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Optical biosensors are indispensable in medical and environmental diagnostics, yet existing approaches are fundamentally limited in their sensitivity due to ensemble-averaged measurements. Digital biosensing has emerged as a promising solution for resolving individual binding events, thereby providing signals at very low analyte concentrations down to the single-molecule level. Here, we present a novel concept for digital optical biosensing empowered by dielectric Mie voids, combining nanoparticle-based contrast enhancement and deep learning for ultrasensitive biomarker detection. The resonantly trapped light in the air cavities of the periodic Mie void arrays ensures strong overlap between the near-fields and the single gold nanoparticles that are captured on the surface in the presence of the protein biomarker. Remarkably, this strong interaction creates high-contrast digital signals for the precise counting of single nanoparticles located both within and outside the voids, yielding efficient use of the entire sensor area for high sensitivity. We employ deep-ultraviolet (DUV) lithography for the scalable and low-cost production of Mie voids in silicon wafers and automated image a

Droplet microlasers, as promising tools for biophotonics and biomedical sciences, have witnessed rapid advances due to their flexible reconfigurability, high sensitivity to stimuli, and label-free biosensing ability. However, designing these biosensors with simultaneously critical properties of low lasing threshold, high spectral purity, and ultimate sensitivity remains challenging. Here, we propose a versatile strategy to build liquid photonic molecules (LPMs) that combine all these features in a single device. We find that through tailoring the spectral Vernier overlap in size-mismatched droplets, this device enables single-mode lasing with a low threshold of ~610 nJ mm-2. The LPM lasers are engineered for dynamic tunability using a molecular isomerization strategy, which induces spectral mode hopping and thus yields a nearly ten-fold enhancement in spectral sensitivity over single droplets. Moreover, by leveraging the self-referenced intensity response of the LPM lasing modes, we demonstrate a three-orders-of-magnitude enhancement in biomolecular sensing, with a detection limit of 30 aM and a dynamic range spanning nine orders of magnitude. Our work offers exciting prospects for

Surface functionalization plays a decisive role in the performance of biosensors, as it governs the efficiency and stability of biomolecule immobilization at the sensor interface and, consequently, the overall performance of the biosensing platforms. In this work, we present a comparative study of three organosilane chemistries - APTES, APDMS, and CPTES - applied to a SiO2 terminated 1D photonic crystal able to sustain Bloch surface waves and designed to operate as optical biosensors in both label free and fluorescence enhanced modes. Each chemistry was evaluated through a standardized label-free protocol based on the interaction between immobilized SARS CoV 2 spike protein and its corresponding antibodies, enabling quantitative assessment of binding efficiency, nonspecific adsorption, and signal repeatability. CPTES exhibited the most favorable balance between specific signals, reduced variability, and low nonspecific adsorption. The three chemistries were subsequently tested in fluorescence mode for the detection of anti SARS CoV 2 IgG antibodies in human serum, demonstrating the suitability of BSW enhanced fluorescence for rapid serological analysis. Overall, the study identifie

This study presents a rigorous comparative analysis of two label-free optical biosensing platforms, Bloch surface wave (BSW) and microring resonator (MRR), for the detection of SARS-CoV-2 antibodies in human serum. To ensure direct comparability, a new BSW readout system was established alongside an existing MRR platform, allowing assays to be conducted under nearly identical experimental conditions. Both sensors were functionalized with various SARS-CoV-2 Spike and Nucleocapsid protein variants to capture specific host antibodies. The results demonstrate that both platforms provide rapid, quantitative, and sensitive detection of anti-Spike and anti-Nucleocapsid antibodies without the need for secondary labels. Furthermore, the platforms show excellent agreement with longitudinal serology benchmarks and high repeatability across different biochip batches. This work establishes both BSW and MRR technologies as powerful, low-cost candidates for next-generation clinical diagnostics and serological surveillance.

