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EFFICIENT LIGHT GAS SEPARATIONS WITH MOFS VIA PREDICTIVE MODELING AND TUNED SYNTHESIS

机译:高效通过预测建模和调整合成与MOF的高效气体分离

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The ability to design, tune and successfully test porous crystalline materials allows for the development and commercialization of materials for many different environmental and energy applications. Metal-organic frameworks (MOFs) have shown great potential in challenging separations of molecules with very similar kinetic diameters. One area of strong focus in our lab is toward a fundamental understanding of the structure-property relationship of selective O2 over N2 adsorption in MOFs. Emphasis is placed on identifying key structural features for highly selective oxygen adsorption, leading to efficiency improvements through oxy-fuel combustion.
机译:设计,调谐和成功测试多孔晶体材料的能力允许对许多不同环境和能源应用的材料进行开发和商业化。金属 - 有机框架(MOF)在具有非常相似的动力学直径的分子分离方面表现出很大的潜力。我们实验室中强烈关注的一个领域是对MOF中N2吸附的选择性O2结构性质关系的基本理解。重点是识别用于高选择性氧气吸附的关键结构特征,导致通过氧燃料燃烧提高效率。

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