Search Results (2,613)

Microfluidic electrokinetic flows play a central role in applications such as lab-on-a-chip diagnostics, microelectronics cooling, and biomedical sample manipulation. These systems involve intricate heat transfer processes, including Joule heating from ionic currents, temperature-driven flow instabilities, and coupled thermal–fluid interactions, that crucially affect device performance, reliability, and scalability. Current challenges include non-equilibrium charge dynamics, incomplete thermophysical property data for complex fluids, and thermal crosstalk in integrated platforms. This review summarizes the literature published over the past 20 years, with occasional reference to earlier work, covering the fundamental mechanisms of heat generation and dissipation in electrokinetic microflows; analytical, numerical, and experimental approaches for characterizing thermal effects; and discussion on the limitations and application-driven opportunities. It also highlights open questions and future research directions and offers a comprehensive view of design principles and guidelines for developing robust, thermally optimized electrokinetic microfluidic technologies. Full article

Central nervous system (CNS) disorders represent a growing healthcare burden, and various drugs are developed for their treatment. However, the blood–brain barrier (BBB) prevents over 98% of therapeutics from reaching brain tissue. Intranasal delivery provides a promising alternative by exploiting olfactory and trigeminal nerve pathways to circumvent the BBB. This review surveys recent advances in nose-to-brain delivery technologies, from carrier design to evaluation methods. Polymeric and lipid-based nanocarriers show enhanced mucosal penetration and prolonged residence time, and microneedle platforms further enable controlled drug release with minimal discomfort. To evaluate these delivery strategies, sensor-integrated organ-on-chip models provide more physiologically relevant testing than static cultures. Although persistent challenges such as rapid mucociliary clearance and formulation stability remain, combining nanotechnology with microfluidic devices and computational modeling shows potential for developing patient-specific therapeutics. Full article

Surface Acoustic Wave (SAW) technology, long central to analog signal processing and RF filtering, is undergoing a major renewal. Driven by advances that decouple SAWs from traditional piezoelectric materials and fixed-function devices, the field is gaining unprecedented control over acoustic, optical, and electronic interactions at the micro and nanoscale. This review synthesizes these developments across four fronts: new physical mechanisms for SAW manipulation, emerging material platforms, ranging from thin films to 2D systems, along with reconfigurable device architectures and circuits, and the expanding landscape of applications they enable. Optical methods are reshaping how SAWs are generated and controlled, bypassing the limits of conventional electromechanical coupling. Coherent optical excitation of high-Q SAW cavities via Brillouin-like optomechanical interactions now grants access to modes in non-piezoelectric substrates such as diamond and silicon, while on-chip SAW excitation in photonic waveguides through backward stimulated Brillouin scattering opens new integrated sensing routes. In parallel, magneto-acoustic experiments have revealed nonreciprocal SAW diffraction from resonant scattering in magnetoelastic gratings. On the device side, ZnO thin-film transistors integrated on LiNbO₃ exploit acoustoelectric coupling to realize voltage-tunable phase shifters; UHF Z-shaped delay lines achieve high sensitivity in a compact footprint; and parametric synthesis of wideband, multi-stage lattice filters targets 5G-class performance. Atomistic simulations show that SAW propagation in 2D MXene films can be engineered via surface terminations, while aerosol jet printing and SAW-assisted particle patterning provide agile, cleanroom-light fabrication of microfluidic and magnetic components. These advances enable applications ranging from hybrid quantum systems and quantum links to lab-on-a-chip particle control, SBS-based and UHF sensing, reconfigurable RF front-ends, and soft robotic actuators based on patterned magnetic composites. At the same time, optical techniques offer non-contact probes of dissipation, and MXenes and other emerging materials open new regimes of acoustic control. Conclusively, they are transforming SAW technology into a versatile, programmable platform for mediating complex interactions in next-generation electronic, photonic, and quantum systems. Full article

Biofilms rapidly form on medical devices such as urinary catheters and surgical materials. These biofilms compromise patient safety and undermine infection prevention and control (IPC). Biofilms also reduce the effectiveness of antibiotics and disinfectants. As a result, they increase healthcare-associated infections and increase costs through device failure and the need for maintenance or replacement. Researchers are increasingly exploring biosurfactants (BSs) as surface coatings and cleaning additives to prevent microbial attachment and disrupt early biofilm formation on medical devices and healthcare-related surfaces. This review examines the translational potential of biosurfactants as preventive, disruptive, and adjunctive antibiofilm agents for medical devices and healthcare-related surfaces. Literature evidence on glycolipids (rhamnolipids, sophorolipids) and lipopeptides (surfactin) from static, flow-based, and microfluidic in vitro models that used clinically relevant materials, such as silicone and polydimethylsiloxane (PDMS), were examined. In our literature search, we focused on pathogens central to IPC, such as Staphylococcus aureus, Pseudomonas aeruginosa, Enterococcus spp., and Candida spp., and it was generally noted that BSs reduced microbial adhesion and delayed early biofilm formation on medical devices and healthcare-related surfaces. Significant evidence also suggests that they partially disrupt biofilms and improve antimicrobial penetration when co-applied, mainly through membrane disruption, destabilization of extracellular substances, interfering with quorum sensing, and synergistic and/or antagonistic interactions with other molecules. Their performance varied with class, formulation, hydrodynamic conditions, and microbial composition. BSs function better as preventive and adjunctive IPC tools than stand-alone antimicrobial agents and can help to reduce biofilm formation on devices and improve surface disinfection. However, translating this promise into practice demands more robust data on long-term safety, stability, and product quality. Full article

