Advanced Simulation Techniques Research Articles

Improving electric field stress using grading ring devices for insulated cross-arm

Insulated cross-arms (ICA) allow for the compaction or enhancement of transmission lines. This study presents a comprehensive approach to designing and evaluating insulated cross-arm (ICA) grading devices to control electric fields for insulated cross-arms on a 132 kV lattice tower. A ring-shaped grading device is designed for the low voltage (LV) end of the insulator. A novel grading device is designed for the high voltage (HV) end—a single piece that controls the field for all four ICA members. Finite element analysis (FEA) simulations assess the electric field stress near the HV and LV ends of the ICAs, ensuring that it remains below the critical threshold of 18 kV/cm and effectively improves electric field stress at both ends of compression insulator by 70 % electric field stress at LV end and 80 % improved at HV end. The study outlines a thorough design methodology and provides valuable guidelines for utilising FEA in developing complex geometries. By adopting this approach, the researchers aim to enable the adequate compaction and upgrading of new and existing 132 kV overhead transmission lines, ultimately contributing to optimising power grid infrastructure. The findings of this study demonstrate the importance of integrating comprehensive design strategies and advanced simulation techniques to enhance the reliability and performance of ICA.

A techno-economic perspective on efficient hybrid renewable energy solutions in Douala, Cameroon’s grid-connected systems

Cameroon is currently grappling with a significant energy crisis, which is adversely affecting its economy due to cost, reliability, and availability constraints within the power infrastructure. While electrochemical storage presents a potential remedy, its implementation faces hurdles like high costs and technical limitations. Conversely, generator-based systems, although a viable alternative, bring their own set of issues such as noise pollution and demanding maintenance requirements. This paper meticulously assesses a novel hybrid energy system specifically engineered to meet the diverse energy needs of Douala, Cameroon. By employing advanced simulation techniques, especially the Hybrid Optimization Model for Electric Renewable (HOMER) Pro program, the study carefully examines the intricacies of load demands across distinct consumer categories while accommodating varied pricing models. The paper offers a detailed analysis of the proposed grid-connected PV/Diesel/Generator system, aiming to gauge its performance, economic feasibility, and reliability in ensuring uninterrupted energy supply. Notably, the study unveils significant potential for cost reduction per kilowatt-hour, indicating promising updated rates of $0.07/kW, $0.08/kW, and $0.06/kW for low, medium, and high usage groups, respectively. Furthermore, the research underscores the importance of overcoming operational challenges and constraints such as temperature fluctuations, equipment costs, and regulatory compliance. It also acknowledges the impact of operational nuances like maintenance and grid integration on system efficiency. As the world progresses towards renewable energy adoption and hybrid systems, this investigation lays a strong foundation for future advancements in renewable energy integration and energy management strategies. It strives to create a sustainable energy ecosystem in Cameroon and beyond, where hybrid energy systems play a pivotal role in mitigating power deficiencies and supporting sustainable development.

A method to design a fast chaotic oscillator using CCTA

This article introduces a novel method for designing a fast chaotic oscillator using a CCTA (Current Conveyor Transconductance Amplifier) based on Chua's circuit. The proposed method uses innovative configurations and advanced simulation techniques to overcome challenges in high-speed operation, nonlinear dynamics, and Analog Building Block (ABB) selection. The design begins with nonlinear negative resistance, essential for Chua's diode characteristics, including two negative resistances, NR1 and NR2. The circuit integrates one CCTA block, two grounded capacitors, two fixed resistors, one inductor, and one potentiometer. It is simulated using PSPICE with IC (Integrated Circuit) macro-models and 180nm CMOS (Complementary Metal Oxide Semiconductor) technology. Various chaotic waveforms and attractors are produced, validating the theoretical and mathematical predictions. By varying the resistance values (1450Ω, 1650Ω, 1800Ω, 1950Ω), the circuit exhibits different chaotic behaviors, such as large limit cycles, double-scroll attractors, Rossler-type attractors, and I-periodic attractors. FFT (Fast Fourier Transform) analysis confirms the highest dominant operating frequency of 37.5MHz. A Monte Carlo simulation with 100 runs shows maximum voltage variations in the chaotic waveforms of 5.21 % and 4.61 % across the capacitors, demonstrating robustness and reliability. This design offers significant advancements in implementing high-frequency chaotic oscillators, with potential applications in various fields requiring chaotic signal generation.•A novel design of Chua's diode and Chua's chaotic oscillator using only one CCTA block is presented in this paper.•The proposed chaotic oscillator achieves the highest operating frequency of 37.5MHz.•The proposed circuit is simulated using commercially available ICs (MAX435 and AD844) and CMOS 180nm technology in PSPICE to confirm its workability.

