Search Results (540)

An integrated approach for enhancing microparticle separation efficiency in acoustofluidic lab-on-a-chip systems is presented, combining numerical modeling in COMSOL 6.2 Multiphysics^® with reinforcement learning techniques implemented in Python 3.10.14. The proposed method addresses the limitations of traditional parameter tuning, which is time-consuming and computationally intensive. A simulation framework based on LiveLink™ for COMSOL–Python integration enables the automatic generation, execution, and evaluation of particle separation scenarios. Reinforcement learning algorithms, trained on both successful and failed experiments, are employed to optimize control parameters such as flow velocity and acoustic frequency. Experimental data from over 100 numerical simulations were used to train a neural network, which demonstrated the ability to accurately predict and improve sorting efficiency. The results confirm that incorporating failed outcomes into the reward structure significantly improves learning convergence and model accuracy. This work contributes to the development of intelligent microfluidic systems capable of autonomous adaptation and optimization for biomedical and analytical applications, such as label-free separation of microplastics from biological fluids, selective sorting of soot and ash particles for environmental monitoring, and high-precision manipulation of cells or extracellular vesicles for diagnostic assays. Full article

Aflatoxins, which are potentially genotoxic and carcinogenic substances, are mainly produced by the Aspergillus section Flavi, including Aspergillus flavus and A. parasiticus. Current Aspergillus spp. detection is often based on molecular methods, such as real-time PCR and loop-mediated isothermal amplification (LAMP), targeting genes of the aflatoxin biosynthetic cluster. In this study, we developed a Lab-on-a-Chip (LoC) method based on real-time PCR and on LAMP for the specific detection of aflatoxigenic strains of A. flavus and A. parasiticus from infected hazelnuts. LoC-LAMP and LoC-real-time PCR assays were tested in terms of specificity, sensitivity, speed, and repeatability. The microfluidic chip allowed quick, specific, sensitive, simple, automatized, cheap, and user-friendly detection of aflatoxigenic strains of A. flavus and A. parasiticus. The LoC-LAMP showed a limit of detection (LOD) of 10 fg of DNA, while the LoC-real-time PCR showed a LOD of 10 pg of DNA. Achieving comparable sensitivity to that of LAMP and real-time PCR techniques, both LoC methods developed in this work offer the advantages of automation, minimal sample requirements, reagent requirements, and cost-effectiveness. Overall, the developed methods open the perspective for alternative monitoring of aflatoxigenic fungi in the agri-food industry. Full article

Electrical impedance measurements are traditionally macroscopic screening techniques designed to obtain information about the macroscopic internal structure of biological systems. In order to overcome the limitations that the technology detects, mainly with the bulk properties, a miniaturization is employed by developing a complex microfluidic system to achieve cell-scale information. In this work, a microelectrode array was incorporated into a microfluidic chip, allowing localized Electrochemical Impedance Spectroscopy (EIS) measurements, providing impedance data obtained in the spatial and frequency domains simultaneously. The height of the capillary in the microfluidic system was also systematically modified; hence, three types of channels with heights of 10 $\mu$m, 30 $\mu$m, and 50 $\mu$m were developed and studied. The EIS data collection was implemented using two different strategies (two- and four-electrode techniques). Sensitivity analysis was conducted using a microbead solution, where the linear mapping of the number of microbeads along the channel was achieved by EIS. Based on the findings, a complete overview of each measurement implementation was obtained, which is well explained by the physical background presented in the paper. In the case where the capillary height (10 $\mu$m) is comparable to the diameter of the microbeads (6 $\mu$m), the four-electrode technique detected the beads in a wider frequency range (approximately between 500 Hz and 50 kHz), while the two-electrode technique detected the beads in a narrower frequency range (approximately between 30 kHz and 300 kHz) with correlation greater than 0.9. In all other cases, a medium (or weak) correlation was found between the impedance data and the longitudinal bead distribution. Based on the results, the technology is ready for further development and adaptation for cell culture purposes. Full article

T cells play a pivotal role in cancer research, particularly in immunotherapy, which harnesses the immune system to target malignancies. However, conventional expansion methods face limitations such as high reagent consumption, contamination risks, and difficulties in maintaining suspension cells in dynamic culture environments. This study presents a microfluidic system for long-term culture of non-adherent cells, featuring automated perfusion and image acquisition. The system integrates deep learning-based image analysis, which quantifies cell coverage and estimates cell numbers, and efficiently processes large volumes of data. The performance of this deep learning approach was benchmarked against the widely used Trainable Weka Segmentation (TWS) plugin for Fiji. Additionally, two distinct lab-on-a-chip (LOC) devices were evaluated independently: the commercial ibidi^® LOC and a custom-made PDMS LOC. The setup supported the proliferation of Jurkat cells and primary human T cells without significant loss during medium exchange. Each platform proved suitable for long-term expansion while offering distinct advantages in terms of design, cell seeding and recovery, and reusability. This integrated approach enables extended experiments with minimal manual intervention, stable perfusion, and supports multi-reagent administration, offering a powerful platform for advancing suspension cell research in immunotherapy. Full article

