A Critical Review of Integration Analysis of Microbial Electrosynthesis (MES) Systems with Waste

Biorefineries for the Production of Biofuel and Chemical from Reuse of CO2

Jhuma Sadhukhan1*, Jon Lloyd4, Keith Scott3, Giuliano C Premier5, Eileen Yu3, Tom Curtis2 and Ian

Head2

1Centre for Environmental Strategy, University of Surrey, Guildford, Surrey, GU2 7XH, UK.

2School of Civil Engineering and Geosciences, Newcastle University, Newcastle upon Tyne, Tyne and

Wear NE1 7RU, UK.

3School of Chemical Engineering and Advanced Materials, Newcastle University, Newcastle upon Tyne,

Tyne and Wear NE1 7RU, UK.

4Manchester Geomicrobiology Group, The University of Manchester, Oxford Road Manchester, M13

9PL, UK.

5Sustainable Environment Research Centre (SERC), Faculty of Computing, Engineering and Science

University of South Wales, Pontypridd, Mid-Glamorgan, CF37 1DL, UK.

Abstract

Despite some success with microbial fuel cells and microbial electrolysis cells in recovering resources

from wastes, challenges with their scale and yield need to be resolved. Waste streams from biorefineries

e.g. bioethanol and biodiesel plants and wastewaters are plausible substrates for microbial

electrosynthesis (MES). MES integration can help biorefineries achieving the full polygeneration

potentials, i.e. recovery of metals turning apparently pollutants from biorefineries into resources,

production of biofuels and chemicals from reuse of CO2 and clean water. Symbiotic integration between

the two systems can attain an economic and environmental upside of the overall system. We envision that

electrochemical technologies and waste biorefineries can be integrated for increased efficiency and

competitiveness with stillage released from the latter process used in the former as feedstock and energy

resource recovered from the former used in the latter. Such symbiotic integration can avoid loss of

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material and energy from waste streams, thereby increasing the overall efficiency, economics and

environmental performance that would serve towards delivering the common goals from both the

systems. We present an insightful overview of the sources of organic wastes from biorefineries for

integration with MES, anodic and cathodic substrates and biocatalysts. In addition, a generic and effective

reaction and thermodynamic modelling framework for the MES has been given for the first time. The

model is able to predict multi-component physico-chemical behaviour, technical feasibility and best

configuration and conditions of the MES for resource recovery from waste streams.

Keywords: lignocellulosic biorefinery, Gibbs free energy minimisation, thermodynamic

optimisation, bioenergy, bioelectrochemistry, resource recovery from waste, MFC, BES

* Author/s to whom correspondence should be addressed: E-mail: jhumasadhukhan@gmail.com; Phone: +44 (0)1483 686642.

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1. Introduction

In the most advanced sense, a biorefinery is a facility with integrated, efficient and flexible conversion of

biomass feedstocks, through a combination of physical, chemical, biochemical and thermochemical

processes, into multiple products [1,2]. The concept was developed by an analogy to the complex crude

oil refineries adopting the process engineering principles applied in their designs, such as feedstock

fractionation, multiple value-added productions, process flexibility and integration [1]. This definition of

biorefinery evolved from the earlier works of the National Renewable Energy Laboratory (NREL) [3] and

the Department of Energy (DOE) of the USA [4]. The products to target from lignocellulosic materials

are the main question for a biorefinery system. Biorefineries are often ambiguously inferred to bioethanol

or biodiesel production plants, which may or may not have accompanying combined heat and power

(CHP) generation [5,6]. The most significant change occurred from 19th century through 1970s (when

major uphill in the production of biofuel was observed) to today, is the use of lignocelluloses or waste

materials as the feedstock [5]. However, biofuel plants are not economically feasible without subsides or

guaranteed return on investment, unless high grade valuable materials from waste are coproduced. To

name a few of the regulatory frameworks that support biofuel development are the “2020 climate and

energy strategy” and the Renewable Energy Directive (RED) in Europe, through which the biofuel blend

has been mandated with the target biofuel blend by 10% (by energy) by 2020 [7]. The Fuel Quality

Directive introduced a mandatory target of a 6% reduction, by 2020, in the greenhouse gas (GHG)

intensity of fuels used in road transport and non-road mobile machinery [7]. The economic return on

investment of biofuel plants however fundamentally depends on the ability of coproduction of high grade

valuable materials, spear-heading of which is the food and pharmaceutical ingredient, followed by

composite, polymer, chemical, hydrogen, respectively. Biofuel and CHP though have high demands and

production volumes, but have lower market values, compared to chemical products. 5.6% growth per year

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in global chemical demand is expected, while China, India, Asia and Africa with expected gross domestic

product (GDP) growth can have more than 10% growth per year in chemical demand [8]. Fig. 1 shows

the targeted products for biorefineries [1]. The products at the top of the triangle have high value, but low

market demand, while the base products have low value, but high demand and volume of production. A

recent report disclosed that biofuel production should not be conflicted with non-fuel added-value uses of

plant / agricultural / forestry residues, especially where there are markets for healthcare and food products

[9]. Thus, innovative biorefineries can be designed to produce numerous high grade valuable materials

alongside energy products, biofuel and CHP, to boost the overall economic gains of the biorefineries and

from wastes [1]. The state of the art biofuel plants have a number of stillage streams, e.g. CO2 from

fermentation [10,11,12], dilute glycerol and waste streams from biodiesel plant [13,14] and effluents [15]

that are being disposed of to the environment. Microbial electrosynthesis (MES) processes are suitable for

sustainable conversion of stillage streams from industrial systems into added value materials

[16,17,18,19]. Thus, the stillage streams from biorefineries can be a substrate for MES to produce added

value products. The coupled system can achieve an overall sustainability, encompassing economic,

environmental, social and technical (scale and efficiency) aspects. Thus, process integration concept is

urgently needed for the sector to take complementary advantages and widen the product portfolio. To

achieve the objective, integrated innovative conceptual process flowsheets and models for integration of

MES are presented and discussed here. We envision that MES processes and waste biorefineries can be

integrated for increased resource recovery efficiency from wastes: 1) agricultural and forestry residues

and energy crops: wood, short rotation coppice, poplar, switchgrass and miscanthus; 2) grass: leaves,

green plant materials, grass silage, empty fruit bunch, immature cereals; 3) oily residues: waste cooking

oils and animal fat; 4) aquatic biomass: algae and seaweed; and 5) organic residues: municipal waste,

manure and sewage [1]. Such symbiotic or synergistic integration can avoid loss of material and energy

from waste streams, thereby increasing the overall efficiency, economics and environmental performance

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that would serve towards delivering the common goals of both systems. We envision that their relatively

small scales would work in each-others favour and be complementary that could give a momentum in

commercialization of these technologies.

Earlier works have considered reuse of CO2 rich streams in chemical reactions to produce syngas,

hydrogen, formic acid, methane, ethylene, methanol, dimethyl ether, urea, Fischer-Tropsch liquid,

succinic acid, etc. as well as materials, such as epoxides acetals and orthoesters as important precursors to

many polymers and carbonates through mineralisation reactions for construction applications [20,21].

