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Publication Metadata only 1.07 - Rubberlike elasticity(Elsevier, 2012) Mark, J.E.; Department of Chemical and Biological Engineering; Erman, Burak; Faculty Member; Department of Chemical and Biological Engineering; College of Engineering; 179997Molecular structure, molecular and phenomenological theories, and computer simulations of amorphous rubberlike polymeric networks of rubber elasticity are discussed. Behavior of responsive gels, multimodal, liquid-crystalline, and reinforced elastomers in the state of thermodynamic equilibrium are outlined. Characterization of structure and properties based on stress–strain experiments, optical and spectroscopic techniques, scanning tunneling microscopy, atomic force microscopy, nuclear magnetic resonance, small-angle and Brillouin scattering, and pulse wave propagation are outlined. © 2012 Elsevier B.V. All rights reserved.Publication Open Access A remarkable class of nanocomposites: aerogel supported bimetallic nanoparticles(Frontiers, 2020) Özbakır, Yaprak; Department of Chemical and Biological Engineering; Güneş, Hande; Barım, Şansım Bengisu; Yousefzadeh, Hamed; Bozbağ, Selmi Erim; Erkey, Can; Researcher; Faculty Member; Department of Chemical and Biological Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; N/A; N/A; 29633Aerogels are a unique class of materials due to their low density, high porosity, high surface area, and an open and interconnected pore structure. Aerogels can be organic, inorganic and hybrid with a plethora of surface chemistries. Aerogel-based products for thermal insulation are already in the market and many studies are being conducted in many laboratories around the world to develop aerogel-based products for other applications including catalysis, adsorption, separations, and drug delivery. On the other hand, bimetallic nanoparticles dispersed on high surface area carriers, which have superior properties compared to their monometallic counterparts, are used or are in development for a wide variety of applications in catalysis, optics, sensing, detection, and medicine. Investigations on using aerogels as high surface area carriers for dispersing bimetallic nanoparticles are leading to development of new composite materials with outstanding properties due to the remarkable properties of aerogels. The review focuses on the techniques to synthesize these materials, their properties, the techniques to tune their pore properties and surface chemistry and the applications of these materials.Publication Open Access A review on computational modeling tools for MOF-based mixed matrix membranes(Multidisciplinary Digital Publishing Institute (MDPI), 2019) Department of Chemical and Biological Engineering; Keskin, Seda; Faculty Member; Department of Chemical and Biological Engineering; College of Engineering; 40548Computational modeling of membrane materials is a rapidly growing field to investigate the properties of membrane materials beyond the limits of experimental techniques and to complement the experimental membrane studies by providing insights at the atomic-level. In this study, we first reviewed the fundamental approaches employed to describe the gas permeability/selectivity trade-off of polymer membranes and then addressed the great promise of mixed matrix membranes (MMMs) to overcome this trade-off. We then reviewed the current approaches for predicting the gas permeation through MMMs and specifically focused on MMMs composed of metal organic frameworks (MOFs). Computational tools such as atomically-detailed molecular simulations that can predict the gas separation performances of MOF-based MMMs prior to experimental investigation have been reviewed and the new computational methods that can provide information about the compatibility between the MOF and the polymer of the MMM have been discussed. We finally addressed the opportunities and challenges of using computational studies to analyze the barriers that must be overcome to advance the application of MOF-based membranes.Publication Open Access A systematic and efficient input selection method for artificial neural networks using mixed-integer nonlinear programming(Konya Teknik Üniversitesi, 2022) Şıldır, Hasan; Department of Chemical and Biological Engineering; Aydın, Erdal; Faculty Member; Department of Chemical and Biological Engineering; College of Engineering; 311745Selection of input variables of the empirical models has vital effect on the prediction performance, reduced overfitting and reduced computational load. Various trials and error and sequential methods in the literature to deal with input selection for artificial neural networks (ANNs). However, these methods are not considered as automatic and systematic. This study proposes a novel and efficient mixed integer nonlinear programming-based approach to handle optimal input selection and the ANN training simultaneously for classification problems. Such selection uses binary (0-1) variables to represent the presence of the input variables and trains traditional continuous network weights simultaneously. Two classification case studies are given to demonstrate the advantages by using widely used data sets and statistical measures. The first data set is related to the characterization of the type of a tumor related to breast cancer, the second data set is about predicting the type of a biotechnological product using different features, the last one is related to heart failure prediction. Results show that better test performance can be achieved with optimally