Microfluidic methods are powerful platforms for synthesizing advanced functional materials because they allow for precise control of microscale reaction environments. Microfluidics manipulates reactants in lab-on-a-chip systems to enable the fabrication of highly uniform materials with tunable properties, which are crucial for drug delivery, diagnostics, catalysis, and nanomaterial design. This review emphasizes recent progress in microfluidic technologies for synthesizing functional materials, with a focus on polymeric, hydrogel, lipid-based, and inorganic particles. Microfluidics provides exceptional control over the size, morphology, composition, and surface chemistry of materials, thereby enhancing their performance through uniformity, tunability, hierarchical structuring, and on-chip functionalization. Our review provides novel insights by linking material design strategies with fabrication methods tailored to biomedical applications. We also discuss emerging trends, such as AI-driven optimization, automation, and sustainable microfluidic practices, offering a practical and forward-looking perspective. As the field advances toward robust, standardized, and user-friendly platforms, microfluidics has the potential to increase industrial adoption and enable on-demand solutions in nanotechnology and personalized medicine. Full article

This paper presents an innovative and low-cost approach to the dispensing of multiple liquids on a microfluidic chip with the aim of dispensing liquids in a controlled sequence. The project focused on the design and development of a microfluidic liquid dispensing system that is an integral part of the Lab-on-Chip (LOC). Liquids are often dispensed into LOCs through blisters, syringes, or electric microfluidic pumps, but these can be impractical for Point-of-Care (POC) settings, especially in remote areas. Additionally, incorrect volumes of biochemical reagents and the introduction of reagents outside the sequence can distort the results of the diagnosis. The process undertaken involved designing and 3D printing prototypes of the dispensing system, along with laser cutting and manufacturing the Polymethyl Methacrylate (PMMA) LOC devices intended for receiving the liquids. The proposed novel low-cost dispensing system uses manually operated actuators and cams to disperse metered fluids sequentially to minimise end-user errors at POC settings. Full article

Microfluidic device prototyping demands rapid, cost-effective, and high-precision mould fabrication, yet ultrashort pulsed laser structuring of polymer inserts remains underexplored. This study presents a novel method for fabricating microfluidic mould inserts using femtosecond (fs) laser ablation of polyimide (PI) films, achieving high precision from design to prototype. PI films (250 µm) were structured using a 355 nm fs laser (300 fs, 500 kHz, 0.95 J/cm²) in a photochemically dominated ablation regime and bonded to reusable steel plates. Injection moulding trials with cyclic olefin copolymer (COC) and polymethyl methacrylate (PMMA) were conducted with diverse designs, including concentration gradient generators (CGG), organ-on-chip (OOC) with 20 µm bridges, and double emulsion droplet generators (DEDG) with 100–500 µm channels, ensuring robustness across complex geometries. The method achieved near 1:1 replication (errors < 2%, microchannel height tolerances < 1%, Sa = 0.02 µm in channels, 0.26 µm in laser-structured areas), machining times under 2 h, and mould durability over 100 cycles without significant deterioration. The PI’s heat-retarding effect mimicked variothermal moulding, ensuring complete micro-penetration without specialised equipment. By reducing material costs using PI films and reusable steel plates, enabling rapid iterations within hours, and supporting industry-compatible prototyping, this approach lowers barriers for small-scale labs. It enables rapid prototyping of diagnostic lab-on-chip devices and supports decentralised manufacturing for biomedical, chemical, and environmental applications, offering a versatile, cost-effective tool for early-stage development. Full article

We present a simple, rapid and low-cost multi-layer mold fabrication method for production of polydimethylsiloxane (PDMS) lab-on-chip (LOC) devices. The new approach offers resource-strained researchers access to microfluidic lab-on-chip fabrication for medical diagnostics, food security and environmental monitoring applications. In this work, photomasks were designed on PowerPoint (2021) and printed on Pelikan transparency sheets using a Canon PIXMA iX6840 Inkjet printer. The photomasks were then tested for ultraviolet (UV) transmission and compared to the masks produced for circuit board manufacture. Another low-cost approach for the alignment of multi-exposure masks was also developed and tested by producing three-layer photoresist pyramid-like structures on silicon (Si) wafer using the soft lithography process. Full article

