sensors. To address this, we propose SmartSLA, a blockchain based solution to ensure Quality of Service (QoS) from third party IoT devices. SmartSLA leverages the decentralized and immutable nature of blockchain to combat the shortcomings of MECs. Using smart contracts, we develop a …

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Icrop+: An Edge-Boosted Crop Disease Detection System Via Tinyml And Lora Communication, Xu Tao, Jackson Butcher, Simone Silvestri, Sajal K. Das Jan 2025

Icrop+: An Edge-Boosted Crop Disease Detection System Via Tinyml And Lora Communication, Xu Tao, Jackson Butcher, Simone Silvestri, Sajal K. Das

Computer Science Faculty Research & Creative Works

Crop disease detection is essential for controlling dis-ease spread and minimizing agricultural losses. In this demo, we present an implementation of iCrop+, an end-to-end autonomous crop disease detection system that integrates on-device AI, low-power long-range communication (LoRa), and server-based deep learning to create a hybrid architecture suitable for real-world deployment. The prototype efficiently balances local processing and remote inference through category-based optimization, adaptive classification, and intelligent data transmission, ensuring that only the most informative segments are transmitted to the server. Built on low-cost devices such as Raspberry Pi, LoRa transceiver modules, and a laptop, the demo showcases its potential for …

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Semi-Supervised Multimodal Multi-Instance Learning For Aortic Stenosis Diagnosis, Zhe Huang, Xiaowei Yu, Benjamin S. Wessler, Michael C. Hughes Jan 2025

Semi-Supervised Multimodal Multi-Instance Learning For Aortic Stenosis Diagnosis, Zhe Huang, Xiaowei Yu, Benjamin S. Wessler, Michael C. Hughes

Computer Science Faculty Research & Creative Works

Automated interpretation of ultrasound imaging of the heart (echocardiograms) could improve the detection and treatment of aortic stenosis (AS), a deadly heart disease. However, existing deep learning pipelines for assessing AS from echocardiograms have two key limitations. First, most methods rely on limited 2D cineloops, thereby ignoring widely available Spectral Doppler imaging that contains important complementary information about pressure gradients and blood flow abnormalities associated with AS. Second, obtaining labeled data is difficult. There are often far more unlabeled echocardiogram recordings available, but these remain underutilized by existing methods. To overcome these limitations, we introduce Semi-supervised Multimodal Multiple-Instance Learning (SMMIL), …

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Brain-Adapter: Enhancing Neurological Disorder Analysis With Adapter-Tuning Multimodal Large Language Models, Jing Zhang, Xiaowei Yu, Yanjun Lyu, Lu Zhang, Tong Chen, Chao Cao, Yan Zhuang, Minheng Chen, Tianming Liu, Dajiang Zhu Jan 2025

Brain-Adapter: Enhancing Neurological Disorder Analysis With Adapter-Tuning Multimodal Large Language Models, Jing Zhang, Xiaowei Yu, Yanjun Lyu, Lu Zhang, Tong Chen, Chao Cao, Yan Zhuang, Minheng Chen, Tianming Liu, Dajiang Zhu

Computer Science Faculty Research & Creative Works

Understanding brain disorders is crucial for accurate clinical diagnosis and treatment. Recent advances in Multimodal Large Language Models (MLLMs) offer a promising approach to interpreting medical images with the support of text descriptions. However, previous research has primarily focused on 2D medical images, leaving richer spatial information of 3D images under-explored, and single-modality-based methods are limited by overlooking the critical clinical information contained in other modalities. To address this issue, this paper proposes Brain-Adapter, a novel approach that incorporates an extra bottleneck layer to learn new knowledge and instill it into the original pre-trained knowledge. The major idea is to …

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Classiffication Of Mild Cognitive Impairment Based On Dynamic Functional Connectivity Using Spatio-Temporal Transformer, Jing Zhang, Yanjun Lyu, Xiaowei Yu, Lu Zhang, Chao Cao, Tong Chen, Minheng Chen, Yan Zhuang, Tianming Liu, Dajiang Zhu Jan 2025