CO2 as a reactant in Sabatier’s reaction for methane formation, in reactions to produce calcite and succinic

acid and CO2 reuse for the growth of algae to produce biofuels, e.g. bioethanol and biodiesel have been

analysed for techno-economic feasibility. But, this is the first review paper on CO2 reduction reactions

using MES. The relevant anode and cathode reactions, their Gibbs free energies and the Gibbs free energy

of formations of the species participating in these reactions [22], along with the calculations of the Gibbs

free energies of reactions are given in Supplementary information 1. 63 anodic and 72 cathodic reactions

of metabolism and 9 metabolic pathways have been collated for future modelling for assessing technical

feasibility / thermodynamic spontaneity (or constraint) of resource recovery from waste substrates and

combinations of anodic and cathodic reactions using MES.

Bio fuel cells were first performed to generate electricity using organic substrate to grow the bacteria

following the rules of nature [23]. The first microbial electrolysis cell reported to generate hydrogen in

technologically significant quantity dates back to 1970s [24], however, the name “microbial electrolysis

cell” (MEC) was coined only in 2008 [25,26,27,28] after evolving through numerous others such as H-

type electrolysis cell [29], biocatalytic electrolysis cell [30] to mention amongst many others. In recent

times, there have been efforts to homogenize the nomenclature in this area [31,32]. The microbial fuel

cell (MFC) and MEC schematics are depicted in Fig. 2 [26,33]. Since 2010, a paradigm shift has

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happened in the ability to generate organics from CO2 reduction in MES [16]. Apart from organics, MES

can recover functional nanommaterials such as nanocatalaysts, quantum dots and nanomagnets [34].

Amongst the earlier developments in MES, electromethanogenesis is a process to reduce carbon dioxide

in the cathode chamber to produce methane [35]. In principle, recovery of aromatic compounds and cyclic

alkanes from organic wastes is possible. Similar to the cathode chamber, the anode chamber can also

generate a number of products, bioethanol or biofuel or bulk chemical, however, relying on the specific

substrate, e.g. glucose, acetate, glycerol, etc. [22]. Also, polymers can be decomposed into pyruvate,

formate and fatty acids by microbial oxidation in the anode chamber. Fig. 3 shows a generic MES

schematic with the range of cathode and anode substrates and products. The substrates can be similar to

those reported for MFC: stillage streams from fermentation, wastewater treatment, biodiesel plants, sugar

rich streams from lignocellulose fractionation, hydrogenation processes, etc. [36]. Anode can be catalysed

by microorganisms or immobilised with enzymes, while cathode can be catalysed by chemical or

microbial catalysts (microorganisms or enzyme immobilization). All such systems are referred as MES in

this paper. Bioelectrochemical oxidation of anode substrates generates carbon dioxide and hydrogen

specie or carbonic acid and hydrogen. A typical anode reaction results in hydrogen specie and electron

generation. Hydrogen can pass through the electrolyte (with or without a proton exchange membrane) to

cathode by the application of external voltage. With the supply of renewable electricity, wind turbines,

photovoltaic cells and hydropower, etc., MES is potentially an important technology for sustainable

resource recovery or polygeneration of biofuels, hydrogen or electricity, chemicals and materials, from

waste [37,38,39]. It is evident that the research interest in this area is truly global with increasing number

of published studies from researchers coming from different countries [18,35]. However, to achieve the

full potential of polygeneration and successful commercial development of MES technologies, new

modelling tools are desperately needed. Although there have already been a number of papers published

on substrates [36,40] and microorganisms [41,42] and electrode material selections [17], most have

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focused on design point performance evaluation (or a particular experimental set up) rather than

optimisation of design and operations and modelling for systematic integration with industrial flowsheets

and scale-up. Systems modelling combined with thermodynamic correlations can be a valuable tool to

predict multi-component physico-chemical behaviour, providing indications of technical feasibility,

identifying ways to improve efficiency and determining the best configuration and conditions for

inherently integrated MES for resource recovery from waste within biorefinery systems [43,44,45]. This

paper makes several novel contributions.

1) Integrated biorefinery and MES process conceptual flowsheets;

2) A plethora of added value product generation options from MES, and integrated biorefinery and

MES process flowsheets;

3) Theoretical modelling framework for MES systems from the fundamental basis of the Gibbs free

energy minimisation or thermodynamic optimisation of biologically relevant reactions to produce

biofuels, hydrogen, energy and chemical products.

4) A market- and sustainability- driven strategy to speed up development of MES combining

metabolic flux analysis, metabolic pathway analysis, thermodynamic optimisation, process

simulation, dynamics and control experimentation.

The paper has been structured as follows. Section 2 gives an insightful overview of novel integrated

biorefinery and MES process schemes. Section 3 gives an overview of relevant CO2 reuse or reduction

reactions. Sections 4-5 discuss the thermodynamic model formulation and future directions in integrated

biorefinery and MES research. Section 6 draws on conclusions

2. Integrated biorefinery and MES conceptual flowsheets

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Biorefineries produce a wide variety of process wastes containing degradable organics that can make

good substrates for MES, specifically the anode. These wastes can be broadly divided into stillage

streams from i) bioethanol plant; ii) lignocellulose fractionation based biorefinery; iii) biodiesel plant; and

iv) sludge and wastewater substrates, discussed as follows. Alongside insightful integration principles

between biorefineries and MES processes are illustrated. Further, some important developments in anode

bacteria have been indicated.

Bioethanol plant: Bioethanol production from sugarcane in Brazil only utilises 38% of the cane energy,

12% is discharged as vinasse and 50% remains in the bagasse [46]. The vinasse is the effluent containing

glycerol, yeast nutrients, cell debris and residual ethanol. In the United States, another large bioethanol

producer, corn or corn stover is used for starch extraction with the majority produced by dry milling and

only some by wet milling, which is followed by fermentation of the starch derived from them into

bioethanol production [47]. The residue generated from dry and wet milling processes is quite similar in

terms of constituents containing carbohydrate, glycerol and ethanol [48]. All these stillage streams make

suitable substrates for MES.

Lignocellulose fractionation followed by fermentation based biorefinery: Lignocelluloses are a complex

mixture of structural polysaccharides, mainly cellulose and hemicellulose, encased by polyphenolic lignin

and are the main constituent of plant cell-wall material [49]. Lignocellulosic wastes can not be directly

utilised in microbial oxidation in MES anode as lignin is recalcitrant and is resistant to hydrolysis, unlike

polysaccharides and sugars. Lignin encasing cellulose in cell walls provides cell walls rigidity and

strength against microbial decomposition [1]. Extraction of lignin thus reduces the cost of production of

cellulosic products as well as increases utilisation using MES. Hence, lignocellulose should be

fractionated or pretreated to recover cellulose and some hemicelluloses, from lignin, before being fed to

the anode chamber of MES process. Pretreatment processes include mechanical, physical: steam

explosion and chemical processes: organosolv (using solvent, in which lignin and some hemicelluloses

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are soluble, thus separating from celluloses), hydrothermal operation under supercritical operation and in

alkaline, pH neutral and acid media etc. [50,51,52]. Pretreatment liberates cellulose microfibrills can be

easily converted into glucose by enzymatic hydrolysis, followed by ethanol and chemical productions [1].

Alternatively, cellulose microfibrills can be used to form continuous phase (matrix) of composite

materials [53,54,55]. Hemicellulose (C5 sugars) upon further processing: alkaline extraction, alkaline

peroxide extraction, hot water/steam extraction and chemical conversion etc. gives rise to a number of

chemicals, xylite, furfural, 5-hydroxymethylfurfural, L-arabinose, furan resins and nylons, etc. [1]. Lignin

can be processed into wood adhesives, epoxy resins, fuel additives, benzene-toluene-xylene, binders,

carbon fiber, polyurethanes, polyolefins and specialty phenolics for high value applications, such as

pharmaceuticals and fragrances (vanillin) [1]. These various routes to polygeneration from wastes (i.e.

concept of multi-platform and multi-product biorefinery systems) are illustrated in Fig. 4 [1].

