Ultrasound-assisted bioalcohol synthesis: review and analysis

Abstract

Sonication (or ultrasound irradiation) has emerged as a potential technique for the intensification of diverse physical/chemical/biological processes. In recent years, sonication has been applied in the synthesis of liquid biofuels, such as biodiesel, and bioalcohols, such as ethanol. The process of bioalcohol synthesis comprises four steps, viz. acid pretreatment, alkaline delignification, enzymatic hydrolysis and fermentation. Significant literature has been published in the last decade on the application of ultrasound for the intensification of all the steps of bioalcohol synthesis. In this paper, a critical review and analysis of the literature on ultrasound-assisted bioalcohol synthesis has been presented. This review has addressed all four steps of bioalcohol synthesis. Essentially, the literature in the areas of ultrasound-assisted biomass pretreatment, delignification and hydrolysis has been reviewed, followed by an analysis of the literature on ultrasound-assisted fermentation. Finally, the mechanistic investigations of the various steps of bioalcohol synthesis have been reviewed, highlighting the synergistic links between the physical/chemical effects of ultrasound and cavitation and the basic physical/chemical mechanisms of the steps of bioalcohol synthesis. The critical analysis of the literature in this review has not only demonstrated the efficacy of ultrasound in the intensification of all the steps of bioalcohol synthesis, but has also brought to light the underlying mechanistic issues; this could provide guidelines for the design and optimization of commercial scale bioalcohol processes.

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Amrita Ranjan

Dr Amrita Ranjan is a biotechnologist with a PhD in Energy from the Indian Institute of Technology Guwahati. As an Erasmus fellow, she pursued postdoctoral studies at Universitat Politechnica de Valencia, Spain. She has authored 13 research papers in international journals. Her papers have more than 300 citations (as of June 2016) with an H-index and i10 index of 7. Her major research interests are in the areas of fermentation technology, biomass to biofuel, biomass saccharification, and characterization of carbohydrates.

Shuchi Singh

Dr Shuchi Singh completed her PhD in energy at the Indian Institute of Technology Guwahati and is currently working as a postdoctoral fellow in the Department of Chemical Engineering, Indian Institute of Technology Kanpur. Her major research interest is lignocellulosic biomass pretreatment and enzymatic hydrolysis of biomass for the production of alcoholic biofuels. She has authored 14 research papers in international journals. She has more than 100 citations, with an H-index of 6.

Ritesh S. Malani

Mr. Ritesh S. Malani received a Master's degree in Petroleum Science and Technology from the Chemical Engineering Department, Indian Institute of Technology , Guwahati in 2013 and currently doing PhD from Center for Energy, Indian Institute of Technology, Guwahati. His major research interest is biodiesel production from non-edible oil using heterogeneous catalysts.

Vijayanand S. Moholkar

Dr Vijayanand S. Moholkar is a full Professor of Chemical Engineering at the Indian Institute of Technology Guwahati (India). He holds a PhD from the University of Twente, The Netherlands. He has published more than 100 research papers in international journals and has also authored several book chapters. He has also co-authored a monograph entitled Cavitation Reaction Engineering. His major research areas include applications of cavitation for the intensification of physical, chemical and biological processes, and thermochemical and biochemical routes to liquid/gaseous biofuels.

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1. Introduction

Due to the rapid depletion of global fossil fuel reserves, energy security is a daunting issue for several developing economies, especially those such as India, which are heavily dependent on the import of crude oil. Additional concerns are climate change risk and environmental pollution due to the enormous rise in the emission of greenhouse gases and particulate matter from vehicular exhaust. As a consequence, the past two decades have witnessed intense research activity in both academic institutions and industrial R&D units focused on alternate renewable liquid transportation fuels. Both thermo-chemical and biochemical routes of conversion of biomass to liquid fuel have been extensively explored. Additional options for renewable liquid transportation fuel are alcoholic fuels such as ethanol and butanol,¹ which can be blended with petrol or gasoline. These alcohols are produced from the fermentation of hexose and pentose sugars. Among the alcoholic biofuels, the most popular fuel is ethanol, which conventionally is a major byproduct of the sugar industry. However, the substrate for ethanol, i.e. molasses, has numerous other outlets, such as the beverage industry and distilleries, which pay higher prices. The sugar industry prefers to sell molasses for potable use, which generates high revenue. Thus, ethanol from the sugar industry is largely unavailable for blending with gasoline. This necessitates the exploration of alternate sources of ethanol derived from cheaper substrates. Lignocellulosic biomass, available in the form of agro-residue or forest-residue, or waste biomasses such as invasive weeds and grasses are potential substrates for bioethanol production. These biomasses have significant cellulose and hemicellulose content, which can be converted to fermentable pentose/hexose sugars after pretreatment and enzyme hydrolysis. However, a major bottleneck of commercial scale bioalcohol production from this route is the high cost of biomass pretreatment and hydrolysis. This necessitates a quest for simple, energy efficient and low-cost technology for effective biomass pretreatment. Another hurdle in the large scale commercial production of bioalcohol is the slow kinetics of fermentation, which severely restricts the rate of production. These two issues hamper the large-scale production and economic feasibility of bioalcohols, despite their promise of mitigating the threats of energy security and climate change risk. Process intensification is a possible solution to these problems related to the large-scale production of bioalcohols.

The basis for the intensification of any process (whether physical, chemical or biological) is to explore and establish new and efficient methods of introduction of energy into the system to bring about the required transformations with higher yields and kinetics. Among the methods of process intensification that have emerged in the past three decades, one is “sonication”, or ultrasound irradiation of the process (or reaction) system. Basically, an ultrasound wave is a longitudinal wave that passes through any compressible medium in the form of compression and rarefaction cycles. The molecules or fluid elements of the medium are set in oscillatory motion due to propagation of the ultrasound wave. The frequency range of the ultrasound wave is 20 kHz to about 10 MHz. As the ultrasound propagates through the medium in the form of compression/rarefaction cycles, the static pressure in the medium undergoes periodic (typically sinusoidal) variation. This variation can lead to occurrence of the cavitation phenomenon in the medium. The cavitation phenomenon basically involves nucleation, volumetric oscillations and implosive collapse of tiny gas or vapor bubbles, driven by the variation in static pressure induced by the ultrasound wave. The major peculiarity of the phenomenon of transient cavitation is that it causes extreme energy concentration in the medium at an incredibly small temporal (∼50 ns) and spatial scale (∼100 nm).² During transient implosive collapse of the bubble, the temperature and pressure inside the bubble reach extremely high values (∼5000 K and ∼50 MPa).^3,4 Energy concentration created by transient cavitation has both physical and chemical implications in the reaction system. The physical effect of ultrasound and cavitation is the generation of intense micro-mixing (or local convection) in the medium through different mechanisms, viz. microstreaming, acoustic streaming, microturbulence, acoustic waves and microjets. This convection can enhance the mass transfer in the system. The chemical effect associated with transient collapse of the cavitation bubble is essentially the generation of highly reactive radical species. These species are generated by thermal dissociation of the gas and vapor molecules entrapped in the bubble at the moment of transient collapse. The cavitation bubble may become fragmented at the instance of maximum compression (or minimum radius) during radial motion. At this moment, all chemical species inside the bubble – including radical species – are released into the medium, where they can induce/accelerate chemical reactions. This is the well known sonochemical effect. Ultrasound-assisted intensification of the synthesis of different types of biofuels has been an active area of research for the last decade, and extensive literature has been published in this area. Greater details on the basics of ultrasound wave phenomena and cavitation bubble dynamics (and associated heat/mass transfer effects) have been given in the supplementary information provided with this paper.

An excellent and comprehensive review of this literature has been recently published by Luo et al.⁵ The main biofuel processes that have been studied for ultrasound assisted intensification include: (1) pretreatment of lignocellulosic biomass (delignification under alkaline treatment/dilute acid hydrolysis), (2) enzymatic hydrolysis (or saccharification) of pretreated (cellulose rich) biomass, (3) fermentation of the pentose/hexose rich hydrolyzates from acid/enzymatic hydrolysis to bioalcohols (mainly ethanol and butanol), (4) microalgal lipid extraction, (5) biodiesel synthesis using homogeneous (acid/alkali), heterogeneous and enzyme catalysts, and (6) biogas digestion.⁶

Most of the literature published in the area of ultrasound-assisted biofuel synthesis has focused more on the results than on the rationale. Previous authors have accounted for the beneficial effects of ultrasound in terms of enhancement of the yield of the process, faster kinetics or reduction of the number of processing steps in the process. However, little effort has been made in these studies towards the deduction of the exact physical mechanism underlying ultrasound-induced enhancement of the process.⁶ Essentially, the relative contributions of the physical and chemical effects of ultrasound and cavitation (noted earlier) towards enhancement of the process have not been identified. Mechanistic investigations are crucial for effective scale-up of the process, as they give insight into the relative influence of all parameters on the gross outcome of the process and form guidelines for the optimization of these parameters.

1.1 Aim and scope of this review

The purpose of this review is to give a critical account of the literature published in the area of ultrasound assisted synthesis of bioalcohols. Since the bioalcohol process also includes the steps of biomass pretreatment, this review also includes an analysis of the literature on ultrasound assisted pretreatment of biomass, including dilute acid hydrolysis, alkaline delignification and enzymatic hydrolysis. The major objectives of this review are not only to present the summaries and overview of the literature in the area of ultrasound assisted biomass pretreatment and fermentation, but also to analyze the literature from a mechanistic viewpoint. This essentially means that we attempt to identify the exact roles played by ultrasound and cavitation in the enhancement of the pretreatment/fermentation process from the results reported in the literature; these could be in the form of an increase in the kinetics or yield of the process or the use of cruder enzymes and non-optimum conditions of pretreatment/hydrolysis/fermentation. In other words, as a peculiar feature of this study, we have attempted to establish the synergy between the basic physics/chemistry of the process and the physical and chemical effects of ultrasound and cavitation.

2. Ultrasound in biomass pretreatment

Bioprocesses for the production of alcoholic fuels comprise three steps, viz. (i) biomass pretreatment (acid hydrolysis and delignification), (ii) enzymatic hydrolysis of pretreated biomass, and (iii) fermentation of the hydrolyzates obtained from acid and enzymatic hydrolysis, which are rich in pentose and hexose sugars, respectively. The first step of this chain is not only crucially important, as it directly influences the production rate of alcohol, but is also cost intensive. The aim of biomass pretreatment is the removal of lignin and hemicellulose components from the biomass. Numerous low-cost pretreatments have been developed for lignocellulosic biomass, which include physical, chemical, and biological techniques and combinations thereof. The best possible pretreatment method is substrate specific. The main criteria used for choosing the optimum pretreatment method for a particular feedstock are: (i) preserving cellulosic and hemicellulosic fractions during treatment, (ii) limitations of formation of side products due to the degradation/oxidation of cellulose/hemicellulose (i.e. to avoid the oxidation of reducible sugars to furfural and other inhibitory products for cell growth and fermentation), (iii) minimum energy input, and (iv) cost effectiveness. In this section, we have presented a consolidated review of the literature in the area of ultrasound-assisted biomass pretreatment. However, prior to this, we give below a brief description of the most common techniques used for the pretreatment of biomass.^7,8

2.1 Physical and physico-chemical pretreatments

This treatment is essentially aimed at reduction of the particle size of the biomass. The common techniques employed in this treatment are milling, irradiation (gamma ray, electron beam, microwave, etc.) and extrusion. Decreasing the biomass particle size (leading to enhanced mass transfer) and decreasing the crystallinity enhance the yield and kinetics of enzymatic hydrolysis.