Microfluidics enables spatially controlled nanostructure synthesis by coupling confined flows with surface reactions. In this work, we study how geometry-induced laminar microenvironments govern the in situ formation of Au and Ag nanostructures inside 3D-printed microfluidic reactors. Proof-of-concept fish-scale valves were fabricated by masked stereolithography in three architectures designed to define three recurring zones in the microreactor, inside the fish-scales (zone 1), between the fish-scales (zone 2), and along the rows of fish-scales (zone 3). A Cu thin film was deposited on the inner walls of the channel to serve as the sacrificial surface for galvanic replacement using AgNO₃ or HAuCl₄. Distinct 0D, 1D, and 2D nanostructures were simultaneously obtained in a zone-dependent manner across the valves, including nanoparticle and nanopore-rich regions, nanowires, nanoflakes and clustered 2D features. COMSOL simulations were used to solve the Navier–Stokes equation and extract specific-zone flow descriptors, including Reynolds number, velocity, and wall shear stress, and relate them to the nanostructure morphologies observed by SEM. The flow throughout the devices is strongly laminar, with local Reynolds numbers up to 0.04, exhibiting systematic spatial gradients imposed by the valve geometry. These results provide a design-guided route to tune nanostructure morphology through microchannel architecture under constant global operating conditions. Full article

The implementation of stringent regulatory policies for foodborne pathogens necessitates ultra-sensitive analytical methods. Digital detection, characterized by absolute quantification and tolerance to complex matrices, serves as a robust approach for food safety monitoring. This review summarizes recent advances in digital detection for foodborne pathogens, including nucleic acid amplification-based platforms such as droplet digital PCR and digital isothermal amplification, as well as emerging preamplification-free approaches based on enzyme-mediated signal conversion, functional nanomaterials, and microfluidic devices. We also profile the applications of digital detection technologies for achieving highly specific and accurate detection of foodborne pathogens and discuss their capabilities in viable bacteria quantification, antimicrobial resistance analysis, and multiplex detection. We finally discuss emerging trends, including partition-free digital detection and artificial intelligence-assisted analysis. These advances are expected to promote the development of intelligent and data-driven food safety surveillance strategies. Full article

Artificial intelligence (AI) has become a transformative tool in the field of molecular biosensing, enabling data-driven optimization in sensor design, signal processing, and real-time monitoring. AI promotes the discovery of biomarkers, the design of high-affinity receptors, and the rational engineering of sensing materials, thereby enhancing sensitivity, specificity, and detection accuracy. In the development of biosensors, AI-assisted strategies have accelerated the identification of novel molecular targets, guided the design of proteins and aptamers with enhanced binding performance, and optimized plasmonic and nanophotonic structures through forward prediction and inverse design frameworks. The integration of artificial intelligence has significantly enhanced the performance of various biosensing platforms, including optical, electrochemical, and microfluidic biosensors. It also enabled automatic feature extraction, noise reduction, dimensionality reduction, and multimodal data fusion, overcoming the challenges posed by complex signals, environmental interference, and device variations. These capabilities are particularly crucial for wearable molecular biosensors, as low signal strength, motion artifacts, and fluctuations in physiological conditions impose strict requirements on robustness and real-time reliability. This review systematically summarizes the latest advancements in AI-assisted molecular biosensors, highlighting representative sensing strategies and algorithms for wearable and real-time monitoring, and discusses the current challenges and future development opportunities of intelligent biosensing technologies. Full article

