Cite we must, cite we do. We cite because we are links in a chain, using properties and methods validated by others. We also cite to negotiate the anxiety of influence. And to be fair. After ...outlining the reasons for citation, we use two case studies of citation amnesia in the field of hypothetical carbon allotropes to present a computer‐age search tool (SACADA) in that subsubfield. Finally, we advise on good search practice, including what to do if you miss a citation.
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Basic concepts of computer topological analysis of crystal structures realized in the current version of the program package ToposPro are considered. Applications of the ToposPro methods to various ...classes of chemical compoundscoordination polymers, molecular crystals, supramolecular ensembles, inorganic ionic compounds, intermetallics, fast-ion conductors, microporous materialsare illustrated by many examples. It is shown that chemically and crystallographically different structures can be automatically treated in a similar way with the ToposPro approaches.
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Adsorptive separation of olefin/paraffin mixtures by porous solids can greatly reduce the energy consumption associated with the currently employed cryogenic distillation technique. Here, the ...complete separation of propane and propylene by a designer microporous metal–organic framework material is reported. The compound, Y6(OH)8(abtc)3(H2O)6(DMA)2 (Y‐abtc, abtc = 3,3′,5,5′‐azobenzene‐tetracarboxylates; DMA = dimethylammonium), is rationally designed through topology‐guided replacement of inorganic building units. Y‐abtc is both thermally and hydrothermally robust, and possesses optimal pore window size for propane/propylene separation. It adsorbs propylene with fast kinetics under ambient temperature and pressure, but fully excludes propane, as a result of selective size exclusion. Multicomponent column breakthrough experiments confirm that polymer‐grade propylene (99.5%) can be obtained by this process, demonstrating its true potential as an alternative sorbent for efficient separation of propane/propylene mixtures.
A tailor‐made microporous metal–organic framework designed through a topologically guided secondary building unit (SBU) replacement strategy exhibits the highest selectivity for fast and efficient separation of propane and propylene via a size‐exclusion adsorption mechanism. This material, with excellent thermal and hydrothermal stability, and facile and scalable synthesis, is capable of producing polymer‐grade propylene (99.5%) from a typical propane/propylene mixture of cracking products.
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Atmospheric moisture is a ubiquitous water resource available at any time and any place, making it attractive to develop materials for harvesting water from air to address the imminent water shortage ...crisis. In this context, we have been exploring the applicability of covalent organic frameworks (COFs) for water harvesting and report here a new porous, two-dimensional imine-linked COF with a voided square grid topology, termed COF-432. Unlike other reported COFs, COF-432 meets the requirements desired for water harvesting from air in that it exhibits an S-shaped water sorption isotherm with a steep pore-filling step at low relative humidity and without hysteretic behaviorproperties essential for energy-efficient uptake and release of water. Further, it can be regenerated at ultra-low temperatures and displays exceptional hydrolytic stability, as demonstrated by the retention of its working capacity after 300 water adsorption–desorption cycles.
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As an alternative technology to energy intensive distillations, adsorptive separation by porous solids offers lower energy cost and higher efficiency. Herein we report a topology-directed design and ...synthesis of a series of Zr-based metal-organic frameworks with optimized pore structure for efficient separation of C6 alkane isomers, a critical step in the petroleum refining process to produce gasoline with high octane rating. Zr
O
(OH)
(bptc)
adsorbs a large amount of n-hexane but excluding branched isomers. The n-hexane uptake is ~70% higher than that of a benchmark adsorbent, zeolite-5A. A derivative structure, Zr
O
(OH)
(H
O)
(abtc)
, is capable of discriminating all three C6 isomers and yielding a high separation factor for 3-methylpentane over 2,3-dimethylbutane. This property is critical for producing gasoline with further improved quality. Multicomponent breakthrough experiments provide a quantitative measure of the capability of these materials for separation of C6 alkane isomers. A detailed structural analysis reveals the unique topology, connectivity and relationship of these compounds.
Generating carbon schwarzites via zeolite-templating Braun, Efrem; Lee, Yongjin; Moosavi, Seyed Mohamad ...
