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Agro-Food Waste Valorization For Sustainable Bio-Based Packaging, Luana De S.C. Carnaval, Amit K. Jaiswal, Swarna Jaiswal
Agro-Food Waste Valorization For Sustainable Bio-Based Packaging, Luana De S.C. Carnaval, Amit K. Jaiswal, Swarna Jaiswal
Articles
In recent years, the increase in the generation of agro-food processing waste, coupled with uncontrolled disposal and inefficient recovery methods, has raised concerns among society, industries, and the research community. This issue is compounded by the accumulation of conventional synthetic packaging. Owing to their significant environmental and economic impacts, the development of sustainable, biocompatible, and biodegradable materials has become an urgent target. In this context, research efforts have been directed toward developing new packaging materials based on renewable sources, such as agro-food waste, contributing to the circular economy concept. However, despite significant advances, novel agro-food-waste-based packaging solutions still largely remain …
Data Justice In Education: Toward A Research Agenda, Luci Pangrazio, Glenn Auld, Julianne Lynch, Carly Sawatzki, Gavin Duffy, Shelley Hannigan, Jo O'Mara
Data Justice In Education: Toward A Research Agenda, Luci Pangrazio, Glenn Auld, Julianne Lynch, Carly Sawatzki, Gavin Duffy, Shelley Hannigan, Jo O'Mara
Articles
Educational institutions increasingly rely on digital platforms to deliver content and learning, monitor attendance, communicate with stakeholders, and evaluate institutional performance. Despite the efficiency and accessibility gains they offer, digital platforms are powered by personal data which, through a process of datafication, can be used to track, monitor, and profile staff and students. The insights drawn from this data can be used to shape educational and professional futures. This article examines how datafication has become a social justice issue in education, discussing the implications for well-being, decision-making, governance, and power in education. Using Hintz and colleagues framework for data justice, …
The Impact Of Emerging Technologies Of Industry 4.0 On Sustainability Dimensions, Mohammed Alnahhal, Waqas Saleem, Bashir Salah
The Impact Of Emerging Technologies Of Industry 4.0 On Sustainability Dimensions, Mohammed Alnahhal, Waqas Saleem, Bashir Salah
Articles
In the Industry 4.0 (I4.0) era, emerging technologies positively affect sustainability both internally within the industry and externally at the global level. Sustainable productive systems are expected to be with the best indicators levels through using emerging technologies in the I4.0. This study aims to investigate the effect of emerging technologies in the I4.0 on the sustainability pillars through an analysis of a case study conducted at King Saud University about a Smart Yogurt Filling System. In this system, the most critical emerging technologies, such as Internet of Things (IoT), 3D printing, Near field communication technology (NFC), and Node-RED, were …
Coffee: Lighting Its Complex Ground Truth And Percolating Its Molecular Brew, Róża Paterek, Sive Geoghegan, Bernadette S. Creaven, Aoife Power
Coffee: Lighting Its Complex Ground Truth And Percolating Its Molecular Brew, Róża Paterek, Sive Geoghegan, Bernadette S. Creaven, Aoife Power
Articles
Coffee is one of the most widely traded commodities worldwide and its popularity is only increasing. The International Coffee Organisation (ICO) reported a 6% increase in global production in 2020 to 10.5 million tonnes. Coffee production is quite involved (from sowing to harvesting, processing, packaging, and storage); consequently, the industry faces major challenges in terms of the assessment of its quality, flavour, and the components which contribute to coffee's characterisation, as well as the sustainability of coffee production and global trade. This has prompted multiple studies on the nature of the aroma and taste of the many varieties of coffee …
A Global Model-Agnostic Rule-Based Xai Method Based On Parameterized Event Primitives For Time Series Classifiers, Ephrem Tibebe Mekonnen, Luca Longo, Pierpaolo Dondio
A Global Model-Agnostic Rule-Based Xai Method Based On Parameterized Event Primitives For Time Series Classifiers, Ephrem Tibebe Mekonnen, Luca Longo, Pierpaolo Dondio
Articles