The discovery of synthetically accessible organic semiconductors with exceptional performance remains a critical bottleneck in materials science. While these materials offer compelling advantages - structural modularity, mechanical flexibility, and cost-effective solution processing - for applications in photovoltaics and biosensors, identifying candidates that balance high efficiency with practical synthesis presents significant challenges. To address this challenge, we developed a high-throughput screening approach using 17 458 molecules from the PubChemQC B3LYP/6-31G*//PM6 dataset. Our strategy employs a composite metric, PCESAScore = PCE - SAScore, which systematically balances power conversion efficiency (PCE) predictions from the Scharber model against synthetic accessibility scores. This approach successfully identified seven multi-functional candidates that demonstrate both exceptional photovoltaic performance (PCE up to 36.1 %) and strong protein-binding affinity for biosensing applications. Notably, molecule 4550 emerged as the optimal candidate, exhibiting a ligand efficiency of 0.340 kcal/mol/heavy atom with 100 % target promiscuity. Our computational framework integrat

We present a numerical study of a divergent-beam Kretschmann surface plasmon resonance (SPR) platform for multiplexed malaria biosensing. A Powell-lens-generated angular fan enables camera-based angular interrogation of spatially separated regions of interest on a single Au film, thereby removing the need for mechanical scanning. The framework combines transfer-matrix modelling of the prism/Au multilayer with an effective-adlayer description of biomolecular binding at the biofunctional interface. As a representative dual-biomarker case, we consider plasmodium lactate dehydrogenase (pLDH) and histidine-rich protein 2 (HRP-2). Benchmarking of the N-SF11/Au (45 nm) baseline against published water/glycerol data reproduces the characteristic resonance positions and yields a bulk angular sensitivity of $73.2181 \,^\circ \text{RIU}^{-1}$. With representative aptamer-like and antibody-like recognition layers, the relevant sensing states remain within $54^\circ$ to $57^\circ$ and produce distinct, detector-resolvable responses. Combining the optical model with effective-medium and Langmuir binding descriptions gives model-based detection limits of approximately $5.5\,\text{ng mL}^{-1}$ for

In the last decade, researchers have increasingly explored using biosensing technologies for music-based affective regulation and stress management interventions in laboratory and real-world settings. These systems -- including interactive music applications, brain-computer interfaces, and biofeedback devices -- aim to provide engaging, personalized experiences that improve therapeutic outcomes. In this scoping and mapping review, we summarize and synthesize systematic reviews and empirical research on biosensing systems with potential applications in music-based affective regulation and stress management, identify gaps in the literature, and highlight promising areas for future research. We identified 28 studies involving 646 participants, with most systems utilizing prerecorded music, wearable cardiorespiratory sensors, or desktop interfaces. We categorize these systems based on their biosensing modalities, music types, computational models for affect or stress detection and music prediction, and biofeedback mechanisms. Our findings highlight the promising potential of these systems and suggest future directions, such as integrating multimodal biosensing, exploring therapeutic me

Quantum sensing with nitrogen-vacancy (NV) centers in diamond promises to revolutionize biological research and medical diagnostics. Thanks to their high sensitivity, NV sensors could, in principle, detect specific binding events with metabolites and proteins in a massively parallel and label-free way, avoiding the complexity of mass spectrometry. Realizing this vision has been hindered by the lack of quantum sensor arrays that unite high-density spatial multiplexing with uncompromising biochemical specificity. Here, we introduce a scalable quantum biosensing platform that overcomes these barriers by integrating the first multiplexed DNA microarray directly onto a subnanometer antifouling diamond surface. The 7x7 DNA array, patterned onto a diamond chip, enables simultaneous detection of 49 distinct biomolecular features with high spatial resolution and reproducibility, as verified by fluorescence microscopy. Molecular recognition is converted into a quantum signal via a target-induced displacement mechanism in which hybridization removes a Gd$^{3+}$-tagged DNA strand, restoring NV center spin relaxation times (T$_1$) and producing a binary quantum readout. This platform establishe

Accurate, label-free quantification of multiple analytes in complex biological media remains a major challenge due to limited multiplexing, signal cross-correlations, and inconsistency across sensor samples and measurement runs. We introduce a multiplexed whispering-gallery-mode (WGM) biosensing framework that overcomes these barriers by jointly advancing photonic integration and data analytics. Our glass-chip platform enables massive, parallelized and flexible multiplexing of >10000 microresonators organized into up to 100 sensing channels, with universal and modular chip design and detection hardware, while maintaining loaded Q-factors of 10^6. Our novel hybrid deep-learning framework BioCCF that integrates domain adaptation with cross-channel fusion enables harmonization of responses across sensing chips and extraction of nonlinear correlations in complex mixtures. Using a highly heterogeneous dataset comprising over 200 hours of sensing data acquired from nine chips with different channel configurations, biological replicates, and repeated regeneration cycles, we demonstrate recalibration-free identification of solution (99.3\% accuracy) and quantification of immunoglobulin

