Citation: Hai The Pham. Biosensors based on lithotrophic microbial fuel cells in relation to heterotrophic counterparts: research progress, challenges, and opportunities[J]. AIMS Microbiology, 2018, 4(3): 567-583. doi: 10.3934/microbiol.2018.3.567
[1] | Dheeraj Rathore, Anoop Singh, Divakar Dahiya, Poonam Singh Nigam . Sustainability of biohydrogen as fuel: Present scenario and future perspective. AIMS Energy, 2019, 7(1): 1-19. doi: 10.3934/energy.2019.1.1 |
[2] | Juan A. Conesa, A. Domene . Synthesis gas production from various biomass feedstocks. AIMS Energy, 2013, 1(1): 17-27. doi: 10.3934/energy.2013.1.17 |
[3] | Saad S. Alrwashdeh . Investigation of the effect of the injection pressure on the direct-ignition diesel engine performance. AIMS Energy, 2022, 10(2): 340-355. doi: 10.3934/energy.2022018 |
[4] | O. Corigliano, G. De Lorenzo, P. Fragiacomo . Techno-energy-economic sensitivity analysis of hybrid system Solid Oxide Fuel Cell/Gas Turbine. AIMS Energy, 2021, 9(5): 934-990. doi: 10.3934/energy.2021044 |
[5] | Angelo Minotti . A new NANOSATs propulsion system: swirling-combustion chamber and water electrolysis. AIMS Energy, 2018, 6(3): 402-413. doi: 10.3934/energy.2018.3.402 |
[6] | Gal Hochman, Shisi Wang, Qing Li, Paul D. Gottlieb, Fuqing Xu, Yebo Li . Cost of organic waste technologies: A case study for New Jersey. AIMS Energy, 2015, 3(3): 450-462. doi: 10.3934/energy.2015.3.450 |
[7] | Eric Danso-Boateng, Osei-Wusu Achaw . Bioenergy and biofuel production from biomass using thermochemical conversions technologies—a review. AIMS Energy, 2022, 10(4): 585-647. doi: 10.3934/energy.2022030 |
[8] | Simona Silvia Merola, Luca Marchitto, Cinzia Tornatore, Gerardo Valentino . Spray-combustion process characterization in a common rail diesel engine fuelled with butanol-diesel blends by conventional methods and optical diagnostics. AIMS Energy, 2014, 2(2): 116-132. doi: 10.3934/energy.2014.2.116 |
[9] | Quoc Dang Tran, Thanh Nhu Nguyen, Vinh Nguyen Duy . Effect of piston geometry design and spark plug position on the engine performance and emission characteristics. AIMS Energy, 2023, 11(1): 156-170. doi: 10.3934/energy.2023009 |
[10] | Mazhyn Skakov, Arman Miniyazov, Timur Tulenbergenov, Igor Sokolov, Gainiya Zhanbolatova, Assel Kaiyrbekova, Alina Agatanova . Hydrogen production by methane pyrolysis in the microwave discharge plasma. AIMS Energy, 2024, 12(3): 548-560. doi: 10.3934/energy.2024026 |
This manuscript is the progress of two previous works, carried out by the author [1,2], that come from the "EU-FP7-HRC-Power" project [3,4].
The goal of that European project is to design a novel energy device, able to overcome the high level of unused capacity and the high variability of the renewable sources over time (the intermittent nature leads to low capacity factors, low flexibility and high amortization costs).
To this end, a hybrid energy system, which adopts solar energy and/or chemical energy, has been defined; this kind of hybridization is able to provide reliable and continuous base-load power, as well as peak-load power.
Moreover, the project imposed the constraint of a miniaturized device, in order to enlarge its fields of application (i.e. smart buildings, mobiles, pc, satellites, space propulsion, etc.), and to allow different configurations (single and/or cluster operability).
The basic idea consists in integrating micro-swirling combustion chambers inside a parallelepiped brick, which is characterized by emitting surfaces that release heat power to be finally converted into electrical energy by a thermophotovoltaic cell (TPV).
Surfaces are heated up by the sun and/or by hot gases, produced during the combustion occurred in the micro-swirling chambers integrated inside the device.
The swirling chambers are adopted to permit efficient combustion in miniaturized devices (swirling motion increases the residence time), without the necessity of catalytic deposition on the internal walls (a procedure as expensive and difficult as the device is shrunk).
No works like this, apart from what it has been carried out by the author, are available; therefore, it is not possible to provide more comparative data than what it has already been done in [2], where a 500 W H2/Air device, under specific design constraints, is reported.
The relative reactive fluid dynamics investigations indicated that the hydrogen-air solution does not present significant drawbacks in terms of combustion stability and efficiency.
In addition, [2] reports a Fourier parametric analysis carried out to mimic the device's performance when works adopting only solar energy (mentioned as the "solar mode operation"), in which the sun has been simulated defining an external radiation source at a fixed temperature.
The "solar mode" investigation has been carried out to understand the effects of the dimensions of the holes (the combustion chambers) on the converter's thermal conductivity and, consequently, on the overall energy efficiency.
