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Articles 61 - 90 of 3959
Full-Text Articles in Physical Sciences and Mathematics
Integrating Knowledge Graphs With Large Language Models For Natural Language Querying, Rakesh Kandula
Integrating Knowledge Graphs With Large Language Models For Natural Language Querying, Rakesh Kandula
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This research explores the integration of knowledge graphs with large language models that have already been trained on a vast pool of unstructured text data. Large language models trained on this type of data have a tendency to hallucinate and produce factually inaccurate results. This behavior is primarily due to the data being trained is unstructured and huge text corpus, and large language model uses predictive text analysis methods to obtain a response. These issues can be addressed by applying Retrieval Augmented Generation and Fine-tuning to large language models, employing an underlying domainspecific knowledge graph. Integrating knowledge graph and large …
Prediction Interpretations Of Ensemble Models In Chronic Kidney Disease Using Explainable Ai, K M Tawsik Jawad
Prediction Interpretations Of Ensemble Models In Chronic Kidney Disease Using Explainable Ai, K M Tawsik Jawad
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Chronic Kidney Disease (CKD) poses significant health and financial threat to millions of patients all around the world. The irreversible nature of this disease not just leads to comorbid diseases like Diabetes Mellitus, Hypertension, Anemia, Bone Disease, Neurological Implants etc. It can permanently damage the kidney by progressing to Acute Kidney Injury (AKI) or End Stage Renal Diseases (ESRD). The risk factors of CKD become more dangerous as patients suffering from it have little to no idea about the presence of CKD in their body until it takes the shape of AKI or ESRD. There are severe economic burdens for …
A Spectrophotometric Determination Of Strontium Complexation With Methylthymol Blue, Adebayo Comlan Djanman
A Spectrophotometric Determination Of Strontium Complexation With Methylthymol Blue, Adebayo Comlan Djanman
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This study examines the complexation behavior of methylthymol blue (MTB) with strontium, particularly focusing on its application in addressing environmental concerns related to radiotoxic 90Sr. Using spectrophotometric techniques, the binding interactions were analyzed at pH = 7.50, 9.60, and 12.20. Results indicate that MTB forms a 1:1 complex with strontium at pH = 7.50, while at pH = 9.60 and 12.20 were assumed to influence complexation due to changes in ligand deprotonation and electrostatic interactions. Equilibrium constants (K1) = 22 (± 2) and molar absorptivities, ε1 = 6.3 x 10^3 (± 0.0008) L·mol⁻¹·cm⁻¹, and ε2 = 9.73 x (± 0.2)10^3 …
Investigation Of Ion Pairing And Clustering Leading To The Nucleation Of Fluorite Using Ion Selective Electrode Potentiometry, Courtney L. Crone
Investigation Of Ion Pairing And Clustering Leading To The Nucleation Of Fluorite Using Ion Selective Electrode Potentiometry, Courtney L. Crone
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Previously, mineral nucleation was described by Classical Nucleation Theory (CNT), a theory based on the thermodynamic properties of bulk materials. However, an alternative model, known as the Prenucleation Cluster Pathway, has been increasingly used to describe nucleation of minerals. This model considers the presence of thermodynamically stable ion clusters known as “prenucleation clusters” (PNCs). In the present research, the nucleation mechanism of calcium fluoride was investigated to identify evidence of PNCs by means of the ion-selective electrode (ISE) method, where a CaCl2 solution was titrated into a NaF solution while investigating the effects of saturation level and the aqueous ratio …
An Ml-Assisted Golden-Free Hardware Trojan Localization And Detection Approach For Trusted Microelectronics, Ashutosh Ghimire
An Ml-Assisted Golden-Free Hardware Trojan Localization And Detection Approach For Trusted Microelectronics, Ashutosh Ghimire
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Hardware Trojans are malicious circuits, hidden in integrated circuits (ICs) which pose a significant threat to security. Detection of hardware Trojans is important to build trust, verify, and make the semiconductor ICs process secure. The existing hardware Trojan detection methods are generally destructive, require intricate comparisons, or require a long time for reverse engineering. In the initial phase of this study, the substitution of supervised hardware Trojan detection methods in ASICs chips is explored with unsupervised approaches, thereby eliminating the dependence on golden references. The Trojan detection uses a ring oscillator (RO) based on NAND as the power monitor. Frequency …
Understanding Impact Of Graph Structure On Knowledge Graph Embedding, Brandon Dave
