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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/6
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Publication Open Access Emergence of near-infrared photoluminescence via ZnS shell growth on the AgBiS2 nanocrystals(American Chemical Society, 2024) Department of Chemistry; Department of Electrical and Electronics Engineering; Önal, Asım; Kaya, Tarık Safa; Metin, Önder; Nizamoğlu, Sedat; Department of Chemistry; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Sciences; College of EngineeringAgBiS2 nanocrystals (NCs), composed of nontoxic, earth-abundant materials and exhibiting an exceptionally high absorption coefficient from visible to near-infrared (>105 cm(-1)), hold promise for photovoltaics but have lack of photoluminescence (PL) due to intrinsic nonradiative recombination and challenging shell growth. In this study, we reported a facile wet-chemical approach for the epitaxial growth of ZnS shell on AgBiS2 NCs, which triggered the observation of PL emission in the near-infrared (764 nm). Since high quality of the core is critical for epitaxial shell growth, we first obtained rock-salt structured AgBiS2 NCs with high crystallinity, nearly spherical shape and monodisperse size distribution (<6%) via a dual-ligand approach reacting Ag-Bi oleate with elemental sulfur in oleylamine. Next, a zincblende ZnS shell with a low-lattice mismatch of 4.9% was grown on as-prepared AgBiS2 NCs via a highly reactive zinc (Zn(acac)(2)) precursor that led to a higher photoluminescence quantum yield (PLQY) of 15.3%, in comparison with a relatively low reactivity precursor (Zn(ac)(2)) resulting in reduced PLQY. The emission from AgBiS2 NCs with ultrastrong absorption, facilitated by shell growth, can open up new possibilities in lighting, display, and bioimaging.Publication Open Access Low complexity adaptation for reconfigurable intelligent surface-based MIMO systems(Institute of Electrical and Electronics Engineers (IEEE), 2020) Yiğit, Zehra; Altunbaş, İbrahim; Department of Electrical and Electronics Engineering; Başar, Ertuğrul; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 149116Reconfigurable intelligent surface (RIS)-based transmission technology offers a promising solution to enhance wireless communication performance cost-effectively through properly adjusting the parameters of a large number of passive reflecting elements. This letter proposes a cosine similarity theorem-based low-complexity algorithm for adapting the phase shifts of an RIS that assists a multiple-input multiple-output (MIMO) transmission system. A semi-analytical probabilistic approach is developed to derive the theoretical average bit error probability (ABEP) of the system. Furthermore, the validity of the theoretical analysis is supported through extensive computer simulations.Publication Open Access Throughput maximization in discrete rate based full duplex wireless powered communication networks(Wiley, 2020) Şadi, Yalçın; Department of Electrical and Electronics Engineering; Ergen, Sinem Çöleri; Iqbal, Muhammad Shahid; Faculty Member; PhD Student; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; 7211; N/AIn this study, we consider a discrete rate full-duplex wireless powered communication network. We characterize a novel optimization framework for sum throughput maximization to determine the rate adaptation and transmission schedule subject to energy causality and user transmit power. We first formulate the problem as a mixed integer nonlinear programming problem, which is hard to solve for a global optimum in polynomial-time. Then, we investigate the characteristics of the solution and propose a polynomial time heuristic algorithm for rate adaptation and scheduling problem. Through numerical analysis, we illustrate that the proposed scheduling algorithm outperforms the conventional schemes such as equal time allocation half-duplex and on-off transmission schemes for different initial battery levels, hybrid access point transmit power and network densities.Publication Open Access Compact and broadband silicon photonic multiplexers based on fast adiabatic structures(Optica Publishing Group, 2021) Department of Electrical and Electronics Engineering; Mağden, Emir Salih; Görgülü, Kazım; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; 276368; N/AWe present the theory and experimental demonstration for compact integrated spectral multiplexers utilizing fast adiabatic structures. The demonstrated 1x2 multiplexers effectively separate/combine broadband long-pass and short-pass signals, with compact footprint and low loss.Publication Open Access Fundamental sensitivity limitations of nanomechanical resonant sensors due to thermomechanical noise(Institute of Electrical and Electronics Engineers (IEEE), 2020) Hanay, M. Selim; Department of Electrical and Electronics Engineering; Demir, Alper; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 3756Nanomechanical resonators are used as high performance sensors of physical stimuli such as force and mass changes. Any such physical stimulus produces a shift in the resonance frequency of the nanomechanical structure, which can be measured