Porous carbons are of interest for a wide range of advanced‐technology ‘green’ energy applications including fuel cells, hydrogen storage, supercapacitors and batteries. Functional groups, heteroatoms and a more accessible hierarchical porous structure would be advantageous for many of these applications. This paper describes the generation of carbonaceous monoliths with hierarchically porous structures and nitrogen functionalities by using a one‐pot, simultaneous combination of hydrogel synthesis and hydrothermal carbonization (HTC) that involves templating within high internal phase emulsions (HIPEs). A carbon monolith with a density of 0.058 g cm−3, a highly interconnected, bimodal porous structure and an apparent specific surface area (SBET) of 101 m2 g−1 was produced by carbonizing a HTC monolith based on 2‐hydroxyethyl methacrylate (HEMA) at 450 °C. SBET of 1540 m2 g−1 was produced through subsequent chemical activation with ZnCl2 at 700 °C, but the overall residual mass (Rm) was only 9 wt%. Direct chemical activation of the HTC monolith, on the other hand, generated SBET of 1250 m2 g−1 and an overall Rm of 28 wt%, corresponding to a higher apparent surface area per mass of HTC monolith. Carbon monoliths with N/C ratios of 0.09 and 0.07 were achieved using nitrogen‐rich monomers (acrylamide and vinylimidazole, respectively) as compared to the HEMA‐based carbon monolith with an N/C ratio of 0.03. This work demonstrates that the hierarchically porous structures and the chemical structures of these highly porous monoliths can be fine‐tuned by modifying the HIPE composition and/or the processing conditions. © 2021 Society of Industrial Chemistry.
Massively-parallel graph algorithms have received extensive attention over the past decade, with research focusing on three memory regimes: the superlinear regime, the near-linear regime, and the sublinear regime. The sublinear regime is the most desirable in practice, but conditional hardness results point towards its limitations.In this work we study a heterogeneous model, where the memory of the machines varies in size. We focus mostly on the heterogeneous setting created by adding a single near-linear machine to the sublinear MPC regime, and show that even a single large machine suffices to circumvent most of the conditional hardness results for the sublinear regime: for graphs with n vertices and m edges, we give (a) an MST algorithm that runs in O(log log(m/n)) rounds; (b) an algorithm that constructs an O(k)-spanner of size O(n 1+1/k ) in O(1) rounds; and (c) a maximal-matching algorithm that runs in O( log(m/n) log log(m/n)) rounds. We also observe that the best known near-linear MPC algorithms for several other graph problems which are conjectured to be hard in the sublinear regime (minimum cut, maximal independent set, and vertex coloring) can easily be transformed to work in the heterogeneous MPC model with a single near-linear machine, while retaining their original round complexity in the near-linear regime. If the large machine is allowed to have superlinear memory, all of the problems above can be solved in O(1) rounds.
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