Understanding Impact Of Graph Structure On Knowledge Graph Embedding, Brandon Dave
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The effectiveness of a deployed knowledge graph is commonly evaluated with defined use-cases from domain experts. This poses challenges during the development cycle in determining how to represent data. Developers of a knowledge graph can optionally include semantics into a knowledge graph by abstracting the data representation in such a way that mirrors information as it exists in the real world. Consequently, the abstraction is represented by additional layers, resulting in performant differences in knowledge graph embedding; such as, the embedded model's ability to infer facts between entities through link predictions. This thesis presents a comprehensive analysis of the performance …
Seismic Refraction Mapping Of The Pre-Glacial Teays River Valley In West Central Ohio Using A Seismic Reflection Dataset, Matthew L. Klempp Ii
Seismic Refraction Mapping Of The Pre-Glacial Teays River Valley In West Central Ohio Using A Seismic Reflection Dataset, Matthew L. Klempp Ii
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The Teays River Valley is an ancient river valley system that existed before the Pleistocene Ice Age and spanned present-day Illinois, Indiana, Ohio, West Virginia, and Virginia. During the Pleistocene Ice Age, the Teays River Valley was buried by advancing continental glaciers and meltwater throughout most of its length. Due to the Teays’ average width of roughly 2 miles and burial depth of approximately 200 meters (656 feet), the Ohio Geological Survey has been pursuing geophysical methods to map the location and depth of the Teays River Valley in Ohio. The present study is a refraction analysis using the first …
Ai-Enabled Hardware Security Approach For Aging Classification And Manufacturer Identification Of Sram Pufs, Harshdeep Singh
Ai-Enabled Hardware Security Approach For Aging Classification And Manufacturer Identification Of Sram Pufs, Harshdeep Singh
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Semiconductor microelectronics integrated circuits (ICs) are increasingly integrated into modern life-critical applications, from intelligent infrastructure and consumer electronics to the Internet of Things (IoT) and advanced military and medical systems. Unfortunately, these applications are vulnerable to new hardware security attacks, including microelectronics counterfeits and hardware modification attacks. Physical Unclonable Functions (PUFs) are state-of-the-art hardware security solutions that utilize process variations of integrated circuits for device authentication, secret key generation, and microelectronics counterfeit detection. The negative impact of aging on Static Random Access Memory Physical Unclonable Functions (SRAM PUFs) has significant consequences for microelectronics authentication, security, and reliability. This research thoroughly …
Ml-Assisted Side Channel Security Approaches For Hardware Trojan Detection And Puf Modeling Attacks, Niraj Prasad Bhatta
Ml-Assisted Side Channel Security Approaches For Hardware Trojan Detection And Puf Modeling Attacks, Niraj Prasad Bhatta
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Hardware components are becoming prone to threats with increasing technological advances. Malicious modifications to such components are increasing and are known as hardware Trojans. Traditional approaches rely on functional assessments and are not sufficient to detect such malicious actions of Trojans. Machine learning (ML) assisted techniques play a vital role in the overall detection and improvement of Trojan. Our novel approach using various ML models brings an improvement in hardware Trojan identification with power signal side channel analysis. This study brings a paradigm shift in the improvement of Trojan detection in integrated circuits (ICs). In addition to this, our further …
Effects Of Geometric Isomerism On Benzothiazole-Carbazole Based Tadf Emitters In Poly(Arylene Ether)S, Grace Olive
Effects Of Geometric Isomerism On Benzothiazole-Carbazole Based Tadf Emitters In Poly(Arylene Ether)S, Grace Olive
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Thermally activated delayed fluorescence (TADF) small molecules have dominated the literature for their use in OLED devices. The use of TADF polymers has been employed to correct for processing issues that small molecules face, providing increased thermal stability and supportive electronic structures. A TADF chromophore based on a 2-(2,6-difluorophenyl)-benzothiazole-carbazole donor-acceptor pair was synthesized via a copper (I) catalyzed reaction. The chromophore exhibited peak absorption at 340 nm and emission at 477 nm. The resulting chromophore was incorporated into a poly(arylene ether) (PAE) backbone via nucleophilic aromatic substitution (NAS) with 4,4’-biphenol, 4,4’-difluorodiphenyl sulfone, and 2-(2,6-difluorophenyl)-benzothiazole as comonomers. UV/Vis analysis of the …
