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Register a new userGraph similarity drives zeolite diffusionless transformations and intergrowth
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Added by
Daniel Schwalbe-Koda
Publication date
2018
fields
Physics
and research's language is
English
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Predicting and directing polymorphic transformations is a critical challenge in zeolite synthesis. Although interzeolite transformations enable selective crystallization, their design lacks predictions to connect framework similarity and experimental observations. Here, computational and theoretical tools are combined to data-mine, analyze and explain interzeolite relations. It is observed that building units are weak predictors of topology interconversion and insufficient to explain intergrowth. By introducing a supercell-invariant metric that compares crystal structures using graph theory, we show that topotactic and reconstructive (diffusionless) transformations occur only between graph-similar pairs. Furthermore, all known instances of intergrowth occur between either structurally-similar or graph-similar frameworks. Backed with exhaustive literature results, we identify promising pairs for realizing novel diffusionless transformations and intergrowth. Hundreds of low-distance pairs are identified among known zeolites, and thousands of hypothetical frameworks are connected to known zeolites counterparts. The theory opens a venue to understand and control zeolite polymorphism.
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Single crystals of the Bi-Ca-Co-O system have been grown using the flux method with cooling from 900$celsius$ and 950$celsius$, respectively. The single crystals are characterized by transmission electron microscopy and X-ray diffraction. The misfit cobaltite [Ca$_2$Bi$_{1.4}$Co$_{0.6}$O$_4$]$^{RS}$[CoO$_2$]$_{1.69}$ single crystals with quadruple ($n$=4) rocksalt (RS) layer are achieved with cooling from 900$celsius$. Such crystal exhibits room-temperature thermoelectric power (TEP) of 180$mu$V/K, much larger than that in Sr-based misfit cobaltites with quadruple RS layer. However, intergrowth of single crystals of quadruple ($n$=4) and triple ($n$=3) RS-type layer-based misfit cobaltites is observed with cooling from 950$celsius$. Both of TEP and resistivity were obviously enhanced by the intergrowth compared to [Ca$_2$Bi$_{1.4}$Co$_{0.6}$O$_4$]$^{RS}$[CoO$_2$]$_{1.69}$ single crystal, while the power factor at room temperature remains unchanged.
The process of rapid solidification of a binary mixture is considered in the framework of local nonequilibrium model (LNM) based on the assumption that there is no local equilibrium in solute diffusion in the bulk liquid and at the solid-liquid interface. According to LNM the transition to complete solute trapping and diffusionless solidification occurs at a finite interface velocity $V=V_D$, where $V_D$ is the diffusion speed in bulk liquid. In the present work, the boundary conditions at the phase interface moving with the velocity $V$ close to $V_D$ ($V lesssim V_D$) have been derived to find the non-equilibrium solute partition coefficient. In the high-speed region, its comparison with the partition coefficient from the work [Phys. Rev. E 76 (2007) 031606] is given.
We demonstrate that the layered room temperature ferromagnet Fe7Se8 and the topological insulator Bi2Se3 form crystallographically oriented bulk composite intergrowth crystals. The morphology of the intergrowth in real space and reciprocal space is described. Critically, the basal planes of Bi2Se3 and Fe7Se8 are parallel and hence the good cleavage inherent in the bulk phases is retained. The intergrowth is on the micron scale. Both phases in the intergrowth crystals display their intrinsic bulk properties: the ferromagnetism of the Fe7Se8 is anisotropic, with magnetization easy axis in the plane of the crystals, and ARPES characterization shows that the topological surface states remain present on the Bi2Se3. Analogous behavior is found for what has been called Fe-doped Bi2Se3.
We have analysed structural motifs in the Deem database of hypothetical zeolites, to investigate whether the structural diversity found in this database can be well-represented by classical descriptors such as distances, angles, and ring sizes, or whether a more general representation of atomic structure, furnished by the smooth overlap of atomic positions (SOAP) method, is required to capture accurately structure-property relations. We assessed the quality of each descriptor by machine-learning the molar energy and volume for each hypothetical framework in the dataset. We have found that SOAP with a cutoff-length of 6 AA, which goes beyond near-neighbor tetrahedra, best describes the structural diversity in the Deem database by capturing relevant inter-atomic correlations. Kernel principal component analysis shows that SOAP maintains its superior performance even when reducing its dimensionality to those of the classical descriptors, and that the first three kernel principal components capture the main variability in the data set, allowing a 3D point cloud visualization of local environments in the Deem database. This ``cloud atlas of local environments was found to show good correlations with the contribution of a given motif to the density and stability of its parent framework. Local volume and energy maps constructed from the SOAP/machine-learning analyses provide new images of zeolites that reveal smooth variations of local volumes and energies across a given framework, and correlations between local volume and energy in a given framework.
The rapid solidification of a binary mixture in the region of the interface velocities $V$ close to the diffusion speed in the bulk of the liquid phase $V_D$ is considered within the framework of the local nonequilibrium approach. In this high-speed region the derivation of the analytical expression for the response function temperature-velocity representing kinetic phase diagram is given without using the concept of the equilibrium phase diagram. The modes of movement of the interface both without and with the drag effect are analyzed. It is shown that the drag effect can be accompanied by a local interface temperature maximum at $V = V_D$.
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