Fig. 5 shows plausible principles for the integration of MES process with bioethanol plants. In route 1 in

Fig. 5, some pretreated lignocellulosic feedstock is diverted to produce enzyme and yeast onsite to be

utilised in solid state fermentation of the rest of the pretreated lignocellulose producing bioethanol

[56,57]. Research has shown that producing the enzyme and yeast on-site from the same biomass saves

on operating cost and makes an economically feasible case. The cases were drawn from USA [56] and

EU and Malaysia [57]. The liquid stillage streams from bioethanol purification section (consisting of

distillation, molecular sieve adsorption and dehydration) are the substrates in MES. The residual solids

from the bioethanol purification section primarily consisting of lignin in the configuration shown are

combusted for CHP generation. However, a more economic value generation route is catalytic

hydrodeoxygenation (HDO) [58] of lignin into functional phenolics, vanillin, syringol, etc. shown in Fig.

4 [1], needing hydrogen that can be sourced from MEC. This way, the two processes, bioethanol

purification and MEC are integrated in both ways and additional economic value can be generated from

lignin valorisation. The bioethanol plant usually has net output electricity generation for export [56,57].

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Hence, lignin can be diverted from electricity generation to HDO, increasing added value product

generation and lowering electricity generation until no external electricity supply is needed and energy

need for the site is met. This example shows replacing low value energy generation by added value

chemical production (Fig. 1).

Route 2 in Fig. 5 leads to C6, C5 and lignin platforms, which would then have a plethora of choices of

products, as illustrated in Fig. 4. The two immediate integration synergies between biorefinery and MES

processes can be identified: C6 and C5 sugars are used in fermentation to produce bioethanol (exploring

the integration synergies in route 1) and C6 and C5 sugars utilisation as substrates for product generation

using MES. The anode can microbially decompose glucose rich stream by glucose metabolism Entner-

Doudoroff pathway into carbon dioxide, hydrogen species and electrons. The cathode either chemically or

microbially catalysed, can generate electricity and water in open to air configuration (MFC) or hydrogen

in anaerobic condition by application of voltage in an MEC (12 moles of hydrogen can be generated from

1 mole of glucose). Alternatively, carbon dioxide and hydrogen from the anode can be utilised to generate

biofuel or chemical, e.g. glucose reduced into glutamate, propionate and butanol, from the anaerobic

cathode in MES. Sugars are the most common substrates in bioelectrochemical systems [59]. The

versatile Shawanella species for example, a functionally electrogenic niche organisms, has been shown to

catabolise a variety of carbon source materials (aquatic debris) typical of their natural environments. A

richer variety of carbon utilising pathways was available than had been known for Shewanella oneidensis

MR-1 [60]. Cofactor expression by various engineered approaches, altering the redox chemistry [61],

could provide tuned redox coupling, or enzyme expression (in e.g. Saccharomyces cerevisiae) for

conversion of lignocellulosic substrates to monosaccharides [62]. Gut bacteria are primarily responsible

for metabolite products. Though mixed cultures are more likely to be used, there are finite families of

naturally available gut bacteria for targeted products, e.g. Butyrivibrio spp and Roseburia spp for

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butyrate; methanogens for methane; acetogens for acetate; and Bacteroides spp and Prevotella spp for

propionate [49].

Biodiesel plant: The biodiesel industry is one of the most prominent biofuel industries in Europe,

produces wastes containing glycerol, residual fatty acids and alcohols. Their conventional purification

technologies are energy intensive [13,14]. A comprehensive energy and greenhouse gas emission analysis

of a cradle to gate biodiesel production system (from raw material extraction upto the production gate)

has been illustrated that concludes the following [13,14].

Per 100 mass units of biodiesel production via conventional methods (e.g. transesterification of waste oils

followed by distillation):

1. 5.3 mass units of oily waste are produced and

2. 10.7 mass units of glycerol are produced;

3. 466 MJ of energy is consumed per 100 kg biodiesel produced

4. 12% of the total energy consumed is spent in the product recovery section.

The energy lost can instead be recovered in the form of useful products and energy vectors by MES. Fig.

6 shows plausible integration schematics of MES with existing biodiesel plant utilising waste oils and oily

residues. The anode microbially oxidises glycerol rich stream into bioethanol, hydrogen species and

electrons. The prokaryotic pathway using Entrerobacteriaceae species primarily results in bioethanol

product from the anode. The cathode, either chemically or microbially catalysed, generates electricity and

water in open to air configurations of MFC or hydrogen generation by application of voltage in anaerobic

condition in an MEC (1 mole of hydrogen is produced per mole of glycerol decomposed). Alternatively,

carbon dioxide and hydrogen from anode can be utilised in combination with or without additional waste

streams as substrate sourced from other industrial systems (e.g. Fig. 5) to generate biofuel or chemical

from anaerobic cathode in MES. Oligochemical industrial processes carry out epoxidation, sulfonation,

ethoxylation, hydrogenation, etc. of fats and oils from plant and animal sources to produce chemicals,

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while generating oil-laden wastes suitable as substrate for MES [37]. Food processing industries are

another example of producing a wide variety of process wastes containing degradable organics [63].

A case of mass balance and productivities of the integrated flowsheet shown in Fig. 6 is illustrated in the

“Supplementary material on biodiesel process flowsheet synthesis and hypothesis for MES creation”.

Sludge and wastewater substrates: In the last century, the activated sludge process has been the mainstay

of wastewater treatment. However, it is a very energy intensive process, with approximately 0.5 kWh

electrical energy consumed in treating 1 m3 municipal wastewater and the total electricity consumption

for wastewater treatment in the USA is 3% of the total energy usage in the USA [37,64]. Wastewater of

low strength is suitable for energy generations, due to low concentration of inhibitory substances, e.g.

ammonia [65]. Amongst the other wastewater streams, starch processing wastewater containing

carbohydrate (2-3.5 g l-1) and starch (1.5-3 g l-1) also makes a good anode substrate [66].

A membrane electrolysis process involves sending the N rich stream through an anode, ammonium moves

as a cation towards the cathode, where it is converted to ammonia by virtue of the high local pH [67]. The

ammonia volatilises together with cathodically generated hydrogen gas. Constituent metals, e.g. K, are

also recovered from the electrochemical extraction process. The membrane electrolysis process can be

integrated downstream to anaerobic digester (AD). The AD effluent free of ammonium can be recycled

back to the AD reactor to boost the biogas production, and to obtain a concentrated effluent stream, easier

for releasing the phosphate and remaining N, and K fertilisers in marketable pellet forms [68]. Thus the

integrated process offers a prospect of high-grade, valuable multi-product generations. Furthermore,

resulting H2/NH3 from the membrane electrolysis process can be reacted to synthesize amines or

alternatively recover NH3 and use H2 in a secondary process. The latter can be the production of methane

(delivering an enriched biogas stream >90 vol% methane this can be used as biomethane for injection into

the gas grid) or carboxylates using CO2 offgases from other processes, e.g. fermentation, giving rise to an

integrated multi-site biorefinery (e.g. AD, fermentation and membrane electrolysis process integration.

