Wink of Knowledge: Improved methanol/water concentration model for fuel cells

Wink of Knowledge: Improved methanol/water concentration model for fuel cells

Wink of Knowledge: Improved methanol/water concentration model for fuel cells

Why this test? 

The methanol fuel cell is an important technology for the energy transition. Although today’s methanol production is still heavily dependent on fossil sources, renewable raw materials such as biogas, sewage sludge or even atmospheric CO2 are becoming increasingly important. A fuel cell such as the direct methanol fuel cell (DMFC) then generates electricity from this methanol in a similar way to a conventional generator. It is important for the efficient and safe operation of such fuel cells to feed in a methanol/water mixture with a constant concentration – the optimum concentration depends on the type of fuel cell. Process control is made more difficult by the incomplete conversion of the methanol. A varying proportion of the mixture exits the fuel cell unused and should be continuously recycled. Figure 1 shows the process schematically:

Figure 1: Schematic of a direct methanol fuel cell with various possible measuring points.

Providing a controlled mixture of the recyclate and a methanol stock solution is therefore a challenge. This is precisely where the concentration measurement using the DLO-M2 density sensor comes into play (orange measuring point 2 in Figure 1).

What is a Wink of Knowledge? 

Do you need to quickly measure, draw or do/build something? The speed with which the result may be achieved counts more than the perfect (scientific) approach. For this reason, we have introduced the Wink of Knowledge. Science in the wink of an eye, so to speak. We don’t want to prove anything scientifically. We simply want to quickly demonstrate something pragmatically. If you are interested, we would be happy to discuss these results in more detail with you and your project. 

Results 

Existing data on aqueous methanol solutions were combined with our own measurements using a DSA 5000 M laboratory density meter (Anton Paar). The own measurements mainly included typical operating conditions of fuel cells such as concentrations <10% at temperatures >40°C.

The collected data was processed into a concentration model for our DLO-M2 density sensor. As a result, this can now calculate and output the methanol concentration of a solution directly from the measured density value with an accuracy of ±0.2%w/w:

Figure 2: Accuracy analysis of the new concentration model methanol in water according to %w/w

Of course, in addition to the model accuracy, the measuring accuracy of the sensor is also crucial. In the case of the VLO-M2, this is approx. ±0.2 kg/m3 for the mixtures under consideration (the DLO-M2 achieves a comparable performance after adjustment). For the entire concentration range and an example temperature of 25°C, the following picture emerges:

 

Figure 3: Overall accuracy of the measurement including the measuring accuracy of the DLO-M2 density sensor

In the complete measurement range of 0-100%w/w, the overall accuracy remains very good and is around ±0.3 %w/w (shaded gray in Figure 3). Thanks to the excellent measurement accuracy of the TrueDyne MEMS sensor technology, the error due to the density measurement affects the overall error in this case even less than the pure model accuracy (shown by the orange line at ± 0.2%w/w).

Which sensors were used? 

density sensor DLO-M2

  • Click here to learn more about our sensor

viscosity sensor VLO-M2

  • Click here to learn more about our sensor

Conclusion 

A new, much more accurate methanol/water concentration model has been integrated into the DML product family (DLO-M2 / VLO-M2). The background for this update is the increasing use of methanol as an energy source, for example for power supply via fuel cells. In combination with the high-precision density measurement of our sensor technology, the model enables real-time concentration monitoring of the methanol/water mixture and thus efficient and safe operation of the fuel cell. This enables optimum efficiency to be achieved with maximum service life of the fuel cell.

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Monitoring fuel concentrations

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Winkle of Knowledge: Concentration measurement protein

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Winkle of Knowledge: Concentration measurement protein This knowledge wink is dedicated to measuring the concentration of protein in water using the physical parameters of density and viscosity. Commercially available whey protein was used as an example, the...

