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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3
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Publication Metadata only Acetylene ligands stabilize atomically dispersed supported rhodium complexes under harsh conditions(Elsevier Science Sa, 2024) Hoffman, Adam S.; Hong, Jiyun; Perez-Aguilar, JorgeE.; Bare, Simon R.; Department of Chemical and Biological Engineering; Zhao, Yuxin; Öztulum, Samira Fatma Kurtoğlu; Uzun, Alper; Department of Chemical and Biological Engineering; Koç University Tüpraş Energy Center (KUTEM) / Koç Üniversitesi Tüpraş Enerji Merkezi (KÜTEM); Koç University Surface Science and Technology Center (KUYTAM) / Koç Üniversitesi Yüzey Teknolojileri Araştırmaları Merkezi (KUYTAM); Graduate School of Sciences and Engineering; College of EngineeringFacile sintering of atomically dispersed supported noble metal catalysts at catalytically relevant temperatures, particularly under reducing conditions, poses a challenge for their practical applications. Some ligands, such as carbonyls, aid in improving the stability at the expense of severely suppressing the catalytic activity. Here, we demonstrate that substitution of the carbonyl ligands with reactive acetylene ligands can maintain the atomic dispersion of the supported mononuclear rhodium complex under harsh reducing conditions (>573 K), as confirmed by in -situ X-ray absorption near -edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) spectroscopies. In contrast, the supported rhodium carbonyl complex aggregates into nanoclusters under identical conditions. Furthermore, our results indicate that the acetylene ligands provide this anti -sintering ability while retaining the hydrogenation activity.Publication Metadata only Energy-efficient production control of a make-to-stock system with buffer- and time-based policies(Taylor and Francis Ltd., 2023) Karabağ, Oktay; Khayyati, Siamak; Department of Business Administration; Tan, Barış; Department of Business Administration; College of Administrative Sciences and EconomicsIncreasing energy efficiency in manufacturing has significant environmental and cost benefits. Turning on or off a machine dynamically while considering the production rate requirements can offer substantial energy savings. In this work, we examine the optimal policies to control production and turn on and off a machine that operates in working, idle, off, and warmup modes for the case where demand inter-arrival, production, and warmup times have phase-type distributions. The optimal control problem that minimises the expected costs associated with the energy usage in different energy modes and the inventory and backlog costs is solved using a linear program associated with the underlying Markov Decision Process. We also present a matrix-geometric method to evaluate the steady-state performance of the system under a given threshold control policy. We show that when the inter-arrival time distribution is not exponential, the optimal control policy depends on both the current phase of the inter-arrival time and inventory position. The phase-dependent policy implemented by estimating the current phase based on the time elapsed since the last arrival yields a buffer- and time-based policy to control the energy mode and production. We show that policies that only use the inventory position information can be effective if the control parameters are chosen appropriately. However, the control policies that use both the inventory and time information further improve the performance.Publication Metadata only Continuous-flow simulation of manufacturing systems with assembly/disassembly machines, multiple loops and general layout(Elsevier Sci Ltd, 2023) Scrivano, Salvatore; Tolio, Tullio; Department of Business Administration; Tan, Barış; Department of Business Administration; College of Administrative Sciences and EconomicsPerformance evaluation methods are important to design and control manufacturing systems. Approximate analytical methods are fast, but they may be limited by the restrictive assumptions on the system. On the contrary, simulation has not specific limitations in its applicability, but the time to model and analyse a manufacturing system can increase as the level of detail addressed by the model increases. The main contribution of this study is presenting a computationally efficient methodology to simulate single-part continuous-flow manufacturing systems with assembly/disassembly machines, multiple loops, general layout and general inter-event time distributions. By using graph theory, a new method is presented to identify the machines causing slowdown, blocking and starvation in a general layout and determine the time before the occurrence of a state transition for each machine and the time before the fulfilment or depletion of each buffer. By advancing the time clock to the next event-time accordingly, the number of discrete events needed to be simulated is decreased compared to a discrete-event simulation with discrete flow of parts. As a result, the proposed method is on average 15 times faster than DES methods in the analysis of discrete-flow systems, and 110 times faster on average in the analysis of continuous-flow systems. The low computational time of the proposed method allows to simulate systems under general assumptions and in a very short time.Publication Metadata only Graph domain adaptation with localized graph signal representations(Elsevier GMBH, 2024) Pilavci, Yusuf Yigit; Guneyi, Eylem Tugce; Vural, Elif; Cengiz, Cemil; ; Graduate School of Sciences and Engineering;In this paper we propose a domain adaptation algorithm designed for graph domains. Given a source graph with many labeled nodes and a target graph with few or no labeled nodes, we aim to estimate the target labels by making use of the similarity between the characteristics of the variation of