Physico-chemical pretreatments. These treatments combine both physical and chemical techniques. Some important pretreatments in this category are steam explosion, ammonia fiber explosion and liquid hot water treatment. Steam explosion is aimed at explosive decomposition of biomass by treatment with high pressure steam followed by a sudden reduction in pressure. Steam explosion causes swelling of the biomass, which increases its porosity. Moreover, this process also involves in situ formation of acids that catalyze the hydrolysis of soluble hemicellulose oligomers. Ammonia fiber explosion (AFEX) is a similar physico-chemical treatment to steam explosion. In this case, the biomass is exposed to liquid ammonia at high temperature and pressure, followed by a sudden reduction in pressure. The AFEX treatment has several beneficial effects, such as reduction of the cellulose crystallinity, depolymerization of hemicellulose, cleavage of lignin-carbohydrate linkages and lignin C–O–C bonds, structure disruption and swelling of the biomass, leading to a higher surface area and enhancement of the wettability. An extension of AFEX treatment is supercritical CO₂ explosion. This technique has distinct merits, such as operation at lower temperature, reduced degradation of sugars and lower formation of inhibitory compounds. Moreover, this technique is more economic than AFEX due to the low cost of CO₂. Liquid hot water pretreatment essentially utilizes water in the liquid state at elevated temperature and pressure for the treatment of biomass, where the biomass undergoes “cooking”. The liquid hot water pretreatment has several merits, such as enhancement of cellulose digestibility, sugar (pentose) extraction and recovery, and no formation of inhibitor compounds from the oxidation of cellulose/hemicellulose. The principal difference between liquid hot water pretreatment and steam pretreatment is the concentration of solubilized products in the solution. Liquid hot water pretreatment achieves a higher total amount of solubilized products, although at relatively lower concentrations than steam pretreatment due to the larger quantities of water used in the treatment. Liquid hot water treatment also yields higher concentrations of xylose sugars. However, at higher concentrations of solids, some of the monomeric xylenes may be lost through degradation to furfural.

2.2 Chemical pretreatments

The common chemical pretreatments for lignocellulosic biomass include: (i) ozonolysis, (ii) acid hydrolysis, (iii) alkaline hydrolysis, (iv) oxidative delignification, and (v) organosolv processes. A brief description of each of these processes is given below:

Ozonolysis. Ozone treatment is essentially the oxidative degradation of lignin. This treatment is usually carried out under aqueous or hydrated conditions, which results in more effective oxidation. Along with lignin, a small fraction of hemicellulose is also degraded; however, cellulose is not affected.

Acid hydrolysis. The acid pretreatment of biomass involves agitation/mixing of the biomass in either concentrated or dilute acid solution at elevated temperature (130 to 210 °C). The acid concentration during treatment varies from 0.2 to 2.5 wt%. Conventionally, dilute sulfuric acid is used for pretreatment, although other acids, such as phosphoric acid, hydrochloric acid and nitric acid, have also been used. Dilute acid pretreatment effectively breaks down the rigid structure of lignocellulosic material and hydrolyzes the hemicellulosic fraction of the biomass to pentose (xylose) sugars. For higher acid concentrations, the xylose sugars are further degraded to furfural. Acid pretreatment also increases the porosity of the biomass, which aids its digestibility during enzyme hydrolysis. Dilute acid pretreatment has also been found to hydrolyze the amorphous fraction of cellulose to hexose sugars, leaving behind the crystalline cellulose fraction.

Alkaline hydrolysis. The alkaline pretreatment or hydrolysis is aimed at removal of the lignin fraction of the biomass. Typical bases employed during alkaline hydrolysis include NaOH, KOH, Ca(OH)₂ and NH₄OH. The main physical/chemical changes induced by alkaline treatment include degradation of the ester and glycosidic side chains, resulting in structural alteration/degradation of lignin, partial de-crystallization/de-polymerization and swelling of the cellulose fraction and partial hydrolysis of the hemicellulose fraction of the biomass. Breaking the lignin structure during alkali treatment increases the accessibility of the cellulose and hemicellulose fractions to enzymes during hydrolysis. Unlike acid pretreatment, the alkaline treatment can be carried out at ambient conditions. However, elevated temperatures are usually employed to enhance the kinetics of the process.

Oxidative delignification. Delignification can also be achieved by enzymatic treatment with peroxidase enzyme in the presence of H₂O₂. For a typical concentration of 2 wt% H₂O₂, treatment at an ambient temperature of 30 °C can remove more than 50% lignin. Moreover, the pretreatment of lignocellulosic biomass with H₂O₂ also enhances its susceptibility to enzymatic hydrolysis. Another variant in this category is wet oxidation combined with the addition of base, which rapidly oxidizes the lignin from lignocellulosic biomasses such as wheat straw. This alternative reduces the formation of furfural or hydroxymethyl furfural, which are known inhibitors of microbial growth.

Organosolv process. The organo-solvation process involves the use of a mixture of organic or aqueous organic solvents with inorganic acid catalysts such as HCl or H₂SO₄ to disrupt the internal lignin/hemicellulose bonds. Solvents commonly used in this process are methanol, ethanol and ethylene glycol. Depending on the biomass, organic acids can also be used in the process. Typical operating conditions are temperature = 180 to 195 °C, ethanol concentration = 35–70% w/w and acidic pH of 2 to 4. Organosolv treatment effectively hydrolyzes hemicellulose to oligo- and mono-saccharides, while lignin is hydrolyzed into low molecular weight fragments that dissolve in aqueous ethanol liquor. Essentially, the organosolv process involves simultaneous prehydrolysis and delignification of lignocellulosic biomass supported by organic solvents and dilute aqueous acid solutions.

Green solvents (ionic liquids). Ionic liquids are a new class of solvents that are in the liquid (fluid) state at room temperature and consist entirely of ionic species. The thermodynamics and kinetics of reactions conducted in ionic liquids are different from those in conventional molecular solvents. Ionic liquids comprise a salt where one ion is large, and the cation has a low degree of symmetry. This feature reduces the lattice energy of the crystalline form of the salt and lowers the melting point. Ionic liquids are efficient solvents for the degradation of lignocellulosic materials. The cellulosic materials regenerated from ionic liquids have more amorphous character and are prone to degradation by cellulase. In addition, ionic liquids are less energy intensive, are easy to operate and are environmentally friendly.

Previous literature studies have reported numerous pretreatments combined with ultrasound. The synergistic effect of conventional pretreatment and the physical/chemical effects of ultrasound and cavitation boost both the kinetics and yields of different pretreatment processes. Tables 1–3 summarize the studies in 3 steps of ultrasound-assisted biomass pretreatments, viz. dilute acid hydrolysis, alkaline delignification and enzymatic hydrolysis. The literature summary presented in Tables 1–3 depicts numerous manifestations of the physical/chemical effects of ultrasound and cavitation on 3 steps of biomass pretreatment, summarized as follows: (1) faster and greater removal of lignin during alkali pretreatment, (2) increased yield of pentose and hexose sugars during acid and enzymatic hydrolysis, along with faster kinetics, (3) faster solubilization of carbohydrates, (4) reduction in particle size of the biomass, (5) disruption of the fibrous material in the biomass, with no impact on granular starch material, (6) disruption of the protein matrix surrounding the starch granules, (7) disruption of the amylase–lipid complexes, (8) reduction in intermolecular hydrogen bonding of lignocellulose, resulting in a reduction in crystallinity, (9) increase in the activities of the cellulase/cellobiase enzymes without significant denaturation. An important observation that can be made from Tables 1–3 is that abovementioned effects are consistent for numerous biomasses with wide variation in their compositions, i.e. net content of hemicellulose/cellulose/lignin. The ultrasound-assisted acid/alkali pretreatment also reduces the level of acid/alkali concentration required during the process, and higher yields are feasible at relatively lower acid/alkali concentrations. This increases the lifetime of the equipment involved in the pretreatment due to decreased corrosion. Another added benefit of this feature is that the formation of inhibitors (due to oxidation of glucose/xylose) in the hydrolyzate decreases significantly, which assists faster fermentation with higher bioalcohol yield.

Table 1 Summary of the literature on ultrasound-assisted acid pretreatment (or dilute acid hydrolysis) of biomass

Reference	Biomass	Experimental details	Major findings
Esfahani and Azin^9	Sugarcane bagasse	Time: 0 to 180 s; sonication conditions: 20 kHz, 120 W; liquid medium: sulfuric acid	94.49% sugar yield, optimum conditions: particle size < 0.18 mm, acid conc. 3% v/v, power 120 W, sonication time 180 s
Kunaver et al.^10	Wood waste	Time: 10 to 60 min; sonication conditions: 24 kHz, 400 W; liquid medium: water	4 to 9 fold reduction in liquefaction time of the biomass in a diethylene glycol/glycerol mixture with sonication with enhanced solubility
Pejin et al.^11	Triticale	Time: 5 min; temperature: 313 to 333 K; sonication conditions: 40 kHz, 125 W; liquid medium: water	Sonication improved the glucose and maltose yields by 15.7% and 52.57%, respectively, and also increased the bioethanol yield (SSF protocol) by 11%. Bioethanol yield: 0.43 g g^−1 of triticale starch
García et al.^12	Olive tree pruning residues	Time: 30 to 120 min; temperature: 323 K; sonication conditions: 50 to 60 kHz, 420 W; liquid media: acetic acid (organosolv treatment), NaOH (delignification) and water (autohydrolysis)	Ultrasound shows a 10 to 20% increase in the yield of reducing sugars, viz., glucose, xylose and arabinose, and also removal of lignin. Lignin obtained by ultrasound assisted treatment did not suffer significant modifications in its physicochemical properties
Harun et al.^13	Water hyacinth	Time: 10 to 30 min; temperature: 303 K; sonication conditions: 20 kHz; liquid medium: distilled water	Sugar yield (untreated sample): 24.7 mg sugar per g dry matter; steaming (121 °C) and boiling (100 °C) increases the sugar yield by 36% and 52%; the highest sugar yield = 132.96 mg sugar per g dry matter with sonication for 20 min
Nikolić et al.^14	Corn	Time: 1 to 10 min; temperature: 333 K; sonication conditions: 40 kHz	Increases in glucose concentration of 6.82% and 8.48% during pretreatment with ultrasound and microwave, respectively; increases in ethanol concentration during SSF of 11% and 13% for ultrasound and microwave treatment, respectively
Karki et al.^15	Hexane-defatted soybean flakes	Time: 15 to 120 s; sonication conditions: 20 kHz; 2.2 kW; liquid medium: tap water	Sonication reduced particle size by 10 fold and increased total sugar release by 50% and total protein yield by 46% at high amplitude
Nikolić et al.^16	Corn	Time: 1 to 30 min; temperature: 333 to 353 K; sonication conditions: 40 kHz; 600 W; liquid medium: water	Sugar yield increased by 7% with sonication. Max ethanol concentration (SSF treatment) of 9.67% w/w with sonication (11.15% augmentation)
Yunus et al.^17	Oil palm empty fruit bunch (OPEFB)	Time: 15 to 60 min; temperature: 298 K; sonication conditions: 20 kHz, 2 kW; liquid medium: sulfuric acid	A 3-fold increase in xylose yield was obtained with sonication at 100 °C; no distinct effect of sonication on the increment in xylose yield for treatment at 120 and 140 °C
Nitayavardhana et al.^18	Cassava chips	Time: 10 to 30 s; temperature: 323 K; sonication conditions: 20 kHz, 2.2 kW; liquid medium: acetate buffer at pH 4.8	40-Fold reduction in cassava particle size with sonication. Sonication reduces fermentation time by 24 h with a 2.7 fold increase in bioethanol yield; reducing sugar yield = 22 g per 100 g of samples
Aimin et al.^19	Eucalyptus cellulose fiber	Time: 0 to 720 s; sonication conditions: 23 to 25 kHz, 400 W; liquid medium: sodium periodate	Change in morphology, accessibility and oxidation reactivity of cellulose with sonication. Increase in cellulose accessibility (73–119%) without much change in structure

