1.2.1.1 Strategies to limit the cross-diffusional mixing

In order to restrict fuel and oxidant mixing to a thin interfacial width Smix sufficiently far from the electrodes (see Fig. 3), the flow rate should be increased to an optimal value to provide little to no fuel crossover, while yielding high reactants consumption (Lee et al., 2007), and besides, the electrodes must have sufficient separation distance within the microchannel (Kjeang et al., 2009). Generally, to confirm that the diffusive crossover doesn’t contribute to the loss of current, the width of the mixed region Smix is calculated using Eq. 6. (Zebda et al., 2009b). Another strategy to prevent the direct contact and the reaction between oxidant and fuel was proposed in the case of a microfluidic fuel cell working from formic acid as fuel (Sun et al., 2007). A three-stream laminar flow fuel cell was developed that consisted to introduce a third stream containing only electrolyte solution between fuel and oxidant streams.

The most suitable waste for converting into bioethanol is the waste from the fruit and vegetable industries, for instance, cotton fiber, milk whey from cheese-making, the waste products of coffee making, and so on. Generally speaking, such waste contains approximately 45% of cellulose (glucose polymer), which can be simultaneously hydrolyzed and fermented to produce ethanol. SSL (Spent Sulfite Liquor) is a byproduct of bisulfite "pulp" manufacturing that can also be fermented to produce ethanol. Waste varies considerably in content from one area to another, but the majority of the volume generally consists of paper (20-40%), gardening waste (10-20%), plastics, glass, metals and various other materials (Prasad et al., 2007).

1.10 Miscanthus

This is a type C4 graminaceous perennial that forms rhizomes. Miscanthus x giganteus is generally used to obtain biofuels: this is a sterile tetraploid hybrid obtained from Miscanthus sinensis and Miscanthus sacchariflorus, characterized by a yield that in autumn reaches 30 t ha-1 in irrigated soils and 10-25 t ha-1 in those without irrigation. The contribution of Miscanthus sacchariflorus to the Miscanthus x giganteus genome lies in its adaptability to warm climates, while Miscanthus sinensis provides the genetic resources needed in the colder regions. It is often used as an ornamental grass or cover crop and it can grow as much as 4 m high. It takes three years to arrive at a stable yield (around 5 years in marginal soils) and in its first year of growth the rhizomes are particularly sensitive to low temperatures, whereas in subsequent years they can even withstand temperatures of around -40°C. The rhizomes remain inactive in winter and begin to grow when the temperatures of the soil reaches 10- 12°C. As for the plant’s energy value, the dry matter has a net calorific value of approximately 17 MJ/kg. The energy value of 20 t of dry Miscanthus is approximately the same as that of 8 t of coal (Heaton et al., 2004; Sanchez & Cardona, 2008; DEFRA, 2011).

When Panicum virgatum and Miscanthus (Heaton et al., 2004) — both type C4 plants of considerable interest as energy sources — are compared, Miscanthus produces more biomass per unit than Panicum virgatum (i. e. 12 Mg ha-1). Both plants are perennials and this means a saving because there is no need to replant them. In areas with an abundant rainfall but problems of nitrogen contamination of the water supply, it is better to use Miscanthus as an energy crop, whereas growing Panicum virgatum with adequate nitrogen fertilizing certainly produces a better yield in uncontaminated dry areas.

Until now, majority of the research was focused on in-vitro experiments by mimicking physiological conditions. The additional complex problems may arise when a BFC chip is placed inside a blood artery. The first is with implantation process itself, which involves a surgery for the insertion of a BFC, and other necessary electronics components. The second is the stability of this chip inside an artery and how/where this chip can be fixed such that it can survive against the blood flow. Third problem is the clotting of the blood. The goal is to put this EBFC chip in such a way that it does not obstruct the flow of blood and lead to substantial pressure drop inside an artery. The fixation of this chip with the blood artery also should not harm the blood vessel walls (Parikh et al., 2010).

In order to improve mass transport around microelectrodes by optimizing the positioning of an EBFC chip, we have adopted the finite element analysis approach to look into the stability of an EBFC inside a blood artery. On the initial stage, we have analyzed only two orientations: horizontal position (HP) and vertical position (VP). The stability of the chip in these positions, diffusion and convectional fluxes around microelectrodes has been finely investigated. We have proposed a novel chip design, with holes in between all electrodes on the substrate, which can drastically improve the diffusion in between microelectrodes.

