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1.
Sensors (Basel) ; 23(18)2023 Sep 15.
Article in English | MEDLINE | ID: mdl-37765971

ABSTRACT

A non-invasive optical fiber sensor for detecting volatile organic compounds (VOCs) as biomarkers of diabetes is proposed and experimentally demonstrated. It offers a low-cost and straightforward fabrication approach by implementing a one-step spray coating of a ZnO colloidal solution on a glass optical fiber. The structure of the optical fiber sensor is based on a single-mode fiber-coreless silica fiber-single-mode fiber (SMF-CSF-SMF) structure, where the CSF is the sensor region spliced between two SMFs. The ZnO layer of a higher refractive index coated over the sensing region improves the light interaction with the surrounding medium, leading to sensitivity enhancement. The optical properties, morphology, and elemental composition of the ZnO layer were analyzed. The sensing mechanism of the developed sensor is based on a wavelength interrogation technique showing wavelength shifts when the sensor is exposed to various VOC vapor concentration levels. Various concentrations of the three VOCs (including acetone, isopropanol, and ethanol) ranging from 20% to 100% were tested and analyzed. The sensor noticeably shows a significant response towards acetone vapor, with a better sensitivity of 0.162 nm/% vapor than for isopropanol (0.082 nm/% vapor) and ethanol (0.075 nm/% vapor) vapors. The high sensitivity and selectivity towards acetone, a common biomarker for diabetes, offers the potential for further development of this sensor as a smart healthcare system for monitoring diabetic conditions.


Subject(s)
Diabetes Mellitus , Volatile Organic Compounds , Zinc Oxide , Humans , 2-Propanol , Acetone , Optical Fibers , Diabetes Mellitus/diagnosis , Biomarkers , Ethanol , Gases
2.
Biosensors (Basel) ; 13(1)2023 Jan 09.
Article in English | MEDLINE | ID: mdl-36671949

ABSTRACT

In general, volatile organic compounds (VOCs) have a high vapor pressure at room temperature (RT). It has been reported that all humans generate unique VOC profiles in their exhaled breath which can be utilized as biomarkers to diagnose disease conditions. The VOCs available in exhaled human breath are the products of metabolic activity in the body and, therefore, any changes in its control level can be utilized to diagnose specific diseases. More than 1000 VOCs have been identified in exhaled human breath along with the respiratory droplets which provide rich information on overall health conditions. This provides great potential as a biomarker for a disease that can be sampled non-invasively from exhaled breath with breath biopsy. However, it is still a great challenge to develop a quick responsive, highly selective, and sensitive VOC-sensing system. The VOC sensors are usually coated with various sensing materials to achieve target-specific detection and real-time monitoring of the VOC molecules in the exhaled breath. These VOC-sensing materials have been the subject of huge interest and extensive research has been done in developing various sensing tools based on electrochemical, chemoresistive, and optical methods. The target-sensitive material with excellent sensing performance and capturing of the VOC molecules can be achieved by optimizing the materials, methods, and its thickness. This review paper extensively provides a detailed literature survey on various non-biological VOC-sensing materials including metal oxides, polymers, composites, and other novel materials. Furthermore, this review provides the associated limitations of each material and a summary table comparing the performance of various sensing materials to give a better insight to the readers.


Subject(s)
Volatile Organic Compounds , Humans , Volatile Organic Compounds/metabolism , Breath Tests/methods , Biomarkers , Exhalation , Oxides
3.
Sensors (Basel) ; 22(16)2022 Aug 20.
Article in English | MEDLINE | ID: mdl-36016038

ABSTRACT

This work demonstrated a ZnO-coated optical fiber sensor for the detection of a volatile organic compound (VOC) biomarker for diabetes for detecting isopropanol (IPA) markers. A coreless silica fiber (CSF) was connected to a single-mode fiber (SMF) at both ends to achieve a SMF-CSF-SMF structure. CSF is the sensing region where multimode interference (MMI) generates higher light interaction at the interface between the fiber and sensing medium, leading to enhanced sensitivity. Optimization of the CSF length was conducted numerically to attain the highest possible coupling efficiency at the output. Surface functionalization was achieved via hydrothermal growth of ZnO nanorods directly onto the CSF at low temperatures. The optical fiber-based sensor was successfully fabricated and tested with 20%, 40%, 60%, 80%, and 100% of IPA. The sensor response was recorded using an optical spectrometer and analyzed for sensor sensitivity. The fabricated sensor shows the potential to detect isopropanol with the sensitivity of 0.053 nm/%IPA vapor. Further improvement of the sensor sensitivity and selectivity is also proposed for future work.


Subject(s)
Volatile Organic Compounds , Zinc Oxide , 2-Propanol , Biomarkers , Equipment Design , Optical Fibers , Silicon Dioxide , Zinc Oxide/chemistry
4.
Appl Opt ; 59(1): 122-128, 2020 Jan 01.
Article in English | MEDLINE | ID: mdl-32225277

ABSTRACT

This study proposes a single-step integrated optical fabrication scheme utilizing a 3D printer using digital light processing technology. Strong light confinement in the fabricated structure is realized through the introduction of an elevated (tower-shaped) waveguide in a transparent photosensitive resin (PX-8880). The fabrication is optimized to maximize light confinement through varying the dimensions of the guiding region and the tower structure. Benefiting from the surface roughness produced by the slicing process in the 3D printing (50 µm resolution), the fabricated structure was tested for vapor sensing. Obvious intensity dynamics have been reported due to the change of the optical scattering due to the presence of vapor as well as polymer vapor interaction. Though the reported response time is long, further optimization can lead to practical operation time.

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