REVERSE ELECTRODIALYSIS’’’’’’’’’’’’’’’ PROJECT’REPORT · determine! the! feasibility of! using reverse ]electrodialysis to! supplement! a! small! portion!

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REVERSE ELECTRODIALYSIS PROJECT REPORT

ALEXANDRA EASTES BME/EE MINOR [email protected]

DYLAN HINGEY CMPE/ISM [email protected]

CHIRAG SHARMA BME [email protected]

DANNY TATE BME [email protected]

ULYSSES MORALES CMPE [email protected]

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TABLE OF CONTENTS Motivation for Researching Reverse Electrodialysis ...................................................................... 4

Background: How Does a Concentration Cell Work [10, 12] .......................................................... 9

Specific Aims ................................................................................................................................. 12

Approach ....................................................................................................................................... 13

Cell construction........................................................................................................................ 13

Experimentation ........................................................................................................................ 15

Developing a storage component for the cell ........................................................................... 21

Battery options/charging methods: ...................................................................................... 21

Circuit Design: ........................................................................................................................ 21

Results: .................................................................................................................................. 23

Transfer sensor readings from client to server ......................................................................... 24

Defining the Problem of Data Transfer ................................................................................. 24

Initial Planning and Considerations ....................................................................................... 25

Intermediate and Final Solutions .......................................................................................... 26

Displaying real-‐time voltage and current readings on a website ............................................. 29

Overview: ............................................................................................................................... 29

Server Setup: ......................................................................................................................... 29

Web Design: ........................................................................................................................... 29

Website Graphs and Table Output: ....................................................................................... 30

Remote Camera monitoring System: .................................................................................... 35

Closure: .................................................................................................................................. 36

Feasibility Conclusion of Reverse Electrodialysis .......................................................................... 37

System block diagram ................................................................................................................... 38

Budget ........................................................................................................................................... 39

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Personnel ...................................................................................................................................... 41

Alexandra Eastes ....................................................................................................................... 41

Dylan Hingey.............................................................................................................................. 42

Ulysses Morales ......................................................................................................................... 43

Chirag Sharma ........................................................................................................................... 44

Danny Tate ................................................................................................................................ 45

References .................................................................................................................................... 46

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MOTIVATION FOR RESEARCHING REVERSE ELECTRODIALYSIS

In the United States, 83% of energy is supplied by petroleum, natural gas and coal, and while there is controversy regarding the depletion timeline of these major sources of energy, it is indisputable that additional sources of energy are needed to meet the increasing global energy demands[1,2]. No single alternative source of energy has proven capable of supplying sufficient amounts of energy to replace oil, yet technological advancements combined with continued exploration in the field of renewable energy provide possibilities for the future [9]. In response to the need to explore additional sources of energy, this project focuses on designing a concentration cell capable of producing energy from a naturally occurring salinity gradient in Santa Cruz, CA and determining the feasibility of implementing a full scale power plant using the aforementioned concentration cell, which generates energy by means of reverse electrodialysis.

Figure 1 [1]: (Taken from Lawrence Livermore National Lab) Estimated U.S. Energy Use in 2009. The U.S. relies heavily on non-‐renewable sources of energy, which are being depleted because of population growth, price of oil and coal compared to renewable energies and the convenience of infrastructure. Alternative sources of energy must be explored to provide energy to the United States in the future.

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The process of reverse electrodialysis generates a voltage from an ionic gradient separated by a semi-‐permeable membrane, forming a concentration cell [3]. Examples of ionic gradients are found in human cells [K+ channels] [4], electric eels [electrocytes] [5], and estuaries [river:ocean]. In the latter example, fresh water mixes with ocean water naturally and becomes brackish water, but this unobstructed diffusion can be harnessed into energy using reverse electrodialysis. The difference in salinity between river water (low concentration of salt) and ocean water (high concentration of salt) at an estuary can be separated with a semi-‐permeable membrane, resulting in a voltage defined by the difference in saline concentrations. The San Lorenzo River in Santa Cruz, CA, which flows into the Monterey Bay forming an estuary next to the Santa Cruz Beach Boardwalk, is the location of interest for this project (Fig. 2).

Figure 2: (Taken from Google Maps) Google Maps Screen Shot of the San Lorenzo River. Part A is the estuary where the San Lorenzo River flows into the Monterey Bay. The salinity at this location is 0.593mol/L 8. Part B was an initial area of interest, but the lack of salinity gradient resulted in low voltage. Part C is the revised fresh water resource and is located under the Water Street Bridge. The salinity at this location is 0.0033mol/L 8. The salinity ratio between these two locations is 1:182, which would provide 127mV for each concentration cell according to the Nernst Equation.

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To determine if the San Lorenzo River and Monterey Bay make a suitable location for a reverse-‐electrodialysis power plant, a ten-‐cell stack of concentration cells will be created and tested for maximum power output with minimal costs. Voltage sensors (Gamry Ref 600) will track real-‐time readings from the ten-‐cell stack and print the results to a website for off-‐site monitoring. The power generated from the ten-‐cell stack prototype will charge a small battery to

Preliminary theoretical research from a 2009 thesis paper from the Netherlandsn Post states that

1m3 of salt water mixing with 1m3 of fresh water, assuming a salinity gradient of 1:50, generates 1.4MJ (Equation 1) [6].

