Resolving the Structure of Ti3C2Tx MXenes through Multilevel Structural Modeling of the Atomic Pair Distribution Function

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• 作者：Hsiu-Wen Wang ; Michael Naguib ; Katharine Page ; David J. Wesolowski ; Yury Gogotsi
• 刊名：Chemistry of Materials
• 出版年：2016
• 出版时间：January 12, 2016
• 年：2016
• 卷：28
• 期：1
• 页码：349-359
• 全文大小：925K
• ISSN：1520-5002

文摘

MXenes are a recently discovered family of two-dimensional (2D) early transition metal carbides and carbonitrides, which have already shown many attractive properties and great promise in energy storage and many other applications. However, a complex surface chemistry and small coherence length have been obstacles in some applications of MXenes, also limiting the accuracy of predictions of their properties. In this study, we describe and benchmark a novel way of modeling layered materials with real interfaces (diverse surface functional groups and stacking order between the adjacent monolayers) against experimental data. The structures of three kinds of Ti₃C₂T_x MXenes (T stands for surface terminating species, including O, OH, and F) produced under different synthesis conditions were resolved for the first time using atomic pair distribution function obtained by high-quality neutron total scattering. The true nature of the material can be easily captured with the sensitivity of neutron scattering to the surface species of interest and the detailed “third-generation” structure model we present. The modeling approach leads to new understanding of MXene structural properties and can replace the currently used idealized models in predictions of a variety of physical, chemical, and functional properties of Ti₃C₂-based MXenes. The developed models can be employed to guide the design of new MXene materials with selected surface termination and controlled contact angle, catalytic, optical, electrochemical, and other properties. We suggest that the multilevel structural modeling should form the basis for a generalized methodology on modeling diffraction and pair distribution function data for 2D and layered materials.