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Author

Marcin Miklitz

Other affiliations: University of Wrocław
Bio: Marcin Miklitz is an academic researcher from Imperial College London. The author has contributed to research in topics: Cryptophane & Density functional theory. The author has an hindex of 9, co-authored 12 publications receiving 438 citations. Previous affiliations of Marcin Miklitz include University of Wrocław.

Papers
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Journal ArticleDOI
TL;DR: A series of porous organic cages is examined for the selective adsorption of sulfur hexafluoride (SF6) over nitrogen and it is shown that cooperative diffusion and structural rearrangements in these molecular crystals can rationalize their superior SF6/N2 selectivity.
Abstract: A series of porous organic cages is examined for the selective adsorption of sulfur hexafluoride (SF6) over nitrogen. Despite lacking any metal sites, a porous cage, CC3, shows the highest SF6/N2 selectivity reported for any material at ambient temperature and pressure, which translates to real separations in a gas breakthrough column. The SF6 uptake of these materials is considerably higher than would be expected from the static pore structures. The location of SF6 within these materials is elucidated by X-ray crystallography, and it is shown that cooperative diffusion and structural rearrangements in these molecular crystals can rationalize their superior SF6/N2 selectivity.

171 citations

Journal ArticleDOI
TL;DR: Computational screening with high-throughput robotic synthesis is combined to create a hybrid discovery workflow for discovering new organic cage molecules, and by extension, other supramolecular systems that form cleanly in one-pot syntheses.
Abstract: Supramolecular synthesis is a powerful strategy for assembling complex molecules, but to do this by targeted design is challenging. This is because multicomponent assembly reactions have the potential to form a wide variety of products. High-throughput screening can explore a broad synthetic space, but this is inefficient and inelegant when applied blindly. Here we fuse computation with robotic synthesis to create a hybrid discovery workflow for discovering new organic cage molecules, and by extension, other supramolecular systems. A total of 78 precursor combinations were investigated by computation and experiment, leading to 33 cages that were formed cleanly in one-pot syntheses. Comparison of calculations with experimental outcomes across this broad library shows that computation has the power to focus experiments, for example by identifying linkers that are less likely to be reliable for cage formation. Screening also led to the unplanned discovery of a new cage topology-doubly bridged, triply interlocked cage catenanes.

134 citations

Journal ArticleDOI
TL;DR: A nomenclature for the classification of porous organic cage molecules is defined, enumerating the 20 most probable topologies and the computational challenges encountered when trying to predict the most likely topological outcomes from dynamic covalent chemistry reactions of organic building blocks.
Abstract: We define a nomenclature for the classification of porous organic cage molecules, enumerating the 20 most probable topologies, 12 of which have been synthetically realised to date. We then discuss the computational challenges encountered when trying to predict the most likely topological outcomes from dynamic covalent chemistry (DCC) reactions of organic building blocks. This allows us to explore the extent to which comparing the internal energies of possible reaction outcomes is successful in predicting the topology for a series of 10 different building block combinations.

80 citations

Journal ArticleDOI
TL;DR: The methodology, validation, and application of pywindow are presented, a python package that enables the automated analysis of structural features of porous molecular materials, such as molecular cages, and some instances of framework materials.
Abstract: Structural analysis of molecular pores can yield important information on their behavior in solution and in the solid state We developed pywindow, a python package that enables the automated analysis of structural features of porous molecular materials, such as molecular cages Our analysis includes the cavity diameter, number of windows, window diameters, and average molecular diameter Molecular dynamics trajectories of molecular pores can also be analyzed to explore the influence of flexibility We present the methodology, validation, and application of pywindow for the analysis of molecular pores, metal-organic polyhedra, and some instances of framework materials pywindow is freely available from githubcom/JelfsMaterialsGroup/pywindow

52 citations

Journal ArticleDOI
TL;DR: In this paper, the authors performed a computational screening of previously reported porous molecular materials, including porous organic cages, cucurbiturils, cyclodextrins, and cryptophanes, for Xe/Kr separation.
Abstract: We performed a computational screening of previously reported porous molecular materials, including porous organic cages, cucurbiturils, cyclodextrins, and cryptophanes, for Xe/Kr separation. Our approach for rapid screening through analysis of single host molecules, rather than the solid state structure of the materials, is evaluated. We use a set of tools including in-house software for structural evaluations, electronic structure calculations for guest binding energies, and molecular dynamics and metadynamics simulations to study the effect of the hosts’ flexibility upon guest diffusion. Our final results confirm that the CC3 cage molecule, previously reported as high performing for Xe/Kr separation, is the most promising of this class of materials reported to date. The Noria molecule was also found to be promising, and we therefore synthesized two related Noria molecules and tested their performance for Xe/Kr separation in the laboratory.

