The status of the U.S. commercial lignocellulosic ethanol facilities.
\r\n\t
",isbn:"978-1-83881-922-4",printIsbn:"978-1-83881-921-7",pdfIsbn:"978-1-83881-923-1",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"dcfc52d92f694b0848977a3c11c13d00",bookSignature:"Dr. Fiaz Ahmad and Prof. Muhammad Sultan",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10454.jpg",keywords:"Agricultural Engineering, Technologies, Application, Sustainable Agriculture, Information Technology in Agriculture, Food Security, Renewable Energies, Precision Farming, Smart Agriculture, Farm Mechanization, Robotics, Post Harvest Technologies",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"November 25th 2020",dateEndSecondStepPublish:"December 23rd 2020",dateEndThirdStepPublish:"February 21st 2021",dateEndFourthStepPublish:"May 12th 2021",dateEndFifthStepPublish:"July 11th 2021",remainingDaysToSecondStep:"2 months",secondStepPassed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"Dr. Ahmad is a researcher in the field of agricultural mechanization and agricultural equipment engineering, in-charge of Farm Machinery Design Laboratory at Bahauddin Zakariya University, with expertise in modeling and simulation. He applied for two patents at the national level.",coeditorOneBiosketch:"Renowned researcher with a focus on developing energy-efficient heat- and/or water-driven temperature and humidity control systems for agricultural storage, greenhouse, agricultural livestock and poultry applications including HVAC, desiccant air-conditioning, adsorption, Maisotsenko cycle (M-cycle), and adsorption desalination.",coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"338219",title:"Dr.",name:"Fiaz",middleName:null,surname:"Ahmad",slug:"fiaz-ahmad",fullName:"Fiaz Ahmad",profilePictureURL:"https://mts.intechopen.com/storage/users/338219/images/system/338219.jpg",biography:"Fiaz Ahmad obtained his Ph.D. (2015) from Nanjing Agriculture University China in the field of Agricultural Bioenvironmental and Energy Engineering and Postdoc (2020) from Jiangsu University China in the field of Plant protection Engineering. He got the Higher Education Commission, Pakistan Scholarship for Ph.D. studies, and Post-Doctoral Fellowship from Jiangsu Government, China. During postdoctoral studies, he worked on the application of unmanned aerial vehicle sprayers for agrochemical applications to control pests and weeds. He passed the B.S. and M.S. degrees in agricultural engineering from the University of Agriculture Faisalabad, Pakistan in 2007. From 2007 to 2008, he was a Lecturer in the Department of Agricultural Engineering, Bahauddin Zakariya University, Multan-Pakistan. Since 2009, he has been an Assistant Professor in the Department of Agricultural Engineering, BZ University Multan, Pakistan. He is the author of 33 journal articles. He also supervised 6 master students and is currently supervising 5 master and 2 Ph.D. students. In addition, Dr. Ahmad completed three university-funded projects. His research interests include the design of agricultural machinery, artificial intelligence, and plant protection environment.",institutionString:"Bahauddin Zakariya University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Bahauddin Zakariya University",institutionURL:null,country:{name:"Pakistan"}}}],coeditorOne:{id:"199381",title:"Prof.",name:"Muhammad",middleName:null,surname:"Sultan",slug:"muhammad-sultan",fullName:"Muhammad Sultan",profilePictureURL:"https://mts.intechopen.com/storage/users/199381/images/system/199381.jpeg",biography:"Muhammad Sultan completed his Ph.D. (2015) and Postdoc (2017) from Kyushu University (Japan) in the field of Energy and Environmental Engineering. He was an awardee of MEXT and JASSO fellowships (from the Japanese Government) during Ph.D. and Postdoc studies, respectively. In 2019, he did Postdoc as a Canadian Queen Elizabeth Advanced Scholar at Simon Fraser University (Canada) in the field of Mechatronic Systems Engineering. He received his Master\\'s in Environmental Engineering (2010) and Bachelor in Agricultural Engineering (2008) with distinctions, from the University of Agriculture, Faisalabad. He worked for Kyushu University International Institute for Carbon-Neutral Energy Research (WPI-I2CNER) for two years. Currently, he is working as an Assistant Professor at the Department of Agricultural Engineering, Bahauddin Zakariya University (Pakistan). He has supervised 10+ M.Eng./Ph.D. students so far and 10+ M.Eng./Ph.D. students are currently working under his supervision. He has published more than 70+ journal articles, 70+ conference articles, and a few magazine articles, with the addition of 2 book chapters and 2 edited/co-edited books. Dr. Sultan is serving as a Leading Guest Editor of a special issue in the Sustainability (MDPI) journal (IF 2.58). In addition, he is appointed as a Regional Editor for the Evergreen Journal of Kyushu University. His research is focused on developing energy-efficient heat- and/or water-driven temperature and humidity control systems for agricultural storage, greenhouse, livestock, and poultry applications. His research keywords include HVAC, desiccant air-conditioning, evaporative cooling, adsorption cooling, energy recovery ventilator, adsorption heat pump, Maisotsenko cycle (M-cycle), wastewater, energy recovery ventilators; adsorption desalination; and agricultural, poultry and livestock applications.",institutionString:"Bahauddin Zakariya University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Bahauddin Zakariya University",institutionURL:null,country:{name:"Pakistan"}}},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"8",title:"Chemistry",slug:"chemistry"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"252211",firstName:"Sara",lastName:"Debeuc",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/252211/images/7239_n.png",email:"sara.d@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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Multiple independently produced datasets confirm that between 1880 and 2012, the global average land and ocean surface temperature increased by 0.85 [0.65–1.06]°C [1]. Since 1979 the rate of warming has approximately doubled (0.13°C/decade, against 0.07°C/decade) [2, 3]. The scientific consensus as of 2013 stated in the intergovernmental panel on climate change (IPCC) Fifth Assessment Report is that it “is extremely likely that human influence has been the dominant cause of the observed warming since the mid-20th century.” In 2018 the IPCC published a Special Report on Global Warming of 1.5°C which warned that, if the current rate of greenhouse gas (GHG) emissions is not mitigated, global warming is likely to reach 1.5°C between 2030 and 2052 causing major crises. The report said that preventing such crises will require a swift transformation of the global economy that has “no documented historic precedent” [4].
\nA mandate required developed countries to take the lead in reducing their emissions and was sustained in the Kyoto Protocol to the United Nations Framework Convention on Climate Change (UNFCCC), which entered into legal effect in 2005. In ratifying the Kyoto Protocol, most developed countries accepted legally binding commitments to limit their emissions. Biofuel mandates are set in more than 60 nations and incentives are provided by the governments to boost bioethanol production [5].
\nIn the U.S., production, transportation and fermentation of the corn was adapted quickly by industry for fuel ethanol production, primarily because corn was the only crop that had the existing infrastructure to easily modify for this purpose, especially when initially incentivized with tax credits, subsidies and import tariffs. Figure 1 shows total U.S. corn use from 1986 to 2018. The amount of corn used for ethanol production increased substantially between 2001 and 2010, as nearly all gasoline was transitioned to 10% ethanol. From 2013, the trend remains consistent with production and usage remaining relatively constant.
\nThe U.S. corn for fuel ethanol, feed, and other use. Source: the United States Department of Agriculture Economic Research Service Feed Grain Yearbook.
There is still some debate on whether biofuel production from food feedstock can truly reduce GHG emissions. The United Nations Intergovernmental Panel on Climate Change released two of its Working Group reports state that “Biofuels have direct, fuel-cycle GHG emissions that are typically 30–90% lower than those for gasoline or diesel fuels. However, since for some biofuels indirect emissions—including from land use change—can lead to greater total emissions than when using petroleum products, policy support needs to be considered on a case by case basis” (IPCC 2014 Chapter 8). The report lists many potential negative risks of ethanol production from food feedstock, such as direct conflicts between land for fuels and land for food, other land-use changes, water scarcity, loss of biodiversity and nitrogen pollution through the excessive use of fertilizers.
\nAlso, the potential of using bioethanol from food feedstock to replace petroleum fuels is limited. The United States will use over 130 billion gallons of gasoline in 2014, and over 50 billion gallons of diesel. On average, one bushel of corn can be used to produce just 2.8 gallons of ethanol. If all of the production of corn in the U.S. were converted into ethanol, it would only displace 25% of that 130 billion.
\nOn the other hand, there is less controversy over GHG reduction from production of lignocellulosic ethanol production as cellulosic materials are mostly the wastes of the agriculture and forest industry. The shift from food crop feedstocks to waste residues and native grasses offers significant opportunities for a range of players, from farmers to biotechnology firms, and from project developers to investors [6]. However, the process to convert lignocellulosic materials to ethanol is much more complex than that used to covert starch and sugars into ethanol.
\nCellulosic ethanol industry is still in its infancy. In the U.S., as of 2013, the first commercial-scale plants to produce cellulosic biofuels have begun operating. In the following 5 years, cellulosic ethanol production grown from 0 to 10 million gallons [7], and most likely topping 15 million in 2018. However, that is far from the Renewable Fuel Standard’s original target of 7 billion gallons of cellulosic biofuel by 2018 and 16 billion by 2022. Of all five commercial cellulosic ethanol plants that were built/to be built in the U.S. from 2010 to 2016, only POET’s Emmetsburg, Iowa facility is still in operation in 2019 (Table 1). In 2017, the total cellulosic ethanol produced was less than half the nameplate capacity (25 million gallons year−1) of this single plant [13].