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Wink of Knowledge: Improved methanol/water concentration model for fuel cells

Wink of Knowledge: Improved methanol/water concentration model for fuel cells

A new concentration model for methanol / water mixtures is shown. The model covers a wide range of process conditions: At temperatures of 0-80°C, concentrations of 0-100% can be calculated from the density with an accuracy of ± 0.2%. The direct methanol fuel cell (DMFC) is an important application for this as the power source of the future.

read more
Wink of Knowledge: smart mass flow controller

Wink of Knowledge: smart mass flow controller

Discover the future of precise gas flow control with the innovative Smart Mass Flow Controller from TrueDyne Sensors AG. In cooperation with IST AG, we have developed a pioneering device capable of measuring density, temperature, pressure and mass flow – all in one sensor. Designed for flexibility and accuracy, this controller automatically adapts to different pure gases and binary gas mixtures, ensuring optimal performance. Learn more about this groundbreaking solution at TrueDyne Sensors AG.

read more
Article: In-line measurements of the physical and thermodynamic properties of single and multicomponent liquids

Article: In-line measurements of the physical and thermodynamic properties of single and multicomponent liquids

Microfluidic devices are becoming increasingly important in various fields of pharmacy, flow chemistry and healthcare. In the embedded microchannel, the flow rates, the dynamic viscosity of the transported liquids and the fluid dynamic properties play an important role. Various functional auxiliary components of microfluidic devices such as flow restrictors, valves and flow meters need to be characterised with liquids used in several microfluidic applications.

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Wink of Knowledge: smart mass flow controller

Wink of Knowledge: smart mass flow controller

Wink of Knowledge: smart mass flow controller 

Why this test? 

With conventional thermal mass flow meters and controllers (MFM/MFC), associated parameters must be set manually for each specific gas or binary gas mixture. 

In cooperation with Innovative Sensor Technology (IST AG), we are currently working on the development of a thermal flow meter called FGF. This module simultaneously measures density, temperature, pressure, and mass flow and calculates the derived measured variables in a single device. The density measurement enables the differentiation of pure gases and the determination of the concentration of binary gas mixtures. This allows the measured flow rate to be corrected and the mass flow to be converted into a volume flow in real time. This means that a sensor with a single, generic gas calibration can be used for (almost) any number of gases. 

A prototype mass flow controller has now been developed based on the FGF. Thanks to the versatile and precise sensor technology, the volume flow can be controlled precisely and independently of the gas. The controller parameters of the valve are automatically optimized for the current gas or binary gas mixture. 

What is a Wink of Knowledge? 

Do you need to quickly measure, draw or do/build something? The speed with which the result may be achieved counts more than the perfect (scientific) approach. For this reason, we have introduced the Wink of Knowledge. Science in the wink of an eye, so to speak. We don’t want to prove anything scientifically. We simply want to quickly demonstrate something pragmatically. If you are interested, we would be happy to discuss these results in more detail with you and your project. 

Results 

After a series of measurements with the mass flow controller, it was found that there is a clear correlation between the ideal controller parameters and the density, as shown in Figure 1. 

The correlation between the optimal controller parameters and the density is because gas becomes heavier with increasing density, which in turn leads to a slower reaction of the valve. 

The current required to open the valve is significantly lower as the density of the gas increases. We also refer to this valve parameter as the zero offset. This is due to the fact that a heavier gas exerts more pressure on the valve when closed compared to a lighter gas. 

With the help of the trend line function, the respective parameters for the controller and the zero-point offset can now be calculated. This means that all valve parameters for any gases or binary gas mixtures within a known density range can be optimally set without manual correction. 

Figure 1: Density dependence of the parameters 

Figure 2 shows the difference between the measured flow rate of our MFC prototype, without specific parameters for the gas mixture, compared to a conventional mass flow controller for a binary mixture of 50% nitrogen and 50% carbon dioxide. 

The orange measurement curve clearly shows that the controller of the conventional MFC does not settle into a stable state, especially at higher flow rates. Thanks to the integrated density measurement and concentration determination of the FGF, the optimal valve parameters are set automatically. This results in short settling times and a stable flow control, which can be seen in the red measurement curve, independent of the mixing ratio over the entire flow range – a patented world first! 