The diffusion between the microelectrodes has shown in Fig. 9, where Fig. 9a and b shows the simulation profiles for diffusive flux along with the streamlines around microelectrodes in HP and VP, respectively. In HP, it is observed that the diffusive flux is less near the central electrodes and increases when going towards outer electrodes. However, the diffusive flux is almost same on top of all electrodes in VP. It is observed that in both the positions, the diffusive flux is following laminar pattern. The diffusive flux from bottom of an electrode to top of an electrode is investigated in HP and VP as shown in Fig. 9c and d, respectively. The flux is not uniform from the central to outer electrodes. The electrodes located at the circumference of a chip are having more flux compared to those located in the centre of the chip. The variation of the diffusive flux distribution around inner to outer electrodes is high in HP. The flux is not constant at every instance, but it is oscillating as shown in inset figures. The diffusive flux profiles in these figures are considered at the time, when the flux reaches its maximum value. This is also evident from Fig. 9e and f, the flux is higher exactly at the top of electrodes while lesser in the vicinity between any two electrodes. In comparison of HP and VP, the diffusive flux is 8 orders larger in case of VP than in HP.

Total flux is the combination of a diffusive flux and a convective flux. Fig. 10 depicts the total flux data for (a) HP and (b) VP of a chip. In HP, flux is negligible up to almost 275 pm height of electrodes and then increasing at the top. Total flux is highest at the top of outer most electrodes and then reducing to the central electrodes. In case of VP, the flux is almost uniform on top of all electrodes, with negligible value in between electrodes up to 200 pm height and then gradually increasing to about 2000-3500 mmol m-2 s-1 at the top of all electrodes.

Based on the results, the new design with the holes in between all microelectrodes has been inspected precisely and compared with the prototype design. The diffusive flux (Fig. 11a, c, e) and convective flux (Fig. 11b, d, f) profiles for the new design are compared with diffusive flux and convective flux profiles of the prototype model, respectively. The streamlines present the lines of motion of glucose at a particular instance.

(a)	(b)
(d)

a)

From Fig. 11 it is inferred that the total flux (combined diffusive and convective flux) has been improved between all microelectrodes in terms of values and their uniformity for the chip with the holes. This enhanced mass transport around microelectrodes is significantly important for an EBFC performance. This proposed design could also be advantageous to prevent blood clotting. Human blood is mainly consisted of red blood cells and white blood cells. The sizes of all these cells such as red blood cells (6 pm), lymphocyte (7-8 pm), neutrophil (10-12 pm), eosinophil (10-12 pm), basophil (12-15 pm), and monocytes (14­17 pm) are mostly smaller than 20 pm, the size of the holes provided in the chip. So these cells can pass through the holes in between microelectrodes without blocking the way in between micro-electrodes. These holes can be made bigger depending on the requirement. The improved convection in between microelectrodes may also be forceful enough to eliminate the bubble formation. However, the biomechanical process and hemodynamic process are more complex than convection and diffusion, especially on the micro-scale level. Cell growth and clotting phenomenon are related to many aspects, such as: biocompatibility, bending of blood artery, platelet and protein components. More detailed research needs to be done with biologists in order to obtain more sufficient and helpful information and further reach the applicable level of the EBFCs.

Fig. 11. Surface plot with streamlines for (a) diffusive flux and (b) convective flux of glucose around microelectrodes; (c) diffusive flux and (d) convective flux in between all 24 electrodes from bottom of electrodes to up to 300 pm height; (e) diffusive and (f) convective flux at top of all the electrodes from leftmost to right most electrodes for 0 — 10 secs.

3. Conclusion

In this chapter, we have introduced the two major kinds of biofuel cells-microbial fuel cells and enzymatic biofuel cells. Significant development on both biofuel cells has been achieved in the past decade. With the demands for reliable power supplies for medical devices for implantable applications, great effort has been made to make the miniaturized biofuel cells. The past experiment results revealed that the enzymatic miniature biofuel cells could generate sufficient power for slower and less power-consuming CMOS circuit. In addition, we have also presented simulation results showing that the theoretical power output generated from C-MEMS enzymatic biofuel cells can satisfy the current implantable medical devices. However, there are some challenges for further advancements in miniaturized biofuel cells. The most significant issues include long term stability and non-sufficient power output. Successful development of biofuel cell technology requires the joint efforts from different disciplines: biology to understand biomolecules, chemistry to gain knowledge on electron transfer mechanisms; material science to develop novel materials with high biocompatibility and chemical engineering to design and establish the system.

4. Acknowledgements

This project is supported by national Science Foundation (CBET# 0709085).

