Photonics-powered augmented reality skin electronics for proactive healthcare: multifaceted opportunities.

Rapid technological advancements have created opportunities for new solutions in various industries, including healthcare. One exciting new direction in this field of innovation is the combination of skin-based technologies and augmented reality (AR). These dermatological devices allow for the continuous and non-invasive measurement of vital signs and biomarkers, enabling the real-time diagnosis of anomalies, which have applications in telemedicine, oncology, dermatology, and early diagnostics. Despite its many potential benefits, there is a substantial information vacuum regarding using flexible photonics in conjunction with augmented reality for medical purposes. This review explores the current state of dermal augmented reality and flexible optics in skin-conforming sensing platforms by examining the obstacles faced thus far, including technical hurdles, demanding clinical validation standards, and problems with user acceptance. Our main areas of interest are skills, chiroptical properties, and health platform applications, such as optogenetic pixels, spectroscopic imagers, and optical biosensors. My skin-enhanced spherical dichroism and powerful spherically polarized light enable thorough physical inspection with these augmented reality devices: diabetic tracking, skin cancer diagnosis, and cardiovascular illness: preventative medicine, namely blood pressure screening. We demonstrate how to accomplish early prevention using case studies and emergency detection. Finally, it addresses real-world obstacles that hinder fully realizing these materials' extraordinary potential in advancing proactive and preventative personalized medicine, including technical constraints, clinical validation gaps, and barriers to widespread adoption.

Passively Q-switching an all polarization-maintaining erbium-doped fiber laser with a rhenium disulfide (ReS2) saturable absorber.

This study demonstrates a linearly polarized Er-doped fiber laser system featuring an all-polarization-maintaining (all-PM) architecture. Short pulses were generated by Q-switching operation based on drop-casting rhenium disulfide (ReS2) saturable absorber (SA) onto a fiber connector placed inside the laser cavity. The Q-switching operation of the laser was able to self-start at a low (23 mW) threshold power of the pump and without the need to use a polarization controller. The proposed laser was able to produce stable pulses with a center wavelength and 3-dB bandwidth of 1558.4 nm and 0.13 nm, respectively. The shortest pulse duration measured (2.8 µs) was achieved at a repetition rate of 37.6 kHz while the highest average output power and pulse energy were 2.2 mW and 76.5 nJ, respectively. Furthermore, as the cavity of the laser was designed to be all-PM the laser that it produced was linearly polarized and had a degree of polarization (DOP) at the level of 94.5 % and 40 dB polarization extinction ratio (PER). Therefore, the proposed laser is a suitable light source for optical applications in environments that are complex.

Uncovering the morphological differences between SARS-CoV-2 and SARS-CoV based on transmission electron microscopy images.

Comprehending the morphological disparities between SARS-CoV-2 and SARS-CoV viruses can shed light on the underlying mechanisms of infection and facilitate the development of effective diagnostic tools and treatments. Hence, this study aimed to conduct a comprehensive analysis and comparative assessment of the morphology of SARS-CoV-2 and SARS-CoV using transmission electron microscopy (TEM) images. The dataset encompassed 519 isolated SARS-CoV-2 images obtained from patients in Italy (INMI) and 248 isolated SARS-CoV images from patients in Germany (Frankfurt). In this paper, we employed TEM images to scrutinize morphological features, and the outcomes were contrasted with those of SARS-CoV viruses. The findings reveal disparities in the characteristics of SARS-CoV-2 and SARS-CoV, such as envelope protein (E) 98.6 and 102.2 nm, length of spike protein (S) 10.11 and 9.50 nm, roundness 0.86 and 0.88, circularity 0.78 and 0.76, and area sizes 25145.54 and 38591.35 pixels, respectively. In conclusion, these results will augment the identification of virus subtypes, aid in the study of antiviral medications, and enhance our understanding of disease progression and the virus life cycle. Moreover, these findings have the potential to assist in the development of more accurate epidemiological prediction models for COVID-19, leading to better outbreak management and saving lives.

Next-generation nanophotonic-enabled biosensors for intelligent diagnosis of SARS-CoV-2 variants.