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The options are shown in Fig. 7. Energy, and water recovery is an important aspect of sustainable

manufacturing. Micro-, ultra-, and nano-filtration (MF / UF / NF), and reverse osmosis (RO) processes,

downstream of the AD process can be coupled to enhance release, and recovery of nutrients, thus

generating pure water, and integration with reverse electrodialysis (RED) / fuel cells (FC) using a part of

the biogas for energy recovery within the integrated systems [38,69].

Biological conversion of organic wastes (sludges, animal waste, food waste, vegetal waste, effluents, and

biological waste [70]) involves four fundamental phenomena: hydrolysis, fermentation, acetogenesis, and

methanogenesis. Diversion to the production of a suitable precursor via any route is possible by metabolic

pathway analysis, metabolic flux analysis and metabolic engineering and control, which should be

pursued for reporting of more meaningful results.

Incorporating all four interlinked microbial conversion steps leads on to AD currently aimed at optimising

biogas production of biomethane nature (>90% by volume) by increasing organic loading rate, and

methane and energy recovery, and suppressing acetogenesis (e.g. there are 220 installations reported in

the UK [71]). Acetogenesis on the other hand leads to added value volatile fatty acid production, e.g.

acetate, propionate, butyrate and caproate and their accumulation inhibits methanogenesis. Shortening the

solid retention time and increasing the temperature are effective strategies for driving microbial

communities towards controlled production of high levels of specific volatile fatty acids [72]that can

generate much higher value for AD operational industries.

Anodic catalysts: Extensive reviews of substrates used in anodic oxidation reactions in microbial cells

that have potential in product generation are available. Electrogenic bacteria used in anodes include:

Geobacter sulfurreducens [73,74] and Shewanella oneidensis [75], which are capable of extracellular

electron transfer [76,77,78]. However, the substrate fed to an anode under non-sterile conditions, as

would be expected with biorefinery waste streams, influences not only the bacterial community formation

in the anode biofilm, but also power density and Coulombic efficiency as well as recovery efficiency of

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metals, nutrients, chemicals or biofuels [79]. Immobilised enzyme catalysed bio fuel or electrolysis cells

on the other hand suffer from enzyme instability and lower electron transfer rate and enzyme loading

[80,81]. Whole microorganisms offer added advantages, self-generation and adaptation to various

substrates and desired productivity. The key transfer mechanism is extracellular electron transfer by

microorganisms, which has to be made efficient. In some cases this can be affected without diffusion of a

mobile redox component into and out of the cell and from or towards an insoluble electron donor or

acceptor [82]. An indirect method of electron transport involves the production of electron shuttles such

as phenazines, which are formed as secondary metabolites by organisms [82,83] or primary metabolites

such as flavins [84,85] as well as humic substances not produced by the cell. Rabaey and Rozendal

provide an excellent review on the mechanisms of direct and indirect transfer in electrogenic

microorganisms [16]. The electrogenic microorganisms are much less prevalent for anodes being fed non-

sterile waste streams as substrate. They may be more relevant in clean cathode-based processes.

3. Cathodic metal and CO2 reduction process and substrates

Cathodic processes using organic substrates in MES to reduce CO2 to produce targeted products are at an

early stage of development. Industrial, municipal and agricultural wastewaters are potential sources of

metals, acids, bases and salts, which could be recovered, while chemicals and biofuels could be

synthesised by CO2 reuse in electrochemical reactions in the cathode [86]. Apart from the potential metal

recovery by MES, Lu et al. also discussed the role of metal ions in enhancing the performance of MES

[87]. With increasing metal ions concentration the conductivity of the electrolyte was increased and so is

the desalination and biocatalyst performance, lowering the internal resistance.

The inherent challenge to sustainable resource recovery is to develop a strategy that is less destructive

(i.e. recovery of constituents of a substrate at milder and safer conditions), disruptive (easy to integrate

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with existing processes) and game changing. Conventional methods, e.g. metal recovery technology from

wastewater using chemical precipitation, filtration and solvent extraction, have low efficacy, high start-up

or operating costs and low metal selectivity. They can also cause secondary pollution from metal enriched

sludge, from which it may not be technically feasible to recover metals. The flow of current in such cells

can also enable selective ionic movement to recover salts, acid and base using electrodialysis and electro-

hydrolysis respectively [88]. Further efforts could be in the synthesis of functional nano-scale materials

ranging from catalysts to novel inorganic antimicrobials, nanomagnets, remediation agents and quantum

dots for electronic and optical devices [89].

Earlier works considered CO2 as a reactant in chemical reactions to products [21]. Further, methods to

harness reducing power from wastewater, possibly supplemented from renewable energy sources, can

also be developed for the synthesis of chemicals and biofuels from reuse of CO2. CO2 is believed to

participate in the cathodic reduction reactions via HCO3−¿ ¿ or higher chain carboxylic acids. Such relevant

reactions that have been proven at lab scale are shown here. In terms of the thermodynamic spontaneity,

the following electron-accepting, hydrogen consuming or hydrogenation reactions and CO2 reuse in the

form of HCO3−¿ ¿ or carboxylation from energy metabolism via C1-C2 molecule synthesis at the cathode,

are shown [22].

HCO3−¿+H +¿+4 H 2→CH 4+3H 2O ¿ ¿ ∆ Gr ,cathode

o'

=−135.6 kJ

2 HCO3−¿+2 H+¿+4 H 2→ CH3COOH+4 H 2O ¿ ¿ ∆ Gr ,cathode

o'

=−64.6 kJ

HCO3−¿+H +¿+3 H2 →CH3 OH+2 H 2O ¿ ¿ ∆ Gr ,cathode

o'

=−23 kJ

HCO3−¿+H +¿+2 H2 →HCHO +2 H 2O ¿ ¿ ∆ Gr ,cathode

o'

=21.8 kJ

HCO3−¿+H +¿+H 2→ HCOOH+H 2O ¿¿ ∆ Gr ,cathode

o'

=38.5 kJ

∆ Gr ,cathodeo'

is the Gibbs free energy for the cathode side reaction under standard conditions (25oC

temperature and 1 atm pressure) and pH 7.

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The starting point should thus be the identification of chemicals that can be sourced from a waste stream,

from which the processing steps that present the closest match to their theoretical recovery limits, can be

defined. This was further evidenced in a study of 20 different valuable products screened from anaerobic

electrically enhanced fermentation [90]. It was found that an increase in a product formation by electrical

enhancement is not as much dependent as on the metabolic pathway producing it. The compounds studied

were those produced at an industrial scale such as succinic acid, lysine and diaminopentane as well as

new bio-commodities such as isoprene, para-hydroxybenzoic acid and para-aminobenzoic acid, etc.

Furthermore, it was shown that electron transport mechanism has an influence on biomass and product

yields. Future models in this area should thus include electron transport and energy conservation

equations relating to metabolic pathways. Furthermore, if a robust model can be developed, it can be used

for validation against experimental performance and optimisation of configurations and operability to

achieve targeted product formations. Some more examples of successful production of products using

MES at lab scale are as follows.

Wheat bran, sugar cane bagasse, coffee husk, pineapple waste and carrot processing waste amongst

others, are sources of citric acid, a suitable anode substrate for undergoing the reaction in equation 1. An

example follows: Solid state fermentation (combined saccharification and fermentation) of agricultural

residues, using Aspergillus niger on an amberlite inert support [91], gives citric acid in a manner free from

heavy metal inhibition [92]. The citric acid formed is a useful anode substrate for microbial oxidation into

succinic acid, carbonic acid and proton generation through the citric acid cycle. Succinic acid can be

separated from the anode chamber as a product. The proton can be reduced to hydrogen and recovered in

the cathode chamber in MEC. Alternatively, the following reaction in the cathode chamber leads to the

production and recovery of formic acid in MES.

