Using Red Blood Cells in Microbial Fuel Cell Catholyte Solution to Improve Electricity Generation

USING RED BLOOD CELLS IN MICROBIAL FUEL CELL CATHOLYTE SOLUTION TO IMPROVE ELECTRICITY GENERATION

THESIS

Presented in Partial Fulﬁllment of the Requirements for the Degree Master of

Science in the Graduate School of the Ohio State University

Ying-Chin Wang, M.S.

Graduate Program in Food, Agricultural, and Biological Engineering

The Ohio State University

2014

Thesis Committee:

Ann D. Christy, PhD., P.E., Advisor

Olli Tuovinen, PhD.

Amy Lovett-Racke, PhD c Copyright by

Ying-Chin Wang

2014 ABSTRACT

The microbial fuel cell (MFC) is an energy production technology that exploits microbial metabolism to produce electrical current. Electricity generation can be produced by MFCs with simulated intestinal ﬂuid from the human body or bovine rumen ﬂuid-based microbial consortia. The objective of this study was to explore the feasibility of blood MFCs. The ultimate goal of this research is to develop a way to generate electricity in vivo to power implantable biomedical devices (e.g., pacemaker) using the body’s own natural materials. Blood-based MFCs, using red blood cells

(RBCs) as catholyte with recycling between the cathodic and aeration chambers, were continuously fed using glucose at 37◦C. Five diﬀerent RBC concentrations were tested with the best results occurring at 12.5 % concentration in the catholyte. The performance of MFCs with 0∼12.5 % RBCs included maximum power density of

27.7∼45.8 mW/m2 at 1000 Ω, open circuit voltage of 495∼527 mV, chemical oxygen demand removal eﬃciency of 83.3∼90.7 %, and coulombic eﬃciency of 6.60∼15.3 % at 100 Ω. It is possible that an increase of RBC concentration can further improve the electricity generation of MFCs in spite of the observed short period of a stable electricity generation. In the future experiments with blood-based MFCs, several challenges need to be overcome and be explored, especially maintenance of the lifetime and activity of RBCs.

ii To my family, my parents and my brother. Your limitless love and support give me

everything. This can be done, because of you.

iii ACKNOWLEDGMENTS

I would like to thank Dr. Ann D. Christy for recruiting me as her master student and her patience and guide on my acdemic research. I would like to thank Dr. Amy

Lovett-Racke, Dr. Jeﬀrey Lakritz, Dr. Andre Palmer, Dr. Gonul Kaletunc, Dr. Jay

Martin, and Dr. Jeﬀrey Firkins for their technological support. It cannot be done without those support. I would like to thank Dr. Olli Tuovinen for his suggestions on my experiments.

I would like to thank Candy McBride, the kindest person in FABE, for her help and encouragement, and Trent Bower, a lab mentor, for his teaching. I would like to thank my best friends as well as my ﬁrst dance crew in OSU including Chao-Ying

Chen, Priscilla Lee, Chieh Hsu, Tien-Lin Hsieh, Tang-Yu Liu, and Yen-Ling Liu for their help and support on my life.

I would like to thank graduate students or technologists from the FABE or the other department including Nannan Lin, Jingxin Guo, Guannan Ding, Xinjie Tong, Wenbo

Yang, Emily Durham, Rogelio Leon, Jorge Fontes, Yue Liu, and Mary Severin for their help on experiments. Also, my second dance crew in OSU including Sirui Chen,

Siting Wang, Xiaoxu Zhang, and TzyJie Yong, brought me a lot of fun in my life. I was very enjoying this journey in my life.

iv VITA

1983 ...... Born in Chiayi, Taiwan (R.O.C.)

2005 ...... B.S. Harbor and River Engineering, Na- tional Taiwan Ocean University

2007 ...... M.S. Harbor and River Engineering, Na- tional Taiwan Ocean University

2012-Present ...... Food, Agricultural, and Biological Engi- neering, The Ohio State University

FIELDS OF STUDY

Major Field: Food, Agricultural, and Biological Engineering

Specialization: Microbial Fuel Cells

v TABLE OF CONTENTS

Abstract ...... ii

Dedication ...... iii

Acknowledgments ...... iv

Vita...... v

List of Figures ...... viii

List of Tables ...... x

CHAPTER PAGE

1 Introdution ...... 1

1.1 Microbial Fuel Cells ...... 1 1.1.1 Theory of Electricity Generation of MFCs ...... 2 1.1.2 The Development of MFCs ...... 2 1.2 Statement of Problem ...... 4 1.3 Hypothesis ...... 4 1.4 Objectives ...... 5

2 Literature Review ...... 7

2.1 Parameters in Microbial Fuel Cells ...... 7 2.1.1 Dissolved Oxygen ...... 7 2.1.2 Temperature ...... 7 2.1.3 Organic Loading Rate and pH Value in Anodic compartment8 2.1.4 Electrodes ...... 8 2.2 Bacterial Consortia ...... 10 2.3 Applications of Microbial Fuel Cells ...... 11 2.4 Red Blood Cells ...... 12

3 Materials and Methods ...... 15

3.1 Materials ...... 15 3.1.1 Reactor Design and MFCs set up ...... 15

vi 3.1.2 Electrode Preparation ...... 18 3.1.3 Membrane ...... 18 3.1.4 Inoculum ...... 18 3.1.5 Incubation of Red Blood Cells ...... 19 3.2 Methods ...... 20 3.2.1 Operation System ...... 20 3.2.2 Experiments ...... 20 3.2.3 Measurements ...... 22 3.2.4 Data Analysis ...... 23

4 Results and Discussion ...... 28

4.1 Effect of Varying Concentrations of RBCs in Blood-based MFCs . 28 4.1.1 Maximum Power Density and Open Circuit Voltage . . . . 28 4.1.2 Dissolved Oxygen and Total Oxygen ...... 33 4.1.3 COD Removal Efficiency ...... 34 4.1.4 Coulombic Efficiency ...... 37 4.1.5 pH in Catholyte ...... 37

5 Conclusion ...... 39

5.1 Summary ...... 39 5.2 Conclusions ...... 40 5.3 Limitations ...... 40 5.4 Biomedical Application ...... 41 5.5 Future Research ...... 41

APPENDICES ...... 43

A Anolyte and Catholyte Solutions ...... 43

A.1 Multi-Purpose Anolyte Solutions ...... 43 A.1.1 Mineral Solution I ...... 43 A.1.2 Mineral Solution II ...... 43 A.1.3 Feedstock Solution I ...... 43 A.1.4 Feedstock Solution II ...... 44 A.2 Catholyte ...... 44 A.2.1 Medium for Red Blood Cells ...... 44 A.2.2 Pottassium Ferricyanide Solution ...... 44

B Polarization and Power Density Curves ...... 45

C Chemical Oxygen Demand Test ...... 50

Bibliography ...... 57

vii LIST OF FIGURES

1.1 Photo of Example MFC from Lab ...... 1

1.2 A Diagram of Microbial Fuel Cell ...... 3

2.1 Blood Gas Transport ...... 14

3.1 Drawing of a Single MFC Testing Chamber ...... 16

3.2 Assembly Drawing of MFC Enrichment Reactor ...... 16

3.3 Drawing of the Opaque Polycarbonate Plate ...... 17

3.4 Assembly Drawing of MFC Reactor ...... 17

3.5 Operation System and MFCs in the Incubator ...... 21

3.6 Dissolved Oxygen Meter and pH Meter ...... 22

3.7 COD Calibration Regression Lines (0 to 150 mg/l and 0 to 1000 mg/l) 23

3.8 Data Logger and Decade Box ...... 24

3.9 An Example of Step Tests ...... 24

3.10 An Example of Polarization and Power Density Curve ...... 25

3.11 Oxygen Dissociation Curve ...... 26

4.1 Average Maximum Power Density by Area (mW/m2) or by Volume (W/m3)...... 30

4.2 Polarization Curves for Diﬀerent RBC Concentration in (a) Cell 01 and (b) 02 ...... 31

4.3 Dissolved Oxygen as a Function of Hemoglobin Concentration . . . . 33

4.4 Total Oxygen as a Function of Hemoglobin Concentration ...... 34

4.5 COD Values in (a) Cell 01 and (b) 02 ...... 35

4.6 Average COD Removal Eﬃciency in Each Experiment ...... 36

4.7 COD Removal Eﬃciency in (a) Cell 01 and (b) 02 ...... 36

viii 4.8 Average Coulombic Eﬃciency ...... 38

4.9 Change of pH in Catholyte over Time ...... 38

B.1 Polarization and Power Density Curves of Cell 01 and 02 for the Medium-only Control ...... 45

B.2 Polarization and Power Density Curves of Cell 01 and 02 in 1% RBCs 46

B.3 Polarization and Power Density Curves of Cell 01 and 02 in 2% RBCs 46

B.4 Polarization and Power Density Curves of Cell 01 and 02 in 5% RBCs 47

B.5 Polarization and Power Density Curves of Cell 01 and 02 in 10% RBCs 47

B.6 Polarization and Power Density Curves of Cell 01 and 02 in 12.5 % RBCs ...... 48

B.7 Polarization and Power Density Curves of Cell 01 and 02 in DI-Water with Aeration ...... 48

B.8 Polarization and Power Density Curves of Cell 01 and 02 for DI-Water without Aeration Control ...... 49

B.9 Polarization and Power Density Curves of Cell 01 and 02 for Potassium Ferricyanide Control ...... 49

ix LIST OF TABLES

TABLE PAGE

4.1 Open Circuit Voltages with Varying RBC Concentration ...... 32

x CHAPTER 1

INTRODUTION

1.1 Microbial Fuel Cells

The demand for energy is increasing quickly and the issue of global warming is gain- ing wide attention, so energy alternatives are needed in place of ﬁnite fossil fuels.

The Microbial Fuel Cell (MFC), as shown Fig. 1.1, a novel and renewable energy conversion technology (Logan, 2008), has several advantages and applications. The

Figure 1.1: Photo of Example MFC from Lab: Selected microorganisms were inoculated into the anodic chamber and fed with substrate which was metabolized and converted to H+ ions and electrons. A proton exchange membrane (PEM) is used to separate the anodic and cathodic chambers.

1 advantages of MFCs include direct conversion from chemical energy to electrical energy; no emissions of carbon dioxide or methane; operation under ambient temperature and pressure conditions; and lower cost (Wang et al., 2012; Rizzo et al., 2013;

Biﬃnger and Ringeisen, 2008). Furthermore, MFCs cannot only be used to generate electricity but also be applied in the areas of wastewater treatment, bioremediation, and desalination (Lefebvre et al., 2013; Kim and Logan, 2013).

1.1.1 Theory of Electricity Generation of MFCs

An MFC consists of two compartments, one aerobic (containing the cathode) and the other anaerobic (containing the anode). In the anodic chamber, bacteria consume substrate and generate H+ ions and electrons, as shown in Fig. 1.2. The H+ ions diﬀuse through a semi-permeable membrane into the cathodic chamber. Electrons arriving at the cathode from the external circuit combine with dissolved oxygen and

+ the H ions to form pure H2O. The common substrates and their associated electron producing chemical equations include

Acetate:

− − + − CH3COOH + 3H2O → CO2 + HCO3 + 8H + 8e Glucose:

+ − C6H12O6 + 6H2O → 6CO2 + 24H + 24e

1.1.2 The Development of MFCs

The ﬁrst MFC (Potter, 1911), was developed by modifying a hydrogen fuel cell, which was inoculated with a microbial consortium (E. coli., Bacillus ﬂuorescens,

Bacillus violaceus, and Sarcina lutea), and was fed with glucose. At that time, the recorded voltage generated was 0.5 V (Potter, 1911). Karube et al. (1977) reported

2 Figure 1.2: A Diagram of Microbial Fuel Cell (Rabaey and Verstraete, 2005)

a biochemical fuel cell utilizing C. butyricum generated 2 to 120 µA/cm2 while the external resistance was changed from 5000 to 5 Ω. In 1991, an MFC was used to treat domestic wastewater containing a high concentration of Na2SO4, and its current density reached 50 mA/cm2 (Habermann and Pommer, 1991). Mediator-less MFCs, which rely on the microbes to self-mediate, were introduced which could directly transfer electrons to the anode electrode using the bateria0 s electron transport chain

(Bond et al., 2002; Kim et al., 2002). Two derivations of the MFC are microbial electrolysis cells (MECs) and microbial desalination cells (MDCs). Diﬀerent from

MFCs, electricity is applied to MECs to generate hydrogen gas or methane (Wagner et al. 2009). MDCs can additionally desalinate hard water or saline water (Kim and Logan, 2013). To date, by using a worldwide search engine, the number of the documents regarding the microbial fuel cell has been over 9,000.