Constantly mutating SARS-CoV-2 is a global concern resulting in COVID-19 infectious waves from time to time in different regions, challenging present-day diagnostics and therapeutics. Early-stage point-of-care diagnostic (POC) biosensors are a crucial vector for the timely management of morbidity and mortalities caused due to COVID-19. The state-of-the-art SARS-CoV-2 biosensors depend upon developing a single platform for its diverse variants/biomarkers, enabling precise detection and monitoring. Nanophotonic-enabled biosensors have emerged as 'one platform' to diagnose COVID-19, addressing the concern of constant viral mutation. This review assesses the evolution of current and future variants of the SARS-CoV-2 and critically summarizes the current state of biosensor approaches for detecting SARS-CoV-2 variants/biomarkers employing nanophotonic-enabled diagnostics. It discusses the integration of modern-age technologies, including artificial intelligence, machine learning and 5G communication with nanophotonic biosensors for intelligent COVID-19 monitoring and management. It also highlights the challenges and potential opportunities for developing intelligent biosensors for diagnosing future SARS-CoV-2 variants. This review will guide future research and development on nano-enabled intelligent photonic-biosensor strategies for early-stage diagnosing of highly infectious diseases to prevent repeated outbreaks and save associated human mortalities.

Density estimation of SARS-CoV2 spike proteins using super pixels segmentation technique.

The worldwide outbreak of COVID-19 disease was caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV 2). The existence of spike proteins, which allow these viruses to infect host cells, is one of the distinctive biological traits of various prior viruses. As a result, the process by which these viruses infect people is largely dependent on spike proteins. The density of SARS-CoV-2 spike proteins must be estimated to better understand and develop diagnostics and vaccines against the COVID-19 pandemic. CT scans and X-rays have three issues: frosted glass, consolidation, and strange roadway layouts. Each of these issues can be graded separately or together. Although CT scan is sensitive to COVID-19, it is not very specific. Therefore, patients who obtain these results should have more comprehensive clinical and laboratory tests to rule out other probable reasons. This work collected 586 SARS-CoV 2 transmission electron microscopy (TEM) images from open source for density estimation of virus spike proteins through a segmentation approach based on the superpixel technique. As a result, the spike density means of SARS-CoV2 and SARS-CoV were 21,97 nm and 22,45 nm, respectively. Furthermore, in the future, we aim to include this model in an intelligent system to enhance the accuracy of viral detection and classification. Moreover, we can remotely connect hospitals and public sites to conduct environmental hazard assessments and data collection.

Targeted delivery of paclitaxel drug using polymer-coated magnetic nanoparticles for fibrosarcoma therapy: in vitro and in vivo studies.

Fibrosarcoma is a rare type of cancer that affects cells known as fibroblasts that are malignant, locally recurring, and spreading tumor in fibrous tissue. In this work, an iron plate immersed in an aqueous solution of double added deionized water, supplemented with potassium permanganate solution (KMnO4) was carried out by the pulsed laser ablation in liquid method (PLAIL). Superparamagnetic iron oxide nanoparticles (SPIONs) were synthesized using different laser wavelengths (1064, 532, and 266 nm) at a fluence of 28 J/cm2 with 100 shots of the iron plate to control the concentration, shape and size of the prepared high-stability SPIONs. The drug nanocarrier was synthesized by coating SPION with paclitaxel (PTX)-loaded chitosan (Cs) and polyethylene glycol (PEG). This nanosystem was functionalized by receptors that target folate (FA). The physiochemical characteristics of SPION@Cs-PTX-PEG-FA nanoparticles were evaluated and confirmed by Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-Ray diffraction (XRD), atomic force microscopy (AFM), and dynamic light scattering (DLS) methods. Cell internalization, cytotoxicity assay (MTT), apoptosis induction, and gene expression of SPION@Cs-PTX-PEG-FA were estimated in fibrosarcoma cell lines, respectively. In vivo studies used BALB/c tumor-bearing mice. The results showed that SPION@Cs-PTX-PEG-FA exhibited suitable physical stability, spherical shape, desirable size, and charge. SPION@Cs-PTX-PEG-FA inhibited proliferation and induced apoptosis of cancer cells (P < 0.01). The results of the in vivo study showed that SPION@Cs-PTX-PEG-FA significantly decreased tumor size compared to free PTX and control samples (P < 0.05), leading to longer survival, significantly increased splenocyte proliferation and IFN-γ level, and significantly decreased the level of IL-4. All of these findings indicated the potential of SPION@Cs-PTX-PEG-FA as an antitumor therapeutic agent.

Palladium/Graphene Oxide Nanocomposite for Hydrogen Gas Sensing Applications Based on Tapered Optical Fiber.

