Smart sustainable biorefineries for lignocellulosic biomass

Culaba, Alvin B.; Mayol, Andres Philip; Juan, Jayne Lois G. San; Vinoya, Carlo L.; Concepcion, Ronnie; Vicerra, Ryan Rhay P.; Ubando, Aristotle T.; Chen, Wei‐Hsin; Chang, Jo‐Shu

doi:10.1016/j.biortech.2021.126215

Cited by 56 publications

(14 citation statements)

References 92 publications

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“…and algorithm development. Potential applications of these technologies include data classification, optimization, pattern recognition, and prediction (Culaba et al 2022).…”

Section: Artificial Intelligence (Ai) Machine Learning (Ml) and Artif...mentioning

confidence: 99%

Integrating the new age of bioeconomy and Industry 4.0 into biorefinery process design

Clauser

Felissia

Área

et al. 2022

BioRes

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Manufacturing processes and their economy are dramatically evolving due to machinery and digital control improvements. Artificial intelligence, big data analytics, and the Internet of Things are key tools for this new industrial revolution era based on Industry 4.0. Bioeconomy and circular economy concepts have appeared in the forest, agriculture, food, pharmaceutical, pulp and paper, chemical, biotechnological, and energy areas, etc., to achieve sustainable economic growth development via biomass valorization in a biorefinery platform. Biorefinery process development at an industrial scale requires the previous design and assessment of processes and technologies. Therefore, economic, environmental, and social factors should be evaluated to prevent the failure in one of these issues that could affect the performance of the others. With a growing interest in sustainable economic development, there is a need to incorporate new technologies early enough in the process design. This study aims to better understand how Industry 4.0 era tools can bring new solutions to the biorefinery process design, in terms of the technical, economic, environmental, and social factors. Thus, these tools could improve and revolutionize the process selection optimization, provide alternatives for biomass valorization, integration strategies, and the metrics selection for process evaluation, adding the approach toward sustainable economic development.

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“…and algorithm development. Potential applications of these technologies include data classification, optimization, pattern recognition, and prediction (Culaba et al 2022).…”

Section: Artificial Intelligence (Ai) Machine Learning (Ml) and Artif...mentioning

confidence: 99%

Integrating the new age of bioeconomy and Industry 4.0 into biorefinery process design

Clauser

Felissia

Área

et al. 2022

BioRes

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“…Lignocellulosic biomass can avoid such a dilemma and enhance the circular economy. − Lignocellulosic biomass has a fascinating structure made of lignin (natural aromatic polymer) and cellulose/hemicellulose which are sugar polymers. The compositions of these elements are different for each plant, implying that operating conditions should be tuned for each biomass.…”

Section: Introductionmentioning

confidence: 99%

Kinetic Study and Model Assessment for n-Butyl Levulinate Production from Alcoholysis of 5-(Hydroxymethyl)furfural over Amberlite IR-120

Bucchianico

Cipolla

Buvat

et al. 2022

Ind. Eng. Chem. Res.

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Alkyl levulinates such as n-butyl levulinate (BL) can play an important role in the fuel sector. Classically, BL is produced from the esterification of levulinic acid, but the butanolysis (or alcoholysis) of sugars requires less stages. The industrialization of this process requires the development of process flow diagrams and thus the knowledge of reaction kinetics and thermodynamics. To the best of our knowledge, there are no kinetic models for the production of BL from sugar butanolysis over heterogeneous catalysts. The kinetics of sugar monomer butanolysis is complex over heterogeneous catalysts due to several side reactions, for example, esterification and humin productions. Hence, developing a kinetic model strategy is vital by primarily focusing on the butanolysis of 5-HMF over Amberlite IR-120. The butanolysis of 5-(hydroxymethyl)furfural (5-HMF) is the crucial step for the production of BL. The effects of temperature, catalyst, and 5-HMF loadings and catalyst deactivation on the kinetics of the different species were investigated. Then, different kinetic models were developed and tested by cross-validation. Special attention was given to vary widely the reaction temperature, catalyst, and 5-HMF loadings. To increase the accuracy of the estimation stage, independent experiments of levulinic and formic acid esterification, side products of 5-HMF dehydration, were included. It was found that the developed model with more reaction steps and by considering the reaction of humin production from 5-HMF as first order was the most reliable model.

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“…The utilization of lignocellulosic material as a renewable carbon source for high value-added products has been developed over the last decade [5]. The lignocellulosic biomass is typically composed of three major natural biomolecules including cellulose hemicellulose and lignin, which are associated together with complex chemical bonding to form a recalcitrant structure [6,7]. This structural complexity and recalcitrance make the proper lignocellulosic valorization become more difficult and have a low conversion yield [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of Combined Hydrothermal-Mechanical Pretreatment of Lignocellulosic Biomass for Enzymatic Enhancement

et al. 2022

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Pretreatment is a crucial process in a lignocellulosic biorefinery. Corncob is typically considered as a natural renewable carbon source to produce various bio-based products. This study aimed to evaluate the performance of the hydrothermal-mechanical pretreatment of corncob for biofuels and biochemical production. Corncob was first pretreated by liquid hot water (LHW) at different temperatures (140–180 °C) and duration (30, 60 min) and then subjected to centrifugal milling to produce bio-powders. To evaluate the performance of this combined pretreatment, the energy efficiency and waste generation were investigated. The results indicated that the maximum fermentable sugars (FS) were 0.488 g/g biomass obtained by LHW at 180 °C, 30 min. In order to evaluate the performance of this combined pretreatment, the energy efficiency and waste generation were 28.3 g of FS/kWh and 7.21 kg of waste/kg FS, respectively. These obtained results indicate that the combined hydrothermal-mechanical pretreatment was an effective pretreatment process to provide high energy efficiency and low waste generation to produce biofuels. In addition, the energy efficiency and waste generation will be useful indicators for process scaling-up into the industrial scale. This combined pretreatment could be a promising pretreatment technology for the production of biofuels and biochemicals from lignocellulosic valorization.

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Smart sustainable biorefineries for lignocellulosic biomass

Cited by 56 publications

References 92 publications

Integrating the new age of bioeconomy and Industry 4.0 into biorefinery process design

Integrating the new age of bioeconomy and Industry 4.0 into biorefinery process design

Kinetic Study and Model Assessment for n-Butyl Levulinate Production from Alcoholysis of 5-(Hydroxymethyl)furfural over Amberlite IR-120

Performance Evaluation of Combined Hydrothermal-Mechanical Pretreatment of Lignocellulosic Biomass for Enzymatic Enhancement

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