Distribution And Fate Of Selected Non-Point Source Pollutants In The Dayton Streams And Tributaries: Effect Of Land Use In An Urban Watershed, Smriti Bastakoti
Distribution And Fate Of Selected Non-Point Source Pollutants In The Dayton Streams And Tributaries: Effect Of Land Use In An Urban Watershed, Smriti Bastakoti
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This study investigates the distribution of water pollutants in the urban and suburban watershed (Beavercreek Sub-watershed (BCS) and Little Beavercreek Sub-watershed (LBS)) of Dayton, Ohio USA focusing on the relationship between water quality and land use types based on 2021 land use maps obtained from MRLC. These watersheds are home for aquatic life and regulate the flow of surface water and recharge groundwater so, it is crucial to maintain good water quality by balancing urbanization and farmland within these two watersheds. We analyzed chloride, nitrate, and sulfate using ion chromatography (IC) and orthophosphate using UV/Vis Spectrophotometry. Additionally, three pesticides (Atrazine, …
Multi-Semantic-Stage Neural Networks For Robust And Interpretable Deep Learning, Christopher J. Menart
Multi-Semantic-Stage Neural Networks For Robust And Interpretable Deep Learning, Christopher J. Menart
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Deep neural networks have great representational power. However, most deep neural nets today optimize directly for performance on a single task defined only by labeled training data. This excludes potential sources of knowledge and ways of learning which could improve their performance, and address challenges, such as explainability, which are pressing to the field. We propose a framework for neural network architecture which generalizes it to a graph of many semantically-meaningful variables. We call it the Multi-Semantic-Stage Neural Network (MSSNN). An MSSNN models its domain as a web of conditional probabilities, i.e. a collection of inter-related tasks which can learn …
Electrochemical-Thermal Model Of A Lithium-Ion Battery, Paul Kalungi
Electrochemical-Thermal Model Of A Lithium-Ion Battery, Paul Kalungi
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Lithium-ion batteries are an integral component of energy storage systems for renewable energy applications owing to their high energy density. Extensive research has therefore been carried out, utilizing both experimental and computational methods, to aid in a deeper understanding of lithium-ion batteries. Challenges related to efficiency, safety and thermal management persist, particularly during high current draw, extreme temperature conditions and extreme dynamic current operation such as in electric vehicles. This thesis work presents an electrochemical-thermal model of a lithium-ion battery that simulates and analyzes the variation of electrical behavior, chemical behavior and thermal behavior. The electrochemical model is developed by …
Pneumonia Detection With Limited And Imbalanced Data Using Energy-Based Out-Of-Distribution Technique, Jasbin Karki
Pneumonia Detection With Limited And Imbalanced Data Using Energy-Based Out-Of-Distribution Technique, Jasbin Karki
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The automated detection of pneumonia through chest X-ray presents a critical challenge in medical diagnostics, particularly due to the restrictions of limited and imbalanced chest X-ray data for training AI models. Traditional methods that depend on softmax confidence scores can be overconfident even when generating erroneous outputs especially when they are processing completely new inputs, leading to unreliable diagnostic results. This research addresses challenges in AI models which aim to develop a robust pneumonia detection system using an Energy-Based Out-of-Distribution (OOD) technique that can work effectively even with limited and imbalanced data. The study focused on creating a more reliable …
Test-Time Backdoor Attack Using Universal Perturbation, Jesse Alexander Smith
Test-Time Backdoor Attack Using Universal Perturbation, Jesse Alexander Smith
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The rapid growth and widespread reliance on machine learning (ML) systems across critical applications such as healthcare, autonomous driving, and cybersecurity have un- derscored their transformative potential and heightened their susceptibility to adversarial attacks and vulnerabilities. This thesis investigates vulnerabilities in ML models, focusing on backdoor attacks, including naive backdoor attack, feature collision backdoor attack, hidden trigger backdoor attack, and test-time backdoor attack using universal perturbation technique. These methodologies demonstrate how adversaries can automate and conceal malicious behaviors to achieve specific objectives, posing significant challenges to ML model integrity and trustworthiness. The research provides a comprehensive analysis of the theoretical …