3 1.2 Statement of Problem

In most MFCs, the rate limiting step is the half reaction at the cathode (Rismani-

Yazdi et al., 2008). Speciﬁcally, the dissolved oxygen concentration in the catholyte solution is one of the parameters that most inﬂuences electricity generation. In many studies, an MFC must be mechanically aerated to maintain the appropriate oxygen level in the cathode. Unfortunately, the electricity consumed for aeration is often higher than the electricity generated by an MFC. In short, an MFC cannot generate enough electricity to aerate itself.

1.3 Hypothesis

In this research project, the hypothesis was that adding red blood cells into catholyte would improve the power generation of MFCs. In human blood, total oxygen concentration including dissolved oxygen and hemoglobin bound oxygen, is approximately

251 mg/l (or 200 ml/l) at 37◦C (Kaushansky, 2010) which is 37 times higher than that of dissolved oxygen in water at the same temperature (6.78 mg/l at 760 mmHg

Stewart et al., 2013). More H+ ions and electrons can be generated by the microbial consortia when the temperature is around 35 to 40◦C (Larrosa-Guerrero et al.,

2010). In addition, even though the oxygen concentration in blood is higher, generally that oxygen will not pass across the membrane from the MFCs0 cathodic to anodic chambers because it is a cation (+) exchange membrane, not an anion (-) exchange membrane and because the dissolved oxygen in blood is as low as 4 mg/l (Pittman,

2011).

According to the Bohr Eﬀect (Wikipedia, 2013), H+ ions modulate oxygen bind- ing to hemoglobin. A decrease of pH in blood leads to a decrease of oxygen aﬃnity

4 and release of oxygen from hemoglobin proteins; on the other hand, hemoglobin can pick up more oxygen in high blood pH. In a blood-based MFC, once H+ ions pass through the membrane from the anode chamber, H+ ions combine with RBCs to force

RBCs to release oxygen. Then this oxygen, including dissolved oxygen and released previously bound oxygen, can combine with H+ ions and electrons to form water and complete the electrical circuit.. It is anticipated that the energy output of an MFC may be improved by the added RBCs which not only provide more oxygen but may catalyze the reaction rate in the cathode.

1.4 Objectives

The short-term goal of this research was to explore the feasibility of blood MFCs by speciﬁcally focusing on the cathode side of the MFC reaction. The long-term future goal is be able to place blood MFCs into living bodies to power implantable medical devices such as pacemakers or insulin pumps, using white blood cells as the anodic electron donor (Justin et al., 2011) and red blood cells to enhance the cathode reaction (this study).

In order to successfully reach the short-term goal, this project includes the following tasks:

• Maintain RBC activity in vitro.

• Increase total oxygen in the catholyte.

• Determine the optimum concentration of RBCs in an MFC catholyte solution

to maximize peak power density.

• Determine the optimum replacement time of the blood solutions in continuous

mode MFCs to maximize peak power density of the MFC.

5 • Determine the optimum hydraulic residence time of the blood solutions in the

aeration chamber to achieve maximum dissolved oxygen concentrations

6 CHAPTER 2

LITERATURE REVIEW

2.1 Parameters in Microbial Fuel Cells

2.1.1 Dissolved Oxygen

In the cathode, dissolved oxygen (DO) is the most limiting parameter for the half

+ − reaction (4H + 4e + O2 → 2H2O). Most studies used an aerator to maintain oxygen level in cathode. Jang et al. (2004) and Pham et al. (2004) showed that the performance of MFCs can be improved by increasing aeration rate. Besides using an aerator, adding hydrogen peroxide into the catholyte solution can also improve the power generation.

However, small amounts of DO could diﬀuse through the exchange membrane from the cathodic to anodic chamber where the presence of oxygen could inhibit electron production. Using high aeration rates with pure oxygen, the columbic eﬃciency of

MFCs decreased from 30.9 to 9.9 %, compared with the same aeration rate but with air containing 20.8 % oxygen (Pham et al., 2004)

2.1.2 Temperature

For maintaining mesophilic microorganisms0 activity, the most important parameter is temperature (Scott et al., 2012). Larrosa-Guerrero et al. (2010) indicated that,

7 in different operating temperatures, the performance of MFCs (i.e., COD removal efficiency, Coulombic efficiency, and power generation) can be affected. Maximum power density was increased from 2.35 mW/m2 at 4◦C to 76.15 mW/m2 at 35◦C

(Larrosa-Guerrero et al., 2010). However, exceeding the optimum temperature in operation can also inhibit the performance of MFCs (Liu et al., 2011).

Optimum temperature for MFCs depends on the speciﬁc bacterial species or consortia. The operating temperature in two studies of MFCs using rumen ﬂuid bacterial consortia was around 39◦C (Rismani-Yazdi et al., 2007; Wang et al., 2012). In comparison, bovine body temperature is around 37.8 to 40◦C and the temperature within a cow0s rumen is around 40◦C.

2.1.3 Organic Loading Rate and pH Value in Anodic compartment

Glucose is one of the more common substrates for MFCs (Chaudhuri and Lovley,

2003; Cheng et al., 2006). Two studies indicated that, in glucose-fed MFCs, coulombic eﬃciency and power generation of MFCs was reduced as organic loading rate (OLR) was increased (Rabaey et al., 2003; Hu, 2008). While loading rate was increased from

0.5 to 5 g COD l−1day−1, coulombic eﬃciency decreased from 89 to 10 %. In addition,

Rabaey et al. (2003) showed that pH values dropped rapidly at high loading rates.

Lower pH value inhibited microbe activity and even destroyed anodic bioﬁlms (Zhang et al., 2011).

2.1.4 Electrodes

For MFC power generation and cost, the choice of suitable electrode materials is very important. Depending on diﬀerent demands in anodic or cathodic conditions, the selected electrode materials should be able to improve eﬃciency and reduce cost. For

8 the anode, the electrode material should be of high electrical conductivity, low resis- tivity, anti-corrosive, biocompatible, high surface area, and durable. For the cathode, the material should have high electrical conductivity, high redox potential, and easily react with protons (Verstraete and Rabaey, 2005). The common electrode materials for MFCs are carbonaceous, including graphite, carbon cloth, carbon paper, carbon mesh, carbon brush, and carbon felt. Based on the diﬀerent conﬁgurations, the carbonaceous materials can be categorized as having plain, packed, or brush structure

(Wei et al., 2011). The plain structure includes graphite plate, carbon cloth, carbon paper and carbon felt. Graphite plate has excellent toughness and high conductivity

(low resistance), but its lower surface aera and higher cost have led to the development of MFCs limited to lab-scale. Carbon cloth has those properties required for an anode, especially a large surface area that is very favorable for microorganism attachment but it is slightly more expensive compared with the other carbon materials. Carbon paper is easy to hand-cut and connect to wiring, but is fragile and nondurable. Zhou et al. (2011) also indicated that the distance between the electrodes could be reduced while using carbon cloth or carbon paper because of their properties of thinness, which could improve MFC performance (Zhou et al., 2011).

Packed structures include granular graphite and carbon felt which allow more bac- treia to grow on its surface area; however, eventually, it inhibits the feedstock passing into inner surface area. Carbon brushes have very good properties and low cost; however, they have same problem as the other packed stucture materials of blocking mass transfer of feedstock substrate (Wei et al., 2011). Some non-carbon materials

(i.e., stainless steel or gold) have been used as the electrode materials in MFCs, but the performance was quite low or the cost was too high (Dumas et al., 2007; Richter et al., 2008). The ratio of surface area between anodic and cathodic electrode also

9 inﬂuences the performance of MFCs. For example, while using potassium ferricyanide as catholyte and carbon paper as electrode, the optimal ratio was one to four between anodic and cathodic electrode of surface area (Uria et al., 2012).

2.2 Bacterial Consortia

To date, some microorganisms, including pure and mixed cultures, have been used for the power generation in MFCs. Pure cultures include genera Geobacter, Rhodoferax, and Shewanella (Kim et al., 2002; Richter et al., 2008), and mixed cultures have been extracted from activated sludge, seafloor sediment, rumen fluids and intestinal fluids

(He et al., 2007; Lefebvre et al., 2013; Rismani-Yazdi et al., 2007; Han et al., 2010).

In many studies of MFCs, the need for an external mediator to increase the rate of electron transfer is one of reasons inhibiting the technology0 s practical applications.

However, some strains of electrochemical microorganisms have their own ability to self-mediate, to transfer electrons directly to electrodes, for example Shewanella putrefaciens(Kim et al., 2002) and Rhodoferax ferrireducens (Chaudhuri and Lovley,

2003). Rabaey et al., (2005) concluded that using mixed cultures as a biocatalyst could have better power generation in MFCs than using pure cultures. By adding pyocyanin into eight pure cultures, the MFC output was increased in six of them

(Rabaey et al. 2005).

Ha et al. (2010) suggested that the microorganisms from intestinal ﬂuids perhaps have the ability to generate electricity. Their results demonstrated that an MFC could achieve maximum power densitiy of 73.3 mW/m2 and open circuit voltage of

552.2 mV under simulated intestinal conditions. This MFC give the large intestine colon surface area (0.3 m2 in humans) could have enough electricity generation to power several implanted medical devices, such as a pacemaker (30-100 µW) or drug

10 pump (100 µW to 2mW). Diﬀerent from the other MFCs, this MFC used carbon paper rather than ion exchange membrane to separate the anodic and cathodic chamber, but no rationale was given.

Microorganisms from rumen ﬂuids were reported to be electrogenic for power generation in MFCs (Rismani-Yazdi et al., 2007; Wang et al., 2012). Rismani-Yazdi et al.,

2007 suggested that rumen microorganisms have both abilities of hydrolying celluose and transferring electrons to the electrodes. Their DGGE, denaturing gradient gel electrophoresis, result showed that the most predominant clones seem to be related to the family Comamonadaceae of the class Betaproteobacteria, which could contribute to electron transfer without mediator. Another detected clone was Clostridium of the phylum Firmicutes which possibly could participate in cellulose hydrolysis. In addition, another potential beneﬁt of these microoganisms could be the ability to generate electricity from various agricultural and industrial celluosic wastes (Rismani-Yazdi et al., 2007). For electricity generation, maximum power density with enriched rumen microorganisms of MFCs was documented to reach 66 mW/m2 when the feedstock was cellulose and external resistance was 20 Ω (Rismani-Yazdi et al., 2011).

2.3 Applications of Microbial Fuel Cells

Besides power generation, additional beneﬁts from MFCs can include wastewater treatment and saltwater desalination. Various wastewaters including high concentration organic substrates could be a potential fuel for MFCs. Maximum power densities were reported as high as 1600 or 261 mW/m2; COD removal eﬃciency could reach

75% or 92 % while substrates were chocolate industrial wastes or swine wastewater, respectively (Min et al., 2005; Patil et al., 2009).

11 Desalination is one way to obtain fresh water. Microbial Desalination Cells (MDCs), derived from MFCs, consist of a three compartment device with a series of exchange membranes that allow speciﬁc ions to pass. MDCs can not only generate electricity but also desalinate hard or saline water. Kim and Logan (2013) indicated that salt removal eﬃciency in MDCs could be over 95 percent, and Chen et al. (2012) reported that maximum power density could reach 529 mW/m2.

Biomedical research is also a potential ﬁeld for microbial fuel cell applications. Several studies described the possibility of implantable power by using enzymatic reactions or electron donors. Barton et al. (2004) indicated that physiological biocatalysts are active at body temperature (25-50◦C) and neutral pH, and most species have high activity in such environment. Moreover, those species do not cause rejection by their host. White blood cells were reported to release electrons even though the metabolism in their MFCs was unclear; this biofuel cell, using white blood cells in the anode, generated 1.5 to 2.7 µA/cm2 while the external resistance was 100 Ω. (Justin et al. 2005). Siu and Chiao (2008) indicated that electricity generation from human plasma consumed by S. cerevisiae could reach 401 nW/cm2 (or 4.01 mW/m2) in a microfabricated polydimethylsiloxane MFC. Liu et al. (2010) demonstrated that simulated intestinal ﬂuid as inoculum in MFCs could generate power densities as high as

73.3 mW/m2 and implied that MFCs have potential for powering implantable medical devices in the future.