Gaseous pollutants such as hydrogen gas (H2) are emitted in daily human activities. They have been massively studied owing to their high explosivity and widespread usage in many domains. The current research is designed to analyse optical fiber-based H2 gas sensors by incorporating palladium/graphene oxide (Pd/GO) nanocomposite coating as sensing layers. The fabricated multimode silica fiber (MMF) sensors were used as a transducing platform. The tapering process is essential to improve the sensitivity to the environment through the interaction of the evanescent field over the area of the tapered surface area. Several characterization methods including FESEM, EDX, AFM, and XRD were adopted to examine the structure properties of the materials and achieve more understandable facts about their functional performance of the optical sensor. Characterisation results demonstrated structures with a higher surface for analyte gas reaction to the optical sensor performance. Results indicated an observed increment in the Pd/GO nanocomposite-based sensor responses subjected to the H2 concentrations increased from 0.125% to 2.00%. The achieved sensitivities were 33.22/vol% with a response time of 48 s and recovery time of 7 min. The developed optical fiber sensors achieved excellent selectivity and stability toward H2 gas upon exposure to other gases such as ammonia and methane.

SARS-CoV-2 Morphometry Analysis and Prediction of Real Virus Levels Based on Full Recurrent Neural Network Using TEM Images.

The SARS-CoV-2 virus is responsible for the rapid global spread of the COVID-19 disease. As a result, it is critical to understand and collect primary data on the virus, infection epidemiology, and treatment. Despite the speed with which the virus was detected, studies of its cell biology and architecture at the ultrastructural level are still in their infancy. Therefore, we investigated and analyzed the viral morphometry of SARS-CoV-2 to extract important key points of the virus's characteristics. Then, we proposed a prediction model to identify the real virus levels based on the optimization of a full recurrent neural network (RNN) using transmission electron microscopy (TEM) images. Consequently, identification of virus levels depends on the size of the morphometry of the area (width, height, circularity, roundness, aspect ratio, and solidity). The results of our model were an error score of training network performance 3.216 × 10-11 at 639 epoch, regression of -1.6 × 10-9, momentum gain (Mu) 1 × 10-9, and gradient value of 9.6852 × 10-8, which represent a network with a high ability to predict virus levels. The fully automated system enables virologists to take a high-accuracy approach to virus diagnosis, prevention of mutations, and life cycle and improvement of diagnostic reagents and drugs, adding a point of view to the advancement of medical virology.

Chlorophyll Detection by Localized Surface Plasmon Resonance Using Functionalized Carbon Quantum Dots Triangle Ag Nanoparticles.

An optical sensor-based localized surface plasmon resonance (LSPR) sensor was demonstrated for sensitive and selective chlorophyll detection through the integration of amino-functionalized carbon quantum dots (NCQD) and triangle silver nanoparticles (AgNPs). The additions of amino groups to the CQD enhance the detection of chlorophyll through electrostatic interactions. AgNPs-NCQD composite was fabricated on the surface of the silanized glass slide using the self-assembly technique. The experimental results showed that the AgNPs-NCQD film-based LSPR sensor detects better than AgNPs and AgNPs-CQD films with a good correlation coefficient (R2 = 0.9835). AgNPs-NCQD showed a high sensitivity response of 2.23 nm ppm-1. The detection and quantification limits of AgNPs-NCQD are 1.03 ppm and 3.40 ppm, respectively, in the range of 0.05 to 6 ppm. Throughout this study, no significant interference was observed among the other ionic species (NO2-, PO4-, NH4+, and Fe3+). This study demonstrates the applicability of the proposed sensor (AgNPs-NCQD) as a sensing material for chlorophyll detection in oceans.

Performance Analysis of Conventional Machine Learning Algorithms for Diabetic Sensorimotor Polyneuropathy Severity Classification Using Nerve Conduction Studies.