Unleashing the Potential of a Hybrid 3D Hydrodynamic Monte Carlo Risk Model for Maritime Structures’ Design in the Imminent Climate Change Era

Submarine pipelines have become integral for transporting resources and drinking water across large bodies. Therefore, ensuring the stability and reliability of these submarine pipelines is crucial. Incorporating climate change impacts into the design of marine structures is paramount to assure their lifetime safety and serviceability. Deterministic design methods may not fully consider the uncertainties and risks related to climate change compared to risk-based design models. The latter approach considers the future risks and uncertainties linked to climate and environmental changes, thus ensuring infrastructure sustainability. This study pioneers a Hybrid 3D Hydrodynamic Monte Carlo Simulation (HMCS) Model to improve the reliability-based design of submarine pipelines, incorporating the effects of climate change. Current design approaches may follow deterministic methods, which may not systematically account for climate change’s comprehensive uncertainties and risks. Similarly, traditional design codes often follow a deterministic approach, lacking in the comprehensive integration of dynamic environmental factors such as wind, waves, currents, and geotechnical conditions, and may not adequately handle the uncertainties, including the long-term effects of climate change. Nowadays, most countries are developing new design codes to modify the risk levels for climate change’s effects, such as sea-level rises, changes in precipitation, or changes in the frequency/intensity of winds/storms/waves in coastal and marine designs. Our model may help these efforts by integrating a comprehensive risk-based approach, utilizing a 3D hydrodynamic model to correlate diverse environmental factors through Monte Carlo Simulations (MCS). The hybrid model can promise the sustainability of marine infrastructure by adapting to future environmental changes and uncertainties. Including such advanced methodologies in the design, codes are encouraged to reinforce the resilience of maritime structures in the climate change era. The present design codes should inevitably be reviewed according to climate change effects, and the hybrid risk-based design model proposed in this research should be included in codes to ensure the reliability of maritime structures. The HMCS model represents a significant advancement over existing risk models by incorporating comprehensive environmental factors, utilizing advanced simulation techniques, and explicitly addressing the impacts of climate change. This innovative approach ensures the development of more resilient and sustainable maritime infrastructure capable of withstanding future environmental uncertainties.

Enhancing community resilience to urban heat waves: A simulation-based approach for volunteer management and shelter selection

This study proposes a novel approach to enhancing urban resilience and emergency management practices in the face of heatwave events, often exacerbated by the urban heat island effect. Recognizing the limitations of traditional government-led responses in shelter allocation—characterized by high costs, logistical challenges, and a lack of adaptability—this paper introduces an innovative framework that integrates community-based volunteer efforts with advanced simulation and stochastic modelling techniques. The primary objective is to optimize the allocation of resources and volunteers to improve the efficiency and cost-effectiveness of heatwave response mechanisms. Utilizing Data Envelopment Analysis (DEA), the research identifies and enhances resource and volunteer distribution strategies, paving the way for more effective emergency services. A case study conducted in Blacktown City, Western Sydney, serves to demonstrate the practical application and implications of these strategies, underscoring the necessity for a paradigm shift towards more adaptable, volunteer-focused, and resource-efficient approaches in mitigating the impact of climate-change-induced heat waves on vulnerable urban populations. The anticipated outcomes include measurable improvements in response times, cost reductions, and enhanced volunteer mobilization efficiency.