(1)

Ci,x = NaCl concentration of water (subscript c-‐ concentrated, d-‐ dilute, b-‐brackish)

[mol/liter]

V = volume of water [liters]

R = universal gas constant [joule/mol K]

T = absolute temperature [K]

(2)

Gx = the free energy from each individual component of the cell

Using data from the United States Geological Survey (USGS), which measured the San Lorenzo River average annual discharge (flow) between 205-‐755 m3/sec, and assuming an ideal situation (1:50 salinity gradient and 100% efficiency), equation 1 can be applied to the San Lorenzo River resulting in a theoretical power output between 0.289GW-‐1.057GW [7]. Even with 1% efficiency, given these theoretical assumptions, there is a 2.5MW potential from the San Lorenzo River between Branciforte, Santa Cruz and the mouth of the river.

However, Post appears to have miscalculated the energy potential from mixing 1m3 of river water with 1m3 of ocean water. His calculation used the following parameters in his paper on page 43: 0.5mol/L (sea water), 0.01mol/L (river water), absolute temperature T=293K, universal

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gas constant R = 8.314J/molK and a volume of 1m3 = 1000 liters for each solution. Breaking equation 1 into three parts, the free energy of each component can be added together where ci is the concentration or molarity, V is the volume, and xi is the molarity of the solution (Note: ci and xi are the same variable, but Post separates them into two difference variables representing the same value. We respectfully retained the equation exactly as reported in

even though it is misleading.)

(3)

=-‐844,253J

(4)

=-‐112,182J

(5)

= -‐1,697,676

= 741,241J +0.74MJ

The corrected value (+0.74MJ) using the same variables as Post is half of his reported calculation and has a sign reversal. The positive sign that results from a recalculation using

system for the reaction to occur, which is inaccurate because a high concentration will spontaneously diffuse into a lower concentration to achieve equilibrium without adding energy. The sign change error appears to be a simple mix-‐up between products and reactants. The standard free energy of formation can be calculated as follows:

[10] (6)

Following equation 6, the high and low initial concentrations are subtracted from the final mixed concentration, resulting in a negative free energy and defining the reaction as spontaneous. Post subtracted the product (mixed solution) from the reactants (unmixed high and low concentrations). Note that the negative/positive sign in front of the energy (Joules) refers to how much energy must be inputted into the system for the reaction to occur. A negative sign means energy can be extracted from a reaction. Calculating the free energy using:

[11] (7)

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= -‐741,241J -‐0.74MJ

Changing the energy potential of 1m3 of river water mixing with 1m3 of sea water to the recalculated 0.74MJ, the maximum theoretical energy from the San Lorenzo River (retaining the 1:50 gradient and 100% efficiency assumptions) is between 151MW-‐558MW. With 1% efficiency from this re-‐calculation, a 1.5MW power plant would be reasonably plausible.

However, the 1:50 assumption, as assumed amount of energy potential in the San Lorenzo Ri

Water Street Bridge (F (Fig. 1 label A) [8]. The salinity of these conductivities is calculated to be: 0.00326M

and 0.593M respectively, which results in a salinity gradient of 1:182. Applying these location-‐ specific molarities and measured temperature of 284K to the Gibbs Free Energy equation above (equation 7), the San Lorenzo River has a theoretical energy of 928,763 Joules/m3, which is almost 200,000 Joules more than the initial estimate and brings the maximum theoretical power potential to 190MW-‐700MW.

This project focuses on harnessing this theoretical energy by designing and building a prototype stack of ten concentration cells to use as a test bed for collecting data regarding the saline energy potential at the estuary between the San Lorenzo River and the Monterey Bay. Voltage sensors will output real-‐time data to a website to track cell production and ultimately determine the feasibility of using reverse-‐electrodialysis to supplement a small portion of current energy sources in Santa Cruz, CA.

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BACKGROUND: HOW DOES A CONCENTRATION CELL WORK [10 , 12] Two solutions containing the same ions but in different concentrations yield a voltage potential if separated by a membrane that only allows specific ions to pass through it.. The expected voltage for each individual cell is calculated from the Nernst equation[10]:

(8)

V = cell potential [volts]

R = Universal Gas Constant: 8.314 [J/molK]

T= Universal Temperature [K]

z= number of valence electrons per ion passed through a membrane

Where V is the cell potential [volts], R is the universal gas constant = 8.314 J/molK, T is absolute temperature [K], z is the number of electrons transferred for each ion passing through the

concentrations are defined by the molarity of each side of the cell. Using these variables and an expected concentration gradient of 1:182, as measured from the San Lorenzo River Watershed Management Update in 2001, each concentration cell is calculated to produce 127mV open circuit.

This voltage is achieved by allowing specific high concentration ions to diffuse into the low concentration solution, which is defined by the type of membrane. The membrane of a concentration cell can be either an anion exchange membrane or a cation exchange membrane. The anion exchange membrane is slightly positively charged and allows negative ions (anions) to pass through, while repelling positively charged ions (cations). The cation exchange membrane does the opposite, attracting positive ions and repelling negative ions. In this

-‐ to flow through the membrane (Fig. 3A).

Since the anion exchange membrane (AEM) is selective for Cl-‐ and the high concentration is disposed to spontaneously equilibrate with the low concentration, the Cl-‐ from the high concentration will flow through the membrane [10, 12]. The movement of Cl-‐ to the low concentration unbalances the neutral charge of the two solutions. To achieve equilibrium, Ag

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from the Ag/AgCl electrode sends its electron across the wire connecting both the anode (low concentration electrode) and the cathode (high concentration electrode). When Ag loses its electron, it becomes Ag+ which bonds with Cl-‐ to become AgCl on the anode (Fig. 3B). The electron that was sent from the anode Ag, pairs with AgCl to become Ag and Cl-‐ (Fig. 3C).

