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Screening catalysts for the synthesis of cyclic carbonates from CO 2 and epoxides presents a challenge for the research community. Thus, we propose the application of quantitative structure-property relationships (QSPR) modeling and exploratory analysis to assist in the selection of catalysts to produce oleochemical carbonates. QSPR modeling was developed by applying 2D-descriptors to evaluate the relationship between the molecular structure of organocatalysts and their activity in the production of biobased organic carbonates. From the virtual screening, 122 potential catalysts were selected, their catalytic activities were estimated, and the best molecular targets highlighted. Already from the data mining and exploratory analysis, the catalysts' key structural features (e.g. organic structure, molecular arrangement, carbon chain size, and substituent type) were identified. Thus, it was possible to evaluate the similarity between the catalysts and to relate the 2D-descriptors to their activity. Then, based on QSPR modeling results, cetyltrimethylammonium bromide (CTAB) was proposed as a new catalyst to produce oleochemical carbonates. From the CTAB application, conversions greater than 98% of epoxide were observed in the cycloaddition of CO 2 to epoxidized vegetable oil (rice bran, canola, and soybean). Thus, it was concluded that QSPR modeling and exploratory analysis show potential for screening catalysts for oleochemical carbonate synthesis.

The present work proposed the application of a multivariate regression model based on image data to monitor the decolorization process. Thus, a PLS regression based on the color histogram was applied to monitor the methylene blue degradation by the Fenton reaction. The results obtained by the digital imaging and UV-Vis methods were compared and the initial (C o) and final (C) methylene blue concentrations, as well as the kinetic parameters, coefficients of determination (R 2), half time degradation (t ½), intercept (ρ), and slope (σ), were evaluated. From our results, the digital imaging and UV-Vis methods have equivalent potential to monitor the color removal profile, similar kinetic term, and low measurement errors. While the coefficient of determination (R 2) of all PLS models and kinetics curves are close to 1.00, the half time degradation (t ½) parameter ranged between 0.29 to 1.39 min for the UV-Vis model, and 0.80 min to 2.17 min for the digital imaging model. Furthermore, the efficiency of methylene blue removal ranged between 92.04% and 97.78% for the UV-Vis model and 91.30% to 93.72% for the digital imaging model. Then, based on statistical comparison tests, it was concluded that the digital imaging method is an alternative to monitor dye degradation processes.