Figure 2: Measured flow of our MFC prototype and a conventional MFC 

Which sensors were used? 

Density sensor DGF-i1

  • Click here to learn more about our sensor

Flow sensor SFS01

  • Click here to learn more about the mass flow sensor of the IST AG.

The density measurement, on which the clean gas detection and concentration determination is based, was carried out with the DGF density sensor for gases from TrueDyne Sensors AG.

The gas flow and its direction were determined using the SFS01 thermal flow sensor from IST AG. 

Conclusion 

Our prototype of a mass flow controller based on the FGF shows clear advantages in the gas-dependent control of flow rates compared to conventional MFCs. By automatically adjusting the valve parameters depending on the density, the mass flow can be controlled precisely and independently of the gas. This enables stable, flexible, and precise flowmeasurement and control in a wide range of applications without having to adjust any parameters manually. 

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Wink of Knowledge: Improved methanol/water concentration model for fuel cells

Wink of Knowledge: Improved methanol/water concentration model for fuel cells

A new concentration model for methanol / water mixtures is shown. The model covers a wide range of process conditions: At temperatures of 0-80°C, concentrations of 0-100% can be calculated from the density with an accuracy of ± 0.2%. The direct methanol fuel cell (DMFC) is an important application for this as the power source of the future.

read more
Wink of Knowledge: smart mass flow controller

Wink of Knowledge: smart mass flow controller

Discover the future of precise gas flow control with the innovative Smart Mass Flow Controller from TrueDyne Sensors AG. In cooperation with IST AG, we have developed a pioneering device capable of measuring density, temperature, pressure and mass flow – all in one sensor. Designed for flexibility and accuracy, this controller automatically adapts to different pure gases and binary gas mixtures, ensuring optimal performance. Learn more about this groundbreaking solution at TrueDyne Sensors AG.

read more
Article: In-line measurements of the physical and thermodynamic properties of single and multicomponent liquids

Article: In-line measurements of the physical and thermodynamic properties of single and multicomponent liquids

Microfluidic devices are becoming increasingly important in various fields of pharmacy, flow chemistry and healthcare. In the embedded microchannel, the flow rates, the dynamic viscosity of the transported liquids and the fluid dynamic properties play an important role. Various functional auxiliary components of microfluidic devices such as flow restrictors, valves and flow meters need to be characterised with liquids used in several microfluidic applications.

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Wink of Knowledge: Monitoring the beer fermentation process via density and CO2 formation

Wink of Knowledge: Monitoring the beer fermentation process via density and CO2 formation

Wink of Knowledge: Monitoring the beer fermentation process via density and CO2 formation

Why this test? 

Density is already measured in most breweries for monitoring the fermentation process and determining the final alcohol content. Especially in micro and small breweries, this is usually still done by using a hydrometer. For this purpose, a sample must be taken from the fermentation tank for each measuring point, which is then used for measurement. To be able to follow the fermentation process, many measurements are required, which requires a significant amount of time and beer. In this Wink of Knowledge we present two automatable alternatives, on the one hand the direct inline density measurement by means of DLO-M2 and on the other hand the (flow) measurement of the formed CO2 with a DGF-SFS module. 

What is a Wink of Knowledge?

Do you need to quickly measure, draw or do/build something? The speed with which the result may be achieved counts more than the perfect (scientific) approach. For this reason, we have introduced the Wink of Knowledge. Science in the wink of an eye, so to speak. We don’t want to prove anything scientifically. We simply want to quickly demonstrate something pragmatically. If you are interested, we would be happy to discuss these results in more detail with you and your project.

Results

The density of the wort (original extract) was measured and found to be 15.82° Plato according to the DLO-M2 with proprietary concentration package. The verification measurement with the laboratory instrument DSA 5000 M (Anton Paar) gave 15.75 °Plato which is in excellent agreement (typical measurement errors with a hydrometer are in the range 0.1° Plato – 0.2° Plato for skilled users, with common handheld instruments at 0.25°Plato). The density curve was measured continuously throughout the fermentation process and is shown together with the apparent extract calculated from it on Figure 1. The progression is as expected: After a short, stable start-up phase, the reaction accelerates before running into saturation and the fermentation process finally comes to a halt again.