Time series classification is a challenging research area where machine learning and deep learning techniques have shown remarkable performance. However, often, these are seen as black boxes due to their minimal interpretability. On the one hand, there is a plethora of eXplainable AI (XAI) methods designed to elucidate the functioning of models trained on image and tabular data. On the other hand, adapting these methods to explain deep learning-based time series classifiers may not be straightforward due to the temporal nature of time series data. This research proposes a novel global post-hoc explainable method for unearthing the key time steps …
A Novel Integration Of Data-Driven Rule Generation And Computational Argumentation For Enhanced Explainable Ai, Lucas Rizzo, Damiano Verda, Serena Berretta, Luca Longo
A Novel Integration Of Data-Driven Rule Generation And Computational Argumentation For Enhanced Explainable Ai, Lucas Rizzo, Damiano Verda, Serena Berretta, Luca Longo
Articles
Explainable Artificial Intelligence (XAI) is a research area that clarifies AI decision-making processes to build user trust and promote responsible AI. Hence, a key scientific challenge in XAI is the development of methods that generate transparent and interpretable explanations while maintaining scalability and effectiveness in complex scenarios. Rule-based methods in XAI generate rules that can potentially explain AI inferences, yet they can also become convoluted in large scenarios, hindering their readability and scalability. Moreover, they often lack contrastive explanations, leaving users uncertain why specific predictions are preferred. To address this scientific problem, we explore the integration of computational argumentation—a sub-field …
Explainable Artificial Intelligence (Xai) 2.0: A Manifesto Of Open Challenges And Interdisciplinary Research Directions, Luca Longo, Mario Brcic, Federico Cabitza, Jaesik Choi, Roberto Confalonieri, Javier Del Ser, Riccardo Guidotti, Yoichi Hayashi, Francisco Herrera, Andreas Holzinger, Richard Jiang, Hassan Khosravi, Freddy Lecue, Gianclaudio Malgieri, Andrés Páez, Wojciech Samek, Johannes Schneider, Timo Speith, Simone Stumpf, Artificial Intelligence And Cognitive Load Research Lab
Explainable Artificial Intelligence (Xai) 2.0: A Manifesto Of Open Challenges And Interdisciplinary Research Directions, Luca Longo, Mario Brcic, Federico Cabitza, Jaesik Choi, Roberto Confalonieri, Javier Del Ser, Riccardo Guidotti, Yoichi Hayashi, Francisco Herrera, Andreas Holzinger, Richard Jiang, Hassan Khosravi, Freddy Lecue, Gianclaudio Malgieri, Andrés Páez, Wojciech Samek, Johannes Schneider, Timo Speith, Simone Stumpf, Artificial Intelligence And Cognitive Load Research Lab
Articles
Understanding black box models has become paramount as systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications. In response, Explainable AI (XAI) has emerged as a field of research with practical and ethical benefits across various domains. This paper highlights the advancements in XAI and its application in real-world scenarios and addresses the ongoing challenges within XAI, emphasizing the need for broader perspectives and collaborative efforts. We bring together experts from diverse fields to identify open problems, striving to synchronize research agendas and accelerate XAI in practical applications. By fostering collaborative discussion and interdisciplinary cooperation, …
Microfluidic Flowmeter Based On A Liquid Crystal-Filled Nested Capillary, Zhe Wang, Arun Kumar Mallik, Fangfang Wei, Zhuochen Wang, Anuradha Rout, Rayhan Habib Jibon, Qiang Wu, Yuliya Semenova, University College Cork
Microfluidic Flowmeter Based On A Liquid Crystal-Filled Nested Capillary, Zhe Wang, Arun Kumar Mallik, Fangfang Wei, Zhuochen Wang, Anuradha Rout, Rayhan Habib Jibon, Qiang Wu, Yuliya Semenova, University College Cork
Articles
Microfluidic flowmeters are a powerful and highly accurate tool, enabling precise monitoring and measurements of flows of gases and fluids in a range of applications. Here we proposed and experimentally demonstrated a whispering gallery modes flowmeter composed of a liquid crystal-filled nested capillary. Whispering gallery modes are excited by a tapered fiber coupled perpendicularly to the nested capillary. The air flowing through the capillary cools it down, which leads to a temperature-induced change of the refractive index of the nematic liquid crystals. This change in turn leads to a spectral shift of the whispering gallery modes resonances, which can be …
Regulating Driving Automation Safety, Matthew Wansley
Regulating Driving Automation Safety, Matthew Wansley
Articles