2.4 Red Blood Cells

In the human body, whole blood consists of plasma (54.3%), red blood cells (45%), and white blood cells (0.7%) (Shier et al., 2003). The lifespan and the total cyclic

12 distance of erythrocytes (red blood cells or RBCs), in the human body, are approximately 120 days and 480 km (300 miles), respectively. The diameter of individual human red blood cells varies from 7.5 to 8.7 µm (Kaushansky, 2010) and their concentration varies from 25 to 125 million per micro liter in human body (Hoﬀbrand et al., 2006). The ﬂow rate of blood is 0.43 to 0.72 m3/hr with an average velocity of

40 cm/s in the aorta (Hoﬀbrand et al., 2006).

The main function of red blood cells is oxygen and carbon dioxide delivery between the lungs and tissues. Each red blood cell includes around 640 million of hemoglobin molecules (Hoﬀbrand et al., 2006). One gram of hemoglobin (Hb) can combine with

1.39 milliliter of oxygen. For example, 100 ml of blood containing 15 g of Hb can carry 20.1 ml of oxygen as much as 70 times higher than dissolved oxygen in blood

(Pittman, 2011). The blood oxygen capacity can be affected by pH value, the concentration of carbon dioxide, and 2,3-diphosphoglycerate (2,3-DPG). In the lung, a high pH, low CO2, and low 2,3-DPG, increase oxygen affinity, and allow oxygen to be carried by red blood cells; on the other hand, a low pH, high CO2, and high 2,3-DPG decrease oxygen affinity and release oxygen from red blood cells that can then diffuse into the tissues (Hoffbrand et al., 2006). Fig. 2.1 demonstrates blood gas tranport in the human body.

+ At the lungs, high partial pressure of oxygen (pO2) causes the conversion of H Hb to

+ − HbO2 and then the released H combines with HCO3 to form carbonic acid. Lastly, the carbonic acid dissociates into H2O and CO2 which diﬀuses to the alveoli from the red cells; at the tissues, low pO2 and CO2 entering the red blood cell from the tissue (Bohr eﬀect) leads to the conversion of oxygenated Hb to deoxygenated Hb, and then

− more CO2 combines with Hb and more HCO3 is produced.

13 10. The Carbon Dioxide Dissociation Curve

The relationship between the PCO 2 & the whole blood CO 2 content (in all 3 forms mentioned above) is known as the carbon dioxide dissociation curve . Within the range of normal blood PCO 2, the curve is nearly a straight line.

Transport of CO 2 is dependent on O 2 release.

The CO 2 dissociation curve is influence by the state of oxygenation of the Hb ( Haldane effect ). The Haldane effect can be explained by the fact that deoxygenated Hb is better than oxygenated Hb in:

1) combining with hydrogen ions and in turn assisting the blood to load more CO 2 from the tissues.

2) combining with carbon dioxide to form carbamino compounds and in turn assisting the blood to load more CO 2 from the tissues for removal at the lungs.

Summary of Blood Gas Transport

Gas exchange at the tissues : As CO 2 leaves the tissue cells and enters the red blood cell, it causes more O 2 to - dissociate fromFigure Hb (Bohr 2.1: shift); thus Blood more CO Gas2 combines Transport with Hb and (Osborne, more HCO 3 is produced. 2013)

Gas exchange at the lungs : As O 2 passes from the alveoli into the red blood cells, Hb becomes saturated with O 2 + - and becomes a stronger acid. The more acidic Hb releases more H that binds to more HCO 3 to form carbonic acid. The carbonic acid dissociates into CO 2 and water. The CO 2 diffuses from the blood into the alveoli.

5 Freedman (1983) indicated that red blood cells need a constant pH value and ade- quate substrates for survival. By using Earles Salt buﬀered with 4-(2-hydroxyethyl)-

1-piperazineethanesulfonic acid (HEPES) and the other nutrients including vitamins, albumin, and antibiotics, around 85 % red blood cells survived at the end of the ﬁrst week, but cell survival decreased to 40 % at the end of the second week of in vitro incubation at 37◦C, and 7.4 pH (Freedman, 1983).

14 CHAPTER 3

MATERIALS AND METHODS

3.1 Materials

3.1.1 Reactor Design and MFCs set up

Two different volumes of reactors were used in this study. To quickly produce a high number of microorganisms, the first type of MFC having larger volume chambers was used to enrich the rumen microorganisms prior to the RBC experiments. In the first reactor type, MFCs were constructed of three chambers (one anode and two cathodes,

Figure 3.1). The MFC walls were constructed of clear polycarbonate (thickness: 0.6 cm; inside dimensions: 7.6 cm) with a volume of 150 ml in each chamber. Graphite plates (3x4x0.5 cm) were used as electrodes, and two Cation Exchange Membranes

(CEMs) was used to separate the three compartments (Figure 3.2). The second type of reactor with smaller volume in each chamber was used for the RBC experiments due to requiring less RBCs, having a shorter distance between the electrodes, and producing less waste. Diﬀerent from the ﬁrst type, the second type of MFC walls were constructed of opaque polycarbonate plate, including 6 chambers in each plate, with a volume of 10 ml in each chamber, as shown in Fig 3.3. The second type of MFCs were also constructed of three chambers separated by CEM, and carbon cloth (9 cm2) and carbon paper (3.14 cm2) material were used as anodic and cathodic electrodes, respectively, as shown in Fig. 3.4.

15 Figure 3.1: Drawing of a Single MFC Testing Chamber

Figure 3.2: Assembly Drawing of MFC Enrichment Reactor Including an Anodic Chamber in the Middle and Two Cathodic Chambers in the Sides

16 Figure 3.3: Drawing of the Opaque Polycarbonate Plate

Figure 3.4: Assembly Drawing of MFC Reactor Including an Anodic Chamber in the Middle and Two Cathodic Chambers in the Sides

17 3.1.2 Electrode Preparation

Three diﬀerent types of electrodes: graphite plates, carbon cloth, and carbon paper, were used in this study. For the anodic electrode, carbon cloth was hand cut to 3x3 cm; for cathodic electrodes, carbon paper was hand cut to produce a ﬂat circle with diameter 2 cm. All electrodes were connected with a stripped end of copper wire.

The connection between electrode material and wire was made using on a mix of graphite powder and contact cement which was allowed to solidify for 12 hours. After solidiﬁcation, the electrodes were soaked in 1 N HCl for 24 hours and then in NaOH for another 24 hours. The resistances of the made electrodes were approximately 1

Ω.

3.1.3 Membrane

The membrane, separating anodic and cathodic chambers, in this study was a 0.45 mm thick Strong Acid Cation Exchange Membrane from Membranes International

(part CMI-7000S). It was hand cut to 3x3 cm and soaked in a mixed mineral solution

(App. A.1.1 and A.1.2) for 24 hours at 40◦C.

3.1.4 Inoculum

Bacterial consortia were from bovine rumen fluid collected via a cannula from a dairy cow at the Waterman Farm dairy barn of the Ohio State University. For the inoculum, flesh rumen fluid (1 % v/v), collected on November 21st, 2013, was inoculated into the first type of microbial fuel cell and batch fed with 25 ml/day of artificial substrate (first substrate, App. A.1.3) with anolyte. The adjusted pH value varied between 6.85 and 6.95. After 10 days, MFC testing began, generally increasing feedstock volume to 60 ml/day.

18 On January 2nd, 2014, enriched rumen microoganisms were inoculated into the second type of microbial fuel cell and batch fed 5 ml/day of the ﬁrst artiﬁcial substrate

(App. A.1.3). Using distilled water as catholyte, the ﬂow continuous rate of the ﬂuid recycling between the aeration chamber and cathodic chamber was 100 ml/hr. After

13 days, MFC testing began, generally decreasing concentrations of glucose from 5 g/l to 0.25 g/l, and the second artiﬁcial substrate (App. A.1.4) was used as feedstock for the following experiments. On January 30th, 2014, the MFC was converted to full continuous mode with feedstock delivered to the anolyte at the volumetric ﬂow rate of 1 ml/hr. Feed rate to the anodic chamber was generally increased to 3.3 ml/hr.

3.1.5 Incubation of Red Blood Cells

RBCs were separated from human whole blood purchased from the U.S. Red Cross.

The samples used in this study were from two diﬀerent blood donors. In this study, all RBCs were incubated at 37◦C and pH 7.3 in the appropriate medium (App. A.2.1) as reported by Freedman (1983). Blood solutions containing diﬀerent concentrations of RBCs and medium totalled 150 ml in each treatment, and the solutions0 pH and temperature values were adjusted to 7.3 and 37◦C before being introduced into the aeration chamber.

19 3.2 Methods

3.2.1 Operation System

The operation system as shown in Fig 3.5 was set up on January 30th, 2014. MFCs were placed in an incubator that maintained temperature at 37◦C and were each connected to 1,000 Ω of external resistance. A data logger recorded the voltages for each MFC every 20 seconds. Feedstock stored in an IV bag was pumped into the

MFCs via infusion pump (Abbott Hospira Plum A+3) with a flow rate 3.3 ml/hr. All catholytes were recycled, with a flow rate of 500 ml/hr, between cathodic chambers and the aeration chamber flask via an infusion pump. The solutions were separated using a manifold from one common tube to three separate tubes. The aeration chamber was placed on a magnetic-stirrer device, and the solutions were stirred to prevent RBCs from settling out of solution. Chemical oxygen demand (COD) and pH values of the anodic influent and effluent solutions were measured and recorded every day. Total oxygen concentrations in the cathodic influent and effluent blood solutions were measured, calculated, and recorded every day. In this study, two MFC replicates were used for all experiments and each treatment involved two repetitions.

All experiments were conducted using sterile technique, solutions, and equipment

(Freedman, 1983). After setting up the MFCs, all chambers were ﬁlled with bleach and then ﬂushed by sterile water (Richter et al., 2008).

3.2.2 Experiments

Eﬀect of RBCs concentration for MFCs performance

In this study, comparisons included four controls: ferricyanide as catholyte, distilled water as catholyte aerated with air, distilled water as catholyte without aeration,

20 Figure 3.5: Operation System and MFCs in the Incubator: (a) Incubator, infusion pumps, decade resistance box, and data acquisition equipment; (b) inside incubator showing MFCs, tubing, and stirred aeration ﬂask for RBCs

and the medium as catholyte without aeration. Different RBC concentration treatments were 1, 2, 5, 10, and 12.5 %. All parameters were described as above during these controls and treatments. In each experiment, the performance of the MFC was recorded including maximum power density, coulombic efficiency, COD removal efficiency. Other factors of the MFC that were monitored included dissolved oxygen

(DO) or/and oxygen, and pH.

In the beginning of each treatment, initial external resistance was 0 Ω and, after

15 or 20 minutes, the MFCs started running step tests, as shown in Fig.3.5, incre- mentally increasing external resistance from 10 Ω to 1M Ω followed by, and then

COD testing and the measurement of DO. Each treatment was run for 24 hours, and then the blood solution was replaced by distilled water (DI-water) for checking the baseline of power generation. Besides the cassette, all materials including stopcocks, manifold, and tubing were ﬂushed using bleach and then with autoclaved DI-water.

21 3.2.3 Measurements

In this study, measurements included DO, COD, pH, temperature, and voltage. A DO meter (YSI 5000; Fig. 3.6a) was used to measure DO values of influent and effluent catholytes. The protocol of the COD test (HACH; Appendix C) included generating two calibration regression lines (Fig. 3.7a for 0 to 150 mg/l COD; 3.7b for 0 to 1000 mg/l COD). A pH meter (Thermo Scientific RL060P; Fig. 3.6b) was inserted into the aeration chamber and used to measure pH values from the beginning of each treatment. Two thermometers were used to measure temperatures in the incubator and catholytes. A data logger (National Instruments; Fig. 3.8a) was used to measure voltages between the anode and cathode every 20 seconds, and the data were directly recorded into the computer.

(a) (b)

Figure 3.6: Dissolved Oxygen Meter and pH Meter

22 160 1200 y = -1306.6x + 1323.2 y = 9188.2x - 246.08 140 R² = 0.9982 R² = 0.9997 1000 120

800

100

80 600 COD mg/l COD COD mg/l 60 400 40 200 20

0 0 0.85 0.9 0.95 1 1.05 0 0.05 0.1 0.15

ABS (OD420) ABS (OD620)

(a) (b)

Figure 3.7: COD Calibration Regression Lines (0 to 150 mg/l and 0 to 1000 mg/l): in −2 +3 COD test, dichromate ion (Cr2O7 ) is reduced to chromic ion (Cr ). In the wave- −2 length of 420 nm, dichromate ion (Cr2O7 ) is sensitive. The COD concentraiton increases as the concentration of hexavalent chromium decreases, and the optimum test range is 0 to 150 mg/l. In the wavelength of 620 nm, chromic ion (Cr+3) is sensitive. The COD concentration increases as the concentration of trivalent chromium increases, and the optimum test range is 0 to 1000 mg/l.

