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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3
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Publication Metadata only Selection of ionic liquid electrolytes for high-performing lithium-sulfur batteries: an experiment-guided high-throughput machine learning analysis(Elsevier B.V., 2024) Kılıç, Ayşegül; Abdelaty, Omar; Yıldırım, Ramazan; Eroğlu, Damla; Department of Chemical and Biological Engineering; Zeeshan, Muhammad; 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 EngineeringThe polysulfide (PS) shuttle mechanism (PSM) is one of the most significant challenges of lithium-sulfur (Li-S) batteries in achieving high capacity and cyclability. One way to minimize the shuttle effect is to limit the PS solubilities in the battery electrolyte. Ionic liquids (IL) are particularly suited as electrolyte solvents because of their tunable physical and chemical properties. In this work, thousands of ILs are screened to narrow down potentially viable candidates to be used as electrolytes in Li-S batteries. To that end, the COnductor-like Screening Model for Realistic Solvents (COSMO-RS) calculations are performed over more than 36,000 ILs. An extensive database containing PS solubilities and other relevant properties is constructed at 25 °C. First, the effectiveness of the COSMO-RS calculations is experimentally tested with six different ILs having a wide range of solubility and viscosity values; a strong correlation between the PS solubility and battery performance is obtained. After specifying the target limits for promising ILs using the experimental battery performance data, machine learning (ML) tools are used to predict and identify the relationship between IL properties and PS solubilities and structural and molecular descriptors of ILs. The extreme gradient boosting (XGBoost) method successfully predicts the solubility and property values. Association rule mining (ARM) and the feature importance analysis show that anion descriptors are more dominant, whereas cations have less impact on the solubilities and properties of ILs. Finally, the imidazolium and pyridinium ILs with bis_imide and borate anion groups are identified as the most promising ones.Publication Metadata only Hydrothermal liquefaction of chlamydomonas nivalis and nannochloropsis gaditana microalgae under different operating conditions over copper-exchanged zeolites(Elsevier B.V., 2024) Borhan, E.; Haznedaroglu, Berat Z.; Department of Chemical and Biological Engineering; Yousefzadeh, Hamed; Uzun, Alper; Erkey, Can; 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); College of EngineeringIn this study, two different green microalgae, Chlamydomonas nivalis (C. nivalis) and Nannochloropsis gaditana (N. gaditana), were cultivated in open ponds and the harvested wet biomass was converted to bio-crude by hydrothermal liquefaction (HTL) with/without catalyst. Catalytic HTL experiments were performed by using copper-exchanged zeolites including Cu-MOR, Cu-ZSM-5, and Cu-SSZ13, synthesized by recently developed supercritical ion exchange method using scCO2. The composition of all bio-crudes was analyzed by elemental analysis and GC/MS. First, the effects of different operating conditions on the yields of the products and the bio-crude composition were determined for non-catalytic process. Temperature, duration, and water/algae biomass ratio in the feed were the process parameters investigated in the ranges of 250–350 ºC, 10–60 min, and 5–20 wt%, respectively. For C. nivalis, 300 ºC, 60 min, and water/algae ratio of 4 were the optimum conditions which led to maximum bio-crude yield of 18.8 wt%, while 300 ºC, 30 min, and water/algae ratio of 9 were the optimum ones for N. gaditana at which the maximum bio-crude yield of 34.0 wt% was observed. Bio-crude yield of N. gaditana was improved using Cu-MOR, while using catalysts for the case of C. nivalis resulted in more gasification with no positive effect on bio-crude yield. Moreover, elemental analysis showed that the fraction of nitrogen and oxygen in biocrude decreased in catalytic HTL runs, in line with the GC/MS results showing that the concentration of hydrocarbons and cyclic compounds increased in the presence of catalysts accompanied by a decrease in concentration of nitrogenous compounds.Publication Metadata only Stepwise conversion of methane to methanol over Cu-mordenite prepared by supercritical and aqueous ion exchange routes and quantification of active Cu species by H2-TPR(Elsevier, 2023) Sushkevich, Vitaly; van Bokhoven, Jeroen A.; Department of Chemical and Biological Engineering; Yousefzadeh, Hamed; Bozbağ, Selmi Erim; Erkey, Can; Department of Chemical and Biological Engineering; Koç University Tüpraş Energy Center (KUTEM) / Koç Üniversitesi Tüpraş Enerji Merkezi (KÜTEM); College of EngineeringCopper-exchanged mordenite prepared by supercritical ion exchange (SCIE) and aqueous ion exchange (AIE) were investigated in stepwise conversion of methane to methanol. Increasing the oxygen activation temperature and methane reaction time enhances the methanol yield of copper-exchanged mordenite prepared by SCIE (CuMORS). The reducibility of Cu-MORS was compared with those of Cu-MORA prepared by aqueous ion exchange (AIE) using H-2-TPR. It was demonstrated for the first time that deconvoluted H2-TPR profile coupled with effects of Cu loading and oxygen activation temperature on methanol yield data can be used to distinguish the active Cu sites from inactive ones based on their