Over forty thousand people die in motor vehicle crashes in the United States each year, and over two million are injured. The careful deployment of driving automation systems could prevent many of these deaths and injuries, but only if it is accompanied by effective regulation. Conventional vehicle safety standards are inadequate because they can only test how technology performs in a controlled environment. To assess the safety of a driving automation system, regulators must observe how it performs in a range of unpredictable, real world edge cases. The National Highway Traffic Safety Administration (NHTSA) is trying to adapt by experimenting …
A Comparative Study On Feature Extraction Techniques For The Discrimination Of Frontotemporal Dementia And Alzheimer's Disease With Electroencephalography In Resting-State Adults, Utkarsh Lal, Arjun Vinayak Chikkankod, Luca Longo
A Comparative Study On Feature Extraction Techniques For The Discrimination Of Frontotemporal Dementia And Alzheimer's Disease With Electroencephalography In Resting-State Adults, Utkarsh Lal, Arjun Vinayak Chikkankod, Luca Longo
Articles
Early-stage Alzheimer's disease (AD) and frontotemporal dementia (FTD) share similar symptoms, complicating their diagnosis and the development of specific treatment strategies. Our study evaluated multiple feature extraction techniques for identifying AD and FTD biomarkers from electroencephalographic (EEG) signals. We developed an optimised machine learning architecture that integrates sliding windowing, feature extraction, and supervised learning to distinguish between AD and FTD patients, as well as from healthy controls (HCs). Our model, with a 90% overlap for sliding windowing, SVD entropy for feature extraction, and K-Nearest Neighbors (KNN) for supervised learning, achieved a mean F1-score and accuracy of 93% and 91%, 92.5% …
Synthetic Dataset Generation Using Photo-Realistic Simulation With Varied Time And Weather Axes, Thomas Lee, Susan Mckeever, Jane Courtney
Synthetic Dataset Generation Using Photo-Realistic Simulation With Varied Time And Weather Axes, Thomas Lee, Susan Mckeever, Jane Courtney
Articles
To facilitate the integration of autonomous unmanned air vehicles (UAVs) in day-to-day life, it is imperative that safe navigation can be demonstrated in all relevant scenarios. For UAVs using a navigational protocol driven by artificial neural networks, training and testing data from multiple environmental contexts are needed to ensure that bias is minimised. The reduction in predictive capacity when faced with unfamiliar data is a common weak point in trained networks, which worsens the further the input data deviates from the training data. However, training for multiple environmental variables dramatically increases the man-hours required for data collection and validation. In …
Action Recognition For Human–Robot Teaming: Exploring Mutual Performance Monitoring Possibilities, Shakra Mehak, John D. Kelleher, Michael Guilfoyle, Maria Chiara Leva
Action Recognition For Human–Robot Teaming: Exploring Mutual Performance Monitoring Possibilities, Shakra Mehak, John D. Kelleher, Michael Guilfoyle, Maria Chiara Leva
Articles
Human–robot teaming (HrT) is being adopted in an increasing range of industries and work environments. Effective HrT relies on the success of complex and dynamic human–robot interaction. Although it may be optimal for robots to possess all the social and emotional skills to function as productive team members, certain cognitive capabilities can enable them to develop attitude-based competencies for optimizing teams. Despite the extensive research into the human–human team structure, the domain of HrT research remains relatively limited. In this sense, incorporating established human–human teaming (HhT) elements may prove practical. One key element is mutual performance monitoring (MPM), which involves …
Analyzing Operator States And The Impact Of Ai-Enhanced Decision Support In Control Rooms: A Human-In-The-Loop Specialized Reinforcement Learning Framework For Intervention Strategies, Ammar N. Abbas, Chidera W. Amazu, Joseph Mietkiewicz, Houda Briwa, Andres Alonso Perez, Gabriele Baldissone, Micaela Demichela, Georgios C. Chasparis, John D. Kelleher, Maria Chiara Leva
Analyzing Operator States And The Impact Of Ai-Enhanced Decision Support In Control Rooms: A Human-In-The-Loop Specialized Reinforcement Learning Framework For Intervention Strategies, Ammar N. Abbas, Chidera W. Amazu, Joseph Mietkiewicz, Houda Briwa, Andres Alonso Perez, Gabriele Baldissone, Micaela Demichela, Georgios C. Chasparis, John D. Kelleher, Maria Chiara Leva
Articles
