Highly porous ZIF-67 (Zeolitic imidazole framework) has a conductive crystalline metal organic framework (MOF) structure which was served as a precursor and template for the preparation of nitrogen-doped carbon nanotubes (NCNTs) electrocatalysts. As a first step, the chloroplatinic acid, a platinum (Pt) precursor was infiltrated in ZIF-67 with a precise amount to obtain 0.12 mg.cm-2 Pt loading. Later, the infiltrated structure was calcined at 700°C in Ar:H2 (90:10 vol%) gas mixture. Multi-walled nitrogen-doped carbon nanotubes were grown on the surface of ZIF-67 crystals following thermal activation at 700°C. The resulting PtCo-NCNTs electrocatalysts were deposited on Nafion-212 solid electrolyte membrane by spray technique to study the oxygen reduction reaction (ORR) in the presence of H2/O2 gases in a temperature range of 50-70°C. The present study elucidates the performance of nitrogen-doped carbon nanotubes ORR electrocatalysts derived from ZIF-67 and the effects of membrane electrode assembly (MEA) steaming on the performance of proton exchange membrane fuel cell (PEMFC) employing PtCo-NCNTs as ORR electrocatalysts. We observed that the peak power density at 70°C was 450 mW/cm2 for steamed membrane electrode assembly (MEA) compared to 392 mW/cm2 for an identical MEA without steaming.

Tandem Solar Cells with Silicon as one of its constituents have flat surfaces (surfaces without texturing). That is why flat surfaces Solar cells have got quite importance. But the issue with the flat surfaces is the high reflection loss (flat) and poor light trapping (no-texturing) in the cells. So, some scattering film, other than direct texturing, that is polydimethylsiloxane (PDMS) polymer with the texture is used. The optimized PDMS film here is the random pyramidal film because random pyramidal PDMS films have a drop of 56.6% in reflectance used on polished Silicon while iso-textured and inverted pyramids have 51.55% and 48.47% respectively. This PDMS film with random textures when applied to 2-terminal monolithic perovskite/Silicon tandem, its external quantum efficiency shows an increase of 1.12mA/cm2in the short-circuit current and reflection loss reduces by 4.1 mA/cm2.

With the commercial availability of mixed precision hardware, mixed precision GMRES-based iterative refinement schemes have emerged as popular approaches for solving sparse linear systems. Existing analyses of these approaches, however, are all based on using a full LU factorization to construct preconditioners for use within GMRES in each refinement step. In practical applications, inexact preconditioning techniques, such as incomplete LU or sparse approximate inverses, are often used for performance reasons.In this work, we investigate the use of sparse approximate inverse preconditioners within GMRESbased iterative refinement. We analyze the computation of sparse approximate inverses in finite precision and derive constraints under which the user-specified stopping criteria will be satisfied. We then analyze the behavior of and convergence constraints for a GMRES-based iterative refinement scheme that uses sparse approximate inverse preconditioning, which we call SPAI-GMRES-IR. Our numerical experiments confirm that in some cases, sparse approximate inverse preconditioning can have an advantage over using a full LU factorization.

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