Semantics-Aware Text-Guided Aerial Image Synthesis By Feature Augmented Diffusion Models, Douglas J. Townsell
Semantics-Aware Text-Guided Aerial Image Synthesis By Feature Augmented Diffusion Models, Douglas J. Townsell
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Aerial imagery provides crucial insights for various fields, including remote monitoring, environmental assessment, and autonomous navigation. However, the availability of aerial image datasets is limited due to privacy concerns and imbalanced data distribution, impeding the development of robust deep learning models. While recent text-guided generative models have shown promise in synthesizing high-quality images, they fall short in handling the unique challenges of aerial imagery, including densely packed objects, intricate spatial relationships, and the absence of paired text-aerial image datasets. To tackle these limitations, we propose STARS, a groundbreaking framework for Semantic-aware Text-guided Aerial image Refinement and Synthesis. STARS introduces a …
Development Of Sulfur-Based N-Heterocyclic Carbenes And Their Potential Energy Applications, Kalpana Sampath
Development Of Sulfur-Based N-Heterocyclic Carbenes And Their Potential Energy Applications, Kalpana Sampath
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N-heterocyclic carbenes (NHCs), a characteristic 5-membered ring structure, contain a carbene carbon and at least one nitrogen atom. The presence of nitrogen atoms in the cyclic structure has two effects on its electronic structure: it withdraws σ-electrons and donates π-electrons to the carbene carbon, significantly enhancing the electronic richness and stability of the carbene center. Incorporating heteroatoms like sulfur, oxygen, or phosphorus into the NHC framework has paved the way for advanced developments in their structural properties. The incorporation of additional aromatic ring/heteroatom into NHC offers novel pathways for functionalization, ultimately broadening its scope of potential applications. The primary goal …
Functionalized 1,4-Naphthoquinone-Annulated N-Heterocyclic Carbenes For Biomedical Applications, Dilsha Samanali Wickramasinghe
Functionalized 1,4-Naphthoquinone-Annulated N-Heterocyclic Carbenes For Biomedical Applications, Dilsha Samanali Wickramasinghe
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Gold has long been recognized for its medicinal applications, dating back centuries. The use of N-heterocyclic carbenes (NHCs), stable, tunable ligands, has revolutionized the development of metal complexes, particularly those involving gold. Among these, Au-NHC complexes have shown significant promise in treating various diseases, especially arthritis and cancer. More recently, our research has focused on synthesizing dual-targeting naphthoquinone-annulated NHC-based gold(I) complexes, which have demonstrated impressive therapeutic potential in cancer treatment. This emphasizes the growing importance of gold-based complexes in developing more selective and effective cancer therapies. By strategically tuning the electronic and steric properties of these complexes, we have explored …
Graph-Centric Bot Detection: Addressing Extreme Data Imbalances, Heterophily, And Scarcity, Bradley T. Ashmore
Graph-Centric Bot Detection: Addressing Extreme Data Imbalances, Heterophily, And Scarcity, Bradley T. Ashmore
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The digital landscape is ever-evolving. In recent years the amount of bot traffic, traffic generated by autonomous applications over the internet has increased significantly. Many bots perform useful and needed functions, however, malicious bots are known sources of both common and emerging security threats. Denial-of-Services (DoS), information theft, and credential stuffing have all been conducted by malicious software running on unknowingly infected machines. The dichotomy of useful bots operating in the same networks as malicious bots combined with novel bot attacks and an ever-increasing number of personal devices connecting to the Internet drives the need for continued advancement of malicious …
A Trusted Adversarial Ml Countermeasure Approach For Secure And Resilient Ai-Driven Hardware Trojan Detection, Mohammed G M Alkurdi
A Trusted Adversarial Ml Countermeasure Approach For Secure And Resilient Ai-Driven Hardware Trojan Detection, Mohammed G M Alkurdi
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Semiconductor microelectronics Integrated Circuits (ICs) are increasingly integrated into critical life applications including medical, aerospace, and Internet of things. Their increasing importance as a technology gave rise to critical concerns regarding their security. This has led to the focus of the research community on hardware Trojans, which are malicious modifications to the ICs with undesirable outcomes. Their detection is becoming increasingly critical, with many researchers proposing methods to do so such as reverse engineering, logic testing, and side-channel analysis. Many of these proposals utilize machine learning methods to detect these malicious modifications with high accuracy and confidence. However, machine learning …
