To assess the techno-economic screening of HTL oil for various
feedstock, it is crucial to have information on molecular composition of
the feed and products. There are limitations of existing analytical
methods to identify and quantify all the molecules present in the
bio-fuel. Therefore, there is a need to find alternate ways to quantify
the molecular composition of feed and expected products. The modelling
work on bio-oil is developed based on a mathematical approach using
simple analytical results like CHNO along with structural analysis of
oil like FTIR, NMR analysis for HTL derived oil from microalgae. This
mathematical framework is further extended to predict the molecular
composition of HTL-oil obtained from feedstocks like mixed plastic
waste, sludge etc. A multi-dimensional molecular matrix is developed
based on the distributions of side chains, aromatic rings, and olefinic
carbon on top of core molecules. Optimum parameters are found using
appropriate optimization algorithms.