Search Results (1,069)

The ability to manipulate and probe individual nano-particles, viruses, and organelles with high sensitivity and specificity is an essential part of modern nanoscience and molecular biology. Plasmonic optical tweezers (POT), which use localized surface plasmons to create nanoscale-confined optical fields, have emerged as a powerful platform for trapping and manipulating single nano–bio entities at low optical powers. When combined with surface-enhanced Raman spectroscopy (SERS) from the same plasmonic nanostructures, these platforms offer a unique multi-modal capability: simultaneous optical manipulation and label-free chemical fingerprinting of a single specimen. However, the field faces critical challenges, including low throughput, thermal noise, photothermal damage, and the overwhelming complexity of interpreting dynamic, single-molecule SERS data. This review examines the transformation of plasmonic optical trapping and spectroscopy as they evolve toward autonomous operation and intelligent decision-making. We begin with the fundamental principles that enable these tools to manipulate and probe single viruses, organelles, and nano-particles. Building on this foundation, we explore how computational intelligence is being integrated into the field to address long-standing challenges. This includes the emergence of data-driven methods for designing optimized plasmonic nanostructures, for decoding the complex molecular fingerprints hidden in single-molecule SERS spectra, and for creating feedback-driven systems capable of adaptive, real-time experiment control. By synthesizing these developments, we illustrate a clear trajectory: from manually operated instruments toward fully integrated intelligent nanophotonic laboratories that can autonomously discover and characterize the nano-world. We conclude by discussing the remaining challenges—from data acquisition and model interpretability to the mitigation of photothermal effects—and the most promising pathways toward realizing this transformative vision for virology, cell biology, and nanomedicine. Full article

The persistent accumulation of tetracycline (TC) antibiotics in aquatic environments poses severe ecological and public health risks, necessitating the development of multifunctional platforms capable of simultaneous detection and degradation. Herein, we report magnetically recoverable plasmonic Fe₃O₄/Cu₂O-Ag nanocomposites (NCs) that integrate visible-light-driven photocatalysis with ultrasensitive surface-enhanced Raman scattering (SERS) detection. Hierarchical flower-like Fe₃O₄ nanocrystals were employed as magnetic supports, followed by in situ growth of Cu₂O nanocrystals and controlled deposition of Ag nanocrystals. The optimized composite (FCA-2) exhibited enhanced visible-light absorption (E_g = 1.86 eV), suppressed electron–hole recombination, and improved photocurrent response, which were attributed to Schottky barrier formation at the Cu₂O-Ag interface and localized surface plasmon resonance (LSPR) effects. Under simulated solar irradiation, FCA-2 NCs achieved 91.79% degradation of TC within 60 min, following pseudo-first-order kinetics (k = 20.37 × 10⁻³ min⁻¹). Finite-difference time-domain (FDTD) simulations revealed that optimal Ag loading maximized plasmonic “hot spot” density, thereby enhancing electromagnetic field intensity and SERS performance. The FCA-2 substrate enabled ultrasensitive TC detection with a limit of detection of as low as 10⁻¹⁰ M. Moreover, the superparamagnetic Fe₃O₄ core allowed for rapid magnetic separation and sustained performance over multiple SERS–photocatalysis cycles, with negligible signal attenuation after 30 days. This work presents a rational strategy for constructing plasmonic magnetic NCs that synergistically couple photocatalytic remediation, ultrasensitive sensing, and magnetic recyclability, offering significant potential for integrated environmental monitoring and sustainable water treatment applications. Full article

Disordered Ag-nanowire localized surface plasmon resonance sensorgrams for glycated hemoglobin (HbA1c) detection exhibit reproducible multi-component temporal structures that cannot be fully explained within conventional equilibrium refractive-index models; in particular, the quantification of the molecular target escapes from the classical theory. The HbA1c-associated contribution emerges at earlier times while displaying slower relaxation dynamics compared with naïve hemoglobin-associated kinetics, revealing the coexistence of distinct activation and interfacial relaxation pathways. Analysis of temporal derivatives, phase-space trajectories, characteristic peak times, and relaxation times aims to suggest that the plasmonic response originates from multiple competing nonequilibrium processes evolving on different timescales. The description of the structured temporal response relies on a phenomenological framework incorporating activation and relaxation dynamics. Dynamical redistribution pathways associated with heterogeneous adsorption, hydration-shell relaxation, and plasmonic coupling within spatially non-uniform electromagnetic environments, along with resonance shift, support molecular fingerprint. The findings suggest that sensorgrams contain molecular information hidden beyond conventional equilibrium optical observables, motivating a transition toward dynamical and time-resolved approaches in plasmonic biosensing. Full article