Figure 1: Progression of density and apparent extract during the fermentation process.

The opposite behavior can be observed for the alcohol content, which can also be calculated from these data (Figure 2).

Figure 2: Course of alcohol content and real extract during the fermentation process. 

Thus, all relevant parameters of beer fermentation could be monitored in real time by density measurement. Extract as well as alcohol content of the finished beer could also be determined. 

The second way to monitor the same parameters is to measure the escaping CO2, since it is formed in a fixed stoichiometric ratio to the ethanol: 

C6H1206 -> 2 C2H5OH+ 2CO2 

Or as a mass balance in g/mol: 

180.16 -> 2 * 46.07 + 2* 44.01 

The summed-up CO2 flow, measured by means of the SFS-DGF module, yields the total amount of CO2 formed, from which the total mass of alcohol and thus the alcohol content can also be deduced according to the above formula. In the experiment, the total measured CO2 flux turned out to be 1.29 times lower than expected according to the density measurement (Figure 3, Figure 4 then shows the correspondingly corrected back calculation of the extract/alcohol content). The reaction course is very well represented by the flow measurement, so that a control of the fermentation process using the correction factor would already be possible.

Figure 3: Measured CO2 flux compared to expected CO2 flux (according to density data)
Figure 4: Back calculation of the alcohol content as well as the extract from the CO2 flow measurement with correction factor

Besides small leakages, a reason for the lower CO2 stream in our measurements could be the humidity and the ethanol content in the measured gas (a thermal measuring principle was used, which is sensitive to the gas composition). Therefore, an additional determination of the humidity and the ethanol content is recommended for future measurements. The former can be accomplished by means of an additional HYT humidity module. After measuring the humidity, the already used DGF density sensor can then determine the concentration of the remaining two components, CO2 and ethanol. Thus, the thermal flow signal of the SFS flow module can be corrected and the actual amount of CO2 formed can be determined more accurately. 

Which sensors were used?

density sensor DLO-M2

  • Click here to learn more about our sensor.

Density sensor DGF-i1

  • Click here to learn more about our sensor

mass flow sensor SFS01

  • Click here to learn more about the mass flow sensor of the IST AG.

Procedure

Wort (15.75 °Plato) was filled into a 3l lab bottle and fermented within < 2 days by adding yeast (many thanks to Severin Ramseyer for wort + yeast). During this process, the mixture was continuously pumped through a DLO-M2 density sensor using a 140um mesh filter. At the same time, the resulting CO2 was passed through a wash bottle (filled with water) to a DGF-SFS module. The module was set to a mixture of air+CO2. In both cases, the data were logged using “Remote Control” software and a laptop. The entire setup can be seen in Figure 5.

 

Figure 5: Test setup 

Conclusion

A continuous density measurement using DLO-M2 was successfully implemented to follow the beer fermentation process. Extract as well as alcohol content of the finished product could be determined. The flow measurement of the resulting CO2 agreed qualitatively very well with the density measurement and could also be used to control the fermentation process. For quantitative back-calculation to alcohol content and extract from the flow data, a correction factor must be used for the time being. In the future, however, a measurement of the humidity and ethanol content in the CO2 stream will be made to determine the CO2 content more accurately. 

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Wink of Knowledge: Improved methanol/water concentration model for fuel cells

Wink of Knowledge: Improved methanol/water concentration model for fuel cells

A new concentration model for methanol / water mixtures is shown. The model covers a wide range of process conditions: At temperatures of 0-80°C, concentrations of 0-100% can be calculated from the density with an accuracy of ± 0.2%. The direct methanol fuel cell (DMFC) is an important application for this as the power source of the future.

read more
Wink of Knowledge: smart mass flow controller

Wink of Knowledge: smart mass flow controller

Discover the future of precise gas flow control with the innovative Smart Mass Flow Controller from TrueDyne Sensors AG. In cooperation with IST AG, we have developed a pioneering device capable of measuring density, temperature, pressure and mass flow – all in one sensor. Designed for flexibility and accuracy, this controller automatically adapts to different pure gases and binary gas mixtures, ensuring optimal performance. Learn more about this groundbreaking solution at TrueDyne Sensors AG.

