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Among the methods for point source carbon capture, the absorption of CO2 using aqueous amines (namely MEA) from the post-combustion gas stream is currently considered the most promising.
A novel approach is presented herein to improve time to onset of natural convection stemming from fuel element porosity during a failure mode of a nuclear reactor.
We have developed an aerosol sampling technique to enable collection of trace materials such as actinides in the atmosphere.
This innovative approach combines optical and spectral imaging data via machine learning to accurately predict cancer labels directly from tissue images.