Background: Diabetic sensorimotor polyneuropathy (DSPN) is a major form of complication that arises in long-term diabetic patients. Even though the application of machine learning (ML) in disease diagnosis is very common and well-established in the field of research, its application in DSPN diagnosis using nerve conduction studies (NCS), is very limited in the existing literature. Method: In this study, the NCS data were collected from the Diabetes Control and Complications Trial (DCCT) and its follow-up Epidemiology of Diabetes Interventions and Complications (EDIC) clinical trials. The NCS variables are median motor velocity (m/sec), median motor amplitude (mV), median motor F-wave (msec), median sensory velocity (m/sec), median sensory amplitude (µV), Peroneal Motor Velocity (m/sec), peroneal motor amplitude (mv), peroneal motor F-wave (msec), sural sensory velocity (m/sec), and sural sensory amplitude (µV). Three different feature ranking techniques were used to analyze the performance of eight different conventional classifiers. Results: The ensemble classifier outperformed other classifiers for the NCS data ranked when all the NCS features were used and provided an accuracy of 93.40%, sensitivity of 91.77%, and specificity of 98.44%. The random forest model exhibited the second-best performance using all the ten features with an accuracy of 93.26%, sensitivity of 91.95%, and specificity of 98.95%. Both ensemble and random forest showed the kappa value 0.82, which indicates that the models are in good agreement with the data and the variables used and are accurate to identify DSPN using these ML models. Conclusion: This study suggests that the ensemble classifier using all the ten NCS variables can predict the DSPN severity which can enhance the management of DSPN patients.

Photonics enabled intelligence system to identify SARS-CoV 2 mutations.

The COVID-19, MERS-CoV, and SARS-CoV are hazardous epidemics that have resulted in many deaths which caused a worldwide debate. Despite control efforts, SARS-CoV-2 continues to spread, and the fast spread of this highly infectious illness has posed a grave threat to global health. The effect of the SARS-CoV-2 mutation, on the other hand, has been characterized by worrying variations that modify viral characteristics in response to the changing resistance profile of the human population. The repeated transmission of virus mutation indicates that epidemics are likely to occur. Therefore, an early identification system of ongoing mutations of SARS-CoV-2 will provide essential insights for planning and avoiding future outbreaks. This article discussed the following highlights: First, comparing the omicron mutation with other variants; second, analysis and evaluation of the spread rate of the SARS-CoV 2 variations in the countries; third, identification of mutation areas in spike protein; and fourth, it discussed the photonics approaches enabled with artificial intelligence. Therefore, our goal is to identify the SARS-CoV 2 virus directly without the need for sample preparation or molecular amplification procedures. Furthermore, by connecting through the optical network, the COVID-19 test becomes a component of the Internet of healthcare things to improve precision, service efficiency, and flexibility and provide greater availability for the evaluation of the general population. KEY POINTS: • A proposed framework of photonics based on AI for identifying and sorting SARS-CoV 2 mutations. • Comparative scatter rates Omicron variant and other SARS-CoV 2 variations per country. • Evaluating mutation areas in spike protein and AI enabled by photonic technologies for SARS-CoV 2 virus detection.

Succinyl-κ-carrageenan Silver Nanotriangles Composite for Ammonium Localized Surface Plasmon Resonance Sensor.

This research investigates the physicochemical properties of biopolymer succinyl-κ-carrageenan as a potential sensing material for NH4+ Localized Surface Plasmon Resonance (LSPR) sensor. Succinyl-κ-carrageenan was synthesised by reacting κ-carrageenan with succinic anhydride. FESEM analysis shows succinyl-κ-carrageenan has an even and featureless topology compared to its pristine form. Succinyl-κ-carrageenan was composited with silver nanoparticles (AgNP) as LSPR sensing material. AFM analysis shows that AgNP-Succinyl-κ-carrageenan was rougher than AgNP-Succinyl-κ-carrageenan, indicating an increase in density of electronegative atom from oxygen compared to pristine κ-carrageenan. The sensitivity of AgNP-Succinyl-κ-carrageenan LSPR is higher than AgNP-κ-carrageenan LSPR. The reported LOD and LOQ of AgNP-Succinyl-κ-carrageenan LSPR are 0.5964 and 2.7192 ppm, respectively. Thus, AgNP-Succinyl-κ-carrageenan LSPR has a higher performance than AgNP-κ-carrageenan LSPR, broader detection range than the conventional method and high selectivity toward NH4+. Interaction mechanism studies show the adsorption of NH4+ on κ-carrageenan and succinyl-κ-carrageenan were through multilayer and chemisorption process that follows Freundlich and pseudo-second-order kinetic model.

Human Body Performance with COVID-19 Affectation According to Virus Specification Based on Biosensor Techniques.

