Publications without Fulltext
Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3
Browse
76 results
Search Results
Publication Metadata only Deep learning-augmented T-junction droplet generation(Elsevier Inc., 2024) N/A; Department of Mechanical Engineering; Ahmadpour, Abdollah; Shojaeian, Mostafa; Taşoğlu, Savaş; Department of Mechanical Engineering; KU Arçelik Research Center for Creative Industries (KUAR) / KU Arçelik Yaratıcı Endüstriler Uygulama ve Araştırma Merkezi (KUAR); Koç Üniversitesi İş Bankası Yapay Zeka Uygulama ve Araştırma Merkezi (KUIS AI)/ Koç University İş Bank Artificial Intelligence Center (KUIS AI); Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); College of EngineeringDroplet generation technology has become increasingly important in a wide range of applications, including biotechnology and chemical synthesis. T-junction channels are commonly used for droplet generation due to their integration capability of a larger number of droplet generators in a compact space. In this study, a finite element analysis (FEA) approach is employed to simulate droplet production and its dynamic regimes in a T-junction configuration and collect data for post-processing analysis. Next, image analysis was performed to calculate the droplet length and determine the droplet generation regime. Furthermore, machine learning (ML) and deep learning (DL) algorithms were applied to estimate outputs through examination of input parameters within the simulation range. At the end, a graphical user interface (GUI) was developed for estimation of the droplet characteristics based on inputs, enabling the users to preselect their designs with comparable microfluidic configurations within the studied range.Publication Metadata only Mechanical properties of silicon nanowires with native oxide surface state(Elsevier, 2024) Department of Mechanical Engineering; Zarepakzad, Sina; Esfahani, Mohammad Nasr; Alaca, Burhanettin Erdem; Department of Mechanical Engineering; n2STAR-Koç University Nanofabrication and Nanocharacterization Center for Scientifc and Technological Advanced Research; Koç University Surface Science and Technology Center (KUYTAM) / Koç Üniversitesi Yüzey Teknolojileri Araştırmaları Merkezi (KUYTAM); Graduate School of Sciences and Engineering; College of EngineeringSilicon nanowires have attracted considerable interest due to their wide-ranging applications in nanoelectromechanical systems and nanoelectronics. Molecular dynamics simulations are powerful tools for studying the mechanical properties of nanowires. However, these simulations encounter challenges in interpreting the mechanical behavior and brittle to ductile transition of silicon nanowires, primarily due to surface effects such as the assumption of an unreconstructed surface state. This study specifically focuses on the tensile deformation of silicon nanowires with a native oxide layer, considering critical parameters such as cross-sectional shape, length -to -critical dimension ratio, temperature, the presence of nano -voids, and strain rate. By incorporating the native oxide layer, the article aims to provide a more realistic representation of the mechanical behavior for different critical dimensions and crystallographic orientations of silicon nanowires. The findings contribute to the advancement of knowledge regarding size -dependent elastic properties and strength of silicon nanowires.Publication Metadata only Magnetic mesoporous janus microrollers for combined chemo- and photothermal ablation therapy(John Wiley and Sons Inc, 2023) Aybar Tural, Gulsen; Bozuyuk, Ugur; Dogan, Nihal Olcay; Alapan, Yunus; Akolpoglu, Mukrime Birgul; Aghakhani, Amirreza; Lazovic, Jelena; Ozer, Ozgen; Department of Mechanical Engineering; Sitti, Metin; Department of Mechanical Engineering; College of Engineering; School of MedicineMobile microrobots have been proposed as a promising approach to overcome the limitations of traditional drug/gene delivery systems. Magnetically actuated surface rolling microrobots, or magnetic surface microrollers, have shown potential for navigation in physiologically relevant environments due to their robust locomotion characteristics. Although much is known about their locomotion abilities in various environments, the full extent of their potential in medical applications has yet to be fully explored. Here, the potential of surface microrollers for combined chemo- and photothermal ablation therapy under medical imaging modalities is demonstrated. The surface microrollers are half-coated with magnetic material, allowing for photothermal heating and magnetic locomotion, and loaded with a biopharmaceutics classification system (BCS) class