The fractionation of crude-oil mixtures through distillation is a large-scale, energy-intensive process. Membrane materials can avoid phase changes in such mixtures and thereby reduce the energy intensity of these thermal separations. With this application in mind, we created spirocyclic polymers with N-aryl bonds that demonstrated noninterconnected microporosity in the absence of ladder linkages. The resulting glassy polymer membranes demonstrated nonthermal membrane fractionation of light crude oil through a combination of class- and size-based “sorting” of molecules. We observed an enrichment of molecules lighter than 170 daltons corresponding to a carbon number of 12 or a boiling point less than 200°C in the permeate. Such scalable, selective membranes offer potential for the hybridization of energy-efficient technology with conventional processes such as distillation.

Amorphous metal–organic frameworks (MOFs) are an emerging class of materials. However, their structural characterisation represents a significant challenge. Fe-BTC, and the commercial equivalent Basolite® F300, are MOFs with incredibly diverse catalytic ability, yet their disordered structures remain poorly understood. Here, we use advanced electron microscopy to identify a nanocomposite structure of Fe-BTC where nanocrystalline domains are embedded within an amorphous matrix, whilst synchrotron total scattering measurements reveal the extent of local atomic order within Fe-BTC. We use a polymerisation-based algorithm to generate an atomistic structure for Fe-BTC, the first example of this methodology applied to the amorphous MOF field outside the well-studied zeolitic imidazolate framework family. This demonstrates the applicability of this computational approach towards the modelling of other amorphous MOF systems with potential generality towards all MOF chemistries and connectivities. We find that the structures of Fe-BTC and Basolite® F300 can be represented by models containing a mixture of short- and medium-range order with a greater proportion of medium-range order in Basolite® F300 than in Fe-BTC. We conclude by discussing how our approach may allow for high-throughput computational discovery of functional, amorphous MOFs.

Amorphous metal–organic frameworks (MOFs) are an emerging class of materials. However, their structural characterisation represents a significant challenge. Fe‑BTC, and the commercial equivalent Basolite® F300, are MOFs with incredibly diverse catalytic ability, yet their disordered structures remain poorly understood. Here, we use advanced electron microscopy to identify a nanocomposite structure of Fe‑BTC where nanocrystalline domains are embedded within an amorphous matrix, whilst synchrotron total scattering measurements reveal the extent of local atomic order within Fe‑BTC. We use a polymerisation-based algorithm to generate an atomistic structure for Fe-BTC, the first example of this methodology applied to the amorphous MOF field outside the well-studied zeolitic imidazolate framework family. This demonstrates the applicability of this computational approach towards the modelling of other amorphous MOF systems with potential generality towards all MOF chemistries and connectivities. We find that the structures of Fe-BTC and Basolite® F300 can be represented by models containing a mixture of short- and medium-range order with a greater proportion of medium-range order in Basolite® F300 than in Fe-BTC. We conclude by discussing how our approach may allow for high-throughput computational discovery of functional, amorphous MOFs.

The rational design of disordered frameworks is an appealing route to target functional materials. However, intentional realisation of such materials relies on our ability to readily characterise and quantify structural disorder. Here, we use multivariate analysis of pair distribution functions to fingerprint and quantify the disorder within a series of compositionally identical metal–organic frameworks, possessing different crystalline, disordered, and amorphous structures. We find this approach can provide powerful insight into the kinetics and mechanism of structural collapse that links these materials. Our methodology is also extended to a very different system, namely the melting of a zeolitic imidazolate framework, to demonstrate the potential generality of this approach across many areas of disordered structural chemistry.

Amorphous metal–organic frameworks (aMOFs) are a class of disordered framework materials with a defined local order given by the connectivity between inorganic nodes and organic linkers, but absent long-range order. The rational development of function for aMOFs is hindered by our limited understanding of the underlying structure–property relationships in these systems, a consequence of the absence of long-range order, which makes experimental characterization particularly challenging. Here, we use a versatile modeling approach to generate in silico structural models for an aMOF based on Fe trimers and 1,3,5-benzenetricarboxylate (BTC) linkers, Fe-BTC. We build a phase space for this material that includes nine amorphous phases with different degrees of defects and local order. These models are analyzed through a combination of structural analysis, pore analysis, and pair distribution functions. Therefore, we are able to systematically explore the effects of the variation of each of these features, both in isolation and combined, for a disordered MOF system, something that would not be possible through experiment alone. We find that the degree of local order has a greater impact on structure and properties than the degree of defects. The approach presented here is versatile and allows for the study of different structural features and MOF chemistries, enabling the derivation of design rules for the rational development of aMOFs.

Collagen proteins are spread in almost every vertebrate's tissue with mechanical function. The defining feature of this fundamental family of proteins is its well-known collagen triple-helical domain. This helical domain can have different geometries, varying in helical elongation and interstrands contact, as a function of the amino acidic composition. The helical geometrical features play an important role in the interaction of the collagen protein with cell receptors, but for the vast majority of collagen compositions, these geometrical features are unknown. Quantum mechanical (QM) simulations based on the density functional theory (DFT) provide a robust approach to characterize the scenario on the collagen composition−structure relationships. In this work, we analyze the role of the adopted computational method in predicting the collagen structure for two purposes. First, we look for a cost-effective computational approach to apply to a large-scale composition− structure analysis. Second, we attempt to assess the robustness of the predictions by varying the QM methods. Therefore, we have run geometry optimization on periodic models of the collagen protein using a variety of approaches based on the most commonly used DFT functionals (PBE, HSE06, and B3LYP) with and without dispersion correction (D3 ABC ). We have coupled these methods with several different basis sets, looking for the highest accuracy/cost ratio. Furthermore, we have studied the performance of the composite HF-3c method and the semiempirical GFN1-xTB method. Our results identify a computational recipe that is potentially capable of predicting collagen structural features in line with DFT simulations, with orders of magnitude reduced computational cost, encouraging further investigations on the topic.

Amorphous metal−organic frameworks (aMOFs) are a class of disordered framework materials with a defined local order given by the connectivity between inorganic nodes and organic linkers, but absent longer-range order. The rational development of function for aMOFs is hindered by our limited understanding of the underlying structure-property relationships in these systems, a consequence of the absence of long-range order, which makes experimental characterization particularly challenging. Here, we use a versatile modelling approach to generate in-silico structural models for an aMOF based on Fe trimers and 1,3,5-benzenetricarboxylate (BTC) linkers, Fe-BTC. We build a phase space for this material that includes nine amorphous phases with different degrees of defects and local order. These models are analyzed through a combination of structural analysis, pore analysis and pair distribution functions. Therefore, we are able to systematically explore the effects of the variation of each of these features, both in isolation and combined, for a disordered MOF system, something that would not be possible through experiment alone. We find that the degree of local order has a greater impact on structure and properties than the degree of defects. The approach presented here is versatile and allows for the study of different structural features and MOF chemistries, enabling the development of design rules for the rational design of aMOFs.

Crystallization of archetypical porphyrins cause sizeable band gap renormalization and redshifts the optical transition except for the visible Q band.