In complex industrial and chemical process control rooms, effective decision-making is crucial for safety and efficiency. The experiments in this paper evaluate the impact and applications of an AI-based decision support system integrated into an improved human-machine interface, using dynamic influence diagrams, a hidden Markov model, and deep reinforcement learning. The enhanced support system aims to reduce operator workload, improve situational awareness, and provide different intervention strategies to the operator adapted to the current state of both the system and human performance. Such a system can be particularly useful in cases of information overload when many alarms and inputs are …
In Situ Tuning And Investigating The Growth Process Of Size Controllable Gold Nanoparticles And Statistical Size Prediction Analysis, Vinayak Sharma, Bilal Javed, Giovani Estrada, Hugh J. Byrne, Furong Tian
In Situ Tuning And Investigating The Growth Process Of Size Controllable Gold Nanoparticles And Statistical Size Prediction Analysis, Vinayak Sharma, Bilal Javed, Giovani Estrada, Hugh J. Byrne, Furong Tian
Articles
A critical understanding of the formation and growth process of gold nanoparticles (GNPs) is crucial, in order to synthesize monodisperse gold nanocrystals of controllable size and shape in a predictable way. GNPs of different shapes and sizes can be produced by altering different physicochemical reaction conditions, such as pH, temperature, and the ratio of reactants. The significant variations in the morphological features of GNPs can be monitored in situ in a time-dependent manner by using UV–visible spectroscopy. In this study, we have synthesized seedless GNPs by reduction of HAuCl4 by using various molar ratios of HEPES and Na2HPO4. The shape …
Mycotoxin Detection Through Colorimetric Immunoprobing With Gold Nanoparticle Antibody Conjugates, Vinayak Sharma, Bilal Javed, Hugh J. Byrne, Furong Tian
Mycotoxin Detection Through Colorimetric Immunoprobing With Gold Nanoparticle Antibody Conjugates, Vinayak Sharma, Bilal Javed, Hugh J. Byrne, Furong Tian
Articles
Driven by their exceptional optical characteristics, robust chemical stability, and facile bioconjugation, gold nanoparticles (AuNPs) have emerged as a preferred material for detection and biosensing applications in scientific research. This study involves the development of a simple, rapid, and cost-effective colorimetric immuno-sensing probe to detect aflatoxin B1 and zearalenone using AuNP antibody (AuNP-mAb) conjugates. Anti-toxin antibodies were attached to the AuNPs by using the physical adsorption method. The colorimetric immunosensor developed operates on the principle that the optical properties of the AuNP are very sensitive to aggregation, which can be induced by a critical high salt concentration. Although the presence …
Biosensor-Enhanced Organ-On-A-Chip Models For Investigating Glioblastoma Tumor Microenvironment Dynamics, Gayathree Thenuwara, Bilal Javed, Baljit Singh, Furong Tian
Biosensor-Enhanced Organ-On-A-Chip Models For Investigating Glioblastoma Tumor Microenvironment Dynamics, Gayathree Thenuwara, Bilal Javed, Baljit Singh, Furong Tian
Articles
Glioblastoma, an aggressive primary brain tumor, poses a significant challenge owing to its dynamic and intricate tumor microenvironment. This review investigates the innovative integration of biosensor-enhanced organ-on-a-chip (OOC) models as a novel strategy for an in-depth exploration of glioblastoma tumor microenvironment dynamics. In recent years, the transformative approach of incorporating biosensors into OOC platforms has enabled real-time monitoring and analysis of cellular behaviors within a controlled microenvironment. Conventional in vitro and in vivo models exhibit inherent limitations in accurately replicating the complex nature of glioblastoma progression. This review addresses the existing research gap by pioneering the integration of biosensor-enhanced OOC …
A Comprehensive Review Of Food Safety Culture In The Food Industry: Leadership, Organizational Commitment, And Multicultural Dynamics, Ashwini Sadashiv Pai, Swarna Jaiswal, Amit K. Jaiswal
A Comprehensive Review Of Food Safety Culture In The Food Industry: Leadership, Organizational Commitment, And Multicultural Dynamics, Ashwini Sadashiv Pai, Swarna Jaiswal, Amit K. Jaiswal
Articles
Food safety culture (FSC) has transitioned from a narrow compliance-based concept to a comprehensive organisational value that is essential for ensuring food safety. This review explores the pivotal roles of leadership, organisational commitment, and cultural diversity in shaping an effective FSC. It highlights how leadership style, particularly transformational leadership, can enhance employee engagement and foster a proactive safety culture. Additionally, the impact of national and organisational cultures on FSC is analysed, emphasising the challenges posed by a multicultural workforce in standardising food safety practices. This article also provides a comparative analysis of FSC across various sectors, such as meat and …
