BioSTEAM: A Fast and Flexible Platform for the Design, Simulation, and Techno-Economic Analysis of Biorefineries under Uncertainty
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Efficient excited-state electron transfer between an iron(III) photosensitizer and organic electron donors was realized with green light irradiation. This advance was enabled by the use of the previously reported iron photosensitizer, [Fe(phtmeimb) 2 ]+ (phtmeimb = {phenyl[tris(3-methyl-imidazolin-2-ylidene)]borate}, that exhibited long-lived and luminescent ligand-to-metal charge transfer (LMCT) excited states. A benchmark dehalogenation reaction was investigated with catalytic yieldsthat exceed 90% and an enhanced stability relative to the prototypical photosensitizer [Ru(bpy) 3 ] 2+ . The initial catalytic step is electron transfer from an amine to the photoexcited iron sensitizer that is shown to occur with a large cage-escape yield. For LMCT excited states, this reductive electron transfer is vectoral and may be a general advantage of Fe(III) photosensitizers. In-depth time-resolved spectroscopic methods, that include transient absorption characterization from the ultraviolet to the infrared regions, provided a quantitative description of the catalytic mechanism with associated rate constants and yields.
In this study, we present PyKrev, a Python library for the analysis of complex mixture Fourier transform mass spectrometry (FT-MS) data. PyKrev is a comprehensive suite of tools for analysis and visualization of FT-MS data after formula assignment has been performed. These comprise formula manipulation and calculation of chemical properties, intersection analysis between multiple lists of formulas, calculation of chemical diversity, assignment of compound classes to formulas, multivariate analysis, and a variety of visualization tools producing van Krevelen diagrams, class histograms, PCA score, and loading plots, biplots, scree plots, and UpSet plots. The library is showcased through analysis of hot water green tea extracts and Scotch whisky FT-ion cyclotron resonance-MS data sets. PyKrev addresses the lack of a single, cohesive toolset for researchers to perform FT-MS analysis in the Python programming environment encompassing the most recent data analysis techniques used in the field.
Industrial Decarbonization is the phasing out of atmospheric greenhouse gas (GHG) emissions from all aspects of the industrial sector. There are a number of industrial decarbonization strategies, including energy efficiency, electrification, the use of low carbon fuels, and carbon capture.