Classiffication Of Mild Cognitive Impairment Based On Dynamic Functional Connectivity Using Spatio-Temporal Transformer, Jing Zhang, Yanjun Lyu, Xiaowei Yu, Lu Zhang, Chao Cao, Tong Chen, Minheng Chen, Yan Zhuang, Tianming Liu, Dajiang Zhu

Computer Science Faculty Research & Creative Works

Dynamic functional connectivity (dFC) using resting-state functional magnetic resonance imaging (rs-fMRI) is an advanced technique for capturing the dynamic changes of neural activities and can be very useful in the studies of brain diseases such as Alzheimer's disease (AD). Yet, existing studies have not fully leveraged the sequential information embedded within dFC that can potentially provide valuable information when identifying brain conditions. In this paper, we propose a novel framework that jointly learns the embedding of both spatial and temporal information within dFC based on the transformer architecture. Specifically, we first construct dFC networks from rs-fMRI data through a sliding …

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Exploring The Trade-Offs: Unified Large Language Models Vs Local Fine-Tuned Models For Highly-Specific Radiology Nli Task, Zihao Wu, Lu Zhang, Chao Cao, Xiaowei Yu, Zhengliang Liu, Lin Zhao, Yiwei Li, Haixing Dai, Chong Ma, Gang Li, Wei Liu, Quanzheng Li, Dinggang Shen, Xiang Li, Dajiang Zhu, Tianming Liu Jan 2025

Exploring The Trade-Offs: Unified Large Language Models Vs Local Fine-Tuned Models For Highly-Specific Radiology Nli Task, Zihao Wu, Lu Zhang, Chao Cao, Xiaowei Yu, Zhengliang Liu, Lin Zhao, Yiwei Li, Haixing Dai, Chong Ma, Gang Li, Wei Liu, Quanzheng Li, Dinggang Shen, Xiang Li, Dajiang Zhu, Tianming Liu

Computer Science Faculty Research & Creative Works

Recently, ChatGPT and GPT-4 have emerged and gained immense global attention due to their unparalleled performance in language processing. Despite demonstrating impressive capability in various open-domain tasks, their adequacy in highly specific fields like radiology remains untested. Radiology presents unique linguistic phenomena distinct from open-domain data due to its specificity and complexity. Assessing the performance of large language models (LLMs) in such specific domains is crucial not only for a thorough evaluation of their overall performance but also for providing valuable insights into future model design directions: whether model design should be generic or domain specific. To this end, in …

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Reindsplit: Reinforced Dynamic Split Learning For Pest Recognition In Precision Agriculture, Vishesh Kumar Tanwar, Soumik Sarkar, Asheesh K. Singh, Sajal K. Das Jan 2025

Reindsplit: Reinforced Dynamic Split Learning For Pest Recognition In Precision Agriculture, Vishesh Kumar Tanwar, Soumik Sarkar, Asheesh K. Singh, Sajal K. Das

Computer Science Faculty Research & Creative Works

To empower precision agriculture through distributed machine learning (DML), split learning (SL) has emerged as a promising paradigm, partitioning deep neural networks (DNNs) between edge devices and servers to reduce computational burdens and preserve data privacy. However, conventional SL frameworks' one-split-fits-all strategy is a critical limitation in agricultural ecosystems where edge insect monitoring devices exhibit vast heterogeneity in computational power, energy constraints, and connectivity. This leads to straggler bottlenecks, inefficient resource utilization, and compromised model performance. Bridging this gap, we introduce ReinDSplit, a novel reinforcement learning (RL)-driven framework that dynamically tailors DNN split points for each device, optimizing efficiency without …

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Fuzzy-Based Deep Reinforcement Learning For Suicidal Ideation Detection In Online Social Networks, Greeshma Lingam, Sajal K. Das Jan 2025

Fuzzy-Based Deep Reinforcement Learning For Suicidal Ideation Detection In Online Social Networks, Greeshma Lingam, Sajal K. Das

