Natural and Mathematical Sciences

Permanent URI for this collectionhttps://hdl.handle.net/10679/313

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Browsing by Author "Altıntaş, Ç."

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    Computational screening of MOFs for CO2 capture
    (Springer, 2021-03-30) Altıntaş, Ç.; Fındıkçı, İlknur Eruçar; Keskin, S.; Mechanical Engineering; FINDIKÇI, Ilknur Eruçar
    The capture of CO2 (carbon dioxide) is an urgent environmental issue due to global warming. Adsorption-based CO2 capture using a new family of porous materials, metal-organic frameworks (MOFs), has been considered as a promising alternative to conventional methods. The rapid increase in the number of synthesized MOFs offers various materials for efficient CO2 capture, but assessing the performance of each MOF material using purely experimental methods is challenging. Recent progress in computational tools, high-throughput molecular simulations, and machine learning algorithms provide great opportunities for effective computational screening of MOFs with the aim of identifying the most promising adsorbents for CO2 capture prior to experimental studies. In this chapter, we focused on the recent advances in high-throughput screening of MOFs for CO2 capture and separation. We first reviewed the details of molecular simulation methods to compute CO2 adsorption properties of MOFs and adsorbent performance evaluation metrics that have been used to assess the CO2 separation potential of MOFs. Large-scale computational screening studies and quantitative structure-performance relationships obtained from molecular simulations were then discussed. Finally, opportunities and challenges of using computational tools to reveal the potential of MOFs for CO2 capture and separation were addressed.
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    High-throughput computational screening of the metal organic framework database for CH4/H-2 separations
    (American Chemical Society, 2018-01) Fındıkçı, İlknur Eruçar; Altıntaş, Ç.; Keskin, S.; Mechanical Engineering; FINDIKÇI, Ilknur Eruçar
    Metal organic frameworks (MOFs) have been considered as one of the most exciting porous materials discovered in the last decade. Large surface areas, high pore volumes, and tailorable pore sizes make MOFs highly promising in a variety of applications, mainly in gas separations. The number of MOFs has been increasing very rapidly, and experimental identification of materials exhibiting high gas separation potential is simply impractical. High throughput computational screening studies in which thousands of MOFs are evaluated to identify the best candidates for target gas separation is crucial in directing experimental efforts to the most useful materials. In this work, we used molecular simulations to screen the most complete and recent collection of MOFs from the Cambridge Structural Database to unlock their CH4/H-2 separation performances. This is the first study in the literature, which examines the potential of all existing MOFs for adsorption-based CH4/H-2 separation. MOFs (4350) were ranked based on several adsorbent evaluation metrics including selectivity, working capacity, adsorbent performance score, sorbent selection parameter, and regenerability. A large number of MOFs were identified to have extraordinarily large CH4/H-2 selectivities compared to traditional adsorbents such as zeolites and activated carbons. We examined the relations between structural properties of MOFs such as pore sizes, porosities, and surface areas and their selectivities. Correlations between the heat of adsorption, adsorbility, metal type of MOFs, and selectivities were also studied. On the basis of these relations, a simple mathematical model that can predict the CH4/H-2 selectivity of MOFs was suggested, which will be very useful in guiding the design and development of new MOFs with extraordinarily high CH4/H-2 separation performances.
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    ReviewPublicationOpen Access
    MOF/COF hybrids as next generation materials for energy and biomedical applications
    (Royal Society of Chemistry, 2022-10-31) Altıntaş, Ç.; Fındıkçı, İlknur Eruçar; Keskin, S.; Mechanical Engineering; FINDIKÇI, Ilknur Eruçar
    The rapid increase in the number and variety of metal organic frameworks (MOFs) and covalent organic frameworks (COFs) has led to groundbreaking applications in the field of materials science and engineering. New MOF/COF hybrids combine the outstanding features of MOF and COF structures, such as high crystallinities, large surface areas, high porosities, the ability to decorate the structures with functional groups, and improved chemical and mechanical stabilities. These new hybrid materials offer promising performances for a wide range of applications including catalysis, energy storage, gas separation, and nanomedicine. In this highlight, we discuss the recent advancements of MOF/COF hybrids as next generation materials for energy and biomedical applications with a special focus on the use of computational tools to address the opportunities and challenges of using MOF/COF hybrids for various applications.