reduction temperature. The copper species responsible for methane activation were found to be reduced below 150 C by H-2 in both Cu-MORS and Cu-MORA. From the stoichiometry of the reaction of H-2 with Cu2+ species, the average number of copper atoms of active sites were calculated as 2.07 and 2.80 for Cu-MORS and Cu-MORA, respectively. Differences in structure of copper species caused by the synthesis routes were also detected by in-situ FTIR upon NO adsorption indicating a higher susceptibility of CuMORS towards autoreduction. The results demonstrated the potential of TPR based methods to identify copper active sites and suggested the importance of site selective ion exchange in order to controllably synthesize active Cu species in zeolites.Publication Metadata only Unveiling hidden connections in omics data via pyPARAGON: an integrative hybrid approach for disease network construction(Oxford University Press, 2024) Arici, Muslum Kaan; Department of Chemical and Biological Engineering; Tunçbağ, Nurcan; Department of Chemical and Biological Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); College of Engineering; School of MedicineNetwork inference or reconstruction algorithms play an integral role in successfully analyzing and identifying causal relationships between omics hits for detecting dysregulated and altered signaling components in various contexts, encompassing disease states and drug perturbations. However, accurate representation of signaling networks and identification of context-specific interactions within sparse omics datasets in complex interactomes pose significant challenges in integrative approaches. To address these challenges, we present pyPARAGON (PAgeRAnk-flux on Graphlet-guided network for multi-Omic data integratioN), a novel tool that combines network propagation with graphlets. pyPARAGON enhances accuracy and minimizes the inclusion of nonspecific interactions in signaling networks by utilizing network rather than relying on pairwise connections among proteins. Through comprehensive evaluations on benchmark signaling pathways, we demonstrate that pyPARAGON outperforms state-of-the-art approaches in node propagation and edge inference. Furthermore, pyPARAGON exhibits promising performance in discovering cancer driver networks. Notably, we demonstrate its utility in network-based stratification of patient tumors by integrating phosphoproteomic data from 105 breast cancer tumors with the interactome and demonstrating tumor-specific signaling pathways. Overall, pyPARAGON is a novel tool for analyzing and integrating multi-omic data in the context of signaling networks.Publication Metadata only Theoretical insight into selectivity and catalytic activity of γ-(Al2O3) supported Ir(CO)2 complex for 1,3-butadiene partial hydrogenation(Elsevier, 2024) Akgul, Deniz; Ince, Deniz; Kozuch, Sebastian; Aviyente, Viktorya; Department of Chemical and Biological Engineering; Uzun, Alper; Department of Chemical and Biological Engineering; Koç University Tüpraş Energy Center (KUTEM) / Koç Üniversitesi Tüpraş Enerji Merkezi (KÜTEM); College of EngineeringSelective hydrogenation reactions of unsaturated hydrocarbons over metal oxide-supported transition metals like palladium, platinum, rhodium, or iridium complexes are common processes, but understanding the reaction mechanisms is still challenging, since the interactions between the reactants and the active center remain unclear. Herein, we have modeled the 1,3-butadiene hydrogenation mechanism in the presence of gamma-(Al2O3)2 supported iridium catalyst, initially present as [Ir(I)(CO)2]+. The origins of the selectivity and reactivity of the reduction reactions of butadiene to butenes has been elucidated by using density functional theory (DFT) within the framework of the energetic span model.Publication Metadata only Design and operation of renewable energy microgrids under uncertainty towards green deal and minimum carbon emissions(Elsevier Ltd, 2024) Department of Chemical and Biological Engineering; Tatar, Su Meyra; Aydın, Erdal; Department of Chemical and Biological Engineering; Koç University Tüpraş Energy Center (KUTEM); Graduate School of Sciences and Engineering; College of EngineeringThe regulations regarding the Paris Agreement are inevitable to keep the global temperature rise within 2 °C. Moreover, integrating renewable energy-based equipment and adopting new ways of producing energy resources, for example Power to Gas (PtG) technology, becomes essential because of the current environmental, economic, and political concerns. It is vital to supply the growing energy demand with the increasing population. Uncertainty must be considered in the transition phase since parameters regarding the electricity demand, carbon tax policies, and intermittency of renewable energy-based equipment have intermittent nature. A multi-period two-stage stochastic MILP model is proposed in this work where the wind speed, solar irradiance, temperature, power demand, carbon emission trading (CET) price, and CO2 emission limit are considered uncertain parameters. Three stochastic case studies with scenarios including different combinations of the aforementioned uncertain parameters are investigated. Results show that more renewable energy-based equipment with higher rated power values is chosen as the sanctions get stricter. In addition, the optimality of PtG technology is also investigated for a specific location. Implementing the CO2 emission limit as an uncertain parameter instead of including CET price