Computer Science Faculty Research & Creative Works

Suicidal ideation is a major psychological problem, and preventing this social risk is recognized as an important research topic. In reality, there can be several reasons why a person experiences suicidal ideation. Each individual can express views, emotions, and several types of symptoms related to suicidal ideation on the most popular social media platforms. In online social networks (OSNs), identification of suicidal ideation is one of the major challenging tasks. Existing studies have shown that the delay in understanding and identifying various risk factors can cause the suicidal event to occur. Due to the scarcity of data and understanding, the …

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When Federated Learning Meets Quantum Computing: Survey And Research Opportunities, Aakar Mathur, Ashish Gupta, Sajal K. Das Jan 2025

When Federated Learning Meets Quantum Computing: Survey And Research Opportunities, Aakar Mathur, Ashish Gupta, Sajal K. Das

Computer Science Faculty Research & Creative Works

Quantum Federated Learning (QFL) is an emerging field that harnesses advances in Quantum Computing (QC) to improve the scalability and efficiency of decentralized Federated Learning (FL) models. This paper provides a systematic and comprehensive survey of the emerging problems and solutions when FL meets QC, from research protocol to a novel taxonomy, particularly focusing on both quantum and federated limitations, such as their architectures, Noisy Intermediate Scale Quantum (NISQ) devices, and privacy preservation, so on. With the introduction of two novel metrics, qubit utilization efficiency and quantum model training strategy, we present a thorough analysis of the current status of …

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Circa: A Framework For Collaborative Identification Of Root Cause Analysis In Iot Microservices, Xingguo Jiang, Hong Luo, Yan Sun, Sajal K. Das Jan 2025

Circa: A Framework For Collaborative Identification Of Root Cause Analysis In Iot Microservices, Xingguo Jiang, Hong Luo, Yan Sun, Sajal K. Das

Computer Science Faculty Research & Creative Works

With continuous growth of IoT applications, service failures are quite inevitable. Due to the complexity and dynamics of IoT services, the root cause analysis (RCA) following an alert can assist in quickly resolving the possible faults. However, the time scales of metrics (e.g., CPU utilization, memory usage) generated by microservices and the dynamic topologies generated by calls between the Application Program Interfaces (APIs) are different. Moreover, the status of devices is an important aspect of RCA in IoT. All these make it extremely challenging to learn failure features of microservice metrics and API calls. Therefore, we propose a novel framework …

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Mgco: Mobility-Aware Generative Computation Offloading In Edge-Cloud Systems., Aswini Ghosh, Nelson Sharma, Shivendu Mishra, Rajiv Misra, Sajal K. Das Jan 2025

Mgco: Mobility-Aware Generative Computation Offloading In Edge-Cloud Systems., Aswini Ghosh, Nelson Sharma, Shivendu Mishra, Rajiv Misra, Sajal K. Das

Computer Science Faculty Research & Creative Works

Mobility introduces significant challenges for optimal computation offloading, latency minimization, and efficient re source utilization in multi-access edge computing (MEC) systems. A key difficulty lies in leveraging real user trajectories to jointly optimize horizontal (inter-edge) and vertical (edge-to-cloud) task offloading decisions. This paper proposes a two-dimensional offloading scheme for a multi-layer edge–cloud architecture that enables collaborative task execution among resource-constrained edge nodes under mobility conditions. We present MGCO (Mobility-Aware Generative Computation Offloading), a generative AI–driven Transformer-based sequence-to-sequence Deep Q-Network (s2s-DQN) framework that learns from real-time trajectory data to anticipate user movement and optimize task placement dynamically. The Transformer architecture is …

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Message From Workshop Chairs, Sushil K. Prasad, Srishti Srivastava, Satish Puri, David Bunde, Shubbhi Taneja, Buddhi Ashan Mallika Kankanamalage Jan 2025

Message From Workshop Chairs, Sushil K. Prasad, Srishti Srivastava, Satish Puri, David Bunde, Shubbhi Taneja, Buddhi Ashan Mallika Kankanamalage

Computer Science Faculty Research & Creative Works

No abstract provided.