Role Of Urban Parks In Carbon Sequestration– A Case Study Of Safari Park, Karachi, Pakistan, Amna Bano, Minzah Shehzad, Hasnain Kazmi, Jamshaid Iqbal
Role Of Urban Parks In Carbon Sequestration– A Case Study Of Safari Park, Karachi, Pakistan, Amna Bano, Minzah Shehzad, Hasnain Kazmi, Jamshaid Iqbal
Journal of Bioresource Management
Urban parks besides their recreational use can be the potential source of climate mitigation through carbon sequestration. Present study aims to identify the carbon sequestration potential of Safari Park which is by far the largest public park of Karachi established in 1970 covering an area of 0.72 km2. A total of 153 individual trees belonging to 25 species and 14 families were included in the study. Five dominant species with highest Important Value Index (IVI) were Cocos nucifera (14.62 %), Azadirachta indica (14.21 %), Guaiacum officinale (9.93 %), Washington robusta (9.31 %) and Delonix regia (7.11 %). The …
Cvii: Enhancing Interpretability In Intelligent Sensor Systems Via Computer Vision Interpretability Index, Hossein Mohammadi, Krishnaprasad Thirunarayan, Lingwei Chen
Cvii: Enhancing Interpretability In Intelligent Sensor Systems Via Computer Vision Interpretability Index, Hossein Mohammadi, Krishnaprasad Thirunarayan, Lingwei Chen
Computer Science and Engineering Faculty Publications
In the realm of intelligent sensor systems, the dependence on Artificial Intelligence (AI) applications has heightened the importance of interpretability. This is particularly critical for opaque models such as Deep Neural Networks (DNN), as understanding their decisions is essential, not only for ethical and regulatory compliance, but also for fostering trust in AI-driven outcomes. This paper introduces the novel concept of a Computer Vision Interpretability Index (CVII). The CVII framework is designed to emulate human cognitive processes, specifically in tasks related to vision. It addresses the intricate challenge of quantifying interpretability, a task that is inherently subjective and varies across …
Wright State University's Celebration Of Student Research, Scholarship & Creative Activities From Thursday, October 26, 2023, Wright State University
Wright State University's Celebration Of Student Research, Scholarship & Creative Activities From Thursday, October 26, 2023, Wright State University
Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Abstract Books
The student abstract booklet is a compilation of abstracts from students' oral and poster presentations at Wright State University's Celebration of Student Research, Scholarship & Creative Activities on October 26, 2023.
On Colorings And Orientations Of Signed Graphs, Daniel Slilaty
On Colorings And Orientations Of Signed Graphs, Daniel Slilaty
Mathematics and Statistics Faculty Publications
A classical theorem independently due to Gallai and Roy states that a graph G has a proper k-coloring if and only if G has an orientation without coherent paths of length k. An analogue of this result for signed graphs is proved in this article.
Mining Themes In Clinical Notes To Identify Phenotypes And To Predict Length Of Stay In Patients Admitted With Heart Failure, Ankita Agarwal, Tanvi Banerjee, William Romine, Krishnaprasad Thirunarayan, Lingwei Chen, Mia Cajita
Mining Themes In Clinical Notes To Identify Phenotypes And To Predict Length Of Stay In Patients Admitted With Heart Failure, Ankita Agarwal, Tanvi Banerjee, William Romine, Krishnaprasad Thirunarayan, Lingwei Chen, Mia Cajita
Computer Science and Engineering Faculty Publications
Heart failure is a syndrome which occurs when the heart is not able to pump blood and oxygen to support other organs in the body. Identifying the underlying themes in the diagnostic codes and procedure reports of patients admitted for heart failure could reveal the clinical phenotypes associated with heart failure and to group patients based on their similar characteristics which could also help in predicting patient outcomes like length of stay. These clinical phenotypes usually have a probabilistic latent structure and hence, as there has been no previous work on identifying phenotypes in clinical notes of heart failure patients …
Sustainable Grain Transportation In Ukraine Amidst War Utilizing Knarm And Knowwheregraph, Yinglun Zhang, Antonina Broyaka, Jude Kastens, Allen M. Featherstone, Cogan Shimizu, Pascal Hitzler, Hande Küçük Mcginty
Sustainable Grain Transportation In Ukraine Amidst War Utilizing Knarm And Knowwheregraph, Yinglun Zhang, Antonina Broyaka, Jude Kastens, Allen M. Featherstone, Cogan Shimizu, Pascal Hitzler, Hande Küçük Mcginty
Computer Science and Engineering Faculty Publications
