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A method for sulfur determination in diesel fuel employing near infrared spectroscopy, variable selection and multivariate calibration is described. The performances of principal component regression (PCR) and partial least square (PLS) chemometric methods were compared with those shown by multiple linear regression (MLR), performed after variable selection based on the genetic algorithm (GA) or the successive projection algorithm (SPA). Ninety seven diesel samples were divided into three sets (41 for calibration, 30 for internal validation and 26 for external validation), each of them covering the full range of sulfur concentrations (from 0.07 to 0.33% w/w). Transflectance measurements were performed from 850 to 1800 nm. Although principal component analysis identified the presence of three groups, PLS, PCR and MLR provided models whose predicting capabilities were independent of the diesel type. Calibration with PLS and PCR employing all the 454 wavelengths provided root mean square errors of prediction (RMSEP) of 0.036% and 0.043% for the validation set, respectively. The use of GA and SPA for variable selection provided calibration models based on 19 and 9 wavelengths, with a RMSEP of 0.031% (PLS-GA), 0.022% (MLR-SPA) and 0.034% (MLR-GA). As the ASTM 4294 method allows a reproducibility of 0.05%, it can be concluded that a method based on NIR spectroscopy and multivariate calibration can be employed for the determination of sulfur in diesel fuels. Furthermore, the selection of variables can provide more robust calibration models and SPA provided more parsimonious models than GA.

The dehydration reaction of d-(−)-fructose into 5-(hydroxymethyl)­furfural (HMF) in both batch and continuous flow conditions was comprehensively studied using the statistical tool design of experiments (DoE), employing i-PrOH/DMSO as the solvent system in the presence of the solid acid catalyst Amberlyst-15. Initially, screening of different alcohols (MeOH, EtOH, i-PrOH, and t-BuOH) showed that i-PrOH provides better selectivity and yield compared to the other alcohols, along with minimum formation of byproducts when associated with small amounts of DMSO (15% v/v) as a cosolvent. To confirm the selectivity of the reaction, all of the possible byproducts (HMF-ethers and/or ketals) formed during the reaction between HMF and i-PrOH were synthesized. Factors like temperature, amount of DMSO, time (flow rate), and catalyst loading were evaluated by a full factorial design, and the results indicated that temperature presents the greatest influence in both batch (HMF in 71% yield) and continuous flow regime (HMF in 95% yield). In addition, a FTIR device was coupled to the continuous flow micro reactor, allowing for the first time constant in-line monitoring for this transformation, thereby showing the long-term stability of Amberlyst-15 and process robustness.