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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/6

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    PublicationOpen Access
    Efficient photocapacitors via ternary hybrid photovoltaic optimization for photostimulation of neurons
    (Optical Society of America (OSA), 2020) Department of Electrical and Electronics Engineering; Srivastava, Shashi Bhushan; Melikov, Rustamzhon; Yıldız, Erdost; Han, Mertcan; Şahin, Afsun; Nizamoğlu, Sedat; Researcher; PhD Student; PhD Student; Master Student; Faculty Member; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; Graduate School of Health Sciences; School of Medicine; College of Engineering; N/A; N/A; N/A; N/A; 171267; 130295
    Optoelectronic photoelectrodes based on capacitive charge-transfer offer an attractive route to develop safe and effective neuromodulators. Here, we demonstrate efficient optoelectronic photoelectrodes that are based on the incorporation of quantum dots (QDs) into poly(3-hexylthiophene-2,5-diyl) (P3HT) and [6,6]-Phenyl-C61-butyric acid methyl ester (PCBM) bulk heterojunction. We control the performance of the photoelectrode by the blend ratio, thickness, and nanomorphology of the ternary bulk heterojunction. The optimization led to a photocapacitor that has a photovoltage of 450 mV under a light intensity level of 20 mW.cm(-2) and a responsivity of 99 mA/W corresponding to the most light-sensitive organic photoelectrode reported to date. The photocapacitor can facilitate action potential generation by hippocampal neurons via burst waveforms at an intensity level of 20 mW.cm(-2). Therefore, the results point to an alternative direction in the engineering of safe and ultra-light-sensitive neural interfaces.
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    PublicationOpen Access
    A cartridge based sensor array platform for multiple coagulation measurements from plasma
    (Royal Society of Chemistry (RSC), 2015) Bulut, Serpil; Yaralioglu, G. G.; Department of Electrical and Electronics Engineering; Department of Molecular Biology and Genetics; Department of Chemical and Biological Engineering; Çakmak, Onur; Ermek, Erhan; Kılınç, Necmettin; Barış, İbrahim; Kavaklı, İbrahim Halil; Ürey, Hakan; PhD Student; Other; Researcher; Teaching Faculty; Faculty Member; Department of Electrical and Electronics Engineering; Department of Molecular Biology and Genetics; Department of Chemical and Biological Engineering; College of Engineering; Graduate School of Sciences and Engineering; College of Sciences; N/A; 109991; N/A; 111629; 40319; 8579
    This paper proposes a MEMS-based sensor array enabling multiple clot-time tests for plasma in one disposable microfluidic cartridge. The versatile LoC (Lab-on-Chip) platform technology is demonstrated here for real-time coagulation tests (activated Partial Thromboplastin Time (aPTT) and Prothrombin Time (PT)). The system has a reader unit and a disposable cartridge. The reader has no electrical connections to the cartridge. This enables simple and low-cost cartridge designs and avoids reliability problems associated with electrical connections. The cartridge consists of microfluidic channels and MEMS microcantilevers placed in each channel. The microcantilevers are made of electroplated nickel. They are actuated remotely using an external electro-coil and the read-out is also conducted remotely using a laser. The phase difference between the cantilever oscillation and the coil drive is monitored in real time. During coagulation, the viscosity of the blood plasma increases resulting in a change in the phase read-out. The proposed assay was tested on human and control plasma samples for PT and aPTT measurements. PT and aPTT measurements from control plasma samples are comparable with the manufacturer's datasheet and the commercial reference device. The measurement system has an overall 7.28% and 6.33% CV for PT and aPTT, respectively. For further implementation, the microfluidic channels of the cartridge were functionalized for PT and aPTT tests by drying specific reagents in each channel. Since simultaneous PT and aPTT measurements are needed in order to properly evaluate the coagulation system, one of the most prominent features of the proposed assay is enabling parallel measurement of different coagulation parameters. Additionally, the design of the cartridge and the read-out system as well as the obtained reproducible results with 10 mu l of the plasma samples suggest an opportunity for a possible point-of-care application.
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    PublicationOpen Access
    Applications of augmented reality in ophthalmology [invited]
    (Optical Society of America (OSA), 2021) Artal, Pablo; Department of Physics; Department of Electrical and Electronics Engineering; Aydındoğan, Güneş; Kavaklı, Koray; Ürey, Hakan; Şahin, Afsun; Faculty Member; Faculty Member; Department of Physics; Department of Electrical and Electronics Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); Graduate School of Sciences and Engineering; College of Engineering; School of Medicine; N/A; N/A; 8579; 171267
    Throughout the last decade, augmented reality (AR) head-mounted displays (HMDs) have gradually become a substantial part of modern life, with increasing applications ranging from gaming and driver assistance to medical training. Owing to the tremendous progress in miniaturized displays, cameras, and sensors, HMDs are now used for the diagnosis, treatment, and follow-up of several eye diseases. In this review, we discuss the current state-of-the-art as well as potential uses of AR in ophthalmology. This review includes the following topics: (i) underlying optical technologies, displays and trackers, holography, and adaptive optics; (ii) accommodation, 3D vision, and related problems such as presbyopia, amblyopia, strabismus, and refractive errors; (iii) AR technologies in lens and corneal disorders, in particular cataract and keratoconus; (iv) AR technologies in retinal disorders including age-related macular degeneration (AMD), glaucoma, color blindness, and vision simulators developed for other types of low-vision patients.
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    PublicationOpen Access
    Machine learning-enabled multiplexed microfluidic sensors
    (American Institute of Physics (AIP) Publishing, 2020) Yetişen, Ali Kemal; N/A; Department of Mechanical Engineering; Department of Electrical and Electronics Engineering; Dabbagh, Sajjad Rahmani; Rabbi, Fazle; Doğan, Zafer; Taşoğlu, Savaş; Faculty Member; Faculty Member; Department of Mechanical Engineering; Department of Electrical and Electronics Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); KU Arçelik Research Center for Creative Industries (KUAR) / KU Arçelik Yaratıcı Endüstriler Uygulama ve Araştırma Merkezi (KUAR); Graduate School of Social Sciences and Humanities; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; 280658; 291971
    High-throughput, cost-effective, and portable devices can enhance the performance of point-of-care tests. Such devices are able to acquire images from samples at a high rate in combination with microfluidic chips in point-of-care applications. However, interpreting and analyzing the large amount of acquired data is not only a labor-intensive and time-consuming process, but also prone to the bias of the user and low accuracy. Integrating machine learning (ML) with the image acquisition capability of smartphones as well as increasing computing power could address the need for high-throughput, accurate, and automatized detection, data processing, and quantification of results. Here, ML-supported diagnostic technologies are presented. These technologies include quantification of colorimetric tests, classification of biological samples (cells and sperms), soft sensors, assay type detection, and recognition of the fluid properties. Challenges regarding the implementation of ML methods, including the required number of data points, image acquisition prerequisites, and execution of data-limited experiments are also discussed.