HCO3−¿+H +¿+H 2→ HCOOH+H 2O ¿¿

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Similarly, acetic, propionic, butyric, lactic, acrylic, malic and fumaric acids can be generated from α-keto

acids (e.g. pyruvate-), α,β-unsaturated acids and hydroxy acids as potential substrates in the cathode [93].

Recently, medium chain fatty acids such as caproate and caprylate were produced from acetate at a

biocathode using mixed microbial cultures (where Clostridium kluyveri was the predominant

microorganism) [40]. The maximum concentrations of reduced organics from 100 mM acetic acid were

739 mg l-1 for caproate, 263 mg l-1 for butyrate, 36 mg l-1 for caprylate and 27 mg l-1 for ethanol. The

cathode reactions to caproate and butyrate are as follows:

3C2 H3O2−¿+2H +¿+4 H 2→Caproate¿ ¿¿ ∆ Gr ,cathode

o'

=−96.6 kJ

2 C2 H 3O2−¿+H +¿+2 H2 →Butyrate ¿¿¿ ∆ Gr ,cathode

o'

=−48.3 kJ

These compounds are liquid at room temperature which makes the product recovery relatively easy.

Broadly, homoacetogenesis by Clostridium thermoaceticum converting hydrogen and carbon dioxide into

acetate; succinate formation from glycerol by Actinobacillus succinogenes; reverse β oxidation for chain

elongation of ethanol and acetate to n-butyrate; and ethanol and n-butyrate to n-caproate by Clostridium

kluyveri are proven cathode carboxylation reactions [94].

4 H2+2CO2→ C2 H 3O2−¿+H +¿+2 H2 O ∆Gr ,cathode

o'=−94.96kJ ¿ ¿

Glycerol+CO2 → Succinate2−¿+2 H +¿+H2 O ∆Gr ,cathodeo'

=−44.5kJ ¿¿ Ethanol+ Acetate−¿ →Butyrate−¿+H 2O ∆Gr , cathodeo'

=−193kJ ¿ ¿

Ethanol+Butyrate−¿ →Caproate−¿+H2O ∆ Gr ,cathodeo'

=−194 kJ ¿¿

The ability of microorganisms to use electrons donated from an electrode to reduce CO2 to simple organic

acids such as acetic acid using the acetogenic microorganism Sporomusa ovata proceeding through

acetyl-coenzyme A (CoA) is proven [42]. Acetyl-CoA is a central intermediate (Wood-Ljungdahl

pathway) for the production of a diverse suit of organic molecules including those relevant to biofuels and

platform chemical, storing electrical energy in chemical bonds.

The microbial processes can be engineered for optimal microbial growth to alter length, functionality, the

degree of fatty acid saturation and branching to maximise fuel effectiveness. In contrast to fatty acids, 17

higher alcohols have higher energy contents. Butanol, a key component of gasoline contains 84% of its

energy content and is immiscible with water [95]. These molecules are easy to use as drop-in fuels in

existing transportation fuel infrastructure and can be used as 100% pure. Engineered microbial

technologies for the synthesis of higher alcohols (e.g. butanol, isobutanol) as biofuels and copolyesters

(e.g. poly(3-hydroxybutyrate-co-4-hydroxybutyrate) as biopolymers, are reaching the pilot scale of

development [96,97,98]. Comparing these technologies to engineered microbial processes that use

exogenous electron donors to supply electrons in-situ within MES reactor, several advantages can be

described: (i) no infrastructure for the supply of hydrogen is required, (ii) in-situ electron supply at the

right cathode potential might result in locally high hydrogen partial pressures, which are favorable for the

reaction, and (iii) the electron donor is renewable when renewable electricity is used [40].

Cathodic catalysts: The cathode reduction process can be affected by a chemical catalytic process (a

metal catalyst at the cathode) as opposed to a microbial oxidation process in the anode in MFC / MEC, or

indeed microbially catalysed reduction at the cathode. The reduction of carbon dioxide in aqueous

solution using a metal catalyst has been demonstrated [99]. The use of ruthenium [100], gallium arsenide

[101] and RuO2-TiO2 mixed cathodes [102] have been reported for methanol synthesis through carbon

dioxide reduction. However, all these catalysts have shown instability compared to enzymatic fixation of

carbon dioxide in organic molecules. For example, the electrochemical synthesis of methanol from CO2

reduction has been demonstrated using formate dehydrogenase and methanol dehydrogenase [103]. The

use of enzymes in electro-reductive fixation of CO2 to yield isocitrate from α-oxoglutaric acid and malate

from pyruvic acid has been demonstrated [99]. Such enzymatic electro-reductive fixation of CO2 is

possible using a photochemical reaction in the cathode and shows higher energy efficiency compared to

corresponding metal cathodes with and without metallocomplexes as the electrocatalysts [103,104,105].

In recent times, there has been an upsurge in the application of microorganisms as opposed to enzymes,

specifically for resource recovery from wastes in MES. This is because the self-renewing microbial

18

growth which is almost unavoidable in the presence of waste substrates and which extracted enzymes

cannot achieve [106]. Laccase as an isolated enzyme has been studied for oxygen reduction in MFC by its

immobilisation on the cathode [107]. Many microorganisms, such as Shewanella putrefaciens,

Pseudomonas aeruginosa, Acinetobacter calcoaceticus, Acidithiobacillus ferrooxidans, Chlamydomonas

reinhardtii were also identified as biocatalyst for oxygen reduction in MFC cathode [108,109]. The

known microorganisms, which have the ability to take up electrons from an electrode and use them in the

production of H2, formate or acetate, include most Gram-negative bacteria such the Shewanella and

Geobacter species, and some Gram-positive bacteria. The catalyst performance in terms of open circuit

potential was found to be in the following order: laccase > microorganisms > Pt catalyst [106]. The

different catalysts were loaded on identical plain carbon cloth electrodes of MFC. Apparently, the

laccase-immobilised cathode direct electron transfer can produce a potential much closer to the

thermodynamic equilibrium potential of the oxygen reduction reaction, compared to microbial and Pt

catalysed cathodes. The low open circuit potential of the Pt catalyst may be attributed to a lower relative

Pt loading and the formation of PtO on the catalyst surface. However, the maximum power density shows

a different trend: Pt catalyst > laccase > microorganisms, and this is attributed to higher conductivity and

greater affinity of Pt to oxygen. Pioneering researchers in the field agree that the cell configuration,

specific architecture, electrode spacing and internal resistance have a more significant effect on

performance than the type of catalyst for MES. For example, methanogens and some acetogens can utilise

the produced H2 or formate as electron donors for anaerobic reduction of carbon dioxide to produce

methane or to form higher tier organic fuels such as 2,3-butanediol, lactate, butyrate, and butanol [106].

The need to establish the energetic favourability of the processes is of paramount importance for all these

conversions, as the reduction of CO2 / organics proceeds at low redox potentials [16]. In order to assess

whether the MES has all the advantageous compared to metabolic systems, the thermodynamic

correlations to estimate the applied voltage can prove to be useful. Hence, the general equations (i.e. a

19

generic model) [22,43,44,45,110,111,112,113], are discussed to determine the thermodynamic

favourability of the MES reactions.