Gold pillar-based plasmonic metasurfaces provide a robust platform for optical sensing owing to their strong localized surface plasmon resonances and tunable near-field distributions. In this work, we present a numerical investigation of a gold-pillar metasurface optimized specifically for high-performance refractive-index sensing. A comprehensive parametric optimization of the metasurface was carried out, including analyses of the inter-pillar gap, the thickness of the underlying gold film, and the optical response under varying angles of incidence. Numerical analysis demonstrates that the engineered plasmonic pillar array achieves a sensitivity of 500 nm/RIU and a Figure of Merit (FOM) of 79. These results demonstrate the potential of the proposed plasmonic metasurface as an optimized platform for high-performance refractive-index sensing, providing practical design guidelines for future chemical and biological sensing applications. Full article

The photothermal response of plasmonic nanomaterials is strongly affected by the electromagnetic and thermal interactions between neighboring particles. In this work, the finite element method was employed to investigate the distance-dependent photothermal behavior of Ag@TiO₂ core–shell nanorods under 808 nm laser irradiation. A single-nanorod model was first used to analyze the optical absorption and temperature distribution of an isolated nanorod, and an idealized two-nanorod model was then established to examine the coupled electromagnetic and thermal fields at different inter-particle spacings. The results show that reducing the inter-particle distance induces two competing effects: thermal-field superposition enhances local heat accumulation, whereas strong near-field plasmonic coupling at small separations modifies the electromagnetic field distribution, induces resonance shifts, and reduces the effective absorption cross-section, thereby weakening heat generation. Consequently, the temperature response exhibits a non-monotonic dependence on inter-particle distance, reflecting the competition between thermal-field overlap and plasmonic coupling. This work helps clarify the electromagnetic–thermal coupling mechanism of Ag@TiO₂ core–shell nanorods under near-infrared irradiation and provides a theoretical reference for understanding their distance-dependent photothermal response. Full article

2,4-Dichlorophenoxyacetic acid (2,4-D) is an extensively applied organic compound, primarily for agricultural weed control and plant growth agents. Although 2,4-D usually exists in the environment in low volumes, the detection of 2,4-D is critical for human health and environmental safety. In this work, a biophotonic biosensor was fabricated by coating the surface of a tapered optical fiber with gold nanoparticles (AuNPs) to excite the localized surface plasmon resonance (LSPR) and functionalizing the fiber with molybdenum disulfide nanosheets (MoS₂-NSs)/zinc oxide nanowires (ZnO-NWs) to extend the effective sensing area. Due to the inhibitory effect of 2,4-D on the hydrolytic activity of ALP, the refractive index (RI) around the sensor surface changes, leading to a shift in the LSPR peak wavelength. According to this sensing technique, the sensor can detect concentrations in the range of 1–10 mg/L, with a limit of detection (LOD) of 0.29 mg/L. The stability, repeatability and selectivity tests show that the sensor has good stability and selectivity. In the actual sample detection experiment, the recovery rates of apples and Chinese cabbage were 96.2–100.4% and 83.8–108.8%, respectively, which indicated that the detection method had good accuracy for the detection of target substances in actual samples. Thus, the proposed sensor has an important application in the detection of 2,4-D herbicides. Full article

