Next-generation PCF sensor: Ensuring purity in vegetable oils at terahertz scale
Abstract
In modern civilization, the oil demand is increasing daily; however, its purity has come into question. There is a concerning trend involving the adulteration of vegetable oils with various harmful chemicals. To address this issue, we are experimenting with a sensor that operates at octagonal photogenic-crystal fiber (PCF) and performs during the terahertz frequency variety of 1 THz to 3.4 THz. This sensor accurately differentiates various vegetable oils, including sunflower, olive, mustard, coconut, and palm oil. By the present investigation, the refractive index (RI) for the oils was found to be as follows at room temperature: sunflower oil (n = 1.4735), olive oil (n = 1.466), mustard oil (n = 1.4760), coconut oil (n = 1.463), palm oil (n = 1.454). The appropriate sensor utilized the COMSOL Multi-physics program using the finite element technique for the operation of their computational analysis. The results from the recommended sensor indicate the highest relative sensitivity (%), the lowest confinement loss (dB/m), and effective material loss (cm⁻¹). In the case of 1.4 THz, the relative sensitivities for sunflower oil, olive oil, mustard oil, coconut oil, and palm oil are 99.35%, 98.87%, 99.51%, 98.68%, and 98.12%, respectively. The confinement losses measured were 7.95 × 10⁻¹³ dB/m, 2.42 × 10⁻¹² dB/m, 3.99 × 10⁻¹³ dB/m, 8.02 × 10⁻¹³ dB/m, and 4.06 × 10⁻¹² dB/m, while the effective material losses were recorded at 1.33 × 10⁻³ cm⁻¹, 1.308 × 10⁻³ cm⁻¹, 1.337 × 10⁻³ cm⁻¹, 1.30 × 10⁻³ cm⁻¹, and 1.275 × 10⁻³ cm⁻¹. This specialized sensor has the potential to accurately monitor and detect vegetable oil products in real-world industrial and market settings. In a laboratory environment, it can also identify the presence of mineral oils resulting from various chemical reactions.
Fields of Study & Subjects
Terahertz technology and applications
Advanced Fiber Optic Sensors
Photonic Crystal and Fiber Optics
Publication details
- Journal / source
- Applied Food Research
- Publisher
- Elsevier BV
- Volume
- 6
- Issue
- 1
- Pages
- 101676–101676
- Publication date
- 11 January 2026
- Language
- EN