\nCompany | \nLocation | \nFeedstock | \nCapacity (mg year−1) | \nStatus | \n
---|---|---|---|---|
Abengoa Bioenergy | \nHugoton, KS | \nWheat straw | \n25–30 | \n2013–2016 Bankrupt [8] | \n
BlueFire Ethanol | \nFulton, MS | \nMultiple sources 19 | \n20 | \nConstruction halted 2011 [9] | \n
DuPont | \nNevada, Iowa | \n\n | 30 | \nSold to Verbio in Nov. 2018 [10] | \n
Mascoma | \nKinross, MI | \nWood waste | \n20 | \nConstruction halted in 2013 [11] | \n
POET LLC | \nEmmetsburg, IA | \nCorn stover | \n20–25 | \nOperational in Sep. 2014 [12] | \n
The status of the U.S. commercial lignocellulosic ethanol facilities.
The future of bioethanol generation from lignocellulosic materials is not clear at this point of time. The sustainability of this renewable fuel business will depend on the success of development of cost-cutting technologies for every stage of lignocellulosic ethanol production.
\nFirst-generation biofuel includes biodiesel produced from vegetable oils through transesterification and bioethanol generated from food feedstock, mainly starchy materials (e.g., corn, wheat, barley, cassava, potato) and sucrose-containing feedstock (e.g., sugarcane, sugar beet, sweet sorghum) [14]. First-generation bioethanol is produced from fermentation of these starchy and sucrose-containing materials in four basic steps: enzymatic saccharification or hydrolysis of starch into sugars, microbial (yeast) fermentation of sugars, distillation, and dehydration.
\n\nFigure 2 shows global ethanol production by country or region, from 2007 to 2017. Together, the U.S. and Brazil produce 85% of the world’s ethanol. The vast majority of Brazil ethanol is produced from sugarcane.
\nGlobal ethanol production by country or region, from 2007 to 2017. Source: Renewable Fuels Association. Last updated October 2018.
The United States is the world’s leading producer of ethanol, with nearly 16 billion gallons in 2017 alone, mainly produced from corn. The annual U.S. production of ethanol from 1981 to 2018 is shown in Figure 3.
\nThe U.S. annual production of ethanol from 1981 to 2018 [15].
Second and subsequent generations of biofuels including bioethanol are produced from non-food raw materials [16]. Second-generation bioethanol is typically produced from sugars derived from lignocellulosic biomass. Various types of biomass have been studied for production of biofuels including agricultural wastes (e.g., corn stover, wheat straw, corn cob, rice husk, and sugar cane bagasse), energy crops which grow on low-quality soil (perennial grasses such as Miscanthus sinensis and M. giganteus and switchgrass), forest-based woody wastes (bark, sawdust, softwood trimmings and hardwood chips), waste from parks and gardens (leaves, grasses, and branches), municipal solid wastes such as food waste, kraft paper and paper sludge, the whey-a byproduct of the cheese industry, and crude glycerol from the biodiesel industry.
\nThe amount of available lignocellulosic biomass far exceeds the amount of food feedstock that can be used for biofuel production. However, the production of lignocellulosic bioethanol requires feedstock preparation prior to fermentation and finding/developing microbes that are able to hydrolyze polysaccharides and ferment sugars from cellulose and hemicellulose breakdown.
\nThe term third generation biofuel refers to biofuel derived from algae and has only recently enter the mainstream. Previously, algae were grouped with other non-food biomass types as feedstock for second generation biofuels. However, the uniqueness in algae’s production methods and potential of much higher yields of biofuel production warrants its separation from other types of non-food biomass to form their own category.
\nWhen it comes to the potential to produce fuel, algae is unique in several ways. First, algae produce an oil that can easily be refined into diesel or even certain components of gasoline [17]. Second, it can be genetically manipulated to produce a wide list of fuels including biodiesel, butanol, gasoline, methane, ethanol, vegetable oil, and jet fuel [18]. Third, it is also capable of producing outstanding yields. In fact, algae have been used to produce up to 9000 gallons of biofuel per acre, which is 10-fold what the best traditional feedstock have been able to generate. Yields as high as 20,000 gallons per acre are believed to be attainable. According to the US Department of Energy, yields of 10-fold high mean that only 0.42% of the U.S. land area would be needed to generate enough biofuel to meet all the U.S. needs.
\nAlgae do have a down side: they require large amounts of water, nitrogen and phosphorus to grow. So much that the production of fertilizer to meet the needs of algae used to produce biofuel would produce more greenhouse gas emissions than were saved by using algae-based biofuel. It also means the cost of algae-base biofuel is much higher than fuel from other sources. This single disadvantage means that the large-scale implementation of algae to produce biofuel will not occur for a long time, if at all. In fact, after investing more than $600 million USD into research and development of algae, Exxon Mobil came to the conclusion in 2013 that algae-based biofuels will not be viable for at least 25 years which was calculated on strictly economical term without considering the environmental impacts that have yet to be solved [19].
\nDry plant materials are mainly comprised of three types of biopolymers: cellulose, hemicellulose, and lignin. Cellulose and hemicellulose account for more than half of the entire dry biomass (see Table 2) [28]. Ethanol yield and conversion efficiency depend on the type of biomass, and benefit from a high content of cellulose and hemicellulose and low lignin content [29]. The domains of the three polymers in plant cell walls are connected strongly through covalent and hydrogen bonds. These bonds make lignocellulosic material resistant to degradation [30] and different methods of pretreatment [31].
\nBiomass | \nCellulose % | \nHemicellulose % | \nLignin % | \n
---|---|---|---|
Corn stover | \n37.5 | \n30 | \n10.3 [20] | \n
Corn cobs | \n33.6 | \n37.2 | \n19.3 [21] | \n
Sugarcane bagasse | \n45 | \n20 | \n30 [22] | \n
Grasses | \n25–40 | \n35–50 | \n10–30 [23] | \n
Switchgrass | \n31.98 | \n25.19 | \n18.13 [24] | \n
Wheat straw | \n35.9 | \n23.9 | \n19.3 [25] | \n
Oat straw | \n39.4 | \n27.1 | \n20.7 [23] | \n
Rice straw | \n44.3 | \n35.5 | \n20.4 [26] | \n
Rice husk | \n34.4 | \n29.3 | \n19.2 [27] | \n
Hardwood | \n\n | \n | \n |
Black locust | \n41.61 | \n17.66 | \n26.70 [24] | \n
Hybrid poplar | \n44.70 | \n18.55 | \n26.44 [24] | \n
Eucalyptus | \n49.50 | \n13.07 | \n27.71 [24] | \n
Hardwood stems | \n40–55 | \n24–40 | \n18–25 [23] | \n
Softwood-pine | \n44.55 | \n21.90 | \n27.67 [24] | \n
Nut shells | \n25–30 | \n25–30 | \n30–40 [23] | \n
Newspaper | \n40–55 | \n24–40 | \n18–25 [23] | \n
Biomass composition.
Cellulose is a β-glucan linear polymer of 500–14,000
Hemicellulose is a branched heteropolymer of different monosaccharides including pentoses (
C5 sugars such as xylose and arabinose are mostly found in xyloglucan, xylan, arabinan and arabinogalactan (substructures of pectin), which are components of polysaccharides in the plant cell wall [38]. Xylan is the largest hemicellulose component, consisted of β-1,4-linked xylose residues with side branches of α-arabinofuranose and α-glucuronic acids and contribute to cross-linking of cellulose microfibrils and lignin through ferulic acid residues [39].
\nLignin is a natural three-dimensional polymer (600–15,000 kda) bio-synthesized from phenylpropanoid units via radical reactions [40]. Lignin accounts for 20–35 wt% in woody biomass (40–50 wt% in bark) and 10–20 wt% in agricultural stems [41]. In lignin, phenolic units are connected by more than eight different linkages, among them arylglycerol β-aryl ether (β-O-4) is the dominant linkage in both softwood and hardwood in most plants, consisting of ~50% of spruce linkages and 60% of birch and eucalyptus linkage [42]. It has long been recognized as the major renewable source of aromatic chemicals such as phenols and aromatic hydrocarbons.
\nDue to the complex polymer structure and heterogeneity in the ways monomeric units are linked, lignin is particularly difficult to biodegrade, making it an undesirable component in plant cell walls for bioethanol production. In plant cell wall, lignin functions like a glue to hold all components together [43]. As such, its recalcitrant character makes this three-dimensional polymer molecule a physical barrier to the enzymes that act on cellulose and hemicellulose.
\nIn biorefinery, around 62 million tonnes of lignin is obtained in the commercial production of lignocellulosic ethanol. A large amount of lignin is also being generated in the pulp industry as lignin has also to be separated from cellulose for a different reason: the aromatic components in lignin can turn yellow as it is oxidized slowly in air. Despite that lignin has mainly been burned to supply heat and to generate electricity, it has long been recognized as the major renewable source of aromatic polymer and chemicals [44].