Results indicate that the converter thickness should not exceed 6 mm to obtain a thermal efficiency greater than 20% when in the "solar mode operation"; this has meant that combustion chambers must not exceed 3 mm of diameter (that is the holes must not be greater than 3 mm for an efficient energy conduction). Moreover, [2] reports that a five connected chambers configuration matches with the following additional design requirements: Tpeak emitting surface > 1000 K, ∆Temitting surface < 100 K and emitting surface of 30 × 30 mm.
The present manuscript investigates the same device, reported in [2], with the same design requirements but fed with methane.
It is important to understand the effectiveness of methane feeding because it is much easier, and safer, to be managed than hydrogen, it is a green propellant and, further, it is widely used, both for civil and space applications.
The current reactive numerical simulations adopt stoichiometric conditions, 500 W of injected chemical power, detailed chemistry, the k-eps turbulence approach and the eddy-dissipation concept to couple chemistry and turbulence.
In particular, the detailed hydrocarbon GRIMech mechanism [5], 32 species and 177 reactions, is adopted to reproduce the internal combustion.
Simulations show that, to fulfill with the design requirements, in terms of dimensions and efficiency, it is mandatory to add hydrogen, to the methane fuel injection, and to increase the operating pressure, up to 10 atm. This is due to the methane chemical structure, stiffer than hydrogen, which requires actions to increase the residence time and/or to accelerate the reaction.
The paper is structured as follows: section 2 describes the converter, the operating and boundary conditions, section 3 describes the numerical modeling, while sections 4–5 report, respectively, the results and the conclusions.
The parallelepiped brick has overall dimensions equal to 30 × 30 × 6 mm, with inside 5 connected swirling combustion chambers characterized by a diameter of 3 mm. The total volume available for combustion is about 1200 mm3 and the relative distance, between 2 consecutive chambers, is 3 mm. Figure 1 shows the hybrid converter with 5 connected chambers, two fuel-air entrances and only one outlet duct. This geometrical configuration permits to increase the residence time throughout the chambers. The internal chamber walls are coupled with the parallelepiped block, in order to permit the combustion products to heat up the emitting surfaces and then to deliver thermal power to the environment through convection and radiation; the emissivity values are reported in Figure 1.
The integration, between the swirling chambers and the emitting converter, is under a pending patent [6].
The external walls are characterized by a convective coefficient H = 12 W/(m2·K), calculated at standard and rest conditions.
Internal chamber walls are thermally conductive, while inlet and exhaust ducts walls are adiabatic (to mimic an eventual insulating material). The parallelepiped element is modeled adopting the following material properties:
Density, ρ = 3100 kg/m3;
Specific heat at constant pressure, Cp = 600 J/(kg·K)
Thermal conductivity, according to the polynomial reported in [7].
Table 1 reports the operating conditions of the 7 (seven) simulations.
H2 vol% | Pressure [atm] | Total injected chemical power (W) (CH4–H2/Air [kg]) |
Re (Fuel, Air) |
0 | 1 | 500 (1 × 10–5–0/1.716 × 10–4) | 430, 4415 |
20 | 1 | 500 (9.26 × 10–6–2.92 × 10–7/1.59 × 10–4) | 390, 4100 |
50 | 1 | 500 (7.86 × 10–6–8.93 × 10–7/1.65 × 10–4) | 365, 4350 |
20 | 5 | 500 (9.26 × 10–6–2.92 × 10–7/1.59 × 10–4) | 390, 4100 |
50 | 5 | 500 (7.86 × 10–6–8.93 × 10–7/1.65 × 10–4) | 365, 4350 |
20 | 10 | 500 (9.26 × 10–6–2.92 × 10–7/1.59 × 10–4) | 390, 4100 |
50 | 10 | 500 (7.86 × 10–6–8.93 × 10–7/1.65 × 10–4) | 365, 4350 |
Pure methane/air and hydrogen-methane/air blends, at different operating pressures, have been investigated. It is evident that laminar and moderately turbulent flow regimes are present, this is a typical feature of micro-meso/combustors [8,9]. Simulations were carried out assuming 500 W of injected power at stoichiometric conditions and adopting inlets temperature equal to 450 K, in order to mimic pre-heating at stationary conditions.
The domain has been reproduced by a mesh with a total number of cells greater than 1.4 M. The grid sensitivity analysis, reported in [1], indicated that a circumferential distance between gridpoints of 0.2 mm, on the chambers, and of 1 mm, on the walls of the brick, is the optimum. The grid analysis has been carried out at cold conditions because high temperature flows are characterized by smaller gradients (and then turbulence) than the ones at cold conditions with the same boundary conditions (Reynolds number decreases with the increase of the temperature).
The mesh has been improved by "reordering, smoothing, and swapping" techniques. In particular, reordering (the reverse Cuthill-Mckee method [10]) was adopted to reduce the bandwidth of the cell neighbour number, in order to speed up the calculations, while "smoothing and swapping" were used, respectively, to reposition nodes (by lowering the maximum skewness of the grid) and to modify the cell connectivity and the relative overall quality.