Monthly hydraulic geometry relationship quantification with environmental LAI by utilizing sentinel data: A case in Jingjiang reach of the Yangtze River

This study presents a novel approach for quantifying the dynamics of monthly hydraulic geometry relationships in the Jingjiang reach of the Yangtze River by integrating leaf area index (LAI) data as an indicator of riparian vegetation. A comprehensive system of ordinary differential equations (ODEs) couples traditional power-law hydraulic geometry equations with LAI, capturing the influence of erosion control on channel morphology. The periodic delayed response theory and automatic differentiation techniques are employed to enhance the modeling framework’s capabilities. Calibration and verification demonstrate the models’ effectiveness in capturing overall trends in discharge, width, and depth dynamics, outperforming traditional constant-parameter approaches. However, model predictive abilities are limited under extreme climate conditions due to training on normal climate data. Key assumptions, including the periodic delayed response theory’s neglect of peak discharges, simplified representation of artificial cut-offs, and reliance on remotely sensed data with limited local validation, introduce uncertainties. The proposed modeling framework shows potential for broader application to other river systems with appropriate adjustments. Future research could incorporate additional environmental factors, integrate models across scales, couple with advanced simulation techniques, and expand stability assessments beyond the riverbed index. By addressing related challenges, this integrated approach lays a foundation for enhancing understanding of river morphodynamics and channel stability.

Review and Assessment of Material, Method, and Predictive Modeling for Fiber-Reinforced Polymer (FRP) Partially Confined Concrete Columns.

The repairing and strengthening of concrete structures using external and internal partial confinements are inevitable in the construction industry due to the new standards and rapid developments. The conventional materials and methods of confinement are unable to meet modern safety and functional standards. The fiber-reinforced polymer (FRP) enhances the strength and ductility of deteriorating and new concrete columns by reducing lateral confinement pressure and resistance against seismic shocks. The precise methods of partial confinement are inevitable for effective FRP-concrete bonding, durability, and cost-effectiveness under different loading conditions and to cope with external environmental factors. Predictive modeling and simulation techniques are pivotal for the optimization of confinement materials and methods by investigating the FRP-concrete novel confinement configurations, stress-strain responses, and failure modes. The novel materials and methods for concrete columns' partial confinement lack high compressive strength, ductility, chemical attack resistivity, and different fiber orientation impacts. This review provides an overview of recent confinement materials, novel methods, and advanced modeling and simulation techniques with a critical analysis of the research gaps for partial FRP confinement of concrete columns. The current challenges and future prospects are also presented.

Assessment of modified chitosan composite in acidic reservoirs through pilot and field-scale simulation studies

Chemical flooding through biopolymers acquires higher attention, especially in acidic reservoirs. This research focuses on the application of biopolymers in chemical flooding for enhanced oil recovery in acidic reservoirs, with a particular emphasis on modified chitosan. The modification process involved combining chitosan with vinyl/silane monomers via emulsion polymerization, followed by an assessment of its rheological behavior under simulated reservoir conditions, including salinity, temperature, pressure, and medium pH. Laboratory-scale flooding experiments were carried out using both the original and modified chitosan at conditions of 2200 psi, 135,000 ppm salinity, and 196° temperature. The study evaluated the impact of pressure on the rheological properties of both chitosan forms, finding that the modified composite was better suited to acidic environments, showing enhanced resistance to pressure effects with a significant increase in viscosity and an 11% improvement in oil recovery over the 5% achieved with the unmodified chitosan. Advanced modeling and simulation techniques, particularly using the tNavigator Simulator on the Bahariya formations in the Western Desert, were employed to further understand the polymer solution dynamics in reservoir contexts and to predict key petroleum engineering metrics. The simulation results underscored the effectiveness of the chitosan composite in increasing oil recovery rates, with the composite outperforming both its native counterpart and traditional water flooding, achieving a recovery factor of 48%, compared to 39% and 37% for native chitosan and water flooding, thereby demonstrating the potential benefits of chitosan composites in enhancing oil recovery operations.

