Conductivity as alternative measurement for WWTP inflow dynamics – MyronLMeters.com

Tweet Myron L Meters Myron L Meters sells the most accurate, reliable conductivity instruments in the water treatment industry.  You can find some of our most popular meters here: http://www.myronlmeters.com/SearchResults.asp?Search=conductivity&x=-1345&y=-145 Introduction Along with the development of  more and more complex integrated models for urban water systems the need of sufficient  data  bases grows as well. [...]

This poster presents a method regarding the possibility of substituting an online ammonia measurement by conductivity measurements in the inflow of a Waste Water Treatment Plant . The aim was the description of the dynamics in wet weather flow through storm water events for modelling purposes.

The conductivity of an aqueous solution is the measure of its ability to conduct electricity. Responsible for that phenomenon are ions of dissolved salts. In natural and drinking water these are mainly carbonates, chlorides and sulphates of calcium, magnesium, sodium and potassium. Conducted experiences and measurements in combined sewers showed a relation between conductivity in Waste Water Treatment Plant inflow and the concentration of dissolved components, e.g. ammonia, in case of rainfall events. The data for different 3 Waste Water Treatment Plant are shown in Figure 1. Rainwater has nearly no ions that cause conductivity to be measured. Therefore, diluted wastewater flowing into the Waste Water Treatment Plant can be detected by a conductivity probe. The measure and quality of linear regression between ammonia concentration and conductivity can be found in Table 1 for all data from Figure 1.

Material and Methods

With this knowledge a simple regression-based inflow model for use in activated sludge modelling of Waste Water Treatment Plant was defined to use conductivity beside available composite samples as a measure for dynamics in ammonia concentration as one of the most dynamic measure.

Results and Discussion

For one of the considered Waste Water Treatment Plants (WWTP) the resulting quality for the inflow model is shown in Figure 2 for a time series of a week.

Furthermore, the inflow model was used as a source for a retention tank model at the inlet of another Waste Water Treatment Plant to describe the impact of different management strategies (storage or flow through) on receiving water and Waste Water Treatment Plant (Figure 3).

A long-term modelling of 9 storm water events was used to show the predictive capacity of the model. The regression parameters were fitted by an optimisation routine to get best fit for all concentrations (also for COD, not presented here). Figure 3 shows the fit for all events. A good prediction of dynamics and absolute values for ammonia can be seen.

The results of different Goodness-of-fit measures are summarized in Table 2 for both presented WWTP inflows. Especially the values for the modified Coefficient of Efficiency, as a well-known and used measure for model quality in hydrological sciences, show the degree of predicting of the used method and the usability of conductivity for description of influent dynamics to Waste Water Treatment Plant in storm water cases.

 Conclusions

This simple and easy-to-use method is well suited for implementation in Waste Water Treatment Plant models to describe the inflow dynamics regarding a more realistic behavior e.g. for optimization of process control.

by Markus Ahnert*, Norbert Günther*, Volker Kuehn*, University of Dresden 

References
Ahnert, M., Blumensaat, F., Langergraber, G., Alex, J., Woerner, D., Frehmann, T., Halft, N., Hobus, I., Plattes, M., Spering, V. und Winkler, S. (2007), Goodness-of-fit measures for numerical modelling in urban water management – a summary to support practical applications., paper presented at 10th IWA Specialised Conference on “Design, Operation and Economics of Large Wastewater Treatment Plants”, 9-13 September 2007, Vienna, Austria, 9-13 September 2007.

Nash, J. E. und Sutcliffe, J. V. (1970), River flow forecasting through conceptual models part I – A discussion of principles, Journal of Hydrology, 10, 282.

The thermal conductivity enhancement of nanofluids – MyronLMeters.com

TweetThe thermal conductivity enhancement of nanofluids  Abstract Increasing interests have been paid to nanofluids because of the intriguing heat transfer enhancement performances presented by this kind of promising heat transfer media. We produced a series of nanofluids and measured their thermal conductivities. In this article, we discussed the measurements and the enhancements of the thermal [...]

The thermal conductivity enhancement of nanofluids

 Abstract

Increasing interests have been paid to nanofluids because of the intriguing heat transfer enhancement performances presented by this kind of promising heat transfer media. We produced a series of nanofluids and measured their thermal conductivities. In this article, we discussed the measurements and the enhancements of the thermal conductivity of a variety of nanofluids. The base fluids used included those that are most employed heat transfer fluids, such as deionized water (DW), ethylene glycol (EG), glycerol, silicone oil, and the binary mixture of DW and EG. Various nanoparticles (NPs) involving Al₂O₃ NPs with different sizes, SiC NPs with different shapes, MgO NPs, ZnO NPs, SiO₂ NPs, Fe₃O₄ NPs, TiO₂ NPs, diamond NPs, and carbon nanotubes with different pretreatments were used as additives. Our findings demonstrated that the thermal conductivity enhancements of nanofluids could be influenced by multi-faceted factors including the volume fraction of the dispersed NPs, the tested temperature, the thermal conductivity of the base fluid, the size of the dispersed NPs, the pretreatment process, and the additives of the fluids. The thermal transport mechanisms in nanofluids were further discussed, and the promising approaches for optimizing the thermal conductivity of nanofluids have been proposed.

More efficient heat transfer systems are increasingly preferred because of the accelerating miniaturization, on the one hand, and the ever-increasing heat flux, on the other. In many industrial processes, including power generation, chemical processes, heating or cooling processes, and microelectronics, heat transfer fluids such as water, mineral oil, and ethylene glycol always play vital roles. The poor heat transfer properties of these common fluids compared to most solids is a primary obstacle to the high compactness and effectiveness of heat exchangers[1]. An innovative way of improving the thermal conductivities of working media is to suspend ultrafine metallic or nonmetallic solid powders in traditional fluids since the thermal conductivities of most solid materials are higher than those of liquids. A novel kind of heat transfer enhancement fluid, the so-called nanofluid, has been proposed to meet the demands [2].

“Nanofluid” is an eye-catching word in the heat transfer community nowadays. The thermal properties, including thermal conductivity, viscosity, specific heat, convective heat transfer coefficient, and critical heat flux have been studied extensively. Several elaborate and comprehensive review articles and books have addressed thermal transport properties of nanofluids [1,3-6]. Among all these properties, thermal conductivity is the first referred one, and it is believed to be the most important parameter responsible for the enhanced heat transfer. Investigations on the thermal conductivity of nanofluids have been drawing the greatest attention of the researchers. A variety of physical and chemical factors, including the volume fraction, the size, the shape, and the species of the nanoparticles (NPs), pH value and temperature of the fluids, the Brownian motion of the NPs, and the aggregation of the NPs, have been proposed to play their respective roles on the heat transfer characteristics of nanofluids [7-19]. Extensive efforts have been made to improve the thermal conductivity of nanofluids [7-19] and to elucidate the thermal transport mechanisms in nanofluids [20-23].

The authors have carried out a series of studies on the heat transfer enhancement performance of nanofluids. A variety of nanofluids have been produced by the one- or two-step method. The base fluids used include deionized water (DW), ethylene glycol (EG), glycerol, silicone oil, and the binary mixture of DW and EG (DW-EG). Al₂O₃ NPs with different sizes, SiC NPs with different shapes, MgO NPs, ZnO NPs, SiO₂ NPs, Fe₃O₄ NPs, TiO₂ NPs, diamond NPs (DNPs), and carbon nanotubes (CNTs) with different pretreatments have been used as additives. The thermal conductivities of these nanofluids have been measured by transient hot wire (THW) method or short hot wire (SHW) technique. In this article, the experimental results that elucidate the influencing factors for thermal conductivity enhancement of nanofluids are presented. The thermal transport mechanisms in nanofluids and promising approaches for optimizing the thermal conductivity of nanofluids are further presented.

Two techniques have been applied to prepare nanofluids in our studies: two- and one-step techniques. Most of the studied nanofluids were prepared by the two-step technique. During the procedure of two-step technique, the dispersed NPs were prepared by chemical or physical methods first, and then the NPs were added into a specified base fluid, with or without pretreatment and surfactant based on the need. In the preparation of nanofluids containing metallic NPs, one-step technique was employed.

The process was quite simple in the preparation of nanofluids containing oxide NPs like Al₂O₃, ZnO, MgO, TiO₂, and SiO₂ NPs. The NPs were obtained commercially and were dispersed into a base fluid in a mixing container. The NPs were deagglomerated by intensive ultrasonication after being mixed with the base fluid, and then the suspensions were homogenized by magnetic force agitation.

Two-step method was used to prepare graphene nanofluids. The first step was to prepare graphene nanosheets. Functionalized graphene was gained through a modified Hummers method as described elsewhere [24]. Graphene nanosheets were obtained by exfoliation of graphite in anhydrous ethanol. The product was a loose brown powder, and it had good hydrophilic nature. The graphene nanosheets could be dispersed well in polar solvents, like DW and EG, without the use of surfactant. For liquid paraffin (LP)-based nanofluid, oleylamine was used as the surfactant. The fixed quality of graphene nanosheets with different volume fractions was dispersed in the base fluids.