The first point near the wall is at y + < 3 and Δy + < 1 (only a few points, in the air inlet ducts where velocities are higher, are close to y + ~ 15). This means that the first point away from the wall inside the chamber is within the viscous sublayer.
As mentioned in [8,9], in micro-meso combustors, laminar zones may co-exist locally with turbulent zones, therefore the laminar vs. turbulent regime uncertainty poses the problem of the modelling approach. A pure laminar approach would be unable to predict turbulent field zones, of crucial importance when reactions are present, while turbulent models would over-predict transport wherever the actual regime was laminar.
In the light of the above, fluid dynamics has been solved adopting the RANS k-eps turbulence approach, with the enhanced wall treatment [11], able to reproduce accurate laminar dynamics [9].
The specific heat at constant pressure, Cpi, is fitted by polynomials of temperature from the GRIMech Thermo Data file [12], properly introduced in the CFD code, while viscosity and thermal conductivity, μ and k, are predicted by the gas kinetic theory [13]; mixtures are composition-dependent according to Wilke's formula [14].
The turbulence-combustion coupling is modelled adopting the eddy dissipation concept (EDC) [15,16], while the methane/air kinetics by means of the GRIMech mechanism [5], 32 species and 177 reactions.
The reactive Navier–Stokes equations were solved adopting a finite-volume solver (Ansys 14 CFD code). In particular, the pressure-based version, the PISO scheme [17,18] (for the pressure-velocity coupling) and the third-order MUSCL scheme [19] (for the spatial discretization of all the variables) have been implemented.
The computing resources are part of the CRESCO/ENEAGRID High Performance Computing infrastructure and its staff [20]. CRESCO/ENEAGRID High Performance Computing infrastructure is funded by ENEA, the Italian National Agency for New Technologies, Energy, and Sustainable Economic Development, and by Italian and European research programs [21].
The overall results are reported in the following Table 2.
H2 vol% | Pressure [atm] | Combustion efficiency | Average Temperature at the exhaust section [K] | Swirling Number (reacting conditions) |
0 | 1 | Burns out | - | - |
20 | 1 | Burns out | - | - |
50 | 1 | Burns out | - | - |
20 | 5 | Burns out | - | - |
50 | 5 | Burns out | - | - |
20 | 10 | 0.917 | 1433 | 1.615 |
50 | 10 | 0.982 | 1451 | 1.396 |
It reports the combustion efficiency [Equation (1)], the average temperature at the exhaust section and the swirling number at reacting conditions calculated at Z = 30 mm. It is evident that the pure-methane feeding (additional H2 equal to 0%) burns out. Therefore new strategies, to obtain stable combustion and efficient energy conversion, adopting hydrocarbon-air in such a small device, are mandatory. The chemical structure of the methane, sp3 ibridized [22], affects the chemistry performance, requiring higher activation energy and longer residence time.
To this end, hydrogen has been added to the methane injection and the operating pressure has been increased; in particular six additional simulations have been carried out adopting a blend of 20% and 50%, in volume of hydrogen, and imposing an operating pressure of 1, 5 and 10 atm, see Table 1.
Combustion efficiency is defined as follow:
$ {\eta _{{\rm{combustion}}}} = {\left. {\frac{{{\chi _{CO2}}}}{{{\chi _{CO2}} + {\chi _{CO}} + {\chi _{UHC}}}}} \right|_{outlet}} $ | (1) |
Where ${\chi _i} = \frac{{{n_i}}}{{{n_{tot}}-{n_{H2O}}}}$; and ni is the molar fraction of species "i" at the exhaust section.
Table 2 indicates that, among all the simulations, only the ones with an operating pressure of 10 atm provide stable combustion, both with 20% and 50% in volume of additional hydrogen. The other configurations burn out.
The figure 2 reports, as an example, the temperatures map on the xz plane, from which the extinction zones inside the two lateral chambers may be easily distinguished.
Table 3 reports the maximum temperature, the minimum temperature, the average temperature, the standard deviation and, finally, the external heat transfer, respectively for "wall 1" and "wall 3" of the two configurations at 10 atm of operating pressure (respectively with H2 = 20%–50% in volume of additional hydrogen).
H2 % vol | External Heat Transfer Wall1–Wall3 [W] | Wall 1 Tmax–Tmin [K] | Wall 1 Taverage–σT [K] | Wall 3 Tmax–Tmin [K] | Wall 3 Taverage–σT [K] |
20 | 70–51 | 1445–1304 | 1395–28 | 1446–1315 | 1397–28 |
50 | 73–53 | 1463–1334 | 1414–25 | 1462–1342 | 1416–25 |
The iterative solution was assumed converged when the difference between the inlet and outlet mass flow rates, Δm/Δt, was at least two orders of magnitude smaller than the smallest flow rate at the inlet section (that is, the hydrogen injection).