Transesterification is the technological route more used for biodiesel production, and can be applied on a small scale, as in laboratories, or in industry, producing millions of gallons of biofuel. Although the esterification also results in biodiesel and is recommended when the raw material is composed of oils rich in free fatty acids, this technique is applied commercially in few industries. That’s why we decide to mention in this chapter only the transesterification process. In this section, mechanisms of the transesterification reaction are going to be explained, identifying all process variables affecting the biodiesel yield and finally some important optimization studies will be presented.

Based on screening in flask fermentations performed in an anaerobic chamber, every feedstock (sugar beet, corn and glucose) was matched with appropriate Clostridium strain regarding to yield and productivity values. Sugar beet is a crop grown in the Czech Republic for the last 160 years which provides high yields and can be used in the non food field for the biofuel production. In fact, non-food utilization of sugar beet is already running in CR but only bioethanol is produced in this way in Agroethanol TTD. Regarding corn, its main portion is grown for cattle feeding in CR but at the same time, the size of cattle herds diminishes every year. As the important goals of the biofuels production are, beside others, also the support of farmers and maintenance of arable land areas, corn can be seen as an energetic crop, too. Glucose was taken as feedstock on assumption glucose cultivation medium can be seen as a very simple model of lignocellulosic material hydrolyzate the use of which is supposed in future.

A comparison of butanol production using corn, sugar beet juice and glucose together with relevant strains is provided in Table 1 and sugar beet seems to be the preferable option according to the presented parameters. It is also noteworthy to look at fermentation courses in all compared cases. Fermentation of corn by C. acetobutylicum was running with textbook­like biphasic behaviour, when at first acids were formed and in the second solventogenic phase coupled with sporulation a reutilization of acids occurred. However, both fermentation of sugar beet juice by Cbeijerinckii and fermentation of glucose by

C. pasteurianum differed from this "typical" course by start of butanol formation during exponential growth phase (both cases) and almost no reutilization of acids (C. pasteurianum).

Overall balances of mentioned fermentation courses can be expressed in form of equations (1-3). Similar expression of products in numbers has already been published (see Equation 4) by Jones & Woods (1986) where this equation reflected average results achieved with C. acetobutylicum and Cbeijerinckii strains published in literature till 1986. In the equations (1­4), C12H22O11, C6H12O6, C4H10O, C3H6O, C2H6O, C2H4O2, C4H8O2 stand for saccharose, glucose, butanol, acetone, ethanol, butyric acid and acetic acid, respectively.

Butanol production from saccharose by Cbeijerinckii:

1.00C12H22O11 ^ 1.22 C4H10O + 0.60C3H6O + 0.04C2H6O + 0.25C2H4O2 ( )

+ 0.20C4H8O2 + 1.60CO2 + 0.80H2 ( )

Butanol production from corn (expressed as glucose) by C. acetobutylicum:

1.0 C6H12O6 ^ 0.42 C4H10O + 0.21 C3H6O + 0.04 C2H6O

+ 0.12C2H4O2 + 0.06C4H8O2 + 0.58CO2 + 0.36H2

Butanol production from glucose by C. pasteurianum:

1.0 C6H12O6 ^ 0.54 C4H10O + 0.40 C3H6O + 0.02 C2H6O + 0.19C2H4O2 + 0.06C4H8O2 + 6.77CO2 + 3.98 H2

Butanol production (Jones & Woods 1986):

1.0 C6H12O6 ^ 0.56 C4H10O + 0.22 C3H6O + 0.07 C2H6O + 0.14 C2H4O2 ( )

+ 0.04 C4H8O2 + 2.21 CO2 + 1.35 H2 ( )

Ratio of 1-butanol per unit of sugar (hexose) was the highest for saccharose (0.61) and the lowest for starch (0.42) but it can be stated the results were similar as presented by Jones and Woods (1986). The only exception was case of C. pasteurianum, in which remarkable amounts of carbon dioxide and hydrogen were produced not only in acidogenesis but throughout the whole fermentation period. Other experiences with the mentioned raw materials and also possible alternation of expensive but usual cultivation medium supplements, yeast extract or yeast autolysate, with cheap waste product of milk industry, whey protein concentrate, is
presented in Patakova et al., (2009). Detailed description of the use of sugar beet juice as fermentation substrate for biobutanol production has been published, recently (Patakova et al., 2011b).

