Plasmonics最新文献

Nanoparticles are substances that are of immense advantage due to their exquisite surface-to-volume ratio. Among them, silver nanoparticles are one of the most notable classes of metallic nanoparticles, which have a wide range of applications in biomedical aspects, material fabrication, and other uses. They are synthesized by both top-down and bottom-up approaches. Yet sustainable methods of silver nanoparticle synthesis are currently being explored using a wide arena of eco-friendly sources. The properties of silver nanoparticles vary deeply in comparison with their macro forms. They possess unique and peculiar properties like strong absorption of photons and increased thermal and electrical conductivity and are capable of being modified into different shapes and various sizes and could be fabricated into many nano-objects. Silver nanoparticles also have many notable pharmacological properties, like anti-cancerous, anti-inflammatory, anti-microbial, anti-oxidative, and anti-angiogenic nature. In addition to this, they are deployed for various other applications like wastewater treatment, biosensing, imaging, cosmetics, and drug delivery. This review briefly describes the conventional and sustainable synthesis strategies, optical properties, physiochemical properties, and electrical properties of the silver nanoparticles along with their application in various fields.

In this article, we present a passive plasmonic metasurface sensor, the square annular cavity array (SACA), designed for ultrasensitive refractive index (RI) detection, structural color modulation, and multiwavelength spectral filtering. This sensor is built on a multilayer plasmonic architecture comprising silver (Ag), silicon nitride (Si(_3)N(_4)), and silicon dioxide (SiO(_2)), featuring tunable square annular nanocavities with gap sizes ranging from 10 to 110 nm. These cavities are engineered to support hybrid plasmon–Fabry–Pérot resonances over a wavelength range of 400 to 1800nm. Finite element method (FEM) simulations conducted in COMSOL and optimized using the Nelder–Mead algorithm reveal the highest sensitivity of 800 nm/RIU, a spectral figure of merit (FOM) of 85.23, a quality factor (Q-factor) of 167.61, and a dots per inch (DPI) value of 169,333. The SACA sensor displays distinct chromatic transitions influenced by changes in the refractive index and angle of incidence. These effects are quantitatively assessed using the CIE 1931 color space under standard D65 illumination, facilitating label-free visual detection. Angle-resolved analysis reveals polarization-dependent mode splitting of up to 30(^{circ }), facilitating multiplexed spectral filtering and sensing. The normalized sRGB color gamut coverage is calculated to be 85.90% under RI modulation, indicating a design balance between visual expressiveness and functional spectral performance. By integrating high RI sensitivity, tunable spectral response, and real-time colorimetric feedback within a compact passive structure, the SACA sensor offers significant advantages. This design provides a versatile solution for point-of-care diagnostics, lab-on-chip optics, and integrated photonic applications.

This work introduces a highly sensitive D-type dual-channel photonic crystal fiber (PCF) sensor designed to detect malaria-induced alterations in the refractive index of red blood cells. The sensor comprises an inner fiber layer, including six air holes that create a positive hexagonal configuration, and an exterior layer with nine symmetrically aligned air holes. The U-channel above the fiber core region is uniformly coated with a layer of gold nanofilms to induce the surface plasmon resonance (SPR) effect. The sensor’s geometrical characteristics, such as the gold film thickness, U-channel diameter, and air hole diameter, were tuned using the finite element approach to enhance its refractive index (RI) sensitivity. The simulation findings indicate that the sensor exhibits a maximum wavelength sensitivity of 24,000 nm/RIU, an ideal resolution of 4.20 × 10⁻⁷ RIU, and a maximum quality factor of 221.36 RIU⁻¹ within the refractive index range of 1.33–1.43. The sensor’s straightforward design and elevated sensitivity present significant possibilities for application in the medical sector.

In this work, we investigate the detection of contaminants in water, including varying concentrations of sodium chloride (NaCl), using angular interrogation-based surface plasmon resonance (ASPR). The proposed sensor structure comprises a silver (Ag) thin film, a graphene/MXene heterostructure, and a sensing medium, integrated with a CaF(_2) prism in the Kretschmann configuration. The optical response of the multilayer system is analyzed using the transfer-matrix method (TMM), and the structural parameters are optimized to achieve enhanced sensitivity and detection accuracy (DA). The optimized configuration yields a maximum angular sensitivity of 289.62(^circ )/RIU and a figure of merit (FoM) of 46.86/RIU, corresponding to a refractive index (RI) variation ((Delta n_s)) of 0.027 and a resonance angle shift ((Delta theta _{text {SPR}})) of 8.1(^circ ). Reflectance spectra are simulated at a wavelength of 633 nm across an RI range from 1.330 to 1.360. Results confirm the sensor’s capability to detect subtle RI changes due to low concentrations of NaCl (as low as 0.2 mg in 10 mL) and other contaminated water samples. This study demonstrates the potential of graphene/MXene-enhanced ASPR sensors as a promising platform for sensitive and label-free water quality monitoring in environmental and industrial applications.

