Thermoelectric Heat Exchangers for Nuclear Reactors - Phase I Final Report
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Engineering topics
Publications and source records attributed to Merrill, Matthew.
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In one embodiment, a method for separating acidic gases from a gas mixture includes exposing the gas mixture to a separation membrane at an elevated temperature, where the separation membrane includes a porous support and at least one molten alkali metal hydroxide disposed within pores of the porous support.
In one embodiment, a separation membrane includes: a porous support structure, wherein the porous support structure comprises a system of continuous pores connecting an inlet of the separation membrane to an outlet of the separation membrane; and at least one alkali metal hydroxide disposed within pores of the porous support structure. Other aspects and embodiments of the disclosed inventive concepts will become apparent from the detailed description, which, when taken in conjunction with the drawings, illustrate by way of example the principles of the invention.
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Disclosed here is a method for producing a graphene macro-assembly (GMA)-fullerene composite, comprising providing a GMA comprising a three-dimensional network of graphene sheets crosslinked by covalent carbon bonds, and incorporating at least 20 wt. % of at least one fullerene compound into the GMA based on the initial weight of the GMA to obtain a GMA-fullerene composite. Also described are a GMA-fullerene composite produced, an electrode comprising the GMA-fullerene composite, and a supercapacitor comprising the electrode and optionally an organic or ionic liquid electrolyte in contact with the electrode.
A separator made of ion conductive ink is produced by additive manufacturing. A micro-battery is produced with the separator made of ion conductive ink located between the battery's anode and cathode. The separator functions to keep the anode and cathode apart and to facilitate the transport of ions to produce an operative micro-battery.
We have developed an artificial neural network (ANN) based carbonate detector capable of running on current and future rover hardware. The detector can identify calcite in visible/NIR (350-2500 nm) spectra of both laboratory specimens covered by ferric dust and rocks in Mars analogue field environments. The ANN was trained using the Backpropagation algorithm with sigmoid activation neurons. For the training dataset, we chose nine carbonate and eight non-carbonate representative mineral spectra from the USGS spectral library. Using these spectra as seeds, we generated 10,000 variants with up to 2% Gaussian noise in each reflectance measurement. We cross-validated several ANN architectures, training on 9,900 spectra and testing on the remaining 100. The best performing ANN correctly detected, with perfect accuracy, the presence (or absence) of carbonate in spectral data taken on field samples from the Mojave desert and clean, pure marbles from CT. Sensitivity experiments with JSC Mars-1 simulant dust suggest the carbonate detector would perform well in aeolian Martian environments.