All the bio-oils were produced either in batch or continuous microwave assisted pyrolysis (MAP) processes at the University of Minnesota (Figure 1). About 250 g samples were put in a 1000 mL quartz flask, which in turn was placed inside the microwave cavity (Panasonic NN-SD797S). The power level was set at 8 (the output power is about 1000 W). After the sample was microwaved for around 12 minutes, the volatile pyrolyzates were condensed with cool water at temperature of around 4-5 °C. The fraction collected from bottles connected to the bottom of the condensers was termed as the bio-oil. The condensates adhering to the interior wall of the tubes were then washed with ethanol and concentrated at 80°C using a vacuum rotovap (Buchi R-141, Flawil, Switzerland) to a near constant weight, and the concentrate was added to the bio-oil.

As mentioned earlier aspen, canola, and corn cob were the feedstocks selected for the bio-oil production. Aspen pellets were used for the production of bio-oil in a batch MAP process. Canola compost pellets were also used in a batch MAP process. All corn cobs were ground to less than 1 cm in size before MAP. Corn cob 1 and corn cob 2 bio-oils were produced using a continuous MAP, where heavy fractions of the bio-oil were not collected. Corn cob 3 bio-oil was produced using a batch MAP, where heavy fractions of the bio-oil were collected. Corn cob 4 was the bio-oil produced in a batch MAP of corn cob pretreated with 4% sulfuric acid; the bio-oil contained more water and furfural than other bio-oil samples. Fig. 2 shows bio-oils from different feedstocks produced through MAP. Heavy fractions of

the bio-oils were collected for all batch processes. The bio-oil separated into two phases: about top one-third of the bio-oil was in oily phase and the bottom two-thirds were in aqueous phase. The oily phase is a relatively stable, light emulsion containing water soluble chemicals and light oily components; whereas the aqueous phase is a large molecule oily mixture characterized by high viscosity and water insolubles (Yang et al., 2010). The aqueous phase yield varied between batch (aspen and canola >60%) and continuous (corn cobs 10-20%) production. The aqueous phase yield of corn cobs were in agreement with corn stover (Yang et al., 2010).

1.1.1 Batch studies

We have recently performed an in depth study in a batch set-up to determine the effects of process conditions on the catalytic hydrotreatment of fast pyrolysis oil using a Ru/ C catalyst 350 oC and 200 bar pressure (Wildschut et al., 2010a). The liquid product after reaction consisted of three different phases, a slightly yellow aqueous phase and two brown oil phases, one with a density higher than water and one with a density lower than water. Furthermore, substantial amounts of solids (coke/char, about 5 wt% on pyrolysis oil intake) and gas phase organics (CO, CO2, CH4) were formed as well. The oil yield and elemental compositions of the product phases were shown to be a strong function of the reaction time. Highest oil yields (65 %-wt.) were obtained after 4 h using a 5 %-wt. intake of catalyst on fast pyrolysis oil (Figure 3). Longer reaction times lead to a reduction of the oil yield due to the formation of gas phase components (methane, ethane, propane, CO/CO2). Hydrogen uptake after 4 h reaction time was about 400 Nm3/t of pyrolysis oil (dry basis).

A solvent-solvent extraction scheme based on the work of Oasmaa et al. (2003) was used to gain insight in the reactivity of various component classes (fractions) in the fast pyrolysis oil during the catalytic hydrotreatment process. The fractionation scheme (Figure 1) was applied to the original fast pyrolysis oil and product oils obtained at different reaction times (350 °C and 200 bar). The results are given in Figure 4.

Acids and esters Water

DCM (in)solubles Carbohydrates

Aldehydes, Ketones and lignin monomers Hydrocarbons

It shows the amounts of the various fractions (carbohydrates, aldehydes/ketones/lignin monomers, hydrocarbons, acids and esters) as a function of the reaction time. A fast decline in the carbohydrate fraction versus time is visible. Almost complete conversion to other components within 6 h reaction time is observed, an indication of the high reactivity of this fraction.

1.3 Compression mechanism

The compression characteristics of ground agricultural biomass vary under various applied pressures. It is important to understand the fundamental mechanism of the biomass compression process, which is required in the design of energy efficient compaction equipment to mitigate the cost of production and enhance the quality of the product (Mani et al., 2004). To a great extent, the strength of manufactured pellets depends on the physical forces that bond the particles together (Tabil and Sokhansanj, 1996). These physical forces come in three different forms during pelleting operations: a) thermal; b) mechanical; and c) atomic forces (Adapa et al., 2002).