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Real-Time Testbed For Studying Cyberattacks And Defense In Der-Integrated Smart Inverter Systems, M. Maliha, A. Oluyomi, M. Booge, S. Bhattacharjee, N. Braasch, P. Gomez, Sajal K. Das Jan 2025

Real-Time Testbed For Studying Cyberattacks And Defense In Der-Integrated Smart Inverter Systems, M. Maliha, A. Oluyomi, M. Booge, S. Bhattacharjee, N. Braasch, P. Gomez, Sajal K. Das

Computer Science Faculty Research & Creative Works

In this paper, we propose a Hardware-in-the-Loop (HIL) simulation testbed suitable for the implementation and testing of realistic cyberattacks on grid-tied smart inverter systems integrated with Distributed Energy Resources (DER) that use the Distributed Network Protocol-3 (DNP3) protocol for communications between grid components. Specifically, our testbed combines a Real-Time Digital Simulator (RTDS) NovaCor device, outfitted with GNETx2 network interface cards, a grid-tied DER topology implemented via the RTDS software package RSCAD, and a custom virtual network that emulates a man-in-the-middle (MITM) attacker. The MITM attacker captures DNP3 traffic and falsifies telemetry data in DNP3 packets to trigger unwarranted commands from …

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Grace-Fl: Green Resource-Aware Communication-Efficient Federated Learning, Dipanwita Thakur, Antonella Guzzo, Giancarlo Fortino, Sajal K. Das Jan 2025

Grace-Fl: Green Resource-Aware Communication-Efficient Federated Learning, Dipanwita Thakur, Antonella Guzzo, Giancarlo Fortino, Sajal K. Das

Computer Science Faculty Research & Creative Works

Federated Learning (FL) enables collaborative model training across distributed clients while preserving data privacy, but its deployment on resource-constrained devices is hindered by high communication overhead, inefficient energy usage, and poor convergence under non-IID data distributions. To address these challenges, we propose GRACE-FL: a Green Resource-Aware Communication-Efficient Federated Learning framework that explicitly incorporates device energy capacity into training. Each client adapts its learning rate, number of local epochs, and gradient quantization bit-width based on its available energy, allowing high-capacity devices to sustain more intensive training while low-capacity devices operate with lighter configurations. A novel energy-weighted aggregation strategy ensures that clients …

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Cold Atmospheric Plasma Induced Degradation Of Organophosphate Pesticides On Kevlar Swatches, Ta Chun Lin, Victor Somtochukwu Mbanugo, Boluwatife Stephen Ojo, Yue-Wern Huang, Marek Locmelis, Frank Daoru Han Jan 2025

Cold Atmospheric Plasma Induced Degradation Of Organophosphate Pesticides On Kevlar Swatches, Ta Chun Lin, Victor Somtochukwu Mbanugo, Boluwatife Stephen Ojo, Yue-Wern Huang, Marek Locmelis, Frank Daoru Han

Biological Sciences Faculty Research & Creative Works

Cold atmospheric plasma (CAP) was evaluated for degrading organophosphate pesticide (OP) residues (acephate, malathion, and dimethoate) from Kevlar fabrics. Fourier transform-Infrared (FTIR) spectroscopy, scanning electron microscope (SEM) imaging and tensile strength testing confirmed that CAP treatment preserved Kevlar's structural integrity and mechanical properties. Results show degradation efficiency increased with higher power, shorter discharge gaps, and longer exposure duration. Hyperspectral imaging supported the detection of plasma-induced spectral changes, reinforcing the presence of reactive species. The strong oxidative potential of CAP facilitated the rapid breakdown of OPs into nontoxic byproducts. These findings demonstrate the potential of CAP as a portable, energy-efficient solution …

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Metal-Free Photoredox Catalysis For The S-Trifluoromethylation Of Thiols, Raheemat Rafiu, Puspa Aryal, V. Prakash Reddy Jan 2025

Metal-Free Photoredox Catalysis For The S-Trifluoromethylation Of Thiols, Raheemat Rafiu, Puspa Aryal, V. Prakash Reddy

