Because of their high surface areas, crystallinity, and tunable properties, metal–organic frameworks (MOFs) have attracted intense interest as next-generation materials for gas capture and storage. While much effort has been devoted to the discovery of new MOFs, a vast catalog of existing MOFs resides within the Cambridge Structural Database (CSD), many of whose gas uptake properties have not been assessed. Here we employ data mining and automated structure analysis to identify, “cleanup,” and rapidly predict the hydrogen storage properties of these compounds. Approximately 20 000 candidate compounds were generated from the CSD using an algorithm that removes solvent/guest molecules. These compounds were then characterized with respect to their surface area and porosity. Employing the empirical relationship between excess H2 uptake and surface area, we predict the theoretical total hydrogen storage capacity for the subset of ∼4000 compounds exhibiting nontrivial internal porosity. Our screening identifies several overlooked compounds having high theoretical capacities; these compounds are suggested as targets of opportunity for additional experimental characterization. More importantly, screening reveals that the relationship between gravimetric and volumetric H2 density is concave downward, with maximal volumetric performance occurring for surface areas of 3100–4800 m2/g. We conclude that H2 storage in MOFs will not benefit from further improvements in surface area alone. Rather, discovery efforts should aim to achieve moderate mass densities and surface areas simultaneously, while ensuring framework stability upon solvent removal.

Zourdos, MC, Goldsmith, JA, Helms, ER, Trepeck, C, Halle, JL, Mendez, KM, Cooke, DM, Haischer, MH, Sousa, CA, Klemp, A, and Byrnes, RK. Proximity to failure and total repetitions performed in a set influences accuracy of intraset repetitions in reserve-based rating of perceived exertion. J Strength Cond Res 35(2S): S158–S165, 2021—The aim of this study was to assess the accuracy of predicting repetitions in reserve (RIR) intraset using the RIR-based rating of perceived exertion (RPE) scale. Twenty-five men (age: 25.3 ± 3.3 years, body mass: 89.0 ± 14.7 kg, height: 174.69 ± 6.7 cm, and training age: 4.7 ± 3.2 years) reported to the laboratory. Subjects performed a 1 repetition maximum (1RM) squat followed by one set to failure at 70% of 1RM. During the 70% set, subjects verbally indicated when they believed they were at a 5RPE (5RIR), 7RPE (3RIR), or 9RPE (1RIR), and then continued to failure. The difference between actual repetitions performed and participant-predicted repetitions was calculated as the RIR difference (RIRDIFF). The average load used for the 70% set was 123.10 ± 24.25 kg and the average repetitions performed were 16 ± 4. The RIRDIFF was lower (RPEs were more accurate) closer to failure (RIRDIFF at 9RPE = 2.05 ± 1.73; RIRDIFF at 7RPE = 3.65 ± 2.46; and RIRDIFF at 5RPE = 5.15 ± 2.92 repetitions). There were significant relationships between total repetitions performed and RIRDIFF at 5RPE (r = 0.65, p = 0.001) and 7RPE (r = 0.56, p = 0.004), but not at 9RPE (r = 0.01, p = 0.97). Thus, being farther from failure and performing more repetitions in a set were associated with more inaccurate predictions. Furthermore, a multiple linear regression revealed that more repetitions performed per set was a significant predictor of RIR prediction inaccuracy at the called 5 (p = 0.003) and 7 (p = 0.011) RPEs, while training age (p > 0.05) was not predictive of rating accuracy. These data indicate RIR predictions are improved during low to moderate repetition sets and when there is close proximity to failure.

This Letter describes molecular dynamics simulations of pressureinduced flow of water and aqueous salt solutions through model nanopores. The systems studied are comprised of (n,n) carbon nanotubes (CNT) that span a membrane constructed of parallel graphene walls separating two solution reservoirs. We employ this system as an idealized model of surface-modified nanoporous membranes, and thus, both native hydrophobic CNT and nanotubes with artificial surface partial charge patterns are considered. The dependence of the fluxes of water and ions on the nanopore size, nanopore charge patterns, and pressure difference are explored using nonequilibrium molecular dynamics simulation. We demonstrate size-and structure-dependent salt rejection and show evidence of salt flux rectification for our asymmetric nanopore model.

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The close association between f b and RPE throughout the run at CHR - 5 and during the last 50 % of the run at CHR + 5 indicated that muscle afferents may have provided feedback from metabolic and mechanical stimuli that contributed to the perceptual responses. In addition, only RPE consistently indicated exhaustion and the current findings supported its use to monitor exercise performed at a constant HR.