Photothermal-assisted electrocatalysis is an effective approach to enhance the efficiency of the oxygen evolution reaction (OER), but the synergistic mechanism between the photothermal effect and the regulation of catalyst electronic structure remains unclear. This work reports the construction of NiFeS/Cs_0.32WO₃ heterostructures, which integrate interfacial electron transfer and localized surface plasmon resonance (LSPR)-induced photothermal effects to enhance OER performance. The Cs_0.32WO₃ component with hexagonal tungsten bronze structure exhibits strong absorption in the near-infrared region, attributed to LSPR (1100 nm to 2500 nm) and small polaron transition (780 nm to 1100 nm), endowing the NiFeS/Cs_0.32WO₃ composite with excellent photothermal conversion capability. Under 808 nm laser irradiation, the steady-state surface temperature of the heterostructure reaches 65.1 °C. X-ray photoelectron spectroscopy and ultraviolet photoelectron spectroscopy analyses reveal that spontaneous electron transfer from NiFeS to Cs_0.32WO₃ occurs at the heterostructure interface, thereby optimizing the electronic structure of active sites. Electrochemical measurements demonstrate that at a current density of 50 mA cm⁻², the NiFeS/Cs_0.32WO₃ composite exhibits an overpotential of 301 mV under near-infrared irradiation, representing a reduction of 53 mV compared to NiFeS under dark conditions. At a current density of 50 mA cm⁻², the photothermal enhancement effect of the NiFeS/Cs_0.32WO₃ composite is identified as the predominant contributor to the overall performance improvement. Nevertheless, the intrinsic interfacial effect associated with the heterojunction also plays a crucial role and makes a non-negligible contribution to the enhanced electrocatalytic activity. The Tafel slope decreases from 57.8 mV dec⁻¹ to 44.5 mV dec⁻¹ under near-infrared illumination, indicating accelerated OER kinetics. This work elucidates the mechanism of synergistic enhancement between heterostructure construction and photothermal effects, providing insights for the design of advanced photothermal electrocatalysts. Full article

Surface-enhanced Raman spectroscopy (SERS) has emerged as a transformative tool in biomedical diagnostics, offering a highly sensitive and non-invasive method for detecting molecular biomarkers at exceptionally low concentrations. This approach takes advantage of the plasmonic characteristics of customized metallic nanostructures that produce intense localized electromagnetic fields via localized surface plasmon resonance and facilitate electron transfer reactions that notoriously enhance the intrinsically weak Raman scattering signals of molecular entities which reside on or next to their surfaces. SERS-based assays have shown remarkable potential in detecting cancer biomarkers, circulating tumor DNA (ctDNA), and proteins at early stages, enabling timely and targeted intervention. Additionally, the combination of SERS with AI-driven data analysis has facilitated real-time diagnostics, enhancing the precision and efficiency of point-of-care testing. Despite its promising capabilities, challenges such as substrate fouling, signal degradation, and the need for better biocompatibility remain. Nevertheless, ongoing research in substrate development, coupled with advances in AI, positions SERS as a leading technology for future diagnostic tools. This paper explores the current state of SERS in biomedical applications, highlighting its potential to revolutionize diagnostics and personalized medicine while addressing the existing limitations and future research directions. Full article

Surface-enhanced Raman scattering (SERS) offers a powerful route for biomolecular detection because it combines molecular specificity with high sensitivity, rapid optical readout, and multiplexing capability. In real biological samples, however, analytical performance is rarely determined by signal enhancement alone. Biofluids such as serum, plasma, saliva, urine, and interstitial fluid contain complex biomolecular mixtures that interfere with target capture, spectral response, and data interpretation. A practical SERS biosensor must therefore localize targets, stabilize spectral responses, tolerate matrix-induced variation, and convert complex spectra into reliable analytical information. This review discusses recent progress in SERS biosensing from an integrated system perspective, with particular focus on artificial intelligence/machine learning (AI/ML)-assisted interpretation. Direct label-free SERS provides chemically transparent readouts but is limited by stochastic adsorption, hotspot heterogeneity, and spectral variation in complex samples. Bio-recognition interfaces improve target localization, while signal-transduction strategies based on nanotags, immunoassays, clustered regularly interspaced short palindromic repeats (CRISPR) systems, nanozymes, and lateral-flow formats decouple molecular recognition from spectral generation. Digital SERS further improves measurement robustness by converting fluctuating intensities into countable, event-based outputs. AI/ML-assisted analysis can support full-spectrum classification, calibration transfer, explainability, and patient-level decision-making. We frame AI/ML-assisted SERS biosensing as an integrated architecture connecting substrate design, interface engineering, signal transduction, digital measurement, and clinical validation. Future progress will depend as much on validation-ready workflows as on plasmonic enhancement itself, especially for systems intended to operate across different samples, instruments, and clinical settings. Full article

