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Higher manganese silicides (HMSs) have emerged as promising candidates for environmentally friendly thermoelectric (TE) materials due to their earth-abundant and non-toxic composition. We report grain boundary engineering in ruthenium-doped HMSs via a melt-quenching followed by annealing method. This approach promotes the formation of MnSi nanoprecipitates and nanopores, preferentially near grain boundaries. The presence of these nanostructures results in a weak temperature-dependent thermal conductivity, resembling glass-like thermal transport behavior. A two-channel model incorporating propagons and diffusons describes this glass-like thermal conductivity, with diffusons contributing about 60 % of the lattice thermal conductivity at 300 K. Furthermore, the quench-annealing process enhances electrical conductivity while preserving a large Seebeck coefficient, which is attributed to a high density-of-states effective mass. As a result of improved power factor and reduced thermal conductivity, the figure of merit zT value increases by 33 % at 300 K compared to undoped HMS synthesized via solid-state reaction. These findings present a promising strategy for manipulating phonon dynamics in functional materials and designing efficient TE systems. 

Abstract As wildfires increase in frequency and intensity, accurately representing the vertical distribution of smoke in numerical models is critical for assessing impacts to air quality, but remains highly uncertain. In this study, we leverage satellite retrievals of total column carbon monoxide (CO) and aerosol layer height (ALH) to evaluate two state-of-the-art regionals and global models, one using a plume rise parameterization to estimate smoke injection height (RAP-Chem) and another placing smoke at the surface (MOMO-Chem). We introduce a novel metric that utilizes the differing vertical sensitivities of two satellite sensors observing CO (TROPOMI and CrIS) to infer the vertical distribution of wildfire smoke using a joint CO column ratio. We find that RAP-Chem better captures the distribution of CO and ALH related to the 2020 western US megafire event than MOMO-Chem. However, RAP-Chem underestimates surface CO concentrations, revealing that current plume rise parameterizations are limited in their ability to partition smoke correctly in the vertical column. These results show that synergistic use of satellite data can provide additional constraints on the vertical distribution of smoke, thus providing insights into the strengths and limitations of current plume rise parameterizations and a pathway to improvement. 

We give an algorithm for finding an ε-fixed point of a contraction mapf: [0, 1]^k\(\mapsto\)[0, 1]^kunder the\(\ell _\infty\)-norm with query complexityO(klog (1/ε).