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.

Fast parallel algorithms for short-range molecular dynamics

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.

Porous Organic Materials: Strategic Design and Structure–Function Correlation

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.

Porous organic cages: soluble, modular and molecular pores

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.

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Structure prediction drives materials discovery

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.

Covalent Organic Frameworks and Cage Compounds: Design and Applications of Polymeric and Discrete Organic Scaffolds

The development of adsorption and membrane-based separation technologies toward more energy and cost-efficient processes is a significant engineering problem facing the world today. An example of a process in need of improvement is the separation of C8 aromatics to recover para-xylene, which is the precursor to the widely used monomer terephthalic acid. Molecular simulations were used to investigate whether the separation of C8 aromatics can be carried out by the porous organic cages CC3 and CC13, both of which have been previously used in the fabrication of amorphous thin-film membranes. Metadynamics simulations showed significant differences in the energetic barriers to the diffusion of different C8 aromatics through the porous cages, especially for CC3. These differences imply that meta-xylene and ortho-xylene will take significantly longer to enter or leave the cages. Therefore, it may be possible to use membranes composed of these materials to separate ortho- and meta-xylene from para-xylene by size ...

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Computational Evaluation of the Diffusion Mechanisms for C8 Aromatics in Porous Organic Cages

Computation is playing an increasing role in the discovery of materials, including supramolecular materials such as encapsulants. In this work, a function-led computational discovery using an evolutionary algorithm is used to find potential fullerene (C60) encapsulants within the chemical space of porous organic cages. We find that the promising host cages for C60 evolve over the simulations towards systems that share features such as the correct cavity size to host C60, planar tri-topic aldehyde building blocks with a small number of rotational bonds, di-topic amine linkers with functionality on adjacent carbon atoms, high structural symmetry, and strong complex binding affinity towards C60. The proposed cages are chemically feasible and similar to cages already present in the literature, helping to increase the likelihood of the future synthetic realisation of these predictions. The presented approach is generalisable and can be tailored to target a wide range of properties in molecular material systems. Computation is proving to be a powerful tool to guide the design of supramolecular cages. Here the authors use an evolutionary algorithm to find potential fullerene encapsulants within the chemical space of porous organic cages.

Marcin Miklitz

Papers

Computational Evaluation of the Diffusion Mechanisms for C8 Aromatics in Porous Organic Cages

Computational Discovery of Molecular C60 Encapsulants with an Evolutionary Algorithm