Severe aggregation always takes place in the as-prepared CNTs (pristine CNTs: PCNTs) because of the non-reactive surfaces, intrinsic Von der Waals forces, and very large specific surface areas, and aspect ratios [25]. In CNT nanofluid preparations, surfactant addition is an effective way to enhance the dispersibility of CNTs [26-28]. However, surfactant molecules attaching on the surfaces of CNTs may enlarge the thermal resistance between the CNTs and the base fluid [29], which limits the enhancement of the effective thermal conductivity. The steps involved in the preparation of surfactant-free CNT nanofluids include (1) disentangling the nanotube entanglement and introducing hydrophilic functional groups on the surfaces of the nanotubes by chemical treatments; (2) cutting the treated CNTs (TCNTs) to optimal length by ball milling; and (3) dispersing the treated and cut CNTs into base fluids. CNTs including single-walled CNTs (SWNTs), double-walled CNTs (DWNTs), and multi-walled CNTs (MWNTs) were obtained commercially. Two chemical routes for treating CNTs were used for this study. One is oxidation with concentrated acid, and the other is mechanochemical reaction with potassium hydroxide (KOH). The detailed treatment processes have been described elsewhere [8,30].

Phase transfer method was used to prepare stable kerosene-based Fe₃O₄ magnetic nanofluid. The first step is to synthesize Fe₃O₄ NPs in water by coprecipitation. Oleic acid was added to modify the NPs. When kerosene is added to the mixture with slow stirring, the phase transfer process took place spontaneously. There was a distinct phase interface between the aqueous and kerosene. After the removal of the aqueous phase using a pipette, the kerosene-based Fe₃O₄ nanofluid was obtained [31].

Nanofluids containing copper NPs were prepared using direct chemical reduction method. Stable nanofluids were obtained with the addition of poly(vinylpyrrolidone) (PVP). The diameters of copper NPs prepared by chemical reduction procedure are in the range of 5-10 nm, and copper NPs disperse well with no clear aggregation [32].

Surface modification is always used to enhance the dispersibility of NPs in the preparation of nanofluids. For example, diamond NPs (DNPs) were purified and surface modified by acid mixtures of perchloric acid, nitric acid and hydrochloric acid according to the literature [33] before being dispersed into the base fluids. SiC NPs were heated in air to remove the excess free carbon and their surfaces modified to enhance their dispersibility.

Inconsistent experimental results and controversial arguments arise unceasingly from different groups conducting research on nanofluids, indicating the complexity of the thermal transport in nanofluids. Through an investigation, a large degree of randomness and scatter have been observed in the experimental data published in the open literature. Given the inconsistency in the data, it is impossible to develop a convincing and comprehensive physical-based model that can predict all the trends. To clarify the suspicion on the scattered and wide-ranging experimental results of the thermal conductivity obtained by different groups, it is preferred to screen the measurement technique and procedure to guarantee the accuracy of the obtained results.

Several researchers observed the “time-dependent characteristic” of thermal conductivity [34-36], that is to say, thermal conductivity was the highest right after nanofluid preparation, and then it decreased considerably with elapsed time. We believe that the “time-dependent characteristic” does not represent the essence of thermal conduction capability of nanofluids. The following two factors may account for this phenomenon. The first one is the motion of the remained particle caused by the agitation during the nanofluid preparation. To make a nanofluid homogeneous and long-term stable, it is always subjected to intensive agitation including magnetic stirring and sonication to destroy the aggregation of the suspended NPs. In very short time after nanofluid preparation, the NPs still keep moving in the base fluid (different from Brownian motion). The motion of the remained particle would cause convection and enhance the energy transport in the nanofluids. Second, when a nanofluid is subjected to long-time sonication, its temperature would be increased. The temperature goes down gradually to the surrounding temperature (thermal conductivity measurement temperature). In very short time after the sonication stops, the process has been remaining. Although the temperature decrease is not severe, the thermal conductivity obtained is very sensitive to the temperature decrease when the transient hot-wire technique is used to measured the thermal conductivity. In our measurements, this phenomenon would be observed. When measuring the thermal conductivity at an unequilibrium state, it was found that the measured data might be very different for a nanofluid even at a specific temperature (see 25°C) if the process to reach this temperature is different. If the temperature is increasing, then the datum obtained of the thermal conductivity would be lower than the true value. While the temperature is decreasing, the datum obtained of the thermal conductivity would be higher than the true value. Therefore, keeping a nanofluid stable and initial equilibrium is very important to obtain accurate thermal conductivity data in measurements.

A transient short hot-wire method was used to measure the thermal conductivities of the base fluids (k₀) and the nanofluids (k). The detailed measurement principle, procedure, and error analysis have been described in [37]. In our measurements, a platinum wire with a diameter of 50 μm was used for the hot wire, and it served both as a heating unit and as an electrical resistance thermometer. The platinum wire was coated with an insulation layer of 7-μm thickness. Initially the platinum wire immersed in media was kept at equilibrium with the surroundings. When a regulation voltage was supplied to initiate the measurement, the electrical resistance of the wire changed proportionally with the rise in temperature. The thermal conductivity was calculated from the slope of the rise in the wire’s temperature against the logarithmic time interval. The uncertainty of this measurement is estimated to be within ± 1.0%. A temperature-controlled bath was used to maintain different temperatures of the nanofluids. Instead of monitoring the temperature of the bath, a thermocouple was positioned inside the sample to monitor the temperature on the spot. When the temperature of the sample reached a steady value, the authors waited for further 20 min to make sure that the initial state is at equilibrium. At every tested temperature, measurements were made three times and the average values were taken as the final results. A 20-min interval was needed between two successive measurements. After the above-mentioned careful check on the measurement condition and procedure, the authors could gain confidence on the experimental results.

In the experiment of the study, it was found that the thermal conductivity enhancements of nanofluids might be influenced by multi-faceted factors including the volume fraction of the dispersed NPs, the tested temperature, the thermal conductivity of the base fluid, the size of the dispersed NPs, the pretreatment process, and the additives of the fluids. The effects of these factors are presented in this section.

Particle loading

The idea of nanofluid application originated from the fact that the thermal conductivity of a solid is much higher than that of a liquid. For example, the thermal conductivity of the most used conventional heat transfer fluid, water, is about 0.6 W/m · K at room temperature, while that of copper is higher than 400 W/m · K. Therefore, particle loading would be the chief factor that influences the thermal transport in nanofluids. As expected, the thermal conductivities of the nanofluids have been increased over that of the base fluid with the addition of a small amount of NPs. Figure 1 shows the enhanced thermal conductivity ratios of the nanofluids with NPs at different volume fractions [7,8,38-42]. (k - k₀)/k₀ and φ refer to the thermal conductivity enhancement ratio of nanofluids and the volume fraction of NPs, respectively, in this article. Figure1a presents oxide nanofluids, while Figure 1b presents nonoxide nanofluids. The results show that all the nanofluids have noticeable higher thermal conductivities than the base fluid without NPs. In general, the thermal conductivity enhancement increases monotonously with the volume fraction. For the graphene nanofluid with a volume fraction of 0.05, the thermal conductivity can be enhanced by more than 60.0%. There is an approximate linear relationship between the thermal conductivity enhancement ratios and the volume fraction of graphene nanosheets. The nanofluids containing graphene nanosheets show larger thermal conductivity enhancement than those containing oxide NPs. It demonstrates that graphene nanosheet is a good additive to enhance the thermal conductivity of base fluid. However, the enhancement ratios of nanofluids containing graphene nanosheets are less than those of CNTs with the same loading. Many factors have direct influence on the thermal conductivity of the nanofluid. One of the important factors is the crystal structure of the inclusion in the nanofluid. Graphene is a one-atom-thick planar sheet of sp²-bonded carbon atoms that are densely packed in a honeycomb crystal lattice. The perfect structure of graphene is damaged when graphite is chemically oxidized by treatment with strong oxidants. There is no doubt that the high thermal conductivity is diminished by defects, and the defects have direct influence on the heat transport along the 2-D structure.

Figure 1. Thermal conductivity enhancement ratios of the nanofluids as a function of nanoparticle loading. (a) Oxide nanofluids: MgO-EG [38]; Al₂O₃-EG [7]; ZnO-EG [39]; (b) Nonoxide nanofluids: CNT-EG [8]; DNP-EG [40]; Graphene-EG [41]; Cu-EG [42].

Temperature

Some studies have demonstrated that the temperature has a great effect on the enhancement of the thermal conductivity for nanofluids. However, there is considerable disagreement in the literature with respect to the temperature dependence of their thermal conductivity. For example, Das et al. reported strong temperature-depended thermal conductivity for water-based Al₂O₃ and CuO nanofluids [43]. The thermal conductivity enhancements of nanofluids containing Bi₂Te₃nanorods in FC72 and in oil had been experimentally found to decrease with increasing temperature [44]. Micael et al. measured the thermal conductivities of EG-based Al₂O₃ nanofluids at temperatures ranging from 298 to 411 K. A maximum in the thermal conductivity was observed at all mass fractions of NPs [45].