Synthesis Of Cationic Liposome Nanoparticles Using A Thin Film Dispersed Hydration And Extrusion Method, Alessandro Cazzolla, Julie Rose Mae Mondala, Janith Wanigasekara, Joanna Carroll, Noah Daly, Brijesh Tiwari, Alan Casey, James F. Curtin
Synthesis Of Cationic Liposome Nanoparticles Using A Thin Film Dispersed Hydration And Extrusion Method, Alessandro Cazzolla, Julie Rose Mae Mondala, Janith Wanigasekara, Joanna Carroll, Noah Daly, Brijesh Tiwari, Alan Casey, James F. Curtin
Articles
Liposome nanoparticles can carry a wide range of therapeutic molecules including small molecules and nucleic acid-based therapeutics. Potential benefits include translocation across physiological barriers, reduced systemic toxicity, and enhanced pharmacokinetic parameters such as absorption, distribution, selective release and optimal elimination kinetics. Liposome nanoparticles can be generated with a wide range of natural and synthetic lipid-based molecules that confer desirable properties depending on the desired therapeutic application Nel et al (2023), Large (2021), Elkhoury (2020). This protocol article seeks to detail the procedures involved in the production of cationic liposomes using thin-film dispersed hydration method with an estimated uniform size of …
Synergistic Cytotoxicity Effect Of Ultrasound And Plasma Microbubble In Glioblastoma 3d Tumor Sphere Model, Janith Wanigasekara, Patrick J. Cullen, Brijesh Tiwari, James F. Curtin
Synergistic Cytotoxicity Effect Of Ultrasound And Plasma Microbubble In Glioblastoma 3d Tumor Sphere Model, Janith Wanigasekara, Patrick J. Cullen, Brijesh Tiwari, James F. Curtin
Articles
The combined application of ultrasound (US) and plasma microbubble (PMB) is a promising technology against glioblastoma (GBM). Here, we determined the effects of US and PMB (alone and combined) on U-251 MG GBM and A431 epidermoid carcinoma spheroids under different conditions. The synergistic treatment of US- and PMB-induced tumor sphere cell death in a time-, dose-, treatment frequency-, and reactive oxygen species dependent manner, while multiple treatments augmented this effect. Synergistic treatments significantly reduced three-dimensional GBM spheroid regrowth and cell proliferation while inducing cytotoxicity, spheroid shrinkage, and damage to the tumor microenvironment. PMB-induced cytotoxicity throughout the tumor sphere, likely via …
Review Of Detection Limits For Various Techniques For Bacterial Detection In Food Samples, Xinyi Zhao Nanolab Research Centre, Abhijnan Bhat, Christine O’Connor School Of Food Science And Environmental Health, James Curtin Faculty Of Engineering And Built Environment, Baljit Singh, Micra Biodiagnostics Technology Gateway And Health, Engineering & Materials Sciences (Hems) Research Hub, Furong Tian Nanolab Research Centre
Review Of Detection Limits For Various Techniques For Bacterial Detection In Food Samples, Xinyi Zhao Nanolab Research Centre, Abhijnan Bhat, Christine O’Connor School Of Food Science And Environmental Health, James Curtin Faculty Of Engineering And Built Environment, Baljit Singh, Micra Biodiagnostics Technology Gateway And Health, Engineering & Materials Sciences (Hems) Research Hub, Furong Tian Nanolab Research Centre
Articles
Foodborne illnesses can be infectious and dangerous, and most of them are caused by bacteria. Some common food-related bacteria species exist widely in nature and pose a serious threat to both humans and animals; they can cause poisoning, diseases, disabilities and even death. Rapid, reliable and cost-effective methods for bacterial detection are of paramount importance in food safety and environmental monitoring. Polymerase chain reaction (PCR), lateral flow immunochromatographic assay (LFIA) and electrochemical methods have been widely used in food safety and environmental monitoring. In this paper, the recent developments (2013–2023) covering PCR, LFIA and electrochemical methods for various bacterial species …
Investigating Abandonment Errors In Cruise/Passenger Ships : Researching The Reasons Leading To Life-Losses During An Evacuation, A. Andreadakis, D. Dalaklis, N. Nikitakos
Investigating Abandonment Errors In Cruise/Passenger Ships : Researching The Reasons Leading To Life-Losses During An Evacuation, A. Andreadakis, D. Dalaklis, N. Nikitakos
Articles
No abstract provided.