Recent progress in microfluidic technologies has led to the development of compact and highly efficient electrochemical platforms, including lab-on-a-chip (LoC) systems, that integrate multiple testing functions into a single, portable device. Combined with smartphone-based electrochemical devices, these systems enable rapid and accurate on-site detection of food contaminants, including pesticides, heavy metals, pathogens, and chemical additives at farms, markets, and processing facilities, significantly reducing the need for traditional laboratories. Smartphones improve the performance of these platforms by providing computational power, wireless connectivity, and high-resolution imaging, making them ideal for in-field food safety testing with minimal sample and reagent requirements. At the core of these systems are electrochemical biosensors, which convert specific biochemical reactions into electrical signals, ensuring highly sensitive and selective detection. Advanced nanomaterials and integration with Internet of Things (IoT) technologies have further improved performance, delivering cost-effective, user-friendly food monitoring solutions that meet regulatory safety and quality standards. Analytical techniques such as voltammetry, amperometry, and impedance spectroscopy increase accuracy even in complex food samples. Moreover, low-cost engineering, artificial intelligence (AI), and nanotechnology enhance the sensitivity, affordability, and data analysis capabilities of smartphone-integrated electrochemical devices, facilitating their deployment for on-site monitoring of food and agricultural contaminants. This review explains how these technologies address global food safety challenges through rapid, reliable, and portable detection, supporting food quality, sustainability, and public health. Full article

Enzyme-based biosensors have emerged as a transformative technology, leveraging the specificity and catalytic efficiency of enzymes across various domains, including medical diagnostics, environmental monitoring, food safety, and industrial processes. These biosensors integrate biological recognition elements with advanced transduction mechanisms to provide highly sensitive, selective, and portable solutions for real-time analysis. This review explores the key components, detection mechanisms, applications, and future trends in enzyme-based biosensors. Artificial enzymes, such as nanozymes, play a crucial role in enhancing enzyme-based biosensors by mimicking natural enzyme activity while offering improved stability, cost-effectiveness, and scalability. Their integration can significantly boost sensor performance by increasing the catalytic efficiency and durability. Additionally, lab-on-a-chip and microfluidic devices enable the miniaturization of biosensors, allowing for the development of compact, portable devices that require minimal sample volumes for complex diagnostic tests. The functionality of enzyme-based biosensors is built on three essential components: enzymes as biocatalysts, transducers, and immobilization techniques. Enzymes serve as the biological recognition elements, catalyzing specific reactions with target molecules to produce detectable signals. Transducers, including electrochemical, optical, thermal, and mass-sensitive types, convert these biochemical reactions into measurable outputs. Effective immobilization strategies, such as physical adsorption, covalent bonding, and entrapment, enhance the enzyme stability and reusability, enabling consistent performance. In medical diagnostics, they are widely used for glucose monitoring, cholesterol detection, and biomarker identification. Environmental monitoring benefits from these biosensors by detecting pollutants like pesticides, heavy metals, and nerve agents. The food industry employs them for quality control and contamination monitoring. Their advantages include high sensitivity, rapid response times, cost-effectiveness, and adaptability to field applications. Enzyme-based biosensors face challenges such as enzyme instability, interference from biological matrices, and limited operational lifespans. Addressing these issues involves innovations like the use of synthetic enzymes, advanced immobilization techniques, and the integration of nanomaterials, such as graphene and carbon nanotubes. These advancements enhance the enzyme stability, improve sensitivity, and reduce detection limits, making the technology more robust and scalable. Full article

The rapid rise of antibiotic-resistant bacteria (ABR) presents an urgent global health challenge, necessitating the development of efficient and scalable diagnostic technologies. Electrochemical biosensors have emerged as a promising solution, offering high sensitivity, specificity, and adaptability for point-of-care applications. These innovative platforms utilize bio-recognition elements, advanced electrode materials, microbial enzymes, and redox-active metabolites to identify antibiotic resistance profiles at a molecular level. Recent progress in microfluidics and lab-on-a-chip systems has enabled real-time, high-throughput antimicrobial susceptibility testing, significantly improving diagnostic precision and speed. This review aims to critically evaluate recent advances in electrochemical biosensing strategies for detecting ABR, identify key challenges, and propose future directions to enhance clinical applicability. Key developments include bio-receptor-based detection strategies, novel electrode surfaces, and multiplexed platforms integrated with microfluidic systems. Additionally, this review examines essential biomarkers for detecting antibiotic resistance and explores key challenges, including variability in biomarker expression and sensor reproducibility. It also highlights practical barriers to clinical implementation, such as cost constraints and scalability concerns. By presenting innovative approaches, such as cost-effective material alternatives, advanced analytical techniques, and portable biosensing systems, this review outlines a strategic pathway for enhancing the accessibility and effectiveness of electrochemical biosensors in antibiotic resistance management. Full article

