In this study, cellulose nanocrystals with cellulose crystal structure I (CNCs I) and with coexisting cellulose crystalline structures I and II (CNCs I-II) were isolated from pine cellulose using acid hydrolysis with H 2 SO 4 . It was possible to obtain CNCs with different morphologies, crystallinities and crystalline structures adjusting only the reaction conditions. The thermal stability is directly related to the crystalline structure and the crystallinity. It was observed that CNCs composed mainly of CNC II have an initial degradation temperature higher than the CNCs I when comparing samples with similar crystallinity. The kinetic results allow us to conclude that activation energy (E a ) not only depends on the crystalline structure and crystallinity of the CNCs but may also be related to the presence of sulfate groups. Understanding the influence of crystallinity and crystalline structure on the thermal stability of CNCs can direct the studies of future applications for these materials.

This study provides a novel value‐added utilization of the agroindustrial waste of royal palm tree leaf sheath to produce cellulose acetate. One of the motivations of this work was the fact that Brazil is one of the largest heart of palm producers in the world. However, as a result of extraction and processing, tons of waste are generated and discharged to the environment. Such waste is rich in lignocellulosic material, which could be reused to obtain derivatives of interest and commercial value. The synthesis of cellulose acetate was performed through a homogeneous acetylation reaction. Three different conditions were tested for delignification of the raw material, which resulted in a reduction in lignin content from 17.75 to 7.72%. The highest yield of cellulose acetate reached 99.5%, with degree of substitutions ranging between 2.08 and 2.82, which indicates satisfactory conversion. The Fourier transform infrared spectrum showed that practically all hydroxyl groups were replaced by acetate groups; this was also confirmed by nuclear magnetic resonance analysis. X‐ray diffraction analysis showed that the cellulose acetate crystallinity index was 8.9%. This demonstrates the viable potential of cellulose acetate production with low cost and use of highly available agroindustrial waste. POLYM. ENG. SCI., 59:891–898, 2019. © 2018 Society of Plastics Engineers

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The present study addresses the novel application of the simulated annealing algorithm (SAA) to optimize the pressure-swing distillation (PSD) process for anhydrous ethanol purification. Three different softwares (Aspen Plus ® , Excel ® and Matlab ®) were integrated to simultaneously optimize seven design and operational variables. The configuration with the best TAC represented a 40.2% saving per year in comparison to the non-optimized PSD. Such reduction was achieved by using the higher acceptance probability and the slower temperature decrement. This saving is mainly related to operational cost reductions, a fact that evidences the viability of using the herein described optimization methodology to improve the PSD design.

Chammem (2019) Essential oil components of Citrus cultivar'MALTAISE DEMISANGUINE' (Citrussinensis) as affected by the effects of rootstocks and viroid infection,

Maize drying is an important process, especially for storage and conservation. For this study, the experimental stage was carried out using a forced convection dryer with air heated at different temperature conditions (306.05–441.85 K) and flow (0.13–0.256 m3/hr), totalizing 15 drying curves. Then the performances of the classic drying kinetics methodology and the approach proposed in this paper, in which the increase in moisture content of the product with time was represented combining exponential models and neural networks based on wavelets, were compared. Good performance was obtained in predictions using the proposed approach. One of the main differentials of the methodology adopted was the obtainment of a model that has a global predictive capacity, within the range of tested operating conditions, which can be used in predicting drying curves for different operating conditions. Practical applications The drying process is also one of the most widely used methods for preserving food, and has the advantage of reducing the costs of storage and transport because of the low volume and weight of the end product. During the last years, this topic has attracted a broad industrial interest, resulting in many research studies investigating the drying process. Usually, with regard to the classic approach for modeling of the drying process, the kinetics of drying curves obtained in different operating conditions is affected separately, that is, the parameters are estimated independently, resulting in different regression problems. With the classical approach, in general, it is not possible to obtain a comprehensive prediction model with regards to operating conditions. We have proposed an alternative modeling method. Aiming to obtain a modeling tool with an overall predictive ability, an approach for drying kinetics prediction that combines exponential models and neural networks was proposed. The proposed modeling method was able to predict drying curves for different operating conditions.

The thermodynamic melting properties (temperature, enthalpy, and entropy) of rosmarinic acid were experimentally determined via differential scanning calorimetry. The solubility of rosmarinic acid in three solvents (water, methyl acetate, and ethyl acetate), and in their binary mixtures, were determined. The data obtained experimentally were correlated by way of a modified Apelblat model. Through solubility measurements, the activity coefficient was calculated for the process of dissolving the rosmarinic acid in pure solvents and in their mixtures.