selected inputs, resulting in reduced overfitting. The proposed approach delivers a significant advantage during the design and training of the ANNs and is also applicable to other empirical models. / Ampirik modellerin girdi değişkenlerinin seçimi, tahmin performansı, azaltılmış fazla uydurma ve hesaplama yükünün azaltılması üzerinde önemli etkiye sahiptir. Literatürde yapay sinir ağları (YSA) için girdi seçimi ile ilgili çeşitli deneme yanılma yöntemleri mevcuttur ancak bu metodlar sistematik ve otomatik olarak kabul edilmemektedir. Bu çalışma, sınıflandırma problemleri için optimal girdi seçimi ve YSA eğitimini aynı anda ele almak için yeni ve verimli bir karma tamsayılı doğrusal olmayan programlama tabanlı bir yaklaşım önermektedir. Bu seçim, girdi değişkenlerinin varlığını temsil etmek için ikili (0-1) değişkenleri kullanır ve geleneksel sürekli ağ ağırlıklarını veya parametrelerini aynı anda eğitir. Yaygın olarak kullanılan veri setleri ve istatistiksel ölçümler kullanarak avantajları göstermek amacıyla üç sınıflandırma vaka çalışması sunulmuştur. Birinci veri seti meme kanseri ile ilgili tümörün tipin-in karakterizasyonu ile ilgili olup, ikinci veri seti ise farklı özellikler kullanılarak bir biyoteknolojik ürünün tipinin tahmin edilmesi ile ilgilidir, son veri seti ise kalp sağlığı ile ilgilidir. Sonuçlar, optimal olarak seçilen girdiler ile düşük fazla uydurma sayesinde daha iyi test performansının elde edilebileceğini göstermektedir. Önerilen yaklaşım, YSA'ların tasarımı ve eğitimi sırasında önemli bir avantaj sağlar ve diğer ampirik modellere de uygulanabilir.Publication Open Access An integrated application of control performance assessment and root cause analysis in refinery control loops(Elsevier, 2020) Yağcı, Mehmet; Department of Chemical and Biological Engineering; Arkun, Yaman; Faculty Member; Department of Chemical and Biological Engineering; College of Engineering; 108526Assessing the performance of control loops is an important component of Control Performance Monitoring (CPM) systems. Most of the industrial chemical processes have a large number of control loops interacting with each other in a complex way due to material and energy integration in the plant. A problem occurring in a certain control loop can easily upset the performance of the other control loops. Therefore, identification of the ""bad"" control loops causing a plant-wide disturbances is a crucial task. In this work, an integrated approach covering performance assessment and interaction analysis is proposed to detect the ""bad"" loops based on their performances. First, Minimum Variance Control (MVC) benchmark is used to screen-out the poor performing loops. Then, the spectral envelope method utilizing frequency analysis is used to identify the common oscillation periods among the loops under study. Finally, Granger causality is used to plot the interaction map between the loops. Even though these methods are well developed and used for several purposes separately, we present an integrated approach which focuses and analyzes the ""bad loops"". The developed approach has been tested in a refinery plant having 18 control loops. The results show that the proposed method is clearly able to identify and isolate the root-cause control loops. The validation of results and further improvements in the control loops under study have been given.Publication Open Access Androgen receptor-mediated transcription in prostate cancer(Multidisciplinary Digital Publishing Institute (MDPI), 2022) Morova, Tunç; Department of Computer Engineering; Department of Chemical and Biological Engineering; Lack, Nathan Alan; Özturan, Doğancan; Faculty Member; PhD Student; Department of Computer Engineering; Department of Chemical and Biological Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); School of Medicine; 120842; N/AAndrogen receptor (AR)-mediated transcription is critical in almost all stages of prostate cancer (PCa) growth and differentiation. This process involves a complex interplay of coregulatory proteins, chromatin remodeling complexes, and other transcription factors that work with AR at cis-regulatory enhancer regions to induce the spatiotemporal transcription of target genes. This enhancer-driven mechanism is remarkably dynamic and undergoes significant alterations during PCa progression. In this review, we discuss the AR mechanism of action in PCa with a focus on how cis-regulatory elements modulate gene expression. We explore emerging evidence of genetic variants that can impact AR regulatory regions and alter gene transcription in PCa. Finally, we highlight several outstanding questions and discuss potential mechanisms of this critical transcription factor.Publication Open Access Application of MD simulations to predict membrane properties of MOFs(Hindawi, 2015) Department of Chemical and Biological Engineering; Adatoz, Elda Beruhil; Keskin, Seda; Faculty Member; Department of Chemical and Biological Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 40548Metal organic frameworks (MOFs) are a new group of nanomaterials that have been widely examined for various chemical applications. Gas separation using MOF membranes has become an increasingly important research field in the last years. Several experimental studies have shown that thin-film MOF membranes can outperform well known polymer and zeolite membranes due to their higher gas permeances and selectivities. Given the very large number of available MOF materials, it is impractical to fabricate and test the performance of every single MOF membrane