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Table 2 Summary of the literature on ultrasound-assisted alkaline pretreatment (or delignification) of biomass

Reference	Biomass	Experimental details	Major findings
Bussemaker et al.^20	Wheat straw	Temperature: 328 K; sonication conditions: 40, 376 and 995 kHz; liquid medium: water	Delignification was favored at a frequency of 40 kHz (7.2%) and carbohydrate solubilization (9.1%) was favored at 995 kHz
Baxi and Pandit^21	Wood	Temperature: 303 K, sonication conditions: 22 kHz, 240 W	The lignin content of wood was reduced to the required value at room temperature and low pressure using hydrodynamic cavitation
Sasmal et al.^22	Arecanut husk, bon bogori and moj (Albizia lucida)	Time: 60 to 180 min; temperature: 308 K; sonication conditions: 30 kHz, 100 W; liquid medium: lime solution	% delignification and bioethanol concentration by SSF of ultrasound pretreated biomass: arecanut husk – 65%, 22.5 g L^−1; bon bogori – 68%, 34.4 g L^−1; moj (Albizia lucida) – 64%, 39.1 g L^−1
Velmurugan and Muthukumar^23	Sugarcane bagasse	Time: 20 min; temperature: 323 K; sonication conditions: 25 kHz, 400 W; liquid medium: NaOH (2%)	Sono-assisted alkali pretreatment removed 81% lignin and 91% hemicellulose. Optimum conditions: reaction time – 360 min, liquid to solid ratio – 15 : 1, cell mass – 15 g L^−1
Velmurugan and Muthukumar^24	Sugarcane bagasse	Time: 5 to 50 min; temperature: 343 K, sonication conditions: 25 kHz, 400 W, liquid medium: NaOH	Maximum sugar yield under optimum conditions: 92.1%, substantial reduction in pretreatment time and temperature with improved efficiency with ultrasound-assisted alkaline pretreatment
Chen et al.^25	Poplar wood	Time: 1 to 2 h; temperature: 338 to 343 K; sonication conditions: 20 to 25 kHz, 400 to 1200 W; liquid medium: 3 to 6 wt% KOH	5 to 20 nm ranged nanofibers obtained with hemicellulose, extensive lignin removal, and crystallinity of 69%
Velmurugan and Muthukumar^26	Sugarcane bagasse	Time: 15 to 75 min; temperature: 323 K; sonication conditions: 24 kHz, sono-assisted alkaline pretreatment	Cellulose and hemi-cellulose recovery – 99% & 79%, respectively; lignin removal – 75%. Very low inhibitor content in hydrolyzate. Bioethanol yield = 0.17 g g^−1 of pretreated sugar cane bagasse
Yuan et al.^27	Poplar wood	Time: 30 min, 3 h; temperature: 298 and 348 K; sonication conditions: 20 to 24 kHz, 570 W; liquid media: ethanol, dimethyl sulfoxide, NaOH	Sonication/extraction with NaOH releases 96% lignin and 75.5% hemicellulose. Purified hemicellulosic fractions contain low amounts of associated lignin
Zhang et al.^28	Corn	Time: 48 h; temperature: 298 K; sonication conditions: 4 kHz, 80 W; liquid medium: NaOH	No change in the surface conformation of the granular raw material by sonication. Increase in the catalytic efficiency of cellulase by 70% and 44% lignin removal with sonication
Sun et al.^29	Sugarcane bagasse	Time: 40 min; temperature: 328 K; sonication conditions: 20 kHz; 100 W; liquid medium: distilled water at pH 11.5	>90% extraction of hemicellulose and lignin in proginal biomass with ultrasound. No change in the structure of the hemicellulosic fraction, which comprised L-arabino(4-o-methyl-D-glucurono)-D-xylans
Sun et al.^30	Wheat straw	Time: 5 to 35 min; temperature: 333 K; sonication conditions: 20 kHz, 100 W; liquid medium: NaOH in 60% aqueous methanol	Increase in hemicellulose yield: 2.9 to 9.2% for 5 to 35 min sonication. Hemicelluloses isolated with sonication had relatively lower molecular weight and greater linearity
Sun and Tomkinson^31	Wheat straw	Time: 5 to 35 min; temperature: 308 K; sonication conditions: 20 kHz, 100 W; liquid medium: KOH	Lignin removal: 43.9 to 49.1% for ultrasound treatment for 5 to 35 min. High purity of lignin with ultrasonic treatment with lower content of polysaccharides

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Table 3 Summary of the literature on ultrasound-assisted enzymatic hydrolysis of biomass

Reference	Biomass	Experimental details	Major findings
Bharadwaja et al.^32	Parthenium hysterophorus	Time: 4 h; temperature: 303 K; sonication conditions: 35 kHz, 35 W. Optimization of enzyme hydrolysis using RSM	Sonication gives 18-fold enhancement in the kinetics of hydrolysis. Total ethanol yield from fermentation of pentose and hexose hydrolyzates = 0.26 g g^−1 raw biomass
Sulaiman et al.^33	Carboxymethyl cellulose (CMC) and insoluble cellulose	Time: 20 min; temperature: 323 K; sonication conditions: 10, 20 and 40% duty cycles; liquid medium: acetate buffer, pH 4.8	Optimum duty cycle: 10% for 2-fold higher reaction rate. Increase in max reaction rate Vmax with decrease in Michaelis constant Km. Loss of enzyme activity with sonication
Li et al.^34	Sugarcane bagasse	Time: 20 to 40 s; temperature: 363 K; sonication conditions: 45 kHz, 100 W; liquid medium: aq. N-methyl morpholine-N-oxide (NMMO)	NMMO-treated cellulose under ultrasound was porous and amorphous, which assists saccharification. Sonication resulted in higher hydrolysis (96.5%) of biomass
Ninomiya et al.^35	Kenaf core fiber	Time: 0 to 120 min; temperature: 298 K; sonication conditions: 24 kHz, 35 W; liquid media: ionic liquids	60 to 95% cellulose hydrolysis to glucose in ionic liquids at 25 °C. Cellulose saccharification ratio in ionic liquid EmimOAc = 86% for 15 min ultrasound pretreatment at 25 °C
Karki et al.^36	Extruded full fat soybean flakes	Time: 30 to 60 s; sonication conditions: 20 kHz, 2.2 kW; liquid medium: sodium acetate buffer	No increase in saccharification yield after 30 and 60 s sonication of the insoluble fraction
Montalbo-Lomboy et al.^37	Corn	Time: 5 to 40 s; sonication conditions: 20 kHz; liquid medium: acetate buffer, hydrolysis of starch using α-amylase and gluco-amylase	3-Fold increase in sugar release with sonication of the maize mash. Partial gelatinization of sugary starch during sonication. Increase in activity of the enzymes during sonication
Yang et al.^38	Microcrystalline cellulose	Time: 30 min; temperature: 333 K; sonication conditions: 45 kHz, 100 W; liquid medium: alkylphosphate ionic liquids (aq. media)	>95% conversion of cellulose to glucose in aq. Mmim dimethyl phosphate with sonication. Ionic liquid-treated cellulose undergoes depolymerization with sonication, which assists saccharification
Shewale and Pandit^39	Three different types of sorghum grains	Time: 1 min; sonication conditions: 20 kHz, 750 W; liquid media: acetate buffer and citrate buffer, pH 4.5 and 5.5, respectively	Sonication increases saccharification by 8% and reduces particle size by 50%. Higher availability of additional starch for hydrolysis due to ultrasound-assisted disruption of the protein matrix
Yu et al.^40	Rice hull	Time: 10 to 60 min; temperature: 298 K; sonication conditions: 40 kHz, 250 W	Pretreatment combining sonication + H2O2 followed by biological treatment. Higher lignin degradation and increase in total reducible sugar yield
Khanal et al.^41	Corn slurry	Time: 20 to 40 s; sonication conditions: 20 kHz, 2.2 kW; liquid medium: acetate buffer and water	Enhanced enzyme activity but did not denature the enzymes. 20-fold particle size reduction, 2-fold increase in total sugar release
Li et al.^42	Waste paper	Temperature: 318 K; sonication conditions: 20 kHz, 250 W; liquid medium: acetate buffer at pH 4.8	Enhancement of saccharification of wastepaper with ultrasound
Imai et al.^43	Carboxymethyl cellulose	Time: 30 min; temperature: 323 K; sonication conditions: 135 W; liquid medium: acetate buffer	Pretreatment of cellulose fibers with sonication before enzymatic hydrolysis improved the hydrolysis reaction rate
Li et al.^44	Paper pulp	Time: 48 h; temperature: 318 K; sonication conditions: 20 kHz, 30 W; liquid medium: acetate buffer	Crystallinity and residual lignin of pulp affect saccharification rate. Sonication increases the reaction velocity of hydrolysis, but there is no effect on Km and the competitive product inhibition constants

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The extent of ultrasound-induced enhancement of pretreatment is, however, highly system specific. It depends on numerous factors, such as the frequency and intensity of the ultrasound, the type of sonicator employed (bath or probe), the geometry of the sonicator or the vessel used for pretreatment, and the temperature of the medium. Due to the significant variation of these factors from one system to another, a quantitative comparison of the results of different studies is quite difficult. Among all factors listed above, the ultrasound intensity (or power) is crucially important, as it determines the amplitude of the ultrasound waves generated in the system. Most of the papers report the rated (or theoretical) power of the sonicator equipment. However, the actual acoustic power input to the system is quite different. This is determined by the “acoustic impedance” of the system. The actual (or net) acoustic power delivered to the system is determined using a calorimetric technique, and the acoustic pressure amplitude can be calculated using a simple procedure described by Sivasankar et al.⁴⁵ The nature of the cavitation bubble dynamics – whether stable or transient – depends on the ultrasound pressure amplitude. The volumetric dissipation of the acoustic power is also an important factor which has not been reported in most of the existing literature. Due to these limitations of the existing literature, the deduction of the physical mechanism of the ultrasound induced enhancement of biomass pretreatment is difficult.

3. Ultrasound assisted fermentation

In addition to biomass pretreatment, ultrasound has also been used to enhance the fermentation of pentose and hexose rich hydrolyzates obtained from biomass pretreatments. Previous authors have addressed the matter of the ultrasound-assisted fermentation process for the production of alcohols. Two approaches have been adopted in previous studies: (1) sonication of the microbial cells (or inoculum) alone before its addition to the fermentation broth (with actual fermentation being carried out using mechanical agitation), and (2) intermittent sonication of the fermentation mixture itself throughout the fermentation period. The literature in this area is quite limited compared to that in the areas of ultrasound-assisted biomass pretreatment and enzymatic hydrolysis. We give below a summary of the literature:

(1) Ofori-Boateng and Lee⁴⁶ have reported ultrasound assisted simultaneous saccharification and fermentation of pretreated oil palm fronds. Prior to fermentation, the biomass was treated with ultrasound assisted organosolv/H₂O₂ at 32 kHz frequency and 200 W power. The ultrasound-assisted SSF process was optimized for the following parameters: fermentation time, temperature, solid loading, pH, and yeast concentration. Optimization was carried out using the “one variable at a time” approach. The ranges of values for the various optimization variables were as follows: fermentation time = 30 to 360 min, temperature = 30 to 50 °C, pH = 3 to 7, yeast concentration = 5 to 20 g L⁻¹, and solid loading = 2.5–15% w/v. The maximum theoretical yield of bioethanol was determined using the following equation:

where C_Bioethanol = maximum concentration of ethanol at the end of fermentation (g L⁻¹), f_cellulose = cellulose fraction in the pretreated biomass, C_substrate = concentration of substrate at the beginning of SSF, 0.51 = theoretical conversion factor from glucose to ethanol, 1.111 = conversion factor for dehydration on polymerization to glucose. The optimum conditions for SSF have been determined as follows: incubation time = 5 h, temperature = 40 °C, pH = 5, yeast concentration = 15 g L⁻¹, and solid loading = 10% w/v. The maximal bioethanol concentration at these conditions was 18.2 g L⁻¹ with a theoretical yield of 57% with the application of sonication; a 6-fold increase in bioethanol concentration and a 4-fold increase in the percentage yield of bioethanol were obtained. Ofori-Boateng and Lee⁴⁶ have attributed the high bioethanol yield at high solid loading and low fermentation time to sonication effects that disrupted the biomass, enabling microorganisms to efficiently penetrate the biomass and convert sugars to bioethanol.