3.2.4 Data Analysis

In this study, data analysis included generating power density and polarization curves, and calculating total oxygen in catholytes, COD removal efficiencies, and coulombic efficiencies. Power density (power density versus current density) and polarization curves (voltage versus current density), as shown in Fig. 3.10, were plotted using the measured voltages and calculated current and power values (Eq. 3.1 and 3.2) for different external resistances from 10 Ω to 1M Ω by using a decade box (Fig. 3.8b).

The equations for determining current and current density are:

V I I I = ; Current Density = or (3.1) R A V

23 (a) (b)

Figure 3.8: Data Logger and Decade Box

where I = Current (mA), V = Voltage (mV ), R = Resistance (Ω), and A = Surface

Area of the Anodic Electrode (m2), V = Volume of the Anodic Chamber (m3).

The equations for determining power and power density are:

P P P = I · V ÷ 1000; P ower Density = or (3.2) A V where P = Power (mW ).

Total oxygen contains DO and hemoglobin bound oxygen. DO was measured by the

1 750 1K 2K 3K 5K 10K 50K 1M Cell 01

0.8

0.6

0.4 Voltage (mV) Voltage

0.2

0 0 20 40 60 80 100 120 140 160 Time (minutes)

Figure 3.9: An Example of Step Tests

24 0.6 60

Polarization Curve Power Density Curve

0.5 50

) 2

0.4 40

0.3 30 Voltage (V) Voltage

0.2 20 Power (mW/m Density Power 0.1 10

0 0 0 0.2 0.4 0.6 0 0.2 0.4 0.6 Current density (A/m2) Current density (A/m2)

(a) (b)

Figure 3.10: An Example of Polarization and Power Density Curve

DO meter (OrionTM StarTM A223), and oxygen dissociation curves (Fig. 3.11) were plotted by using a HEMOX analyzer. Hemoglobin bound oxygen in the catholyte was calculated by using estimated DO values, the oxygen-dissociation curve (Fig. 3.11), and Eq. 3.3 to 3.6, at pH 7.3 and 37◦C assuming no abnormal form of hemoglobin.

The barometric pressure was calculated using the following equation:

DO(mg/l) · (49(◦C) + T (◦C)) B (torr) = + W (torr) (3.3) P 0.827(◦C/torr · mg/l) V where BP = Barometric Pressure (torr), DO = Dissolved Oxygen (mg/l), T = Tem-

◦ perature ( C), and WV = Water Vapor (torr).

pO2(torr) = (BP − WV ) · O2 fraction (3.4)

where pO2 = Partial Pressure of Oxygen (torr), and O2 fraction = 0.209.

2.3564 (pO2) SaO2(%) = 2.3564 2.3564 (3.5) (pO2) + p50

25 Oxygen Dissociation Curve 1.0

0.8

0.6

0.4

OxygenSaturation (%) 0.2 P50 = 21.59 n = 2.3564 0.0 0 20 40 60 80 100 120 140 pO (torr) 2

Figure 1 - Run 1 hRBCs in Buffer Figure 3.11: Oxygen Dissociation Curve Oxygen Dissociation Curve 1.0

0.8

0.6 where SaO2 = Oxygen Saturation (%) and P50 (torr) is the value of pO2 when oxygen 0.4 saturation = 50 %.

OxygenSaturation (%) 0.2 P50 = 21.047 n = 2.3192 0.0 0 20 40 60 80 100 120 140 pO (torr) Oxygen Content(ml/l) = 2

Figure 2 - Run 2 hRBCs in Buffer

(Hgb · 1.36(ml/g) · SaO2) + (0.0031(ml/(l · torr)) · pO2(torr)) (3.6)

where Hgb = the concentration of hemoglobin in blood solution (g/l). COD removal eﬃciencies were calculated by using Eq. 3.7.

COD − COD COD Removal Efficiency(%) = i e · 100(%) (3.7) CODi where CODi = the COD concentration of the influent flow (mg/l), and CODe = the COD concentration of the effluent (mg/l).

Coulombic eﬃciencies were calculated using Eq. 3.8.

C Coulombic Efficiency(%) = 0 · 100% (3.8) Ci where C0 = the total coulombic output calculated by integrating the current generated by the MFC over time (C ), and Ci = the theoretical amount of coulombs (C ) available

26 from the feedstock. Integration of C0 was performed for that time interval where

Rext = 100 Ωs, to standardize between diﬀerent experiments during the step tests/ polarization curve tests. Ci was calculated according to Eq. 3.9.

Ci = F · n · M (3.9) where F = the Faradays constant (96,485 C/mol), n = the number of moles of electrons produced per mol of glucose equivalent, and M = the moles of glucose

(mol). The number of moles of glucose equivalents was calculated from Eq. 3.10.

COD − COD M = i e · v (3.10) 1.067 · 180(mg/mole) where v = the anolyte volume (l)

27 CHAPTER 4

RESULTS AND DISCUSSION

In this study, treatments included RBC concentrations of 0, 1, 2, 5, 10, and 12.5

% in the medium catholyte (App. A.2.1), and the control was deﬁned as the 0 %

RBC solution. Comparison experiments included three other catholyte variations:

DI-water with aeration, DI-water without aeration, and potassium ferricyanide. The operational conditions for the treatments and comparisons were 3.3 ml/hr of feed rate delivering 0.25 g/l glucose to the anolyte, 500 ml/hr recirculation rate with 150 ml of catholyte in cathodic chamber, and a temperature of 37◦C. Under these conditions, the baseline observed average voltage of the MFCs was determined to be 175 mV at

1,000 Ω, when using autoclaved distilled water without aeration as the catholyte.

4.1 Eﬀect of Varying Concentrations of RBCs in Blood-based

MFCs

4.1.1 Maximum Power Density and Open Circuit Voltage

Maximum power density was calculated by using Eq. 3.1 and 3.2 while external resistance was maintained at 1000, 2000, or 3000 Ω. Fig. 4.1 shows that the maximum power density of the medium control was 27.7 mW/m2 or 2.49 W/m3. In the treatment experiments, the highest average maximum power density reached 42.4 mW/m2 or 3.81 W/m3 attained with the highest concentration of RBCs (12.5 %)

28 in the medium; however, the lowest maximum power density did not appear in the lowest concentration of RBCs (0 %) but rather with 10 % RBCs. In addition, during the treatment of 10 % RBCs, the voltage dropped very quickly, which was diﬀerent from what was observed with the other treatments. It is speculated that the RBCs could have been damaged by remnants of bleach either in the tubing or on the pH meter. Among the treatments with the lower concentrations of RBCs (1, 2, and 5

%), maximum power density slightly increased from 27.7 to 31.4 mW/m2 (average maximum power density among the treatments of 1, 2, and 5 % RBCs). In the comparison experiments, MFCs with potassium ferricyanide catholytes had the highest average maximum power density of 100.9 mW/m2 or 9.06 W/m3. When catholytes were DI-water with aeration and DI-water without aeration, the average maximum power densities were 38 and 35.7 mW/m2 (or 3.42 and 3.41 mW/m3), respectively.

Figure 4.2 shows that the main voltage loss in the MFCs was activation loss probably caused by the surface structure and area of the anodic electrode and the amount of electrons transferred from bacteria to the anodic electrode. In this study, the anodic electrode was carbon cloth which has high surface area for attachment of bacteria, so it could suggest that most energy from substrate was not eﬀectively transferred into electrical energy. In the step test, the voltage rose to its open-circuit voltage (OCV) value when the external resistance was over 1 MΩ. Table 4.1 showed that OCV increased with an increase of the concentration of RBCs in the catholyte medium.

Compared with another MFC using rumen ﬂuid as inoculum while the catholyte was potassium ferricyanide, the maximum power density (101 mW/m2) in this study was higher than the maximum power density (66 mW/m2) reported by Rismani-Yazdi et al., (2011). Diﬀerences between this study and the reported 2011 study included:

29 120 100.9 12

9.06

)

100 ) 10 3

80 8

60 6 42.35 38 35.7 3.81 3.42 3.21 40 31.4 31.8 4 30.9 2.83 2.86 27.7 25.1 2.78 Power (W/m Density Power 2.49

Power (mW/m Density Power 2.26 20 2

0 0

2% RBC 2% 1% 1% RBC 5% RBC

1% RBC 1% RBC 5% 2% 2% RBC

10% RBC 10%

Potassium

Aeration

12.5% RBC 12.5%

Ferricyanide

Aeration

DI-Water with DI-Water

Medium Control Medium

MediumControl

DI-water without DI-water DI-waterwithout

(a) (b)

RBCs 10 RBCs Potassium Ferricyanide Potassium Ferricyanide DI-water with aeration DI-water with aeration 0 DI-water without aeration DI-water without aeration

120 0 1 2 3 4 5 12

HGB (g/l)

)

) 2 2 100 100.9 10 9.06 80 8

60 6 42.35 3.81

40 38 4 3.42 Power (mW/m Density Power Power (mW/m Density Power 35.7 3.21 31.8 30.9 20 31.4 25.1 2 2.86 2.78 27.7 2.49 2.83 2.26 0 0 0 1 2 3 4 5 0 1 2 3 4 5 Hgb (mg/l) Hgb (mg/l)

Figure 4.1: Average Maximum Power Density by Area (mW/m2) or by Volume (W/m3): the standard error bars representing the highest or lowest maximum power density in each experiment

different substrates (glucose vs. cellulose), different electrodes (carbon cloth and carbon paper vs. graphite plate), different reactor design (two vs. one cathodic chambers) and different operation (continuous vs. batch mode). The performance of an air-cathode MFC (Hu, 2008) using activated sludge as inoculum and glucose as substrate generated 129 mW/m2.

30 0.6 0 % RBC Cell 01 y = 0.5765e-10.11x 1 % RBC Cell 01 y = 0.807e-13.72x 2 % RBC Cell 01 y = 0.7498e-10.87x 0.5 5 % RBC Cell 01 y = 0.7849e-12.52x 10 % RBC Cell 01 y = 0.8852e-19.88x 12.5 % RBC Cell 01 y = 0.8186e-8.403x

0.4

0.3 Voltage (V) Voltage

0.2

0.1

0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Current density (A/m2)

(a)

0.6 0 % RBC Cell 02 y = 0.5621e-7.597x 1 % RBC Cell 02 y = 0.7055e-10.09x 2 % RBC Cell 02 y = 0.7298e-9.177x 0.5 5 % RBC Cell 02 y = 0.8381e-12.06x 10 % RBC Cell 02 y = 0.9382e-17.6x 12.5 % RBC Cell 02 y = 0.6421e-8.421x

0.4

0.3 Voltage (V) Voltage

0.2

0.1

0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Current density (A/m2)

(b)

Figure 4.2: Polarization Curves for Diﬀerent RBC Concentration in (a) Cell 01 and (b) 02 indicating ineﬀective electrons transfer from bacteria to the anodic electrode

31 Table 4.1: Open Circuit Voltages with Varying RBC Concentration

Open Circuit Voltage (mV) Catholyte Concentration Cell 01 Cell 02 Average

Control (0 % RBCs) 490 499 494.5

1% RBCs 492 494 493.0

2% RBCs 500 517 508.5

5% RBCs 505 507 506.0

10% RBCs 515 514 514.5

12.5% RBCs 526 527 526.5

32 4.1.2 Dissolved Oxygen and Total Oxygen

The DO values of the influent to the cathodic chamber fluctuated between 4 and 5 mg/l, as shown in Fig. 4.3, and the values were slightly lower than the control DO value of 5.63 mg/l in water at 37◦C without aeration. The DO values of the effluent decreased from 4.8 to 3.0 mg/l when the concentration of RBCs was increased from 0 to 10 %. When the RBC concentration was higher than 5 %, the difference of

DO values between influent and effluent flow was minutely raised from 0.3 to 0.9 mg/l.

Total oxygen (TO) was calculated by using the determined DO value and equations 3.3 to 3.6. Figure 4.4 demonstrated that TO values achieved a maximum of

71.5 mg/l while the concentration of RBCs was 12.5 % (or 4.1 mg/l Hgb), and the difference of TO values between influent and effluent was slightly increased as the

RBCs concentration was higher than 10 % (or 3.3 mg/l Hgb). It appears that the oxygen was not being released by hemoglobin.