Stakeholders’ Perceptions On The Introduction Of Additive Manufacturing (Am) In The Maritime Spare Parts Supply Chain, E. Kostidi, N. Nikitakos, T. Lilas, D. Dalaklis
Stakeholders’ Perceptions On The Introduction Of Additive Manufacturing (Am) In The Maritime Spare Parts Supply Chain, E. Kostidi, N. Nikitakos, T. Lilas, D. Dalaklis
Articles
No abstract provided.
Wind Turbine Condition Monitoring Based On Three Fitted Performance Curves, Shuo Zhang, Emma Robinson, Malabika Basu
Wind Turbine Condition Monitoring Based On Three Fitted Performance Curves, Shuo Zhang, Emma Robinson, Malabika Basu
Articles
Based on SCADA data, this study aims at fitting three performance curves (PCs), power curve, pitch angle curve, and rotor speed curve, to accurately describe the normal behaviour of a wind turbine (WT) for performance monitoring and identification of anomalous signals. The fitting accuracy can be undesirably affected by erroneous SCADA data. Hence, outliers generated from raw SCADA data should be removed to mitigate the prediction inaccuracy, so various outlier detection (OD) approaches are compared in terms of area under the curve (AUC) and mean average precision (mAP). Among them, a novel unsupervised SVM-KNN model, integrated by support vector machine …
Analysis Of Delta In-Out For Irish Natural Gas Distribution Network, Utkarsha Chavan, Anthony Reynolds, Michael Carr, L. Walsh
Analysis Of Delta In-Out For Irish Natural Gas Distribution Network, Utkarsha Chavan, Anthony Reynolds, Michael Carr, L. Walsh
Articles
This article investigates the issue of Unaccounted for Gas (UAG) in the natural gas distribution network of Ireland, focusing on the DeltaIO (i.e. the difference between the gas entering and leaving the network). The study applies the DeltaIO methodology developed for Italian distribution networks to Gas Networks Ireland (GNI), the sole Distribution System Operator (DSO) in Ireland. The analysis covers the period from 2013 to 2019 and provides insights into the magnitude and trends of UAG in the Irish context. The results show that GNI's DeltaIO ranges from 0.93% to 1.57%, with an average of 1.15%. Comparisons with large Italian …
Finite Element Investigation Of Cutting Speed Effects On The Machining Of Ti6al4v Alloy, Surinder Pal, Xavier Velay, Waqas Saleem
Finite Element Investigation Of Cutting Speed Effects On The Machining Of Ti6al4v Alloy, Surinder Pal, Xavier Velay, Waqas Saleem
Articles
In modern times, titanium alloy has a great application prospect in the medical field. Still, the pitiful machinability of titanium alloy material brings incredible difficulty to its ultra-precision cutting. This work presented the effect of parametric sensitivity analysis of the orthogonal cutting process using the finite element method, which dramatically enhances the cutting performance of Ti–6AL–4V. The simulation results are attained by applying Abaqus® explicit 6.14 software. The mechanical reaction of two-dimensional finite element models has been examined for cutting forces. Additionally, the impacts of rake angle, clearance angle, and nose radius on the stress distribution in orthogonal cutting of …
Assessing The Corrosive Effects Of Unmelted Particles In Additively Manufactured Ti6al4v: A Study In Simulated Body Fluid, Surinder Pal, Xavier Velay, Waqas Saleem
Assessing The Corrosive Effects Of Unmelted Particles In Additively Manufactured Ti6al4v: A Study In Simulated Body Fluid, Surinder Pal, Xavier Velay, Waqas Saleem
Articles
This study investigates the corrosion behavior of Grade 23 Ti6Al4V alloys produced through laser powder bed fusion (L-PBF) when exposed to simulated body fluid at room temperature, focusing on the role of unmelted particles. This research aims to understand how these microstructural features, resulting from the additive manufacturing process, influence the corrosion resistance of the alloys. It was observed that unmelted particles serve as critical sites for initiating localized corrosion, including pitting, which significantly compromises the material's overall durability. Electrochemical testing and detailed surface analysis revealed that these particles, alongside other defects such as voids, exacerbate the susceptibility to corrosion …
High-Precision Digital Light Processing (Dlp) Printing Of Microstructures For Microfluidics Applications Based On A Machine Learning Approach, Xinhui Wang, Jinghang Liu, Ruihai Dong, Michael D. Gilchrist, Nan Zhang