Impact of radioactive emissions from the Laguna Verde nuclear power plant using CALPUFF

Monitoring and regulating radioactive emissions from nuclear power plants is important for evaluating and managing the associated radiological risks to humans and the environment. Radioactive emissions can occur during different stages of nuclear power generation, posing concerns about exposure to ionizing radiation. Modeling, particularly using advanced simulation techniques, is a crucial tool for assessing both routine and accidental emissions. This work assesses the potential environmental and radiological impacts of radioactive emissions from the Laguna Verde nuclear power plant (Veracruz, México) using the CALPUFF model for dispersion and the ERICA tool for ecological risk assessment. Normal operations simulations showed that the higher concentrations and ground depositions were observed in Veracruz. The probability of exceeding screening doses was acceptably low (<5%), indicating minimal cancer risk from controlled releases. During nuclear accidents, dispersed plumes were observed with varying directions depending on wind speed. The study identified potential risks to five designated cities as receptor sites, with some plume sweeps diverting pollutants. The most affected receptor site (Veracruz) recorded the highest air concentrations, depositions, and radiation doses. These findings offer valuable insights for regulators, decision-makers, and the public, emphasizing low impacts from controlled releases but highlighting potential risks during nuclear accidents.

Electrically Small Antenna for Sensing Application: A Review

Abstract: This study focuses on the electrically small antennas (ESAs) tailored for sensing applications. Recognizing the critical role of antenna size and performance in modern sensing systems, the research employs advanced simulation and optimization techniques to explore various configurations. Additionally, discussions on potential enhancements, such as meta material, Dielectric resonating antenna, meander line antenna, etc. integration and reconfigurable structures, provide insights for future developments in compact antenna technology for wireless sensing systems. Thus, in In this paper, a comprehensive overview of various types of electrically small antennas (ESAs) is presented, along with their significance in enhancing performance and their application in 5G and 6G communication systems.

FEA and CFD analysis and optimization of tube in tube heat exchanger for various cases

This research describes the use of advanced simulation techniques to investigate use of different materials for a tube-in-tube heat exchanger. Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) simulations are employed to simulate thermal aspects and optimize the heat exchanger design. The objective is to identify the best-Suitable material combination considering both design and thermal considerations. The findings of this research contribute to the development of more efficient heat exchanger designs.

Enhancing thermal transfer in airfoil structures through advanced simulation techniques and MOPSO optimization

This research employs advanced simulation techniques by integrating Python, CAD, ANSYS Fluent, and other execution programs, to optimize the thermal transfer performance of an airfoil structure. The study involves a design of experiments (DOE) analysis employing optimal Latin hypercube (OLH) sampling to study the influence of airfoil structural parameters on Nu, f, and comprehensive heat index (CHI). Subsequently, multi-objective particle swarm optimization (MOPSO) is applied, resulting in a remarkable 93.4% increase in CHI, elevating it from 101.13 to 195.61. Experimental validation of the optimized airfoil structure demonstrates close agreement with simulated results, affirming the reliability of our numerical simulations. The results establish the superior heatexchange capabilities of the optimized airfoil structure over the unoptimized reference airfoil and the traditional circular structure. This research contributes significantly to the structural optimization of heat exchange equipment, particularly for configurations characterized by substantial height-to-diameter ratios.