Dissolved Oxygen

Influent Effluent

2 Dissolved(mg/l) Oxygen

0 0 1 2 3 4 5 Hgb (mg/l)

Figure 4.3: Dissolved Oxygen as a Function of Hemoglobin Concentration

33 Total Oxygen

Influent

40 Effluent Total Oxygen (mg/l) Oxygen Total 20

0 0 1 2 3 4 5 Hgb (mg/l)

Figure 4.4: Total Oxygen as a Function of Hemoglobin Concentration

4.1.3 COD Removal Eﬃciency

The theoretical COD value of 0.25 g/l glucose is 266 mg/l which was calculated using

Eq. 4.1 based on the biochemical reaction of C6H12O6 + 6O2 → 6CO2 + 6H2O.

0.25(g/l) · 1000(mg/g) · 6(mole O /mole glucose) · 32(g/mole) 180(g/mole) 2 = 266(mg/l) (4.1)

During the experiments, the average COD values of influent flow to the anodic chamber was 241 mg/l, and Fig. 4.5 showed the COD effluent values for each MFC in each experiment. Between the IV bag and the MFC reactor, feedstock passed through the cassette and tubing where the growth of bacteria in these feed lines led to a decrease of COD value before the feedstock reached the MFCs. In order to avoid the reduced concentration of substrate, the cassette and tubing were either cleaned using

DI-water rinses or replaced with new materials. After the treatment of 1 % RBCs, the cassette and tubing of both cells were flushed, and, as a result, COD values of the influent were slightly increased. After the treatment of 5 % RBCs, the cassette and tubing to both cells were replaced by new materials, and the COD values of 34 influent flow increased, achieving close to the theoretical COD value. The cassette and tubing of cell 02 were replaced again after the treatment of 12.5 % RBCs due to the low COD value in the influent flow. COD removal efficiency was calculated

Effluent Flow Effluent Flow 300 Removal 300 Removal 259 266 246 252 259 253 250 246 246 250 239 240 240 233 227 233 233 233

214 220

200 200

150 150

Total COD Total COD COD (mg/l) COD 100 (mg/l) COD 100

50 50

0 0

1% RBC 1% 2% RBC 2% RBC 5%

2% RBC 2% 1% RBC 1% RBC 5%

10% RBC 10%

10% RBC

Potassium

Aeration

12.5% RBC 12.5%

Ferricyanide

Aeration

DI-Water with DI-Water

Medium Control Medium

MediumControl

DI-waterwithout DI-waterwithout

(a) (b)

Figure 4.5: COD Values in (a) Cell 01 and (b) 02

by using Eq. 3.7 and the measured COD value. The range of average COD removal eﬃciency in each experiment was between 81.5 and 90.7 %, as shown in Fig. 4.6. Fig- ure 4.7 showed COD removal eﬃciency in cells 01 and 02, respectively. According to

Fig. 4.6, the COD removal efficiency was not affected by the concentration of RBCs, but rather the COD values of influent flow. The highest COD removal efficiency ap- peared in the treatment of 10 % RBCs for which the COD value of influent flow was also the highest. Moreover, the COD removal efficiency was lowered with a decrease of the COD value between the treatments of 12 % RBCs and potassium ferricyanide.

COD removal eﬃciency in an air-cathode MFC (Cheng et al., 2006) and another

MFC (Zhang et al., 2011) were 89-93 and 83-88 %, respectively. An air-cathode

35 100% 90.0% 84.4% 85.7% 89.5% 90.7% 85.3% 83.7%

83.3% 81.5%

80%

60%

40%

20% COD Removal Removal EfficiencyCOD

1% RBC 1% 2% RBC 2% RBC 5%

10% RBC 10%

Potassium

Aeration

12.5% RBC

Ferricyanide

Aeration

DI-Water with DI-Water

Medium Control Medium DI-water without DI-water

Figure 4.6: Average COD Removal Eﬃciency in Each Experiment

Effluent Flow Effluent Flow 92.8% 88.7% 89.6% 92.2% 88.2% 82.7% 82.2% 79.6% 84.0% 87.2% 80.1% 81.7% 86.8% 93.2% 84.0% 88.4% 87.8% 79.0%

100% Removal 100% Removal

80% 80%

60% 60%

40% 40%

20% 20%

COD Removal Removal Efficiency COD COD Removal Removal Efficiency COD

0% 0%

1% RBC 1% RBC 2% RBC 5%

2% RBC 2% 1% 1% RBC 5% RBC

10% RBC 10%

10% 10% RBC

Potassium

Aeration

12.5% RBC 12.5%

Ferricyanide

Aeration

DI-Water with DI-Water

Medium Control Medium

DI-water without DI-water DI-waterwithout

(a) (b)

Figure 4.7: COD Removal Eﬃciency in (a) Cell 01 and (b) 02

MFC (Cheng et al., 2006), used carbon cloth with platinum coating as the cathodic electrode, and was batch fed using glucose; the two chambers MFC (Zhang et al.,

2011), with plain graphite felt as the electrode materials, was batch fed using sodium acetate. In addition, in both studies microoganisms were collected from wastewater sludge. Compared to these MFCs in the literature, the MFCs in this research had very similar COD removal eﬃciency (81-91 %).

36 4.1.4 Coulombic Eﬃciency

Coulombic efficiency, the ratio between the electrical energy generated in the electrochemical reaction and the energy removed from substrate, was calculated by using equations 3.8 to 3.10, the measured COD value, and the calculated current while external resistance was 100 Ω. Fig. 4.8 indicated that coulombic efficiency varied between 11 and 13.9 % in the treatments with lower concentrations of RBCs. In the treatment section, the highest coulombic efficiency was 15.3 % corresponding to the highest concentration of RBCs (12.5 %); however, the lowest coulombic efficiency did not appear with the lowest concentration of RBCs (0 %) but rather with 10 % RBCs, due to the lower current in the treatment of 10 % RBCs. The coulombic efficiency of the control was 12.7 %. In the comparison section, the coulombic efficiency was slightly increased from 12.7 to 13.9 % when DI-water was aerated. Coulombic efficiency achieved 24.9 % with a catholyte of potassium ferricyanide.

Low coulombic efficiency may be caused by side metabolic reactions and the losses including activation, ohmic, and concentration losses. Besides electricity generation, the energy from the substrate could be used for formation of methane or other highly reduced metabolites due to the mixed culture. Coulombic efficiencies of an air-cathode MFC (Cheng et al., 2006) and the cellulose-fed MFC (Rismani-Yazdi et al., 2011) were reported to be 28 % (at 200 Ω) and 19 % (at 20 Ω), respectively. At the external resistances of 200 Ω and 20 Ω, coulombic efficiency of the blood-based

MFCs (with 12.5 % RBCs) was 14.1 and 20.5 %, respectively.

4.1.5 pH in Catholyte

In the treatment experiments, initial pH values of the catholytes were adjusted to

7.3. After inoculation of catholyte into the MFCs, pH quickly dropped to 7.18∼7.20

37 RBCs Potassium Ferricyanide 30% DI-water with aeration DI-water without aeration 24.9%

25% 30%

20%

25% 24.9%

13.9% 15.3% 12.7% 15% 13.6% 13.3% 12.2% 11.0% 20% 10% 6.6% 13.9% Coulombic Efficiency Coulombic 15.3% 15% 13.6% 5% 13.3% 12.2% 10% 12.7% 11.0% 0% Coulombic Coulombic Efficiency 6.6%

2% RBC 2% 1% RBC 1% RBC 5% 10% RBC 10%

Potassium 0%

Aeration

12.5% RBC 12.5%

Ferricyanide Aeration

DI-Water with DI-Water 0 1 2 3 4 5 Medium Control Medium DI-waterwithout Hgb (mg/l)

(a) (b)

Figure 4.8: Average Coulombic Eﬃciency, the ratio between the electrical energy generated in the electrochemical reaction and the energy removed from substrate

7.8 y = 0.0026x + 7.1625 7.7 7.6

7.5

pH 7.4 7.3 7.2 7.1 7 0 50 100 150 200 250

Time (minutes)

Figure 4.9: Change of pH in Catholyte over Time

within 20 minutes, and then generally increased to 7.4 within 100 minutes, and ﬁnally reached 7.6∼7.7, as shown in Fig.4.9. Even though the medium contained a buﬀer

(HEPES) for maintaining the stabilization of pH, the severe change of pH in the catholytes was inevitable, and eventually pH reached over 7.7. This caused not only a decrease of RBCs activity but also inhibition of the power generation of the MFCs.

38 CHAPTER 5

CONCLUSION

5.1 Summary

Blood-based MFCs, using RBCs in the catholyte solution, recycling that solution between the cathodic chamber and the aeration chamber (flask), were continuously fed using glucose at 37◦C. The best performance was observed with 12.5 % RBC which included maximum power density (45.75 mW/m2 at 1000 Ω), OCV (526.5 mV), COD removal efficiency (83.3 %), and coulombic efficiency (15.3 % at 100 Ω).

The materials and methods are:

• Microoganisms were from bovine rumen ﬂuid and RBC was from human blood.

• Feedstock contained 0.25 g/l glucose and salts.

• Feed rate was 3.3 ml/hr.

• RBC concentration was 0, 1, 2, 5, 10, and 12.5 %.

• RBC recycling rate was 500 ml/hr between the aeration chamber and the ca-

thodic chamber.

• Electrode materials included carbon cloth (anode) and carbon paper (cathode).

• CEMs were used to separate the anodic and cathodic chambers

39 5.2 Conclusions

According to Fig. 4.1 and Table 4.1, the hypothesis was proven to be true. It was demonstrated that an increase of RBC concentration in the catholyte can improve the electricity generation of MFCs. It should be noted that only short periods of stable electricity generation were observed. Many limitations of the experiment were artifacts of the in vitro system used. It is likely that in vivo conditions would solve many of these problems.

5.3 Limitations

During this research, five limitations of blood-based MFCs were observed: 1) an increase of pH value in the catholyte medium for incubation of RBCs, 2) limited flow rates of the blood solution, 3) settling of RBCs in the cathodic chamber, 4) limited concentrations of RBCs, 5) different blood samples. The limiting flow rate with water in the second type of MFC (small array system) was 600 ml/hr. Once the flow rate exceeded this value, the reactor started leaking from the holes or membranes, and potentially led to cross-contamination between anodic and cathodic chambers.

However, ﬂow rates less than 600 ml/hr could not prevent RBCs from settling out of solution, and the settling of RBCs was inevitable under 500 ml/hr. Those RBCs which had settled to the ﬂoor of the cathodic chamber weren’t able to deliver oxygen from the aeration chamber to the cathodic chamber. The highest concentration of

RBCs in this study (12 %) was quite low compared to the percentage of RBCs in whole blood (45 %). The limitation of the highest concentration of RBCs in this research was due to the relative scarcity of blood samples. Although no leaking happened during the treatment process but did during the pretest process, it is possible that higher concentrations of RBCs caused the leaking in these MFCs. In this study, two

40 different RBC samples were used and the samples were not from the same patient because only 25 to 30 ml of RBC can be isolated from a pack of purchased whole bloood via Red Cross. It is posslibe that different RBC samples inffluence the power generation.

5.4 Biomedical Application

The lowest power generation of the MFCs (2.26 W/m3) is higher than the output of a typical battery (0.29 W/m3) used in a pacemaker. However, the total volume

(including anode and cathode) of a battery in a pacemaker is only 5 to 8 cm3, much less than the total volume of the MFC (40 cm3) used in this study. Moverover, in an vivo environment, whole blood also contains white blood cells and platelets which could cause ﬁbrin formation around uncompatible materials.

5.5 Future Research

In future experiments with blood-based MFCs, several challenges need to be overcome and explored.

• Under MFC operation, in order to prolong and maintain the lifetime and ac-

tivity of RBCs, appropriate pH values need to be controlled.

• A new reactor design should be developed to overcome the viscous resistance

to high speed ﬂow rates and be a better simulation of the in vivo environment.

• A new operational system design is needed for measurement of pH and total

oxygen in the cathodic chamber.

• A study of higher concentrations of RBCs in the catholyte should be conducted.

41 • A study of appropriate materials for surfaces and electrodes of the MFCs is

needed to identify compatible materials which will prevent formation of ﬁbrin

in whole blood.

• It is important to improve oxygen release characteristics of RBCs in vitro by

exploring and controlling pH and CO2.