(2) Indra Neel et al.⁴⁷ have reported an enhancement in glucose fermentation by S. cerevisiae to produce ethanol under mild sonication conditions. Fermentation was carried out in an ultrasound bath at 40 kHz frequency and 120 W of theoretical power at two temperatures, viz. 20 and 30 °C. The kinetics of fermentation was assessed using ¹³C NMR spectroscopy, as well as the weight reduction of the fermentation broth due to CO₂ formation. The overall reaction rate constant of fermentation was determined by fitting first order kinetics to the glucose conversion profile. Microscopic analysis of the yeast cells revealed that mild sonication caused deagglomeration of the yeast cells; however, no disruption of the cells was observed. The kinetic constants of the fermentation process were enhanced 2.3 and 2.5 fold at 30 °C and 20 °C, respectively. Indra Neel et al.⁴⁷ did not observe yeast proliferation (or growth) in the presence of ultrasound. Indra Neel et al.⁴⁷ have attributed the ultrasound-induced enhancement of fermentation to several factors, viz., (1) removal of ethanol from the cell surface due to strong micro-stirring, (2) desorption of CO₂ from the fermentation broth, (3) changes in the membrane permeability of the cells, and (4) enhancement in the mass transfer of the cells. Indra Neel et al.⁴⁷ also determined the energy efficiency of the ethanol production process using the EROEI (Energy Return on Energy Invested) index, which was calculated as ∼0.9.

(3) Sulaiman et al.⁴⁸ studied ethanol production from the fermentation of lactose using the yeast Kluyveromyces marxianus (ATCC 46537) under ultrasound irradiation in a bioreactor (BIOFLO 110). Low-intensity sonication using 10%, 20% and 40% duty cycles was applied during fermentation in batch mode. The fermentation broth was sonicated using a sonotrode mounted in an external chamber, and the fermentation broth was continuously recirculated between the bioreactor (total capacity 7.5 L, working volume 3 L) and the sonication chamber with a flow rate of 0.2 L min⁻¹. For the optimum duty cycle of 20%, a final ethanol concentration of 5.20 ± 0.68 g L⁻¹ was achieved, which was 3.5-fold higher than that under control conditions (with mechanical agitation). Sonication at duty cycles of 10% and 20% substantially improved the biomass growth rate and final concentration relative to the control conditions; however, a further increase in the duty cycle to 40% adversely affected the biomass growth rate and final concentration. The adverse effect of sonication at the 40% duty cycle was reflected in the dissolved oxygen concentration during exponential growth, which was found to be less than that for smaller duty cycles. Pulsed ultrasound with duty cycles at all levels augmented ethanol production relative to control conditions; however, the duty cycles of 10% and 20% were most effective. Sonication at 10% and 20% cycles enhanced both the extracellular and the intracellular levels of β-galactosidase enzyme. Cell viability studies showed that the viability progressively decreased with increasing duty cycles of sonication. The maximum reduction in cell viability was seen for the ultrasound duty cycle of 40%. At the end of the fermentation, >65% of the yeast cells retained viability in the broth.

(4) Jomdecha and Prateepasen⁴⁹ have investigated the effects of pulsed ultrasound irradiation on the lag phase of Saccharomyces cerevisiae growth. Ultrasound of 20 kHz and 600 W maximum theoretical power was applied at power levels of 2, 8, 16, 24 and 32% with a duty cycle of 10%. The total sonication periods were 10 and 20 min for the two flasks containing microbial cultures. After sonication, the flasks were incubated for 24 h at 30 °C with orbital agitations of 100 rpm. For an ultrasound energy density of 230 J m⁻³, the shortest lag duration of 4.74 h was observed, while the longest lag time of 5.9 h was obtained for an ultrasound energy input of 918 J m⁻³. The highest specific growth rate of 0.476 h⁻¹ was obtained for an energy input of 525 J m⁻³. Higher microbial growth was seen for the cultures in the flasks sonicated for 20 min. The authors have explained their results on the basis of faster transport of the nutrients and oxygen across the cell membrane, which reduced the lag period. Contrastingly, a longer lag time was seen at high ultrasound energy levels, which was sufficient to induce cavitation. Jomdecha and Prateepasen⁴⁹ have suggested that cavitation and the irradiation force from high ultrasonic energies may inactivate the microbial growth.

(5) Lanchun et al.⁵⁰ have reported the effect of low intensity ultrasound on the physiological characteristics of Saccharomyces cerevisiae. The cells of Saccharomyces cerevisiae were grown at 29 °C in YPD medium until the logarithmic growth phase was reached, after which the ultrasound treatment was applied at 24 kHz, 2 W power and 6.7% duty cycle (1 s sonication followed by 14 s silent treatment for every 15 s treatment). The characteristics of the ultrasound-treated cells, such as flocculation, substrate consumption, ascospore production and proteinase activity, were assessed. It was revealed that flocculation of the cells decreased after ultrasonic treatment. This result was attributed to alternations of the surface characteristics of the cell membrane induced by sonication. The substrate consumption rate increased with the sonication. Lanchun et al.⁵⁰ have attributed this result to the change in membrane osmosis induced by sonication, in addition to enhancement of the enzyme activity. Overall, the cell metabolism was enhanced due to sonication. However, this enhancement was not permanent in nature and was observed only in the presence of ultrasound.

(6) Radel et al.⁵¹ studied the viability of S. cerevisiae cells (NCYC1006) in standing and propagating ultrasound wave fields with a frequency of 2.2 MHz and 14 W power. The standing wave field is created by interaction of the incident and reflected ultrasound waves from the glass surface of the flask containing the cell culture. To generate the propagating wave field, a spike-shaped sponge was attached to the glass surface of the flask so as to dampen and scatter the incident wave. In the standing wave field, the microbial cells are driven towards the pressure nodes due to Bjerknes forces and remain at this location. The viability of the cells was determined using two methods: (i) measurement of the percentage of dead cells using methylene blue staining, and (ii) monitoring of the morphological changes by SEM. Micrographs of the sonicated yeast cells show morphological changes compared to the native cells. Ultrasound also altered the integrity of the cell vacuole, while the nucleus and the envelope of the cells are not affected. The presence of fermentation end products in the medium was found to influence the separation and viability of the yeast cells. The loss of cell viability increased with the concentrations of the end products in the medium, and leakage of intracellular material was also seen. Addition of 12% v/v ethanol to the medium disrupted the standing wave field. Under these conditions, the microbial cells were not concentrated at pressure nodes but were dispersed in the medium. The agglomeration of yeast cells within the pressure nodal planes was revealed to minimize the damaging effects of the ultrasonic field on the cells.

(7) Schläfer et al.⁵² have studied the improvement in the biological activity of microbial cultures in bioreactors at low ultrasound intensity. A microbial culture of S. cerevisiae was used with glucose as the substrate. Sonication treatment was carried out at 25 kHz frequency and two power levels, viz. 0.3 W/L for low energy ultrasound and 12 W/L for high power ultrasound. Interestingly, the use of high power ultrasound did not result in a higher ethanol yield. Schläfer et al.⁵² have claimed that due to low power, cavitation did not occur in the medium. However, sonication reduced the agglomeration of the cells. Intermittent sonication in the form of pulses resulted in greater production of ethanol compared to continuous sonication. The microbial cells retained higher activity even after stoppage of the sonication. Schläfer et al.⁵² have suggested the enhancement of the membrane permeability and the activity of the enzymes involved in intracellular metabolism as probable causes leading to the enhancement in the “bioactivity” of the microbial cultures, resulting in higher bioethanol production.

(8) Wood et al.⁵³ have studied the enhancement effects of ultrasound on the simultaneous saccharification and fermentation (SSF) process for ethanol production using mixed waste office paper as the substrate. The mixed waste paper contained approximately 90% carbohydrates and 10% inert materials. K. oxytoca P2 was used as the microbial culture in the fermentation. A mixture of two commercial enzymes, viz. Spezyme CP and Novozyme 188, was used for saccharification. Ultrasound was generated using a Telsonic 36 kHz tube resonator with a maximum theoretical power of 150 W attached to the head plate of the fermenter. The enzyme stability (cellulase and β-glucosidase) in the presence of ultrasound treatment was ascertained. Control experiments with mechanical agitation revealed that the kinetics of the saccharification process was a limiting factor at low enzyme concentrations. Sonication of the fermentation broth at a 5.88% duty cycle (15 min sonication/240 min silent period) resulted in increased ethanol yield. For 24 h treatment, the ultrasound-induced enhancement in ethanol production was ∼50% (ethanol concentration of 14.3 g L⁻¹ against 9.5 g L⁻¹ under the control conditions), while for 96 h treatment, the enhancement was ∼15% (ethanol concentration of 34 g L⁻¹ against 29.4 g L⁻¹ under the control conditions). This result indicated that the influence of ultrasound on the SSF process is more marked in terms of kinetics rather than the final yield of ethanol. It was revealed that sonication of the fermentation broth resulted in higher ethanol yield at relatively lower concentrations of the enzymes for hydrolysis. Intermittent sonication of the fermentation broth was more beneficial for saccharification than continuous sonication, which could decrease cellulase binding. Continuous sonication of the K. oxytoca microbial culture was found to inhibit sugar metabolism, cell growth and division. A probable cause underlying this effect could be leakage of intracellular metabolites and induction of SOS proteins. Intense microturbulence generated by ultrasound causes dissociation of the cellulose substrate, which assists the binding of the active enzymes at new sites for faster hydrolysis.

4. Mechanistic insight into ultrasound assisted synthesis of bioalcohols

The literature in the areas of ultrasound assisted biomass pretreatment, enzymatic hydrolysis and fermentation reviewed in the preceding sections has reported several beneficial influences of ultrasound irradiation or sonication on the kinetics and yield of these processes. However, most of this literature is focused on results rather than rationale. Few attempts have been made to establish the physical mechanism of the enhancements in the kinetics or yield of the processes induced by ultrasound and cavitation. In other words, the synergistic links between the physics/chemistry of the pretreatment, enzymatic hydrolysis and fermentation process and the physical/chemical effects of ultrasound and cavitation have not been explored and identified. In this section, we have presented a review of the literature that has investigated the pretreatment/hydrolysis/fermentation processes with a mechanistic approach. In the papers reviewed in this section, an attempt is made to establish the physical mechanism of the influence of ultrasound and cavitation on pretreatment/hydrolysis/fermentation systems by concurrent analysis of the results of cavitation bubble dynamics simulations and experimental results. These papers have also attempted to discriminate between the relative contributions of the physical and chemical effects of ultrasound and cavitation to this enhancement.