We demonstrate a mechanism-oriented Surface-Enhanced Raman Scattering (SERS) platform based on a hybrid structure integrating monolayer molybdenum disulfide (MoS₂) and gold nanospheres (AuNSs) on an optical microfiber (MF). The microfiber serves as a whispering-gallery-mode (WGM) microcavity. Monolayer MoS₂, grown directly on the microfiber surface via chemical vapor deposition (CVD), provides a chemically active interface for molecular adsorption and charge-transfer-related chemical enhancement. Subsequently deposited AuNSs couple with the microfiber-supported WGM, leading to the formation of hybrid photonic–plasmonic modes. This coupling results in a narrowed scattering resonance and a localized electromagnetic hotspot near the AuNS–microfiber interface. The combined contribution of electromagnetic enhancement from the microfiber–AuNS hybrid cavity and chemical enhancement from the MoS₂ layer produces discernible Raman enhancement for Rhodamine 6G (R6G) molecules under proof-of-concept measurement conditions. This work provides a useful platform for studying SERS enhancement mediated by hybrid photonic–plasmonic modes and offers guidance for the future development of optimized fiber-based SERS sensors. Full article

Alternating glycopolymers bearing periodically arranged pendant carbohydrate residues were synthesized by reversible addition–fragmentation chain transfer (RAFT) copolymerization of maltose-containing vinyl ether (MalVE) and ethyl maleimide (EtMI). The resulting trithiocarbonate-terminated polymers were subsequently converted into thiol-terminated glycopolymers through post-polymerization end-group transformation. These structurally well-defined alternating glycopolymers were immobilized onto gold nanoparticles (AuNPs) via Au–S interactions to construct glycopolymer-functionalized glycointerfaces. Surface functionalization of the AuNPs was confirmed by an increase in hydrodynamic diameter from approximately 42 to 59 nm after polymer immobilization. The resulting glycopolymer-functionalized AuNPs exhibited concentration-dependent lectin-mediated aggregation behavior in the presence of concanavalin A, accompanied by characteristic red shifts and broadening of the localized surface plasmon resonance (LSPR) band arising from multivalent carbohydrate–lectin interactions at the nanoparticle interface. Although the apparent association constants obtained for free alternating glycopolymers using fluorescently labeled lectin cannot be directly compared with those obtained from LSPR-based aggregation assays of AuNP-immobilized glycopolymers, the values increased from the order of 10⁵ L mol⁻¹ in solution to the order of 10⁷ L mol⁻¹ at the nanoparticle interface. This trend suggests that immobilization onto AuNPs enhances multivalent carbohydrate–lectin interactions through multivalent presentation of the glycopolymer chains at the nanoparticle interface. As a control experiment, peanut agglutinin (PNA), which does not recognize maltose residues, was added to the glycopolymer-functionalized AuNPs. No significant LSPR shift or spectral broadening was observed, indicating that nanoparticle aggregation was not induced by nonspecific lectin addition but arose from specific interactions between maltose residues and Con A. Quantitative analysis suggested that polymer chain length may influence the aggregation behavior. These results demonstrate that alternating glycopolymers provide a useful platform for constructing sequence-regulated glycointerfaces and for investigating multivalent biomolecular interactions at nanoparticle surfaces. Full article

This work presents an intrinsic optical fiber sensor based on plasmonic phenomena in modified plastic optical fibers (POFs). The sensing area is achieved by replacing the polymethyl methacrylate (PMMA) core with a molecularly imprinted polymer (MIP) containing gold nanorods (GNRs). Thus, in the sensing area, the MIP acts as both a selective recognition element and an optically sensitive guiding medium where plasmonic phenomena occur. This optical–chemical configuration has been developed as a proof-of-concept for the detection of furfural in aqueous solution. The proposed sensor achieves a limit of detection (LOD) of 27 pM, demonstrates high selectivity for the analyte of interest, and is applicable even in real-world scenarios, as demonstrated by experimental results (a commercially available infant milk). The proposed sensor presents a significant enhancement of the sensor response, of about six orders of magnitude, compared to a conventional configuration where the same (or a similar) mixture of MIP/GNRs is spun over the exposed PMMA of a D-shaped POF area for comparison. Notably, even if this study has been carried out via a proof-of-concept in furfural detection, this substantial improvement is achieved while preserving a simple, portable, and cost-effective optical setup, highlighting the potential of this sensing strategy for the development of highly selective sensors by changing the MIP template. Full article