Droplet microfluidics has been widely used in biological, chemical, and medical research owing to its advantages of miniaturization, high throughput, and low reagent consumption. However, limited sensitivity and optical path length in on-chip absorbance detection remain major challenges for droplet-based microfluidic analysis. Traditional absorbance detection suffers from low sensitivity due to the extremely short optical path in microfluidic channels, while existing optical path extension methods have drawbacks such as complex fabrication, easy droplet rupture, or strict incident angle requirements. To address these issues, this study developed a droplet microfluidic absorbance detection platform integrating optical fibers, on-chip micromirrors, external fluidic actuation, and an absorbance detection module. Microchannel sidewalls filled with low-melting-point metal act as mirrors; the multi-reflection optical path, combined with optical fibers and micromirrors, compensates for insufficient light manipulation and effectively extends the absorption path length, improving sensitivity and accuracy. Using this method, the detection limit for methylene blue solution was 20 μM, and the sensitivity for Escherichia coli (E. coli) suspension was doubled compared with traditional Nanodrop OD600 measurement. This device features low fabrication difficulty and cost and stable detection, providing a proof-of-concept strategy for enhanced absorbance detection in droplet microfluidic systems. Full article

The design of millimeter-scale micro-turbine blades is challenging due to conflicting requirements: achieving aerodynamic performance while remaining compatible with microfabrication, and exploring high-dimensional morphological design spaces without prohibitive computational cost. To address these challenges, this study proposes an intelligent framework for the design and optimization of the three-dimensional blade profile of a 3 mm diameter micro-turbine. The blade morphology is parameterized using 22 variables, ensuring geometric feasibility for micro-EDM (Electrical Discharge Machining) fabrication. A physics-informed neural network (PINN) surrogate model, efficiently trained through a two-stage active learning strategy combining KD-tree exploration and residual-based sampling, provides accurate predictions of flow fields. Multi-objective optimization using Non-dominated Sorting Genetic Algorithm II (NSGA-II) is then performed to maximize torque and thrust. Experimental results show that the optimized blade achieves a 38.6% increase in rotational speed while retaining 75.1% of thrust at 0.2 MPa inlet pressure, validating the framework’s effectiveness. This methodology offers a systematic solution for designing microfluidic devices characterized by high-dimensional parameters and high-fidelity simulation requirements. Full article

Spiral inertial microfluidic devices provide a simple, high-throughput approach for size-based particle separation; however, translating PDMS-optimized designs into monolithic, fully enclosed 3D-printed channels is often limited by printability and post-print channel clearing. In our previous PDMS study, a $400\times 120\mu \mathrm{m}$ spiral achieved high separation performance after computational optimization and experimental validation. To translate this high-performing PDMS concept into a faster and more cost-effective manufacturing approach, the same separation principle is transferred to a fully 3D-printed, closed-channel spiral device, and the geometry is re-optimized around manufacturability constraints. Printing trials showed that enclosed channels at $400\times 120\mu \mathrm{m}$ and $600\times 180\mu \mathrm{m}$ could not be cleared reliably due to trapped resin and frequent blockage, most often near the inner-outlet region. In contrast, $800\times 240\mu \mathrm{m}$ and $1200\times 360\mu \mathrm{m}$ channels were printed and flushed successfully, and $800\times 240\mu \mathrm{m}$ was selected as the smallest reproducibly functional cross-section. Particle-tracking simulations were then used to re-optimize spiral development length, showing that a 4-turn device provides limited collection for $12\mu \mathrm{m}$ targets (10%), intermediate lengths (5–7 turns) improve collection to 50%, and an 8-turn spiral achieves complete large-particle collection (100%) across tested target sizes (12–$24\mu \mathrm{m}$) while reducing small-particle crossover. Experimental validation of the 8-turn $800\times 240\mu \mathrm{m}$ device at $Q=6\mathrm{m}\mathrm{L} {\min }^{-1}$ using fluorescent polystyrene particles ($18\mu \mathrm{m}$ target; $6\mu \mathrm{m}$ background) yielded an average collection efficiency of 84% and an inner-outlet purity of 92%. Overall, these results demonstrate that spiral inertial separation can be retained in a monolithic 3D-printed format when the design is re-optimized around the smallest reliably clearable enclosed cross-section and sufficient spiral development length. Full article

Deterministic lateral displacement (DLD) and related microfluidic sorting devices are typically evaluated based on the size distributions of particles collected at each outlet, even though the more relevant measure of performance is the probability that a particle of a given size ends up in a specific outlet. Here, we use Bayes’ rule to infer these size-dependent routing probabilities from experimentally accessible measurements of outlet size distributions, inlet size distributions, and outlet subpopulations. Using a DLD array designed to separate microspheres and microsphere clusters, we determine the probabilities that particles of different sizes are directed to each outlet and define a probabilistic critical size ($D_C$) at which particles are equally likely to follow a zigzag and a displacement trajectory. Based on this, we calculate key performance metrics, purity, and yield. Our results demonstrate high-quality separations and show that routing probabilities provide a general and robust framework for benchmarking microfluidic sorting devices beyond traditional outlet-based analyses. Full article