4.1 Ultrasound assisted acid hydrolysis/alkaline delignification of biomass

As noted earlier, pretreatment of the biomass is an energy intensive step in bioalcohol production. Combining conventional pretreatment techniques with sonication can enhance the kinetics/yield of the process with faster and higher production of reducible sugars. Rice is a major crop in many developing countries, such as India. The residues of rice crops (rice straw or rice husks) are rich in cellulose/hemicellulose and, hence, are potential fermentation substrates. Suresh et al.⁵⁴ have carried out mechanistic investigations of sono-hybrid techniques for the pretreatment of rice straw prior to its fermentation into alcohol liquid fuels. Two chemical techniques, viz. dilute acid and dilute alkali treatment, and two physical techniques, viz. hot water bath and autoclaving, were coupled with sonication. The yardstick for the assessment of the efficacy of sono-hybrid techniques was the total sugar and reducing sugar released. The total sugar released during acid and alkali pretreatment includes sugars in all forms, viz. monomer sugars (i.e. pentose sugars such as xylose and arabinose and hexose sugars such as glucose and mannose), oligomers (cellobiose) and dehydrated forms that form at low pH from xylose and glucose, such as furfural and hydroxymethyl furfural. The reducing sugar or fermentable sugar fraction of the total sugar is essentially the monomeric sugar. Suresh et al.⁵⁴ used the technique of application of elevated static pressure to discriminate between the physical and chemical effects of ultrasound and cavitation. The experimental results were correlated with simulations of cavitation bubble dynamics, which predicted the magnitudes of micro-streaming, microturbulence and shock waves generated by ultrasound and cavitation. In addition, the acoustic streaming near the boundaries was also accounted for using the model of Nyborg⁵⁵ for steady circulations induced by high amplitude sound fields near the surfaces of obstacles, vibrating elements and bounding walls. Nyborg⁵⁵ proposed that gas is released from solution under the influence of ultrasound at a solid–liquid surface, which leads to the formation of gas nuclei on the surface. The oscillatory velocities of the liquid induced by volume oscillations of these gas bodies generate highly localized streaming. As per the analysis of Nyborg,⁵⁵ the micro-streaming velocity induced by a pulsating hemispherical bubble has been determined as follows (eqn (2)):

U_ms = (U²/ω_R) (2)

where U_ms is the velocity amplitude of oscillations of the fluid elements, ω is the angular frequency of the acoustic wave and R is the radius of the bubble. For an acoustic pressure amplitude of 150 kPa, the velocity of fluid elements is 0.1 m s⁻¹. For an ultrasound frequency of 35 kHz, as used by Suresh et al.,⁵⁴ and 5 μm bubbles trapped in the biomass matrix, the localized micro-streaming velocity is 0.09 m s⁻¹.

Suresh et al.⁵⁴ observed the following trends in the release of reducing and total sugars:

(1) The physical technique of autoclaving alone did not provide significant sugar release. However, when autoclaving was coupled with subsequent sonication, the sugar release increased markedly.

(2) Sonication after autoclaving in an acidic environment resulted in a twofold increase of the sugar release. However, increasing the static pressure of the system was revealed to reduce the sugar release.

(3) The highest sugar release (∼54% w/w rice straw) was obtained for autoclaving and stirring followed by sonication in an acidic environment. As per the composition of rice straw, this was the highest possible sugar yield from rice straw with hydrolysis of all cellulose and hemicellulose components of the biomass.

The chemical mechanism of different reactions occurring during biomass pretreatment must be considered during analysis of the results. Autoclaving causes hydrolysis of hemicelluloses in the biomass, resulting in the formation of organic acids such as acetic acid. Water itself promotes hydrolysis at elevated temperatures due to the change in the ion product, which assists in the reaction of hemicelluloses. Autoclaving causes rapid thermal expansion of the biomass, which expands the biomass structure with increased pore volume. Hot water bath treatment enhances the digestibility and sugar extraction of cellulose. Dilute acid treatment causes solubilization of the hemicellulose fraction in the biomass but leaves the lignin and cellulose intact. This helps increase the accessibility of cellulose during enzymatic hydrolysis. High xylose (monosaccharide) yield with complete hydrolysis of oligomeric hemicellulose saccharides can be obtained under optimized conditions of acid pretreatment. The main effect of alkaline pretreatment on biomass is delignification; however, partial hydrolysis of hemicelluloses may also occur. The principal chemical mechanism of alkaline treatment is saponification of the intermolecular ester bonds cross-linking xylan hemicelluloses, other celluloses and lignin. Acetyl and uronic acid substitutions on hemicelluloses are removed during alkaline treatment. In addition to these chemical effects, alkaline treatment also has the physical effect of swelling the biomass, resulting in a reduction in the degrees of polymerization and crystallinity, an increase in the surface area, and disruption of the lignin structure and the structural linkages between lignin and carbohydrates.

The above discussion clearly shows the role of mass transfer in the acid/alkali pretreatment of biomass. Long chain cellulose is less soluble in water than the short chain oligomers formed as intermediates during hydrolysis; however, the solubility of both species decreases with temperature. Continuous liquid flow through the reaction system causes effective removal of the oligomers from the biomass matrix, which facilitates further dissolution of the oligomers. This process increases the recovery of sugar monomers and oligomers before they can degrade under the reaction conditions. This process also prevents the re-precipitation of oligomers onto the surface of the biomass due to decreased solubility at reduced temperature. Reactive lignin and sugar degradation products can promote the reattachment of cellulose, hemicelluloses, their oligomers and lignin in the solution to the solid biomass, and these may also form complexes with monomeric sugars. Strong micro-convection-generated ultrasound and cavitation cause effective circulation of water through the biomass matrix with regular removal of monomeric sugars and refreshment of the medium, which obviates these adverse effects. In addition to the physical effects of the generation of intense microturbulence, radicals generated during the transient collapse of cavitation bubbles can also enhance sugar release due to cleavage of the lignin carbohydrate components.

(1) Increasing the autoclaving period of the biomass did not enhance the sugar yield. The extent of hemicellulose hydrolysis may increase with higher periods of autoclaving. However, as the convection in the reaction system is low, sugar molecules are not effectively transported out of the biomass matrix. Thus, the sugar concentration in the bulk medium shows negligible change with increasing autoclaving periods. The autoclaving step followed by sonication of the reaction mixture aids the effective transport of sugar molecules out of the biomass matrix, leading to increased sugar concentration in the bulk.

(2) Stirring the biomass solution after autoclaving also does not increase the sugar yield. The result of Suresh et al.⁵⁴ indicates that mechanical stirring of the solution does not produce sufficiently strong currents to penetrate the biomass matrix and enable sugar transport out of the biomass, as observed in case of sonication.

(3) Elevation of the static pressure of reaction system causes elimination of the transient cavitation events in the medium. However, the reduction in the sugar yield is slight at elevated pressure, which indicates the negligible contribution of transient cavitation to the overall process of pretreatment and sugar release. Neither the microturbulence nor the shock waves generated by the cavitation bubbles were sufficiently intense to open up the biomass matrix and create liquid flow through the matrix, which would assist sugar release. Contrastingly, micro-streaming due to ultrasound and acoustic streaming made a greater contribution to the enhancement of the transport of sugar molecules. Opening of the biomass structure due to expansion is found to occur only with autoclaving (a thermal effect), and ultrasonic micro-streaming plays the secondary role of enhancing the transport of sugar molecules through the expanded biomass.

Ultrasound-assisted alkaline delignification. Singh et al.⁵⁶ have performed a mechanistic assessment of the process of alkaline delignification with ultrasound using the waste biomass of Parthenium hysterophorus. NaOH was used as the delignifying agent, with pretreated biomass (after dilute acid hydrolysis and autoclaving) as the substrate. The study included optimization of process parameters and conditions such as temperature, NaOH concentration and biomass concentration.

The extent of delignification under various treatment conditions was determined according to standard TAPPI⁵⁷ protocols. Characterization of the delignified biomass was carried out using FTIR, XRD and FESEM analysis. Prior to analysis of experimental results, the chemical mechanism of delignification vis-à-vis the physical/chemical effects of ultrasound and cavitation must be considered:

Lignin is derived from three monomer units, viz. trans-coniferyl, trans-sinapyl and trans-p-coumaryl alcohol. These units are linked randomly, mostly via ester linkages at the α- and β-positions, to construct the lignin macromolecules. The reactive sites in lignin are mainly the ester linkages and functional groups, since C–C bonds are resistant to chemical attack. The areas of lignin susceptible to chemical attack are the hydrolysable ester linkages, phenolic and aliphatic hydroxyl groups, methoxy groups, unsaturated groups and uncondensed units. The main mechanism of lignin degradation in an alkaline environment is the cleavage of α- and β-aryl ether linkages. Ultrasound and cavitation can contribute to the depolymerization and separation of lignin, in addition to the degradation of the lignin components. Fig. 1 shows graphical simulations of the radial motion of cavitation bubbles in an alkaline solution of 1.5% w/v NaOH. It can be seen that the temperature peak in the bubble at transient collapse reaches ∼5000 K, at which the water molecules in the bubble dissociate, forming ˙H and ˙OH radicals. The transient bubble collapse also generates acoustic waves of high pressure amplitude (∼500 bar). Depolymerization of lignin with sonication can occur through homolytic cleavage of phenyl ether β-O-4 and α-O-4 bonds, while separation of lignin due to sonication can occur as a result of the cleavage of lignin–hemicellulose linkages. Lignin degradation may also be affected by the hydroxyl radicals produced from transient cavitation bubbles. ˙OH radicals can attack aromatic rings, leading to the formation of hydroxylated, demethoxylated and side chain eliminated products. A relatively small extent of attack can also occur on the side chains, leading to the formation of dimers and the oxidation of aromatic aldehydes to carboxylic acids. An increase in the number of non-conjugated carboxyl moieties also indicates hydroxyl radical induced degradation. It should be noted that sonication can also cause lignin condensation and re-polymerization.

Fig. 1 Representative simulation results (5 μm air bubble at 303 K, NaOH conc. 1.5% w/v). Time variation of (A) normalized bubble radius (R/R_o); (B) temperature in the bubble; (C) number of water molecules in the bubble; (D) pressure inside the bubble; (E) micro-turbulence generated by the cavitation bubble; (F) acoustic (or shock) waves emitted by the bubble (reproduced from Singh et al.⁵⁶ with permission of American Chemical Society).

The major findings of Singh et al.⁵⁶ are as follows:

(1) The kinetics of delignification is enhanced more than twofold with ultrasound.

(2) The extent of delignification with ultrasound was practically the same in the range of 30 to 80 °C. At higher biomass concentration, the extent of delignification decreased, while delignification was seen to level off with respect to NaOH concentration above 2% w/v.

A mechanistic explanation of these results on the basis of bubble dynamic simulations can be given as follows: although the intensity of transient cavitation decreases drastically with temperature, the intrinsic reactivity of OH⁻ increases, which compensates the effect; thus, delignification remains practically the same in the temperature range of 30 to 80 °C. A higher concentration of biomass causes scattering of the ultrasound waves; therefore, the intensity of convection in the system decreases. The strong convection generated by ultrasound and cavitation eliminates mass transfer in the system, making the biomass accessible to OH⁻ ions. This leads to leveling off of the delignification beyond a certain concentration of NaOH.

XRD analysis revealed a reduction in the crystallinity index of the biomass after delignification, which is attributed to the depolymerization of cellulose with ultrasound by the scission of β-1-4 glycosidic bonds. FTIR spectra of the delignified biomass revealed a reduction in the intensities of all bonds corresponding to lignin removal, as well as rupture of the cellulose bonds and carbohydrate–lignin linkages. Moreover, the band intensities corresponding to aromatic ring stretching and the cellulose band also decreased. The changes in the XRD and FTIR spectra of the biomass after delignification are essentially manifestations of the physical and chemical effects of cavitation. The reduction in the aromatic ring stretching and aromatic ring vibration bands along with the reduction in the bands corresponding to side chain removal are attributed to reactions induced by ˙OH radicals from transient cavitation. Transient cavitation also generates high pressure amplitude shock waves. The biomass particles drift randomly in these waves at high velocities, leading to collisions between them. The energy released in such collisions is sufficient to cause hemolytic cleavage of the phenyl ester β-1-4 and α-1-4 bonds, leading to the depolymerization of lignin. The FESEM micrographs depicted in Fig. 2 reveal higher surface roughness for biomass delignified with sonication (as a result of erosion or attrition induced by strong microconvection) compared to the biomass treated with mechanical agitation. Thus, the study of Singh et al.⁵⁶ portrays a vivid picture of the mechanistic facets of ultrasonic delignification.