IV anti-cancer drug, Docetaxel (DTX), for combined therapy. Synergistic action of on-demand photothermal ablation and the controlled release of DTX result in the efficient elimination of cancer cells. Furthermore, microrollers can be detected ex vivo with magnetic resonance imaging (MRI) and photoacoustic imaging (PA), highlighting the potential of surface microrollers for future targeted medical applications.Publication Metadata only Anisotropic wettability induced by femtosecond laser ablation(Wiley-V C H Verlag Gmbh, 2023) Yetisen, Ali K.; Department of Mechanical Engineering; Shojaeian, Mostafa; Taşoğlu, Savaş; Department of Mechanical 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 Sciences and Engineering; College of EngineeringLaser ablation has been utilized for locally and selectively modifying the surface wettability of materials in situ and enabling on-demand microfabrication. The anisotropic wettability has been observed on chemical and/or topographical patterns, such as an array of laser-inscribed strips with spacings, created on surfaces during the fabrication process. Herein, the effectiveness of the femtosecond laser ablation is evaluated in selectively modifying surface wettability. The areas processed by laser ablation exhibit anisotropic wetting behavior, even after the laser strips are overlapped. The laser-induced anisotropic surface wettability is present in space governed by laser scanning speed, scan/strip overlap, laser fluence, scan repetition, and bidirectional scanning angle. Moreover, the femtosecond laser ablation process is optimized to enhance the conventional laser inscription, leading to a modified and consistent methodology to achieve cost-effective fabrication. Herein, an approach for locally and selectively modifying surface wettability of materials in situ induced by femtosecond laser ablation is described. The laser-induced anisotropic surface wettability is found to appear in space governed by laser scanning speed, scan/strip overlap, laser fluence, scan repetition, and bidirectional scanning angle.Publication Metadata only Effect of the micro-textured piston on the performance of a hermetic reciprocating compressor(Sage Publications Ltd, 2023) Haque, Umar Ul; Department of Mechanical Engineering; Shahzad, Aamir; Lazoğlu, İsmail; Department of Mechanical Engineering; Manufacturing and Automation Research Center (MARC); Graduate School of Sciences and Engineering; College of EngineeringA hermetic reciprocating compressor is one of the most critical parts for the energy efficiency of a household refrigerator. Piston-cylinder contact in the hermetic compressor accounts for most of the energy loss. The tribological performance of the piston-cylinder pair can be enhanced by introducing micro-texturing on the piston surface. In this research, an experimental study is presented to tribologically assess the effect of the micro-textured piston on the performance of the hermetically sealed reciprocating compressor. The micro-texture on the piston surface was prepared by the laser surface texturing method. Four different micro-textures were studied: radial micro-grooves, axial micro-grooves, mesh micro-grooves, and micro-dimples. The textures’ size, shape, and depth were studied using scanning electron microscopy (SEM) and white light interferometry (WLI) techniques. The results were compared with the non-textured piston compressor. It was found that the radial, axial, and mesh micro-grooves pistons have a negative effect on the coefficient of performance of the hermetic reciprocating compressor. However, the piston with the micro-dimples texture increased the compressor's coefficient of performance by 1%. Refrigerant leakage from the piston-cylinder clearance was also investigated and it was observed that micro-dimples on the piston surface decrease the refrigerant leakage by 35% due to the presence of a continuous oil film between piston and cylinder. The compressor's cooling capacity (Qc) was observed to be increased by 1 W in the case of a micro-dimpled piston.Publication Metadata only Effect of finger moisture on tactile perception of electroadhesion(Institute of Electrical and Electronics Engineers, 2024) Lefevre, Philippe; Martinsen, Orjan Grottem; Department of Mechanical Engineering; Aliabbasi, Easa; Muzammil, Muhammad; Şirin, Ömer; Başdoğan, Çağatay; Department of Mechanical Engineering; Graduate School of Sciences and Engineering; College of EngineeringWe investigate the effect of finger moisture on the tactile perception of electroadhesion with 10 participants. Participants with moist fingers exhibited markedly higher threshold levels. Our electrical impedance