Figure 3 [10, 12]: How a concentration cell works. (A) Two solutions containing the same ions are separated by a semi-‐permeable membrane (green). The left side is the low concentration; the right side is the high concentration. Both electrodes are the same material, Ag/AgCl. (B) The solutions work to achieve equilibrium. Our membrane only allows negative ions to flow through since it is an anion exchange membrane, thus Cl-‐

from the cathode flows through the membrane. (C) Ag+ and Cl-‐ bond to form AgCl on the anode sending an electron to the cathode, which takes the electron to split AgCl into Ag and Cl-‐. Slowly, the concentrated side becomes more dilute and the lower concentration side becomes more concentrated[14]. The voltage is a result of the high concentration selective-‐ion diffusion to the low concentration.

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SPECIFIC AIMS

Construct a concentration cell that generates energy to charge a battery using the salinity gradient between the San Lorenzo River and the Monterey Bay.

Develop a storage component (i.e. battery) for the cell to transfer the energy generated. Output real-‐time voltage and current readings to website. Transfer sensor readings from client to server. This will be done in real-‐time and

autonomously so that the information available for display on the website is as relevant as possible.

Determine feasibility of reverse electrodialysis as a realistic alternative to current energy sources.

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APPROACH

CELL CONSTRUCTION A key motivation of the project is to keep the cost of the total construction low while still generating a significant voltage and current from the system. The setup consists of ten unions that hold the membranes in place and uses gravity instead of pumps to deliver water to the unions. Each union is connected to two 3-‐way tees which are then connected to piping that deliver water to each side of the union. In order to add a level of rigidity in the system, there are two rows of five unions with PVC piping connecting each side of the union with river and seawater. The fresh water and seawater are held in 5 gallon buckets and water flow is controlled by a ball valve on each bucket. Vinyl tubing connects to the bottom of the 3-‐way tees to allow for drainage of brackish water and is plugged by 20 mL syringes which serve a dual purpose.

In order to prevent a possible short circuit between all the cells when water has filled the system to capacity, 20 mL syringes were used to plug the drainage piping. Once water has completely filled the system, the syringes can be extended to lower the total water level in the system by 400 mL. This reduction is water level allows for air gaps to exist between each cell and eliminating the chance of a short circuit. This was an important design feature because the cells closest to the two sources of water fill up first and there is no way to control how much water enters each individual cell. By plugging the drainage tubing with the syringes, the threat of a short circuit is eliminated and we have a convenient method to drain the system of water.

Based on our belief that diffusion drives our voltage, we wanted our electrodes to be as close to the membrane as possible and for a steady reading they would need to remain in the same place throughout the experiment. This led us to install mesh wiring in each side of the union to which we attached the electrodes using caulking. By having the electrodes secured in a position very close to the membrane, we ensured a steady reading and could rule out the position of the electrodes as a variable in our experiments.

The wiring of each electrode goes up through the 3-‐way tee through a hole at the top of the tubing providing water, which also proves to be advantageous. By having the wires protruding from the top of the piping, we can wire the system to be in any combination to maximize the voltage generated. Initially, we believed all the cells in series would provide us the maximum voltage but when that proved to be incorrect, it was very simple to re-‐wire the system to have ten cells in parallel.

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The original design consisted of around 50 valves to control the flow of water into and out of the unions but this proved to be extremely costly and not practical for our vision of the system. In place of this design, Professor Karplus helped us drastically reduce the number of valves needed and the most current design can be seen in Figure 4.

Figure 4: Revised Cell Design. This design drastically reduces the number of valves needed to control the flow of water into the 3-‐way tee. The membrane will be placed in the union and water will be delivered to the 3-‐way tee and discharged using Tygon tubing. The tubing used for discharging water will be controlled by clamps and the main water supply from the two tanks will be controlled by quarter-‐turn valves.

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EXPERIMENTATION The initial approach to this project was to stack ten cells in series by alternating concentrations and membranes. For example, the stack would have the following set-‐up: ELECTRODE: High : CEM : Low : AEM : High : CEM : Low : AEM : High : ELECTRODE, where AEM is an anion exchange membrane and CEM is a cation exchange membrane. The initial results from trying these alternating cells showed more voltage coming from an individual cell than from the whole stack. Therefore, the prototype changed into a single membrane type of cell that would connect serially to other cells via electrodes, not membranes.

Choosing the appropriate membrane to separate the two saline concentrations was the next experimental task. There were three candidate membranes: Millipore VCWP-‐ Membrane, Millipore GNWP-‐ Membrane, and Fumasep FAD-‐ Anion Exchange Membrane. To compare the membranes, a small test cell (0.5cm diameter, 0.7cm depth, 0.196cm2 membrane surface area and 0.137cm3 volume) was fabricated out of a silicon polymer, poly-‐dimethylsiloxane (PDMS) (Fig. 5).

This experiment was performed using water from the Monterey Bay (Fig. 2 label A) and the San Lorenzo River (Fig. 2 label B). A low gradient was expected from these samples, since the

Figure 5: Dimensions of Test Cell. Each cell half-‐cell has a depth of 0.7cm and a diameter of 0.5cm. The volume of the cell is 0.137cm3 and the surface area of cell:membrane is 0.196cm2. The left half-‐cell is the low concentration. The right half-‐cell is the high concentration and the membrane (grey) is sandwiched between. Platinum wire electrodes are placed on the outer part (away from membrane) of the cell and two glass slides (one on each side) is pressed against the outer part of the cell to contain the solutions and electrodes. A binder clip is used to hold the whole cell together during experiments.

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Monterey Bay reaches the low concentration location during high tide. However, maintaining the same conditions for each experiment, the best of three different membranes could be determined. Figure 6 shows the experimental set-‐up.

