Pore topology analysis in porous molecular systems

Abstract

Porous molecular materials are constructed from molecules that assemble in the solid-state such that there are cavities or an interconnected pore network. It is challenging to control the assembly of these systems, as the interactions between the molecules are generally weak, and subtle changes in the molecular structure can lead to vastly different intermolecular interactions and subsequently different crystal packing arrangements. Similarly, the use of different solvents for crystallization, or the introduction of solvent vapour, can result in different polymorphs and pore networks being formed. It is difficult to uniquely describe the pore networks formed, and thus we analyse 1033 crystal structures of porous molecular systems to determine the underlying topology of their void spaces and potential guest diffusion networks. Material-agnostic topology definitions are applied. We use the underlying topological nets to examine whether it is possible to apply isoreticular design principles to porous molecular materials. Overall, our automatic analysis of a large dataset gives a general insight into the relationships between molecular topologies and the topological nets of their pore network. We show that while porous molecular systems tend to pack similarly to non-porous molecules, the topologies of their pore distributions resemble those of more prominent porous materials, such as metal–organic frameworks and covalent organic frameworks.

Characteristics of planar and planar layer-stacked CHON-containing molecules

“…This criterion is referenced to that of TATNBZ, 0.058 Å. TATNBZ is a crystal code of 1,3,5-triamino-2,4,6-trinitrobenzene (TATB), 28 which is generally regarded as representative of planar layer-stacked energetic compounds. [15][16][17][18][19][20][21][22][23] Next, planar layer-stacked molecules were defined further by carrying out the following steps: (1) expanding a unit cell to a supercell with a certain quantity of molecules, for example, n molecules; (2) fitting the molecular plane equations of these n molecules; (3) calculating the angles between any two planes and identifying the maximum (α), and primarily ascertaining the planar layer-stacking or ladder-like stacking at an angle of α ≤ 5°; (4) defining the layer thickness as the sum of the complete values of the maximal positive and negative derivations of atoms from the molecule, and refining the planar layer-stacking by a layer thickness no larger than 0.40 Å, corresponding to that of TATB; and (5) removing ladderlike stacking by defining the interlayer distance to be no less than 2.4 Å, which is double the van der Waals radius of the H atom and can be regarded as the minimal interlayer distance for stacking of CHNO-containing molecules.…”

“…), and serves as the basis for studying crystalline materials. [2][3][4] For example, regarding energetics, we can in principle deduce or predict macroscopic properties and performance, such as energy, stability, safety, mechanical properties, and so forth, from a known crystal packing structure. Furthermore, insights into the origins of these properties and performance generally stem from crystal packing, too.…”

The Impact of Digitalized Data Management on Materials Systems Workflows

“…As a result, scientists make more informed decisions, and develop new materials faster and sometimes more economically. [ 2 ] These examples hint at the potential of a fully digitalized materials science, which has not yet come close to being achieved. Previous examples each refer to a subarea of scientific work that is supported by digital processes, or they show work with a selection of digitalized data.…”