4. Model formulation and parametric analysis

The anode side oxidation of substrate can be expressed as in equation 1, generating the substrates of

interest for the cathode side.

C x H y O z+(3 x−z )H 2 O→ x HCO3−¿+ wH+¿+w e

−¿+ y+5x −w−2z2 H2¿

¿¿

∀ (3 x−z )>0 , ( y+5 x−w−2 z ) ≥0 ,∧w , x , y , z>0 (equation 1)

The Gibbs free energy (∆ Gr ,anodeo ' ) of the anode reaction in equation 1 can be expressed in terms of the

Gibbs free energy of formation of the species (∆ G f ,io ' ∀i∈HCO3

−¿ , H +¿ ,H 2O ,Cx H yO z¿¿) under standard conditions

(25oC temperature and 1 atm pressure) and pH 7, as shown in equation 2.

∆ Gr ,anodeo ' =x ∆ Gf , HCO3

¿+w ∆ Gf , H¿− (3 x−z ) ∆Gf , H2O

o'−∆G f ,Cx H y O z

o' ¿¿ (equation 2)

By substituting the ∆ G f ,io ' values of HCO3

−¿ , H +¿ , H2 O ¿¿, −586.85 ,−39.9 ,−237.178 kJ

mol of substrate ,

respectively [22], into equation 2, the following expression is obtained for the specific anode reaction

case, generating HCO3−¿ , H +¿, H2 ¿¿. Upon simplification, equation 3 is obtained.

∆ Gr ,anodeo'

(¿ kJmol of substrate

)=−586.85 x−39.9 w+237.178 (3 x−z )−∆ Gf , Cx H y Oz

o '

∆ Gr ,anodeo'

(¿ kJmol of substrate

)=124.684 x−39.9 w−237.178 z−∆ G f ,C x H y O z

o ' (equation 3)

Cathode side reduction of oxygen in MFC results in the formation of water. Hence, the Gibbs free energy

of 0.5 mole of oxygen reduction into 1 mole of water formation is equal to the Gibbs free energy of

formation of 1 mole of water subtracted from the Gibbs free energy of formation of 2 H+¿¿ species under

20

the standard conditions and pH 7 (equation 4a). Note that w number of H+¿¿ specie is responsible for

electricity generation from MFC.

w4

O2+w H+¿+w e−¿= w

2H

2O ¿

¿

∆ Gr ,cathodeo' (¿ kJ

mol of substrate )=−237.178+79.82

w=−78.689 w (equation 4a)

In the case of MEC, the cathode side reduction of H+¿¿ species results in the formation of molecular

hydrogen, as follows. Thus, ∆ Gr ,cathodeo' (¿ kJ

mol of substrate ) results in equation 4b.

w H+¿+we−¿=w

2H

2¿

¿

∆ Gr ,cathodeo' (¿ kJ

mol of substrate )=39.9 w (equation 4b)

Hence, the net energy generation from the MFC and the net energy consumption by the MEC is the

summation of the Gibbs free energies between the cathode reaction and the anode reaction, shown in

equations 5a and 5b, respectively. Negative value of ∆ Gr ,cello ' for MFC indicates that this is an energy

generation from the MFC and positive value indicates energy consumption by the MEC.

∆ Gr ,cello ' =∆ Gr , cathode

o'

+∆ Gr , anodeo'

∆ Gr , MFCo' (¿ kJ

mol of substrate )=124.684 x−118.589w−237.178 z−∆ Gf ,Cx H y O z

o ' (equation 5a)

∆ Gr , MECo' (¿ kJ

mol of substrate )=124.684 x−237.178 z−∆ Gf ,Cx H y O z

o ' (equation 5b)

Equations 5a-b can be presented in terms of 1 eV potential generation from MFC or 1 eV consumption by

MEC as shown in equations 6-7 respectively, from the substrate of C x H y O z formula in the anode.

∆ Gr , MFCo'

(¿ kJ1 electrontransfer

)=124.684 x−118.589 w−237.178 z−∆ Gf , Cx H y Oz

o '

w (equation 6)

∆ Gr , MECo'

(¿ kJ1 electrontransfer

)=124.684 x−237.178 z−∆G f ,C x H yO z

o '

w (equation 7)

21

In the case of MES with cathode reactions for the formation of products, the energy needed must take

account of the Gibbs free energy of electron-accepting hydrogenation or reduction reactions in the

cathode. As an example, for HCO3−¿+H +¿+4 H 2→CH 4+3H 2O ¿ ¿ reaction, the Gibbs free energy of the MES cathode can

be derived from the negative of equation 3, with x=1, w=1 and z=0, as follows [22].

∆ Gr ,cathodeo' (¿ kJ

mol of hydrogen )=−84.784+∆G f ,CH 4

o'

=−135.6 ∆ G f ,CH 4

o ' =−50.8

Thus, as the cathode reaction becomes endogenous, the thermodynamic spontaneity of the MES system

reduces. The methodology can be followed to calculate ∆ Gr ,cathodeo' (¿ kJ

mol of substrate ) and equation 3 can

be applied to calculate ∆ Gr ,anodeo'

(¿ kJmol of substrate

) for different types of substrates in MES reported in

[22]. Thus, ∆ Gr , MESo' (¿ kJ

molof substrate )=∆ Gr , cathodeo'

+∆ Gr , anodeo'

can be estimated for various combinations

of anode and cathode reactions to examine the overall energy performance and feasibility. The

methodology is adaptable for given substrates or waste streams as long as their chemical formulae are

predicted (e.g. by elemental analysis: proximate and ultimate analyses).

The model is further useful to link to economic profitability and environmental

impact analysis. A comparative life cycle analysis will be useful to determine the

most feasible combinations of substrate and target products and anode and

cathode reactions. This will be a novel and smart approach for screening of best

options before experimental based approaches [114]. Without this aspect,

commercialisation of MES will be a long process.

The Gibbs free energy change across the cell under actual conditions prevailing can be obtained from the

molar Gibbs free energy change at standard condition and pH = 7. Equation 8a can be used to estimate the

Gibbs free energy change for MFCs, where oxygen reduction occurs in the cathodic chamber [115].

∆ Gr , MFC=∆ Gr , MFCo'

−RT ln ¿ (equation 8a)22

∆ Gr , MFC is the molar Gibbs free energy change as a function of temperature (T) and pressure (P).

R is the universal gas constant, 8.314 J mol-1 K-1.

[O2] is the partial pressure of oxygen; ¿ is equal to 10−7M/l when pH = 7.

Equation 8b can be used to estimate the Gibbs free energy change for MECs, where H+¿¿ reduction occurs

in the cathodic chamber [115]. [H 2] is the partial pressure of hydrogen.

∆ Gr , MEC=∆ Gr , MECo'

−RT ln ¿ (equation 8b)

A generic thermodynamic equation for the Gibbs free energy change for multi-component systems should

be applied. However, it is necessary to replicate the case in reality as far as possible. A generic

thermodynamic equation for the Gibbs free energy change across the cell under the cell conditions thus

can be applied as shown in equation 9 [1,116].

∆ Gr ,cell=∆ Gr , cello'

+ ∑j=1

Nreact

n j RT ln( n j

nT)−¿∑

j '=1

Npdt

n j' RT ln( n j'

nT)¿ (equation 9)

n j is the stoichiometric number of moles of reactant j in the overall reaction equation of the cell and nT is

the total number of moles of reactants and products in the overall reaction equation of the cell. n j ' is the

stoichiometric number of moles of product j’ in the overall reaction equation of the cell. Nreact is the

total number moles of reactants in the overall reaction equation of the cell and Npdt is the total number of

moles of products in the overall reaction equation of the cell.

