A novel hollow core photonic sensor for liquid analyte detection in the terahertz spectrum: design and analysis

Design of highly sensitive biosensors using hollow-core microstructured fibers for plasma sensing in aids with human metabolism

Detection of low index liquid analytes in real-time, in-situ, and with high accuracy is of great importance in various scientific fields, particularly in medicine and biology. Accurate detection of plasma concentration in blood samples is one of the most significant usages of biosensors in medicine. In this paper, we report a highly sensitive biosensor using hollow core microstructure optical fibers (HC-MOFs) to detect low index liquid analytes with a particular focus on detection of plasma concentration in blood samples. We demonstrate how variations in plasma concentration in blood can change transmission spectra of the HC-MOF due to the photonic bandgap mechanism. We use the finite element approach to explore how the biosensor's performance depends on the number of capillary rings encircling the hollow core of the fibre. An average spectral and amplitude sensitivity of 8928.57 nm/RIU and 1.21 dB/RIU is reported for the optimized design of HC-MOF for five capillary rings with a refractive index detection range of 1.333 to 1.3385 for different ratios of plasma in blood serum. The proposed biosensor can have potential application in liquid analyte detection in medicine, chemistry, and biology where real-time and accurate data about liquid analytes are necessary for human metabolism.

A new technology for rapid determination of isomers of hydroxybenzoic acid by terahertz spectroscopy

This study investigated the feasibility of using terahertz (THz) technology for the rapid identification of isomers. The time-domain spectra of 2-hydroxybenzoic acid (2-HA), 3-hydroxybenzoic acid (3-HA), and 4-hydroxybenzoic acid (4-HA) were measured by a THz time-domain spectroscopy system (THz-TDS) in the range of 0.3-1.8 THz. Aiming at the isomer classification problem, a THz spectral data classification model based on a variational mode decomposition-particle swarm optimization-support vector machine (VMD-PSO-SVM) method was proposed. Empirical mode decomposition (EMD) and variational mode decomposition (VMD) were used to extract the first eight intrinsic mode functions (IMFs) of the time-domain signal. Principal component analysis (PCA) was used to extract the first 80 principal components of each modal component as the classification feature vector. The particle swarm optimization (PSO) and support vector machine (SVM) algorithms were used to construct 2-, 3-, and 4-HA classification models. We found that the prediction accuracy of the VMD-PSO-SVM model was significantly higher than that of EMD-PSO-SVM model regardless of the modal components. For both EMD and VMD, with the increase in the IMF number, the corresponding classification recognition accuracy tended to decrease. The results showed that the rapid identification model of hydroxybenzoic acid isomers based on THz spectroscopy and SVM was effective and feasible, providing an accurate and rapid method for the chemical synthesis and quality monitoring of biomedicine.

Wheel structured Zeonex-based photonic crystal fiber sensor in THz regime for sensing milk

In this paper, a wheel structured Zeonex-based hexagonal packing photonic crystal fiber (PCF) sensor has been proposed for sensing camel milk with a refractive index of 1.3423 and cow milk with a refractive index of 1.3459. This sensor has been investigated for porosities of 85%, 90%, and 98% within a terahertz (THz) region ranging from 0.2 to 2.0 THz. At an operating frequency of 2 THz, this sensor has shown a maximum sensitivity of 81.16% and 81.32% for camel and cow milk, respectively. EML of 0.033013 cm^-1 and 0.03284 cm^-1 has been found for camel and cow milk, respectively, at the same operating conditions with negligible confinement losses of 8.675  ×  10^-18 cm^-1 1.435  ×  10^-18 cm^-1. Several other parameters, such as the effective area, flattened dispersion, and numerical aperture, have also been obtained during the investigation. Since considerable attention has not been given yet in detecting various types of dairy products using PCF terahertz sensors, this design will pave a whole new path in further implementing THz sensing in the dairy industry.