Organosolv pretreatment for biorefineries: Current status, perspectives, and challenges.

Biorefineries integrate processes for the sustainable conversion of biomass into chemicals, materials, and bioenergy so that resources are optimized and effluents are minimized. Despite the vast potential of lignocellulosic biorefineries, their success depends heavily on effective, economically viable, and sustainable biomass fractionation. Although efficient, organosolv pretreatment still faces challenges that must be overcome for its widespread utilization, mainly related to solvent type and recycling, robustness regarding biomass type and integration of hemicellulose recovery and use. This review shows the recent advances and state-of-the-art of organosolv pretreatment, discussing the advances, such as the use of biobased solvents, whilst also shedding light on the perspectives of using the streams - cellulose, hemicellulose, and lignin - to produce biofuels and products of high added value. In addition, it presents an overview of the existing industrial implementations of organosolv processes and, lastly, shows the main scientific and industrial challenges and opportunities for this process.

Improvement on sugar cane bagasse hydrolysis using enzymatic mixture designed cocktail.

The aim of this work was to study cocktail supplementation for sugar cane bagasse hydrolysis, where the enzymes were provided from both commercial source and microorganism cultivation (Trichoderma reesei and genetically modified Escherichia coli), followed by purification. Experimental simplex lattice mixture design was performed to optimize the enzymatic proportion. The response was evaluated through hydrolysis microassays validated here. The optimized enzyme mixture, comprised of T. reesei fraction (80%), endoglucanase (10%) and ß-glucosidase (10%), converted, theoretically, 72% of cellulose present in hydrothermally pretreated bagasse, whereas commercial Celluclast 1.5L converts 49.11%±0.49. Thus, a rational enzyme mixture designed by using synergism concept and statistical analysis was capable of improving biomass saccharification.

Non-linear multivariable predictive control of an alcoholic fermentation process using functional link networks

Neste trabalho um controlador preditivo não linear multivariável foi desenvolvido para um processo de fermentação alcoólica extrativa. O modelo interno do controlador foi representado por duas redes do tipo Functional Link (FLN), identificadas usando dados de simulação gerados a partir de um modelo validado experimentalmente. A estrutura FLN apresenta como vantagem o treinamento rápido e convergência garantida, já que a estimação dos seus pesos é um problema de otimização linear. Além disso, a eliminação de pesos não significativos gera modelos parsimoniosos, o que permite a rápida execução em algoritmos de controle preditivo baseado em modelo. Os resultados mostram que o algoritmo proposto tem grande potencial para identificação e controle de processos não lineares.