the label functions on the two graphs. Our assumption about the source and the target domains is that the local behavior of the label function, such as its spread and speed of variation on the graph, bears resemblance between the two graphs. We estimate the unknown target labels by solving an optimization problem where the label information is transferred from the source graph to the target graph based on the prior that the projections of the label functions onto localized graph bases be similar between the source and the target graphs. In order to efficiently capture the local variation of the label functions on the graphs, spectral graph wavelets are used as the graph bases. Experimentation on various data sets shows that the proposed method yields quite satisfactory classification accuracy compared to reference domain adaptation methods.Publication Metadata only Ice growth detection and the de-icing using dual functional capacitive sensor(ELSEVIER SCI LTD, 2024) Department of Mechanical Engineering; Malik, Anjum Naeem; Lazoğlu, İsmail; Department of Mechanical Engineering; Manufacturing and Automation Research Center (MARC); Graduate School of Sciences and Engineering; College of EngineeringIce detectors are vital for ice mitigation systems, ensuring accurate ice growth measurements across multiple icing-de-icing cycles. Residue ice on the sensor can lead to erroneous readings in subsequent cycles, so its removal is critical to obtain accurate readings. This article presents a novel capacitive ice detector with selfdeicing functionality employing nichrome electrodes for both sensing and de-icing. The sensor underwent testing in a cooling chamber for validation. The results confirm the developed ice detector's ability to quantify ice within 1 to 4 mm with up to 7.5 % error, while the de-icing unit consumes 35 W to remove a 2 mm ice layer in 60 s. Capacitive sensor de-icing can significantly enhance the performance of ice mitigation systems. This research significantly advances ice detection technology by providing a reliable method for accurate ice measurement and removal, offering a valuable foundation for future improvements in the field of ice mitigation systems.Publication Metadata only Experimental admittance-based system identification for equivalent circuit modeling of piezoelectric energy harvesters on a plate(Academic Press, 2024) Aghakhani, Amirreza; Department of Mechanical Engineering; Hoseyni, Seyedmorteza; Başdoğan, İpek; Department of Mechanical Engineering; Graduate School of Sciences and Engineering; College of EngineeringEquivalent circuit modeling is a useful tool for piezoelectric energy harvesters to analyze the electromechanical response of the system especially when complex host structure geometries and nonlinear circuits are used in the harvesting systems. Previous studies have used analytical and finite element models to estimate the equivalent circuit model (ECM) of piezoelectric energy harvesters (PEH) on beam- and plate-like structures. However, those methods require accurate analytical and/or numerical representation of the PEH. Here, we present an experimental admittance-based system identification method that allows us to identify the multi-modal ECM without prior knowledge of the host plate's geometry and/or physical properties of the piezoelectric patches. Using the proposed experimental method, we obtain the electromechanical frequency–response admittance of the PEH system at each vibration mode, and thereby, we calculate the equivalent system parameters. Additionally, a novel experimental technique is presented for the identification of the equivalent voltage sources associated with each LCR branch of the ECM. The derived ECM is experimentally validated for single and multiple piezoelectric patch harvesters on a plate. The electrical frequency response of the system has been validated for standard AC and rectifier circuits using SPICE software. Overall, the proposed admittance-based system identification is an accurate and robust method to identify the equivalent system parameters, making it a practical and reliable tool for modeling piezoelectric energy harvesting systems.Publication Metadata only Tool wear prediction through ai-assisted digital shadow using industrial edge device(Elsevier Sci Ltd, 2024) Kecibas, Gamze; Uresin, Ugur; Irican, Mumin; Department of Mechanical Engineering; Chehrehzad, Mohammadreza; Beşirova, Cemile; Lazoğlu, İsmail; Department of Mechanical Engineering; Manufacturing and Automation Research Center (MARC); Graduate School of Sciences and Engineering; College of EngineeringFlank wear of drilling tools in manufacturing is among the main factors affecting product quality and productivity. In this study, an AI-assisted digital shadow was created for the instant prediction of the drilling flank tool wear. The drilling data were collected simultaneously using an industrial edge device and a rotary dynamometer. Feature engineering was conducted on the collected data from devices in time and frequency domains. A recurrent neural network (RNN) based on bidirectional long short-term memory (Bi-LSTM) and bidirectional gated recurrent unit (Bi-GRU) architectures was implemented on specified tool wear regions dataset. The digital shadow was created using the industrial edge device and the predictive AI model to minimize costs by reducing the need for expensive multi-sensors, manufacturing downtime, and tool underuse or overuse in a smart manufacturing system. The proposed model predicts with high accuracy and computational time efficiency and can be integrated into digital twin systems.Publication Metadata only IL-modified MOF-177 filler boosts the CO2/N2 selectivity of Pebax membrane(Elsevier, 2024) Department of Chemical and Biological Engineering; Habib, Nitasha; Tarhanlı, İlayda; Şenses, Erkan; Keskin, Seda; Uzun, Alper; Department of Chemical and Biological Engineering; Koç