42 Appendix A

ANOLYTE AND CATHOLYTE SOLUTIONS

A.1 Multi-Purpose Anolyte Solutions

A.1.1 Mineral Solution I

K2HPO4: 3 g DI Water: 1000 mL

A.1.2 Mineral Solution II

KH2PO4: 3 g

NH4Cl: 4.86 g NaCl: 6 g

MgSO4: 0.6 g DI Water: 1000 mL

A.1.3 Feedstock Solution I

Glucose: 5 g

NH4H2PO4: 1 g NaCl: 5 g

MgSO4: 0.2 g

K2HPO4: 1 g

43 Reducing Agent: 20.00 mL

DI Water: 980.00 mL

A.1.4 Feedstock Solution II

Glucose: 0.25 g

Mineral Solution I: 150.00 mL

Mineral Solution II: 150.00 mL

Reducing Agent: 20.00 mL

DI Water: 680.00 mL

A.2 Catholyte

A.2.1 Medium for Red Blood Cells

HEPES: 10 ml(1 M)

Strep-Pen: 5 ml(10,000 U/ml)

Bovine Serum Albumin: 10 g

L-Gutamine: 1.25 ml(200 mM)

Basal Medium Eagle: 500 ml

A.2.2 Pottassium Ferricyanide Solution

Pottassium Ferricyanide (50 mM K3Fe(CN)6 in 100 mM K2HPO4)(pH 7)

K3Fe(CN)6 16.46 g

K2HPO4 17.42 g DI Water: 1000 mL

44 Appendix B

POLARIZATION AND POWER DENSITY CURVES

0.6 30 0.6 35 0.6 Polarization Curve Polarization Curve

0.5 25 0.5 30

Power Density Curve Power Density Curve 0.5

)

) 2 2 25

0.4 20 0.4 0.4

20 0.3 15 0.3 0.3

Voltage (V) Voltage

Voltage (V) Voltage Voltage (V) Voltage 0.2 10 0.2 0.2

Power density(mW/m Power Power density(mW/m Power

0.1 5 0.1 5 0.1

0 0 0 0 0 0 0.2 0.4 0.6 0 0.2 0.4 0.6 0.8 0 0.2 Current density (A/m2) Current density (A/m2)

Figure B.1: Polarization and Power Density Curves of Cell 01 and 02 for the Medium- only Control

45 0.6 30 0.6 40 Polarization Curve Polarization Curve 35 0.5 25 0.5

Power Density Curve Power Density Curve

)

30 )

2 2

0.4 20 0.4

0.3 15 0.3 20 Voltage (V) Voltage Voltage (V) Voltage 15

0.2 10 0.2 Power density(mW/m Power 10 (mW/m density Power 0.1 5 0.1 5

0 0 0 0 0 0.1 0.2 0.3 0.4 0 0.2 0.4 0.6 Current density (A/m2) Current density (A/m2)

Figure B.2: Polarization and Power Density Curves of Cell 01 and 02 in 1% RBCs

0.6 35 0.6 40 Polarization Curve Polarization Curve 35 0.5 30 0.5

Power Density Curve Power Density Curve

)

) 30 2 25 2

0.4 0.4

25 20 0.3 0.3 20

15 Voltage (V) Voltage Voltage (V) Voltage 15 0.2 0.2

10 Power (mW/m density Power Power density(mW/m Power 10 0.1 0.1 5 5

0 0 0 0 0 0.1 0.2 0.3 0.4 0.5 0 0.2 0.4 0.6 Current density (A/m2) Current density (A/m2)

Figure B.3: Polarization and Power Density Curves of Cell 01 and 02 in 2% RBCs

46 0.6 35 0.6 35 Polarization Curve Polarization Curve

0.5 30 0.5 30

Power Density Curve Power Density Curve

) ) 2 25 2 25

0.4 0.4

20 20 0.3 0.3

15 15

Voltage (V) Voltage Voltage (V) Voltage 0.2 0.2

10 10

Power (mW/m density Power Power (mW/m density Power

0.1 5 0.1 5

0 0 0 0 0 0.1 0.2 0.3 0.4 0.5 0 0.1 0.2 0.3 0.4 0.5 Current density (A/m2) Current density (A/m2)

Figure B.4: Polarization and Power Density Curves of Cell 01 and 02 in 5% RBCs

0.6 30 0.6 30 Polarization Curve Polarization Curve

0.5 25 0.5 25

Power Density Curve Power Density Curve

)

2 2

0.4 20 0.4 20

0.3 15 0.3 15

Voltage (V) Voltage Voltage (V) Voltage

0.2 10 0.2 10

Power (mW/m density Power Power density(mW/m Power 0.1 5 0.1 5

0 0 0 0 0 0.1 0.2 0.3 0.4 0 0.1 0.2 0.3 0.4 Current density (A/m2) Current density (A/m2)

Figure B.5: Polarization and Power Density Curves of Cell 01 and 02 in 10% RBCs

47 0.6 60 0.6 40 Polarization Curve Polarization Curve

0.5 50 0.5

Power Density Curve Power Density Curve

)

30 )

2 2

0.4 40 0.4

0.3 30 0.3 20

Voltage (V) Voltage Voltage (V) Voltage

0.2 20 0.2 Power (mW/m density Power 10 (mW/m density Power 0.1 10 0.1

0 0 0 0 0 0.2 0.4 0.6 0 0.2 0.4 0.6 Current density (A/m2) Current density (A/m2)

Figure B.6: Polarization and Power Density Curves of Cell 01 and 02 in 12.5 % RBCs

0.7 35 0.7 50 Polarization Curve Polarization Curve 45 0.6 30 0.6

Power Density Curve Power Density Curve 40

)

) 2

0.5 25 2 0.5 35

30 0.4 20 0.4 25

0.3 15 0.3 Voltage (V) Voltage

Voltage (V) Voltage 20

0.2 10 0.2 15

Power density(mW/m Power Power density(mW/m Power 10 0.1 5 0.1 5

0 0 0 0 0 0.2 0.4 0.6 0 0.2 0.4 0.6 0.8 Current density (A/m2) Current density (A/m2)

Figure B.7: Polarization and Power Density Curves of Cell 01 and 02 in DI-Water with Aeration

48 0.7 35 0.7 45 Polarization Curve Polarization Curve 40 0.6 30 0.6

Power Density Curve Power Density Curve 35

)

) 2 0.5 25 0.5 2

0.4 20 0.4 25

0.3 15 0.3 20

Voltage (V) Voltage

Voltage (V) Voltage Voltage (V) Voltage 15

0.2 10 0.2 Power density(mW/m Power 10 density(mW/m Power 0.1 5 0.1 5

0 0 0 0 0 0.1 0.2 0.3 0.4 0.5 0 0.2 0.4 0.6 0.8 Current density (A/m2) Current density (A/m2)

Figure B.8: Polarization and Power Density Curves of Cell 01 and 02 for DI-Water without Aeration Control

0.7 100 0.7 120 Polarization Curve Polarization Curve 90 0.6 0.6 100

Power Density Curve 80 Power Density Curve

)

) 2 0.5 70 2 0.5

60 0.4 0.4 50 60

0.3 0.3 Voltage (V) Voltage Voltage (V) Voltage 40 40

0.2 30 0.2

Power density(mW/m Power Power (mW/m density Power 20 0.1 0.1 20 10

0 0 0 0 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 Current density (A/m2) Current density (A/m2)

Figure B.9: Polarization and Power Density Curves of Cell 01 and 02 for Potassium Ferricyanide Control

49 Appendix C

CHEMICAL OXYGEN DEMAND TEST

The Science of CHEMICAL OXYGEN DEMAND Technical Information Series, Booklet No. 9 By: Wayne Boyles

K71.3 7053 Printed in U.S.A.

50 Table 2:

Major Oxidants Other than K2Cr2O7 and Mn2(SO4)3 Used in COD Determinations

Oxidant Advantages Disadvantages

KMnO4 • Stable for several months, MnO2 must be excluded • Relatively slow-acting and is not quantitative • Is used in acidic, neutral and basic media • Results may depend upon sample size • Manganese is a non-hazardous metal • Does not oxidize volatile acids or amino acids • Incomplete oxidation of many organic compounds

• Unstable in solution: Forms MnO2 precipitate which catalyzes reagent decomposition.

Ce(SO4)2 • More complete oxidation of organic compounds • Incomplete oxidation of many organic compounds than KMnO4 • Poor reproducibility • More stable than KMnO4 • Photometric measurement at 320 nm where incompletely oxidized organic compounds interfere • Relatively expensive

K2S2O • Oxidizes many organic nitrogen-containing • Requires elaborate equipment compounds more completely than other oxidants • More labor intensive • Widely used with TOC instrumentation • Relatively unstable

KIO3 • Strong oxidant • Difficult to use • Questionable accuracy

O2 • Oxygen consumption measured directly • Elaborate equipment required

The oxidants described in Table 2 have a number of limitations which are eliminated when K2Cr2O7 are used as an oxidant.

II. DICHROMATE CHEMICAL which is inserted into a block heater. Reagent and sample volumes are considerably smaller, which OXYGEN DEMAND decreases reagent cost and waste volume. Dichromate has been used to oxidize organic matter for more than 70 years. It has been preferred over other The two-hour digestion time can be reduced if caution is oxidants because of its superior oxidizing ability on a observed. Many types of waste are digested completely large variety of samples, and for its ease of use. The test in 30 minutes or less at 150 °C, the normal operating measures the oxygen equivalent of the amount of organic temperature. The time of complete digestion can be matter oxidized by potassium dichromate in a 50% recognized through experience, or by using a colorimetric sulfuric acid solution. Generally, a silver compound is reading with the micro method discussed later. In this added as a catalyst to promote the oxidation of certain approach, many consecutive readings are taken on a classes of organic compounds. A mercuric compound single sample, allowing a final determination of when may be added to reduce the interference from oxidation the reaction is complete. of chloride ions. After the oxidation step is completed, the amount of There are two digestion methods used in the COD test: dichromate consumed is determined titrimetrically the older Macro Digestion Method, and the Micro or colorimetrically. Either Digestion Method. The Macro Digestion Method requires the amount of reduced a considerable amount of space, equipment and volume chromium (trivalent) of reagents for each test. Each set-up includes a flask, a or the amount of glass condenser with hose, a hot plate, a laboratory stand, unreacted dichromate and clamps. Sample volumes are also relatively large. (hexavalent) can be Because of these inconveniences, the macro method has measured. End been virtually replaced by the micro method. The Micro products of the Digestion Method minimizes reagent consumption and reaction are carbon reduces the required space and equipment to one dioxide, water, and reactor block that will digest up to 25 samples at one various states of the time. Each test set-up is a self-contained disposable vial, chromium ion.

51 The micro method has several advantages over the macro Pros and Cons of Dichromate method, including the capture of volatile organics, small Pros sample size, elimination of cumbersome equipment, ț Dichromate accomplishes a complete oxidation when and a reduction in the volume of expensive and hazard- used with a catalyst and a two-hour digestion period. ous reagents. ț Dichromate is stable at room temperature when protected from exposure to light. Dichromate COD Chemistry When organic matter is oxidized by dichromate in sulfuric Cons ț acid, most of the carbon is converted to CO2. Hydrogen Some organic compounds are only partially oxidized. ț present is converted to H2O. The reaction is illustrated Some organic compounds, such as pyridine, are using the primary standard, potassium acid phthalate not oxidized. (KHP), as an example: ț There can be interference from inorganic pollutants, mainly chloride ions. 2 KC H O + 10 K Cr O + 41 H SO ——> 8 5 4 2 2 7 2 4 ț Reaction temperature is limited by thermal decom- 16 CO + 46 H O + 10 Cr (SO ) + 11 K SO 2 2 2 4 3 2 4 position of the oxidant. -2 ț Dichromate ions (Cr2O7 ) form orange-colored solutions. Dichromate is classified as a carcinogen. When dichromate is reduced to chromic ion (Cr+3), the solution becomes green. Intermediate valence states may Improving the Dichromate COD Test also occur. The standard reduction potential, E° (25 °C vs. Through careful research, many of the disadvantages to Normal Hydrogen Electrode, pH = 0) is about 1.36 volts. the COD test have been overcome or reduced in signi- The actual potential will vary with temperature, pH, and ficance. Incomplete oxidation of aliphatic hydrocarbons, the ratio of dichromate to chromic ion concentrations organic acids or alcohols have been improved by using according to the following equation: silver ion as a catalyst. Some compounds are not oxidized even with the catalyst. Disposal considerations play an E = E° + 0.0001983 T [H+] [Cr O 2–] ______log ______2 7 increasingly important role in chemical testing. +3 2 6 [Cr ] Although the micro method minimizes the volume of waste generated, the dichromate COD does contain Precision and Accuracy hexavalent chromium, which must be treated as A number of samples have been tested using Hach’s High hazardous wastes and mercury. Range, Low Range, and Ultra Low Range Dichromate COD vials. Results are given in Table 3 below.