Life was once normal before the first announcement of COVID-19's first case in Wuhan, China, and what was slowly spreading became an overnight worldwide pandemic. Ever since the virus spread at the end of 2019, it has been morphing and rapidly adapting to human nature changes which cause difficult conundrums in the efforts of fighting it. Thus, researchers were steered to investigate the virus in order to contain the outbreak considering its novelty and there being no known cure. In contribution to that, this paper extensively reviewed, compared, and analyzed two main points; SARS-CoV-2 virus transmission in humans and detection methods of COVID-19 in the human body. SARS-CoV-2 human exchange transmission methods reviewed four modes of transmission which are Respiratory Transmission, Fecal-Oral Transmission, Ocular transmission, and Vertical Transmission. The latter point particularly sheds light on the latest discoveries and advancements in the aim of COVID-19 diagnosis and detection of SARS-CoV-2 virus associated with this disease in the human body. The methods in this review paper were classified into two categories which are RNA-based detection including RT-PCR, LAMP, CRISPR, and NGS and secondly, biosensors detection including, electrochemical biosensors, electronic biosensors, piezoelectric biosensors, and optical biosensors.

Effects of Tungsten Disulphide Coating on Tapered Microfiber for Relative Humidity Sensing Applications.

Tungsten disulphide (WS2) is a two-dimensional transition-metal dichalcogenide material that can be used to improve the sensitivity of a variety of sensing applications. This study investigated the effect of WS2 coating on tapered region microfiber (MF) for relative humidity (RH) sensing applications. The flame brushing technique was used to taper the standard single-mode fiber (SMF) into three different waist diameter sizes of MF 2, 5, and 10 µm, respectively. The MFs were then coated with WS2 via a facile deposition method called the drop-casting technique. Since the MF had a strong evanescent field that allowed fast near-field interaction between the guided light and the environment, depositing WS2 onto the tapered region produced high humidity sensor sensitivity. The experiments were repeated three times to measure the average transmitted power, presenting repeatability and sensing stability. Each MF sample size was tested with varying humidity levels. Furthermore, the coated and non-coated MF performances were compared in the RH range of 45-90% RH at room temperature. It was found that the WS2 coating on 2 µm MF had a high sensitivity of 0.0861 dB/% RH with linearity over 99%. Thus, MF coated with WS2 encourages enhancement in the evanescent field effect in optical fiber humidity sensor applications.

A Review on Rhenium Disulfide: Synthesis Approaches, Optical Properties, and Applications in Pulsed Lasers.

Rhenium Disulfide (ReS2) has evolved as a novel 2D transition-metal dichalcogenide (TMD) material which has promising applications in optoelectronics and photonics because of its distinctive anisotropic optical properties. Saturable absorption property of ReS2 has been utilized to fabricate saturable absorber (SA) devices to generate short pulses in lasers systems. The results were outstanding, including high-repetition-rate pulses, large modulation depth, multi-wavelength pulses, broadband operation and low saturation intensity. In this review, we emphasize on formulating SAs based on ReS2 to produce pulsed lasers in the visible, near-infrared and mid-infrared wavelength regions with pulse durations down to femtosecond using mode-locking or Q-switching technique. We outline ReS2 synthesis techniques and integration platforms concerning solid-state and fiber-type lasers. We discuss the laser performance based on SAs attributes. Lastly, we draw conclusions and discuss challenges and future directions that will help to advance the domain of ultrafast photonic technology.

Comprehensive Review Tapered Optical Fiber Configurations for Sensing Application: Trend and Challenges.

Understanding environmental information is necessary for functions correlated with human activities to improve healthcare quality and reduce ecological risk. Tapered optical fibers reduce some limitations of such devices and can be considerably more responsive to fluorescence and absorption properties changes. Data have been collected from reliable sources such as Science Direct, IEEE Xplore, Scopus, Web of Science, PubMed, and Google Scholar. In this narrative review, we have summarized and analyzed eight classes of tapered-fiber forms: fiber Bragg grating (FBG), long-period fiber grating (LPFG), Mach-Zehnder interferometer (MZI), photonic crystals fiber (PCF), surface plasmonic resonance (SPR), multi-taper devices, fiber loop ring-down technology, and optical tweezers. We evaluated many issues to make an informed judgement about the viability of employing the best of these methods in optical sensors. The analysis of performance for tapered optical fibers depends on four mean parameters: taper length, sensitivity, wavelength scale, and waist diameter. Finally, we assess the most potent strategy that has the potential for medical and environmental applications.

Digital Filtering Techniques for Performance Improvement of Golay Coded TDM-FBG Sensor.