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Article: In-line measurements of the physical and thermodynamic properties of single and multicomponent liquids

Article: In-line measurements of the physical and thermodynamic properties of single and multicomponent liquids

Microfluidic devices are becoming increasingly important in various fields of pharmacy, flow chemistry and healthcare. In the embedded microchannel, the flow rates, the dynamic viscosity of the transported liquids and the fluid dynamic properties play an important role. Various functional auxiliary components of microfluidic devices such as flow restrictors, valves and flow meters need to be characterised with liquids used in several microfluidic applications.

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Wink of Knowledge: Measurement of the hydrogen peroxide concentration in water with <0.025% measurement uncertainty

Wink of Knowledge: Measurement of the hydrogen peroxide concentration in water with <0.025% measurement uncertainty

Wink of Knowledge: Measurement of the hydrogen peroxide concentration in water with <0.025% measurement uncertainty

Why this test?

Hydrogen peroxide is used in areas such as medicine, the food industry, pharmaceutical technology and biology for the decontamination and sterilisation of all surfaces. Applications on the human body, e.g. for disinfection, are also widespread. In order to be effective on the one hand, but to avoid showing any undesirable side effects on the other, the hydrogen peroxide must be present in the right concentration. Correct dosing is rendered complicated by the spontaneous decomposition of hydrogen peroxide in water + oxygen. To ensure that the hydrogen peroxide is always present in the desired concentration, continuous measurement is recommended. Density can be used as a measurand for determining the concentration of aqueous hydrogen peroxide solutions, and this Wink of Knowledge is therefore concerned with the extent to which this measurement can be accurately achieved under typical conditions.

What is a Wink of Knowledge?

Do you need to quickly measure, draw or do/build something? The speed with which the result may be achieved counts more than the perfect (scientific) approach. For this reason, we have introduced the Wink of Knowledge. Science in the wink of an eye, so to speak. We don’t want to prove anything scientifically. We simply want to quickly demonstrate something pragmatically. If you are interested, we would be happy to discuss these results in more detail with you and your project.

Results

The achievable measurement accuracy of the VLO-M2 was put to the test by comparing its density measurements to those of a laboratory instrument. In the case of (nominal) hydrogen peroxide concentrations between 0% and 6%, the following measurements were performed using the VLO-M2 and the laboratory instrument DSA 5000 M (Anton Paar) :

Density measurement [kg/m 3 ]
Concentration [w/w%] DSA 5000 M VLO-M2 Difference
6.00% 1017.068 1017.045 -0.023
0.547% 998.849 998.889 0.040
0.059% 997.168 997.183 0.015
0.030% 996.890 996.872 -0.018
0% 996.840 996.879 0.039

 

The difference between the laboratory unit and the VLO-M was 2 < 0.05 kg/m 3 over the entire concentration range. This is far below the VLO-M2’s specified measurement error of ±  0.2 kg/m 3 and closer to the specified measurement error of the laboratory instrument of ±0.007 kg/m3, as can be seen quite clearly in the following graphic :

Converted to the density difference of 20.23 kg/m 3 between the 6% stock solution and deionised water, the maximum measured deviation of ±0. 04 kg/m 3 corresponds to an uncertainty in the concentration of <0.025% (250ppm) or < 0.0125% (125ppm). Although in reality, the dependence between concentration and density is not linear, this value provides a good indication.