Chemistry Faculty Research & Creative Works

The S-trifluoromethylation of thiols is accomplished using a simple and cost-effective organic catalyst (diacetyl) along with a bench-stable and environmentally friendly trifluoro methylating reagent (Langloi's reagent). Under optimized conditions (2.5 equivalents of Langlois reagent, Blue LED irradiation, 48-h reaction time at room temperature), the reaction yielded up to 81% S-trifluoro methylated product. This method's high yields, compatibility with a broad substrate scope (aliphatic, heteroaromatic, and aromatic thiols), and environmentally friendly conditions demonstrate its potential for broader synthetic applications. In contrast to traditional methods that rely on organometallic catalysts and environmentally hazardous reagents, this novel photoredox catalysis method offers a more …

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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 Jan 2025

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 …

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Formation Of Hydrocarbons And Carbon Oxides In Mxene Reactions With Water Under Varying Oxidative Conditions, Shuohan Huang, Guanglei Xiang, Vadym Mochalin Jan 2025

Formation Of Hydrocarbons And Carbon Oxides In Mxene Reactions With Water Under Varying Oxidative Conditions, Shuohan Huang, Guanglei Xiang, Vadym Mochalin

Chemistry Faculty Research & Creative Works

Titanium carbide / carbonitride MXenes have garnered significant attention due to their remarkable properties, versatile solution processability, and broad range of potential applications. However, when exposed to the environment, MXenes are susceptible to degradation, which ultimately leads to the formation of metal oxides, a process that may be regarded as either disadvantageous or beneficial, depending on the application of a MXene and our knowledge about the underlying mechanisms. Therefore, it is very important to understand the reactivity of MXenes in different environments and conditions. Although researchers have made efforts to understand MXene degradation in air and water, our knowledge of …

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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 Jan 2025

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 …

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Synthesis And Characterization Of Free Radical Scavenging Dendrimer Nanogels Via Cross-Linking Reaction-Enabled Flash Nanoprecipitation, Lin Qi, Da Huang, Huari Kou, Anna Chernatynskaya, Nuran Ercal, Hu Yang Jan 2025

Synthesis And Characterization Of Free Radical Scavenging Dendrimer Nanogels Via Cross-Linking Reaction-Enabled Flash Nanoprecipitation, Lin Qi, Da Huang, Huari Kou, Anna Chernatynskaya, Nuran Ercal, Hu Yang

Chemistry Faculty Research & Creative Works

This work reports the development and evaluation of dendrimer-based nanogels based on Poly amidoamine (PAMAM) dendrimer generation 5, engineered to act as a carrier with reactive oxygen species (ROS)-scavenging capabilities. We developed a cross-linking reaction-enabled flash nanoprecipitation method in which the cross-linking reaction occurs during the flash nanoprecipitation process to form a cross-linked nanostructure. Using this approach, an N-hydroxy succinimide (NHS)-functionalized ROS-responsive thioketal cross-linker (TK-NHS) was synthesized and utilized to cross-link DAB-core PAMAM dendrimer G5, resulting in the formation of G5-TK nanogels. The resulting nanogels were characterized using dynamic light scattering and transmission electron microscopy, and their cytocompatibility, irritancy, cellular …

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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 Jan 2025

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 …

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Unveiling Pseudocapacitance: A Kinetic Treatment Of The Pseudocapacitive Biosensor, Rokas Gerulskis, Egor Baiarashov, Maryam Karimi, Wassim El Housseini, Shelley D. Minteer Jan 2025

Unveiling Pseudocapacitance: A Kinetic Treatment Of The Pseudocapacitive Biosensor, Rokas Gerulskis, Egor Baiarashov, Maryam Karimi, Wassim El Housseini, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

A kinetic framework is introduced for a pseudocapacitive potentiometric biosensor. Mathematical derivation and kinetic modeling demonstrate that experimentally observed linearity in analyte-OCP response arises from a dynamic equilibrium between competing redox reactions on a single electrode. This system can be expanded to develop a new generation of biosensors.