Assessing road vulnerability in seismic conditions: a comprehensive study

Road infrastructure is indispensable for societal functionality, yet it is highly susceptible to the devastating impacts of seismic events. This paper focuses on enhancing the resilience of road systems by systematically identifying, quantifying, and assessing factors contributing to their vulnerability during earthquakes. The core objective of this study is to develop and validate a seismic vulnerability index for road sections, which aims to evaluate and classify the susceptibility of road infrastructure to earthquake-induced damage comprehensively. This systematic approach is pivotal for guiding effective mitigation strategies and prioritization efforts. To fulfill this objective, the study employs the Analytic Hierarchy Process (AHP) to introduce a novel methodology for calculating the seismic vulnerability index, incorporating various factors that influence road vulnerability. This method allows for the accurate classification of road sections into distinct levels of susceptibility, providing a solid foundation for implementing targeted interventions and enhancing road resilience. Further, the paper validates the theoretical model through several case studies, demonstrating the practical applicability and effectiveness of the seismic vulnerability index in real-world scenarios. Additionally, the use of Geographic Information System (GIS) technology to simulate earthquake scenarios within an urban road network offers valuable insights into the potential seismic behavior of roads. These simulations are crucial for identifying critical areas that require intervention and for planning resilience-building efforts more effectively. By proposing a comprehensive framework that combines rigorous analysis, empirical validation, and advanced simulation techniques, this paper seeks to make a significant contribution to the field of infrastructure resilience. It aims to advance the understanding of road vulnerability in seismic conditions and supports the development of strategic approaches for enhancing the resilience of road infrastructure against earthquakes. Through the development and validation of a seismic vulnerability index, this study meets its primary objective, providing a valuable resource for researchers, policymakers, and practitioners in disaster management and infrastructure planning.

Interaction of 3,9-disubstituted acridine with single stranded poly(rA), double stranded poly(rAU) and triple stranded poly(rUAU): molecular docking – A spectroscopic tandem study

RNA plays an important role in many biological processes which are crucial for cell survival, and it has been suggested that it may be possible to inhibit individual processes involved in many diseases by targeting specific sequences of RNA. The aim of this work is to determine the affinity of novel 3,9-disubstited acridine derivative 1 with three different RNA molecules, namely single stranded poly(rA), double stranded homopolymer poly(rAU) and triple stranded poly(rUAU). The results of the absorption titration assays show that the binding constant of the novel derivative to the RNA molecules was in the range of 1.7–6.2 × 104 mol dm−3. The fluorescence and circular dichroism titration assays revealed considerable changes. The most significant results in terms of interpreting the nature of the interactions were the melting temperatures of the RNA samples in complexes with the 1. In the case of poly(rA), denaturation resulted in a self-structure formation; increased stabilization was observed for poly(rAU), while the melting points of the ligand-poly(rUAU) complex showed significant destabilization as a result of the interaction. The principles of molecular mechanics were applied to propose the non-bonded interactions within the binding complex, pentariboadenylic acid and acridine ligand as the study model. Initial molecular docking provided the input structure for advanced simulation techniques. Molecular dynamics simulation and cluster analysis reveal π – π stacking and the hydrogen bonds formation as the main forces that can stabilize the binding complex. Subsequent MM-GBSA calculations showed negative binding enthalpy accompanied the complex formation and proposed the most preferred conformation of the interaction complex.

SIMULATION-DRIVEN STRATEGIES FOR ENHANCING WATER TREATMENT PROCESSES IN CHEMICAL ENGINEERING: ADDRESSING ENVIRONMENTAL CHALLENGES

Water treatment processes in chemical engineering play a critical role in addressing environmental challenges and ensuring the sustainability of water resources. This paper examines simulation-driven strategies aimed at enhancing water treatment processes within the domain of chemical engineering. By leveraging advanced simulation techniques and methodologies, engineers can optimize the design, operation, and performance of water treatment systems, thereby mitigating environmental impacts and improving overall efficiency. The review highlights the importance of addressing environmental challenges through innovative approaches in water treatment processes. It underscores the role of simulation-driven strategies in chemical engineering to achieve sustainable solutions for water management. Through a comprehensive review of simulation techniques and case studies, this paper elucidates how simulation-driven approaches can enhance the effectiveness and sustainability of water treatment processes. Furthermore, the review emphasizes the interdisciplinary nature of this research, bridging chemical engineering principles with environmental science and technology. By integrating simulation tools with knowledge of water chemistry, fluid dynamics, and process engineering, engineers can develop robust strategies for optimizing water treatment processes while minimizing environmental footprints. Key topics covered include the application of computational fluid dynamics (CFD), process simulation software, and advanced modeling techniques in the analysis and design of water treatment systems. Case studies illustrating the successful implementation of simulation-driven strategies in various water treatment applications are presented to provide practical insights and demonstrate the potential benefits. Overall, this paper underscores the pivotal role of simulation-driven strategies in advancing water treatment processes in chemical engineering. It advocates for the adoption of innovative approaches to address environmental challenges and promote sustainability in water management practices within the oil and gas industry and other sectors reliant on chemical engineering processes.&#x0D; Keywords: Water treatment, Environmental Challenges, Chemical Engineering, Processes, Simulation Driven Strategies.

