Environment friendly emerging techniques for the treatment of waste biomass: a focus on microwave and ultrasonication processes

Shabbirahmed, Asma Musfira; Joel, J.; Goméz, Aldana; Patel, Anil Kumar; Singhania, Reeta Rani; Haldar, Dibyajyoti

doi:10.1007/s11356-023-28271-9

Cited by 10 publications

(6 citation statements)

References 167 publications

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“…The extraction efficiency peaks at 30 s (60.02%) but decreases sharply afterward, while the maximum purity is found at 60 s. The results when considering an ultrasound power of 240 W (Figure 3b) are vastly different from those found at 600 W. Due to lower power, longer exposure times were considered (0-25 min). Before 20 min, the sugar yield increases with the increasing exposure time, mainly due to the dissolution caused by ultrasonic thermal effect [37,39]. All parameters were maximized at an ultrasound treatment time of 20 min, with maximum values of sugar yield, purity, and efficiency of 34.22%, 46.80%, and 99.84%, respectively.…”

Section: Effects Of Ultrasounds On the Efficiency Of Sugar Extractionmentioning

confidence: 99%

Optimizing the Extraction of Sugars from Sewage Sludge Using Ultrasound Combined with Thermal–Alkali

Fan,

Li,

Fonseca

et al. 2024

Water

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The extraction and utilization of sugars from readily available and cost-effective sewage sludge increases the economic potential of this residue, contributing to sustainable urban development. The work presented here presents a novel method in which sugars can be directly extracted from sewage sludge following an ultrasound + thermal–alkali pretreatment. The best results indicated that by subjecting the sludge to a 240 W ultrasound for 20 min, followed by alkali digestion using 6 mL of a 2 M NaOH solution at 48 °C for 60 min, it was possible to maximize the yield of crude sugar (34.22 wt.% dry) with the purity of crude sugar at 46.80%, reaching an extraction efficiency of 99.84%. Response surface methodology was used to optimize the crude sugar yields based on experimental data, reaching a value of 34.67 wt.% dry when employing an ultrasound exposure time of 12.5 min and 6 mL of the NaOH solution for a digestion time of 57.5 min; these results were considered consistent with the experimental data.

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Section: Effects Of Ultrasounds On the Efficiency Of Sugar Extractionmentioning

confidence: 99%

Optimizing the Extraction of Sugars from Sewage Sludge Using Ultrasound Combined with Thermal–Alkali

Fan,

Li,

Fonseca

et al. 2024

Water

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“…Before lignocellulosic biomass is used in the processing to produce bio-based products or biofuels, it has to be deconstructed, and this is the main function of any pretreatment (Part II). The deconstruction of lignocellulosic biomass by the incidence of microwave radiation is possible because the microwaves force the dipolar macromolecules of the biomass to align with the oscillating electric field, which results in the rupture of hydrogen bonds and the breakdown of cell walls [57].…”

Section: Cross Linkages Types Of Bonds Polymers Involvedmentioning

confidence: 99%

“…(ii) the effect on lignin, hemicellulose, and cellulose content; (iii) the effect on the cellulose crystallinity index; (iv) the effect on the solubilization of organic matter; (v) and the effect on hydrolysis and the reduction of sugars [57,60,68,69]. Below, some examples showing each of these effects are presented and discussed.…”

Section: Physical Effects and Chemical Effects Of Microwave And Ultra...mentioning

confidence: 99%

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Microwaves and Ultrasound as Emerging Techniques for Lignocellulosic Materials

Fernandes,

Cruz-Lopes,

Esteves

et al. 2023

Materials

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Currently, in the context of biorefinery and bioeconomy, lignocellulosic biomass is increasingly used to produce biofuels, biochemicals and other value-added products. Microwaves and ultrasound are emerging techniques that enable efficient and environmentally sustainable routes in the transformation of lignocellulosic biomass. This review presents some of the most important works published in the last few years on the application of microwaves and/or ultrasound in lignocellulosic materials pretreatment and can be used as a starting point for research into this theme. This review is divided into four parts. In Part I, the theoretical fundamentals of microwave and ultrasound treatments are reviewed. Dielectric constants for biomass, factors that influence pretreatment, are some of the subjects addressed. In Part II, the effects that these techniques have on lignocellulosic biomass (on the size and surface area of the particle; on the content of lignin, hemicellulose and cellulose; on the crystallinity index of cellulose; on the effect of solubilization of organic matter; on hydrolysis and reduction of sugars) are discussed. In Part III, emphasis is given to the contribution of microwaves and ultrasound in obtaining value-added products. In this context, several examples of liquefaction and extraction procedures are presented. Part IV describes examples of performing sonocatalysis on lignocellulosic biomass to obtain value-added products, such as furfural, whose production is significantly reduced by ultrasound treatment.

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“…Though easily and widely available in nature, the proportion of cellulose, hemicellulose and lignin varies with the biomass type, geographical location or season (for the same biomass) (Luo et al, 2022;Maibam & Goyal, 2022). The intricate association of carbohydrate fractions (cellulose, hemicellulose) with lignin, maintained through hydrogen and covalent bonds (Shabbirahmed et al, 2023), must be disrupted before conversion of LCB into usable biofuels like bioethanol, biodiesel or biogas.…”

Section: Introductionmentioning

confidence: 99%

Machine learning models for the prediction on efficacy of ionic liquid-aided biomass pretreatment

Mahanty,

Gharami,

Haldar

2024

Preprint

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The influence of ionic liquids (ILs) characteristics, lignocellulosic biomass (LCB) properties, and process conditions on LCB pretreatment is not well understood. In this study, a total of 129 experimental data on cellulose, hemicellulose, lignin, and solid recovery from IL-based LCB pretreatment were compiled from literature to develop machine learning models. Following data imputation, bilayer artificial neural network (ANN) and random forest (RF) regression were developed to model the dataset. The full-featured ANN following Bayesian hyperparameter (HP) optimization though offered excellent fit on training (R2:0.936–0.994), cross-validation (R2CV) performance remained marginally poor, i.e., between 0.547 and 0.761. The fitness of HP-optimized RF models varied between 0.824–0.939 for regression, and between 0.383–0.831 in cross-validation. Temperature and pretreatment time had been the most important predictors, except for hemicellulose recovery. Bayesian predictor selection combined with HPO improved the R2CV boundary for ANN (0.555–0.825), as well as for RF models (0.474–0.824). As the predictive performance of the models varied depending on the target response, the use of a larger homogeneous dataset may be warranted.

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Environment friendly emerging techniques for the treatment of waste biomass: a focus on microwave and ultrasonication processes

Cited by 10 publications

References 167 publications

Optimizing the Extraction of Sugars from Sewage Sludge Using Ultrasound Combined with Thermal–Alkali

Optimizing the Extraction of Sugars from Sewage Sludge Using Ultrasound Combined with Thermal–Alkali

Microwaves and Ultrasound as Emerging Techniques for Lignocellulosic Materials

Machine learning models for the prediction on efficacy of ionic liquid-aided biomass pretreatment

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