\nDue to the lower oxygen content in lignin as compared to that in cellulose, the energy value of lignin could be as high as cellulose despite of its lower weight percentage in lignocellulosic biomass. This has generated a lot of interest in converting lignin into liquid fuels using thermochemical and biological methods including pyrolysis, hydrothermal liquefaction, and enzymatic decomposition [45]. Among these methods, hydrothermal liquefaction has been more investigated recently and appears to be a promising way to decompose lignin into bio oil which could be further processed into liquid transportation fuels.
\nSecond-generation bioethanol is produced using a process involving the four primary steps of (i) pre-treatment, (ii) hydrolysis to sugars, (iii) fermentation, and (iv) product/coproduct recovery [46]. During pre-treatment, the feedstock is subjected to physical (heat, steam) or chemical (acid or base) conditions that disrupt the fibrous matrix of the material, resulting in the separation of the hemicelluloses from the cellulose chains and the lignin that binds them together. Hydrolysis follows pre-treatment, releasing individual glucose from cellulose and hexose and pentose from hemicellulose. These monomers can then be fermented to ethanol by yeasts that have been modified to ferment both hexose and pentose sugars and adapted to deal with the inhibitors that are produced during pre-treatment and unavoidably associated with the hexose and pentose sugars [34]. Distillation and dehydration of the aqueous ethanol solution produces ethanol of 99.9% purity. Coproduct recovery will depend upon the feedstock and pre-treatment process used and can include a range of products such as extractives, lignin, and unhydrolyzed cellulose [47].
\nIn the following three sections (Sections 4–7), each of the four primary steps will be reviewed. Current topics of research, which are concentrated on recombinant fermentative microbes development and a consolidated process of hydrolysis and co-fermentation of hexoses and pentoses, will be covered in Section 8. A review on cost analysis is given in Section 9 to present opportunities for cost reduction for second-generation bioethanol production.
\nWithout pretreatment before the enzymatic saccharification stage, the non-biodegradable lignin in lignocellulosic material presents as a major obstacle to the enzymatic hydrolysis of crystalline cellulose and hemicellulose which themselves already have low digestibility [48]. Pretreatment removes or decomposes the lignin (delignification) [49] and thus makes cellulose and hemicellulose more readily available to cellulases and hemicellulose’s.
\nIn principle, there are three methods for pretreatment: biological, chemical and physical processes. Some processes, where chemical and physical actions are inherently inseparable, are termed physiochemical. Two or all of these basic methods can be used in combination to gain benefits from each method. Various pretreatment methods have been described and compared critically in a recent review [50].
\nBiological treatment uses microorganisms such as white, brown or soft rot fungi which break up the structure of lignin via the action of extracellular lignolytic enzymes released by the fungi [51]. Further research is needed to overcome the issues of selectivity, cost, retention time and effectiveness to make it a practical choice [50].
\nChemical treatments include treatment with bases, diluted acids, and oxygen as an oxidizer. These reagents react with lignin and cause the polymer to breakdown into smaller and more soluble fragments. Physical pretreatment is usually performed before chemical or biological treatment to reduces cell wall crystallinity and particle size by physical milling or grinding [50]. In some treatment methods, both physical action and chemical reaction play important roles in lignin removal. Such physicochemical pretreatment can involve steam explosion, liquid hot water, ammonia fiber explosion, ammonia recycle percolation or a supercritical carbon dioxide.
\nPretreatment contributes a vital role in the cost evaluation process of whole technology, because they contribute about 30–35% of overall production cost [52]. There are many issues that arise from this process [50] including loss of sugars (mainly pentose sugars derived from hemicellulose degradation), and generation of toxic substances that inhibits the downstream fermentation process. Both need to be minimized to make ethanol production more efficient.
\nSteam explosion has become one of the most adopted pretreatment processes, where hydrolysis of hemicellulose also happens which improves cellulose digestibility. It is a physiochemical method that uses both physical changes caused by sudden pressure reduction and heat- and catalyst-induced chemical changes. An impregnation agent is sometimes used before the pretreatment step. Upon steam explosion after 1–5 min soaking in 160–270°C and 20–50 bar steam, fibers loose up and sugar polymers (mainly hemicellulose) partially degrade into sugars via hydrolysis of glycoside bonds in polysaccharides and lignin into soluble fragments including some inhibitors and phenolic products [50]. The process allows for subsequent solubilization of hemicellulose in water and lignin in organic or alkaline solvent. Cellulose undergoes some degree of polymerization but is still insoluble in water or organic solvents and remains in the solid phase. Acid (sulfuric acid and sulfur dioxide) impregnation before steam explosion reduce the time and temperature necessary for proper depolymerization of the feedstock, increases the efficiency of enzymatic hydrolysis of polysaccharides to glucose and xylose and reduce enzyme consumption [53]. Compared to other methods of biomass fractionation, steam explosion uses less dangerous chemicals, less demanding on investment and energy consumption [54]. Steam explosion is not recommended for agricultural and hardwood wastes with high contents of pentoses and low levels of lignin, due to the susceptibility of pentoses to thermal degradation. Steam explosion is recommended for processing straw and bagasse.
\nOne of the lasting issues in the second-generation bioethanol production is the formation of inhibitors during the pretreatment. The inhibitors create unfriendly environments for fermentative microbes, increases the length of lag phase, causes loss of cell density and lower growth rates of fermenting microbes, and consequently decreases ethanol yields [55]. The commonly observed inhibitors are aldehydes such as 5-hydroxymethyl-2-furaldehyde and 2-furaldehyde (furfural), weak organic acids (formic, acetic and levulinic acids) and phenolic compounds [56]. Acetic acid is the major organic acid found in hydrolysates coming from the hydrolysis of acetyl side-chain groups in hemicellulose [57]. Cell growth of fermentative microbes is inhibited by the intracellular process of anions of weak acids. Furan aldehydes are poisonous for microbes and phenolic compounds interfere with the function and integrity of cell membranes [58].
\nThere are several methods used for the removal of inhibitors [59]. The detoxification of lignocellulosic hydrolysates can be performed using inhibitor sorbents such as excess of lime, active carbon or lignite (brown coal).
\nAfter pretreatment to partially remove lignin and loose up polysaccharide structures, polysaccharides need to be hydrolyzed into sugar molecules which will be converted into ethanol by fermentation [38]. The hydrolysis can be accomplished chemically via acid-catalyzed cleavage of glycosidic bonds or by enzymes produced by microbes. Enzymatic method is more popular due to less impact on the environment and higher selectivity in the hydrolysis. Glucose and xylose are the main products in hydrolysates from the enzymatic breakdown of polysaccharides.
\nEnzymes produced by the filamentous fungi such as Aspergillus nidulans, Aspergillus niger, Penicillium spp. and Trichoderma reesei are dominant in commercial biorefinery [38]. Among different types of cellulases, endoglucanases attack the internal glycosidic bonds in the amorphous cellulose regions, causing fragmentation of the cellulose structure, and exoglucanase works of the termini of β-glucan molecules to release glucose molecules one at a time, while β-glucosidase attacks catalyzes the hydrolysis of the glycosidic bonds to terminal non-reducing residues in beta-
Various strains of yeasts and bacteria are being investigated with the goal of developing a consolidated process of hydrolysis and co-fermentation of glucose and xylose, without the need for adding exogenous cellulases [63].
\nSugars in the hydrolysate are converted into ethanol by fermentation using microorganisms such as yeasts. Ethanol-producing ability of yeasts depends on lignocellulosic hydrolysate, their strain and fermentation conditions (temperature, pH, aeration and nutrient supplementation). For use in industrial bioethanol production, microorganisms (mainly yeasts) must show thermotolerance and high fermentative activity for simple carbohydrates such as glucose and xylose. They should also be resistant to environmental stressors, including inhibitors mentioned in Section 4.3, acidic pH, high sugar level at the beginning of fermentation (causing hyperosmotic stress), and higher temperatures which prevents microbiological contamination, and are able to grow on various lignocellulosic substrates at a fast growth rate [58, 64].
\nSaccharomyces cerevisiae JRC6 and Candida tropicalis JRC1 are recommended for hydrolysates after alkali pretreatment and acid pretreatment, respectively [41]. Saccharomyces sp. yeasts are used in biorefineries to ferment glucose released during starch hydrolysis. Apart from glucose, they are capable of fermenting galactose and mannose.
\nZymomonas mobilis is a Gram negative, facultative anaerobic, non-sporulating, polarly-flagellated, rod-shaped bacterium. It has notable bioethanol-producing capabilities, which surpass yeast in some respects. However, it only ferments glucose, fructose and sucrose [65]. This prevents them from being used in industrial production of bioethanol. The Z. mobilis strains are tolerant to ethanol concentration up to 120 g/L, and have low nutritional requirements for growth [58]. However, its tolerance to acetic acid is low: as little as 2.5 g/L of HOAc. Its recombinant strain AX101 also has low tolerance to acetic acid.