Figure 2 shows our measured temperature-depended thermal conductivity enhancements of nanofluids [8,38-42]. For EG-based nanofluids containing MgO, ZnO, SiO₂, and graphene NPs, the thermal conductivity enhancements almost remain constant when the tested temperature changes (see Figure 2a), which means that the thermal conductivity of the nanofluid tracks the thermal conductivities of the base liquid in the experimented temperature range of this study. The thermal conductivity enhancements of DW-EG-based nanofluids containing MgO, ZnO, SiO₂, Al₂O₃, Fe₂O₃, TiO₂, and graphene NPs also appear to have the same behavior. It was further found that kerosene-based Fe₃O₄ nanofluids presented temperature-independent thermal conductivity enhancements. Patel et al. [46] reported that the thermal conductivity enhancement ratios of Cu nanofluids are enhanced considerably when the temperature increases. The experimental results of this study shown in Figure 2b demonstrated similar tendency. At 10°C, the thermal conductivity enhancement of EG based Cu nanofluid with 0.5% nanoparticle loading is less than 15.0%. When the temperature is increased to 60°C, the enhancement reaches as large as 46.0%. Brownian motion of the NPs has been proposed as the dominant factor for this phenomenon. For the EG-based CNT nanofluids, cylindrical nanotubes with large aspect ratios were used as additions. The effect of Brownian motion will be negligible. Typical conduction-based models will give (k - k₀)/k₀, independent of the temperature. However, results shown in Figure 2b illustrate that (k - k₀)/k₀increases, though not drastically, with the temperature. CNT aggregation kinetics may contribute to the observed differences [21]. It is worthy of bearing in mind that the temperatures of the base fluid and the nanofluid should be the same when compared with the thermal conductivities between them. Comparison of the thermal conductivities between the nanofluid at one temperature and the base at another one is meaningless.

Figure 2. Thermal conductivity enhancement varying with the tested temperatures. (a) Oxide nanofluids: MgO-EG [38]; ZnO-EG[39]; Graphene-EG [41]; (b) Nonoxide nanofluids: Cu-EG [42]; CNT-EG[8]; DNP-EG [40].

Base fluid

Figure 3 shows the relation between the enhanced thermal conductivity ratios of the nanofluids and the thermal conductivities of the base fluids [7,8,40,41]. It is clearly seen that no matter what kind of nanoparticle was used, the thermal conductivity enhancement decreases with an increase in the thermal conductivity of the base fluid. For pump oil (PO)-based Al₂O₃ nanofluid with 5.0% nanoparticle loading, the thermal conductivity can be enhanced by more than 38% compared to that of PO. When the base fluid is substituted with water, the thermal conductivity enhancement achieved is only about 22.0% [7]. A greater dramatic improvement in thermal conductivity of CNT nanofluid is seen for a base fluid with lower thermal conductivity. At 1.0% nanoparticle loading, the thermal conductivity enhancements are 19.6, 12.7, and 7.0% for CNT nanofluids in decene, EG, and DW, respectively. No matter what kind of base fluid is used, the thermal conductivity enhancement of CNT nanofluids is much higher than that for Al₂O₃ nanoparticle suspensions [8] at the same volume fraction. The reason would lie in the substantial difference in thermal conductivity and morphology between alumina nanoparticle and carbon nanotube.

Figure 3. Thermal conductivity enhancement ratios as a function of the thermal conductivities of the base fluids: Al2O3 NFs [7]; CNT NFs [8]; Graphene NFs [41]; DNP NFs [40].

Particle size

Figure 4 presents the thermal conductivity enhancement of the nanofluids as a function of the specific surface area (SSA) of the suspended particles [7]. It is seen that the thermal conductivity enhancement increases first, and then decreases with an increase in the SSA, with the largest thermal conductivity at a particle SSA of 25 m² · g^-1. We ascribe the thermal conductivity change behavior to twofold factors. First, as particle size decreases, the SSA of the particle increases proportionally. Heat transfer between the particle and the fluid takes place at the particle-fluid interface. Therefore, a dramatic enhancement in thermal conductivity is expected because a reduction in particle size can result in large interfacial area. Second, the mean free path in polycrystalline Al₂O₃ is estimated to be around 35 nm, which is comparable to the size of the particle that was used. The intrinsic thermal conductivity of nanosized Al₂O₃ particle may be reduced compared to that of bulk Al₂O₃ due to the scattering of the primary carriers of energy (phonon) at the particle boundary. It is expected that the suspension’s thermal conductivity is reduced with an increase in the SSA. Therefore, for a suspension containing NPs at a particle size much different from the mean free path, the thermal conductivity increases when the particle size decreases because the first factor is dominant. However, when the size of the dispersed NPs is close to or smaller than the mean free path, the second factor will govern the mechanism of the thermal conductivity behavior of the suspension.

Figure 4. Enhanced thermal conductivity ratios as a function of the SSAs: Al2O3-EG [7]; Al2O3-PO [7].

Figure 5 depicts the thermal conductivity enhancements of nanofluids containing CNTs with different sizes [47]. The base fluid is DW, and the volume fraction of the CNTs is 0.0054. It is observed from Figure 5 that the thermal conductivity enhancements show differences among these three kinds of nanofluids containing SWNTs, DWNTs, and MWNTs as the volume fraction of CNTs is the same. Two influencing factors may be addressed. The first one is the intrinsic heat transfer performance of the CNTs. It is reported that the thermal conductivity of CNTs decreases with an increase in the number of the nanotube layer. The tendency of the thermal conductivity enhancement of the obtained CNT nanofluids accords with that of the heat transfer performance of the three kinds of CNTs. The second one is the alignment of the liquid molecules on the surface of CNTs. There are greater number of water molecules close to the surfaces of CNTs with smaller diameter due to the larger SSA if the volume fractions of CNTs are the same. These water molecules can form an interfacial layer structure on the CNT surfaces, increasing the thermal conductivity of the nanofluid [47].

Figure 5. Thermal conductivity enhancements of nanofluids containing CNTs with different sizes: SWNT-DW [47]; DWNT-DW[47]; MWNT-DW [47].

Pretreatment

In the preparation of nanofluids, solid additives are always subjected to various pretreatment procedures. The initial incentive is to tailor the surfaces of the NPs to enhance their dispersibility, thereby to enhance the stability of the nanofluids. The morphologies would be significantly changed when CNTs were subjected to chemical or mechanical treatments. Theoretical research into the thermal conductivity of composites containing cylindrical inclusions has demonstrated that the morphologies, including the aspect ratio, have influence on the effective thermal conductivity of the composites. Therefore, it can be expected that the thermal conductivity of CNT contained nanofluids would be affected by the pretreatment process.

Figure 6 shows the dependence of the thermal conductivity enhancement on the ball milling time of CNTs suspended in the nanofluids [48]. From theoretical prediction, the thermal conductivity of a composite increases with the aspect ratio of the included solid particles [49-51]. Intuition suggests that increasing the milling time should therefore decrease (k - k₀)/k₀ because of the reduced aspect ratio. Figure 6, however, shows clear peak and valley values in the thermal conductivity enhancement with respect to the milling time for all the studied CNT loadings. For nanofluid at a volume fraction of 0.01, the thermal conductivity enhancements present a peak value of 27.5% and a valley value of 10.4% when the milling times are 10 and 28 h, respectively. The maximal enhancement is intriguingly more than two and half times as the minimal one. Interestingly, when further increased the milling time from 28 to 38 h, (k - k₀)/k₀ increases from the valley value of 10.4 to 12.8%. Though the increment is not pronounced, it illustrates a difference in tendency from that in the milling time range from 10 to 28 h. Temperature-dependent thermal conductivity enhancement data further indicate that, at all the measured temperatures, nanofluid with CNTs milled for 10 h has the largest increment in thermal conductivity. Glory et al. [52] reported that the enhancement of the thermal conductivity noticeably increases when the nanotube aspect ratio increases. However, the thermal conductivity enhancement behavior of our CNT nanofluid is very different and cannot be explained only by the effect of the aspect ratio.

Figure 6. Dependence of the thermal conductivity enhancement on the ball milling time of CNTs suspended in the nanofluids [48].

The above results suggest other dominant factors that have the influence over the thermal conductivity of the CNT nanofluids. The authors proposed that the nonstraightness and the aggregation would play significantly roles. As is known, the walls of CNTs have similar structure of graphene sheet, and the thermal conductivity of CNTs shows greatly anisotropic behavior. Heat transports substantially quicker through axial direction than through radial direction [53]. For a nonstraight CNT, the high thermal anisotropy of CNTs induces a unique property that individual CNTs are nearly perfect one-dimensional thermal passages with negligibly small heat flux losses during long distance heat conductions [54]. For a nonstraight CNT with length L under a two-end temperature difference, the heat flux q goes through a curled passage. This CNT can be regarded as an equivalent straight thermal passage with a distance of L^e. The same heat flux q is conducted between the two ends of this straight passage. Obviously, the equivalent length L^e depends on the curvature of the actual nanotube in the nanofluid. A concept, straightness ratio η (η = L^e/L), can be adopted to describe the straightness of a curled CNT. The lowest straightness ratio arises when a suspended nanotube forms ring closure [55].