The theoretical maximum voltage corresponding to the Gibbs free energy change across the cell is given

by the Nernst equation, shown in equation 10. The Gibbs free energy change is related to the process

operating conditions, in this case, cell temperature, pressure and the difference in pH between the anode

and cathode compartments.

E=−∆ Gr , cell

ne F (equation 10)

23

ne is the number of electrons transferred in the overall reaction of the cell, and F = 96,485 C mol−1 is

Faraday’s constant. For hydrogen generation, thus the adjusted potential required for MEC at 298 K =

39.9× 100096485 = 0.414 V.

The voltage calculated using equation 10 is the theoretical maximum voltage obtained corresponding to

reversible process that results in minimum Gibbs free energy change. However, the actual voltage is less

than the theoretical voltage in MFC and more than the theoretical voltage in MEC. This is due to the three

types of polarisation effects, which are universal to all types of electrochemical cells: activation, ohmic

and concentration potentials in equations 11-16.

Activation overpotentials are a result of resistance to electrochemical reaction kinetics occurring in the

anode and cathode. According to the general Butler–Volmer equation, the respective theoretical

activation overpotentials of the anode and cathode can be calculated as shown in equations 11-12

[1,113,117].

V activation ,anode=2 RTne F sinh−1( i

2 i0 ,anode ) (equation 11)

V activation ,cathode=2RTne F sinh−1( i

2 i0 ,cathode ) (equation 12)

V activation ,anode /cathode is the voltage loss due to activation overpotentials in anode / cathode.

i0 ,anode /ca thode is the anode / cathode exchange current density.

Ohmic overpotentials (V ohmic) are due to the resistance to conduction of ions through the electrolyte,

electrons through the electrodes and current collectors and by contact, resistance between cell

components, shown in equation 13 [1,118].

V ohmic=i( Lelectrolyte

σelectrolyte+

Lanode

σanode+

Lcathode

σcathode+

Linterconnect

σ interconnect) (equation 13)

Lk is the thickness, ∀ k∈{electrolyte , anode , cathode ,interconnect }

24

σ k is the electronic or ionic conductivity in k, ∀ k∈{electrolyte , anode , cathode ,interconnect }, which is a

function of temperature in K shown in equation 14a-b [1,118].

σ k=C 1k

Texp(C 2k

T ) ∀ k∈{anode , cathode ,interconnect } (equation 14a)

σ k=C 1k exp( C 2k

T ) ∀ k∈{electrolyte } (equation 14b)

C 1k and C 2k are the constants.

Concentration overpotentials caused by mass transfer limitations from the substrate and through the

electrode result in further voltage loss, shown in equations 15-16 [118].

V concentration ,anode=−RTne F ln(1− i

il ,anode ) (equation 15)

V concentration ,cathode=−RTne F ln (1− i

il ,cathode ) (equation 16)

V concentration ,anode /cathode is the voltage loss due to concentration overpotentials in anode / cathode.

il ,anode /cathode is the limiting current density of the anode / cathode, assumed constant.

The net voltage thus obtained is the Nernst theoretical voltage (equation 10) minus the voltage losses

(equations 11-16), shown in equation 17 [1,43].

V=E−V activation−V ohmic−V conce ntration=E− RTne F

d1 (equation 17)

where,

d1=2sinh−1( i2 i0 ,anode )+2sinh−1( i

2 i0 ,cathode )+ ine F

RT ( Lelectrolyte

σ electrolyte+

Lanode

σanode+

Lcathode

σcathode+

Linterconnect

σ interconnect)

−ln(1− iil ,anode )−ln(1− i

il ,cathode )

25

In the case of MFCs, the Nernst theoretical voltage and the net voltage, E and V , respectively, with E >

V , are positive, indicating energy generation from MFCs.

In case of MEC, E and V are negative with|V|>|E|, indicating that a higher voltage would be needed by

the MEC than the Nernst theoretical voltage provides.

To determine the conditions for maximum net energy generation (MFC) or minimum net energy

consumption (MEC) by thermodynamic analysis, the activation overpotential is the most important

contributor in decreasing the Nernst theoretical voltage. The activation overpotential is a function of

current density and exchange current density. The higher the current density, exchange current density

and their ratio, the greater is the activation overpotential. This is illustrated in Figs. 8a-b: current densities

in logarithmic (log10) scale on y-axis versus activation overpotentials in linear scale on x-axis. The current

density was varied from 1 to 16 A m-2 for two exchange current densities of 3.33 and 1.67 A m-2. As a

result, the activation overpotential increased to 153 and 42 mV, respectively. The concentration

overpotential increases with increasing current density, decreasing limiting current density and increasing

ratio between them, as shown in Fig. 9. However, while activation overpotential contributes to ~84% of

the polarisation effect, the concentration overpotential only contributes to the remaining proportion of the

polarisation effect, ~16%. The ohmic overpotential can be overcome by increasing conduction of ions

through the electrolyte, electrons through the electrodes and current collectors and by contact between

cell components and hence would have negligible polarisation effect.

Amongst the various substrates identified for MFC, acetogenesis is the least hassled or the easiest

metabolic process to control / occur and acetate is the most established substrate for which consistent data

are available in literature [119]. Thus, the results [119] are used to validate the model. Equations 5a and

10-17 were used to predict the performance of acetate as substrate at various concentrations, 0.15, 0.5 and

1 g l-1 and compared against the experimental results, in terms of power density and potential (V in

equation 17) with respect to current density, as shown in Figs. 10a-b, respectively. For the net potential (V

26

in equation 17), the Nernst theoretical potential was first estimated from ∆ Gr , MFCo'

using equation 5a and

then overpotentials estimated using equations 11-17, are subtracted.

For Acetate−¿ ¿, x = 2, w = 2, z = 2 and ∆ G f , Acetate¿ ¿ = −¿369.41 kJ mol-1

∆ Gr , MFCo'

= −¿92.756 kJ mol-1

Thus, the Nernst theoretical potential calculated per mole of acetate is calculated to be 0.9614 V.

The best values of exchange current densities, limiting current density and effective surface area per

reactor volume for closest match of the net potential to the experimentally measured potentials [119],

alongside other reactor geometric parameters and conductivities for equations 13-14 are given in Table 1.

The coefficient of determination (R-squared) of this generalised model (equations 5 and 10-17) is greater

than 0.96. The R-squared value could also be affected by the fact that the experimental values were read

from the published graphs rather than from the measurements [119]. Next, the distributions of the ratio of

cathode surface area to reactor volume (m2 m-3) for the three concentrations of acetate (shown in Fig. 11)

are estimated to transform the value of V × i or the power density, in W m-3. The power density was

shown as a linear function of the cathode specific surface area for the case where wastewater used as

substrate [119].

The generalised model (equations 5 and 10-17) can be applied to predict energy performance of MES

systems for the synthesis of biofuels or chemicals or polymers (Fig. 3). This is a pragmatic and robust

way to determine whether a plausible integration schematic of MES in terms substrate inputs is feasible.