Infectious diseases poses a growing public health challenge. The COVID-19 pandemic has further emphasized the urgent need for rapid, accessible diagnostics. This study presents the development of an integrated, flexible point-of-care (POC) diagnostic system for the rapid detection of Corynebacterium diphtheriae, the pathogen responsible for diphtheria. The system comprises a microfluidic polymerase chain reaction (micro-PCR) device and an electrochemical DNA biosensor, both fabricated on flexible substrates. The micro-PCR platform offers rapid DNA amplification overcoming the time limitations of conventional thermocyclers. The biosensor utilizes specific molecular recognition and an electrochemical transducer to detect the amplified DNA fragment, providing a clear and direct indication of the pathogen’s presence. The combined system demonstrates the effective amplification and detection of a gene fragment from a toxic strain of C. diphtheriae, chosen due to its increasing incidence. The design leverages lab-on-a-chip (LOC) and microfluidic technologies to minimize reagent use, reduce cost, and support portability. Key challenges in microsystem design—such as flow control, material selection, and reagent compatibility—were addressed through optimized fabrication techniques and system integration. This work highlights the feasibility of using flexible, integrated microfluidic and biosensor platforms for the rapid, on-site detection of infectious agents. The modular and scalable nature of the system suggests potential for adaptation to a wide range of pathogens, supporting broader applications in global health diagnostics. The approach provides a promising foundation for next-generation POC diagnostic tools. Full article

Acoustic tweezers, as advanced micro/nano manipulation tools, play a pivotal role in biomedical engineering, microfluidics, and precision manufacturing. However, piezoelectric-based acoustic tweezers face performance limitations due to multi-physical coupling effects during microfabrication. This study proposes a novel approach using injection molding with embedded electronics (IMEs) technology to fabricate piezoelectric micro-ultrasonic transducers with micron-scale precision, addressing the critical issue of acoustic node displacement caused by thermal–mechanical coupling in injection molding—a problem that impairs wave transmission efficiency and operational stability. To optimize the IME process parameters, a hybrid multi-objective optimization framework integrating NSGA-II and MOPSO is developed, aiming to simultaneously minimize acoustic node displacement, volumetric shrinkage, and residual stress distribution. Key process variables—packing pressure (80–120 MPa), melt temperature (230–280 °C), and packing time (15–30 s)—are analyzed via finite element modeling (FEM) and validated through in situ tie bar elongation measurements. The results show a 27.3% reduction in node displacement amplitude and a 19.6% improvement in wave transmission uniformity compared to conventional methods. This methodology enhances acoustic tweezers’ operational stability and provides a generalizable framework for multi-physics optimization in MEMS manufacturing, laying a foundation for next-generation applications in single-cell manipulation, lab-on-a-chip systems, and nanomaterial assembly. Full article

The widespread and persistent occurrence of micropollutants—such as pesticides, pharmaceuticals, heavy metals, personal care products, microplastics, and per- and polyfluoroalkyl substances (PFAS)—has emerged as a critical environmental and public health concern, necessitating the development of highly sensitive, selective, and field-deployable detection technologies. Microfluidic sensors, including biosensors, have gained prominence as versatile and transformative tools for real-time environmental monitoring, enabling precise and rapid detection of trace-level contaminants in complex environmental matrices. Their miniaturized design, low reagent consumption, and compatibility with portable and smartphone-assisted platforms make them particularly suited for on-site applications. Recent breakthroughs in nanomaterials, synthetic recognition elements (e.g., aptamers and molecularly imprinted polymers), and enzyme-free detection strategies have significantly enhanced the performance of these biosensors in terms of sensitivity, specificity, and multiplexing capabilities. Moreover, the integration of artificial intelligence (AI) and machine learning algorithms into microfluidic platforms has opened new frontiers in data analysis, enabling automated signal processing, anomaly detection, and adaptive calibration for improved diagnostic accuracy and reliability. This review presents a comprehensive overview of cutting-edge microfluidic sensor technologies for micropollutant detection, emphasizing fabrication strategies, sensing mechanisms, and their application across diverse pollutant categories. We also address current challenges, such as device robustness, scalability, and potential signal interference, while highlighting emerging solutions including biodegradable substrates, modular integration, and AI-driven interpretive frameworks. Collectively, these innovations underscore the potential of microfluidic sensors to redefine environmental diagnostics and advance sustainable pollution monitoring and management strategies. Full article