When subjected to ball milling, CNTs were broken and cut short with appropriate average length. The straightness ratio was significantly increased and heat transports more effectively through the CNTs and across the interfaces between the CNT tips and the base fluid, resulting in the highest thermal conductivity enhancement in a nanofluid containing CNTs milled for 10 h. For nanofluids containing relatively straight nanotubes, the influence of the aspect ratio will surpass that of straightness ratio. Therefore, by further treatment on nanotubes with relatively high straightness ratio, the excessive deterioration of the aspect ratio would decrease the thermal conductivity of nanofluids, causing (k - k₀)/k₀ decrease from 10 to 28 h. Recent theoretical analysis has revealed that the aggregation of nanoparticle plays a significant role in deciding (k - k₀)/k₀ [21]. Percolation effects in the aggregates, as highly conducting nanotubes touch each other in the aggregate, help in increasing the thermal conductivity. Our experiments demonstrate that aggregates are the dominant appearance of CNTs when the ball-milling time is increased to 38 h. The aggregation accounts for the increment of thermal conductivity enhancement when the ball-milling time is increased from 28 to 38 h. This result implies that the positive influence of the aggregation surpasses the negative influence of the aspect ratio deterioration.

pH value

For some nanofluids, the pH values of the suspensions have direct effects on the thermal conductivity enhancement. Figure 7 presents the thermal conductivity enhancement ratios at different pH values [7,40]. The results show that the enhanced thermal conductivity increases with an increase in the difference between the pH value of aqueous suspension and the isoelectric point of Al₂O₃ particle [7]. When the NPs are dispersed into a base fluid, the overall behavior of the particle-fluid interaction depends on the properties of the particle surface. For Al₂O₃ particles, the isoelectric point (pH_iep) is determined to be 9.2, i.e., the repulsive forces among Al₂O₃ particles is zero, and Al₂O₃ particles will coagulate together under this pH value. Therefore, when pH value is equal or close to 9.2, Al₂O₃ particle suspension is unstable according to DLVO theory [56]. The hydration forces among particles increase with the increasing difference of the pH value of a suspension from the pH_iep, which results in the enhanced mobility of NPs in the suspension. The microscopic motions of the particles cause micro-convection that enhances the heat transport process. Wensel’s study showed that the thermal conductivity of nanofluids containing oxide NPs and CNTs with very low percentage loading decreased when the pH value is shifted from 7 to 11.45 under the influence of a strong outside magnetic field [14].

Figure 7. Thermal conductivity enhancement ratios at different pH values: Al2O3-DW [7]; DNP-EG [40].

For DNP-EG nanofluids, it is observed from Figure 7 that the thermal conductivity enhancement increases with pH values in the range of 7.0-8.0. When pH value is above 8.0, there is no obvious relationship between pH value and the thermal conductivity enhancement. In our opinion, the influence of pH value on thermal conductivity is that pH value has a direct effect on the stability of nanofluids. When pH value is below 8.5, the suspension is not very stable, and DNPs are easy to form aggregations. The alkalinity of the solution is helpful to the dispersion and the stability of the nanofluids. In order to verify the above statement, the influence of settlement time on the thermal conductivity enhancement was further investigated. It is found that the thermal conductivity enhancement decreases with elapsed time for DNP-EG nanofluid when pH is 7.0. However, for the stable DNP-EG nanofluids with pH of 8.5, there is no obvious thermal conductivity decrease for 6 months [40].

Surfactant addition

Surfactant addition is an effective way to enhance the stability of nanofluids. Kim’s study revealed that the thermal conductivity decreased rapidly for the instable nanofluids without surfactants after preparation. However, no obvious changes in the thermal conductivity of the nanofluids with sodium dodecyl sulfate (SDS) as surfactant were observed even after 5-h settlement [57]. Assael et al. investigated the thermal conductivities of the aqueous suspension of CNTs. When Sodium dodecyl sulfate (SDS) was employed as the dispersant, the maximum thermal conductivity enhancement obtained was 38.0% for a nanofluid with 0.6 vol% CNT loadings [58]. When the surfactant is substituted with hexadecyltrimethyl ammonium bromide (CTAB), the maximum thermal conductivity enhancement obtained was 34.0% for same fraction of CNT loading [26]. Liu et al. reported that the thermal conductivity of carbon nanotube-synthetic engine oil suspensions is higher compared with that of same suspensions without the addition of surfactant. The presence of surfactant as stabilizer has positive effect on the carbon nanotube-synthetic engine oil suspensions[59].

We used cationic gemini surfactants (12-3(4,6)-12,2Br^-1) to stabilize water-based MWNT nanofluids. These surfactants were prepared following the process described in [60]. Figure 8presents the thermal conductivity enhancement ratios of the CNT-contained nanofluids with different surfactant concentrations. The volume fraction of the dispersed CNTs is 0.1%. The critical micelle concentration of 12-3-12, 2Br^-1 is reported as 9.6 ± 0.3 × 10^-4 mol/l [61]. Ten times critical micelle concentration of 12-3-12, 2Br^-1 is 0.6 wt%. Solutions of 12-3-12, 2Br^-1 with different concentrations (0.6, 1.8, and 3.6 wt% at room temperature) were selected to prepare CNT nanofluids. It is observed that at all the measured temperatures the thermal conductivity enhancement decreases with the surfactant addition. The surfactant added in the nanofluids acts as stabilizer which improves the stability of the CNT nanofluids. However, excess surfactant addition might hinder the improvement of the thermal conductivity enhancement of the nanofluids.

Figure 8. Thermal conductivity enhancement ratios with different surfactant concentrations.

The effect of the structures of cationic gemini surfactant molecules on the thermal conductivity enhancement is shown in Figure 9. The fractions of the dispersed CNTs and the cationic gemini surfactants is 0.1 vol% and 0.6 wt%, respectively. The spacer chain length of the cationic gemini surfactant increase from 3 methylenes to 6 methylenes. It is seen that the thermal conductivity enhancement ratio increases with the decrease of spacer chain length of cationic gemini surfactant. Zeta potential analysis indicates that the CNT nanofluids stabilized by gemini surfactant with short spacer chain length have better stabilities. Increase of spacer chain length of surfactant might give rise to sediments of CNTs in the nanofluids, resulting in the decrease of thermal conductivity enhancement of the nanofluids.

Figure 9. Effect of surfactant structures on the thermal conductivity enhancement ratio.

Nanofluids have great potential for heat transfer enhancement and are highly suited to application in practical heat transfer processes. This provides promising ways for engineers to develop highly compact and effective heat transfer equipments. More and more researchers have paid their attention to this exciting field. When addressing the thermal conductivity of nanofluids, it is foremost important to guarantee the accuracy in the measurement of the thermal conductivity of nanofluids. Two aspects should be considered. The first one is to prepare homogeneous and long-term stable nanofluids. The second one is to keep the initial equilibrium before measuring the thermal conductivity. In general, the thermal conductivity enhancement increases monotonously with the particle loading. The effect of temperature on the thermal conductivity enhancement ratio is somewhat different for different nanofluids. It is very important to note that the temperatures of the base fluid and the nanofluid should be the same while comparing the thermal conductivities between them. With an increase in the thermal conductivity of the base fluid, the thermal conductivity enhancement ratio decreases. Considering the effect of the size of the inclusion, there exists an optimal value for alumina nanofluids, while for the CNT nanofluid, the thermal conductivity increases with a decrease of the average diameter of the included CNTs. The thermal characteristics of nanofluids might be manipulated by means of controlling the morphology of the inclusions, which also provide a promising way to conduct investigation on the mechanism of heat transfer in nanofluids. The additives like acid, base, or surfactant play considerable roles on the thermal conductivity enhancement of nanofluids.

CNTs: carbon nanotubes; DNPs: diamond NPs; DW: deionized water; DWNTs: double-walled CNTs; EG: ethylene glycol; KOH: potassium hydroxide; LP: liquid paraffin; MWNTs: multi-walled CNTs; NPs: nanoparticles; PVP: poly(vinylpyrrolidone); SDS: sodium dodecyl sulfate; SHW: short hot wire; SSA: specific surface area; SWNTs: single-walled CNTs; THW: transient hot wire; TCNTs: treated CNTs.

The authors declare that they have no competing interests.

HQ supervised and participated all the studies. He wrote this paper. WY carried out the studies on the nanofluids containing copper nanoparticles, graphene, diamond nanoparticles, and several kinds of oxide nanoparticles. YL carried out the studies on the nanofluids containing other oxide nanoparticles. LF carried out the studies on the nanofluids containing carbon nanotubes.

This study was supported by the National Science Foundation of China (50876058), Program for New Century Excellent Talents in University (NCET-10-883), and the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning.

1. Daungthongsuk W, Wongwises S: A critical review of convective heat transfer of nanofluids.

Renewable Sustainable Energy Rev 2007, 11:797. Publisher Full Text

1. Jang S, Choi SUS: Effects of Various parameters on nanofluid thermal conductivity.

J Heat Transf 2007, 129:617-623. Publisher Full Text

1. Yu WH, France DM, Routbort JL, Choi SUS: Review and comparison of nanofluid thermal conductivity and heat transfer enhancements.

Heat Transf Eng 2008, 29:432-460. Publisher Full Text

1. Li Y, Zhou J, Tung S, Schneider E, Xi S: A review on development of nanofluid preparation and characterization.

Powder Technol 2009, 196:89-101. Publisher Full Text

1. Wang L, Fan J: Nanofluids research: key issues.

Nanoscale Res Lett 2010, 5:1241-1252. PubMed Abstract | Publisher Full Text |PubMed Central Full Text

1. Zerinc SÖ, Kakac S, Güvenc A: Enhanced thermal conductivity of nanofluids: a state-of-the-art review.

Microfluid Nanofluid 2010, 8:145-170. Publisher Full Text

1. Xie H, Wang J, Xi T, Ai F: Thermal conductivity enhancement of suspensions containing nanosized alumina particles.

J Appl Phys 2002, 91:4568. Publisher Full Text

1. Xie H, Lee H, Youn W, Choi M: Nanofluids containing multi-walled carbon nanotubes and their enhanced thermal conductivities.

J Appl Phys 2003, 94:4971.

1. Patel HE, Das SK, Sundararajan TA, Nair S, George B, Pradeep T: Thermal conductivity of naked and monolayer protected metal nanoparticles based nanofluids: manifestation of anomalous enhancement and chemical effects.