Smart manufacturing, Industry 4.0, and cyber-physical systems (CPSs) require sensing architectures capable of resolving both spatially distributed asset behavior and highly localized process states. This review examines optical fiber sensors (OFSs) and integrated photonic sensors for industrial monitoring through a deployment-oriented, multi-scale perspective. The discussion covers five major application regimes: continuous infrastructure surveillance, structural health monitoring (SHM) of load-bearing composites, dynamic condition monitoring of machinery, in situ observability in advanced manufacturing, and localized chemical or gas sensing. Extended fiber-optic networks, including distributed fiber-optic sensing (DFOS) based on Rayleigh, Raman, and Brillouin scattering, together with multiplexed fiber Bragg grating (FBG) sensors, provide passive, embeddable, and remotely interrogated monitoring for large-scale assets and harsh environments. Photonic integrated circuits (PICs) shift transduction to compact node-level devices for localized thermal, mechanical, refractive-index, absorption, vibration, and inertial measurements, while plasmonic and dielectric nanophotonic sensors extend optical monitoring toward surface-selective and chemically specific detection. Across these platforms, digital signal processing (DSP), machine learning (ML), sensor fusion, and digital-twin (DT) coupling are treated as artificial-intelligence-enabled (AI-enabled) layers for signal recovery, inverse mapping, uncertainty reduction, and predictive maintenance. The review argues that scalable industrial adoption is less limited by sensing physics than by the complete deployment chain: packaging, fiber–chip interfacing, calibration stability, interrogation robustness, and AI-enabled data interpretation. This manuscript is structured as a deployment-oriented narrative review of optical fiber and integrated photonic sensors for industrial monitoring and smart manufacturing. Full article

Localized surface plasmon resonance (LSPR) is an optical phenomenon that occurs when light interacts with free electrons on the surface of metallic thin films, producing intensified electromagnetic fields at specific sites, often called “hot spots”. LSPR-based sensing technologies respond to chemical and associated optical interfacial changes. Inherent advantages include enhanced sensitivity, compact size, low production cost, and strong potential for integration into portable, point-of-care diagnostic systems. This study focuses on a detailed investigation into the surface functionalization of localized surface plasmon resonance (LSPR)-based nanohole array (NHA) sensors for biomedical applications. Gold-coated NHA surfaces were functionalized using polyethylene glycol (PEG) self-assembled monolayers (SAMs), enabling specific attachment of biomolecular species. As a proof-of-concept, bovine serum albumin (BSA) and SARS-CoV-2 nanobody proteins were successfully immobilized on the PEGylated surfaces. Individual steps of surface modification including PEGylation, protein immobilization and nanobody immobilization were validated through a dual-method approach which combined measurement of LSPR optical spectral shifts and x-ray photoelectron spectroscopy (XPS) chemical analyses. Reproducibility was assessed across multiple sensors and repeated trials, confirming the repeatability of each functionalization and binding process. The sensor system, consisting of NHA-based plasmonic platform, microfluidics, and a portable optical spectrometer, exhibits the capability for reliable and sensitive, label-free detection of biomolecular targets, including viral antigens, in liquid-phase environments. Full article

Bowl-shaped gold nanoparticles (BAuNPs) are of significant interest due to their tunable localized surface plasmon resonance (LSPR) properties. This report presents a new synthesis method that uses hemispherical hydrogen nanobubbles on planar, non-conducting surfaces as templates for gold shell deposition. Initial synthesis under stagnant conditions yielded non-uniform sub-micron particles, attributed to localized hydrogen concentration gradients. The cyclonic flow was introduced aiming to reduce these gradients, although simultaneously inducing significant particle aggregation, obscuring the open structure. To overcome these challenges, an electrochemical microfluidic system was implemented to create a laminar flow environment. This configuration optimizes ion distribution and introduces shear forces that promote particle detachment, successfully limiting particle dimensions to below 200 nm, and preventing the accumulation. Systematic optimization identified optimal parameters: an ideal channel length of 7.5 mm, an applied potential of −0.6 V, and a flow rate of 0.028 µL s⁻¹. These parameters that strike a balance between nanobubble growth and gold deposition kinetics can produce highly uniform BAuNPs with a well-defined open structure and thin solid gold shells, with an outer diameter of 105.3 ± 12.1 nm and a core diameter of 80.1 ± 11.9 nm. These structural parameters successfully shift the plasmonic resonance to 760 nm, which responds perfectly with the first biological window for potential in vivo biomedical applications. Full article