The results from this experiment are shown in Figure 7. The peaks at the beginning of the graph are results of noise from a small salinity gradient and noise from removing the platinum electrodes, quickly rinsing and drying and then placing into the next cell for measurement. The Fumasep FAD membrane had instructions to soak the membrane in NaCl prior to using the membrane, so data is included for the FAD membrane from a soaked and non-‐soaked FAD membrane.

Figure 6: Membrane Experimental Set-‐up. Each cell is independent, so there is a total of six individual cells. Voltage was recorded for three individual cells; one cell for the Fumasep FAD membrane, one cell

was recorded one at a time with the same 100k resistor as a load. Electrodes were made of platinum, and connected to copper wire attached to sensor leads from the Gamry Ref. 600 Potentiostat. Cells were completely set-‐up and solutions were injected via syringe after voltage reading script was running. The FAD and VCWP membranes are anion exchange membranes and the GNWP membrane is a cation exchange membrane. Each cell was recorded for 600 seconds for a simple peak voltage test.

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The voltage, although negative, was notably higher for longer using the Fumasep FAD membrane, soaked. From this experiment, we concluded the Fumasep FAD anion exchange membrane to be the best membrane of the three.

Following these preliminary tests, which supported continued exploration of reverse

11. An individual cell was tested with water from near the Water Street Bridge (Figure 2, label C) and the Monterey Bay (Figure 2, label A). The open circuit voltage, as shown in figure 8A was around 225mV. The same cell had a 1M load applied to measure the current; a voltage of 165mV, as shown in figure 8B, with a 1M law to determine a current of 0.165 A. This current was too small for the energy storage component, so a new design of two parallel stacks of five cells in series was proposed.

Figure 7: Results from Different Membrane Experiment. Three different membranes were tested for maximum voltage. A 100K resistor was placed in series with a cell containing one of three membranes: Millipore anion exchange membrane, Millipore cation exchange membrane and Fumasep FAD membrane. The Fumasep membrane came with instructions to soak the membrane in a 2-‐4% solution of NaCl prior to use, so a fourth cell was used to test a soaked FAD membrane.

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Figure 8, which used platinum electrodes, suggests that with two parallel stacks of five cells in series, a possible 825mV can be generated with 0.33 A of current for a power output of 0.272 W. Ten individual cells were constructed with adaptable wiring to test both ten serial cells and two parallel stacks of five serial cells. The results of ten cells in series, in figure 9, suggest that the cells do not stack up as expected. Disregarding the spikes, which are due to manually recorded voltage interference, the average voltage is ~341mV; 15% of what was expected for ten cells in series (2.25V = 0.225V X 10 cells). The non-‐uniformity amongst the cells suggests that these cells do not stack up like batteries. This data was recorded near the end of the ten-‐week deadline, so a quick re-‐wiring of the cells, to stack ten cells in parallel was proposed to generate 165mV (10 cells in parallel each generating ~165mV with load) and boost the current.

Figure 8: Results from Individual Cell. -‐way tees, ¼ in mesh wiring (to hold electrodes in place) and platinum electrodes. (A) The Gamry potentiostat voltage recording script was started prior to water introduction to the cell, thus the voltage shows a steep peak at the beginning of the graph. The voltage remained a constant ~-‐225mV for 36,000 seconds (10 hours). (B) A 1M load was set in parallel to the cell and the voltage was recorded across the load. The voltage reached ~-‐150mV for a constant 30,000 seconds (8 hours, 20 minutes). The script was ended early due to voltage output consistency. A 1M load on a 165mV source determines a 0.165 A current.

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Ten cells stacked in parallel yielded results opposite of expectation, as shown in the figure 10. The voltage was unstable for the first 30,000 seconds at ~85mV, then the voltage climbed

Figure 9: Ten Individual Cells in Series. The initial voltage spikes are due to noise induced by manual voltage measurements. Once the Gamry script was reading out voltages lower than the expected

manually by a handheld multi-‐meter. The manually gathered data is shown in the chart below the graph with the time the voltages were recorded and the respective voltage for each cell.

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~100mV to 200mV from 30,000 seconds to 40,000 seconds. At time 43,140, a 200k load was put in parallel with the cells to determine the current. Applying a load made the voltage jump to ~550mV with sporadic drops back towards 0mV. The voltage lasted approximately 15,000

demand for using the Gamry potentiostats prevented additional experiments, but these two experiments suggest that more experiments are needed to make a conclusion assessment of the feasibility of reverse electrodialysis as an alternative source of energy.

Figure 10: Ten Individual Cells in Parallel. The first 43,000 seconds were open circuit. At t=43,140, a 200,000 load was put in parallel with the stack. A voltage of 550mV with a 200k load has a 2.75 A current, which is over eight times greater than the cells in series. The voltage drops significantly 15,000 seconds after the load was placed into the circuit, which may be due to a depletion of ionic gradients, but further tests (conductivity) would need to confirm this.

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DEVELOPING A STORAGE COMPONENT FOR THE CELL

BATTERY OPTIONS/CHARGING METHODS: The charging method is dependent on the amount of power available from the concentration cell. Because the cell is predicted to generate very low power, a low charge rate occurs and the battery will need to be trickle charged. Trickle charging is a constant current applied to the battery for an indefinite amount of time. Trickle charging does not need any circuitry to detect charge termination. The battery type was then chosen based on this charging method because not all battery chemistries can tolerate specific charging methods.