Pellets are formed by subjecting the biomass grinds to high pressures, wherein the particles are forced to agglomerate. It is generally accepted that the compression process is categorized in several distinct stages and difficult to let one simple monovariate equation to cover the entire densification region (Sonnergaard, 2001). Compression of grinds is usually achieved in three stages (Holman, 1991). In the first stage, particles rearrange themselves under low pressure to form close packing. The particles retain most of their original properties, although energy is dissipated due to inter-particle and particle-to-wall friction. During the second stage, elastic and plastic deformation of particles occurs, allowing them to flow into smaller void spaces, thus increasing inter-particle surface contact area and as a result, bonding forces like van der Waal forces become effective (Rumpf, 1962; Sastry and Fuerstenau, 1973; Pietsch, 1997). Brittle particles may fracture under stress, leading to mechanical interlocking (Gray, 1968). Finally, under high pressure the second stage of compression continues until the particle density of grinds has been reached. During this

phase, the particles may reach their melting point and form very strong solid bridges upon cooling (Ghebre-Sellassie, 1989). Figure 2 shows the deformation mechanisms of ground particles under compression (Comoglu, 2007; Denny, 2002).

1.1 Materials preparation and experimental procedure

Cellulose in fibrous powder form and lignin in brown alkali powder form were purchased from Sigma Aldrich Sdn. Bhd., Malaysia. EFB and PS were collected from local palm oil industry in Perak, Malaysia. Biomass samples were dried at 105°C and the weighted was monitored at one hr interval, until the readings became constant. Samples were then grinded to particle size of 150-250pm. The method for drying, characterization and analysis were given in previous work (Abdullah et al., 2010). The biomass, pure cellulose and lignin properties are given in Tables 1 and 2.

The biomass decomposition experiments were carried out in EXSTAR TG/DTA 6300 (SII, Japan). N2 was used as inert gas with a constant flow rate of 100 ml/min for the entire range of experiments. The sample initial weight used in all experiments was within the range of 3­6 mg. TG experiments were performed at heating rate of 10, 30 and 50 °С/ min. All samples were first heated from 50 °C to 150 °C where it was kept constant for 10 min to remove moisture content, and then heated up to the final temperature of 800 °С. All experiments were carried twice for reproducibility. No significant variations were observed in the second experimental measurements.

1.2 Kinetic parameters determination

The biomass decomposition rate under non-isothermal condition is described (Cai & Bi, 2009).

A E

—-exp(—— ) f (a)

в RT
f (a) depends on the reaction mechanism as listed in Table 3 and a is the mass fraction reacted.

w — w a = —°

w0 — wf

Where, — and f shows initial and final sample weight

“ da AT E AE E

g(“) = f—— = — f exp(—- )dT = p(——- )

{ f (“) в { RT $R RT

p(E/RT) function has no exact analytical solution, and therefore different approximations are reported to evaluate the function (Budrugeac et al., 2000). The method developed by Flynn-Wall (Flynn & Wall, 1996), Ozawa (1965) using Doyle’s approximation (1961) is the most popular and commonly used by several researchers for biomass decomposition (Cai & Bi, 2009; Hu et al., 2007; Zhouling et al., 2009).

E

E -1.0516(- )

p(— ) = 0.0048e RT

RT

(3) is then rearranged for в

Іпв = ln( A“E“ ) — 5.331 -1.0516—E^ (5)

R g(“) RTV V ‘

Where; w = sample weight (mg); в = heating rate (K/ min); R = universal gas constant (8.314 x 10-3 kJ mol-1 K-1)

To determine the activation energy, lnei vs. 1/Ta, i is plotted for different a values and heating rates (i) to give a straight line and the slope of which gives the activation energy (Doyle, 1961; Ozawa, 1965; Zsako, & Zsako, 1980; Flynn & Wall, 1996).

a Kelly-Yong et al. (2007)

1.3 Model for kinetic parameter determination

The following assumptions are considered for the decomposition of EFB, PS, pure cellulose and lignin.

• Reaction is purely kinetic controlled.

• The decompositions follow single-step processes.

• First order reaction kinetics is considered for pure cellulose and lignin and PS and EFB kinetics are assumed to be nth order.

• No secondary reaction takes place among the gaseous products.

Following ISO 14041 guidelines, we define the system boundary in the biomass energy system.

The system boundary includes the entire life cycle of Bio-H2 fuel or electricity and thermal energy products, including the pre-processing process and the energy conversion process. (See Fig. 4). In the pre-processing process, there are sub-processes of chipping, transportation by trucks, and drying. In the energy conversion process, there are sub­processes of the gasification through the BT plant with a purification process or a CGS unit. Also, in our estimation, we focused on "well to tank (WtW)" analysis.

3.1 Functional unit

The target product is Bio-H2 and CGS products of electricity and/or heat energy. Thus, the functional unit is assumed to be the unit per a produced energy. The lower heating values of H2 and electricity are 10.8 MJ/Nm3 and 3.6 Mj/kWh, respectively.