Rapid discrimination of porous bio-carbon derived from nitrogen rich biomass using Raman spectroscopy and artificial intelligence methods

Granular porous bio-carbons were prepared by pyrolysis of different biomass precursors such as mung bean, black urad bean, and black grape seed, using ZnCl2 as an activating agent at different activation temperatures of 450–750 °C. The derived bio-carbons samples were extensively characterized using...

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Veröffentlicht in:	Carbon (New York) 2021-06, Vol.178, p.792-802
Hauptverfasser:	Kumbhar, D., Palliyarayil, A., Reghu, D., Shrungar, D., Umapathy, S., Sil, S.
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial intelligence Biomass Carbon dioxide Classification CO2 capture Deep learning Discriminant analysis Machine learning Model accuracy Multivariate analysis Partial least square analysis Porous bio-carbon Porous materials Precursors Principal components analysis Pyrolysis Raman spectroscopy Spectrum analysis Studies Surface area Zinc chloride
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