Nickel metal hydride (NiMH) batteries were chosen because NiMH and Nickel cadmium (NiCd) are the most popular batteries to use when trickle charging. Lead acid batteries were not considered because while they can tolerate a short duration of trickle charging, extra circuitry is usually needed to prevent overcharging. While NiCd batteries are the most robust type of battery with respect to overcharging [13],the recombination process that keeps the voltage at a safe level when overcharging occurs also causes a shorter battery life. NiCd batteries also suffer

holds less charge because it had been repeatedly charged after being only partially discharged. On the other hand, technologically newer and more environmentally friendly without the toxic cadmium found in NiCd batteries. NiMH batteries are also more common than and are recommended over NiCd.

CIRCUIT DESIGN: A voltage boost circuit will be implemented to increase the low voltage generated from the cell to charge a battery with a higher voltage. Storage components, such as capacitors and inductors, are used to step up the voltage. Once the storage component reaches a certain voltage, one or more transistors turn on to send power to or from another storage component. A simple voltage boost circuit is shown in figure 11. At the top, the switch is closed and a current begins to increase across the inductor. After a fixed amount of time the switch opens, as seen in the bottom. When the switch is open, the voltage across the switch increases until it causes the magnetic field across the inductor to collapse as it is trying to maintain the current. The current is then driven through the diode and into the capacitor until the inductor is

biggest problem in designing the circuit.

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The current generated from the cell is in the microwatts range, which means that the biggest issue in the circuit design is the loss of current due to the leakage in the components involved. I picked the components with the lowest leakage current so as not to lose the current generated from the cell altogether. The circuit shown in figure 12 shows a more complicated boost circuit.

The inductor requires a larger current than is being provided. In figure 12, the cell charges the capacitor C2 to provide bursts of voltage and current higher than the cell initially provides. When C2 contains a sufficient amount of voltage to turn on Q2, U1a turns on. In response to U1a, Q3 turns on and transfers the energy stored in C2 into the inductor. Because the current is still very small, the inductor chosen needed to be physically larger in order to decrease the current lost across the inductor. After a certain amount of time, Q3 turns off. The inductor will

Figure 11[15]: Circuit diagram. When the switch is closed a current begins to increase across the inductor. After a fixed amount of time the switch opens and the voltage across the switch increases until it causes the magnetic field across the inductor to collapse as it is trying to maintain the current. The current is then driven through the diode and into the capacitor until the inductor is expended. This circuit generates pulses of a greater voltage.

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then transfer the energy into C1, which will then be used to charge the battery. The simple filter using R8 and C5 serve as the smoothing circuit required to reduce ripple caused by the bursts of energy, allowing a constant current to charge the battery.

RESULTS: The circuit was tested in lab using a power supply with 0.3V and 1mA. The first test consisted of a battery pack of 2 AAA NiMH rechargeable batteries being charged for 40 minutes. The voltage of the combined batteries (2.4V) was too small for the circuit to charge because the circuit was designed to charge at least 3V. The second test consisted of a battery pack of 4 AAA NiMH rechargeable batteries being charged for 40 minutes. This yielded 2 partially charged batteries. The battery charge was detected by placing each battery in a small flashlight and timing how long the light stayed on. The third test consisted of the battery pack containing 4 AAA NiMH rechargeable batteries being charged overnight for 12 hours. This yielded the same results as the 40 minute charge time.

Figure 12 [16]: The cell charges the capacitor C2 to provide bursts of voltage and current higher than the cell initially provides. When C2 contains a sufficient amount of voltage to turn on Q2, U1a turns on. In response to U1a, Q3 turns on and transfers the energy stored in C2 into the inductor. After a certain amount of time, Q3 turns off. The inductor will then transfer the energy into C1, which will then be used to charge the battery.

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TRANSFER SENSOR READINGS FROM CLIENT TO SERVER

DEFINING THE PROBLEM OF DATA TRANSFER The primary issue to be addressed is the transfer of sensor readings at the Gamry potentiostat

potentiostat will communicate with a connected via USB. From the client machine, the sampled data must be transmitted to the

emote database server. Figure 13 below shows an outline of the data transfer process, illustrating how solving the problem of data transfer requires the creation of two communication interfaces between three components.

Gamry Potentiostat

(Sensor)

Sensor output data (Raw text)

Client Machine Program

Web

Server

SQL insertion statements

Figure 13: The data transfer process involves the connection of three components across two communication interfaces. Our sensor device must be able to transmit data to a program running on a nearby computer. From there, the data will need to be sent as SQL insertion commands to the database/web server.

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There are additional needs that should be addressed while implementing these communication interfaces. This includes the need for data to be sent at a rate as close as possible to real-‐time. The data monitoring process must support a rapid sampling rate of one sample per one to two

continued development of this and similar projects, the process should be implemented as independently as possible from the operating system.

INITIAL PLANNING AND CONSIDERATIONS To address the need for operating system independence, Python was chosen as the primary coding language for the client program. Python is fast, and is very good for rapid text and data

Python program will access the sampled data, translate this data into SQL insertion statements, and send these commands to the server via a direct and secure connection over Ethernet.

One of the difficulties of this part of the project is that a race condition exists within the interface between the Gamry potentiostat and the Python program. Controlling the Gamry potentiostat is done through the use of Explain scripts, an open-‐source scripting language developed by Gamry. Gamry has provided a set of scripts which do certain common tasks, such as monitor the voltage across two probes. The Explain script which monitors voltage creates a file which contains the sampled data. The challenging aspect of this is that the script keeps this

data in real-‐time. To overcome this obstacle, there were a few appealing options. One was to have the Explain script call the Python script directly, and to pass the voltage sample as a parameter at the command line. Another solution was to make sure that the file being written to by the Explain script is closed for a period of time, during which time the Python program will open, read, and close the same file.