Table 3: Dichromate COD Precision and Accuracy Relative Sample Dichromate Standard Standard Number COD Deviation Deviation of Tests mg/L mg/L % n 500 mg/L 5001 1.7 0.3 3 COD 500 mg/L 5081 1.0 0.1 3 COD + 500 mg/L Chloride Wastewater 2451 6 2.4 5 Influent Wastewater 452 4.7 2.6 5 Effluent Textile 1761 4.6 2.6 5 Industry ASTM 10181 14 1.3 3 Synthetic Wastewater Sample Swimming 133 0.6 4.6 3 Pool

1Hach High Range Dichromate COD Vial 2Hach Low Range Dichromate COD Vial 3Hach Ultra Low Range Dichromate COD Vial

6 52 COLORIMETRIC DETERMINATION A reagent blank must be prepared from each new lot of Procedures for COD measurement vials. This is done by carrying a sample of high-purity The measurement of COD test results is done using deionized water through the digestion process. The colorimetric and titrimetric procedures. Colorimetric blank is used to zero the spectrophotometer and can be procedures are easier and quicker to run and are gener- reused until a new lot of reagent is introduced. It must, ally more accurate. However, when samples are turbid however, be monitored for degradation. To monitor the or colored, or if a spectrophotometer is not available, a blank, fill a clean, empty COD vial with 5 mL of deion- titrimetric procedure should be used. Titrimetric proce- ized water. Set the instrument to absorbance mode and dures require a higher degree of operator skill and take the appropriate wavelength. Zero the instrument with longer to perform. the deionized water blank and measure the reagent blank absorbance. When the absorbance changes by approxi- Colorimetric Procedures mately 0.010 from its initial value, a new blank must be The micro COD test vial used run. Dichromate COD Reagent blanks are photosensitive for this digestion also serves and must be stored in the dark. Manganese III COD as a cuvette for colorimetric Reagent blanks are not photosensitive. measurement. Use with a test Hach provides Dichromate COD vials in four ranges, tube adapter in a Hach Ultra Low Range (0-40 mg/L), Low Range (0-150 mg/L), spectrophotometer or other High Range (0-1500 mg/L), and High Range Plus comparable model. Tests (0-15,000 mg/L). The Manganese III COD is available have shown that the in the 20-1000 mg/L range. optical properties of COD vials are very Dichromate COD Tests good. The variation Colorimetric Measurement for the in vial absorbance Ultra Low Range COD (0-40 mg/L Range) from batch to batch is (Using a Hach DR/4000) less than 0.004 units. A Hach DR/4000 and Figure 4. The Hach Ultra Low Range COD test is the lowest range test tube adapter are Hach DR/4000 and Test Tube Adapter and highest sensitivity COD test available. Results are shown in Figure 4. measured at a wavelength of 350 nm. The maximum sensitivity is at 345 nm, but the test measurement is made Colorimetric measurements allow the digestion to be at 350 nm for instrumentation considerations. The cali- monitored periodically for completeness. This means bration line for this test has a negative slope. The amount that easy-to-digest samples can be analyzed with confi- of hexavalent chromium remaining after digestion is dence in a short period of time. Typical time study measured and it decreases as the COD concentration curves are shown in Figure 5. They clearly demonstrate increases. High quality, organic-free, deionized water is that COD determinations made for process control required for blanks and dilution water with this test purposes can be conducted in a shorter digestion time range. Figure 6 shows several scan overlays of COD than specified in the procedure. For samples which are standards at various concentrations tested. difficult to oxidize, the digestion time can be extended up to four hours if a blank is also run for the same period +0.800 of time. 0 mg/L

600 +0.640 Manure 10 mg/L

Glutamic Acid (Theory = 500) 500 +0.450 20 mg/L Acetic Acid (Theory = 530)

400 +0.320 30 mg/L ABSORBANCE

+0.160 40 mg/L 300 COD mg/L 0.0000 200 320 330 340 350 360 370 380 390 400 410 WAVELENGTH

2-Picoline (Theory = 450) 100 Figure 6. Ultra Low Range COD scan using standards at 0, 10, 20, 30, 40 mg/L COD.

0 0 20 40 60 80 100 120 MINUTES Figure 5. Typical Digestion Curves - COD vs. Time 15 53 Colorimetric Measurement for the Ultra Low Range COD Test (0-40 mg/L) An example of a completely illustrated, easy-to-follow procedure from Hach.

HACH PROGRAM: 2700 COD, ULR

1. Perform the digestion 2. Press the soft key 3. The display will show: according to given under HACH PROGRAM. HACH PROGRAM: 2700 instructions. Select the stored program COD, ULR. The wavelength number for ultra low range (λ), 350 nm, is automatically COD by pressing 2700 with selected. the numeric keys. Press: ENTER

4. Insert the Test Tube 5. Clean the outside of 6. Place the blank into the Adapter into the sample the blank with a towel. adapter with the Hach cell module by sliding it logo facing the front of under the thumb screw the instrument. Close the and into the alignment light shield. grooves. Fasten with the thumb screw.

7. Press the soft key 8. Clean the outside of 9. Place the sample vial under ZERO. The display the sample vial with a into the adapter. Close the will show: 0.0 mg/L COD. towel. light shield. Results in mg/L COD (or chosen units) will be displayed.

16 54 Accuracy Check 9. Place the sample vial into the adapter. Close the Standard Solution Method. light shield. Results in mg/L COD (or chosen units) will Check the accuracy of the 0 to 40 mg/L range with a 30 be displayed. mg/L standard. Using Class A glassware, prepare a 1000- mg/L solution by diluting 850 mg of dried (120 °C, Accuracy Check overnight) potassium acid phthalate (KHP) in 1000 mL of Standard Solution Method organic-free deionized water. Prepare a 30 mg/L dilution Check the accuracy of the 0 to 150 mg/L range with a by diluting 3.00 mL of this solution into a 100.0 mL 100 mg/L KHP standard. Prepare by dissolving 85 mg of volumetric flask. Dilute to volume with deionized water, dried (120 °C, overnight) potassium acid phthalate (KHP) stopper, and invert 10 times to mix. in 1 liter of deionized water. Use 2 mL as the sample volume. Or dilute 10 mL of 1000-mg/L COD Standard Method Performance Precision Solution to 100 mL to produce a 100-mg/L standard. Standard: 30.0 mg/L COD To adjust the calibration curve using the reading obtained Program 95% Confidence Limits ______with the 100-mg/L standard solution, press the soft keys 2700 29.9 - 30.1 mg/L COD under OPTIONS< MORE then STD:OFF. Press ENTER to accept the displayed concentration, the value of which Estimated Detection Limit depends on the selected units. If an alternate concentra- Program EDL ______tion is used, enter the actual concentration and press 2700 0.2 mg/L COD ENTER to return to the read screen. Sensitivity Method Performance Precision Program Number: 2700 Standard: 100.0 mg/L COD ∆ ∆ ______Portion of Curve _____Abs ______Concentration ______Program ______95% Confidence Limits Entire Range 0.010 -0.52 mg/L 2710 99.4 - 100.6 mg/L O2 Estimated Detection Limit COLORIMETRIC MEASUREMENT FOR THE ______Program ______EDL LOW RANGE COD (0-150 mg/L RANGE) 2710 1.1 mg/L COD (Using a Hach DR/4000: Please note—procedure is fully illustrated with icons in the instrument manual.) Sensitivity Program Number: 2710 The Hach Low Range COD is measured at 420 nm. The Portion of Curve ∆Abs ∆Concentration test range is 0-150 mg/L COD. The COD concentration ______increases as the concentration of hexavalent chromium Entire Range 0.010 3.45 mg/L decreases. This results in a calibration line with a negative slope. The optimum test range is about 20 to 150 mg/L COD. COLORIMETRIC MEASUREMENT FOR THE HIGH RANGE COD (0-1500 mg/L Procedure RANGE) AND HIGH RANGE PLUS 1. Perform the digestion according to given instructions. (0-15000 mg/L RANGE) 2. Press the soft key under HACH PROGRAM. Select the (Using a Hach DR/4000: Please note—procedure is fully stored program number for Low Range COD by pressing illustrated with icons in the instrument manual.) 2710 with the numeric keys. Press: ENTER Hach’s High Range and High Range Plus COD are the 3. The display will show: HACH PROGRAM: 2710 COD, highest test ranges available from Hach Company. The LR. The wavelength (λ), 420 nm, is automatically selected. chemistry and calibration data are identical for both 4. Insert the Test Tube Adapter into the sample cell tests. High Range Plus COD is designed to eliminate module by sliding it under the thumb screw and into the the dilution step normally required for COD samples alignment grooves. Fasten with the thumb screw. which have concentrations from 1500 mg/L up to 15,000 mg/L. When the High Range Plus vial is manufac- 5. Clean the outside of the blank with a towel. tured, dilution water is added directly to the High Range 6. Place the blank into the adapter with the Hach logo COD Reagent to accomplish a 1 to 10 dilution when facing the front of the instrument. Close the light shield. 0.20 mL of sample is added to the reagent vial. The results are measured at 620 nm, and the calibration line 7. Press the soft key under ZERO. The display will show: has a positive slope. The amount of trivalent chromium 0.0 mg/L COD. is measured, and its concentration increases as the COD 8. Clean the outside of the sample vial with a towel. concentration increases.

17 55 Procedure Method Performance Precision 1. Perform the digestion according to given instructions. 0-1500 mg/L range Standard: 1000 mg/L COD 2. Press the soft key under HACH PROGRAM. Select the Program 95% Confidence Limits stored program number for High and High Range Plus ______COD by pressing 2720 with the numeric keys. Press: 2720 998 - 1002 mg/L COD ENTER 0-15,000 mg/L range 3. The display will show: HACH PROGRAM: 2720 COD, Standard: 10,000 mg/L COD HR, HR Plus. The wavelength (λ), 620 nm, is automati- ______Program 95%______Confidence Limits cally selected. 2720 9980 - 10,020 mg/L COD 4. Insert the Test Tube Adapter into the sample cell Estimated Detection Limit module by sliding it under the thumb screw and into the Program EDL alignment grooves. Fasten with the thumb screw. ______2720 (0 - 1500 mg/L) 3 mg/L COD 5. Clean the outside of the blank with a towel. 2720 (0 - 15,000 mg/L) 30 mg/L COD 6. Place the blank into the adapter with the Hach logo Sensitivity facing the front of the instrument. Close the light shield. Program Number: 2720 ∆ ∆ 7. Press the soft key under ZERO. The display will show: ______Portion of Curve _____Abs ______Concentration 0.0 mg/L COD. Entire Range 0.010 -23.5 mg/L 8. Clean the outside of the sample vial with a towel. 9. Place the sample vial into the adapter. Close the light shield. Results in mg/L COD (or chosen units) will be MANGANESE III COD TEST displayed. When High Range Plus COD vials are used, Colorimetric Measurement for the multiply the displayed value by ten. Manganese III COD (20 to 1000 mg/L COD) (Using a Hach DR/4000: Please note—procedure is fully Accuracy Check illustrated with icons in the instrument manual.) Standard Solution Method The Hach Manganese III COD Procedure can be run with 0-1500 mg/L range: Check the accuracy of the 0 to or without the chloride removal pretreatment. If chloride 1,500 range by using either a 300 mg/L or 1000 mg/L is absent or does not present a significant interference, COD Standard Solution. Use 2 mL of one of these the pretreatment steps can be omitted. The working solutions as the sample volume; the expected result will range of the test is 20 to 1000 mg/L COD. The test is mea- be 300 or 1000 mg/L COD respectively. sured at 510 nm, and the calibration line has a negative Or, prepare a 500-mL standard by dissolving 425 mg slope. When manganese III is measured spectrophoto- of dried (120 °C, overnight) KHP in 1000 mL of metrically, its concentration decreases as the COD concen- deionized water. tration increases. High quality, organic-free deionized water is required for blanks and dilution water. Figure 7 To adjust the calibration curve using the reading obtained shows scans of COD standards tested using the Mn III with the 100-mg/L standard solution, press the soft keys COD Reagent. under OPTIONS< MORE then STD:OFF. Press ENTER to +1.200 accept the displayed concentration, the value of which Blank depends on the selected units. If an alternate concentration 100 mg/L is used, enter the actual concentration and press ENTER +0.960 to return to the read screen. 300 mg/L

0-15,000 mg/L range: Check the accuracy of the 0 to +0.720 15,000 mg/L range by using a 10,000 mg/L COD Standard 500 mg/L

Solution. Prepare the 10,000 mg/L solution by dissolving +0.480 8.500 g of dried (120 °C, overnight) KHP in 1 liter of

ABSORBANCE 800 mg/L deionized water. Use 0.2 mL of this solution as the sam- +0.240 ple volume; the expected result will be 10,000 mg/L 1000 mg/L COD (display x 10). 0.0000 To adjust the calibration curve using the reading obtained 450 500 550 600 with 1000 mg/L COD Standard Solution, press the soft WAVELENGTH keys under OPTIONS< MORE then STD:OFF. Press Figure 7. Overlay scans of standards with concentrations of ENTER to accept the value and return to the screen. The (blank) 0, 100, 300, 500, 800, and 1000 mg/L COD, which were instrument will only allow adjustment if the entered con- tested using the Mn III COD Reagent. centration is within 10% of the measured concentration. 18 56 BIBLIOGRAPHY

Barton, S. C., J. Gallaway, and P. Atanassov. 2004. Enzymatic Biofuel Cells for Implantable and Microscale Devices. Chemical Reviews. 104 (10): 4867–86.

