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This paper applies a symmetry-adapted method to examine the influence of deformation and defects on the electronic structure and band structure in carbon nanotubes. First, the symmetry-adapted approach is used to develop the analog of Bloch waves. Building on this, the technique of perfectly-matched layers is applied to develop a method to truncate the computational domain of electronic structure calculations without spurious size effects. This provides an efficient and accurate numerical approach to compute the electronic structure and electromechanics of defects in nanotubes. The computational method is applied to study the effect of twist, stretch, and bending, with and without various types of defects, on the band structure of nanotubes. Specifically, the effect of stretch and twist on band structure in defect-free conducting and semiconducting nanotubes is examined, and the interaction with vacancy defects is elucidated. Next, the effect of localized bending or kinking on the electronic structure is studied. Finally, the paper examines the effect of 5-8-5 Stone-Wales defects. In all of these settings, the perfectly-matched layer method enables the calculation of localized non-propagating defect modes with energies in the bandgap of the defect-free nanotube. 

Pyrazine‐linked hybrid ultramicroporous (pore size <7 Å) materials (HUMs) offer benchmark performance for trace carbon capture thanks to strong selectivity for CO₂over small gas molecules, including light hydrocarbons. That the prototypal pyrazine‐linked HUMs are amenable to crystal engineering has enabled second generation HUMs to supersede the performance of the parent HUM,SIFSIX‐3‐Zn, mainly through substitution of the metal and/or the inorganic pillar. Herein, we report that two isostructural aminopyrazine‐linked HUMs,MFSIX‐17‐Ni(17=aminopyrazine; M=Si, Ti), which we had anticipated would offer even stronger affinity for CO₂than their pyrazine analogs, unexpectedly exhibit reduced CO₂affinity but enhanced C₂H₂affinity.MFSIX‐17‐Niare consequently the first physisorbents that enable single‐step production of polymer‐grade ethylene (>99.95 % forSIFSIX‐17‐Ni) from a ternary equimolar mixture of ethylene, acetylene and CO₂thanks to coadsorption of the latter two gases. We attribute this performance to the very different binding sites inMFSIX‐17‐NiversusSIFSIX‐3‐Zn.

 

Pyrazine‐linked hybrid ultramicroporous (pore size <7 Å) materials (HUMs) offer benchmark performance for trace carbon capture thanks to strong selectivity for CO₂over small gas molecules, including light hydrocarbons. That the prototypal pyrazine‐linked HUMs are amenable to crystal engineering has enabled second generation HUMs to supersede the performance of the parent HUM,SIFSIX‐3‐Zn, mainly through substitution of the metal and/or the inorganic pillar. Herein, we report that two isostructural aminopyrazine‐linked HUMs,MFSIX‐17‐Ni(17=aminopyrazine; M=Si, Ti), which we had anticipated would offer even stronger affinity for CO₂than their pyrazine analogs, unexpectedly exhibit reduced CO₂affinity but enhanced C₂H₂affinity.MFSIX‐17‐Niare consequently the first physisorbents that enable single‐step production of polymer‐grade ethylene (>99.95 % forSIFSIX‐17‐Ni) from a ternary equimolar mixture of ethylene, acetylene and CO₂thanks to coadsorption of the latter two gases. We attribute this performance to the very different binding sites inMFSIX‐17‐NiversusSIFSIX‐3‐Zn.

 

The high energy footprint of commodity gas purification and increasing demand for gases require new approaches to gas separation. Kinetic separation of gas mixtures through molecular sieving can enable separation by molecular size or shape exclusion. Physisorbents must exhibit the right pore diameter to enable separation, but the 0.3–0.4 nm range relevant to small gas molecules is hard to control. Herein, dehydration of the ultramicroporous metal–organic framework Ca‐trimesate, Ca(HBTC)⋅H₂O (H₃BTC=trimesic acid), bnn‐1‐Ca‐H₂O, affords a narrow pore variant, Ca(HBTC), bnn‐1‐Ca. Whereas bnn‐1‐Ca‐H₂O (pore diameter 0.34 nm) exhibits ultra‐high CO₂/N₂, CO₂/CH₄, and C₂H₂/C₂H₄binary selectivity, bnn‐1‐Ca (pore diameter 0.31 nm) offers ideal selectivity for H₂/CO₂and H₂/N₂under cryogenic conditions. Ca‐trimesate, the first physisorbent to exhibit H₂sieving under cryogenic conditions, could be a prototype for a general approach to exert precise control over pore diameter in physisorbents.

 

The high energy footprint of commodity gas purification and increasing demand for gases require new approaches to gas separation. Kinetic separation of gas mixtures through molecular sieving can enable separation by molecular size or shape exclusion. Physisorbents must exhibit the right pore diameter to enable separation, but the 0.3–0.4 nm range relevant to small gas molecules is hard to control. Herein, dehydration of the ultramicroporous metal–organic framework Ca‐trimesate, Ca(HBTC)⋅H₂O (H₃BTC=trimesic acid), bnn‐1‐Ca‐H₂O, affords a narrow pore variant, Ca(HBTC), bnn‐1‐Ca. Whereas bnn‐1‐Ca‐H₂O (pore diameter 0.34 nm) exhibits ultra‐high CO₂/N₂, CO₂/CH₄, and C₂H₂/C₂H₄binary selectivity, bnn‐1‐Ca (pore diameter 0.31 nm) offers ideal selectivity for H₂/CO₂and H₂/N₂under cryogenic conditions. Ca‐trimesate, the first physisorbent to exhibit H₂sieving under cryogenic conditions, could be a prototype for a general approach to exert precise control over pore diameter in physisorbents.

 

Abstract Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb -1 at  √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.