The development of the communication interface between the Python program and the server was mucestablishing a secure connection to a MySQL server within the Python program. This approach is well-‐documented in online tutorials, and was not expected to be a complex problem.

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INTERMEDIATE AND FINAL SOLUTIONS Communication between the Python program and the database server was finished very fast. A proof-‐of-‐concept was complete within the first two weeks, where the Python program could randomly generate data values and send corresponding SQL insertion commands to the server.

Python program quickly became the more challenging and time-‐consuming task. The Explain script language is based on C, although there is no way to execute pure C code from within an Explain script. Over time, we discovered several other severe limitations of the scripting language. This includes the fact that while the potentiostat is polling for data, the script cannot execute any commands. This means that if the potentiostat is continuously polling for data, as we had planned, the script cannot execute commands except for before and after the data is gathered. This invalidated our original idea to pass the sampled data value as a launch parameter to the Python program, since the program would need to be launched between each

the task of properly formatting the string to launch the Python program.

Through our correspondence with Gamry technicians, we attempted to bypass the ongoing issue of the script becoming unresponsive during data sampling. They offered various convoluted techniques, none of which completely solved the problem in a way that would allow for real-‐time data transfer. We eventually found a way to repeatedly signal the potentiostat to start and stop the data polling process. This allowed us to implement the full sequence of events shown in Figure 14. Due to the Explain script language having such poor support for string formatting, we decided to use a file-‐based solution to pass the sampled data to the Python program, rather than passing the data as a parameter when the Python program is called.

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Figure 14 shows the complete process that is used within the communication interface between the potentiostat and the Python program. This process is fully implemented with

between samples is two seconds, while the Python program takes only 0.25 seconds to fully execute from the time it is called. Using this looping Explain script, can be monitored indefinitely at a rate of one sample per two seconds, until an operator manually stops the script. Although the Python script is very straightforward, it has been included in Figure 15 below for completeness and reference.

Signal potentiostat active

Open file

Poll for voltage data

Write to file

Close file

Signal potentiostat inactive

Call Python Program

Wait

Loop

Figure 14: The execution process of the Explain script, which supports communication

avoid a race condition where the Python program and the Explain script compete for the use of the same data file.

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Open file

Read data

Convert data from string to float

Establish secure database server connection

Generate SQL insertion command

Send SQL command to database server

Close file

Figure 15: The execution process of the Python program, which supports communication between the Python program and the web/database server. SQL-‐related functionality is

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DISPLAYING REAL-‐TIME VOLTAGE AND CURRENT READINGS ON A WEBSITE

OVERVIEW: Displaying real-‐time data on a website will help monitor the concentration cell off-‐site. This data will also be saved in the server so that researchers can examine and look at this past history of current and voltage readings. Our team has developed an interactive design so that users can specify specific options like dates or style of plot output.

SERVER SETUP: In order to display the real-‐time sensor readings of our project, a LAMP Server has been set up and configured. A LAMP stack consists of Linux, Apache, MySQL and PHP. This is a powerful and professional stack used by industry to maintain and run powerful websites. A LAMP server has been chosen because it runs on Linux, which offers a range variety of open source software that can be used to complete and expand this project.

Apache is a popular and open source webserver. Apache is running our website which will help to display static and dynamic pages to the public with useful project progress and sensor data.

the local machine or through SSH.

MySQL is open source database software that is used to manipulate and output data in a readable fashion. MySQL has been configured so that it can be accessible from any public and external ip address. MySQL has been set up to work implicitly with SSH, which will allow users to manipulate the settings and permissions of databases. Databases in MySQL have been created and set up to receive and store autonomous data from the client program. These databases are also used to simultaneously display the data to our website.

WEB DESIGN: PHP is a scripting language that is used implicitly with MySQL queries to recognize sensor readings from the client program and to store the data accordingly. A connection has been established with the database and webserver to retrieve the data into a query and output it to a dynamic page using PHP.

The website has been created using css, xhtml, php, mysql, jquery, python and javascript. It includes static and dynamic pages. The static pages provide an overview of the project. The

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dynamic content is composed of real-‐time plots that have been configured for outputting real-‐time data output. To provide the user with this data in a nice comprehensible way we have integrated ajax(asynchronous javascript and xhtml). Ajax allow us to update specific areas of our website without updating the whole page.

The website has been given a static ip and a domain name of red.soe.ucsc.edu. This website can be accessible from any web browser by typing the domain name(url). This domain name can also be used to access the server through ssh.

WEBSITE GRAPHS AND TABLE OUTPUT: One of the main purposes of the website is to display comprehensible real-‐time data. Our data will be displayed on our website via comprehensible graphs and tables. To achieve a user-‐friendly interface we have made our website versatile to the point were it is OS and web browser independent. Our website gives the user two options a flash or no flash data view. This allows users/clients to view the data even from an iPhone or school computers, which usually

-‐time graphs are all located at red.soe.ucsc.edu in the results tab.

We use Jighi Jcharts to display real-‐time flash graphs and charts. We fed in our mysql database to Jighi, with their user interface we were able to customize the graphs and charts to display data comprehensively to the user. In Figure 13 and 14 we can see a graph and chart from the Jcharts output that we got from our stored voltage data. The graphs and tables have display options, this can allow the user to view data within a range or even specify a custom order for the tables.