Biﬃnger, J. C., and B. R. Ringeisen. 2008. Engineering Microbial Fuels Cells: Recent Patents and New Directions Engineering Microbial Fuels Cells: Recent Patents and New Directions. Recent Patents on Biotechnology. (2): 150–155.

Chaudhuri, S. K., and D. R. Lovley. 2003. Electricity Generation by Direct Oxida- tion of Glucose in Mediatorless Microbial Fuel Cells. Nature Biotechnology. 21 (10): 1229–32.

Chen, S., G. Liu, R. Zhang, B. Qin, and Y. Luo. 2012. Development of the Mi- crobial Electrolysis Desalination and Chemical-production Cell for Desalination as Well as Acid and Alkali Productions. Environmental Science and Technology. 46 (4): 2467–72.

Cheng, S., H. Liu, and B. E. Logan. 2006. Increased Power Generation in a Con- tinuous Flow MFC with Advective Flow through the Porous Anode and Reduced Electrode Spacing. Environmental Science and Technology. 40 (7): 2426–32.

Dumas, C., A. Mollica, D. Fron, R. Bassguy, L. Etcheverry, and A. Bergel. 2007. Marine Microbial Fuel Cell: Use of Stainless Steel Electrodes as Anode and Cathode Materials. Electrochimica Acta. 53 (2): 468–473.

Freedman, J. C. 1983. Partial Requirements for in Vitro Survival of Human Red Blood Cells. Membrane Biology. 231 (75): 225–231.

Habermann, W., and E. H. Pommer. 1991 Biological fuel cells with sulphide storage capacity. Applied Microbiology and Biotechnology. 35 (1): 128–133

Han, Y., C. Yu, and H. Liu. 2010. A Microbial Fuel Cell as Power Supply for Implantable Medical Devices. Biosensors and Bioelectronics. 25 (9): 2156–60.

He, Z., H. Shao, and L. T. Angenent. 2007. Increased Power Production from a Sediment Microbial Fuel Cell with a Rotating Cathode. Biosensors and Bioelectronics. 22 (12): 3252–5.

57 Hoﬀbrand, A. V., Moss, P. A. H., and Pettit, J. E. Essential Haematology. Chapter 2, Erythropoiesis and general aspects of anaemia. Malden: Blackwell Publishing Ltd., 2006

Hu, Z. 2008. Electricity Generation by a Baﬄe-chamber Membraneless Microbial Fuel Cell. Journal of Power Sources. 179 (1): 27–33.

Huang, L., and B. E. Logan. 2008. Electricity Generation and Treatment of Pa- per Recycling Wastewater Using a Microbial Fuel Cell. Applied Microbiology and Biotechnology. 80 (2): 349–355.

Huggins, T., P. H. Fallgren, S. Jin, and Z. J. Ren. 2013. Energy and Performance Comparison of Microbial Fuel Cell and Conventional Aeration Treating of Wastewa- ter. Microbial and Biochemical Technology. S6 (2):1–5.

Jang, J. K., T. H. Pham, I. S. Chang, K. H. Kang, H. Moon, K. S. Cho, and B. H. Kim. 2004. Construction and Operation of a Novel Mediator- and Membrane-less Microbial Fuel Cell. Process Biochemistry. 39 (8): 1007–1012.

Justin, G. A., Y. Zhang, M. Sun, and R. Sclabassi. 2005. An Investigation of the Ability of White Blood Cells to Generate Electricity in Biofuel Cells. Proceedings of the IEEE 31st Annual Northeast Bioengineering Conference, 2005. 277–278.

Karube, I., T. Matsunaga, S. Tsuru, and S. Suzuki. 1977. Biochemical fuel cell utilizing immobilized cells of clostridium butyricum. Biotechnology Bioengineering. 19: 1727–1733.

Kaushansky, Lichtman, Beutler, Kipps, Swligsohn, and Prchal. Williams Hematol- ogy. Chapter 29, Morphology of the Erythron. Chapter 33, Clinical Manifestations and Classiﬁcation of Erythrocyte Disorders. New York: McGraw-Hill Medical, 2010, pp. 418, 455.

Kim, H. J., H. S. Park, M. S. Hyun, I. S. Chang, M. Kim, and B. H. Kim. 2002. A Mediator–less Microbial Fuel Cell Using a Metal Reducing Bacterium, Shewanella Putrefaciens. Enzyme and Microbial Technology. 30 (2): 145–152.

Kim, Y., and B. E. Logan. 2013. Microbial Desalination Cells for Energy Production and Desalination. Desalination. 308: 122–130.

Larrosa–Guerrero, A., K. Scott, I. M. Head, F. Mateo, A. Ginesta, and C. Godinez. 2010. Eﬀect of Temperature on the Performance of Microbial Fuel Cells. Fuel. 89 (12): 3985–3994.

Lefebvre, O., Z. Tan, Y. Shen, and H. Y. Ng. 2013. Optimization of a Microbial Fuel Cell for Wastewater Treatment Using Recycled Scrap Metals as a Cost–eﬀective Cathode Material. Bioresource Technology. 127: 158–64.

58 Liu, Y., V. Climent, A. Bern, and J. M. Feliu. 2011. Eﬀect of Temperature on the Catalytic Ability of Electrochemically Active Bioﬁlm as Anode Catalyst in Microbial Fuel Cells. Electroanalysis. 23 (2): 387–394.

Min, Booki, J. K., S. Oh, J. M. Regan, and B. E. Logan. 2005. Electricity Generation from Swine Wastewater Using Microbial Fuel Cells. Water Research. 39 (20): 4961–8.

Sally, O. Blood Gas Transport. Accessed April 9, 2014. http://www.sallyo sborne.com /Med%20Lecture–%20Transport%20Of%20Blood%20Gases.pdf

Patil, S. A., V. P. Surakasi, S. Koul, S. Ijmulwar, A. Vivek, Y. S. Shouche, and B. P. Kapadnis. 2009. Electricity Generation Using Chocolate Industry Wastewater and Its Treatment in Activated Sludge Based Microbial Fuel Cell and Analysis of Developed Microbial Community in the Anode Chamber. Bioresource Technology. 100 (21): 5132–9.

Pham, T. H., J. K. Jang, I. S. Chang, and B. H. Kim. 2004. Improvement of Cathode Reaction of a Mediatorless Microbial Fuel Cell. Microbiology Biotechnology. 14 (2): 324–9.

Pittman RN. 2011. Regulation of Tissue Oxygenation. Chapter 4, Oxygen Transport. San Rafael (CA): Morgan and Claypool Life Sciences. Available from: http://www.nc bi.nlm.nih.gov/books/NBK54103/

Potter, M. C. 2010. Electrical Eﬀects Accompanying the Decomposition of Organic Compounds. The Royal Society. 84 (571): 260–276.

Rabaey, K., G. Lissens, S. D. Siciliano, and W. Verstraete. 2003. A Microbial Fuel Cell Capable of Converting Glucose to Electricity at High Rate and Eﬃciency. Biotechnology Letters. 25 (18): 1531–5.

Rabaey, K., N. Boon, M. Hfte, and W. Verstraete. 2005a. Microbial Phenazine Production Enhances Electron Transfer in Biofuel Cells. Environmental Science and Technology. 39 (9): 3401–8.

Rabaey, K., and W. Verstraete. 2005b. Microbial Fuel Cells: Novel Biotechnology for Energy Generation. Trends in Biotechnology. 23 (6): 291–8.

Richter, H., K. McCarthy, K. P. Nevin, J. P. Johnson, V. M. Rotello, and D. R. Lovley. 2008. Electricity Generation by Geobacter Sulfurreducens Attached to Gold Electrodes. American Chemical Society. 24 (8): 4376–9.

Rismani–Yazdi, Hamid, Ann D Christy, Sarah M Carver, Zhongtang Yu, Burk a Dehority, and Olli H Tuovinen. 2011. Eﬀect of External Resistance on Bacterial Di- versity and Metabolism in Cellulose-fed Microbial Fuel Cells. Bioresource Technology. 102 (1): 278–83.

59 Rismani–Yazdi, H. S. Carver, A. D. Christy, and O. H. Tuovinen. 2008. Cathodic limitations and optimization in microbial fuel cells; An overview. Journal of Power Sources. 180:683-694.

Rismani–Yazdi, H., A. D. Christy, B. A. Dehority, M. Morrison, Z. Yu, and O. H. Tuovinen. 2007. Electricity Generation From Cellulose by Rumen Microorganisms in Microbial Fuel Cells. Biotechnology and Bioengineering. 97 (6): 1398–1407.

Rizzo, A., F. Boano, R. Revelli, and L. Ridolﬁ. 2013. Can Microbial Fuel Cells Be an Eﬀective Mitigation Strategy for Methane Emissions from Paddy Fields? Ecological Engineering. 60: 167–171.

Scott, K., E. H. Yu, M. M. Ghangrekar, B. Erable, and M. M. Duteanu. Comprehen- sive Renewable Energy. Chapter 4, Fuel Cells and Hydrogen Technology. Waltham: Elsevier Ltd., 2012, pp. 277–300.

Shier, D., J. Butler, and R. Lewis. Hole’s essentials of human anatomy and physiology. Chapter 12, Blood. Boston : McGraw-Hill, 2003.

Siu, C., and M. Chiao. 2008. A Microfabricated PDMS Microbial Fuel Cell Journal of Microelectromechanical Systems. 17 (6): 1329–1341.

Stewart A. R., F. D. Wilde, and G. F. Ritz. U.S. Geological Survey Techniques of Water-Resources Investigations. 2013. Accessed April 9, 2014, http://water.u sgs.gov/owq/FieldManual/Chapter6/6.2−ver3.pdf Uria, N., D. Snchez, R. Mas, O. Snchez, and F. Xavier. 2012. Chemical Eﬀect of the Cathode/Anode Ratio and the Choice of Cathode Catalyst on the Performance of Microbial Fuel Cell Transducers for the Determination of Microbial Activity. Sensors and Actuators. B170: 88–94.

Wagner, R. C., J. M. Regan, S. Oh, Y. Zuo, and B. E. Logan. 2009. Hydrogen and Methane Production from Swine Wastewater Using Microbial Electrolysis Cells. Water Research. 43 (5): 1480–1488.

Wang, C., C. J. Yang, and Z. Chen. 2012a. Rumen Microbial Volatile Fatty Acids in Relation to Oxidation Reduction Potential and Electricity Generation from Straw in Microbial Fuel Cells. Biomass and Bioenergy. 37: 318–329.

Wang, Y., X. Liu, W. Li, F. Li, G. Sheng, R. J. Zeng, and H. Yu. 2012. A Micro- bial Fuel Cellmembrane Bioreactor Integrated System for Cost–eﬀective Wastewater Treatment. Applied Energy. 98: 230–5.

Wei, J., P. Liang, and X. Huang. 2011. Recent Progress in Electrodes for Microbial Fuel Cells. Bioresource Technology. 102 (20): 9335–44.

60 Zhang, L., C. Li, L. Ding, K. Xu, and H. Ren. 2011. Inﬂuences of Initial pH on Performance and Anodic Microbes of Fed–batch Microbial Fuel Cells. Journal of Chemical Technology and Biotechnology. 86 (9): 1226–1232.

Zhou, M., M. Chi, J. Luo, H. He, and T. Jin. 2011. An Overview of Electrode Materials in Microbial Fuel Cells. Journal of Power Sources. 196 (10): 4427–4435.