Photoelectrochemical (PEC) biosensors exhibit significant potential for biomolecule detection due to their high sensitivity and low background noise. However, their performance is severely constrained by the rapid recombination of photogenerated charge carriers. This study innovatively introduces a non-contact magnetic modulation strategy to suppress electron-hole recombination by manipulating carrier spin states, thereby significantly enhancing photoelectric conversion efficiency. Building on this mechanism, we developed a novel magnetically modulated PEC biosensing platform based on the MXenes/cobalt-doped titanium dioxide (Co-TiO2) heterostructure. This platform achieved ultrasensitive detection of protein kinase A (PKA) activity. Compared to an identical probe-modified biosensor without magnetic field application, the developed platform demonstrated a 68.75% enhancement in detection sensitivity and achieved an ultralow detection limit for PKA of 0.00016 U/mL. It also exhibited a wide linear range from 0.005 to 80 U/mL. This research not only provides a novel methodology for kinase activity analysis but also pioneers the innovative strategy of magnetic modulation for enhanced PE

Optical biosensors based on micro-/nano-fibers are highly valuable for probing and monitoring liquid environments and bioactivity. Most of current optical biosensors, however, are still based on glass, semiconductors, or metallic materials, which might be not fully suited for biologically-relevant environments. Here, we introduce biocompatible and flexible microfibers from Lotus silk as micro-environmental monitors that exhibit waveguiding of intrinsic fluorescence as well as of coupled light. These features make single-filament monitors excellent building blocks for a variety of sensing functions, including pH-probing and detection of bacterial activity. These results pave the way for the development of new and entirely eco-friendly, potentially multiplexed biosensing platforms.

We present a method where a bioactive functional layer on an electrically conductive thin film with high sheet resistance can be effectively used for complementary electrochemical impedance spectroscopy biosensing. The functional layer's properties, such as double-layer capacitance and charge-transfer resistance, influence the complex impedance of the thin film in direct contact with the layer. These measurements can be performed using a simple low-frequency setup with a lock-in amplifier. When graphene is used as the resistive thin film, the signal may also include contributions from graphene's quantum capacitance, which is sensitive to charge transfer to and from the graphene. Unlike in traditional graphene biosensors, changes in electrolyte properties over time, such as those caused by the dissolution of ambient gases, do not significantly affect AC measurements. This technique supports biosensor miniaturization, ensures stable operation, and provides reliable biomarker detection with a high signal-to-noise ratio.

Considerable attention has been directed towards the prognosis of lung diseases primarily due to their high prevalence. Despite advancements in detection technologies, current methods such as computed tomography, chest radiographs, bold proteomic patterns, nuclear magnetic resonance, and positron emission tomography still face limitations in detecting diseases related to the lungs. Consequently, there is a need for swift, non-invasive and economically feasible detection methods. Our study explores the interaction between BeS monolayer and breathe biomarkers related to lung disease utilizing the density functional theory (DFT) method. Through comprehensive DFT analysis, including electronic properties analysis, charge transfer evaluations, work function, optical properties assessment and recovery times, the feasibility and efficiency of BeS as a VOC (volatile organic compound) detection are investigated. Findings reveal significant changes in bandgap upon VOC adsorption, with notable alteration in work function for selective compounds. Optical property analyses demonstrate the potential for selective detection of biomarkers within specific wavelength ranges. Moreover, the study eval

A novel framework is proposed that combines multi-resonance biosensors with machine learning (ML) to significantly enhance the accuracy of parameter prediction in biosensing. Unlike traditional single-resonance systems, which are limited to one-dimensional datasets, this approach leverages multi-dimensional data generated by a custom-designed nanostructure, a periodic array of silicon nanorods with a triangular cross-section over an aluminum reflector. High bulk sensitivity values are achieved for this multi-resonant structure, with certain resonant peaks reaching up to 1706 nm/RIU. The field analysis reveals Mie resonances as the physical reason behind the peaks. The predictive power of multiple resonant peaks from transverse magnetic (TM) and transverse electric (TE) polarizations is evaluated using Ridge Regression modeling. Systematic analysis reveals that incorporating multiple resonances yields up to three orders of magnitude improvement in refractive index detection precision compared to single-peak analyses. This precision enhancement is achieved without modifications to the biosensor hardware, highlighting the potential of data-centric strategies in biosensing. The finding