For our non-‐flash version we have a picture that updates with an ajax call every time there is new data. This graph was created via a python library called matplotlib, this library works great because it works directly with mysql. It is set up and configured to display comprehensive and readable incoming voltage and current readings. In Figure 15 we can see this graph with data samples. Every 100 samples a new image is created and the previous one is archived in our gallery archive this can be seen in Figure 16. Our gallery archive allows users to skim trough past sensor recordings and make decisions on how to approach it differently to have a greater output.

Jquery was a big help to merge all of these graphs into a nice user-‐friendly interface. Jquery gave us the ability to create tabs that asynchronously only update the tab sections. This cleans up the website and makes everything short and concise.

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Figure 13: Flash graph, this user interface was provided by Jighi. The graph shows Voltage readings vs Timestamps

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Figure 14: Flash table, this user interface was provided by Jighi. The table shows relevant rows to Figure 14, it also allows you to view columns by order by clicking on them.

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Figure 15: Non-‐have flash installed to still view real-‐time data.

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Figure 16: Non-‐flash gallery archive, this gallery archive allows users with iPhones or -‐time data. This gallery archive

allows us to scroll through past data and view previous recorded results.

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REMOTE CAMERA MONITORING SYSTEM: The website also serves as a Remote Camera Monitoring system, it allows us to remotely control a camera through the web browser. This camera allows users and clients to remotely monitor their sensor readings. For any reason that there is any doubt about the sensor readings we can watch the physical concentration cell setup to detect leaks, wire disconnections or unforeseen mishaps.

The remote camera monitoring system has features that allow users to specify different view options. In Figure 17 we can see the physical user interface on our website, as you can see you are given the option to pan and tilt the camera to view the concentration cell(or what ever is present in its location) from different angles.

The camera supports real-‐time high quality video and audio over the internet. The camera has been location of the camera and transfer voice across. The camera is equipped with night vision and it is also supports ftp uploading and email notification with images triggered by motion detection or schedule. The motion detection is great because if something occurs in our setup like an unplugged wire or someone interrupts we will be notified.

Besides ftp uploading you can also have a NAS(Network Address Storage), meaning you can have a hard drive or usb connected to the camera to record the data via mpeg4 codec.

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CLOSURE: As we can see this server implementation setup is a great way to monitor our offsite recordings. It will serve as a test bench for our researchers to be able to completely monitor their lab setup efficiently.

Figure 17: Remote Monitoring Camera System. Allows users to pan/tilt and view the concentration cell in Night Vision mode.

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FEASIBILITY CONCLUSION OF REVERSE ELECTRODIALYSIS

power output at maximum was 1.51 W, the actual amount of water mixing in each cell was significantly less than 1m3 of fresh water and salt water mixing. [Note: the dimensions of the cell result in the following approximated volumes: cell (pvc union): 0.0062m2 + two 3-‐way tees: 0.0065m2 + 0.0046m2 for a total of 0.0173m2 per cell.] The total amount of water mixing for this design was 0.0865m2 of fresh water mixing with 0.0865m2 of ocean water.

0.08MJ is available. Over the course of the 15,000 seconds when the ten cells were in parallel and had a load to draw a current, 0.0227J were extracted. This is a 0.000028% recovery, which does not indicate strong alternative energy potential.

Additional experiments would be needed to conclusively deduce that reverse electrodialysis is not a practical alternative source of energy, however it can be concluded that this particular design will not provide adequate percent yield of energy.

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SYSTEM BLOCK DIAGRAM

Send measurement data

Read voltage and current (analog)

Energy harvesting

Read voltage and current (digital)

Read voltage and current (analog) Cell

(x2 BME)

Sensors (x1 BME/EE)

Client Program

(x1 CMPE)

Storage (x1 BME/EE)

Web Server

(x1 CMPE)

Figure 13: The block diagram shows how the concentration cell will relay voltage and current information to the sensors and transfer some of the energy to a storage cell. The sensors will the relay the information

website. This will allow for the concentration cell to be monitored remotely.

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BUDGET

Cell BME (x2)

Components Costs

Anode + Cathode $260 ($8.50 ea.)

Membranes $20 (8 ½ x 11 sheet)

PVC $55

Tubing $60

Valves $20

Total $415

Storage Component EE (x1)

Components Costs

Discrete Components $100

Total $100

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Web Server CMPE (x1)

Components Costs

Domain Name Registration $0

Data Hosting $0

Remote Camera Monitoring System $185

Total $185

Client Computer CMPE (x1)

Components Costs

Used Computer $0

USB / Serial / Etc. Cables $0

Total $0

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PERSONNEL

ALEXANDRA EASTES

Responsibilities:

Responsible for developing a storage component for the energy generated from the cell.

Summarized Biography:

Alex is a bioengineering major with a concentration in bioelectronics and an electrical engineering minor. She has a broad knowledge of classes from a variety of engineering backgrounds. She is currently working on redesigning the old EMG (electromyography) system

-‐limb exoskeleton.

Expertise:

Analog electronics Sensors (biomedical) Electrochemistry

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DYLAN HINGEY

Responsibilities:

Responsible for facilitating communication between the sensor device and the web server. Current and voltage data should be continuously collected from the sensor, and must be transmitted to the server accordingly. This implies the responsibility of creating a client program which reads in the sensor data, and converts the data into SQL queries. Furthermore, the program will need to maintain a secure connection with the server so that data is streamed in real-‐time.


A student majoring in Computer Engineering: Networks and Information Systems Management,

management. Skills gained through numerous programming courses and software-‐related internships witeam-‐based projects through the Information Systems Management curriculum will be useful in facilitating collaboration and communication amongst team members.