Fig. 2 FESEM micrographs of P. hysterophorus biomass (A) pretreated biomass, (B) delignified biomass with mechanical agitation, and (C) delignified biomass with ultrasound (Reproduced from Singh et al.⁵⁶ with permission of Elsevier BV).

4.2 Ultrasound assisted enzymatic hydrolysis

Bharadwaja et al.³² have performed a preliminary assessment of the effects of ultrasound on the enzymatic hydrolysis of delignified biomass. Two commercial enzymes, viz. cellulase and cellobiase, were employed for hydrolysis. Initially, statistical optimization of the enzymatic hydrolysis with mechanical shaking was carried out using central composite design (CCD) coupled with response surface method (RSM) analysis to optimize the parameters of the concentrations of the two enzymes and the biomass concentration. Later, under the optimum conditions of mechanical shaking, sonication was applied. However, the temperature of the reaction mixture was reduced to 30 °C for sonication (compared to 50 °C for mechanical shaking), as the intensity of transient bubble collapse and the associated physical/chemical effects decrease with temperature. The kinetics of enzymatic hydrolysis were found to increase 18-fold with ultrasound. Analysis of the experimental results with the Michaelis–Menten model and Lineweaver–Burk plots revealed that the values of V_max (reaction velocity) increased 18-fold, while the values of K_m (substrate affinity constant) remained constant when mechanical shaking was replaced with sonication. Bharadwaja et al.³² attributed this enhancement in the reaction velocity to enhancement of the convection in the medium, which eliminates mass transfer and increases the accessibility of the substrate for the enzyme. The enzyme–substrate affinity, however, is an intrinsic property which does not show any beneficial influence of ultrasound. The findings of Bharadwaja et al.³² gave preliminary insight into the influence of ultrasound on the enzymatic hydrolysis of biomass. The matter of ultrasound-assisted enzymatic hydrolysis was later examined in greater detail and rigor by Borah et al.,⁵⁸ whose findings are summarized later in this section. Bharadwaja et al.³² have developed a complete conceptual process for bioethanol production from P. hysterophorus, which includes all three steps of biomass pretreatment and the fermentation of both pentose and hexose hydrolyzates obtained from dilute acid pretreatment and enzymatic hydrolysis. The flow sheet for this conceptual process with complete mass balance is shown in Fig. 3. It can be inferred from Fig. 3 that the total bioethanol yield from P. hysterophorus is 256 g kg⁻¹ of raw biomass.

Fig. 3 Conceptual process for bioethanol production from P. hysterophorus: Flow sheet with complete mass balance (reproduced from Bharadwaja et al.³² with permission of Elsevier BV).

Singh et al.⁵⁹ have investigated the mechanics of ultrasound assisted enzymatic hydrolysis of pretreated and delignified biomass of Parthenium hysterophorus. This study comprised two parts, viz., (1) optimization of the enzymatic hydrolysis by mechanical agitation using statistical design of experiments, and (2) intensification of enzymatic hydrolysis with ultrasound under the optimized conditions. The experimental results were fitted to the first-order product-inhibited HCH-1 model for the enzymatic hydrolysis of cellulose.^60,61 The reaction mechanism for this model is shown in Fig. 4A, while the schematic of the mechanism of ultrasound-assisted enzymatic biomass hydrolysis is depicted in Fig. 4B. A brief description of this model is as follows.⁵⁹ This model hypothesizes that the first step in the enzymatic hydrolysis of cellulose is the adsorption of free enzyme, E^f, onto a free cellulose site, G^f_x. This adsorption is reversible. Combination of the active site of the adsorbed enzyme with the cellulose site yields the enzyme/substrate complex, characterized by the equilibrium constant, 1/η. Irreversible decomposition of the enzyme/substrate complex yields the solute product, G_s. The rate constant of the hydrolysis step is given by k. The HCH-1 model also hypothesizes that the enzyme in all forms (free, adsorbed and complex) can be inhibited by the product (glucose), which is characterized by the product binding constant, β. The net reaction velocity is given as:

where and factor ϕ signifies the extent of enzyme adsorption onto cellulose, given as:

Fig. 4 (A). Reaction mechanism for the HCH-1 model (reproduced from Singh et al.⁵⁹ with permission of Elsevier BV). (Notation: G^f_x – free cellulose, G_x – cellulose site, G_s – soluble product, E^f – free enzyme, E^a – enzyme adsorbed on cellulose, EG_x – enzyme substrate complex, G_sE^f – inhibited free enzyme, G_sE^a – inhibited adsorbed enzyme, G_sEG_x – inhibited complexed enzyme, η – complexing constant, β – product binding constant, δ – adsorption constant, k – reaction rate constant), (B). Schematic of ultrasound-assisted enzymatic biomass hydrolysis (reproduced from Singh et al.⁵⁹ with permission of Elsevier BV).

The four parameters, viz. α, β, ε and κ, in the expression for reaction velocity characterize the kinetics and physiology of the enzymatic hydrolysis process. Singh et al.⁵⁹ have matched the numerical solution of the ordinary differential equation for reaction velocity with the experimental profile of the total reducing sugar using a genetic algorithm. This match essentially yields the optimum values of the four parameters listed above, which gives physical insight into ultrasound assisted enzymatic hydrolysis. The major findings and conclusions of Singh et al.⁵⁹ are summarized below:

(1) The results of the Lineweaver–Burk analysis, i.e. the values of the Michaelis–Menten model parameters K_m and V_max, revealed that sonication not only increases the enzymatic/substrate affinity (indicated by the reduction in K_m) but also enhances the conversion of the enzyme/substrate complex into products, as indicated by the increase in the reaction velocity, V_max. The reduction in K_m is attributed to enhanced convection and mass transfer, resulting in greater interaction of the enzyme and substrate. This is essentially a consequence of the micro-turbulence and intense micro-mixing generated by ultrasound and cavitation in the reaction mixture. The increase in V_max (due to faster splitting of the enzyme–substrate complex and the diffusion of solute products into the bulk) is also attributed to enhanced convection due to ultrasound/cavitation.

(2) As noted earlier, matching of the experimental and simulated time profiles of the total reducing sugar yield in enzymatic hydrolysis through genetic algorithm optimization yields the values of the kinetic/physiological parameters of the HCH-1 model, which are listed in Table 4. Comparative evaluation of the parameters of the HCH-1 model under the control (mechanical agitation) and test (sonication) conditions reveals the following trends, which demonstrate the effects of sonication on enzymatic hydrolysis: (1) increase in the lumped kinetic constant (κ) of hydrolysis; (2) decrease in the lumped constant of enzyme/substrate complexion (α); (3) decrease in the product binding constant (β), which is indicative of the level of product inhibition; and (4) no change in the extent of enzyme adsorption on the cellulose sites. A physical explanation for these results can be given as follows: the enhancements in κ and α can be explained along the same lines as the trends in the Lineweaver–Burk parameters (K_m and V_max) stated previously. The decrease in the product binding constant is essentially an outcome of the faster transport of the product of enzyme hydrolysis (i.e. glucose) away from the biomass and further dilution in the reaction mixture due to intense micro-mixing. Rapid transport of glucose away from the cellulose surface and dilution in the medium reduces the probability that the product will bind to the active sites of the enzyme, which would result in inhibition. The similar values of ϕ in the control and test experiments indicate that mass transfer is not a limiting factor for enzyme adsorption on cellulose. The net effect of the variations in κ, α and β with sonication is a 4-fold increase in the kinetics of enzyme hydrolysis with sonication, although the net sugar yield shows only a marginal improvement of ∼20%. Singh et al.⁵⁹ have hypothesized that ultrasound-induced enhancement of the kinetics of enzyme hydrolysis could be a consequence of “unfolding” of the proteins of the enzymes, cellulase and β-glucosidase. Intense mass turbulence generated by ultrasound and cavitation could induce conformational changes in the secondary structures of the enzymes, which results in exposure of the inner hydrophobic amino acid residues and increases the activity of the enzyme. This hypothesis has later been confirmed by Borah et al.,⁵⁸ as will be explained in detail later in this section.

Table 4 Kinetic/physiological parameters of the HCH-1 model for enzymatic hydrolysis of Parthenium hysterophorous (reproduced from Singh et al.⁵⁹ with permission of Elsevier BV)

(A) Lineweaver–Burk analysis (enzyme kinetic parameters)
Experiment	Km (g L^−1)	Vmax (mM min^−1)
Control (mechanical agitation)	42.77	0.046
Test (with ultrasound)	24.44	0.055
(B) Analysis with HCH-1 model with GA optimization
Parameter	Control experiment (mechanical agitation)	Test experiment (with ultrasound)
Lumped kinetic constant of enzymatic hydrolysis, κ (h^−1)	0.31	1.22
Lumped constant for enzyme/substrate complexation, α (g L^−1)	0.49	0.19
Product binding constant, β (L g^−1)	1.01	0.76
Number of cellulose sites covered by adsorbed or complexed enzyme, ϕ	0.17	0.19
Best fitness value for the model parameters	5.71	4.3

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Borah et al.⁵⁸ have investigated the ultrasound-induced enhancement of the enzymatic hydrolysis of invasive biomass species. Pretreated and delignified biomasses of four invasive weeds, viz. S. spontaneum, M. micrantha, L. camara and E. crasspies, were subjected to enzymatic hydrolysis under mechanical agitation or mechanical agitation coupled with sonication. The study of Borah et al.⁵⁸ also included assessment of the morphological changes in the secondary and ternary structures of the cellulase and cellobiase enzymes, induced by the physical/chemical effects of ultrasound/cavitation. This assessment has been performed using intrinsic fluorescence and circular dichroism analysis. The circular dichroism spectra of the native and ultrasound treated cellulase and cellobiase enzymes were analyzed using the DICHROWEB server.^62–64

The intrinsic fluorescence spectra and circular dichroism spectra of the cellulose and cellobiase enzymes are shown in Fig. 5 and 6, respectively. Mainly, three amino acid residues (viz. Trp, Tyr and Phe) contribute to the intrinsic fluorescence of the enzymes. Fig. 5 shows the Trp fluorescence spectra for the individual cellulase and cellobiase enzymes and also for their mixtures, with a maximum fluorescence emission wavelength at 348 nm. Although enzymatic treatment with mechanical agitation and sonication causes a reduction in the fluorescence intensity, this effect is more marked for sonication. The fluorescence spectra do not show any red or blue shifts in the optimum fluorescence emission wavelength, which is a consequence of the rupture of the hydrophobic interactions between protein molecules, leading to molecular unfolding of the proteins. This is attributed to the intense micro-convection generated by ultrasound and cavitation. These conformational changes cause exposure of hydrophobic amino-acid groups and structures inside the enzyme molecules, which results in augmentation of the enzyme activity. The structural analysis of the CD spectra of cellulase and cellobiase enzymes and their mixtures (shown in Fig. 6) further corroborates the fluorescence spectroscopy results. The percentage contents of the secondary structure components of the enzymes are depicted in Table 5. The data shown in Table 5 clearly show a reduction in the α-helix conformation content of the enzymes, with increases in the β-sheet and random coil structures. The decrease in the α-helix content of both enzymes is more marked for ultrasound treatment than mechanical agitation. These conformational changes help augment the activities of both the cellulase and cellobiase enzymes. As per the analyses of Davies and Henrissat⁶⁵ and Rouvinen et al.,⁶⁶ the active sites of cellulase and cellobiase enzymes are located in the β-barrel tunnels, and an increase in the β-sheet/β-turn components in the enzyme structures can increase the number of active sites, thus enhancing the enzyme activity. Moreover, a reduction in the α-helix components can also expose catalytic sites located inside said components; thus, the substrate can bind to the enzyme more easily, without requiring twisted and linear confirmations. These effects can also result in an augmentation of the catalytic efficiency of the enzyme.