as uncertain results in lower annual CO2 emission rates and higher net present cost values. © 2023 Elsevier LtdPublication 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 High-throughput computational screening of MOF adsorbents for efficient propane capture from air and natural gas mixtures(AIP Publishing, 2024) Department of Chemical and Biological Engineering; Erçakır, Göktuğ; Aksu, Gökhan Önder; Keskin, Seda; Department of Chemical and Biological Engineering; Graduate School of Sciences and Engineering; College of EngineeringIn this study, we used a high-throughput computational screening approach to examine the potential of metal-organic frameworks (MOFs) for capturing propane (C3H8) from different gas mixtures. We focused on Quantum MOF (QMOF) database composed of both synthesized and hypothetical MOFs and performed Grand Canonical Monte Carlo (GCMC) simulations to compute C3H8/N2/O2/Ar and C3H8/C2H6/CH4 mixture adsorption properties of MOFs. The separation of C3H8 from air mixture and the simultaneous separation of C3H8 and C2H6 from CH4 were studied for six different adsorption-based processes at various temperatures and pressures, including vacuum-swing adsorption (VSA), pressure-swing adsorption (PSA), vacuum-temperature swing adsorption (VTSA), and pressure-temperature swing adsorption (PTSA). The results of molecular simulations were used to evaluate the MOF adsorbents and the type of separation processes based on selectivity, working capacity, adsorbent performance score, and regenerability. Our results showed that VTSA is the most effective process since many MOFs offer high regenerability (>90%) combined with high C3H8 selectivity (>7 x 103) and high C2H6 + C3H8 selectivity (>100) for C3H8 capture from air and natural gas mixtures, respectively. Analysis of the top MOFs revealed that materials with narrow pores (<10 angstrom) and low porosities (<0.7), having aromatic ring linkers, alumina or zinc metal nodes, typically exhibit a superior C3H8 separation performance. The top MOFs were shown to outperform commercial zeolite, MFI for C3H8 capture from air, and several well-known MOFs for C3H8 capture from natural gas stream. These results will direct the experimental efforts to the most efficient C3H8 capture processes by providing key molecular insights into selecting the most useful adsorbents.Publication Metadata only Atomically dispersed zeolite-supported rhodium complex: selective and stable catalyst for acetylene semi-hydrogenation(Academic Press Inc., 2024) Su Yordanli, Melisa; Hoffman, Adam S.; Hong, Jiyun; Perez-Aguilar, Jorge E.; Saltuk, Aylin; Akgül, Deniz; Demircan, Oktay; Ateşin, Tülay A.; Aviyente, Viktorya; Gates, Bruce C.; Bare, Simon R.; Department of Chemical and Biological Engineering; Zhao, Yuxin; Bozkurt, Özge Deniz; 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 EngineeringSupported rhodium catalysts are known to be unselective for semi-hydrogenation reactions. Here, by tuning the electronic structure of supported mononuclear rhodium sites determined by the metal nuclearity and the electron-donor properties of the support, we report that atomically dispersed HY zeolite-supported rhodium with reactive acetylene ligands affords a stable ethylene selectivity > 90 % for acetylene semi-hydrogenation at 373 K and atmospheric pressure, even when ethylene is present in a large excess over acetylene. Infrared and X-ray absorption spectra and measurements of rates of the catalytic reaction complemented with calculations at the level of density functional theory show how the catalyst performance depends on the electronic structure of the rhodium, influenced by the support as a ligand that is a weak electron donor.Publication Metadata only Attenuation of Type IV pili activity by natural products(Taylor & Francis Inc, 2024) Yalkut, Kerem; Hassine, Soumaya Ben Ali; Kula, Ceyda; Ozcan, Aslihan; Avci, Fatma Gizem; Akbulut, Berna Sariyar; Ozbek, Pemra; Department of Chemical and Biological Engineering; Başaran, Esra; Keskin, Özlem; Department of Chemical and Biological Engineering; Graduate School of Sciences and Engineering; College of EngineeringThe virulence factor Type IV pili (T4P) are surface appendages used by the opportunistic pathogen Pseudomonas aeruginosa for twitching motility and adhesion in the environment and during infection. Additionally, the use of these appendages by P. aeruginosa for biofilm formation increases its virulence and drug resistance. Therefore, attenuation of the activity of T4P would be desirable to control P. aeruginosa infections. Here, a computational approach has been pursued to screen natural products that can be used for this purpose. PilB, the elongation ATPase of the T4P machinery in P. aeruginosa, has been selected as the target subunit and virtual screening of FDA-approved drugs has been conducted. Screening identified two natural compounds, ergoloid and irinotecan, as potential candidates for inhibiting this T4P-associated ATPase in P. aeruginosa. These candidate compounds underwent further rigorous evaluation through molecular dynamics (MD) simulations and then through in vitro twitching motility and biofilm inhibition assays. Notably, ergoloid emerged as a particularly promising candidate for weakening the T4P activity by inhibiting the elongation ATPases associated with T4P. This repurposing study paves the way for the timely discovery of antivirulence drugs as an alternative to classical antibiotic treatments to help combat infections caused by P. aeruginosa and related pathogens.