Expertise:

Database systems Software development Computer networks Hardware systems Project management

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ULYSSES MORALES

Responsibilities:

Responsible for setting up a web server and completing the web interface that displays voltage and current. The website will feature dynamic real-‐time content in the form of updated sensor data. He will need to use data modeling to display sensor readings in a comprehensive way. If time permits, he will also be responsible in setting up a Remote Camera Monitoring System.


A Computer Engineering st experience working with servers will be a great help in assuring that he completes his duties in this project. He has designed and maintained websites in the past. He has a great amount of experience using Linux, this will help with data modeling and server configuration. His skills will also allow him to expand on the project specifications if there is sufficient time.

Expertise:

Wireless systems Software development Database systems Website development and maintenance Server communication and development

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CHIRAG SHARMA

Responsibilities:

Responsible for the membrane stack and construction of the part of the cell which will hold the membrane. Also, Chirag is responsible for conducting the tests to verify that the expected energy values match the experimental.


A Biomolecular Engineering student, Chirag has prior research experience with membranes and electrochemistry from working in the Akeson Laboratory. This knowledge will be useful for making the concentration cell, choosing the membrane and conducting the experiments on the concentration cell.

Expertise:

Electrochemistry Salinity gradients in biological systems Working with membranes

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DANNY TATE

Responsibilities:

Calculate theoretical voltage, power and energy from mixing the San Lorenzo River with the Monterey Bay. Run experiments for initial prototype cell testing. Combining these theoretical calculations with experimental results, design and build a functioning concentration cell stack.


Danny is a Bioengineer with a biomolecular concentration. His work with the Quantum Electronics Group, headed by Professor Ali Shakouri, involves developing a self-‐recharging battery powered by ions within humans to provide energy to biomedical devices. He has worked on this research for two years and has a strong background in power generation form ionic gradients.

Expertise:

Reverse-‐electrodialysis o Power calculations o Ionic selection o Technical workings

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REFERENCES

(1): United States. U.S. Energy Flowchart 2009. , 2009. Web. 31 Jan 2011. <https://flowcharts.llnl.gov/content/energy/energy_archive/energy_flow_2009/EFC_2009_Annotated.pdf>.

(2) United States. International Energy Outlook. , 2007. Web. 31 Jan 2011. <http://tonto.eia.doe.gov/ftproot/forecasting/0484(2007).pdf>

(3) Veerman, J. "Reverse Electrodialysis: Performance of a Stack with 50 Cells on the Mixing of Sea and River Water." Journal of Membrane Science. 327 (2009): 136-‐144. Print.

(4) Tao, Xiao. "Crystal Structure of the Eukaryotic Strong Inward-‐Rectifier K+ Channel Kir2.2 at 3.1 A Resolution." Science. 326. (2009): 1669-‐1674. Print.

(5) Xu, Jian. "Designing Artificial Cells to harness the Biological Ion Concentration Gradient." Nature Nanotechnology: Letters. 3. (2008): 666-‐669. Print.

(6) Post, Jan. "Blue Energy: Electricity Production from Salinity Gradients by Reverse Electrodialysis."Thesis 3 Nov 2009: 1-‐224. Web. 4 Sep 2010.

(7) United States. USGS Surface-‐ Water Annual Statistics for California Grouped by Hydrological Unit. , 2010. Web. 4 Sep 2010. <http://waterdata.usgs.gov/ca/nwis/annual?referred_module=sw&county_cd=06087&site_tp_cd=OC&site_tp_cd=OC-‐CO&site_tp_cd=ES&site_tp_cd=LK&site_tp_cd=ST&site_tp_cd=ST-‐CA&site_tp_cd=ST-‐DCH&site_tp_cd=ST-‐TS&index_pmcode_00060=1&format=station_list&sort_key=site_no&group_key=NONE&list_of_search_criteria=county_cd,site_tp_cd,realtime_parameter_selection>.

(8) Ricker, John. County of Santa Cruz. Evaluation of Urban Water Quality: San Lorenzo River Watershed Management Plan Update. Santa Cruz, 2001. Web. 25 Jan 2011.

( 9 ) Lewis, Nate. "The Terawatt Dilemma." Photovoltaic Summit 2008. San Diego, CA. 18 Jun 2008. Lecture.

(10) Zumdahl, Steven. Chemical Principles. 5th. Boston, MA: Houghton Mifflin Company, 2005. 432-‐475. Print.

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(11) Salzman, W. "Properties of ideal solutions: Mixtures; Partial Molar Quantities; Ideal Solutions. N.p., 21 Oct 2004. Web. 31 Jan 2011. <http://www.chem.arizona.edu/~salzmanr/480a/480ants/mixpmqis/mixpmqis.html>.

(12) "Thermodynamics." Spark Notes. N.p., 2011. Web. 1 Feb 2011. <http://www.sparknotes.com/chemistry/electrochemistry/thermo/section1.rhtml>.

(13) Simpson, Chester. Battery Charging. National Semiconductor. http://www.national.com/appinfo/power/files/f7.pdf

Journal of Applied Electrochemistry. (2010) 40, 1461-‐1474

(15) "Prototypes Electromagnetic Pistol." Coilgun Systems. Web. 2 Feb. 2011. <http://www.coilgun.eclipse.co.uk/electromagnetic_pistol_voltage_converter_design.html>

Electronic Design 28 Sept. 2006: 60.

http://www.national.com/appinfo/power/files/f7.pdf

http://www.coilgun.eclipse.co.uk/electromagnetic_pistol_voltage_converter_design.html

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REVERSE ELECTRODIALYSIS’’’’’’’’’’’’’’’ PROJECT’REPORT · determine! the! feasibility of! using reverse ]electrodialysis to! supplement! a! small! portion!