The added hydrogen, being characterized by higher latent heat value and faster chemistry, than the methane, speeds up the overall reaction mechanism, while the increased pressure reduces the inlet velocities and increases the overall reaction rates.
These two strategies contribute, simultaneously, to increase the Damkohler number [23], defined as:
$ Da = \frac{{flow\;time\;scale}}{{chemical\;time\;scale}} $ | (2) |
As expected, the configuration with H2 = 50% in volume provides better performance in terms of combustion efficiency, maximum temperature and ∆T, on the emitting surfaces, than the one with additional H2 = 20% in volume.
Notwithstanding, the overall outcomes are only slightly different, as the following discussion demonstrates.
Table 3 reports that the maximum temperatures, on both the emitting walls, are significantly greater than the design requirement (T > 1450 K vs. T > 1000 K). The total delivered power to the ambient is about 70 W–73 W, from "wall 1", and 51 W–53 W, from "wall 3".
Significant is the difference in combustion efficiency, ${\eta _{{H_2} = 50\% }} > 0.98$ while ${\eta _{{H_2} = 20\% }} > 0.91$, demonstrating how the faster hydrogen chemistry affects the final performance.
On the other hand the ∆T < 100 K requirement is not fulfilled neither in the H2 = 20% not in the H2 = 50% configurations; in fact, the best result is ∆T ≈ 120 K, 20 K higher than the design requirement for the H2 = 50% configuration. This value is confirmed also by the standard deviation value that is about 25 K versus 28 K in the H2 = 20% configuration. This result would affect the overall performance in terms of compatibility with a thermo-photovoltaic cell, but only an experimental test would provide the concrete effects of such a ∆T.
The converter thermal behavior is shown in Figures 3–5, which present, respectively, the temperature maps of the combustion chambers walls, of the xz-plane and of the external walls.
In particular, Figure 4 shows that the maximum temperature, in the central core of the chambers, is around 2400 K for both the configurations.
Figure 5 reports the temperature maps of the emitting surfaces. It is evident that the low temperature zones, close to the inlet part of the converter, affect the overall performance, increasing the delta temperature, the standard deviation, and then lowering the eventual TPV energy conversion.
Finally, it is important to highlight the result regarding the average temperatures at the exhaust sections. The numerical investigations figure out 1433 K and 1451 K of exhaust temperature; this indicates that there is a lot of energy that might be still used, in both the configurations, to further increase the overall energy efficiency. To this end, the feasibility of connecting micro-turbine or micro-nozzle, for additional energy production or for space micro-propulsion, is under investigation.
Figure 6 reports, instead, the pressure maps inside the chambers; an overpressure of about 0.4–0.5 atm is present between the inlet and the outlet sections.
This work is the last development of a series of works, coming from an EU-FP7 project, that investigate the potentialities of an emitting parallelepiped block, with inside swirling chambers, as a hybrid energy converter connected to a TPV (hybridization considers to adopt solar energy and/or chemical energy).
The works in [1,2] investigated different configurations of a hydrogen-fed hybrid-converter, and in particular their effectiveness when compared to specific project's requirements.
The "solar mode investigations" imposed swirling combustion chambers of maximum 3 mm of diameter, while the combustion simulations showed no particular drawbacks or limitations when fed with hydrogen.
The present manuscript translated the previous outcomes to a hybrid-converter fed with hydrocarbons and the first result is the fact that methane is too stiff to maintain stable combustion inside the 3 mm-diameter connected swirling chambers; therefore, hydrogen has been added to the methane injection and the operating pressure has been increased up to 10 atm.
In particular, six simulations are carried out, adopting several hydrogen-methane blends (H2 = 20% and H2 = 50% in volume) and several operating pressure (1, 5 and 10 atm).
Among all the simulations, only the ones with 10 atm of operating pressure obtained successful results; all the other ones burn out.
The configuration with additional H2 = 50% in volume performs, as expected, better in terms of combustion efficiency, maximum temperature and ∆T, than the one with H2 = 20% in volume.
Both the configurations match with all the design requirements but miss the ∆T < 100 K requirement. The best result is ∆T = 120 K and it has been obtained adding H2 = 50% in volume.
In the light of the above, only an experimental test could quantify whether, or not, this affects the TPV energy conversion performance.
The hydrogen addition and the pressure increase permit to reach high value of combustion efficiency (${\eta _{{H_2} = 50\% }} > 0.98$).
Moreover, a lot of energy is still available at the exhaust section of the converter.
This indicates that it is possible to increase the overall energy efficiency, for instance connecting the exhaust section with a microturbine or micronozzle in order to produce additional electrical energy or even thrust for microsatellite applications.
EU-FP7 ENERGY.2012.10.2.1: Future Emerging Technologies Grant, HRC Power Project.
The author declares no conflict of interest in this paper.