accurately by using a feedback system that locks the frequency of a signal generator to the resonance. Closed-loop frequency tracking is the most prevalent technique in the fields of nanomechanical sensors and non-contact atomic force microscopy. Ultimate performance of sensors is limited by various nonideal effects such as temperature variations, radiation, electromagnetic interference, and noise arising from inherent physical mechanisms. Here, we consider the noise performance of nanomechanical resonant sensors, which has so far eluded explanation with conflicting results reported in the literature. We present a precise theory for these ubiquitous sensors based on nanomechanical resonators under feedback in order to decipher the fundamental sensitivity limitations due to thermomechanical noise. The results we obtain, when the performance is limited by the thermomechanical noise of the resonator, are in complete agreement with the ones from stochastic simulations. Our findings shed light on recent results in the literature and resolve a critical problem regarding the frequency noise of nanomechanical sensors under feedback. Our results have applications in nanomechanics, atomic force microscopy, microwave and suspended microchannel resonators.Publication Open Access A hybrid architecture for federated and centralized learning(Institute of Electrical and Electronics Engineers (IEEE), 2022) Elbir, Ahmet M.; Papazafeiropoulos, Anastasios K.; Kourtessis, Pandelis; Chatzinotas, Symeon; Department of Electrical and Electronics Engineering; Ergen, Sinem Çöleri; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 7211Many of the machine learning tasks rely on centralized learning (CL), which requires the transmission of local datasets from the clients to a parameter server (PS) entailing huge communication overhead. To overcome this, federated learning (FL) has been suggested as a promising tool, wherein the clients send only the model updates to the PS instead of the whole dataset. However, FL demands powerful computational resources from the clients. In practice, not all the clients have sufficient computational resources to participate in training. To address this common scenario, we propose a more efficient approach called hybrid federated and centralized learning (HFCL), wherein only the clients with sufficient resources employ FL, while the remaining ones send their datasets to the PS, which computes the model on behalf of them. Then, the model parameters are aggregated at the PS. To improve the efficiency of dataset transmission, we propose two different techniques: i) increased computation-per-client and ii) sequential data transmission. Notably, the HFCL frameworks outperform FL with up to 20% improvement in the learning accuracy when only half of the clients perform FL while having 50% less communication overhead than CL since all the clients collaborate on the learning process with their datasets.Publication Open Access Hybrid federated and centralized learning(Institute of Electrical and Electronics Engineers (IEEE), 2021) Mishra, K.V.; Department of Electrical and Electronics Engineering; Ergen, Sinem Çöleri; Elbir, Ahmet Musab; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 7211; N/AMany of the machine learning tasks are focused on centralized learning (CL), which requires the transmission of local datasets from the clients to a parameter server (PS) leading to a huge communication overhead. Federated learning (FL) overcomes this issue by allowing the clients to send only the model updates to the PS instead of the whole dataset. In this way, FL brings the learning to edge level, wherein powerful computational resources are required on the client side. This requirement may not always be satisfied because of diverse computational capabilities of edge devices. We address this through a novel hybrid federated and centralized learning (HFCL) framework to effectively train a learning model by exploiting the computational capability of the clients. In HFCL, only the clients who have sufficient resources employ FL; the remaining clients resort to CL by transmitting their local dataset to PS. This allows all the clients to collaborate on the learning process regardless of their computational resources. We also propose a sequential data transmission approach with HFCL (HFCL-SDT) to reduce the training duration. The proposed HFCL frameworks outperform previously proposed non-hybrid FL (CL) based schemes in terms of learning accuracy (communication overhead) since all the clients collaborate on the learning process with their datasets regardless of their computational resources.Publication Open Access Highly sensitive optical sensor for hydrogen gas based on a polymer microcylinder ring resonator(Elsevier, 2020) Eryürek, Mustafa; Department of Physics; Department of Chemistry; Department of Electrical and Electronics Engineering; Bavili, Nima; Balkan, Timuçin; Morova, Berna; Uysallı, Yiğit; Kaya, Sarp; Kiraz, Alper; Researcher; Researcher; PhD Student; Faculty Member; Faculty Member; Department of Physics; Department of Chemistry; Department of Electrical and Electronics Engineering; Koç University Tüpraş Energy Center (KUTEM) / Koç