measurements show a substantial reduction in impedance magnitude when sweat is present at the finger-touchscreen interface, indicating increased conductivity. Supporting this, our mechanical friction measurements show that the relative increase in electrostatic force due to electroadhesion is lower for a moist finger.Publication Metadata only Stencil-based selective surface functionalization of silicon nanowires in 3D device architectures for next-generation biochemical sensors(American Chemical Society, 2024) Esfahani, Mohammad Nasr; Leblebici, Yusuf; Department of Mechanical Engineering; Ali, Basit; Özkan, Sena Nur; Akıncı, Seçkin; Öztürk, Ece; Alaca, Burhanettin Erdem; Department of Mechanical Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); n2STAR-Koç University Nanofabrication and Nanocharacterization Center for Scientifc and Technological Advanced Research; Koç University Surface Science and Technology Center (KUYTAM) / Koç Üniversitesi Yüzey Teknolojileri Araştırmaları Merkezi (KUYTAM); Graduate School of Sciences and Engineering; Graduate School of Health Sciences; College of Engineering; School of MedicineSurface functionalization of 1D materials such as silicon nanowires is a critical preparation technology for biochemical sensing. However, existing nonselective functionalization techniques result in nonlocal binding and contamination, with potential device damage risks. Associated risks are further exacerbated for next-generation devices of a 3D nature with challenging topographies. Such 3D devices draw inspiration from the out-of-plane evolution of planar transistors to FinFETs and to today's gate-all-around transistors. This study is the first reported technological work addressing stencil-based surface decoration and selective functionalization of a suspended silicon nanowire building block embedded within such a device that involves two-order-of-magnitude thicker features compared to the nanowire critical dimensions. A gold pattern resolution of 3.0 mu m atop the silicon nanowires is achieved with a stencil aperture critical dimension of 2.2 mu m, accompanied by a die-level registration accuracy of 1.2 +/- 0.3 mu m. Plasma-enhanced chemical vapor deposition-based silicon nitride stencil membranes as large as 300 x 300 mu m2 are used to define the apertures without any membrane fracture during fabrication and membrane cleaning. The pattern-blurring aspect as a resolution-limiting factor is assessed by using 24 individual nanowire devices. Finally, gold-patterned silicon nanowires are functionalized using thiolated heparin and employed for selective attachment and detection of the human recombinant basic fibroblast growth factor (FGF-2). With the potential involvement in angiogenesis, the process of new blood vessel formation crucial for tumor growth, FGF-2 can serve as a potential prognostic biomarker in oncology. Demonstrated selectively on nanowires with high pattern resolution, the proposed functionalization approach offers possibilities for parallel sensing using vast nanowire arrays embedded in 3D device architectures developed for next-generation biochemical sensors in addition to serving various encapsulation and packaging needs.Publication Metadata only Doxorubicin-loaded liposome-like particles embedded in chitosan/hyaluronic acid-based hydrogels as a controlled drug release model for local treatment of glioblastoma(Elsevier B.V., 2024) Adiguzel, Seyfure; Karamese, Miray; Kugu, Senanur; Kacar, Elif Ayse; Esen, Muhammed Fevzi; Erdogan, Hakan; Bacanli, Merve Güdül; Altuntas, Sevde; Department of Mechanical Engineering; Taşoğlu, Savaş; Department of Mechanical Engineering; College of EngineeringGlioblastoma (GBM) resection and medication treatment are limited, and local drug therapies are required. This study aims to create a hybrid system comprising liposome-like particles (LLP-DOX) encapsulated in chitosan/hyaluronic acid/polyethyleneimine (CHI/HA/PEI) hydrogels, enabling controlled local delivery of doxorubicin (DOX) into the resection cavity for treating GBM. CHI/HA/PEI hydrogels were characterized morphologically, physically, chemically, mechanically, and thermally. Findings revealed a high network and compact micro-network structure, along with enhanced physical and thermal stability compared to CHI/HA hydrogels. Simultaneously, drug release from CHI/HA/PEI/LLP-DOX hydrogels was assessed, revealing continuous and controlled release up to the 148th hour, with no significant burst release. Cell studies showed that CHI/HA/PEI hydrogels are biocompatible with low genotoxicity. Additionally, LLP-DOX-loaded CHI/HA/PEI hydrogels significantly decreased cell viability and gene expression levels