Enhancement of biofuels production by means of co-pyrolysis of Posidonia oceanica (L.) and frying oil wastes: Experimental study and process modeling.

Energy recovery from lignocellulosic solid marine wastes, Posidonia oceanica wastes (POW) with slow pyrolysis responds to the growing trend of alternative energies as well as waste management. Physicochemical, thermogravimetric (TG/DTG) and spectroscopic (FTIR) characterizations of POW were performed. POW were first converted by pyrolysis at different temperatures (450°C, 500°C, 550°C and 600°C) using a fixed-bed reactor.

Robust estimation of thermodynamic parameters (ΔH, ΔS and ΔCp) for prediction of retention time in gas chromatography - Part I (Theoretical).

An approach that is commonly used for calculating the retention time of a compound in GC departs from the thermodynamic properties ΔH, ΔS and ΔCp of phase change (from mobile to stationary). Such properties can be estimated by using experimental retention time data, which results in a non-linear regression problem for non-isothermal temperature programs. As shown in this work, the surface of the objective function (approximation error criterion) on the basis of thermodynamic parameters can be divided into three clearly defined regions, and solely in one of them there is a possibility for the global optimum to be found.

Robust estimation of thermodynamic parameters (ΔH, ΔS and ΔCp) for prediction of retention time in gas chromatography - Part II (Application).

For this work, an analysis of parameter estimation for the retention factor in GC model was performed, considering two different criteria: sum of square error, and maximum error in absolute value; relevant statistics are described for each case. The main contribution of this work is the implementation of an initialization scheme (specialized) for the estimated parameters, which features fast convergence (low computational time) and is based on knowledge of the surface of the error criterion. In an application to a series of alkanes, specialized initialization resulted in significant reduction to the number of evaluations of the objective function (reducing computational time) in the parameter estimation.

Fast and accurate numerical method for predicting gas chromatography retention time.

Predictive modeling for gas chromatography compound retention depends on the retention factor (ki) and on the flow of the mobile phase. Thus, different approaches for determining an analyte ki in column chromatography have been developed. The main one is based on the thermodynamic properties of the component and on the characteristics of the stationary phase.