Appl Phys Lett 2003, 83:2931. Publisher Full Text

1. Wen D, Ding Y: Experimental investigation into the pool boiling heat transfer of γ-alumina nanofluids.

J Nanoparticle Res 2005, 7:265. Publisher Full Text

1. Li CH, Peterson GP: Size effect on the effective thermal conductivity of Al₂O₃/Di water nanofluids.

J Appl Phys 2006, 99:084314. Publisher Full Text

1. Wright B, Thomas D, Hong H, Groven L, Puszynski J, Duke E, Ye X, Jin S: Magnetic field enhanced thermal conductivity in heat transfer nanofluids containing Ni coated single wall carbon nanotubes.

Appl Phys Lett 2007, 91:173116. Publisher Full Text

1. Garg J, Poudel B, Chiesa M, Gordon JB, Ma JJ, Wang JB, Ren ZF, Kang YT, Ohtani H, Nanda J, McKinley GH, Chen G: Enhanced thermal conductivity and viscosity of copper nanoparticles in ethylene glycol nanofluid.

J Appl Phys 2008, 103:074301. Publisher Full Text

1. Wensel , Wright B, Thomas D, Douglas W, Mannhalter B, Cross W, Hong H, Kellar J, Smith P, Roy W: Enhanced thermal conductivity by aggregation in heat transfer nanofluids containing metal oxide nanoparticles and carbon nanotubes.

Appl Phys Lett 2008, 92:023110. Publisher Full Text

1. Xie H, Yu W, Li Y: Thermal performance enhancement in nanofluids containing diamond nanoparticles.

J Phys D 2009, 42:095413. Publisher Full Text

1. Shima PD, Philip J, Raj B: Magnetically controllable nanofluid with tunable thermal conductivity and viscosity.

Appl Phys Lett 2009, 95:133112. Publisher Full Text

1. Yu W, Xie H, Chen W: Experimental investigation on thermal conductivity of nanofluids containing graphene oxide nanosheets.

J Appl Phys 2010, 107:094317. Publisher Full Text

1. Kole M, Dey TK: Thermal conductivity and viscosity of Al₂O₃ nanofluid based on car engine coolant.

J Phys D 2010, 43:315501. Publisher Full Text

1. Yeganeh M, Shahtahmasebi N, Kompany A, Goharshadi EK, Youssefi A, Šiller L: Volume fraction and temperature variations of the effective thermal conductivity of nanodiamond fluids in deionized water.

Int J Heat Mass Transf 2010, 53:3186. Publisher Full Text

1. Prasher R, Bhattacharya P, Phelan PE: Thermal conductivity of nanoscale colloidal solutions (nanofluids).

Phys Rev Lett 2005, 94:025901. PubMed Abstract | Publisher Full Text

1. Prasher R, Phelan PE, Bhattacharya P: Effect of aggregation kinetics on the thermal conductivity of nanoscale colloidal solutions (nanofluid).

Nano Lett 2006, 6:1529. PubMed Abstract | Publisher Full Text

1. Gao JW, Zheng RT, Ohtani H, Zhu DS, Chen G: Experimental investigation of heat conduction mechanisms in nanofluids clue on clustering.

Nano Lett 2009, 9:4128. PubMed Abstract | Publisher Full Text

1. Eapen J, Rusconi R, Piazza R, Yip S: The classical nature of thermal conduction in nanofluids.

J Heat Transf 2009, 132:102402. Publisher Full Text

1. Xu YX, Bai H, Lu GW, Li C, Shi GQ: Flexible graphene films via the filtration of water-soluble noncovalent functionalized graphene sheets.

J Am Chem Soc 2008, 130:5856. PubMed Abstract | Publisher Full Text

1. Park C, Qunaies Z, Watson K, Crooks R, Smith J, Lowther S, Connell J, Siochi E, Harrison J, Clair T: Dispersion of single wall carbon nanotubes by in situ polymerization under sonication.

Chem Phys Lett 2002, 364:303. Publisher Full Text

1. Assael MJ, Metaxa IN, Arvanitidis J, Christofilos D, Lioutas C: Thermal conductivity enhancement in aqueous suspensions of carbon multi-walled and double-walled nanotubes in the presence of two different dispersants.

Int J Thermophys 2005, 26:647. Publisher Full Text

1. Ding Y, Alias H, Wen D, Williams RA: Heat transfer of aqueous suspensions of carbon nanotubes (CNT nanofluids).

Int J Heat Mass Transf 2005, 49:240. Publisher Full Text

1. Wen D, Ding Y: Experimental investigation into convective heat transfer of nanofluids at the entrance region under laminar flow conditions.

Int J Heat Mass Transf 2004, 47:5181. Publisher Full Text

1. Huxtable T, Cahill DG, Shenogin S, Xue LP, Ozisik R, Barone P, Usrey M, Strano MS, Siddons G, Shim M, Keblinski P: Interfacial heat flow in carbon nanotube suspensions.

Nat Mater 2003, 2:731. PubMed Abstract | Publisher Full Text

1. Chen LF, Xie HQ, Li Y, Yu W: Surface chemical modification of multiwalled carbon nanotubes by wet mechanochemical reaction.

J Nanomater 2008, 783981.

1. Yu W, Xie HQ, Chen LF, Li Y: Enhancement of thermal conductivity of kerosene-based magnetic nanofluids prepared via phase-transfer method.

Colloids Surf A 2010, 355:109. Publisher Full Text

1. Yu W, Xie HQ, Chen LF, Li Y, Zhang C: Synthesis and characterization of monodispersed copper colloids in polar solvents.

Nanoscale Res Lett 2009, 4:465. PubMed Abstract | Publisher Full Text |PubMed Central Full Text

1. Jang T, Xu K: FTIR study of ultradispersed diamond powder synthesized by explosive detonation.

Carbon 1995, 33:1663. Publisher Full Text

1. Liu MS, Lin MCC, Tsai CY, Wang CC: Enhancement of thermal conductivity with Cu for nanofluids using chemical reduction method.

Int J Heat Mass Transf 2006, 49:3028. Publisher Full Text

1. Das SJ, Putra N, Roetzel W: Pool boiling characteristics of nanofluids.

Int J Heat Mass Transf 2003, 46:851. Publisher Full Text

1. Hong KS, Hong TK, Yang HS: Thermal conductivity of Fe nanofluids depending on the cluster size of nanoparticles.

Appl Phys Lett 2006, 88:031901. Publisher Full Text

1. Xie HQ, Gu H, Fujii M, Zhang X: Short hot wire technique for measuring thermal conductivity and thermal diffusivity of various materials.

Meas Sci Technol 2006, 17:208. Publisher Full Text

1. Yu W, Xie H, Li Y, Chen L: Investigation of thermal conductivity and viscosity of ethylene glycol based ZnO nanofluid.

Thermochimica Acta 2009, 491:92. Publisher Full Text

1. Xie H, Yu W, Li Y, Chen L: MgO nanofluids: higher thermal conductivity and lower viscosity among ethylene glycol based nanofluids containing oxide nanoparticles.

J Exp Nanosci 2010, 5:463. Publisher Full Text

1. Yu W, Xie H, Li Y, Chen L: Experimental investigation on the thermal transport properties of ethylene glycol based nanofluids containing low volume concentration diamond nanoparticles.

Colloids Surf A

1. Yu W, Xie H, Bao D: Enhanced thermal conductivities of nanofluids containing graphene oxide nanosheets.

Nanotechnology 2010, 21:055705. PubMed Abstract | Publisher Full Text

1. Yu W, Xie H: Investigation on the thermal transport properties of ethylene glycol-based nanofluids containing copper nanoparticles.

Powder Technol 2010, 197:218. Publisher Full Text

1. Das SK, Putra N, Thiesen P, Roetzel W: Temperature dependence of thermal conductivity enhancement for nanofluids.

J Heat Transf 2003, 125:567. Publisher Full Text

1. Yang B, Han ZH: Thermal conductivity enhancement in water-in-FC72 nanoemulsion fluids.

Appl Phys Lett 2006, 89:083111. Publisher Full Text

1. Michael PB, Tongfan S, Amyn ST: The thermal conductivity of alumina nanoparticles dispersed in ethylene glycol.

Fluid Phase Equilibria 2007, 260:275. Publisher Full Text

1. Patel HE, Das SK, Sundararajan TA, Nair S, George B, Pradeep T: Thermal conductivity of naked and monolayer protected metal nanoparticles based nanofluids: manifestation of anomalous enhancement and chemical effects.

Appl Phys Lett 2003, 83:2931. Publisher Full Text

1. Chen LF, Xie HQ: Surfactant-free nanofluids containing double- and single-walled carbon nanotubes functionalized by a wet-mechanochemical reaction.

Thermochimica Acta 2010, 497:67-71. Publisher Full Text

1. Xie HQ, Li Y, Chen LF: Adjustable thermal conductivity in carbon nanotube nanofluids.

Phys Lett A 2009, 373:1861. Publisher Full Text

1. Nan C, Liu G, Lin Y, Li M: Interface effect on thermal conductivity of carbon nanotube composites.

Appl Phys Lett 2004, 85:3549. Publisher Full Text

1. Xue QZ: Model for the effective thermal conductivity of carbon nanotube composites.

Nanotechnology 2006, 17:1655. Publisher Full Text

1. Gao L, Zhou X, Ding Y: Effective thermal and electrical conductivity of carbon nanotube composites.

Chem Phys Lett 2007, 434:297. Publisher Full Text

1. Glory J, Bonetti M, Helezen M, Mayne-L’Hermite M, Reynaud C: Thermal and electrical conductivities of water-based nanofluids prepared with long multiwalled carbon nanotubes.