compared to LLP-DOX alone. It was also observed that the viability of GBM spheroids decreased over time when interacting with CHI/HA/PEI/LLP-DOX hydrogels, accompanied by a reduction in total surface area and an increase in apoptotic tendencies. In this study, we hypothesized that creating a hybrid drug delivery system by encapsulating DOX-loaded LLPs within a CHI/HA/PEI hydrogel matrix could achieve sustained drug release, improve anticancer efficacy via localized treatment, and effectively mitigate GBM progression for 3D microtissues.Publication Metadata only ML-augmented bayesian optimization of pain induced by microneedles(Wiley, 2024) Department of Mechanical Engineering; Choukri, Abdullah Ahmed; Taşoğlu, Savaş; Department of Mechanical Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); Koç Üniversitesi İş Bankası Yapay Zeka Uygulama ve Araştırma Merkezi (KUIS AI)/ Koç University İş Bank Artificial Intelligence Center (KUIS AI); KU Arçelik Research Center for Creative Industries (KUAR) / KU Arçelik Yaratıcı Endüstriler Uygulama ve Araştırma Merkezi (KUAR); Graduate School of Sciences and Engineering; College of EngineeringMicroneedles (MNs) have emerged as a promising solution for drug delivery and extraction of body fluids. Pain is an important physiological attribute to be examined when designing MNs. There is no known representation of pain with geometric features of a MN despite the focus on experimental work. This study focuses on optimizing MN designs with the aim of minimizing pain through means of machine learning, finite element analysis, and optimization tools. Three distinct approaches are proposed. The first approach involves training multiple regression models on data obtained through finite element analysis in COMSOL. The second approach uses COMSOL's built-in nonlinear optimization solver. Finally, the third approach utilizes the LiveLink interface between COMSOL and MATLAB, combined with Bayesian optimization. Each approach presents unique strengths and challenges, with the third approach demonstrating significant promise due to its efficiency, practicality, and time-saving. A machine learning (ML)-augmented Bayesian framework is described in the article number by Ahmed Choukri Abdullah and Savas Tasoglu to optimize and minimize pain induced by microneedles. Introduction of ML-based optimization frameworks into microfabrication processes can pave the way for a much more effective and customized designs of minimally invasive microneedles.Publication Metadata only Optimizing solid microneedle design: a comprehensive ML-augmented DOE approach(American Chemical Society, 2024) Department of Mechanical Engineering; Choukri, Abdullah Ahmed; Ahmadinejad, Erfan; Taşoğlu, Savaş; Department of Mechanical Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); Koç Üniversitesi İş Bankası Yapay Zeka Uygulama ve Araştırma Merkezi (KUIS AI)/ Koç University İş Bank Artificial Intelligence Center (KUIS AI); KU Arçelik Research Center for Creative Industries (KUAR) / KU Arçelik Yaratıcı Endüstriler Uygulama ve Araştırma Merkezi (KUAR); Graduate School of Sciences and Engineering; College of EngineeringMicroneedles (MNs), that is, a matrix of micrometer-scale needles, have diverse applications in drug delivery, skincare therapy, and health monitoring. MNs offer a minimally invasive alternative to hypodermic needles, characterized by rapid and painless procedures, cost-effective fabrication methods, and reduced tissue damage. This study explores four MN designs, cone-shaped, tapered cone-shaped, pyramidal with a square base, and pyramidal with a triangular-shaped base, and their optimization based on predefined criteria. The workflow encompasses three loading conditions: compressive load during insertion, critical buckling load, and bending loading resulting from incorrect insertion. Geometric parameters such as base radius/width, tip radius/width, height, and tapered angle tip influence the output criteria, namely, total deformation, critical buckling loads, factor of safety (FOS), and bending stress. The comprehensive framework employing a design of experiment approach within the ANSYS workbench toolbox establishes a mathematical model and a response surface fitting model. The resulting regression model, sensitivity chart, and response curve are used to create a multiobjective optimization problem that helps achieve an optimized MN geometrical design across the introduced four shapes, integrating machine learning (ML) techniques. This study contributes valuable insights into a potential ML-augmented optimization framework for MNs via needle designs to stay durable for various physiologically relevant conditions.