Üniversitesi Tüpraş Enerji Merkezi (KÜTEM); Graduate School of Sciences and Engineering; College of Sciences; College of Engineering; N/A; N/A; N/A; N/A; 116541; 22542A highly sensitive platform is demonstrated for hydrogen gas (H-2) sensing based on a polymer microcylinder ring resonator (PMRR) obtained by an optical fiber coated with an inner nanofilm of amorphous palladium (Pd) and an outer polymer layer of polydimethylsiloxane (PDMS) permeable to H-2. The sensing scheme is based on monitoring the spectral shifts of high-quality optical resonances called whispering gallery modes (WGMs) that propagate in the vicinity of the outer rim of the PDMS layer without being affected by the absorption and scattering losses caused by the Pd nanofilm. WGMs are excited by a single-mode tapered optical fiber evanescently coupled to the PMRR. The observed reversible spectral shifts of the WGMs are induced by changes in the diameter of the PDMS layer caused by expansion or contraction of the Pd nanofilm exposed to varying concentrations of H-2. Maximum spectral shift sensitivity of 140 pm/% H-2, a minimum response time of 95 s, and minimum limit of detection of similar to 60 ppm were measured for sensors prepared with different thicknesses of the amorphous Pd nanofilm and tested in the H-2 concentration range up to 1%, having nitrogen gas (N-2) as a carrier. Experiments were also conducted with Pd nanofilms annealed in air or N-2 atmosphere after the deposition. In both cases, smaller sensitivities were observed due to the formation of larger grains within the film, resulting in slower diffusion and reduced solubility of H in the Pd layer. The impacts of oxygen gas and humidity on sensor performance were also studied.Publication Open Access Self-organized variational autoencoders (self-vae) for learned image compression(Institute of Electrical and Electronics Engineers (IEEE), 2021) Malik, J.; Kıranyaz S.; Department of Electrical and Electronics Engineering; Tekalp, Ahmet Murat; Keleş, Onur; Yılmaz, Mustafa Akın; Güven, Hilal; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; 26207; N/A; N/A; N/AIn end-to-end optimized learned image compression, it is standard practice to use a convolutional variational autoencoder with generalized divisive normalization (GDN) to transform images into a latent space. Recently, Operational Neural Networks (ONNs) that learn the best non-linearity from a set of alternatives, and their “self-organized” variants, Self-ONNs, that approximate any non-linearity via Taylor series have been proposed to address the limitations of convolutional layers and a fixed nonlinear activation. In this paper, we propose to replace the convolutional and GDN layers in the variational autoencoder with self-organized operational layers, and propose a novel self-organized variational autoencoder (Self-VAE) architecture that benefits from stronger non-linearity. The experimental results demonstrate that the proposed Self-VAE yields improvements in both rate-distortion performance and perceptual image quality.Publication Open Access Understanding the link between inflammasome and apoptosis through the response of THP-1 cells against drugs using droplet-based microfluidics(American Chemical Society (ACS), 2022) Gençtürk, E.; Kasım, M.; Ülgen, K.O.; Department of Physics; Department of Electrical and Electronics Engineering; Kiraz, Alper; Morova, Berna; Faculty Member; Researcher; Department of Physics; Department of Electrical and Electronics Engineering; College of Sciences; College of Engineering; 22542; N/ADroplet-based microfluidic devices are used to investigate monocytic THP-1 cells in response to drug administration.Consistent and reproducible droplets are created, each of which acts as a bioreactor to carry out single cell experiments withminimized contamination and live cell tracking under an invertedfluorescence microscope for more than 2 days. Here, the effects ofthree different drugs (temsirolimus, rifabutin, and BAY 11-7082) on THP-1 are examined and the results are analyzed in the contextof the inflammasome and apoptosis relationship. The ASC adaptor gene tagged with GFP is monitored as the inflammasomereporter. Thus, a systematic way is presented for deciphering cell-to-cell heterogeneity, which is an important issue in cancertreatment. The drug temsirolimus, which has effects of disrupting the mTOR pathway and triggering apoptosis in tumor cells, causesTHP-1 cells to express ASC and to be involved in apoptosis. Treatment with rifabutin, which inhibits proliferation and initiatesapoptosis in cells, affects ASC expression byfirst increasing and then decreasing it. CASP-3, which has a role in apoptosis and isdirectly related to ASC, has an increasing level in inflammasome conditioning. Thus, the cell under the effect of rifabutin might befaced with programmed cell death faster. The drug BAY 11-7082, which is responsible for NF Kappa B inhibition, shows similar results totemsirolimus with more than 60% of cells having highfluorescence intensity (ASC expression). The microfluidic platform presentedhere offers strong potential for studying newly developed small-molecule inhibitors for personalized/precision medicine.