Fig. 5 Intrinsic fluorescence spectra of hydrolysis enzymes in various forms (native enzyme and post-treatment with mechanical shaking and sonication at atmospheric or 101.3 kPa pressure). (A) Spectra of cellulase enzyme; (B) spectra of cellobiase enzyme; (C) spectra of mixture of cellulase and cellobiase enzymes (reproduced from Borah et al.⁵⁸ with permission of Elsevier BV).

Fig. 6 Circular dichroism spectra of hydrolysis enzymes in various forms (native enzyme and post-treatment with mechanical shaking and sonication at atmospheric or 101.3 kPa pressure). (A) Spectra of cellulase enzyme; (B) spectra of cellobiase enzyme; (C) spectra of mixture of cellulase and cellobiase enzymes (reproduced from Borah et al.⁵⁸ with permission of Elsevier BV).

Table 5 Composition of the secondary structure of native and ultrasound treated enzymes for biomass hydrolysis (reproduced from Borah et al.⁵⁸ with permission of Elsevier BV)

Form of cellulase enzyme	α-Helix (%)	β-Sheet (%)	β-Turn (%)	Random coil (%)
Results for cellulase enzyme
1. Native enzyme	32.7	13.20	23.1	30.8
2. Enzyme treated with mechanical shaking	30.67	25.24	18.54	25.53
3. Enzyme treated with sonication (at atmospheric conditions)	19.10	29.75	18.40	32.73
Results for cellobiase enzyme
1. Native enzyme	11.68	44.46	10.23	33.71
2. Enzyme treated with mechanical shaking	9.84	45.5	10.76	33.5
3. Enzyme treated with sonication (at atmospheric conditions)	9.85	45.6	10.77	33.7
Results for mixture of cellulose and cellobiase enzymes
1. Native enzyme	33.04	11.46	23.89	31.69
2. Enzyme treated with mechanical shaking	32.88	11.63	23.84	31.73
3. Enzyme treated with sonication (at atmospheric conditions)	32.08	11.87	24.04	31.99

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Borah et al.⁵⁸ have fitted the experimental profiles of the reducing sugar concentration during enzymatic hydrolysis of invasive weeds under the control (mechanical agitation) and test (sonication) conditions to the HCH-1 model described earlier. Table 6 depicts the principal results of the study of Borah et al.⁵⁸ Sonication enhanced the kinetics of the enzymatic hydrolysis by more than 10-fold; very similar TRS yields were obtained with sonication after 10 h treatment and after 120 h treatment with mechanical agitation. The parameters of the HCH-1 model, viz. κ, α, β and ε, for the control (mechanical agitation) and test (sonication) conditions shows the following trend, which reveals the mechanism of the effect of sonication on enzymatic hydrolysis: (1) enhancement of the lumped kinetic constant (κ) of hydrolysis; (2) reduction in the lumped constant for enzyme/substrate complexation (α); (3) reduction in the product binding constant (β); and (4) similar values of ε under the test (sonication) and control (mechanical agitation) conditions. These trends are quite similar to those observed in the study of Singh et al.⁵⁹ for the enzymatic hydrolysis of Parthenium hysterophorus. A similar explanation for these trends can be given to that in the study of Singh et al.:⁵⁹ the enhancement in κ with a concurrent reduction in α is attributed to micro-turbulence and intense micro-mixing generated by ultrasound/cavitation in the reaction mixture, which promotes faster transport and enhanced interaction of the enzyme with the substrate. Intense micro-convection also aids faster diffusion of the soluble product away from the cellulose surface and its dilution in the medium. This reduces the extent of product inhibition by the enzyme, as indicated by the reduction in β. The intense micro-turbulence also assists faster splitting of the enzyme–substrate complex, which results in enhanced reaction velocity, as indicated by the larger value of the lumped kinetic constant κ. The practically identical values of ε with mechanical agitation and sonication indicate that the enzyme adsorption on cellulose is not limited by mass transfer.

Table 6 Kinetic/physiological parameters of the HCH-1 model for enzymatic hydrolysis of invasive biomass species (reproduced from Borah et al.⁵⁸ with permission of Elsevier BV)^a

Biomass species	Control experiment (mechanical agitation)					Test experiment (under sonication)
	κ	α	β	ε	F-Best	κ	α	β	ε	F-Best
a Notation: κ – lumped kinetic constant of enzymatic hydrolysis (h^−1); α – lumped constant for enzyme–substrate complexation (g L^−1); β – product binding constant (L g^−1); ε – number of cellulose sites covered by adsorbed or complexed enzyme; F-best – best fitness value for the model parameters.
SS	0.51	0.31	0.21	0.10	4.60	1.98	0.26	0.12	0.11	6.10
LC	1.05	0.49	0.79	0.03	5.00	1.69	0.35	0.32	0.04	5.60
EC	1.01	0.34	0.56	0.14	4.60	1.85	0.25	0.25	0.15	4.76
MM	0.38	0.55	0.33	0.11	3.40	1.66	0.42	0.28	0.10	4.20

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A peculiar feature of the study of Borah et al.⁵⁸ was that the conditions of enzyme hydrolysis (such as pH, temperature, substrate concentration and enzyme concentration) were not optimized for the biomasses of each of the four invasive weeds. The enzyme hydrolysis was carried out under the same conditions as that for the hydrolysis of Parthenium hysterophorus (in the study of Singh et al.⁵⁶). Despite non-optimum conditions, the enhancement effect of sonication (in terms of a several-fold increase in the hydrolysis kinetics) was observed. This result essentially demonstrates that process intensification due to ultrasound/cavitation helps overcome the limitations of the non-optimum conditions during enzymatic hydrolysis. The study of Borah et al.⁵⁸ has thus provided a deeper mechanistic insight into the enhancement of enzymatic hydrolysis due to sonication.

4.3 Ultrasound assisted ethanol fermentation: separate hydrolysis and fermentation (SHF) mode

Singh et al.⁶⁷ have presented mechanistic investigations of ultrasound-assisted bioethanol fermentation using Parthenium hysterophorus biomass. Ultrasound of 35 kHz frequency and 1.5 bar pressure amplitude with a 10% duty cycle was employed. The protocol for the experiments was separate hydrolysis and fermentation (SHF). Both steps of the enzymatic hydrolysis and fermentation were carried out with sonication. The experimental profiles of the concentration of total reducing sugar, cell mass and ethanol during fermentation were fitted to the mathematical model proposed by Philippidis et al.,⁶⁸ which is based on the HCH-1 model of Holtzapple⁶⁰ and Holtzapple et al.⁶¹ The essential equations of this model are as follows:

Cell mass. Glucose is assumed to be the primary carbon source, which is metabolized into cell mass with concomitant synthesis of ethanol and CO₂. The microbial (or cell mass) growth as a function of glucose and ethanol concentration has been described using a Monod type kinetic expression, which includes non-competitive substrate inhibition and non-competitive product inhibition, as follows:

Glucose. The glucose in the fermentation broth is consumed through cell mass synthesis and cell maintenance requirements. The profile for glucose is given as:

Ethanol. Ethanol is formed through two mechanisms, viz. growth-associated and non-growth associated, and it is also a function of the glucose concentration in the medium as follows:

The set of three differential equations in the Philippidis model and the kinetic/physiological parameters therein characterize the fermentation process. The three equations for X, G and E have 10 total parameters, viz. K₃, K_i, K_3E, k_d, μ_m, a, b, Y_X/G, m and K₄. Fitting of this model to the experimental profiles of X, G and E yields the numerical values of the parameters in the model. Comparative analysis of the model parameters under the control (mechanical agitation) and test (sonication) conditions give physical insight into the influence of ultrasound/cavitation on the fermentation process.

The principal findings of the experimental and modeling studies of Singh et al.⁶⁷ were as follows: (1) compared to the control experiments (with mechanical agitation), the test experiments (with sonication) had 2-fold higher productivity. Moreover, the final ethanol and cell mass concentration attained with sonication was 10% higher than that attained with mechanical agitation. (2) The experimental and simulated profiles of cell mass, glucose and ethanol concentration were in good agreement, indicating the suitability of the Philippidis model. The model parameters showed the following trends under the test and control conditions:

(a) Reduction in the Monod constant for glucose for cell growth (K₃), which reveals higher utilization of the substrate for cell growth.

(b) Increase in the inhibition constant (K_i) for cell growth, which indicates a higher tolerance of the cells towards non-competitive substrate inhibition.

(c) Enhancement in the maximum specific growth rate, with concurrent reduction in the specific death rate under the test conditions.

(d) Similar values of K_3E for the test and control conditions, which reveals that the inhibition of the cell growth by product (ethanol) is unaltered with sonication.

These trends in the model parameters are essentially manifestations of the physical/chemical effects of ultrasound and cavitation. The reduction in the Monod constant for cell growth (which is the substrate concentration required to achieve half of the maximum specific growth rate of the biomass) essentially represents faster transport of glucose across the cell membrane, due to which a lower bulk concentration of glucose is required to achieve the maximum specific growth rate. Sonication also improved the utilization of glucose for cell growth, which is endorsed by the increase in the values of Y_X/G and μ_max. Faster transport and utilization of glucose also resulted in an increase in the inhibition constant, K_i, which indicates superior tolerance of the cells towards substrate inhibition. The concurrent decrease in K₃ and increase in K_i could be considered to be synergistic effects of sonication on fermentation. Similar values of K_3E (inhibition constant for product ethanol) for both the control and test experiments indicates that this is an intrinsic physiological property of the cells which does not depend on the ambience (or environment) of the cells. Ethanol is essentially a growth associated product (associated with energy generation by microorganisms). Nevertheless, the non-zero value for the constant b in eqn (7) indicated that ethanol fermentation also occurred during the stationary phase; this is non-growth associated production. Moreover, similar values of constants a and b for the control and test experiments show that these are also intrinsic properties which do not depend on the ambience of the cell.

The values of k_d (specific cell death rate) and m (specific substrate consumption rate for cell maintenance) also decreased under sonication. Cellular maintenance represents the energy expenditure for the repair of damaged cellular components and the transfer of nutrients and products across the cell membrane. It also includes the energy required for motility and for adjustment of the osmolality of the interior volume of the cells. The intense micro-mixing and micro-convection generated by ultrasound waves assists cell motility, de-agglomeration of the cells and trans-membrane transport, which aids the regulation of osmolality. This implies a reduction in the dependence of the cells on the substrate for the maintenance and utilization of a large fraction of glucose ethanol production. Depletion of nutrients and accumulation of toxic products is the principal cause leading to the death phase of cells. The intense micro-turbulence generated by ultrasound/cavitation results in efficient transfer of nutrients across cells. Moreover, it also assists the transport of toxic substances away from the cells by diluting them in the medium. Both of these effects lead to enhancement of the growth phase with simultaneous reduction in the cell death rate. The similar values of K_3E in the test and control experiments can be explained as follows: Thomas and Rose⁶⁹ and Leao and van Uden⁷⁰ have attributed the inhibition of cell growth to a reduction in the fluidity of the plasma membrane due to the inhibitory effect of ethanol on the action of proteins involved in the transport of compounds in the cells. Secondly, the modification of lipid content in the environment of the sugar transport system by ethanol also has a major effect on the membrane permeability. These mechanisms are mainly intrinsic and remain unaffected by the physical effects of microturbulence/microconvection induced by ultrasound/cavitation. Thus, the values of K_3E for the test and control experiments are similar.