For almost a half-decade, the unique autocorrelation properties of Golay complementary pairs (GCP) have added a significant value to the key performance of conventional time-domain multiplexed fiber Bragg grating sensors (TDM-FBGs). However, the employment of the unipolar form of Golay coded TDM-FBG has suffered from several performance flaws, such as limited improvement of the signal-to-noise ratio (SNIR), noisy backgrounds, and distorted signals. Therefore, we propose and experimentally implement several digital filtering techniques to mitigate such limitations. Moving averages (MA), Savitzky-Golay (SG), and moving median (MM) filters were deployed to process the signals from two low reflectance FBG sensors located after around 16 km of fiber. The first part of the experiment discussed the sole deployment of Golay codes from 4 bits to 256 bits in the TDM-FBG sensor. As a result, the total SNIR of around 8.8 dB was experimentally confirmed for the longest 256-bit code. Furthermore, the individual deployment of MA, MM, and SG filters within the mentioned decoded sequences secured a further significant increase in SNIR of around 4, 3.5, and 3 dB, respectively. Thus, the deployment of the filtering technique alone resulted in at least four times faster measurement time (equivalent to 3 dB SNIR). Overall, the experimental analysis confirmed that MM outperformed the other two techniques in better signal shape, fastest signal transition time, comparable SNIR, and capability to maintain high spatial resolution.

Detection of COVID-19 Virus on Surfaces Using Photonics: Challenges and Perspectives.

The propagation of viruses has become a global threat as proven through the coronavirus disease (COVID-19) pandemic. Therefore, the quick detection of viral diseases and infections could be necessary. This study aims to develop a framework for virus diagnoses based on integrating photonics technology with artificial intelligence to enhance healthcare in public areas, marketplaces, hospitals, and airfields due to the distinct spectral signatures from lasers' effectiveness in the classification and monitoring of viruses. However, providing insights into the technical aspect also helps researchers identify the possibilities and difficulties in this field. The contents of this study were collected from six authoritative databases: Web of Science, IEEE Xplore, Science Direct, Scopus, PubMed Central, and Google Scholar. This review includes an analysis and summary of laser techniques to diagnose COVID-19 such as fluorescence methods, surface-enhanced Raman scattering, surface plasmon resonance, and integration of Raman scattering with SPR techniques. Finally, we select the best strategies that could potentially be the most effective methods of reducing epidemic spreading and improving healthcare in the environment.

Cantilever Beam with a Single Fiber Bragg Grating to Measure Temperature and Transversal Force Simultaneously.

This work investigates a new interrogation method of a fiber Bragg grating (FBG) sensor based on longer and shorter wavelengths to distinguish between transversal forces and temperature variations. Calibration experiments were carried out to examine the sensor's repeatability in response to the transversal forces and temperature changes. An automated calibration system was developed for the sensor's characterization, calibration, and repeatability testing. Experimental results showed that the FBG sensor can provide sensor repeatability of 13.21 pm and 17.015 pm for longer and shorter wavelengths, respectively. The obtained calibration coefficients expressed in the linear model using the matrix enabled the sensor to provide accurate predictions for both measurements. Analysis of the calibration and experiment results implied improvements for future work. Overall, the new interrogation method demonstrated the potential to employ the FBG sensing technique where discrimination between two/three measurands is needed.

Fabrication of a carbon nanotube/tungsten disulfide visible spectrum photodetector.

Two-dimensional-material-based photodetectors are gaining prominence in optoelectronic applications, but there are certain factors to consider with bulk material usage. The demand for a highly responsive and highly efficient device with an inexpensive fabrication method is always of paramount importance. Carbon nanotubes (CNT) are well known, owing to their upheld vigorous structural and optoelectronic characteristics, but to fabricate them at a large scale involves multifarious processes. A visible range photodetector device structure developed using a simple and inexpensive drop-casting technique is reported here. The optoelectronic characteristics of the device are studied with IV measurements under the light and dark conditions by incorporating a thin CNT layer on top of tungsten-disulfide-based heterojunction photodetector to enhance the overall characteristics such as detectivity, responsivity, photocurrent, rise time, and fall time in the visible range of the light spectrum with a violet light source at 441 nm. In the DC bias voltage range of -20 to 20 V, IV measurements are carried out under dark and illumination conditions with different incident power densities. The threshold voltage is recognized at 2.0 V. Photocurrent is found to be highly dependent on the state of the incident light. For 0.3074mW/cm2 illuminated power, the highest responsivity and detectivity are determined to be 0.57 A/W and 2.89×1011 Jones. These findings encourage an alternative fabrication method at a large scale to grow CNTs for the enhancement of optoelectronic properties of present two-dimensional-material-based optoelectronic and photonics applications.