[1] |
Lei Y, Chen W, Mulchandani A (2006) Microbial biosensors. Anal Chim Acta 568: 200–210. doi: 10.1016/j.aca.2005.11.065
![]() |
[2] |
D'Souza SF (2001) Microbial biosensors. Biosens Bioelectron 16: 337–353. doi: 10.1016/S0956-5663(01)00125-7
![]() |
[3] |
Chang IS, Jang JK, Gil GC, et al. (2004) Continuous determination of biochemical oxygen demand using microbial fuel cell type biosensor. Biosens Bioelectron 19: 607–613. doi: 10.1016/S0956-5663(03)00272-0
![]() |
[4] |
Di Lorenzo M, Curtis TP, Head IM, et al. (2009) A single-chamber microbial fuel cell as a biosensor for wastewaters. Water Res 43: 3145–3154. doi: 10.1016/j.watres.2009.01.005
![]() |
[5] |
Stein NE, Hamelers HMV, van Straten G, et al. (2012) On-line detection of toxic components using a microbial fuel cell-based biosensor. J Process Contr 22: 1755–1761. doi: 10.1016/j.jprocont.2012.07.009
![]() |
[6] | Lee H, Yang W, Wei X, et al. (2015) A microsized microbial fuel cell based biosensor for fast and sensitive detection of toxic substances in water. IEEE 2015: 573–576. |
[7] |
Webster DP, TerAvest MA, Doud DFR, et al. (2014) An arsenic-specific biosensor with genetically engineered Shewanella oneidensis in a bioelectrochemical system. Biosens Bioelectron 62: 320–324. doi: 10.1016/j.bios.2014.07.003
![]() |
[8] |
Liu Z, Liu J, Zhang S, et al. (2011) Microbial fuel cell based biosensor for in situ monitoring of anaerobic digestion process. Bioresource Technol 102: 10221–10229. doi: 10.1016/j.biortech.2011.08.053
![]() |
[9] |
Rabaey K, Rodriguez J, Blackall LL, et al. (2007) Microbial ecology meets electrochemistry: electricity-driven and driving communities. ISME J 1: 9–18. doi: 10.1038/ismej.2007.4
![]() |
[10] |
Pham TH, Aelterman P, Verstraete W (2009) Bioanode performance in bioelectrochemical systems: recent improvements and prospects. Trends Biotechnol 27: 168–178. doi: 10.1016/j.tibtech.2008.11.005
![]() |
[11] |
Mohan SV, Velvizhi G, Modestra JA, et al. (2014) Microbial fuel cell: Critical factors regulating bio-catalyzed electrochemical process and recent advancements. Renew Sust Energ Rev 40: 779–797. doi: 10.1016/j.rser.2014.07.109
![]() |
[12] |
Dávila D, Esquivel JP, Sabaté N, et al. (2011) Silicon-based microfabricated microbial fuel cell toxicity sensor. Biosens Bioelectron 26: 2426–2430. doi: 10.1016/j.bios.2010.10.025
![]() |
[13] |
Lovley DR, Nevin KP (2011) A shift in the current: New applications and concepts for microbe-electrode electron exchange. Curr Opin Biotech 22: 441–448. doi: 10.1016/j.copbio.2011.01.009
![]() |
[14] |
Kim BH, Chang IS, Gadd GM (2007) Challenges in microbial fuel cell development and operation. Appl Microbiol Biot 76: 485–494. doi: 10.1007/s00253-007-1027-4
![]() |
[15] |
Rabaey K, Rozendal RA (2010) Microbial electrosynthesis-revisiting the electrical route for microbial production. Nat Rev Microbiol 8: 706–716. doi: 10.1038/nrmicro2422
![]() |
[16] |
Arends JB, Verstraete W (2012) 100 years of microbial electricity production: three concepts for the future. Microb Biotechnol 5: 333–346. doi: 10.1111/j.1751-7915.2011.00302.x
![]() |
[17] |
Tran PHN, Luong TTT, Nguyen TTT, et al. (2015) Possibility of using a lithotrophic iron-oxidizing microbial fuel cell as a biosensor for detecting iron and manganese in water samples. Environ Sci Proc Impacts 17: 1806–1815. doi: 10.1039/C5EM00099H
![]() |
[18] |
Pant D, Van Bogaert G, Diels L, et al. (2010) A review of the substrates used in microbial fuel cells (MFCs) for sustainable energy production. Bioresource Technol 101: 1533–1543. doi: 10.1016/j.biortech.2009.10.017
![]() |
[19] |
Yang H, Zhou M, Liu M, et al. (2015) Microbial fuel cells for biosensor applications. Biotechnol Lett 37: 2357–2364. doi: 10.1007/s10529-015-1929-7
![]() |
[20] |