J Appl Phys 2008, 103:094309. Publisher Full Text

1. Ajayan PM, Terrones M, de la Guardia A, Huc V, Geobert N, Wei BQ, Lezec H, Ramanath G, Ebbesen TW: Nanotubes in a flash-ignition and reconstruction.

Science 2002, 296:705. PubMed Abstract | Publisher Full Text

1. Deng F, Zheng QS, Wang LF, Nan CW: Effects of anisotropy, aspect ratio, and nonstraightness of carbon nanotubes on thermal conductivity of carbon nanotube composites.

Appl Phys Lett 2007, 90:021914. Publisher Full Text

1. Sano M, Kamino A, Okamura J, Shinkai S: Ring closure of carbon nanotubes.

Science 2001, 293:1299. PubMed Abstract | Publisher Full Text

1. Russel WB, Saville DA, Schowwalter WR: Colloidal Suspensions. Cambridge, UK: Cambridge University Press; 1989.
2. Kim SH, Choi SR, Kim DS: Thermal conductivity of metal-oxide nanofluids: particle size dependence and effect of laser irradiation.

J Heat Transf 2007, 129:298. Publisher Full Text

1. Assael MJ, Chen CF, Metaxa I, Wakeham WA: Thermal conductivity of suspensions of carbon nanotubes in water.

Int J Thermophys 2004, 25:971. Publisher Full Text

1. Liu MS, Lin CC, Huang IT, Wang CC: Enhancement of thermal conductivity with carbon nanotube for nanofluids.

Int Commun Heat Mass Trans 2005, 32:1202-1210. Publisher Full Text

1. Chen QB, Wei YH, Shi YH, Liu HL, Hu Y: Measurement of surface tension and electrical conductivity of cationic gemini surfactants.

J East China Univ Sci Technol 2003, 29:33-37.

1. Zana R, Benrraou M, Rueff R: Alkanediyl-α, ω-bis (dimethylalkylammonium bromide) surfactants. 1. effect of the spacer chain length on the critical micelle concertration and micelle ionization degree.

Langmuir 1991, 7:1072-1075. Publisher Full Text

Huaqing Xie^*, Wei Yu, Yang Li and Lifei Chen

• *Corresponding author: Huaqing Xie hqxie@eed.sspu.cn

Author Affiliations

School of Urban Development and Environmental Engineering, Shanghai Second Polytechnic University, Shanghai 201209, China

For all author emails, please log on.

Nanoscale Research Letters 2011, 6:124 doi:10.1186/1556-276X-6-124

The electronic version of this article is the complete one and can be found online at:http://www.nanoscalereslett.com/content/6/1/124

© 2011 Xie et al; licensee Springer.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Testing Fountain Solution Conductivity – MyronLMeters.com

Tweet WHY TEST FOUNTAIN SOLUTIONS? Accurate fountain (dampening) solution concentration control is essential for consistent, high-quality results in lithography. Low concentration can cause drying on the non-image area of the plate resulting in tinting, scumming, blanket piling, etc. High concentrations, on the other hand, bring about over-emulsification of the ink. This results in weakening of [...]

Application Bulletin: POOL & SPA Water – MyronLMeters.com

Tweet                 Anyone responsible for operating and maintaining a swimming pool or spa has to test, monitor, and control complex, interdependent chemical factors that affect the quality of water. Additionally, aquatic facilities operators must be familiar with all laws, regulations, and guidelines governing what these parameters should be. [...]

SALTWATER SANITATION

A relatively new development, saltwater pools use regular salt, sodium chloride, to form chlorine with an electrical current much in the same way liquid bleach is made. As chlorine – the sanitizer – is made from the salt in the water, it is critical to maintain the salt concentration at the appropriate levels to produce an adequate level of sanitizer. It is even more important to test water parameters frequently in these types of pools and spas, as saltwater does not have the ability to respond adequately to shock loadings (superchlorination treatments).

Most saltwater chlorinators require a 2,500 – 3,000 ppm salt concentration in the water (though some may require as high as 5,000-7,000 ppm).* This can barely be tasted, but provides enough salt for the system to produce the chlorine needed to sanitize the water.

(It is important to have a good stabilizer level – 30 – 50 ppm* – in the pool, or the sunlight will burn up the chlorine. Without it, the saltwater system may not be able to keep up with the demand regardless of salt concentration.)

Taste and salt shortages are of little concern to seawater systems that maintain an average of 32,000 ppm. In these high-salt environments, you need to beware of corrosion to system components that can distort salt level and other parameter readings.

Additionally, incorrect salt concentration readings can occur in any saltwater system. The monitoring/controlling components can and do fail or become scaled— sometimes giving a false low salt reading. Thus, you must test manually for salt concentration with separate instrumentation before adding salt.

You must also test salt concentration manually with separate instrumentation to re-calibrate your system. This is critical to system functioning and production of required chlorine. Both the PoolPro and PT1 conveniently test for salt concentration at the press of a button as a check against automatic controller systems that may have disabled equipment or need to be re-calibrated.

Though no one instrument or method can be used to determine ALL of the factors that affect the comfort and sanitation of pool and spa water, PoolPro is a comprehensive water testing instrument that is reliable durable, easy-to-use and easy-to-maintain and calibrate. As a pool professional, a PoolPro will not only simplify your life, it will save you time and money.

 RECORD KEEPING – WHAT TO DO WITH ALL THOSE MEASUREMENTS …

Data handling should be done objectively, and data recorded in a common format in the most accurate way. Also, data should be stored in more than one permanent location and made available for future analysis. Most municipalities require commercial aquatic facilities to keep permanent records on site and available for inspection at any time.

PoolPro makes it easy to comply with record keeping requirements. The PoolPro is an objective means to test free chlorine, ORP, pH, TDS, temperature and the mineral/salt content of any pool or spa. You just rinse and fill the cell cup by submerging the waterproof unit and press the button of the parameter you wish to measure. You immediately get a standard, numerical digital readout –  no interpretation required – eliminating all subjectivity. And model PS9TK features the added ability to perform in-cell conductometric titrations for Alkalinity, Hardness and LSI on the spot. Up to 100 date-time-stamped readings can be stored in memory and then later transferred directly to a computer wirelessly using the bluDock™ accessory package. Simply pair the bluDock with your computer, then open the U2CI software application to download data. The user never touches the data, reducing the potential for human error in transcription. The data can then be imported into any program necessary for record-keeping and analysis. The bluDock is a quick and easy way to keep records that comply with governing standards.*

*Consult your governing bodies for specific testing, chemical concentrations, and all other guidelines and requirements. The ranges and methods suggested here are meant as general examples.

Save 10% when you order online here at MyronLMeters.com.

Frequently Asked Questions – MyronLMeters.com

TweetHow long will my Standard Solutions and Buffers last? The warranty on all standards and buffers is one year from the date it is manufactured (see the label on the bottle). If the standards and buffers become contaminated by the user pouring test samples back into the bottle or inserting the probe into the bottle [...]

How long will my Standard Solutions and Buffers last?

The warranty on all standards and buffers is one year from the date it is manufactured (see the label on the bottle). If the standards and buffers become contaminated by the user pouring test samples back into the bottle or inserting the probe into the bottle the solution will not be accurate and should be discarded. The life of standards and buffers can exceed 1 year if the bottle is stored tightly capped and is not exposed to direct sunlight or freezing temperatures. If the solution becomes frozen, do not remove the cap – allow the standard or buffer solution to thaw completely and shake the bottle vigorously before opening.

How do I clean the conductivity cell cup on the handheld units?

With everyday sampling, the cell cup may build up a residue or film on the cell walls that may cause the readings to become erratic. Use a 50/50 mixture of a common household cleaner (i.e. Lime-A-Way, CLR, Tilex, etc) and DI water. Pour into conductivity cell cup and scrub with a q-tip. Be sure to get around all the electrodes and the thermistor probe. On the DS handheld unit, use an acid brush to scrub the cell cup. Let it set for about 10 minutes. Rinse the cell cup thoroughly with tap water, then a final rinse with DI water.

The display on my Ultrameter II 6P reads “Error 1″. What does that mean?

This is possibly caused by contamination to the circuit board. One or more of the traces on the PCB have been jumped/bridged and there is a contamination. Possible moisture, condensation, dirt, dried salts or other condensation inside is a potential cause for this display.

Where can I get an operations manual for my meter?

Go to MyronLMeters.com. Click on Manuals and Literature at the top of the page. Once on the Manuals and Literature page, you’ll find application bulletins, operations manuals, material safety data sheets, and product datasheets.  All are free, downloadable pdf files.

How do I pick the correct range module for my Monitor or Monitor/Controller?

Pick a range module that covers 2/3 of your operating range. If you pick a range module that is too broad, then your accuracy will suffer or it will not show a number on the display. For example, if your operating range is 100-150 microsiemens, a range module of 0-200 microsiemens (-115) would be a good choice. A range module of 0- 5,000 microsiemens (-123) would not be a good choice for this application

Got questions? Visit us at MyronLMeters.com and Ask An Expert.

TDS (Total Dissolved Solids) and TDS Meters – MyronLMeters.com

TweetA TDS Meter indicates the Total Dissolved Solids (TDS) of a solution (the concentration of dissolved solids in it). Since dissolved ionized solids such as salts and minerals increase the conductivity of a solution, a TDS meter measures the conductivity of the solution and estimates the TDS from that. Dissolved organic solids such as sugar [...]

A TDS Meter indicates the Total Dissolved Solids (TDS) of a solution (the concentration of dissolved solids in it). Since dissolved ionized solids such as salts and minerals increase the conductivity of a solution, a TDS meter measures the conductivity of the solution and estimates the TDS from that.
Dissolved organic solids such as sugar and colloids don’t affect the conductivity of a solution much so a TDS meter does not include them in its reading.