Proceedings of the National Academy of Sciences - PNAS,
08/2018, Volume:
115, Issue:
35
Journal Article
Peer reviewed
Open access
Zeolite-templated carbons (ZTCs) comprise a relatively recent material class synthesized via the chemical vapor deposition of a carbon-containing precursor on a zeolite template, followed by the ...removal of the template. We have developed a theoretical framework to generate a ZTC model from any given zeolite structure, which we show can successfully predict the structure of known ZTCs. We use our method to generate a library of ZTCs from all known zeolites, to establish criteria for which zeolites can produce experimentally accessible ZTCs, and to identify over 10 ZTCs that have never before been synthesized. We show that ZTCs partition space into two disjoint labyrinths that can be described by a pair of interpenetrating nets. Since such a pair of nets also describes a triply periodic minimal surface (TPMS), our results establish the relationship between ZTCs and schwarzites—carbon materials with negative Gaussian curvature that resemble TPMSs—linking the research topics and demonstrating that schwarzites should no longer be thought of as purely hypothetical materials.
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Carbon allotropes have been explored intensively by ab initio crystal structure prediction, but such methods are limited by the large computational cost of the underlying density functional theory ...(DFT). Here we show that a novel class of machine‐learning‐based interatomic potentials can be used for random structure searching and readily predicts several hitherto unknown carbon allotropes. Remarkably, our model draws structural information from liquid and amorphous carbon exclusively, and so does not have any prior knowledge of crystalline phases: it therefore demonstrates true transferability, which is a crucial prerequisite for applications in chemistry. The method is orders of magnitude faster than DFT and can, in principle, be coupled with any algorithm for structure prediction. Machine‐learning models therefore seem promising to enable large‐scale structure searches in the future.
Chemistry ex machina: A Gaussian approximation potential model is used to explore the potential energy surface of elemental carbon, which leads to the prediction of several hitherto unknown allotropes. This proof‐of‐concept shows the benefits of coupling transferable machine‐learning algorithms with automated structure searches, and the results are then discussed in the language of topology and crystal chemistry.
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Crystal structure prediction algorithms, including
ab initio
random structure searching (AIRSS), are intrinsically limited by the huge computational cost of the underlying quantum-mechanical methods. ...We have recently shown that a novel class of machine learning (ML) based interatomic potentials can provide a way out: by performing a high-dimensional fit to the
ab initio
energy landscape, these potentials reach comparable accuracy but are orders of magnitude faster. In this paper, we develop our approach, dubbed Gaussian approximation potential-based random structure searching (GAP-RSS), towards a more general tool for exploring configuration spaces and predicting structures. We present a GAP-RSS interatomic potential model for elemental phosphorus, which identifies and correctly "learns" the orthorhombic black phosphorus (A17) structure without prior knowledge of any crystalline allotropes. Using the tubular structure of fibrous phosphorus as an example, we then discuss the limits of free searching, and discuss a possible way forward that combines a recently proposed fragment analysis with GAP-RSS. Examples of possible tubular (1D) and extended (3D) hypothetical allotropes of phosphorus as found by GAP-RSS are discussed. We believe that in the future, ML potentials could become versatile and routine computational tools for materials discovery and design.
Machine learning-based interatomic potentials, fitting energy landscapes "on the fly", are emerging and promising tools for crystal structure prediction.
We consider two metal–organic frameworks as identical if they share the same bond network respecting the atom types. An algorithm is presented that decides whether two metal–organic frameworks are ...the same. It is based on distinguishing structures by comparing a set of descriptors that is obtained from the bond network. We demonstrate our algorithm by analyzing the CoRe MOF database of DFT optimized structures with DDEC partial atomic charges using the program package ToposPro.
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Designing new 2D
systems with tunable properties is an important
subject for science and technology. Starting from graphene, we developed
an algorithm to systematically generate 2D carbon crystals ...belonging
to the family of graphdiynes (GDYs) and having different structures
and sp/sp
2
carbon ratios. We analyze how structural and
topological effects can tune the relative stability and the electronic
behavior, to propose a rationale for the development of new systems
with tailored properties. A total of 26 structures have been generated,
including the already known polymorphs such as α-, β-,
and γ-GDY. Periodic density functional theory calculations have
been employed to optimize the 2D crystal structures and to compute
the total energy, the band structure, and the density of states. Relative
energies with respect to graphene have been found to increase when
the values of the carbon sp/sp
2
ratio increase, following
however different trends based on the peculiar topologies present
in the crystals. These topologies also influence the band structure,
giving rise to semiconductors with a finite band gap, zero-gap semiconductors
displaying Dirac cones, or metallic systems. The different trends
allow identifying some topological effects as possible guidelines
in the design of new 2D carbon materials beyond graphene.
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