Sulonen MLK, Lakaniemi AM, Kokko ME, et al. (2016) Long-term stability of bioelectricity generation coupled with tetrathionate disproportionation. Bioresource Technol 216: 876–882. doi: 10.1016/j.biortech.2016.06.024
![]() |
[21] |
Zhong L, Zhang S, Wei Y, et al. (2017) Power recovery coupled with sulfide and nitrate removal in separate chambers using a microbial fuel cell. Biochem Eng J 124: 6–12. doi: 10.1016/j.bej.2017.04.005
![]() |
[22] |
He Z, Kan J, Wang Y, et al. (2009) Electricity production coupled to ammonium in a microbial fuel cell. Environ Sci Technol 43: 3391–3397. doi: 10.1021/es803492c
![]() |
[23] |
Nguyen TT, Luong TTT, Tran PHN, et al. (2015) A lithotrophic microbial fuel cell operated with pseudomonads-dominated iron-oxidizing bacteria enriched at the anode. Microb Biotechnol 8: 579–589. doi: 10.1111/1751-7915.12267
![]() |
[24] |
Rabaey K, Van de Sompel K, Maignien L, et al. (2006) Microbial fuel cells for sulfide removal. Environ Sci Technol 40: 5218–5224. doi: 10.1021/es060382u
![]() |
[25] |
Logan BE, Hamelers B, Rozendal R, et al. (2006) Microbial fuel cells: Methodology and technology. Environ Sci Technol 40: 5181–5192. doi: 10.1021/es0605016
![]() |
[26] |
Kim M, Youn SM, Shin SH, et al. (2003) Practical field application of a novel BOD monitoring system. J Environ Monitor 5: 640–643. doi: 10.1039/b304583h
![]() |
[27] |
Kim BH, Chang IS, Gil GC, et al. (2003) Novel BOD (biological oxygen demand) sensor using mediator-less microbial fuel cell. Biotechnol Lett 25: 541–545. doi: 10.1023/A:1022891231369
![]() |
[28] |
Kang KH, Jang JK, Pham TH, et al. (2003) A microbial fuel cell with improved cathode reaction as a low biochemical oxygen demand sensor. Biotechnol Lett 25: 1357–1361. doi: 10.1023/A:1024984521699
![]() |
[29] |
Liu B, Lei Y, Li B (2014) A batch-mode cube microbial fuel cell based "shock" biosensor for wastewater quality monitoring. Biosens Bioelectron 62: 308–314. doi: 10.1016/j.bios.2014.06.051
![]() |
[30] |
Di Lorenzo M, Thomson AR, Schneider K, et al. (2014) A small-scale air-cathode microbial fuel cell for on-line monitoring of water quality. Biosens Bioelectron 62: 182–188. doi: 10.1016/j.bios.2014.06.050
![]() |
[31] |
Ringeisen BR, Henderson E, Wu PK, et al. (2006) High power density from a miniature microbial fuel cell using Shewanella oneidensis DSP10. Environ Sci Technol 40: 2629–2634. doi: 10.1021/es052254w
![]() |
[32] |
Kim M, Hyun MS, Gadd GM, et al. (2007) A novel biomonitoring system using microbial fuel cells. J Environ Monitor 9: 1323–1328. doi: 10.1039/b713114c
![]() |
[33] |
Quek SB, Cheng L, Cord-Ruwisch R (2015) Microbial fuel cell biosensor for rapid assessment of assimilable organic carbon under marine conditions. Water Res 77: 64–71. doi: 10.1016/j.watres.2015.03.012
![]() |
[34] |
Kaur A, Kim JR, Michie I, et al. (2013) Microbial fuel cell type biosensor for specific volatile fatty acids using acclimated bacterial communities. Biosens Bioelectron 47: 50–55. doi: 10.1016/j.bios.2013.02.033
![]() |
[35] |
Ni G, Christel S, Roman P, et al. (2016) Electricity generation from an inorganic sulfur compound containing mining wastewater by acidophilic microorganisms. Res Microbiol 167: 568–575. doi: 10.1016/j.resmic.2016.04.010
![]() |
[36] |
Stein NE, Hamelers HVM, Buisman CNJ (2010) Stabilizing the baseline current of a microbial fuel cell-based biosensor through overpotential control under non-toxic conditions. Bioelectrochemistry 78: 87–91. doi: 10.1016/j.bioelechem.2009.09.009
![]() |
[37] |
Kim BH, Park HS, Kim HJ, et al. (2004) Enrichment of microbial community generating electricity using a fuel-cell-type electrochemical cell. Appl Microbiol Biot 63: 672–681. doi: 10.1007/s00253-003-1412-6
![]() |
[38] |
Logan BE, Regan JM (2006) Electricity-producing bacterial communities in microbial fuel cells. Trends Microbiol 14: 512–518. doi: 10.1016/j.tim.2006.10.003
![]() |
[39] |