Novel, accurate molecular diagnostics are driving new advances across medicine, public health, and environmental monitoring. Surface-enhanced Raman spectroscopy (SERS) nanotags are powerful platforms for ultrasensitive, multiplexed, and quantitative detection of molecular targets. This review focuses on indirect sensing strategies, where SERS nanotags act as signal transducers, resulting in enhanced and unique Raman spectra upon binding of target analytes (high specificity) and allowing for ultralow limits of detection. These indirect SERS sensors typically consist of a plasmonic core, a Raman reporter molecule, and a ligand that targets the analyte of interest. Each of these components contributes to the sensitivity, stability, and selectivity of the system. Rational design of SERS nanotags requires balancing enhancement efficiency with reproducibility, biocompatibility, and assay integration. The choice of reporter molecules, for instance, governs spectral uniqueness and enables multiplexed detection of multiple analytes within a single sample. Recent advances in artificial intelligence and machine learning are accelerating nanotag development by enabling predictive control over nanostructure geometry, composition, and optical response. SERS nanotags are increasingly being integrated into diagnostic formats, such as lateral flow assays and microfluidic devices, offering both qualitative and quantitative analysis at the point of care. This review provides an overview of key design principles, common strategies for nanostructure functionalization and stabilization, and emerging biosensing applications, serving as a practical guide for researchers seeking to design and implement SERS nanotags. Full article

The integration of whole-cell biosensors in miniaturized measuring devices to exploit synergetic effects as small, rapid, cost-effective, sensitive, and highly specific platforms with point-of-care applicability was often discussed in recent years and many different setups have been presented to date. In many cases these setups were envisaged as powerful systems in their respective fields; however, the anticipated success often failed to materialize, and the systems remained a proof-of-concept. We elaborate on the hurdles and possible challenges that have to be overcome for the successful development and application of such systems. Further, we critically discuss and rank the impact of different challenges during system development, application, and commercialization. Finally, we point out possible future applications and conclude future perspectives for whole-cell biosensors integrated into microfluidic platforms. Full article

Molecular point-of-care testing (POCT) for respiratory infections has undergone remarkable advancement over the past two decades, driven by technological innovation and urgent clinical needs highlighted by the COVID-19 pandemic. This comprehensive systematic review was conducted following PRISMA 2020 guidelines, synthesizing evidence from 254 peer-reviewed studies published between 2006 and 2026, with detailed analysis of the 30 most relevant papers selected through a rigorous four-stage screening process. The review examines the evolution of molecular POCT technologies, including reverse transcription polymerase chain reaction (RT-PCR), loop-mediated isothermal amplification (LAMP), recombinase polymerase amplification (RPA), and CRISPR-based detection systems. Key findings demonstrate that modern molecular POCT platforms achieve diagnostic performance comparable to laboratory-based testing, with sensitivities ranging from 88% to 100% and specificities from 98% to 100%, while delivering results in 15 to 80 min. These technologies enable rapid, accurate detection of major respiratory pathogens, including SARS-CoV-2, influenza A/B, respiratory syncytial virus (RSV), and atypical bacteria. The integration of microfluidic systems, portable devices, and smartphone-based analysis has expanded access to testing in resource-limited settings, emergency departments, and wearable platforms. This review provides critical insights for clinicians, researchers, and policymakers regarding the current state, clinical applications, and future directions of molecular POCT for respiratory infections. Full article

Additive Manufacturing (AM) and Wearable Technologies (WT) have rapidly evolved over the past decade. AM offers highly customisable fabrication, while WT enables minimally invasive health monitoring. The intersection of these fields presents emerging opportunities in biomedical and engineering domains. This study aims to map the scientific landscape of AM–WT research between 2015 and 2025 through a comprehensive bibliometric analysis. A total of 718 peer-reviewed publications were extracted from Web of Science (WoS), Scopus, and PubMed, following PRISMA-ScR guidelines. Using RStudio and the Bibliometrix package, analyses included co-authorship, citation trends, keyword co-occurrence, and thematic mapping. Custom author disambiguation scripts enhanced data quality and reliability. An annual publication growth of 24.89% was observed, with notable increases after 2020. Core themes included 3D printing, biosensors, microfluidics, and organ-on-a-chip devices. A shift from manufacturing-oriented research to biomedical integration is evident. Research output is dominated by the US, China, and South Korea, with moderate but not yet highly internationalised collaboration. The field of AM–WT research is undergoing a decisive transition from fabrication-focused studies to interdisciplinary, application-driven innovations. This shift is marked by increasing integration in healthcare and bioelectronics, yet hindered by regional imbalances and thematic gaps. Addressing these will be critical to advancing global impact. This study offers a cross-database bibliometric overview of AM–WT research. By combining three major data sources, it provides enhanced coverage and introduces novel analytical dimensions to guide future interdisciplinary efforts in personalised healthcare and wearable device innovation. Full article