Finally, the measured density difference between the measured hydrogen peroxide solutions and the theoretical value of pure water (according to REFPROP, NIST) is once again shown here graphically:

An almost identical offset to the reference value can be observed with both measuring methods, with pure deionised water and the lowest concentration of 0.03% H2O2. Possibleexplanations could include a rapid decay of H2O2 at very low concentrations or a weak influence of H2O2 on the density in this range. If the density were to increase in linear fashion, the laboratory instrument, at least, should be able to resolve the density difference between 0% and 0.03% without any problems, with the result that a measurement error would appear unlikely.

However, a clear increase in density is then observed with both instruments when the H2O2 concentration is doubled to 0.059% (note the logarithmic scales). Here, correspondence between the measurements is also excellent, which speaks for the measurement accuracy of the VLO-M2

Which sensors were used?

Density sensor VLO-M2

  • Click here to learn more about our sensor.

Procedure

The VLO-M2 and the laboratory instrument DSA 5000 M (Anton Paar) were used to measure the densities of a hydrogen peroxide stock solution of 6% as well as the dilutions thereof, which consisted of 0.547%, 0.059%, 0.030% and 0% hydrogen peroxide in deionised water . Concentrations of <0.1% were volumetrically created and density to percentages by weight recalculated, and the higher concentration was weighed in directly. The measurements on the two devices took place simultaneously. The temperature on the laboratory unit was adjusted to the temperature in the VLO-M2 in order, to permit a direct comparison (25.2 – 25.7°C ). The VLO-M2 does not have active temperature stabilisation like the laboratory measuring device, and so the available data was averaged in a temperature window of ± 0.02°C and used accordingly.

Summary

This test answers the question regarding the measurement accuracy of the VLO-M2 with aqueous hydrogen peroxide solutions from 0% – 6% under ambient conditions : The measurement error was < 0.05 kg/m 3 when we performed our test. This is far below the specified ± 0.2 kg/m 3 for the VLO-M2 . Since the specification at extreme temperatures, from -40 °C to 6 0 °C and in the entire density ranges from 0 kg/m 3 up to 1200 kg/m 3 must be complied with , the measurement error with aqueous solutions and temperatures close to room temperature can be many times smaller, as shown here . The measured errors (<0.025%) correspond approximately to an accuracy of 250 ppm for the determination of the concentration of H2O2 in water which, in the case of many applications of this mixture, is more than sufficient .

 

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Winkle of Knowledge: Concentration measurement protein

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Winkle of Knowledge: Concentration measurement protein This knowledge wink is dedicated to measuring the concentration of protein in water using the physical parameters of density and viscosity. Commercially available whey protein was used as an example, the...

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Wink of Knowledge: Improved methanol/water concentration model for fuel cells

Wink of Knowledge: Improved methanol/water concentration model for fuel cells

A new concentration model for methanol / water mixtures is shown. The model covers a wide range of process conditions: At temperatures of 0-80°C, concentrations of 0-100% can be calculated from the density with an accuracy of ± 0.2%. The direct methanol fuel cell (DMFC) is an important application for this as the power source of the future.

read more
Wink of Knowledge: smart mass flow controller

Wink of Knowledge: smart mass flow controller

Discover the future of precise gas flow control with the innovative Smart Mass Flow Controller from TrueDyne Sensors AG. In cooperation with IST AG, we have developed a pioneering device capable of measuring density, temperature, pressure and mass flow – all in one sensor. Designed for flexibility and accuracy, this controller automatically adapts to different pure gases and binary gas mixtures, ensuring optimal performance. Learn more about this groundbreaking solution at TrueDyne Sensors AG.

read more
Article: In-line measurements of the physical and thermodynamic properties of single and multicomponent liquids

Article: In-line measurements of the physical and thermodynamic properties of single and multicomponent liquids

Microfluidic devices are becoming increasingly important in various fields of pharmacy, flow chemistry and healthcare. In the embedded microchannel, the flow rates, the dynamic viscosity of the transported liquids and the fluid dynamic properties play an important role. Various functional auxiliary components of microfluidic devices such as flow restrictors, valves and flow meters need to be characterised with liquids used in several microfluidic applications.