\nAfter fermentation, the mash is heated so that the ethanol evaporates. This process, known as distillation, separates the ethanol, but its purity is limited to 95–96% due to the formation of a water-ethanol azeotrope with maximum 96.5% v/v) ethanol. This hydrous ethanol can be used as a fuel alone, but is not miscible in all ratios with gasoline, so the water fraction is typically removed before ethanol is added to gasoline.
\nWater can be removed by passing hydrous ethanol vapor through a bed of molecular sieve beads. The bead’s pores are sized to allow adsorption of water while excluding ethanol. Two beds are often used so that one is available to adsorb water while the other is being regenerated. This dehydration technology can save 3000 BTUs/gallon over the azeotropic distillation and has been adopted by most modern ethanol plants.
\nRecent research has demonstrated that complete dehydration prior to blending with gasoline is unnecessary. When the azeotropic mixture is blended directly with gasoline, water separates from the gasoline/ethanol phase and can be removed in a two-stage counter-current setup of mixer-settler tanks with minimal energy consumption [66].
\nNumerous life cycle analyses (LCAs) of lignocellulosic ethanol have been published over the last 15 years and several reviews of these LCA studies have been completed and are cited in a more recent review [67]. These studies show a clear reduction in GHG emissions for lignocellulosic ethanol compared to gasoline. However, accurate quantification of GHG emission reduction is hard to obtain as gaps remain in understanding life cycle performance due to insufficient data, and model and methodological issues. Critical unresolved issues that are expected to impact its energy/GHG emissions performance include feedstock-related emissions, consequential versus attributional life cycle aspects, choice of system boundaries, and allocation methods.
\nDecisions regarding feedstock, process technology and co-products can significantly impact GHG emissions calculations. Predicted life cycle GHG emissions vary widely depending on how the following key parameters are considered: nitrogen-related emissions due to supplemental fertilizer requirements and the N content of feedstock, cellulase requirements, farming energy, ethanol yield, and how the value of co-products such as lignin are realized, among others.
\nGovernment support (i.e., Ethanol mandate, tax credit, etc.) is not expected to last forever. To be sustainable, lignocellulosic biofuels production must meet or exceed the economic performance of their first-generation counterparts. The growth in the capacity of commercial lignocellulosic ethanol production has been slow in the past decade, despite significantly better predicted performance on various environmental and energy security criteria than corn-based ethanol in the various techno-economic evaluations published before 2010 [68]. The slow growth has been due to both large technological risk, large capital cost, and the poor predicted economic performance of biorefineries in the short term.
\nAn LCA of US softwood cellulosic ethanol was reported in 2012 by Stephen et al. [68]. In the paper, the base case (capacity: 50 mL ethanol year−1) softwood ethanol production cost was compared with costs of ethanol produced from corn and sugarcane found in the literature. Softwood lignocellulosic ethanol was predicted to have a production cost of $0.90 L−1, 250–300% higher than US corn and Brazilian sugarcane ethanol production costs, which were in the range of $0.30–$0.40 L−1. The lignocellulosic base case scale of 50 mL year−1, compared to 150 mL year−1 of US corn and 365 mL year−1 of and Brazilian sugarcane, is much smaller as it was chosen based both on the projects funded under the US Department of Energy’s commercial biorefinery program and those operating in other places such as Denmark. Production costs of sugar- or starch-based ethanol are expected to continue to decline to $0.22–$0.25 L−1 by 2020. Thus, second-generation ethanol is not going to catch up with first-generation ethanol on production cost soon.
\nAnother very recent techno-economic evaluation was performed on production cost of ethanol produced from corn stover using either biochemical or thermochemical methods. For heat integrated biochemical route, the predicted bioethanol product costs at $2.00 for a production capacity of 43,300,000 gallon year−1 [69]. This result was clearly an underestimation of lignocellulosic ethanol as a major cost item, capital investment cost, was not included. Furthermore, the corn stover price of 46.8 $/ton was an underestimation, and feedstock transportation cost was not included in LCA. Feedstock cost can impact total cost by 40 percent according to a Lux Research report of 2016 [70]. The Brazilian birefinery company Raizen has the lowest projected minimum ethanol selling price of $2.17 per gallon while Abengoa’s capital-intensive $500 million Hugoton facility has the highest price of $4.55 with feedstock cost emerging as the most critical variable. The low cost of Raizen’s cellulosic ethanol is largely attributed to its access to low cost sugarcane straw and sugarcane bagasse ($40 and $38 per dry metric ton), respectively, compared with corn stover ($90) used by Abengoa and POET-DSM and wheat straw ($75) used by Beta Renewables [71].
\nIt is apparent that second-generation ethanol is currently much more costly to produce than first-generation ethanol. It is hard to predict when the cost of lignocellulosic ethanol will be reduced to the level of corn/sugar cane ethanol. Dramatic reductions in the capital and operational costs must occur before the potential superior environmental benefits from cellulosic ethanol relative to corn ethanol can be realized. Pretreatment, enzymatic hydrolysis and distillation are responsible for much of the cost of producing bioethanol. Currently, intensive research is being conducted to improve each of the processes to make them more economical.
\nAn effective pretreatment increases specific surface area of biomass, making cellulose better available for the action of hydrolytic enzymes obtained from fungi and bacteria, minimizing reductions in enzyme activity, and thus improving the rate of biomass hydrolysis and providing the highest possible concentration of fermentable sugars. Effective pretreatment also reduces the degradation of monosugars [72]. In selecting pretreatment methods, factors such as their environmental impact and recycling of chemical compounds (for example ammonia in the ammonia fiber explosion process [73, 74]) must be considered. Different pretreatment methods and their combinations are being explored for different types of biomass [50].
\nBetter results, e.g., improved ethanol yield, have been obtained from combination of two or more pretreatment methods, but have resulted often at the cost of more energy consumption compared to single method of pretreatment. Among single treatment methods, dilute acid pretreatment is more suitable for various types of biomass as it solubilizes most of hemicellulose and partially remove lignin [50].
\nIt is vital to analyze the pros and cons of each pretreatment technology before scaling up for industrial application. However, technoeconomic assessment will only give a rough estimate on capital cost and the final fuel cost in commercial scale production when many research findings are still in pilot scale level and demonstration plant level [52].
\nEfficient fermentation of pentoses helps reduce ethanol production cost since pentoses can be 25.8 wt% as in sugarcane bagasse [75, 76] 22.3–74.9 wt% in corn stover (Table 3). Wild microorganisms are incapable of producing ethanol in high yields, as they are unable to utilize both pentoses and hexoses. Pentose-specific transporter proteins and enzymatic reactions determining the metabolism of pentoses such as
Biomass | \nLignin | \nHexoses | \nPentoses | \nCarbohydrate | \n|||
---|---|---|---|---|---|---|---|
Glucan | \nMannan | \nGalactan | \nXylan | \nArabinan | \n|||
Corn stover | \n18.2 | \n30.6 | \n0.5 | \n0.7 | \n16.0 | \n1.9 | \n49.7 [76] | \n
\n | 20.2 | \n38.1 | \n0.4 | \n0.7 | \n20.3 | \n2.0 | \n61.5 [76] | \n
\n | 17.2 | \n36.1 | \nN/A | \n2.5 | \n21.4 | \n3.5 | \n65.3 [77] | \n
Corn leaf | \nN/A | \n34.2 | \n1.8 | \n2.5 | \n22.1 | \n3.5 | \n64.1 [68] | \n
Corn stalk | \nN/A | \n36.5 | \n1.7 | \n2.4 | \n21.6 | \n3.2 | \n65.4 [68] | \n
Corn fiber | \n6.9 | \n36.5 | \nN/A | \n2.9 | \n18.4 | \n13.3 | \n71.1 [77] | \n
DDG | \n3.1 | \n22.0 | \nN/A | \n0.3 | \n9.5 | \n5.5 | \n37.3 [77] | \n
Wheat straw | \n14.5 | \n36.6 | \n0.8 | \n2.4 | \n19.2 | \n2.4 | \n61.4 [77] | \n
\n | 16.9 | \n32.6 | \n0.3 | \n0.8 | \n19.2 | \n2.4 | \n55.3 [76] | \n
Switchgrass | \n23.2 | \n32.2 | \n0.4 | \n0.0 | \n20.3 | \n3.7 | \n56.6 [77] | \n
\n | 23.1 | \n35.9 | \n0.4 | \n0.5 | \n19.6 | \n1.5 | \n57.9 [76] | \n
\n | 27.6 | \n31.9 | \n0.3 | \n0.3 | \n10.6 | \n1.1 | \n44.2 [76] | \n
\n | 24.1 | \n42.6 | \n0.3 | \n0.5 | \n23.1 | \n1.5 | \n68.0 [76] | \n
S. bagasse | \n18.4 | \n38.1 | \n0.4 | \n0.0 | \n23.3 | \n2.5 | \n65.0 [77] | \n
Softwood | \n\n | \n | \n | \n | \n | \n | \n |
Spruce | \n28.3 | \n43.2 | \n11.5 | \n2.7 | \n5.7 | \n1.4 | \n64.5 [76] | \n
Red pine | \n29.0 | \n42.0 | \n7.4 | \n1.8 | \n9.3 | \n2.4 | \n62.9 [76] | \n
Lodgepole pine | \n27.9 | \n42.5 | \n11.6 | \n2.1 | \n5.5 | \n1.6 | \n63.3 [76] | \n
Ponderosa pine | \n26.9 | \n41.7 | \n10.8 | \n3.9 | \n6.3 | \n1.8 | \n64.5 [76] | \n
Loblolly pine | \n28.0 | \n45.0 | \n11.0 | \n2.3 | \n6.8 | \n1.7 | \n66.8 [76] | \n
Douglas-fir | \n32.0 | \n44.0 | \n11.0 | \n4.7 | \n2.8 | \n2.7 | \n65.2 [76] | \n
Hardwood | \n\n | \n | \n | \n | \n | \n | \n |
Red maple | \n24.0 | \n46.0 | \n2.4 | \n0.6 | \n19.0 | \n0.5 | \n68.5 [76] | \n
Aspen | \n23.0 | \n45.9 | \n1.2 | \n0.0 | \n16.7 | \n0.0 | \n63.8 [76] | \n
Yellow poplar | \n23.3 | \n42.1 | \n2.4 | \n1.0 | \n15.1 | \n0.5 | \n61.1 [76] | \n
Poplar | \nN/A | \n39.8 | \n2.4 | \n0.0 | \n14.8 | \n1.2 | \n58.2 [77] | \n
Poplar stem | \nN/A | \n40.3 | \n3.1 | \n0.7 | \n17.6 | \n0.6 | \n62.3 [68] | \n
Poplar DN34 | \n23.9 | \n43.7 | \n2.9 | \n0.6 | \n17.4 | \n0.6 | \n65.2 [76] | \n
Euclyptus saligna | \n26.9 | \n48.1 | \n1.3 | \n0.7 | \n10.4 | \n0.3 | \n60.8 [76] | \n
Salix | \n26.4 | \n41.4 | \n3.2 | \n2.3 | \n15.0 | \n1.2 | \n63.1 [76] | \n
Hexose, pentose and lignin contents in different types of biomass.