Units of TDS

A TDS meter usually displays TDS in parts per million (ppm). For example, a TDS reading of 1 ppm would indicate there is 1 milligram of dissolved solids in each kilogram of water.

Measurement

The two chief methods of measuring total dissolved solids are gravimetry and conductivity. Gravimetric methods are the most accurate and involve evaporating the liquid solvent and measuring the mass of residues left. This method is generally the best but time-consuming. If inorganic salts comprise the majority of TDS, gravimetric methods are recommended.

Electrical conductivity of water is directly related to the concentration of dissolved ionized solids in the water. Ions from the dissolved solids in water create the water’s ability to conduct an electrical current, which can be measured using a conventional conductivity meter or TDS meter. When correlated with laboratory TDS measurements, conductivity provides an approximate value for the TDS concentration.

TDS

Total Dissolved Solids (TDS) is a measure of the combined content of all inorganic and organic substances contained in a liquid in: molecular, ionized or micro-granular (colloidal sol) suspended form. The operational definition is that the solids must be small enough to survive filtration through a two micrometer sieve. Total dissolved solids are normally discussed only for freshwater systems, as salinity comprises some of the ions constituting the definition of TDS. The principal application of TDS is in the study of water quality for streams, rivers and lakes, although TDS is not generally considered a primary pollutant (e.g. it is not deemed to be associated with health effects) it is used as an indication of aesthetic characteristics of drinking water and as an aggregate indicator of the presence of a broad array of chemical contaminants.
Primary sources for TDS in receiving waters are agricultural and residential runoff, leaching of soil contamination and point source water pollution discharge from industrial or sewage treatment plants. The most common chemical constituents are calcium, phosphates, nitrates, sodium, potassium and chloride, which are found in nutrient runoff, storm water runoff and runoff from snowy climates where road de-icing salts are applied. The chemicals may be cations, anions, molecules or agglomerations on the order of one thousand or fewer molecules, so long as a soluble micro-granule is formed. More exotic and harmful elements of TDS are pesticides arising from surface runoff. Certain naturally occurring total dissolved solids arise from the weathering and dissolution of rocks and soils. The United States has established a secondary water quality standard of 500 mg/l to provide for palatability of drinking water.

TDS Measurement Applications

High TDS levels indicate hard water, which can cause scale buildup in pipes, valves, and filters, reducing performance and adding to system maintenance costs. These effects can be seen in aquariums, spas, swimming pools, and reverse osmosis water treatment systems. Typically, in these applications, total dissolved solids are tested frequently, and filtration membranes are checked in order to prevent adverse effects.
In the case of hydroponics and aquaculture, TDS is often monitored in order to create a water quality environment favorable for organism productivity. For freshwater oysters, trouts, and other high value seafood, highest productivity and economic returns are achieved by mimicking the TDS and pH levels of each species’ native environment. For hydroponic uses, TDS is considered one of the best indices of nutrient availability for the aquatic plants being grown.

Because the threshold of acceptable aesthetic criteria for human drinking water is 500 mg/l, there is no general concern for odor, taste, and color at a level much lower than is required for harm. A number of studies have been conducted and indicate various species’ reactions range from intolerance to outright toxicity due to elevated TDS. The numerical results must be interpreted cautiously, as true toxicity outcomes will relate to specific chemical constituents. Nevertheless, some numerical information is a useful guide to the nature of risks in exposing aquatic organisms or terrestrial animals to high TDS levels. Most aquatic ecosystems involving mixed fish fauna can tolerate TDS levels of 1000 mg/l.

Applications
Boilers & cooling towers, Deionization, Reverse osmosis, Chemical concentrations, Printing fountain solutions, Swimming pools & spas, Water pollution control, Wastewater & more…
Myron L Meters Top-selling TDS Meters

Ultrapen PT1 Conductivity, TDS, Salinity pen

http://www.myronlmeters.com/Ultrapen-PT1-Multiparameter-Meter-p/dh-up-pt1.htm

ULTRAPEN PT1 Conductivity – TDS – Salinity Pen
Accuracy of +/-1% of READING (+/-.2% at Calibration Point)
Reliable Repeatable Results
Solution modes: KCl, NaCl and 442
Automatic Temperature Compensation
Autoranging
Durable, Fully Potted Circuitry
Waterproof

http://www.myronlmeters.com/Analog-Conductivity-Multirange-Meter-p/ah-ds-ep-10.htm

EP-10: 0-10, 100, 1000, 10,000 micromhos/microsiemens
Instant and accurate TDS tests
Electronic Internal Standard for easy field calibration
Fast Auto Temperature Compensation
Rugged design for years of trouble-free testing
Simple to use

Multi-Parameter: Conductivity, TDS, Resistivity, Temperature

http://www.myronlmeters.com/Ultrameter-II-4P-Multiparameter-Meter-p/dh-umii-4pii.htm

Multi-Parameter: Conductivity, TDS, Resistivity, Temperature
+/-1% Accuracy of Reading
Memory Storage: Save up to 100 samples w/ Date & Time stamp
Wireless Download Module Optional
Waterproof

material from Wikipedia shared via  Creative Commons Attribution-ShareAlike License

Conductivity and Conductivity Meters – MyronLMeters.com

TweetThe conductivity (or specific conductance) of a solution is a measure of its ability to conduct electricity. The standard unit of conductivity is siemens per meter (S/m). Conductivity measurements are used routinely in many industrial and environmental applications as a fast, inexpensive and reliable way of measuring ionic content in a solution. For example, the [...]

The conductivity (or specific conductance) of a solution is a measure of its ability to conduct electricity. The standard unit of conductivity is siemens per meter (S/m).

Conductivity measurements are used routinely in many industrial and environmental applications as a fast, inexpensive and reliable way of measuring ionic content in a solution. For example, the measurement of product conductivity is a typical way to monitor and continuously trend the performance of water purification systems.

In many cases, conductivity is linked directly to the total dissolved solids (TDS). High quality deionized water has a conductivity of about 5.5 μS/m, typical drinking water in the range of 5-50 mS/m, while sea water about 5 S/m (i.e., sea water’s conductivity is one million times higher than deionized water).

Conductivity is traditionally determined by measuring the AC resistance of the solution between two electrodes.

Resistivity of pure water (in MΩ-cm) as a function of temperature

The standard unit of conductivity is S/m and usually refers to 25 °C (standard temperature). Often encountered in industry is the traditional unit of μS/cm. 106 μS/cm = 103 mS/cm = 1 S/cm. The numbers in μS/cm are higher than those in μS/m by a factor of 100 (i.e., 1 μS/cm = 100 μS/m). Occasionally a unit of “EC” (electrical conductivity) is found on scales of instruments: 1 EC = 1 μS/cm. Sometimes encountered is a so-called mho (reciprocal of ohm): 1 mho/m = 1 S/m. Historically, mhos antedate Siemens by many decades; good vacuum-tube testers, for instance, gave transconductance readings in micromhos.

The commonly used standard cell has a width of 1 cm, and thus for very pure water in equilibrium with air would have a resistance of about 106 ohm, known as a megohm. Ultra-pure water could achieve 18 megohms or more. Thus in the past megohm-cm was used, sometimes abbreviated to “megohm”. Sometimes conductivity is given just in “microSiemens” (omitting the distance term in the unit). While this is an error, it’s usually assumed to be equal to the traditional μS/cm. The typical conversion of conductivity to the total dissolved solids is done assuming that the solid is sodium chloride: 1 μS/cm is then an equivalent of about 0.6 mg of NaCl per kg of water.

A conductivity meter and probe

The electrical conductivity of a solution is measured by determining the resistance of the solution between two flat or cylindrical electrodes separated by a fixed distance. An alternating voltage is used in order to avoid electrolysis. The resistance is measured by a conductivity meter. Typical frequencies used are in the range 1–3 kHz. The dependence on the frequency is usually small, but may become appreciable at very high frequencies, an effect known as the Debye–Falkenhagen effect.

A wide variety of instrumentation is commercially available. There are two types of cell, the classical type with flat or cylindrical electrodes and a second type based on induction. Many commercial systems, Myron L meters, e.g.,  offer automatic temperature correction.

MyronLMeters.com offers many reliable conductivity meters – some analog, some digital, some pen-style, some multiparameter – but all accurate, reliable, and easy-to-use.

Analog Handheld conductivity meter

512M5: 0-5000 micromhos/microsiemens

Instant and accurate Conductivity tests

Electronic Internal Standard for easy field calibration

Fast Auto Temperature Compensation

Rugged design for years of trouble-free testing

Simple to use

Digital Handheld Conductivity, TDS, Salinity Pen

ULTRAPEN PT1 Conductivity – TDS – Salinity Pen

Accuracy of +/-1% of READING (+/-.2% at Calibration Point)

Reliable Repeatable Results

Solution modes: KCl, NaCl and 442

Automatic Temperature Compensation

Autoranging

Durable, Fully Potted Circuitry

Waterproof

Digital Handheld Multi-Parameter meter: Conductivity, TDS, Resistivity, pH, ORP, Temperature, Free Chlorine (FC^E)
+/-1% Accuracy of Reading
Memory Storage: Save up to 100 samples w/ Date & Time stamp
Wireless Download Module Optional
Waterproof

Digital In-Line Conductivity Monitor/Controller

The unique circuitry of our 750 Series II Conductivity Inline Meters guarantees accurate and reliable measurements. Drift-free performance is assured by “field proven” electronics, including automatic DC offset compensation and highly accurate drive voltage.