Solar-Assisted Carbon Capture Process Integrated with a Natural Gas Combined Cycle (NGCC) Power Plant—A Simulation-Based Study

In the realm of Natural Gas Combined Cycle (NGCC) power plants, it is crucial to prioritize the mitigation of CO2 emissions to ensure environmental sustainability. The integration of post-combustion carbon capture technologies plays a pivotal role in mitigating greenhouse gas emissions enhancing the NGCC’s environmental profile by minimizing its carbon footprint. This research paper presents a comprehensive investigation into the integration of solar thermal energy into the Besmaya Natural Gas Combined Cycle (NGCC) power plant, located in Baghdad, Iraq. Leveraging advanced process simulation and modeling techniques employing Aspen Plus software, the study aims to evaluate the performance and feasibility of augmenting the existing NGCC facility with solar assistance for post-carbon capture. The primary objective of this research is to conduct a thorough simulation of the Besmaya NGCC power plant under its current operational conditions, thereby establishing a baseline for subsequent analyses. Subsequently, a solar-assisted post-combustion capture (PCC) plant is simulated and seamlessly integrated into the existing power infrastructure. To accurately estimate solar thermal power potential at the Baghdad coordinates, the System Advisor Model (SAM) is employed. The integration of solar thermal energy into the NGCC power plant is meticulously examined, and the resulting hybrid system’s technical viability and performance metrics are rigorously evaluated. The paper contributes to the field by providing valuable insights into the technical feasibility and potential benefits of incorporating solar thermal energy into conventional natural gas power generation infrastructure, particularly in the context of the Besmaya NGCC plant in Baghdad. The power generation capacity of the plant was set at 750 MW. With this capacity, the annual CO2 generation was estimated at 2,119,318 tonnes/year which was reduced to 18,064 tonnes/year (a 99% reduction). The findings aim to inform future decisions in the pursuit of sustainable and efficient energy solutions, addressing both environmental concerns and energy security in the region.

INNOVATIVE MATERIAL PROCESSING TECHNIQUES IN PRECISION MANUFACTURING: A REVIEW

Precision manufacturing plays a pivotal role in various industries, demanding high accuracy, efficiency, and quality in the production process. The continual pursuit of innovation in material processing techniques is essential to meet evolving demands and challenges. This review explores the latest advancements and innovations in material processing methods within precision manufacturing. The review encompasses a comprehensive analysis of various innovative material processing techniques, including additive manufacturing, subtractive manufacturing, and hybrid approaches. Additive manufacturing, often referred to as 3D printing, has gained significant attention for its capability to produce complex geometries with high precision. The exploration of novel materials, such as metal alloys, polymers, and composites, expands the applicability of additive manufacturing in diverse industrial sectors. Subtractive manufacturing techniques, such as milling, turning, and grinding, are also undergoing transformative advancements to enhance precision and efficiency. Emerging technologies like abrasive waterjet machining, electrical discharge machining (EDM), and laser machining offer improved accuracy and surface finish while enabling the processing of a wide range of materials, including hard-to-machine alloys and composites. Hybrid manufacturing approaches, combining additive and subtractive techniques, are revolutionizing precision manufacturing by leveraging the strengths of both methods. These hybrid systems enable the production of intricate components with high precision, reduced lead times, and minimized material waste, addressing the challenges of traditional manufacturing processes. Furthermore, the review highlights advancements in process monitoring and control technologies, such as in-process sensing, real-time feedback systems, and adaptive control algorithms, facilitating enhanced quality assurance and productivity in precision manufacturing. The integration of advanced computational tools, simulation techniques, and artificial intelligence further augments the optimization and customization capabilities of material processing techniques, driving efficiency and innovation in precision manufacturing. Overall, this review provides valuable insights into the latest developments and trends in innovative material processing techniques, offering a roadmap for future research directions and applications in precision manufacturing industries.&#x0D; Keywords: Material, Processing, Techniques, Precision, Manufacturing, Review.