S. bagasse = sugarcane bagasse.
Owing to large microbial biodiversity, fermentation of pentoses can be achieved either by finding a potent naturally occurring pentose utilizing microorganism or by a genetically engineered C5 utilizing strain [78, 79]. One effective strategy is to create recombinant strain with genes for xylose metabolism [80]. Genetic engineering has been conducted mainly on Saccharomyces cerevisiae yeast, [81] the Gram-positive bacteria Clostridium cellulolyticum and Lactobacillus casei and the Gram-negative bacteria Zymomonas mobilis, Escherichia coli and Klebsiella oxytoca [43]. Recombinant yeasts consume xylose much slower than glucose, thus requiring prolonged fermentation time due to a lack of reaction intermediates and efficient pentose transporters [82].
\nA common problem of xylose-fermenting strains is the production of xylitol or the reabsorption of ethanol, which lead to low ethanol yield. One grand challenge is glucose repression, which results in di-auxic fermentation of a mixture of glucose and pentoses since glucose prevents the catabolism and/or utilization of other non-glucose sugars, leading reduced volumetric ethanol yield [83]. Approaches and conditions sought to improve glucose and xylose fermentation to ethanol are reviewed in a recent paper with emphasis on microbial systems used to maximize biomass resource efficiency, ethanol yield, and productivity [64].
\nSeparate processes have been established for enzymatic hydrolysis of cellulose and hemicellulose and fermentation (SHF) of sugars in hydrolysate. In the SHF processes, saccharification and fermentation take place in separate vessels, so the two processes can be optimized separately. One drawback of SHF is that accumulation of simple carbohydrates (such as cellobiose) causes end-product inhibition of hydrolytic enzymes, for example cellulases or cellobioses. To prevent end-product inhibition, extra doses of β-glucosidase are needed together with the commercial cellulase preparations [84].
\nThere is a strong incentive to develop a process to perform simultaneous saccharification and fermentation (SSF) as it reduces investment costs by reducing the number of vessels and has the potential to become the preferred approach. In SSF, the problem of end-product feedback inhibition is largely eliminated because glucose molecules are fermented immediately by the fermentative microbes as it is produced from hydrolysis of cellulose [85]. However, the benefits come with a major downside which is an inherent mismatch between the optimal temperatures for the enzymes (fungal cellulases and hemicellulose’s) on the one hand, and yeast biocatalysts on the other. The temperature optima for saccharifying enzymes (50–55°C for cellulase) are higher than those for fermenting mesophilic culture. The optimal temperature for yeasts is below 35°C. Mesophilic yeasts (that thrive best in a moderate temperature) exhibit slower growth rates at higher temperatures. Currently, SSF must run at temperatures between the optimum temperature for cellulase and the optimum temperature for fermentative organisms. The compromise results in higher cellulase loading and an increase in enzyme costs. Efficient bioethanol production by SSF requires the use of thermotolerant ethanologenic yeast. It is a hot topic for research to genetically modify microorganisms with the ability to ferment at higher temperatures [43]. Some isolated yeasts, including Pichia, Candida, Saccharomyces and Wickerhamomyces, are found to grow at temperatures of 40°C and ferment sugars at higher temperatures [41]. To make SSF process highly efficient in ethanol production, the pentose metabolic pathway is been engineered into microorganisms to enables the use of C5 sugars by microbes that do not ferment them earlier [86].
\nReduction in enzyme cost is been sought by searching for new organisms with cellulolytic and hemicellulytic activities [87], lowering the enzyme dosage through protein engineering [86, 88], and improving cellulase thermostability for performing hydrolysis at elevated temperatures to increase the efficiency of cellulose hydrolysis [89]. Cellulase enzyme cost reductions are challenging as cellulase costs need to be significantly lower than those of amylase enzymes on a unit-of-protein basis. The high price of the enzymes encouraged research into solutions to the problem of glucose inhibition and to the deactivation caused by lignin by-products [90].
\nFurther integration of enzyme production with SSF leads to a new technology of consolidated bioprocessing (CBP). One area of research is aimed at engineering all three capabilities (saccharification, hexose fermentation and pentose fermentation) into a single strain for the CBP process [91, 92]. Cellulase-encoding genes may be introduced into specific species during recombination [63] to eliminate the need for exogenous cellulases in the process of SSF and decrease the capital costs of processing. CBP technology promises to eliminate costs associated with enzyme production and additional infrastructure/vessels [93].
\nWorking with a high dry matter (DM) concentration is also potentially an effective way to reduce the hydrolytic enzyme costs. However, high DM content causes an increase in viscosity, inadequate mass and heat transfer within the bioreactor, and, consequently, a strong reduction in the conversion of cellulose/hemicellulose to fermentable sugars. This problem could be overcome by adopting various fed-batch strategies or coprocessing substrates with different degrees of porosity [94].
\nA variation of SSF, simultaneous saccharification and co-fermentation (SSCF), in which a starch material is co-fermented, has been adopted to address low ethanol concentration issue in lignocellulosic ethanol production. SSCF can reduce ethanol production cost by increasing ethanol concentration and thus reducing distillation cost [95].
\nRecycling yeasts and enzymes is also an effective way to reduce the cost of ethanol production. The remaining unhydrolyzed solids with some enzymes adsorbed are collected by filtration or centrifuge and are recycled to the next cycle for further hydrolysis. In one study, the enzyme loading was reduced from 36 to 22.3 and 25.8 mg protein per gram glucan, respectively, for separate hydrolysis and fermentation (SHF) and for SSCF on AFEX™ pretreated corn stover [96]. Enzyme adsorption to the residual solids is probably inhibited at high sugar concentrations in the fast SHF process [97] and hence affected enzyme recycling. The fast SSCF process removed most of the sugars by fermentation but produced ethanol whose effect on enzyme adsorption is unclear.
\nCost effect renewable fuel generation from lignocellulosic materials is one of the few options the human beings have to slow down/eliminate global warming and achieve energy independence from fossil fuels. Second generation bioethanol is a promising path in the roadmap to the future world of renewable energy. The cellulosic ethanol industry is still in its infancy and its survival is relying on heavy policy support. Major technological advances at every stage of the cellulosic ethanol production are critically needed to lower the ethanol production cost to a level comparable to the corn ethanol. The key problems that remain to be solved include: (1) Effective and low-cost biomass pretreatment method that exposes polysaccharides to enzymes for efficient saccharification, (2) efficient fermentation of all sugars (pentoses and hexoses) released during the pretreatment and hydrolysis steps into ethanol, (3) development of enzymes that tolerate various inhibitors including monosaccharides (mainly glucose), and ethanol accumulation, and (4) heat-tolerant fermentation microbes and enzymes for efficient simultaneous saccharification and fermentation.
\nThe support of the South Dakota NSF EPSCoR Program (Grant No. IIA-1330842) is greatly appreciated.
\nThere is no conflict of interest involved in this work.
Stability constant of the formation of metal complexes is used to measure interaction strength of reagents. From this process, metal ion and ligand interaction formed the two types of metal complexes; one is supramolecular complexes known as host-guest complexes [1] and the other is anion-containing complexes. In the solution it provides and calculates the required information about the concentration of metal complexes.