Liu Z, Li H, Liu J, et al. (2008) Effects of inoculation strategy and cultivation approach on the performance of microbial fuel cell using marine sediment as bio-matrix. J Appl Microbiol 104: 1163–1170. doi: 10.1111/j.1365-2672.2007.03643.x
![]() |
[40] |
Tran P, Nguyen L, Nguyen H, et al. (2016) Effects of inoculation sources on the enrichment and performance of anode bacterial consortia in sensor typed microbial fuel cells. AIMS Bioeng 3: 60–74. doi: 10.3934/bioeng.2016.1.60
![]() |
[41] |
Mathuriya AS (2013) Inoculum selection to enhance performance of a microbial fuel cell for electricity generation during wastewater treatment. Environ Technol 34: 1957–1964. doi: 10.1080/09593330.2013.808674
![]() |
[42] | Vázquez-Larios AL, Poggi-Varaldo HM, Solorza-Feria O, et al. Effect of type of inoculum on microbial fuel cell performance that used RuxMoySez as cathodic catalyst. Int J Hydrogen Energ 40: 17402–17412. |
[43] |
Hsieh MC, Chung YC (2014) Measurement of biochemical oxygen demand from different wastewater samples using a mediator-less microbial fuel cell biosensor. Environ Technol 35: 2204–2211. doi: 10.1080/09593330.2014.898700
![]() |
[44] |
Logan BE, Regan JM (2006) Microbial challenges and applications. Environ Sci Technol 40: 5172–5180. doi: 10.1021/es0627592
![]() |
[45] |
Rabaey K, Boon N, Siciliano SD, et al. (2004) Biofuel cells select for microbial consortia that self-mediate electron transfer. Appl Environ Microb 70: 5373–5382. doi: 10.1128/AEM.70.9.5373-5382.2004
![]() |
[46] |
Rabaey K, Boon N, Hofte M, et al. (2005) Microbial phenazine production enhances electron transfer in biofuel cells. Environ Sci Technol 39: 3401–3408. doi: 10.1021/es048563o
![]() |
[47] |
Sudek LA, Templeton AS, Tebo BM, et al. (2009) Microbial Ecology of Fe (hydr)oxide Mats and Basaltic Rock from Vailulu'u Seamount, American Samoa. Geomicrobiol J 26: 581–596. doi: 10.1080/01490450903263400
![]() |
[48] | Straub KL, Benz M, Schink B, et al. (1996) Anaerobic, nitrate-dependent microbial oxidation of ferrous iron. Appl Environ Microbiol 62: 1458–1460. |
[49] |
Gil GC, Chang IS, Kim BH, et al. (2003) Operational parameters affecting the performance of a mediator-less microbial fuel cell. Biosens Bioelectron 18: 327–334. doi: 10.1016/S0956-5663(02)00110-0
![]() |
[50] | Kim BH, Chang IS, Moon H (2006) Microbial fuel cell-type biochemical oxygen demand sensor. Studies 3. |
[51] |
Liu H, Cheng SA, Logan BE (2005) Power generation in fed-batch microbial fuel cells as a function of ionic strength, temperature, and reactor configuration. Environ Sci Technol 39: 5488–5493. doi: 10.1021/es050316c
![]() |
[52] | Stein NE, Hamelers HVM, Buisman CNJ (2012) The effect of different control mechanisms on the sensitivity and recovery time of a microbial fuel cell based biosensor. Sensor Actuat B-Chem 171: 816–821. |
[53] |
Pham TH, Rabaey K, Aelterman P, et al. (2006) Microbial fuel cells in relation to conventional anaerobic digestion technology. Eng Life Sci 6: 285–292. doi: 10.1002/elsc.200620121
![]() |
[54] |
Logan B, Cheng S, Watson V, et al. (2007) Graphite fiber brush anodes for increased power production in air-cathode microbial fuel cells. Environ Sci Technol 41: 3341–3346. doi: 10.1021/es062644y
![]() |
[55] |
Rabaey K, Clauwaert P, Aelterman P, et al. (2005) Tubular microbial fuel cells for efficient electricity generation. Environ Sci Technol 39: 8077–8082. doi: 10.1021/es050986i
![]() |
[56] |
Bond DR, Lovley DR (2003) Electricity production by Geobacter sulfurreducens attached to electrodes. Appl Environ Microb 69: 1548–1555. doi: 10.1128/AEM.69.3.1548-1555.2003
![]() |
[57] |
Liu H, Ramnarayanan R, Logan BE (2004) Production of electricity during wastewater treatment using a single chamber microbial fuel cell. Environ Sci Technol 38: 2281–2285. doi: 10.1021/es034923g
![]() |
[58] |