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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 Jan 2025

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.

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Electrochemically Active Molybdenum Phosphate With Open-Framework Structure, Sutapa Bhattacharya, Milad Aghayi-Anaraki, Nikolay Gerasimchuk, Steven P. Kelley, Amitava Choudhury Jan 2025

Electrochemically Active Molybdenum Phosphate With Open-Framework Structure, Sutapa Bhattacharya, Milad Aghayi-Anaraki, Nikolay Gerasimchuk, Steven P. Kelley, Amitava Choudhury

Chemistry Faculty Research & Creative Works

Somewhat less investigated, lithium ion containing molybdenum phosphate compounds are synthesized via simple template free hydrothermal method. Single-crystal X-ray diffraction (SCXRD) study reveals that the compounds Li0.89Mo2O1.89F0.11(PO4)2(H2PO4)·xH2O (x ≈1) and Li3Mo2O2(PO4)3·xH2O (x ≈1) crystallize in monoclinic C2/m and C2/c space group, respectively. The structures are built of alternate corner-sharing of MoO6 octahedra and PO4 tetrahedra forming layers, which are pillared by phosphate groups creating a 3D framework with channels. These …

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Atomistic Mechanisms Of Ti3alc2 Etching: Oxidation, Surface Stability, And Selectivity, Valentina Nesterova, Ana Maria Stratulat, Walter Malone, Vadym Mochalin, Majid Beidaghi, Konstantin Klyukin Jan 2025

Atomistic Mechanisms Of Ti3alc2 Etching: Oxidation, Surface Stability, And Selectivity, Valentina Nesterova, Ana Maria Stratulat, Walter Malone, Vadym Mochalin, Majid Beidaghi, Konstantin Klyukin

Chemistry Faculty Research & Creative Works

Mechanisms governing MAX-phase etching set the properties and stability of resulting MXenes, yet the details of this complex process remain poorly understood. Combining thermodynamic analysis of surface chemistries with ab initio molecular dynamics and enhanced free-energy sampling, we directly model elementary steps at the MAX/etching solution interface. We find that purely thermodynamic analysis overestimates etching selectivity, which is governed by the kinetics of elementary reaction steps. Our calculations reveal that initial exposure to water drives localized, thermodynamically favored edge oxidation that seeds MXene-like terminations into the uppermost layers of Ti3AlC2 with oxygen occupying the interlayer space between …

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Thermo-Rheological And Tribological Properties Of Low- And High-Oleic Vegetable Oils As Sustainable Bio-Based Lubricants, Abiodun Saka, Tobechukwu K. Abor, Anthony C. Okafor, Monday U. Okoronkwo Jan 2025

Thermo-Rheological And Tribological Properties Of Low- And High-Oleic Vegetable Oils As Sustainable Bio-Based Lubricants, Abiodun Saka, Tobechukwu K. Abor, Anthony C. Okafor, Monday U. Okoronkwo

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Vegetable oil-based lubricants have attracted increased research attention in recent decades as sustainable alternatives to conventional petroleum-based lubricants in metal machining. However, more studies are required to fully elucidate the thermo-rheological and tribological properties. This study presents an investigation of the thermo-rheological and tribological properties of different vegetable oils, including low- and high-oleic soybean oil, high-oleic sunflower, safflower, and canola oils. The lubricity, and evolution of viscosity and thermodynamic properties as a function of temperature were investigated to obtain important parameters including the viscosity index, flow behavior index, flow activation energy, specific heat capacity, thermal conductivity, coefficient of friction, contact …

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Hyper B-Ary Representations Of A Number, Mingway Wang Jan 2025

Hyper B-Ary Representations Of A Number, Mingway Wang

Masters Theses

In this work, we summarize combinatorial, analytical, and computational properties of Stern's diatomic sequence, and do the same for a generalization of a combinatorial property of this sequence to higher bases. We then construct special ``bit conversion'' functions $g_{b}$ that allows us to find a semi-explicit formula for the generalized sequences. Lastly, we analyze some of the properties of these $g_{b}$ functions.

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