The maximum oxidation of anode substrate and the maximum reduction of cathode substrate and the

product chemicals need to be determined in order to hypothesise the overall balanced anode and cathode

reaction stoichiometry. The overall balanced reaction equation can be developed for multi-component

systems. From the balanced reaction equations, the Gibbs free energies of anode and cathode reactions

and thereby the overall reaction can be calculated. These steps are shown in equations 1-5 for the simpler

forms of anode and cathode reactions in MFC and MEC. Once the Nernst theoretical potential is

27

estimated from the Gibbs free energy of the overall reaction, it can be deducted or increased by the

overpotentials (equation 17) calculated using equations 11-16. The model is suitable to best fit

experimental data as well as for predicting optimal factors: electrode specific surface area (influencing

power density), substrate concentration (influencing overall reactions and potential) and current densities,

conductivity and reactor geometry (influencing overpotentials and thereby potential and power density)

for the highest feasible energy performance, as applied generically for performance estimation, analysis

and optimisation of other fuel cell systems [120,121,122,123]. The model is not as data intensive as

computational fluid dynamics [124], but adequate for screening of substrates for MES and for the

estimation of energy performance and thereby avoided environmental impacts from MES [125]. Equally,

the model that uses reaction controlled charge transfer, the Butler-Volmer equation and has a general

basis in non-equilibrium thermodynamics can be applied to smaller dimensions to predict performances

of finite elements that can be compiled for up-scaled systems [113]. The analysis of metabolic pathways

to expand the source of feedstock, engineer microorganisms and to tune the properties of products

[126,127,128,129,130,131] is another thread of research should be explored for optimising MES process

design.

5. Future research directions

Biorefinery simulation frameworks on the other hand are established having been developed for more

than a decade [1]. A few of the earliest works in the field, much well ahead of the times, looked at the

added value production (arabinoxylans) in bioethanol plant to increase the number of platform and

product, hence economic viability using process integration tools [10,11,12].

The process integration tools developed by a group of process engineers at ICI in 1970s to dramatically

increase the energy efficiency of crude oil refineries and combat against drastic depletion of finite fossil

28

resources are now proving to be effective for integration within and between systems [1,58,132] and for

CO2 reduction system [21,133] and thus are desperately needed for MES integration within and to link up

industrial systems, e.g. biorefinery systems, for overall sustainability. Process flowsheet simulation

software such as Aspen PlusTM has been effectively used for modelling of both electrochemical and

biorefinery systems using a modular approach and thermodynamic optimisation methodology to estimate

detailed mass and energy balance analysis [1,44,45]. The advantage of the software is the in-built

thermodynamic property packages needed to take account of the non-ideality of the flows / mixtures /

blends concerned, which are complex and heterogeneous [134]. Aspen PlusTM v7.1 offers the following

base-property methods [135]:

1) Peng-Robinson equation of state,

2) Braun K-10 for petroleum applications,

3) Chao Seader correlation with Lee-Kesler enthalpy,

4) Electrolyte non-random two liquid (NRTL) model with Redlich-Kwong (RK) equation of state for

aqueous and mixed solvent systems,

5) Ideal property method using Rault’s law and Henry’s law,

6) NRTL,

7) Peng-Robinson equation of state,

8) Polymer NRTL with RK equation of state,

9) Henry’s law for polymer solutions,

10) Soave-Redlich-Kwong (SRK) equation of state,

11) Predictive Redlich-Kwong-Soave (RKS) equation of state,

12) Solids property method for general solids and pyrometallurgy applications,

13) UNIFAC with RK equation of state and Henry’s law,

14) Wilson with ideal gas and Henry’s law,

29

15) UNIQUAC with ideal gas and Henry’s law and

16) Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) property method for copolymer

system.

Any of the above property packages can be selected based on the type of the system under consideration.

For the electrochemical systems, the most relevant ones are Peng-Robinson equation of state and

Electrolyte NRTL methods. The package then leads to a collection of estimation methods of several

thermodynamic (fugacity, enthalpy, entropy, Gibbs free energy, and volume) and transport (viscosity,

thermal conductivity, diffusion coefficient, and surface tension) properties. The key results of mass and

energy balance analysis and stream properties of the integrated flowsheet once simulated using a

thermodynamic package are validated against practical results. Different thermodynamic packages may

need to be examined for the selection of the best thermodynamic package that gives the closest match.

The overall system performance will then be optimized for highest productivity, purity, economic and

environmental performances. Such tools allow engineering of real plant configurations, optimisation of

design and operability and definitive and detailed estimates of economics, such as using Aspen Icarus

software, needed for feasibility [1,136]. We are now in a position to test this aspiration technologically.

This way the right innovations and options for advanced integration can be supported. Research efforts

should be more on the metabolic flux and pathway analyses to reduce the number of experimental trials

and optimise the experimental strategy [126,127,128,129,130,131]. It is time to make use of computer-

aided analytical tools to increase the search efficiency and speed up the commercial uptake of MES

technologies, as shown in Fig 12. Finally, the targeted chemicals are listed in Table 2 and the targeted

polymers are shown in Fig. 13, respectively, [1]. Both MES and biorefinery process units can be coupled

to target such products.

6. Conclusions

30

A comprehensive overview of integration between waste biorefinery and MES system has been

presented. The biofuel and biorefinery industries are currently facing the challenges resulting from

increasing volume of stillage streams representing unconverted lignocellulose, fermentation /

fractionation / transesterification / and hydrogenation byproducts, which are discharged to the

environment. However, these should not be directly disposed of to the environment due to increasing

concerns over land, aquatic and atmospheric emissions. MES can help recover these biorefinery

pollutants as resources and thereby eliminate discharges to the environment. Biorefineries and MES

systems may be symbiotically integrated to increase product yields and selectivities and thereby overall

efficiency to resolve the key issues with up-scaling of both the technologies.

By the virtue of different reduction potentials, selective synthesis of biofuels and chemicals is possible in

MES utilising carbon sources from waste streams. Realizing the full polygeneration potentials, i.e.

simultaneous recovery of metals (apparently pollutants from biorefineries), production of biofuels and

chemicals from reuse of CO2, and synergistic integration within biorefineries, is imperative to attain an

economic and environmental upside of novel electrochemical synthesis processes.

Furthermore, a generalised model based on classical thermodynamics and linear flux has been discussed

with a view to optimise operation of the MES. The total Gibbs free energy change summed over each

reaction step correlated to the molar compositions can be minimized. This determines the optimal molar

distributions and thus yields, and physico-chemical behaviour, providing indications of technical

feasibility and identifying the best conditions to achieve highest efficiency, reduced overpotentials and

mass transfer losses incurred in a cell. The thermodynamic modelling, as discussed in this paper is

applicable to multi-component systems. The model takes account of the specific surface area of

electrodes, substrate concentration, current densities, conductivities and reactor geometry, in predicting

highest feasible energy performance. The model can be used to estimate the best substrate or

31

combinations of substrates with appropriate number of electron transfers in the reaction steps of the

electrochemical cell. The anode and cathode exchange and limiting current densities can also be updated

for a specific set up. Furthermore, the operating and design parameters, such as anode and cathode

exchange and limiting current densities, anode, cathode, electrolyte and interconnect thickness and

conductivity constants, can be defined for a specific experimental design to estimate the overpotentials

that must be deducted from the Nernst theoretical potential, estimated for overall balanced reactions of

the cell. Current research must be complemented by process integration research to facilitate

commercialisation of MES technologies.

Acknowledgement: The authors gratefully acknowledge the financial support of the Natural

Environmental Research Councils (NERC), UK Grant NE/L014246/1.

References

[1] Sadhukhan J, Ng KS, Hernandez EM. Biorefineries and chemical processes: Design, integration and

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