Browsing by Author "Gurboga B."

Now showing 1 - 5 of 5
  • No Thumbnail Available
    Item
    Development an optical sensor using lyotropic cholesteric liquid crystals for the detection of toxic gases
    (Elsevier GmbH, 2021) Kemiklioglu E.; Gurboga B.; Tuncgovde E.B.
    In the current study, a lyotropic cholesteric liquid crystal (ChLC) based sensor for the identification of vapors of polar (toluene and phenol) and apolar (1,2 dicholoropropane) toxic gases was investigated. The lyotropic ChLC sample including cholesteryl oleyl carbonate, cholesteryl pelargonate, and cholesteryl benzoate was supported on the chemically modified glass surfaces as an optical sensor for the detecting of these toxic gases vapors. The glass surfaces were modified by coating Dimethyloctadecyl [3-(trimethoxysilyl) propyl] ammonium chloride (DMOAP). The optical signal generated by the incorporation of different toxic gases vapors in the lyotropic ChLC layers which disturbs the pitch length. These toxic gases were evaporated at different temperatures and the exposure time was differentiated. Increasing solvent evaporation temperature lead a shift in the wavelength maximum to smaller wavelengths which can be observed by a naked eye. © 2021 Elsevier GmbH
  • No Thumbnail Available
    Item
    Liquid crystal-based elastomers in tissue engineering
    (John Wiley and Sons Inc, 2022) Gurboga B.; Tuncgovde E.B.; Kemiklioglu E.
    Liquid crystal elastomers (LCEs) play role in tissue engineering investigations, with the combination of orientational ordering generated by liquid crystal (LC) moieties and the elastic capabilities of polymers. Liquid crystal-based polymer materials require a thorough understanding of their features that set them apart from other smart materials for proper design and application. LCEs offer many advantages for their widespread use in the field of biomaterials, by virtue of their simplicity of processing, anisotropic behavior, and responding to numerous external stimuli. Especially, LCEs have widespread usage in bioengineering applications such as scaffolds due to their biocompatibility, viability, and proliferation properties of these materials. This study introduces a brief overview of the new areas of liquid crystal-based elastomer applications combining both biomaterials and engineering. © 2022 Wiley Periodicals LLC.
  • No Thumbnail Available
    Item
    Optical sensing of organic vapor using blue phase liquid crystals
    (Taylor and Francis Ltd., 2022) Gurboga B.; Kemiklioglu E.
    This study presents the investigation of the use of blue phase liquid crystals (BPLCs) for the sensing of toxic gas vapours of toluene, phenol and 1,2 dichloropropane. The vapours of these three toxic solvents were obtained by evaporating at different temperatures within the different times, and BPLC was separately exposed to these gas vapours. The diffusion and adsorption of these vapours on the BPLCs were investigated depending on the dimensions and polarity of the molecules. The optical response of BPLC exposed to gas vapours of toluene, phenol and 1,2 dichloropropane was determined with Bragg reflection wavelength as a function of temperature and time. We found that BPLC produced a remarkable change to the red side of the spectrum due to diffusion of toluene gas vapour by the BPLC sample and itsBragg reflection wavelength change within the time showed a good linearity correlation. Moreover, the diffusion coefficient of the toluene gas vapour in BPLC sample was calculated, and it was determined as 8.224 × 10−12 (cm2/s) by using a least-squares method. © 2022 Informa UK Limited, trading as Taylor & Francis Group.
  • No Thumbnail Available
    Item
    Exploring PEMFCs for Powering Untethered Small-Scale Robots
    (IEEE Computer Society, 2024) Manikandan A.L.; Gurboga B.; Munzenrieder N.; Raman A.; Gardeniers H.J.G.E.; Susarrey-Arce A.; Abelmann L.; Khalil I.S.M.
    Magnetically guided untethered devices are used in a variety of medical applications. These devices are typically powered by onboard battery units. Hydrogen fuel cells (FC) are a promising alternative power source for such small-scale devices since they rely on a sustainable fuels which produce electric power from the redox reaction of hydrogen and oxygen across a proton exchange membrane (PEM). Understanding the impact of decreasing the active electrode area in FCs is crucial for deploying FCs in untethered devices and gaining insights into the challenges of downscaling the devices. This paper investigates the performance of PEM FCs (PEMFCs) when their active area is reduced, and when the FC is supplied with reactants at different flow rates from a PEM electrolyzer. PEMFCs with three active electrode areas, 3.5 × 3.5 cm2, 2.7×2.7 cm2, and 1.6×1.6 cm2were designed, fabricated, and characterised. Maximum fuel cell output powers of 0.3 W, 0.09 W, and 0.03 W (maximum power densities of 0.025 W/cm2, 0.012 W/cm2, and 0.013 W/cm2) corresponding to the three aforementioned areas were achieved. Mathematical modeling of the PEMFC simulated the FC response, providing insights into the activation kinetics of the fuel cell. The smallest PEMFC with an active area of 1.6 × 1.6 cm2was used to power an inductor coil (rated 130 mA, 150 mH, 8 Ω). This study can guide the development of FCs to power untethered devices. © 2024 IEEE.
  • No Thumbnail Available
    Item
    Modeling of the lyotropic cholesteric liquid crystal based toxic gas sensor using adaptive neuro-fuzzy inference systems
    (Elsevier Ltd, 2024) Araz O.U.; Kemiklioglu E.; Gurboga B.
    Detection of toxic gases is important in a variety of settings, including industrial facilities, laboratories, and even in homes. In these settings, toxic gas detection can help prevent accidents and protect the health and safety of workers, researchers, and others who may be exposed to these gases. This study evaluates an Adaptive Neuro-Fuzzy Inference System (ANFIS) models in predicting the machining responses in the detection of toxic gases vapor, such as toluene (T), phenol (P) and 1,2 dichloropropane (D) using lyotropic cholesteric crystal (CLC) have been shown to have potential as gas sensors due to their unique optical and liquid crystal (LC) properties, and the ANFIS model may be used to better understand and optimize these properties for toxic gas detection. Experiments were carefully carried out to gather data on the response of a lyotropic CLC toxic gas vapor sensor. The effectiveness of using ANFIS combined with Grid Partitioning (GP) was then carefully studied and evaluated in terms of modeling and predicting the responses of the sensor. The best ANFIS-GP model is chosen from these criteria; RSS, PCC, R2, RMSE, MSE, MAE, and MAPE. In addition, validation was performed between the model and experimental data using the LOOCV method. The results show that the ANFIS-GP5 model with 96 fuzzy inference systems (FIS) rules with high R2 values. According to the ANFIS-GP5 model, R2varied ranges from 0.77 to 1 for train, test, and total data of lyotropic CLC sensor exposed to toluene, phenol and 1,2 dichloropropane toxic gases vapors. © 2023 Elsevier Ltd