using purely experimental techniques. In this study, we used molecular simulations, Monte Carlo and Molecular Dynamics, to estimate both single-gas and mixture permeances of MOF membranes. Predictions of molecular simulations were compared with the experimental gas permeance data of MOF membranes in order to validate the accuracy of our computational approach. Results show that computational methodology that we described in this work can be used to accurately estimate membrane properties of MOFs prior to extensive experimental efforts.Publication Open Access Band alignment engineers faradaic and capacitive photostimulation of neurons without surface modification(American Physical Society (APS), 2019) Department of Electrical and Electronics Engineering; N/A; Department of Chemical and Biological Engineering; Department of Molecular Biology and Genetics; Srivastava, Shashi Bhushan; Melikov, Rustamzhon; Aria, Mohammad Mohammadi; Dikbaş, Uğur Meriç; Kavaklı, İbrahim Halil; Nizamoğlu, Sedat; Researcher; PhD Student; Master Student; Faculty Member; Faculty Member; Department of Electrical and Electronics Engineering; Department of Chemical and Biological Engineering; Department of Molecular Biology and Genetics; College of Engineering; Graduate School of Sciences and Engineering; College of Sciences; N/A; N/A; N/A; N/A; 40319; 130295Photovoltaic substrates have attracted significant attention for neural photostimulation. The control of the Faradaic and capacitive (non-Faradaic) charge transfer mechanisms by these substrates are critical for safe and effective neural photostimulation. We demonstrate that the intermediate layer can directly control the strength of the capacitive and Faradaic processes under physiological conditions. To resolve the Faradaic and capacitive stimulations, we enhance photogenerated charge density levels by incorporating PbS quantum dots into a poly(3-hexylthiophene-2,5-diyl):([6,6]-Phenyl-C61-butyric acid methyl ester (P3HT:PCBM) blend. This enhancement stems from the simultaneous increase of absorption, well matched band alignment of PbS quantum dots with P3HT:PCBM, and smaller intermixed phase-separated domains with better homogeneity and roughness of the blend. These improvements lead to the photostimulation of neurons at a low light intensity level of 1 mW cm(-2), which is within the retinal irradiance level. These findings open up an alternative approach toward superior neural prosthesis.Publication Open Access Causality, transfer entropy, and allosteric communication landscapes in proteins with harmonic interactions(Wiley, 2017) Department of Chemical and Biological Engineering; Hacısüleyman, Aysima; Erman, Burak; Faculty Member; Department of Chemical and Biological Engineering; College of Engineering; N/A; 179997A fast and approximate method of generating allosteric communication landscapes in proteins is presented by using Schreiber's entropy transfer concept in combination with the Gaussian Network Model of proteins. Predictions of the model and the allosteric communication landscapes generated show that information transfer in proteins does not necessarily take place along a single path, but an ensemble of pathways is possible. The model emphasizes that knowledge of entropy only is not sufficient for determining allosteric communication and additional information based on time delayed correlations should be introduced, which leads to the presence of causality in proteins. The model provides a simple tool for mapping entropy sink-source relations into pairs of residues. By this approach, residues that should be manipulated to control protein activity may be determined. This should be of great importance for allosteric drug design and for understanding the effects of mutations on function. The model is applied to determine allosteric communication in three proteins, Ubiquitin, Pyruvate Kinase, and the PDZ domain. Predictions are in agreement with molecular dynamics simulations and experimental evidence.Publication Metadata only Challenges with atomically dispersed supported metal catalysts: controlling performance, improving stability, and enhancing metal loading(Elsevier, 2023) Kurtoğlu-Öztulum, Samira Fatma; Uzun, Alper; Department of Chemical and Biological Engineering; 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 EngineeringAtomically dispersed supported metal catalysts offer opportunities of maximum utilization of expensive noble metals and provide unprecedented catalytic properties. Thus, these novel materials have received tremendous attention, especially in the last decade. Notwithstanding their advantages and such rapidly growing interest, these novel materials face various challenges, which need to be overcome to make them industrially viable. One of these challenges is the limited ability to control their catalytic properties. Changing the ligand environment, which also includes the support, varying the metal nuclearity, and the use of promoters (also including ionic liquid sheets) have shown to offer broad opportunities for tuning the catalytic performance. The other challenges are mostly related with the limited stability of the active species under reaction conditions, which also limits the metal loadings on the support surfaces. Control of electronic structure on the metal sites and the use of functional groups on support surfaces have been shown to be effective in this direction. In this chapter, some of the recent approaches aiming at overcoming these challenges related with the atomically dispersed supported metal catalysts are presented.