The present study investigates the abilities of MoS₂-Au plasmonic nanostructures for highly sensitive SPR biosensors and efficient photocatalysts for organic pollutant degradation. For instance, COMSOL Multiphysics is utilized to simulate the novel multilayered MoS₂-Au grating on glass substrates in order to improve the sensitivity of SPR biosensors and UV–visible light degradation efficiency of organic pollutants. The optimized configuration is obtained by keeping the periodicity of the proposed model constant (720 nm) and by varying slit widths in order to enhance electric and magnetic field interactions. The inclusion of Au nanoparticles that promote light absorption and charge separation significantly improves the photocatalytic degradation of organic pollutants like methylene blue (MB), methomyl, methylene orange (MO), phenol, and tetracycline (TC). Additionally, MoS₂-Au nanostructures exhibit enhanced sensitivity in detecting liquid and gas analytes, making them highly effective for various environmental, food safety, and medical applications.

This paper presents a novel plasmonic sensor architecture incorporating graphene with an asymmetric grating structure to harness the Fano resonance effect. By exploiting discrete-continuum interference, this design achieves enhanced sensitivity and spectral tunability across a broad frequency range. To achieve optimization of sensor’s performance, a methodological fusion of a Deep Neural Network (DNN) with the Particle Swarm Optimization (PSO) algorithm is implemented. The training dataset for the DNN is derived from simulations conducted via the Finite Element Method (FEM), enabling the meticulous calibration and predictive analysis of pivotal structural parameters, including the periodicity of the grating, the asymmetry height, and the Fermi energy level of graphene. The resultant optimized sensor is characterized by a sensitivity of 5890 nm/RIU and a Figure of Merit (FoM) of 150, highlighting the significant advancements achievable through the integration of state-of-the-art optimization methodologies with metamaterial design principles.

This study presents an innovative hybrid plasmonic biosensor design for non-invasive glucose detection in urine samples. Through optimization of geometric parameters and electrical properties, the sensor demonstrates exceptional performance with maximum absorption of 1.589 at 80° incident angle and graphene chemical potential of 0.9 eV. The device exhibits a competitive sensitivity of 1000 GHz/RIU, matching or exceeding existing designs, with optimal operation at 0.321 THz where maximum field confinement occurs. The sensor shows a frequency tuning range of 25 GHz (0.33 THz to 0.305 THz) for glucose detection, with figure of merit values ranging from 58.82 to 9.80 RIU⁻¹. On the other the integration of machine learning demonstrates the remarkable performance with the ability of cutting down simulation time and resources. This multi-material approach leverages the complementary advantages of each component while mitigating individual material limitations, offering a promising solution for point-of-care glucose monitoring applications.

In this paper, a dual-side polished photonic crystal fiber (PCF)-based surface plasmon resonance (SPR) sensor for refractive index (RI) and temperature (T) sensing is presented and studied theoretically using finite element method (FEM). Metal alloy film coating for core 1 (C₁) and a composite of silver and polydimethylsiloxane (PDMS) is used for core 2 (C₂) for RI and temperature sensing, respectively. Detection ranges of 1.33 to 1.42 RI and − 20 to 100 °C were realized for RI and T measurements, respectively. The alloy coating generates two distinct resonance peaks. A maximum wavelength sensitivity of 54,300 nm/RIU and a resolution of 1.84 × 10⁻⁶ RIU were achieved at the second peak of core 1 (C₁) for analytes with RI values of 1.41 and 1.42. The Ag/PDMS composite coating yields a wavelength sensitivity of 39.6 nm/°C and a resolution of 2.52 × 10⁻³ °C in the temperature range of − 20 to − 10 °C. Eleven air holes in the cladding with two cores are simple to fabricate, cost effective, and show improved sensitivities with two peaks of core 1 using alloy coating is the key innovation in this work. Wide detection range, high sensitivities, and dual-parameter sensing make this work suitable for various applications including bio-sensing, environmental detection, and chemical sensing.

This study presents a novel dual-band metamaterial sensor designed for the detection of cancer cells. The proposed sensor features a gold octagonal loop structure with carefully constructed gaps, achieving perfect absorption at 1994 GHz and 2700 GHz with absorption of 100% and 88%, respectively. The sensor demonstrates exceptional sensitivity to the analyte refractive index (RI) change, with sensitivities of 600 GHz/RIU and 800 GHz/RIU for the first and second resonance bands, respectively, with corresponding quality factor of 12.24 and 8.9 and a FOM of 3.66 and 2.64, respectively. Additionally, the reported design can be used for sensing different types of cancer types such as breast, cervical, Jurkat, PC12, and MCF-7 with an average sensitivity of 560 GHz/RIU and 770 GHz/RIU for the first and second resonances, respectively. The design is also simple and can be fabricated by current technology using photolithography technique. These results surpass those reported in recent literature, highlighting the sensor’s superior performance. Additionally, the sensor performance exhibits high linearity across the studied frequency range, robustness against fabrication tolerances, and compatibility with established fabrication technologies. The proposed metamaterial sensor represents a significant advancement in cancer detection, offering high sensitivity, flexibility, and ease of integration into biomedical applications.