Winkel LHE, Trang PTK, Lan VM, et al. (2011) Arsenic pollution of groundwater in Vietnam exacerbated by deep aquifer exploitation for more than a century. P Natl Acad Sci USA 108: 1246–1251. doi: 10.1073/pnas.1011915108
![]() |
[59] | Wasserman GA, Liu X, Parvez F, et al. (2006) Water manganese exposure and children's intellectual function in Araihazar, Bangladesh. Environ Health Persp 114: 124–129. |
[60] |
Habibul N, Hu Y, Sheng GP (2016) Microbial fuel cell driving electrokinetic remediation of toxic metal contaminated soils. J Hazard Mater 318: 9–14. doi: 10.1016/j.jhazmat.2016.06.041
![]() |
[61] |
Li Y, Wu Y, Liu B, et al. (2015) Self-sustained reduction of multiple metals in a microbial fuel cell-microbial electrolysis cell hybrid system. Bioresource Technol 192: 238–246. doi: 10.1016/j.biortech.2015.05.030
![]() |
[62] |
Shen J, Huang L, Zhou P, et al. (2017) Correlation between circuital current, Cu(II) reduction and cellular electron transfer in EAB isolated from Cu(II)-reduced biocathodes of microbial fuel cells. Bioelectrochemistry 114: 1–7. doi: 10.1016/j.bioelechem.2016.11.002
![]() |
[63] |
Sophia AC, Saikant S (2016) Reduction of chromium(VI) with energy recovery using microbial fuel cell technology. J Water Process Eng 11: 39–45. doi: 10.1016/j.jwpe.2016.03.006
![]() |
1. | Angelo Minotti, A new NANOSATs propulsion system: swirling-combustion chamber and water electrolysis, 2018, 6, 2333-8334, 402, 10.3934/energy.2018.3.402 | |
2. | Angelo Minotti, 2018, Chapter 15, 978-3-319-91790-0, 119, 10.1007/978-3-319-91791-7_15 |
H2 vol% | Pressure [atm] | Total injected chemical power (W) (CH4–H2/Air [kg]) |
Re (Fuel, Air) |
0 | 1 | 500 (1 × 10–5–0/1.716 × 10–4) | 430, 4415 |
20 | 1 | 500 (9.26 × 10–6–2.92 × 10–7/1.59 × 10–4) | 390, 4100 |
50 | 1 | 500 (7.86 × 10–6–8.93 × 10–7/1.65 × 10–4) | 365, 4350 |
20 | 5 | 500 (9.26 × 10–6–2.92 × 10–7/1.59 × 10–4) | 390, 4100 |
50 | 5 | 500 (7.86 × 10–6–8.93 × 10–7/1.65 × 10–4) | 365, 4350 |
20 | 10 | 500 (9.26 × 10–6–2.92 × 10–7/1.59 × 10–4) | 390, 4100 |
50 | 10 | 500 (7.86 × 10–6–8.93 × 10–7/1.65 × 10–4) | 365, 4350 |
H2 vol% | Pressure [atm] | Combustion efficiency | Average Temperature at the exhaust section [K] | Swirling Number (reacting conditions) |
0 | 1 | Burns out | - | - |
20 | 1 | Burns out | - | - |
50 | 1 | Burns out | - | - |
20 | 5 | Burns out | - | - |
50 | 5 | Burns out | - | - |
20 | 10 | 0.917 | 1433 | 1.615 |
50 | 10 | 0.982 | 1451 | 1.396 |
H2 % vol | External Heat Transfer Wall1–Wall3 [W] | Wall 1 Tmax–Tmin [K] | Wall 1 Taverage–σT [K] | Wall 3 Tmax–Tmin [K] | Wall 3 Taverage–σT [K] |
20 | 70–51 | 1445–1304 | 1395–28 | 1446–1315 | 1397–28 |
50 | 73–53 | 1463–1334 | 1414–25 | 1462–1342 | 1416–25 |
H2 vol% | Pressure [atm] | Total injected chemical power (W) (CH4–H2/Air [kg]) |
Re (Fuel, Air) |
0 | 1 | 500 (1 × 10–5–0/1.716 × 10–4) | 430, 4415 |
20 | 1 | 500 (9.26 × 10–6–2.92 × 10–7/1.59 × 10–4) | 390, 4100 |
50 | 1 | 500 (7.86 × 10–6–8.93 × 10–7/1.65 × 10–4) | 365, 4350 |
20 | 5 | 500 (9.26 × 10–6–2.92 × 10–7/1.59 × 10–4) | 390, 4100 |
50 | 5 | 500 (7.86 × 10–6–8.93 × 10–7/1.65 × 10–4) | 365, 4350 |
20 | 10 | 500 (9.26 × 10–6–2.92 × 10–7/1.59 × 10–4) | 390, 4100 |
50 | 10 | 500 (7.86 × 10–6–8.93 × 10–7/1.65 × 10–4) | 365, 4350 |
H2 vol% | Pressure [atm] | Combustion efficiency | Average Temperature at the exhaust section [K] | Swirling Number (reacting conditions) |
0 | 1 | Burns out | - | - |
20 | 1 | Burns out | - | - |
50 | 1 | Burns out | - | - |
20 | 5 | Burns out | - | - |
50 | 5 | Burns out | - | - |
20 | 10 | 0.917 | 1433 | 1.615 |
50 | 10 | 0.982 | 1451 | 1.396 |
H2 % vol | External Heat Transfer Wall1–Wall3 [W] | Wall 1 Tmax–Tmin [K] | Wall 1 Taverage–σT [K] | Wall 3 Tmax–Tmin [K] | Wall 3 Taverage–σT [K] |
20 | 70–51 | 1445–1304 | 1395–28 | 1446–1315 | 1397–28 |
50 | 73–53 | 1463–1334 | 1414–25 | 1462–1342 | 1416–25 |