40 citations


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01 May 1993
TL;DR: Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems.
Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

29,323 citations

Journal ArticleDOI
TL;DR: This review encompasses the recent significant breakthroughs and the conventional functions and practices in the field of porous Organic materials to find useful applications and imparts a comprehensive understanding of the strategic evolution of the design and synthetic approaches of porous organic materials with tunable characteristics.
Abstract: Porous organic materials have garnered colossal interest with the scientific fraternity due to their excellent gas sorption performances, catalytic abilities, energy storage capacities, and other intriguing applications. This review encompasses the recent significant breakthroughs and the conventional functions and practices in the field of porous organic materials to find useful applications and imparts a comprehensive understanding of the strategic evolution of the design and synthetic approaches of porous organic materials with tunable characteristics. We present an exhaustive analysis of the design strategies with special emphasis on the topologies of crystalline and amorphous porous organic materials. In addition to elucidating the structure–function correlation and state-of-the-art applications of porous organic materials, we address the challenges and restrictions that prevent us from realizing porous organic materials with tailored structures and properties for useful applications.

838 citations

Journal ArticleDOI
TL;DR: Porosity is a rare property for molecular materials but, surprisingly, porous solids built from discrete organic cage molecules have emerged as a versatile functional-materials platform as mentioned in this paper, and the surface areas of molecular organic cage solids now rival those of metal-organic frameworks.
Abstract: Porosity is a rare property for molecular materials but, surprisingly, porous solids built from discrete organic cage molecules have emerged as a versatile functional-materials platform. From modest beginnings less than a decade ago, there are now organic cage solids with surface areas that can rival extended metal–organic frameworks. In contrast to network polymers and frameworks, these organic cages are synthesized first and then assembled in the solid state in a separate step. This offers solution-processing options that are not available for insoluble organic and inorganic frameworks. In this Review, we highlight examples of porous organic cages and focus on the unique features that set them apart, such as their molecular solubility, their increased tendency to exhibit polymorphism and the scope for modular co-crystallization. The surface areas of molecular organic cage solids now rival those of metal–organic frameworks. In this Review, the synthesis and structures of various porous organic cages are outlined together with a discussion of the characteristics — such as solubility, polymorphism and modular co-crystallization — that distinguish these cages from their inorganic or hybrid counterparts.

498 citations

Journal ArticleDOI
TL;DR: This Review discusses structure prediction methods, examining their potential for the study of different materials systems, and presents examples of computationally driven discoveries of new materials — including superhard materials, superconductors and organic materials — that will enable new technologies.
Abstract: Progress in the discovery of new materials has been accelerated by the development of reliable quantum-mechanical approaches to crystal structure prediction. The properties of a material depend very sensitively on its structure; therefore, structure prediction is the key to computational materials discovery. Structure prediction was considered to be a formidable problem, but the development of new computational tools has allowed the structures of many new and increasingly complex materials to be anticipated. These widely applicable methods, based on global optimization and relying on little or no empirical knowledge, have been used to study crystalline structures, point defects, surfaces and interfaces. In this Review, we discuss structure prediction methods, examining their potential for the study of different materials systems, and present examples of computationally driven discoveries of new materials — including superhard materials, superconductors and organic materials — that will enable new technologies. Advances in first-principle structure predictions also lead to a better understanding of physical and chemical phenomena in materials. Recent breakthroughs in crystal structure prediction have enabled the discovery of new materials and of new physical and chemical phenomena. This Review surveys structure prediction methods and presents examples of results in different classes of materials.

415 citations

Journal ArticleDOI
TL;DR: Porous organic materials are an emerging class of functional nanostructures with unprecedented properties and the potential of these materials for applications ranging from gas storage to catalysis and organic electronics is highlighted.
Abstract: Porous organic materials are an emerging class of functional nanostructures with unprecedented properties. Dynamic covalent assembly of small organic building blocks under thermodynamic control is utilized for the intriguingly simple formation of complex molecular architectures in one-pot procedures. In this Review, we aim to analyze the basic design principles that govern the formation of either covalent organic frameworks as crystalline porous polymers or covalent organic cage compounds as shape-persistent molecular objects. Common synthetic procedures and characterization techniques will be discussed as well as more advanced strategies such as postsynthetic modification or self-sorting. When appropriate, comparisons are drawn between polymeric frameworks and discrete organic cages in terms of their underlying properties. Furthermore, we highlight the potential of these materials for applications ranging from gas storage to catalysis and organic electronics.

344 citations