Singh et al.⁶⁷ have also assessed the effects of sonication on the morphology and viability of yeast cells using flow cytometric analysis. No changes in SSC and FSC were observed after sonication of the microbial cells, which indicated that the internal complexity and morphology of the yeast cells remained intact during sonication, with no adverse effects.

4.4 Ultrasound assisted ethanol fermentation: simultaneous saccharification and fermentation (SSF) mode

In another study, Singh et al.⁷¹ explored the physical mechanism of the influence of ultrasound on the fermentation of a pretreated and delignified biomass of Parthenium hysterophorus for ethanol production in the SSF (simultaneous saccharification and fermentation) mode. The fermentation model of Philippidis et al.⁶⁸ described earlier was used for fitting of the experimental results. However, due to experimental limitations for the estimation of the profiles of cellulose and the intermediate, dimeric cellobiose, only the equations for cell mass and ethanol concentration in the Philippidis model were used to fit the experimental data. These equations had a total of 7 parameters, viz. K₃, K_i, K_3E, k_d, μ_m, a and b; these values were obtained after matching the experimental and simulated profiles using a genetic algorithm. These results have been correlated with the simulations of cavitation bubble dynamics using the diffusion limited model of Toegel.⁷² Table 7 depicts the kinetic and physiological parameters in the fermentation model, while Table 8 depicts the summary of the cavitation bubble dynamics simulations, i.e. the physical and chemical effects of transient cavitation. The main results and analysis of Singh et al.⁷¹ are summarized below:

Table 7 Kinetic and physiological parameters for simultaneous saccharification and fermentation (SSF) of Parthenium hysterophorous (reproduced from Singh et al.⁷¹ with permission of Elsevier BV)

Parameter	Control experiments	Test experiments
Monod constant for cell growth, K3 (g L^−1)	25.01	20.02
Inhibition constant of cell growth by glucose, Ki (g L^−1)	50.06	60.02
Inhibition constant of cell growth by ethanol, K3E (g L^−1)	30.03	30.01
Specific cell death rate, kd (h^−1)	0.12	0.09
Maximal specific growth rate, μm (h^−1)	0.48	0.61
Constant for growth associated ethanol formation, a (g g^−1)	2.98	2.99
Non-growth associated specific ethanol production rate, b (g g^−1 h^−1)	1.99	1.99

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Table 8 Summary of simulations of cavitation bubble dynamics (reproduced from Singh et al.⁷¹ with permission of Elsevier BV)^a,b

a Conditions for simulations: ultrasound frequency = 35 kHz; ultrasound pressure amplitude = 150 kPa; equilibrium bubble radius = 5 and 10 μm; vapor pressure of water (in bar) is calculated using Antoine type correlation: Properties of water: density = 1000 kg m^−3, kinematic viscosity = 10^−6 Pa s, surface tension = 0.072 N m^−1 and sonic velocity = 1481 m s^−1.b Notation: Ro – initial radius of the cavitation bubble; Vturb – average velocity of the micro-turbulence in the medium generated by cavitation bubbles in the medium (estimated at 1 mm distance from the bubble center); PAW – pressure amplitude of the acoustic wave generated by the cavitation bubble (estimated at 1 mm distance from the bubble center); Tmax – temperature peak reached in the bubble at the time of first collapse; Pmax – pressure peak reached in the bubble at the time of first collapse.
Parameters for simulations
Water
Air bubble	Air bubble
Ro = 5 μm	Ro = 10 μm
Conditions at the first collapse of the bubble
Tmax = 3258 K	Tmax = 2304 K
Pmax = 384 MPa	Pmax = 88.4 MPa
Vturb = 0.03 mm s^−1	Vturb = 0.05 mm s^−1
PAW = 72 kPa	PAW = 31.6 kPa

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Species	Equilibrium composition of the bubble at transient collapse
N2	7.1952 × 10^−1	7.0137 × 10^−1
O2	1.6608 × 10^−1	1.8081 × 10^−1
O	1.6723 × 10^−3	7.2220 × 10^−5
O3	6.4788 × 10^−6	—
H	7.1808 × 10^−5	1.3605 × 10^−6
H2	1.8629 × 10^−4	1.6934 × 10^−5
NO	5.6173 × 10^−2	1.4597 × 10^−2
NO2	1.3272 × 10^−3	4.1249 × 10^−4
N2O	1.7158 × 10^−4	2.0512 × 10^−5
OH	7.3692 × 10^−3	1.3447 × 10^−3
H2O	4.6767 × 10^−2	1.0124 × 10^−1
HO2	4.3753 × 10^−4	7.0556 × 10^−5
H2O2	2.6760 × 10^−5	5.7095 × 10^−6
HNO	2.2534 × 10^−5	—
HNO2	1.646 × 10^−4	3.6992 × 10^−5

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(1) The most notable effect of sonication on the SSF process was a 3-fold reduction in the time of fermentation. Marked 4-fold increases in the productivities of ethanol and cell mass concentration were achieved with sonication compared to mechanical agitation. The final ethanol titre was 15.62 g L⁻¹, with a yield of 0.4 g ethanol per g pretreated biomass or 0.21 g ethanol per g raw biomass.

(2) Comparative analysis of the physiological parameters of the fermentation model under the control (mechanical agitation) and test (sonication) conditions revealed the following mechanistic account of the influence of ultrasound/cavitation on the SSF process, which is significantly similar to the SHF process: (a) decrease in K₃, the Monod constant for glucose for cell growth. (b) Increase in the maximal specific growth rate (μ_m) and decrease in the specific cell death rate. (c) Increase in K_i, the inhibition constant of cell growth by glucose, indicating increased tolerance of cells towards non-competitive inhibition by the substrate. Similar to the SHF process, the concurrent reduction in K₃ and K_i is a synergistic effect attributed to faster transport and utilization of glucose due to intense mixing generated by ultrasound/cavitation. (d) Similar values of K_3E (inhibition constant of cell growth by ethanol) in the control and test experiments, indicating the sole dependence of this property on the physiology of the cells and not on their environment. (e) As stated earlier, ethanol production by cells is a growth-associated process and is related to energy generation by microorganisms. However, the parameter b in eqn (13) has a non-zero value of 1.99 g g⁻¹ h⁻¹, which implies that ethanol production also occurs in the stationary phase of the cell life cycle. However, the larger numerical value for parameter a than for parameter b signifies that ethanol production is predominantly a growth-associated process.

Similar to the SHF process of fermentation, an explanation for these results can be given as follows: there are two causes leading to cell growth inhibition by ethanol, viz. (1) inhibition of enzymes involved in the glycolytic pathway, and (2) effects on fluidity, transport mechanism or enzymes associated with membranes (as noted earlier). As these properties are mostly intrinsic, they are not affected by the physical or chemical effects of ultrasound/cavitation. Another peculiar feature of the study of Singh et al.⁷¹ is that despite the use of low activity cellulase enzymes (for hydrolysis of cellulose) from natural isolates, the net productivity and yield of ethanol was at par with studies using commercial enzymes. This result is also attributed to the enhancement effect induced by microconvection generated by ultrasound/cavitation, due to which the activities of cruder enzymes are improved.

A comparative analysis of the two studies by Singh et al.^67,71 employing SHF and SSF protocols gives interesting accounts of the links between the physical effects of sonication and the mode of fermentation. The higher values of maximum ethanol concentration in ultrasound-assisted fermentation in SSF mode (compared to SHF mode) are attributed to acceleration of the fermentation as well as enzymatic hydrolysis under the influence of ultrasound. However, the ethanol productivity in SHF mode is higher than in SSF mode. This could lead to a misinterpretation that the SHF process is more efficient than SSF. However, it should be noted that the productivity in the SHF protocol has been determined only for the fermentation period (which does not include the time for enzymatic hydrolysis). The cell mass concentrations in SHF and SSF modes show an inverse trend in that SSF mode results in higher cell concentration. An explanation for this result is as follows: intense micro-convection due to ultrasound/cavitation in the SSF protocol causes significant augmentation of the rate of enzymatic hydrolysis. This can significantly enhance the instantaneous levels of sugar concentration in the fermentation broth; these levels are even higher than those achieved in SHF mode, which leads to higher cell mass production. Fermentation in the SHF protocol starts with the highest concentration of reducing sugar, which continuously decreases with time. On the other hand, in the SSF protocol, the enzymatic hydrolysis of solid cellulose occurs simultaneously with fermentation, which results in continuous generation of reducing sugar in the broth. Therefore, the time-averaged concentration of reducing sugar in the broth in the SSF protocol is likely to be higher than in the SHF protocol, which is manifested in terms of larger cell mass concentration. Comparing the cell mass concentration under control conditions (mechanical agitation) in the SHF and SSF protocols, an opposite trend is seen in that the SSF protocol yields a lower cell mass. This is attributed to the slower kinetics of the enzymatic hydrolysis using mechanical agitation, due to which the time-averaged sugar concentration in the fermentation broth is expected to be lower than that obtained by the SHF protocol.

5. Overview and conclusions

Bioalcohols have emerged as potential renewable alternate liquid transportation fuels. However, the large scale production of bioalcohols has been hampered by factors such as the high cost of conventional substrates and the slow kinetics of enzymatic hydrolysis and fermentation. The use of inexpensive substrates such as lignocellulosic biomass is a viable solution; however, the energy intensive step of biomass pretreatment adds to the production cost. New technologies employing smart ways of introducing energy into the system can improve the kinetics/yield of the bioalcohol production process, which can enhance its economy. Sonication (or ultrasound irradiation) is one such technology. Laboratory scale studies on ultrasound-assisted biomass pretreatment, enzymatic hydrolysis and fermentation have given encouraging results. In order to successfully scale up ultrasound-assisted bioalcohol processes, knowledge of the physical mechanism of the process, linking the physics/chemistry of the process and the physical/chemical effects of ultrasound and cavitation, is necessary. In this review, we have attempted to present a critical analysis of the literature in the area of ultrasound assisted biomass pretreatment and fermentation. This review also includes a critical analysis of the literature that has investigated the mechanistic issues of ultrasound assisted processes. This analysis of the published literature results essentially indicates that the physical effects of ultrasound and cavitation are beneficial for the intensification of various steps in the bioalcohol production process. Intense microconvection and microturbulence generated by ultrasound and cavitation enhance the transport characteristics of the biomass pretreatment and fermentation systems. Microconvection also assists in enhancing the activity of the enzymes and microbial cells, which boosts the yield/kinetics of enzymatic hydrolysis and fermentation. Microconvection also aids the reduction of substrate/product inhibition and speeds the growth of the microbial culture itself.

To summarize: ultrasound-assisted bioalcohol production (including biomass pretreatment and fermentation) has high potential for commercialization but also has highly interwoven physics and chemistry. Proper investigations from a mechanistic viewpoint are crucially important for efficient optimization and scale up of the process. This review is likely to be a useful source of literature in the area of ultrasound-assisted biomass pretreatment, enzymatic hydrolysis and fermentation, and its critical mechanistic analysis for the scientific fraternity in bioalcohol synthesis.

Acknowledgements

The authors gratefully acknowledge the anonymous reviewers for their meticulous assessment of the manuscript and constructive criticism.

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Footnotes

† Electronic supplementary information (ESI) available: Section entitled Physics of ultrasound and cavitation: a brief overview, along with two tables, viz. Table S1: essential equations (ODE's) of the diffusion-limited ODE model, and Table S2: thermodynamic data for the diffusion limited model. See DOI: 10.1039/c6ra11580b

‡ Equal contribution by these authors.

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