Solubility, light, absorption conductance, partitioning behavior, conductance, and chemical reactivity are the complex characteristics which are different from their components. It is determined by various numerical and graphical methods which calculate the equilibrium constants. This is based on or related to a quantity, and this is called the complex formation function.
During the displacement process at the time of metal complex formation, some ions disappear and form a bonding between metal ions and ligands. It may be considered due to displacement of a proton from a ligand species or ions or molecules causing a drop in the pH values of the solution [2]. Irving and Rossotti developed a technique for the calculation of stability constant, and it is called potentiometric technique.
To determine the stability constant, Bjerrum has used a very simple method, and that is metal salt solubility method. For the studies of a larger different variety of polycarboxylic acid-, oxime-, phenol-containing metal complexes, Martel and Calvin used the potentiometric technique for calculating the stability constant. Those ligands [3, 4] which are uncharged are also examined, and their stability constant calculations are determined by the limitations inherent in the ligand solubility method. The limitations of the metal salt solubility method and the result of solubility methods are compared with this. M-L, MLM, and (M3) L are some types of examples of metal-ligand bonding. One thing is common, and that is these entire types metal complexes all have one ligand.
The solubility method can only usefully be applied to studies of such complexes, and it is best applied for ML; in such types of system, only ML is formed. Jacqueline Gonzalez and his co-worker propose to explore the coordination chemistry of calcium complexes. Jacqueline and et al. followed this technique for evaluate the as partial model of the manganese-calcium cluster and spectrophotometric studies of metal complexes, i.e., they were carried calcium(II)-1,4-butanediamine in acetonitrile and calcium(II)-1,2-ethylendiamine, calcium(II)-1,3-propanediamine by them.
Spectrophotometric programming of HypSpec and received data allows the determination of the formation of solubility constants. The logarithmic values, log β110 = 5.25 for calcium(II)-1,3-propanediamine, log β110 = 4.072 for calcium(II)-1,4-butanediamine, and log β110 = 4.69 for calcium(II)-1,2-ethylendiamine, are obtained for the formation constants [5]. The structure of Cimetidine and histamine H2-receptor is a chelating agent. Syed Ahmad Tirmizi has examined Ni(II) cimetidine complex spectrophotometrically and found an absorption peak maximum of 622 nm with respect to different temperatures.
Syed Ahmad Tirmizi have been used to taken 1:2 ratio of metal and cimetidine compound for the formation of metal complex and this satisfied by molar ratio data. The data, 1.40–2.4 × 108, was calculated using the continuous variation method and stability constant at room temperature, and by using the mole ratio method, this value at 40°C was 1.24–2.4 × 108. In the formation of lead(II) metal complexes with 1-(aminomethyl) cyclohexene, Thanavelan et al. found the formation of their binary and ternary complexes. Glycine,
Using the stability constant method, these ternary complexes were found out, and using the parameters such as Δ log K and log X, these ternary complex data were compared with binary complex. The potentiometric technique at room temperature (25°C) was used in the investigation of some binary complex formations by Abdelatty Mohamed Radalla. These binary complexes are formed with 3D transition metal ions like Cu2+, Ni2+, Co2+, and Zn2+ and gallic acid’s importance as a ligand and 0.10 mol dm−3 of NaNO3. Such types of aliphatic dicarboxylic acids are very important biologically. Many acid-base characters and the nature of using metal complexes have been investigated and discussed time to time by researchers [7].
The above acids (gallic and aliphatic dicarboxylic acid) were taken to determine the acidity constants. For the purpose of determining the stability constant, binary and ternary complexes were carried in the aqueous medium using the experimental conditions as stated above. The potentiometric pH-metric titration curves are inferred for the binary complexes and ternary complexes at different ratios, and formation of ternary metal complex formation was in a stepwise manner that provided an easy way to calculate stability constants for the formation of metal complexes.
The values of Δ log K, percentage of relative stabilization (% R. S.), and log X were evaluated and discussed. Now it provides the outline about the various complex species for the formation of different solvents, and using the concentration distribution, these complexes were evaluated and discussed. The conductivity measurements have ascertained for the mode of ternary chelating complexes.
A study by Kathrina and Pekar suggests that pH plays an important role in the formation of metal complexes. When epigallocatechin gallate and gallic acid combine with copper(II) to form metal complexes, the pH changes its speculation. We have been able to determine its pH in frozen and fluid state with the help of multifrequency EPR spectroscopy [8]. With the help of this spectroscopy, it is able to detect that each polyphenol exhibits the formation of three different mononuclear species. If the pH ranges 4–8 for di- or polymeric complex of Cu(II), then it conjectures such metal complexes. It is only at alkaline pH values.
The line width in fluid solutions by molecular motion exhibits an incomplete average of the parameters of anisotropy spin Hamilton. If the complexes are different, then their rotational correlation times for this also vary. The analysis of the LyCEP anisotropy of the fluid solution spectra is performed using the parameters determined by the simulation of the rigid boundary spectra. Its result suggests that pH increases its value by affecting its molecular mass. It is a polyphenol ligand complex with copper, showing the coordination of an increasing number of its molecules or increasing participation of polyphenol dimers used as ligands in the copper coordination region.
The study by Vishenkova and his co-worker [8] provides the investigation of electrochemical properties of triphenylmethane dyes using a voltammetric method with constant-current potential sweep. Malachite green (MG) and basic fuchsin (BF) have been chosen as representatives of the triphenylmethane dyes [9]. The electrochemical behavior of MG and BF on the surface of a mercury film electrode depending on pH, the nature of background electrolyte, and scan rate of potential sweep has been investigated.
Using a voltammetric method with a constant-current potential sweep examines the electrical properties of triphenylmethane dye. In order to find out the solution of MG and BF, certain registration conditions have been prescribed for it, which have proved to be quite useful. The reduction peak for the currents of MG and BF has demonstrated that it increases linearly with respect to their concentration as 9.0 × 10−5–7.0 × 10−3 mol/dm3 for MG and 6.0 × 10−5–8.0 × 10−3 mol/dm3 for BF and correlation coefficients of these values are 0.9987 for MG and 0.9961 for BF [10].
5.0 × 10−5 and 2.0 × 10−5 mol/dm3 are the values used as the detection limit of MG and BF, respectively. Stability constants are a very useful technique whose size is huge. Due to its usefulness, it has acquired an umbrella right in the fields of chemistry, biology, and medicine. No science subject is untouched by this. Stability constants of metal complexes are widely used in the various areas like pharmaceuticals as well as biological processes, separation techniques, analytical processes, etc. In the presented chapter, we have tried to explain this in detail by focusing our attention on the applications and solutions of stability of metal complexes in solution.
Stability or formation or binding constant is the type of equilibrium constant used for the formation of metal complexes in the solution. Acutely, stability constant is applicable to measure the strength of interactions between the ligands and metal ions that are involved in complex formation in the solution [11]. A generally these 1-4 equations are expressed as the following ways:
Thus
K1, K2, K3, … Kn are the equilibrium constants and these are also called stepwise stability constants. The formation of the metal-ligand-n complex may also be expressed as equilibrium constants by the following steps:
The parameters K and β are related together, and these are expressed in the following example:
Now the numerator and denominator are multiplied together with the use of [metal-ligand] [metal-ligand2], and after the rearranging we get the following equation:
Now we expressed it as the following:
From the above relation, it is clear that the overall stability constant βn is equal to the product of the successive (i.e., stepwise) stability constants, K1, K2, K3,…Kn. This in other words means that the value of stability constants for a given complex is actually made up of a number of stepwise stability constants. The term stability is used without qualification to mean that the complex exists under a suitable condition and that it is possible to store the complex for an appreciable amount of time. The term stability is commonly used because coordination compounds are stable in one reagent but dissociate or dissolve in the presence of another regent. It is also possible that the term stability can be referred as an action of heat or light or compound. The stability of complex [13] is expressed qualitatively in terms of thermodynamic stability and kinetic stability.
In a chemical reaction, chemical equilibrium is a state in which the concentration of reactants and products does not change over time. Often this condition occurs when the speed of forward reaction becomes the same as the speed of reverse reaction. It is worth noting that the velocities of the forward and backward reaction are not zero at this stage but are equal.
If hydrogen and iodine are kept together in molecular proportions in a closed process vessel at high temperature (500°C), the following action begins:
In this activity, hydrogen iodide is formed by combining hydrogen and iodine, and the amount of hydrogen iodide increases with time. In contrast to this action, if the pure hydrogen iodide gas is heated to 500°C in the reaction, the compound is dissolved by reverse action, which causes hydrogen iodide to dissolve into hydrogen and iodine, and the ratio of these products increases over time. This is expressed in the following reaction:
For the formation of metal chelates, the thermodynamic technique provides a very significant information. Thermodynamics is a very useful technique in distinguishing between enthalpic effects and entropic effects. The bond strengths are totally effected by enthalpic effect, and this does not make any difference in the whole solution in order/disorder. Based on thermodynamics the chelate effect below can be best explained. The change of standard Gibbs free energy for equilibrium constant is response:
Where:
R = gas constant
T = absolute temperature
At 25°C,
ΔG = (− 5.708 kJ mol−1) · log β.