Having a flat device-solution interface is crucial for nanophotonic biosensors to achieve stable and reproducible performance, by mitigating solid-liquid-gas interfacial processes at the nanometer scale. In this aspect, the metal-insulator-metal (MIM) film presents a capable solution, by hybridizing surface plasmon polaritons (SPP) and MIM gap plasmons, which is enabled by the latter's unique dispersion characteristic and wide tunability. In this meta-film, the SPPs propagate along a flat interface, and seal the gap plasmons which can be integrated with nanostructures, e.g., a coupling grating. In addition, by tuning the gap plasmons, the SPP-MIM hybridization meta-film can be designed to achieve a significantly reduced SPP evanescent depth and a significantly improved surface sensitivity. Using gold as the plasmonic material, such improvements are theoretically predicted across a broad spectral range, from visible to near infrared. Particularly, at 1550 nm, we show that a grating-coupled meta-film device is designed to have its evanescent depth shortened from 1.4 micrometers to 0.16 micrometers, with an enhancement factor of 5.6 in its surface sensitivity, as compared with traditi

This paper presents a novel methodology for modeling memristive biosensing within COMSOL Multiphysics, focusing on critical performance metrics such as antigen-antibody binding concentration and output resistive states. By studying the impact of increasing inlet concentrations, insights into binding concentration curve and output resistance variations are uncovered. The resultant simulation data effectively trains a support vector machine classifier (SVMC), achieving a remarkable accuracy rate of 97%. The incorporation of artificial intelligence (AI) through SVM demonstrates promising strides in advancing AI-based memristive biosensing modeling, potentially elevating their performance standards and applicability across diverse domains.

We propose a conceptual device for multiplexed biosensor in a photonic crystal chip based on the Su-Schrieffer-Heeger mechanism. Remarkably, the proposed biosensor can identify three distinct disease markers through a single-shot photon transmission measurement, due to the couplings among the three Su-Schrieffer-Heeger boundary modes in the photonic crystal. Our biosensor design is more robust against defects and disorders inevitable in real-life device applications than previous designs. Such robustness is invaluable for achieving efficient, reliable, and integrated biosensing based on nanophotonic systems. We further demonstrate that various combinations of disease markers can be recognized via the photon transmission spectrum, unveiling a promising route toward high performance advanced biosensing for future biomedical technology.

Optical metasurface has brought a revolution in label-free molecular sensing, attracting extensive attention. Currently, such sensing approaches are being designed to respond to peak wavelengths with a higher Q factor in the visible and near-infrared regions.Nevertheless, a higher Q factor that enhances light confinement will inevitably deteriorate the wavelength sensitivity and complicate the sensing system. We propose a Q-switched sensing mechanism, which enables the real part of the refractive index to effectively perturbate the damping loss of the oscillator, resulting in a boost of peak intensity.Consequently, a higher Q factor in Q-switched sensor can further enhance the peak sensitivity while remaining compatible with broadband light sources, simultaneously meeting the requirements of high performance and a compact system.This is achieved in a unique 3D bound-state-in-continuum (BIC) metasurface which can be mass-produced by wafer-scale aluminum-nanoimprinting technology and provides a peak intensity sensitivity up to 928 %/RIU.Therefore, a miniaturized BIC biosensing system is realized, with a limit of detection to 10E-5 refractive index units and 129 aM extracellular vesic

The promising field of organic electronics has ushered in a new era of biosensing technology, offering a promising frontier for applications in both medical diagnostics and environmental monitoring. This review paper provides a comprehensive overview of the remarkable progress and potential of organic electronics in biosensing applications. It explores the multifaceted aspects of organic materials and devices, highlighting their unique advantages, such as flexibility, biocompatibility, and low-cost fabrication. The paper delves into the diverse range of biosensors enabled by organic electronics, including electrochemical, optical, piezoelectric, and thermo sensors, showcasing their versatility in detecting biomolecules, pathogens, and environmental pollutants. Furthermore, integrating organic biosensors into wearable devices and the Internet of Things (IoT) ecosystem is discussed, offering real-time, remote, and personalized monitoring solutions. The review also addresses the current challenges and prospects of organic biosensing, emphasizing the potential for breakthroughs in personalized medicine, environmental sustainability, and the advancement of human health and well-being.