University Tüpraş Energy Center (KUTEM) / Koç Üniversitesi Tüpraş Enerji Merkezi (KÜTEM); Koç University Surface Science and Technology Center (KUYTAM) / Koç Üniversitesi Yüzey Teknolojileri Araştırmaları Merkezi (KUYTAM); Koç University Boron and Advanced Materials Application and Research Center (KUBAM) / Koç Üniversitesi Bor ve İleri Malzemeler Uygulama ve Araştırma Merkezi (KUBAM); Graduate School of Sciences and Engineering; College of EngineeringMixed matrix membranes (MMMs) having ionic liquid (IL) modified metal-organic frameworks (MOF) as fillers present a broad potential for enhancing the separation properties of the polymers. Here, we incorporated an IL, 1butyl-1-methyl-pyrrolidinium tricyanomethanide [BMPyr][TCM], into MOF-177 and used the corresponding composite as filler in Pebax polymer to fabricate IL/MOF-177/Pebax MMMs at different filler loadings. These MMMs along with those prepared by using pristine MOF-177 as a filler were then tested for CO2/N2 separation by measuring their CO2 and N2 permeabilities at 35 degrees C and 1 bar. The [BMPyr][TCM]/MOF-177/Pebax MMM having 10 wt.% filler loading showed remarkable improvements in both CO2 permeability (137 f 2.0 Barrer) and CO2/N2 selectivity (622 f 105) compared to the neat Pebax membrane having corresponding performance values of 98.0 f 2.0 Barrer and 64.5 f 6.0, respectively. This simultaneous improvement in both CO2 permeability and CO2/N2 selectivity breaks the trade-off limitation of polymer membranes. Besides, the MMMs having 10 and 15 wt.% loadings of fillers were located well above the updated Robeson's upper bound, demonstrating the great promise of [BMPyr][TCM]/MOF-177/Pebax MMMs for CO2/N2 separation.Publication Metadata only Bismuthene nanosheets as a photodynamic and photothermal antibacterial agent under NIR light illumination(Elsevier Inc., 2024) Cekceoglu, Ilknur Aksoy; Patir, Imren Hatay; Department of Chemistry; Eroğlu, Zafer; Kubanaliev, Temirlan; Metin, Önder; Department of Chemistry; Koç University Surface Science and Technology Center (KUYTAM) / Koç Üniversitesi Yüzey Teknolojileri Araştırmaları Merkezi (KUYTAM); College of Sciences; Graduate School of Sciences and EngineeringBacterial infections remain a significant public health burden due to the emergence of antibiotic resistance and their non-specific cytotoxic effects, leading to the search for novel antibacterial agents. Two-dimensional (2D) pnictogens, which stand out with their advantegeous properties such as large surface areas, compatibility with biological systems, and permeability across biological membranes, have emerged as potential materials in the fight against bacterial infections. By considering all these advantages, here for the first time, the antibacterial activity of 2D bismuth (Bismuthene, Biene) on Gram-negative Escherichia coli (E. coli) and Pseudomonas aeruginosa (P. aeruginosa), Gram-positive Staphylococcus aureus (S. aureus) and Methicillin-Resistant Staphylococcus aureus (MRSA) were examined under NIR light illumination. A growth curve analysis was conducted with a concentration of 256 mu g*mL-1 of exfoliated Biene nanosheets to assess the inhibition effect and corresponding antibacterial effect (%) against each bacterial strain. The photodynamic theraphy (PDT) and photothermal therapy (PTT)-mediated antibacterial mechanisms were explored by analyzing the generation of reactive oxygen species (ROS) via Glutathione (GSH) oxidation assay while a photothermal camera monitored temperature dynamic changes during irradiation. The high specific surface area-dependent membrane damage ability of Biene and morphological changes of the bacteria were visualized by field emission scanning electron microscope (FESEM). The exciting growth inhibition activity of Biene nanosheets for all bacterial strains was increased during irradiation, and breathtakingly the inhibition rate reached up to >= 99.1 % for P. aeruginosa, S. aureus, and MRSA. Besides, S. aureus and MRSA are more susceptible to Biene than E. coli and P. aeruginosa.Publication Metadata only Sustainable vehicle allocation decisions under a vertical logistics collaboration setting(Elsevier Ltd, 2024) Çimen, Mustafa; Soysal, Mehmet; Benli, Damla; Graduate School of Sciences and EngineeringEnhancing vehicle utilization through a collaborative logistics approach allows businesses to contribute to the three pillars of sustainability by reducing fuel consumption and emissions, enhancing profit margins, and increasing customer satisfaction. This paper aims to introduce an Integer Linear Programming model for solving a vehicle allocation problem within a proposed vertical logistics collaboration setting. In this collaboration setup, production capacity allocation decisions are jointly made by collaborating customers and the logistics service provider, in order to create a more balanced and profitable logistics plan for all involved parties. Through the application of the proposed mathematical model, our numerical analyses illustrate the effects of the vertical logistics collaboration on the performance of transportation operations, including improved vehicle utilization rate and increased satisfied demand amount. Besides, we analyze the outputs of this operation related to the economic (by focusing on profit growth), environmental (by measuring the reduction in emissions), and social (by assessing the discounted transportation costs for customers) aspects of sustainability. To the best of our knowledge, no current study in the literature has established the vehicle allocation problem in the context of vertical logistics collaboration across all three sustainability pillars at the same time. The model can also serve as a tool for evaluating the potential economic, environmental, and social benefits arising from vertical collaboration and joint projects with customers, along with the support offered to logistics decisions.