The enthalpy term creates free energy, i.e.,
For metal complexes, thermodynamic stability and kinetic stability are two interpretations of the stability constant in the solution. If reaction moves from reactants to products, it refers to a change in its energy as shown in the above equation. But for the reactivity, kinetic stability is responsible for this system, and this refers to ligand species [14].
Stable and unstable are thermodynamic terms, while labile and inert are kinetic terms. As a rule of thumb, those complexes which react completely within about 1 minute at 25°C are considered labile, and those complexes which take longer time than this to react are considered inert. [Ni(CN)4]2− is thermodynamically stable but kinetically inert because it rapidly exchanges ligands.
The metal complexes [Co(NH3)6]3+ and such types of other complexes are kinetically inert, but these are thermodynamically unstable. We may expect the complex to decompose in the presence of acid immediately because the complex is thermodynamically unstable. The rate is of the order of 1025 for the decomposition in acidic solution. Hence, it is thermodynamically unstable. However, nothing happens to the complex when it is kept in acidic solution for several days. While considering the stability of a complex, always the condition must be specified. Under what condition, the complex which is stable or unstable must be specified such as acidic and also basic condition, temperature, reactant, etc.
A complex may be stable with respect to a particular condition but with respect to another. In brief, a stable complex need not be inert and similarly, and an unstable complex need not be labile. It is the measure of extent of formation or transformation of complex under a given set of conditions at equilibrium [15].
Thermodynamic stability has an important role in determining the bond strength between metal ligands. Some complexes are stable, but as soon as they are introduced into aqueous solution, it is seen that these complexes have an effect on stability and fall apart. For an example, we take the [Co (SCN)4]2+ complex. The ion bond of this complex is very weak and breaks down quickly to form other compounds. But when [Fe(CN)6]3− is dissolved in water, it does not test Fe3+ by any sensitive reagent, which shows that this complex is more stable in aqueous solution. So it is indicated that thermodynamic stability deals with metal-ligand bond energy, stability constant, and other thermodynamic parameters.
This example also suggests that thermodynamic stability refers to the stability and instability of complexes. The measurement of the extent to which one type of species is converted to another species can be determined by thermodynamic stability until equilibrium is achieved. For example, tetracyanonickelate is a thermodynamically stable and kinetic labile complex. But the example of hexa-amine cobalt(III) cation is just the opposite:
Thermodynamics is used to express the difference between stability and inertia. For the stable complex, large positive free energies have been obtained from ΔG0 reaction. The ΔH0, standard enthalpy change for this reaction, is related to the equilibrium constant, βn, by the well thermodynamic equation:
For similar complexes of various ions of the same charge of a particular transition series and particular ligand, ΔS0 values would not differ substantially, and hence a change in ΔH0 value would be related to change in βn values. So the order of values of ΔH0 is also the order of the βn value.
Kinetic stability is referred to the rate of reaction between the metal ions and ligand proceeds at equilibrium or used for the formation of metal complexes. To take a decision for kinetic stability of any complexes, time is a factor which plays an important role for this. It deals between the rate of reaction and what is the mechanism of this metal complex reaction.
As we discuss above in thermodynamic stability, kinetic stability is referred for the complexes at which complex is inert or labile. The term “inert” was used by Tube for the thermally stable complex and for reactive complexes the term ‘labile’ used [16]. The naturally occurring chlorophyll is the example of polydentate ligand. This complex is extremely inert due to exchange of Mg2+ ion in the aqueous media.
The nature of central atom of metal complexes, dimension, its degree of oxidation, electronic structure of these complexes, and so many other properties of complexes are affected by the stability constant. Some of the following factors described are as follows.
In the coordination chemistry, metal complexes are formed by the interaction between metal ions and ligands. For these type of compounds, metal ions are the coordination center, and the ligand or complexing agents are oriented surrounding it. These metal ions mostly are the transition elements. For the determination of stability constant, some important characteristics of these metal complexes may be as given below.
Ligands are oriented around the central metal ions in the metal complexes. The sizes of these metal ions determine the number of ligand species that will be attached or ordinated (dative covalent) in the bond formation. If the sizes of these metal ions are increased, the stability of coordination compound defiantly decreased. Zn(II) metal ions are the central atoms in their complexes, and due to their lower size (0.74A°) as compared to Cd(II) size (0.97A°), metal ions are formed more stable.
Hence, Al3+ ion has the greatest nuclear charge, but its size is the smallest, and the ion N3− has the smallest nuclear charge, and its size is the largest [17]. Inert atoms like neon do not participate in the formation of the covalent or ionic compound, and these atoms are not included in isoelectronic series; hence, it is not easy to measure the radius of this type of atoms.
The properties of stability depend on the size of the metal ion used in the complexes and the total charge thereon. If the size of these metal ions is small and the total charge is high, then their complexes will be more stable. That is, their ratio will depend on the charge/radius. This can be demonstrated through the following reaction:
An ionic charge is the electric charge of an ion which is formed by the gain (negative charge) or loss (positive charge) of one or more electrons from an atom or group of atoms. If we talk about the stability of the coordination compounds, we find that the total charge of their central metal ions affects their stability, so when we change their charge, their stability in a range of constant can be determined by propagating of error [18]. If the charge of the central metal ion is high and the size is small, the stability of the compound is high:
In general, the most stable coordination bonds can cause smaller and highly charged rations to form more stable coordination compounds.
When an electron pair attracts a central ion toward itself, a strong stability complex is formed, and this is due to electron donation from ligand → metal ion. This donation process is increasing the bond stability of metal complexes exerted the polarizing effect on certain metal ions. Li+, Na+, Mg2+, Ca2+, Al3+, etc. are such type of metal cation which is not able to attract so strongly from a highly electronegative containing stable complexes, and these atoms are O, N, F, Au, Hg, Ag, Pd, Pt, and Pb. Such type of ligands that contains P, S, As, Br and I atom are formed stable complex because these accepts electron from M → π-bonding. Hg2+, Pb2+, Cd2+, and Bi3+ metal ions are also electronegative ions which form insoluble salts of metal sulfide which are insoluble in aqueous medium.
Volatile ligands may be lost at higher temperature. This is exemplified by the loss of water by hydrates and ammonia:
The transformation of certain coordination compounds from one to another is shown as follows:
A ligand is an ion or small molecule that binds to a metal atom (in chemistry) or to a biomolecule (in biochemistry) to form a complex, such as the iron-cyanide coordination complex Prussian blue or the iron-containing blood-protein hemoglobin. The ligands are arranged in spectrochemical series which are based on the order of their field strength. It is not possible to form the entire series by studying complexes with a single metal ion; the series has been developed by overlapping different sequences obtained from spectroscopic studies [19]. The order of common ligands according to their increasing ligand field strength is
The above spectrochemical series help us to for determination of strength of ligands. The left last ligand is as weaker ligand. These weaker ligand cannot forcible binding the 3d electron and resultant outer octahedral complexes formed. It is as-
Increasing the oxidation number the value of Δ increased.
Δ increases from top to bottom.
However, when we consider the metal ion, the following two useful trends are observed:
Δ increases with increasing oxidation number.
Δ increases down a group. For the determination of stability constant, the nature of the ligand plays an important role.
The following factors described the nature of ligands.
The size and charge are two factors that affect the production of metal complexes. The less charges and small sizes of ligands are more favorable for less stable bond formation with metal and ligand. But if this condition just opposite the product of metal and ligand will be a more stable compound. So, less nuclear charge and more size= less stable complex whereas if more nuclear charge and small in size= less stable complex. We take fluoride as an example because due to their smaller size than other halide and their highest electro negativity than the other halides formed more stable complexes. So, fluoride ion complexes are more stable than the other halides:
As compared to S2− ion, O22− ions formed more stable complexes.
It is suggested by Calvin and Wilson that the metal complexes will be more stable if the basic character or strength of ligands is higher. It means that the donating power of ligands to central metal ions is high [20].
It means that the donating power of ligands to central metal ions is high. In the case of complex formation of aliphatic diamines and aromatic diamines, the stable complex is formed by aliphatic diamines, while an unstable coordination complex is formed with aromatic diamines. So, from the above discussion, we find that the stability will be grater if the e-donation power is greater.
Thus it is clear that greater basic power of electron-donating species will form always a stable complex. NH3, CN−, and F− behaved as ligands and formed stable complexes; on the other hand, these are more basic in nature.
We know that if the concentration of coordination group is higher, these coordination compounds will exist in the water as solution. It is noted that greater coordinating tendency show the water molecules than the coordinating group which is originally present. SCN− (thiocynate) ions are present in higher concentration; with the Co2+ metal ion, it formed a blue-colored complex which is stable in state, but on dilution of water medium, a pink color is generated in place of blue, or blue color complex is destroyed by [Co(H2O)6]2+, and now if we added further SCN−, the pink color will not appear:
Now it is clear that H2O and SCN− are in competition for the formation of Co(II) metal-containing complex compound. In the case of tetra-amine cupric sulfate metal complex, ammonia acts as a donor atom or ligand. If the concentration of NH3 is lower in the reaction, copper hydroxide is formed but at higher concentration formed tetra-amine cupric sulfate as in the following reaction:
For a metal ion, chelating ligand is enhanced and affinity it and this is known as chelate effect and compared it with non-chelating and monodentate ligand or the multidentate ligand is acts as chelating agent. Ethylenediamine is a simple chelating agent (Figure 1).