Understanding cellulose pyrolysis via ab initio deep learning potential field

Comprehensive and dynamic studies of cellulose pyrolysis reaction mechanisms are crucial in designing experiments and processes with enhanced safety, efficiency, and sustainability. The details of the pyrolysis mechanism are not readily available from experiments but can be better described via molecular dynamics (MD) simulations. However, the large size of cellulose molecules challenges accurate ab initio MD simulations, while existing reactive force field parameters lack precision. In this work, precise ab initio deep learning potentials field (DPLF) are developed and applied in MD simulations to facilitate the study of cellulose pyrolysis mechanisms. The formation mechanism and production rate of both valuable and greenhouse products from cellulose at temperatures larger than 1073 K are comprehensively described. This study underscores the critical role of advanced simulation techniques, particularly DLPF, in achieving efficient and accurate understanding of cellulose pyrolysis mechanisms, thus promoting wider industrial applications.

High performance flow-focusing droplet microreactor. Extractive separation of rare earths as case of study

This work advances the knowledge of the design and manufacture of microdroplet reactors for reactive liquid–liquid systems assisted by advanced simulation techniques (CFD). The mathematical model is based on the integrated analysis of the fluid dynamics for multiphase systems, passive mixing of reactants inside and outside the microdroplet and interfacial reaction rate. To validate the results obtained with the predictive model a spiral microdevice with droplet generation using flow-focusing geometry has been designed and fabricated by additive manufacturing. First, the influence of fluid flowrate, hold-up and viscosity on the droplets frequency and size has been evaluated with the model and assessed experimentally. Next, the performance in the separation of a binary Dysprosium-Lanthanum system has been tested, working with a dispersed aqueous phase containing the rare earth elements (REEs) solution and a continuous organic phase constituted of a solution of the extractant Cyanex® 572 in Shellsol® D70. The extraction experiments have been conducted at residence times between 3 and 60 s to generate aqueous phase monodispersed droplets with high interfacial area that varies between 61.4 and 49.2 cm2·cm−3 depending on the operating conditions. At pH 1, 90 % of dysprosium has been extracted, and almost complete separation of both REEs has been achieved. Very good agreement between simulated and experimental results has been reached with an error lower than 12 %. Therefore, here we provide the tools to design and predict the microdroplet enhanced performance of extractive liquid–liquid microreactors.

Multiplexed near infrared fluorescence lifetime imaging in turbid media.

Fluorescence lifetime imaging (FLI) plays a pivotal role in enhancing our understanding of biological systems, providing a valuable tool for non-invasive exploration of biomolecular and cellular dynamics, both in vitro and in vivo. Its ability to selectively target and multiplex various entities, alongside heightened sensitivity and specificity, offers rapid and cost-effective insights. Our aim is to investigate the multiplexing capabilities of near-infrared (NIR) FLI within a scattering medium that mimics biological tissues. We strive to develop a comprehensive understanding of FLI's potential for multiplexing diverse targets within a complex, tissue-like environment. We introduce an innovative Monte Carlo (MC) simulation approach that accurately describes the scattering behavior of fluorescent photons within turbid media. Applying phasor analyses, we enable the multiplexing of distinct targets within a single FLI image. Leveraging the state-of-the-art single-photon avalanche diode (SPAD) time-gated camera, SPAD512S, we conduct experimental wide-field FLI in the NIR regime. Our study demonstrates the successful multiplexing of dual targets within a single FLI image, reaching a depth of 1cm within tissue-like phantoms. Through our novel MC simulation approach and phasor analyses, we showcase the effectiveness of our methodology in overcoming the challenges posed by scattering media. This research underscores the potential of NIR FLI for multiplexing applications in complex biological environments. By combining advanced simulation techniques with cutting-edge experimental tools, we introduce significant results in the non-invasive exploration of biomolecular dynamics, to advance the field of FLI research.