High-Precision Digital Light Processing (Dlp) Printing Of Microstructures For Microfluidics Applications Based On A Machine Learning Approach, Xinhui Wang, Jinghang Liu, Ruihai Dong, Michael D. Gilchrist, Nan Zhang
Articles
Digital light processing (DLP) is renowned for its precision, but the challenge lies in the identification of optimal print parameters to minimise print errors and enhance overall print accuracy. This study introduces a groundbreaking approach by integrating 'Random Forest' (RF) models with DLP printing to construct a predictive model for printing errors to achieve unparalleled precision. We conducted experiments using common commercial resins to print, resulting in a comprehensive dataset of 690 experimental datasets. Consequently, we validated this approach by fabricating Y-type microfluidic structures with a minimum feature size printing of 2 µm and herringbone mixer structures with feature sizes …
Optical Response Of Pdms Surface Diffraction Gratings Under Exposure To Volatile Organic Compounds, Aleksandra Hernik, Faolan Radford Mcgovern, Izabela Naydenova
Optical Response Of Pdms Surface Diffraction Gratings Under Exposure To Volatile Organic Compounds, Aleksandra Hernik, Faolan Radford Mcgovern, Izabela Naydenova
Articles
Monitoring volatile organic compounds (VOCs) in indoor air is significantly gaining importance due to their adverse effects on human health. Among the diverse detection methods is optical sensing, which employs materials sensitive to the presence of gases in the environment. In this work, we investigate polydimethylsiloxane (PDMS), one of the materials utilized for gas sensing, in a novel transducer: a surface relief diffraction grating. Upon adsorption of the volatile analyte, the PDMS grating swells, and its refractive index changes; both effects lead to increased diffraction efficiency in the first diffraction order. Hence, the possibility of VOC detection emerges from the …
Optically Accessible Gas Exposure Apparatus For Testing And Characterization Of Holographic Gas Sensors, Graceson Antony, Rinto Eyyalil Joseph, Saji George, Dervil Cody, Izabela Naydenova
Optically Accessible Gas Exposure Apparatus For Testing And Characterization Of Holographic Gas Sensors, Graceson Antony, Rinto Eyyalil Joseph, Saji George, Dervil Cody, Izabela Naydenova
Articles
Holographic gas sensors are of great interest due to their widespread applicability and potential for high sensitivity, fast response, immunity to electromagnetic interference, and compact and lightweight nature. For effective design and development of holographic gas sensors, it is essential to have a reliable and safe gas exposure system allowing for optical access for testing purposes. Here, the design and operation of a custom gas exposure apparatus for the performance evaluation of holographic grating-based gas sensors within a research laboratory setting is presented. The apparatus enables the real-time measurement of analyte-induced changes in key holographic grating parameters: grating diffraction efficiency …
Comparison Of Holographic Recording Options For Reflection-Format And Transmission-Format Coupler-Type Diffractive Optical Elements: Theoretical Exploration And Experimental Validation, Dipanjan Chakraborty, Rosen Georgiev, Vincent Toal, Izabela Naydenova, Dervil Cody, Suzanne Martin
Comparison Of Holographic Recording Options For Reflection-Format And Transmission-Format Coupler-Type Diffractive Optical Elements: Theoretical Exploration And Experimental Validation, Dipanjan Chakraborty, Rosen Georgiev, Vincent Toal, Izabela Naydenova, Dervil Cody, Suzanne Martin
Articles
The holographic recording of gratings that have very large diffraction angles and/or slants is challenging because recording requires beam angles that are not possible without the use of prisms. However, by using a recording wavelength that is different from (usually shorter than) the intended operating wavelength, it is possible to record with less challenging beam angles. In this paper, a recently developed model that allows systematic investigation of the potential and limits of this wavelength-shift recording technique is extended to include a reflection format. Transmission and reflection recording options are compared systematically for the first time, and it is shown …