In this work, we propose a sustainable path-finding application for grain transportation during the ongoing Russian military invasion in Ukraine. This application is to build a suite of algorithms to find possible optimal paths for transporting grain that remains in Ukraine. The application uses the KNowledge Acquisition and Representation Methodology(KNARM) and the KnowWhereGraph to achieve this goal. Currently, we are working towards creating an ontology that will allow for a more effective heuristic approach by incorporating the lessons learned from the KnowWhereGraph. The aim is to enhance the path-finding process and provide more accurate and efficient results. In the future, …
A Preliminary Study Of The Efficacy Of Using A Wrist-Worn Multiparameter Sensor For The Prediction Of Cognitive Flow States In University-Level Students, Josephine Graft, William Romine, Brooklynn Watts, Noah Schroeder, Tawsik Jawad, Tanvi Banerjee
A Preliminary Study Of The Efficacy Of Using A Wrist-Worn Multiparameter Sensor For The Prediction Of Cognitive Flow States In University-Level Students, Josephine Graft, William Romine, Brooklynn Watts, Noah Schroeder, Tawsik Jawad, Tanvi Banerjee
Computer Science and Engineering Faculty Publications
Engagement is enhanced by the ability to access the state of flow during a task, which is described as a full immersion experience. We report two studies on the efficacy of using physiological data collected from a wearable sensor for the automated prediction of flow. Study 1 took a two-level block design where activities were nested within its participants. A total of five participants were asked to complete 12 tasks that aligned with their interests while wearing the Empatica E4 sensor. This yielded 60 total tasks across the five participants. In a second study representing daily use of the device, …
Exploration Of C9or72c9-500 Sk2, Sk3 Channel Expression, Teresa L. Garrett
Exploration Of C9or72c9-500 Sk2, Sk3 Channel Expression, Teresa L. Garrett
Festival of Research
ALS (also known as Lou Gehrig's Disease) is a neurodegenerative disease that weakens muscles and impacts physical function. The C9 Gene is responsible for creating proteins that help neurons send and receive signals across the synapse. Small Conductance calcium activated potassium channels (SK channels) affect the hyperpolarization phase of an action potential. Hypothesis: SK2 and SK3 clusters of C9 positive cells should decrease in size and intensity when exposed to a disease state compared to C9 negative controls.
Predicting Thermoelectric Power Factor Of Bismuth Telluride During Laser Powder Bed Fusion Additive Manufacturing, Ankita Agarwal, Tanvi Banerjee, Joy Gockel, Saniya Leblanc, Joe Walker, John Middendorf
Predicting Thermoelectric Power Factor Of Bismuth Telluride During Laser Powder Bed Fusion Additive Manufacturing, Ankita Agarwal, Tanvi Banerjee, Joy Gockel, Saniya Leblanc, Joe Walker, John Middendorf
Computer Science and Engineering Faculty Publications
An additive manufacturing (AM) process, like laser powder bed fusion, allows for the fabrication of objects by spreading and melting powder in layers until a freeform part shape is created. In order to improve the properties of the material involved in the AM process, it is important to predict the material characterization property as a function of the processing conditions. In thermoelectric materials, the power factor is a measure of how efficiently the material can convert heat to electricity. While earlier works have predicted the material characterization properties of different thermoelectric materials using various techniques, implementation of machine learning models …
In-Situ Preparation Of Cofe2o4 Nanoparticles On Eggshell Membrane-Activated Carbon For Microwave Absorption, Hassan Soleimani, Jemilat Yetunde Yusuf, Lee Kean Chuan, Hojjatollah Soleimani, Mustapha Lutfi Bin Sabar, Andreas Öchsner, Zulkifly Abbas, Asmau Iyabo Balogun, Gregory Kozlowski
In-Situ Preparation Of Cofe2o4 Nanoparticles On Eggshell Membrane-Activated Carbon For Microwave Absorption, Hassan Soleimani, Jemilat Yetunde Yusuf, Lee Kean Chuan, Hojjatollah Soleimani, Mustapha Lutfi Bin Sabar, Andreas Öchsner, Zulkifly Abbas, Asmau Iyabo Balogun, Gregory Kozlowski
Physics Faculty Publications
This study explores the potential of using cobalt ferrite (CF) nanoparticles grown in situ on eggshell membranes (ESM) to mitigate the increasing problem of electromagnetic interference (EMI). A simple carbonization process was adopted to synthesize CF nanoparticles on ESM. The study further examines the composites' surface morphology and chemical composition and evaluates their microwave absorption performance (MAP) at X-band frequency. Results showed that the composite of CF and ESM - CESM@CF, exhibited a strong RL peak value of −39.03 mm with an optimal thickness of 1.5 mm. The combination of CF and ESM demonstrates excellent impedance matching and EM wave …