Structure of ethylenediamine.
Due to the bidentate nature of ethylenediamine, it forms two bonds with metal ion or central atom. Water forms a complex with Ni(II) metal ion, but due to its monodentate nature, it is not a chelating ligand (Figures 2 and 3).
Structure of chelating configuration of ethylenediamine ligand.
Structure of chelate with three ethylenediamine ligands.
The dentate cheater of ligand provides bonding strength to the metal ion or central atom, and as the number of dentate increased, the tightness also increased. This phenomenon is known as chelating effect, whereas the formation of metal complexes with these chelating ligands is called chelation:
or
Some factors are of much importance for chelation as follows.
The sizes of the chelating ring are increased as well as the stability of metal complex decreased. According to Schwarzenbach, connecting bridges form the chelating rings. The elongated ring predominates when long bridges connect to the ligand to form a long ring. It is usually observed that an increased a chelate ring size leads to a decrease in complex stability.
He interpreted this statement. The entropy of complex will be change if the size of chelating ring is increased, i.e., second donor atom is allowed by the chelating ring. As the size of chelating ring increased, the stability should be increased with entropy effect. Four-membered ring compounds are unstable, whereas five-membered are more stable. So the chelating ring increased its size and the stability of the formed metal complexes.
The number of chelating rings also decides the stability of complexes. Non-chelating metal compounds are less stable than chelating compounds. These numbers increase the thermodynamic volume, and this is also known as an entropy term. In recent years ligands capable of occupying as many as six coordination positions on a single metal ion have been described. The studies on the formation constants of coordination compounds with these ligands have been reported. The numbers of ligand or chelating agents are affecting the stability of metal complexes so as these numbers go up and down, the stability will also vary with it.
For the Ni(II) complexes with ethylenediamine as chelating agent, its log K1 value is 7.9 and if chelating agents are trine and penten, then the log K1 values are 7.9 and 19.3, respectively. If the metal ion change Zn is used in place of Ni (II), then the values of log K1 for ethylenediamine, trine, and penten are 6.0, 12.1, and 16.2, respectively. The log βMY values of metal ions are given in Table 1.
Metal ion | log βMY (25°C, I = 0.1 M) |
---|---|
Ca2+ | 11.2 |
Cu2+ | 19.8 |
Fe3+ | 24.9 |
Metal ion vs. log βMY values.
Ni(NH3)62+ is an octahedral metal complex, and at 25 °C its log β6 value is 8.3, but Ni(ethylenediamine)32+ complex is also octahedral in geometry, with 18.4 as the value of log β6. The calculated stability value of Ni(ethylenediamine)32+ 1010 times is more stable because three rings are formed as chelating rings by ethylenediamine as compared to no such ring is formed. Ethylenediaminetetraacetate (EDTA) is a hexadentate ligand that usually formed stable metal complexes due to its chelating power.
A special effect in molecules is when the atoms occupy space. This is called steric effect. Energy is needed to bring these atoms closer to each other. These electrons run away from near atoms. There can be many ways of generating it. We know the repulsion between valence electrons as the steric effect which increases the energy of the current system [21]. Favorable or unfavorable any response is created.
For example, if the static effect is greater than that of a product in a metal complex formation process, then the static increase would favor this reaction. But if the case is opposite, the skepticism will be toward retardation.
This effect will mainly depend on the conformational states, and the minimum steric interaction theory can also be considered. The effect of secondary steric is seen on receptor binding produced by an alternative such as:
Reduced access to a critical group.
Stick barrier.
Electronic resonance substitution bond by repulsion.
Population of a conformer changes due to active shielding effect.
The macrocyclic effect is exactly like the image of the chelate effect. It means the principle of both is the same. But the macrocyclic effect suggests cyclic deformation of the ligand. Macrocyclic ligands are more tainted than chelating agents. Rather, their compounds are more stable due to their cyclically constrained constriction. It requires some entropy in the body to react with the metal ion. For example, for a tetradentate cyclic ligand, we can use heme-B which forms a metal complex using Fe+2 ions in biological systems (Figure 4).
Structure of hemoglobin is the biological complex compound which contains Fe(II) metal ion.
The n-dentate chelating agents play an important role for the formation of more stable metal complexes as compared to n-unidentate ligands. But the n-dentate macrocyclic ligand gives more stable environment in the metal complexes as compared to open-chain ligands. This change is very favorable for entropy (ΔS) and enthalpy (ΔH) change.
There are so many parameters to determination of formation constants or stability constant in solution for all types of chelating agents. These numerous parameters or techniques are refractive index, conductance, temperature, distribution coefficients, refractive index, nuclear magnetic resonance volume changes, and optical activity.
Solubility products are helpful and used for the insoluble salt that metal ions formed and complexes which are also formed by metal ions and are more soluble. The formation constant is observed in presence of donor atoms by measuring increased solubility.
To determine the solubility constant, it involves the distribution of the ligands or any complex species; metal ions are present in two immiscible solvents like water and carbon tetrachloride, benzene, etc.
In this method metal ions or ligands are present in solution and on exchanger. A solid polymers containing with positive and negative ions are ion exchange resins. These are insoluble in nature. This technique is helpful to determine the metal ions in resin phase, liquid phase, or even in radioactive metal. This method is also helpful to determine the polarizing effect of metal ions on the stability of ligands like Cu(II) and Zn(II) with amino acid complex formation.
At the equilibrium free metal and ions are present in the solution, and using the different electrometric techniques as described determines its stability constant.
This method is based upon the titration method or follows its principle. A stranded acid-base solution used as titrate and which is titrated, it may be strong base or strong acid follows as potentiometrically. The concentration of solution using 103− M does not decomposed during the reaction process, and this method is useful for protonated and nonprotonated ligands.
This is the graphic method used to determine the stability constant in producing metal complex formation by plotting a polarograph between the absences of substances and the presence of substances. During the complex formation, the presence of metal ions produced a shift in the half-wave potential in the solution.
If a complex is relatively slow to form and also decomposes at measurable rate, it is possible, in favorable situations, to determine the equilibrium constant.
This involves the study of the equilibrium constant of slow complex formation reactions. The use of tracer technique is extremely useful for determining the concentrations of dissociation products of the coordination compound.
This method is based on the study of the effect of an equilibrium concentration of some ions on the function at a definite organ of a living organism. The equilibrium concentration of the ion studied may be determined by the action of this organ in systems with complex formation.
The solution of 25 ml is adopted by preparing at the 1.0 × 10−5 M ligand or 1.0 × 10−5 M concentration and 1.0 × 10−5 M for the metal ion:
The solutions containing the metal ions were considered both at a pH sufficiently high to give almost complete complexation and at a pH value selected in order to obtain an equilibrium system of ligand and complexes.
In order to avoid modification of the spectral behavior of the ligand due to pH variations, it has been verified that the range of pH considered in all cases does not affect absorbance values. Use the collected pH values adopted for the determinations as well as selected wavelengths. The ionic strengths calculated from the composition of solutions allowed activity coefficient corrections. Absorbance values were determined at wavelengths in the range 430–700 nm, every 2 nm.
For a successive metal complex formation, use this method. If ligand is protonate and the produced complex has maximum number of donate atoms of ligands, a selective light is absorbed by this complex, while for determination of stability constant, it is just known about the composition of formed species.
Bjerrum (1941) used the method stepwise addition of the ligands to coordination sphere for the formation of complex. So, complex metal–ligand-n forms as the following steps [22]. The equilibrium constants, K1, K2, K3, … Kn are called stepwise stability constants. The formation of the complex metal-ligandn may also be expressed by the following steps and equilibrium constants.
Where:
M = central metal cation
L = monodentate ligand
N = maximum coordination number for the metal ion M for the ligand
If a complex ion is slow to reach equilibrium, it is often possible to apply the method of isotopic dilution to determine the equilibrium concentration of one or more of the species. Most often radioactive isotopes are used.
This method was extensively used by Werner and others to study metal complexes. In the case of a series of complexes of Co(III) and Pt(IV), Werner assigned the correct formulae on the basis of their molar conductance values measured in freshly prepared dilute solutions. In some cases, the conductance of the solution increased with time due to a chemical change, e.g.,
It is concluded that the information presented is very important to determine the stability constant of the ligand metal complexes. Some methods like spectrophotometric method, Bjerrum’s method, distribution method, ion exchange method, electrometric techniques, and potentiometric method have a huge contribution in quantitative analysis by easily finding the stability constants of metal complexes in aqueous solutions.
All the authors thank the Library of University of Delhi for reference books, journals, etc. which helped us a lot in reviewing the chapter.
IntechOpen publishes different types of publications
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