read more

Article: In-line measurements of the physical and thermodynamic properties of single and multicomponent liquids

Article: In-line measurements of the physical and thermodynamic properties of single and multicomponent liquids

In-line measurements of the physical and thermodynamic properties of single and multicomponent liquids

Authors: Hugo Bissig, Oliver Büker, Emmelyn Graham, Leslie Wales, Andreia Furtado, Sara Moura, Zoe Metaxiotou, Seok Hwan Lee, Sabrina Kartmann, Jarno Groenesteijn and Joost C. Lötters

Abstract

Microfluidic devices are becoming increasingly important in various fields of pharmacy, flow chemistry and healthcare. In the embedded microchannel, the flow rates, the dynamic viscosity of the transported liquids and the fluid dynamic properties play an important role. Various functional auxiliary components of microfluidic devices such as flow restrictors, valves and flow meters need to be characterised with liquids used in several microfluidic applications. However, calibration with water does not always reflect the behaviour of the liquids used in the different applications. Therefore, several National Metrology Institutes (NMI) have developed micro-pipe viscometers for traceable inline measurement of the dynamic viscosity of liquids used in flow applications as part of the EMPIR 18HLT08 MeDDII project. These micro-pipe viscometers allow the calibration of any flow device at different flow rates and the calibration of the dynamic viscosity of the liquid or liquid mixture used under actual flow conditions. The validation of the micro-pipe viscometers has been performed either with traceable reference oils or with different liquids typically administered in hospitals, such as saline and/or glucose solutions or even glycerol-water mixtures for higher dynamic viscosities. Furthermore, measurement results of a commercially available device and a technology demonstrator for the inline measurement of dynamic viscosity and density are presented in this paper.

Published by
De Gruyter

Publishing date
10. November 2022

Link to the document

(nur in Englisch verfügbar)

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Article: In-line measurements of the physical and thermodynamic properties of single and multicomponent liquids

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Microfluidic devices are becoming increasingly important in various fields of pharmacy, flow chemistry and healthcare. In the embedded microchannel, the flow rates, the dynamic viscosity of the transported liquids and the fluid dynamic properties play an important role. Various functional auxiliary components of microfluidic devices such as flow restrictors, valves and flow meters need to be characterised with liquids used in several microfluidic applications.

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Monitoring of fuel concentrations
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Wink of Knowledge: Thermal flow measurement and correction by means of gas detection

Wink of Knowledge: Thermal flow measurement and correction by means of gas detection

Wink of Knowledge: Thermal flow measurement and correction by means of gas detection

Why this test?

Calorimetric flow sensors are typically adjusted to a specific medium, as the measured value is influenced by the thermal conductivity and capacity of the gas. Thus, a specially calibrated sensor is required for each gas. In combination with a density measurement for clean gas detection or concentration determination of binary gas mixtures, calibration data and correction factors can be assigned flexibly and while the process is running. This means that the correct flow value is calculated at all times, regardless of the clean gas or mixing ratio of the mixture, and only one sensor solution is required for this measuring point.

What is a wink of knowledge?

Do you need to quickly measure, draw or do something? The speed to the result counts more than the perfect (scientific) approach. For this reason, we have introduced the wink of knowledge. Science with a wink, so to speak. We don’t want to prove anything scientifically, but quickly demonstrate something pragmatically. If you are interested, we would be happy to discuss these results in more detail with you and your project.

Results

In Figure 1, the raw flow values are plotted in blue on the right-hand axis and the corrected volume flow in orange on the left-hand axis. The blue linear fit clearly shows how the different thermal parameters of CO2 and N2 falsify the determined measured value without density or concentration correction. However, by adding an inline density measurement, the flow can be corrected to within approx. 2% of the set 100 sccm, as shown by the orange linear fit. It has thus been demonstrated that the combination of the TrueDyne density sensor DGF-I1 and the IST flow sensor SFS01 can accurately determine the flow velocity regardless of the concentration ratios of the binary gas mixture.

In addition to binary gas mixtures of known gas components, this principle can also be extended to switching between gases with different densities. Using a clean gas detection system, it is thus possible to select the appropriate calibration data or correction factors and correct the measured value in real time. This makes it possible to realise a flexible, price-performance-optimised flow measurement with all the advantages of the thermal measuring principle:

  • Long-term stable and vibration-resistant measurement
  • Compact design
  • Suitable for process control, thanks to particularly fast response times (<10 msec.)
  • High sensitivity from the lowest flow velocities including direction detection
  • Clean gas detection
  • Multi-parametric measuring system (flow, density, pressure, temperature)
  • Microleakage monitoring
DLO Sensor - Tetrachloroethene - Measurement results
Figure 1: Comparison between corrected and raw flow rate

Experimental setup

Figure 2 shows the setup of the experimental station. The desired flow rate value for various pure gases and gas mixtures was set using thermal mass flow controllers (MFC 1-5) connected in parallel. The mass flow controllers are each calibrated to the corresponding clean gas, which means that the mixing ratio can be precisely controlled. The gas mixture then flows through the two density and flow sensors connected in series.

The I2C measurement signal from the flow sensor is transmitted directly to the gas density sensor, which uses the measured density and the concentration derived from it to calculate the raw value with a correction factor. The resulting flow measured value can now be compared with the set target value of the gas mixers to verify the functionality of the prototype.

 

Figure 2: Experimental setup

Which sensors were used?

Density sensor DGF-i1

  • Click here to learn more about our sensor.

Flow sensor SFS01

  • Click here to learn more about the flow sensor from IST AG.

Procedure

The density measurement, on which the clean gas detection and concentration determination is based, was carried out with the DGF-I1 density sensor for gases from TrueDyne. The gas flow and its direction were determined using the SFS01 Evalkit thermal flow sensor from Innovative Sensor Technology (IST AG).

Two external thermal mass flow controllers (MFC) were used to set several concentrations of a binary gas mixture of CO2 and N2 and to constantly flow through the sensors. Using the logging function, three readings per second were recorded for the following parameters: concentration, flow rate raw value and corrected flow rate.

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to mass (kg)
Monitoring of welding gas mixtures
Monitoring of gas mixtures for food packaging

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Winkle of Knowledge: Concentration measurement protein

Winkle of Knowledge: Concentration measurement protein

Winkle of Knowledge: Concentration measurement protein This knowledge wink is dedicated to measuring the concentration of protein in water using the physical parameters of density and viscosity. Commercially available whey protein was used as an example, the...

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Wink of Knowledge: Improved methanol/water concentration model for fuel cells

Wink of Knowledge: Improved methanol/water concentration model for fuel cells

A new concentration model for methanol / water mixtures is shown. The model covers a wide range of process conditions: At temperatures of 0-80°C, concentrations of 0-100% can be calculated from the density with an accuracy of ± 0.2%. The direct methanol fuel cell (DMFC) is an important application for this as the power source of the future.

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Wink of Knowledge: smart mass flow controller

Wink of Knowledge: smart mass flow controller

Discover the future of precise gas flow control with the innovative Smart Mass Flow Controller from TrueDyne Sensors AG. In cooperation with IST AG, we have developed a pioneering device capable of measuring density, temperature, pressure and mass flow – all in one sensor. Designed for flexibility and accuracy, this controller automatically adapts to different pure gases and binary gas mixtures, ensuring optimal performance. Learn more about this groundbreaking solution at TrueDyne Sensors AG.

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Article: In-line measurements of the physical and thermodynamic properties of single and multicomponent liquids

Article: In-line measurements of the physical and thermodynamic properties of single and multicomponent liquids

Microfluidic devices are becoming increasingly important in various fields of pharmacy, flow chemistry and healthcare. In the embedded microchannel, the flow rates, the dynamic viscosity of the transported liquids and the fluid dynamic properties play an important role. Various functional auxiliary components of microfluidic devices such as flow restrictors, valves and flow meters need to be characterised with liquids used in several microfluidic applications.

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