Since Temperature Compensation is at the heart of accurate water measurement, all Myron L Monitor/controllers feature a highly refined and precise TC circuit. This feature perfectly matches the water temperature coefficient as it changes. All models are corrected to 25′C. The TC may be disabled to conform to USP requirements.

Boiler and Cooling Tower Water – MyronLMeters.com

TweetBoilers and cooling towers share two major water related problems: deposits and corrosion. As a boiler or water evaporating from a cooling tower generates steam, dissolved minerals are left behind, increasing the concentration of these minerals. Additional minerals are introduced via the water added to makeup the water lost to steam/evaporation. Eventually, the minerals reach [...]

Boilers and cooling towers share two major water related problems: deposits and corrosion. As a boiler or water evaporating from a cooling tower generates steam, dissolved minerals are left behind, increasing the concentration of these minerals. Additional minerals are introduced via the water added to makeup the water lost to steam/evaporation. Eventually, the minerals reach a level (or cycle) of concentration that will cause either loss of efficiency due to scale or damage from corrosion. This level can be determined by the Ryznar or Langlier indices and correlated to a conductivity or TDS range. Most people recognize problems associated with corrosion. Effects from scale deposits, however, are equally important. For example, as little as 1/8″ of scale can reduce the efficiency of a boiler by 18% or a cooling tower heat exchanger by 40%!

A variety of water treatment methods are employed in an effort to control these problems. Even with water treatment, it is still necessary to regularly blow down or bleed off part of the concentrated water and make up with lower salinity water to reduce the overall mineral concentration.

To conserve water and treatment chemicals, it is desirable to allow the dissolved minerals to reach a maximum cycle of concentration while still avoiding problems. Because feed water/make-up waters vary in the types and amounts of minerals present, the allowable cycles of concentration will vary. As a result, regular testing of boiler and cooling waters is essential to optimize water treatment programs and blow down schedules. Tests commonly performed include conductivity or TDS, pH and ORP. Myron L meters provide you with a simple, fast, and accurate means of testing these parameters.

Many cooling towers and boilers have inline controllers used to release water from the tower or boiler and feed chemical(s) into the system. The controllers must be calibrated regularly to ensure fouling or drift of the sensor has not occurred. Our portable instruments in conjunction with NIST traceable standard solutions provide rapid verification of the accuracy of inline controllers. This method reduces manpower and the likelihood of disturbing or damaging sensors.

Conductivity

Conductivity is the measurement of a solution’s ability to transmit an electrical current. It is usually expressed in microsiemens/cm (micromhos/cm). Pure water is actually a poor electrical conductor (18,200,000 ohms/cm of resistance). It is the amount of ionized substances (or salts) dissolved in water, which determines the conductivity. Because the vast majority of the dissolved minerals in water are these conductive inorganic impurities, conductivity measurement is an excellent indicator of mineral concentration.

Myron L meters were developed for just this purpose. Models are available which display conductivity and/or ppm of TDS. For detailed information regarding the relationship between conductivity and TDS, please see the our Application Bulletin: Standard Solutions and Buffers.

pH

pH, the measurement of acid or base, is one of the most important factors affecting scale formation or corrosion in a boiler or cooling system. The types of impurities comprising the mineral concentration behave differently at various pHs. Low pH waters have a tendency to cause corrosion, while high pH waters may cause scale formation.

Boiler water

Boiler water requirements can range from very pure to more than 6500 microsiemens, depending on size, pressure, application, and feed water. Once the maximum cycles of concentration has been established, a conductivity instrument can conveniently help you to determine if the blow down schedule is adequate. Samples should be cooled to at least 160°F/71°C to ensure accurate temperature compensated readings.

Boiler condensate

Boiler condensate samples are often tested to determine if there is any carryover of boiler water solids or contaminants entering from outside the system. Condensate is relatively pure water, and values of 2-100 microsiemens are common. Because of these low values, a multiple-range instrument is recommended to increase the resolution and accuracy of the reading. Monitoring the pH of condensate is also important since condensate is very corrosive at low pHs. Treatment additives are often added to elevate the pH to minimize corrosion in condensate lines.

Cooling tower water

Cooling tower water has become more challenging since the reduced use of acid and the elimination of chromate. Monitoring conductivity and pH has become imperative to maintain a proper treatment program. Although many systems have controls on these parameters, the possibility of a system upset is always present. Even slight upsets can cause rapid scaling of heat exchangers.

Biological Growth

Biological growth is another extremely important facet to proper cooling water management. Microbes can cause corrosion, fouling, and disease. Oxidizing biocides (chlorine, chlorine dioxide, ozone and bromine) have been employed to keep bacteria under control. Monitoring of the ORP (Oxidation Reduction Potential)/redox is very useful in its ability to correlate millivolt readings to sanitization strength of the water. The ULTRAMETER II™ 6P includes this parameter for quick on-site determinations.

Ultrameter II 4P  Ultrameter II 6P  TechPro II TH1  TechPro II TP1  TechPro II TPH1  M6/pH

EP11/pH   512M5   EP10  EP  inline monitors/controllers

Reverse Osmosis and Measurement for Home and Commercial Systems

Tweet OSMOSIS Osmosis is the phenomenon of lower dissolved solids in water passing through a semi-permeable membrane into higher dissolved solids water until a near equilibrium is reached. Reverse Osmosis (RO) is a membrane process of purification which removes most of the total dissolved solids (TDS) in water by reversing the natural process of osmosis. [...]

OSMOSIS

Osmosis is the phenomenon of lower dissolved solids in water passing through a semi-permeable membrane into higher dissolved solids water until a near equilibrium is reached. Reverse Osmosis (RO) is a membrane process of purification which removes most of the total dissolved solids (TDS) in water by reversing the natural process of osmosis. Pressure is applied to a TDS-concentrated solution against a semi-permeable membrane, causing pure water to diffuse through the membrane. RO has become an important process for a wide variety of applications including: medical, laboratory, desalination, industrial wastewater, Deionized (Dl) pretreatment, and drinking water.

TESTING RO WATER QUALITY

Electrical conductivity is the most convenient method for testing RO water quality and membrane performance. Pure water is actually a poor electrical conductor. The amount of ionized substances (salts, acids, or bases) dissolved in water determines its conductivity. Normally, the vast majority of the dissolved minerals in tap, surface or ground water are conductive impurities. Myron L Company has conducted extensive research relating conductivity to TDS, resulting in instrumentation and calibration solutions which have become the standard of the RO industry.

When calibrating your conductivity instrument for testing fresh water, the “442 Natural Water Standard™” solutions are the best choice. These solutions are available in various concentrations.
442 solutions contain the following salts diluted in pure water: 40% sodium bicarbonate, 40% sodium sulfate and 20% sodium chloride. These are the most common salt compounds in surface and ground water. A sodium chloride solution provides better results in brackish or sea water because the predominant salt in these waters is sodium chloride.

ORP

ORP (Oxidation Reduction Potential/REDOX) and pH are important parameters in measuring the success and useful life of an RO membrane. The ORP may be used to determine the activity of an oxidizer. RO membranes are susceptible to attack by oxidizers such as chlorine, bromine, ozone and hydrogen peroxide. The activity of the oxidizer is more informative than the chemical residual because it determines the ability and speed of oxidation. A high ORP reading would indicate a need for pretreatment. A low ORP may indicate biological activity which may cause fouling of the membranes.

ORP can also be used to determine an overfeed of sodium bisulfite, which is used to reduce chlorine. If the ORP reading is under 200 mV, you have a reducing condition. This overfeed costs extra money and can lead to environmental discharge problems. It is best to check the reject water, where the concentration is highest. This will show even minute quantities of oxidizers or reducers.

pH

pH is very useful in predicting membrane life and the scaling potential of feedwater. The higher the pH and calcium, the more likely it is that scale will form on the membranes. However, with silicon based compounds, a low pH will increase the tendency for scaling. Membranes also have a pH range where operation is optimal. It is often useful to check the pH of the reject water to help determine scaling potential.

HOME SYSTEMS
Myron L Meters carries single and multiple range handheld instruments. Model RO-1 and RO-1NC are reliable, single range instruments used to demonstrate the RO process to a prospective buyer. The color coding of the model RO-1 dial dramatizes the difference between high TDS (red- above EPA recommended limits for drinking water), medium TDS (orange – within EPA recommended standards for drinking water), and low TDS RO water (blue-high purity water). Installers prefer the three range 532 models or TechPro II™ TP1 or TPH1 because they are ideal for accurately testing both feed and product water.

COMMERCIAL/INDUSTRIAL
Larger RO systems such as those found in bottled water plants, hospitals, industrial process, or seawater desalination require continuous monitoring to verify water quality and membrane condition. For continuous measurement of water quality, Myron L Meters carries the 720 and 750 Series II Monitor/ controllers. Monitor only, and monitor/controller models are available. Monitor/controller models contain an adjustable set point and a heavy-duty 10 amp relay which can be used to activate alarms, valves, autodialers, etc. A variety of options and outputs are available to cost-effectively tailor the monitor to the particular RO application.

The Ultrameter™ 9PTK, 6PII and 4PII are preferred by water treatment professionals for calibrating and checking Commercial/industrial RO systems. They appreciate the waterproof case, ability to store and record 100 memory data records, and three preprogrammed solution curves. Ultrameters are compact, but their multiple parameters give them the versatility of several instruments.

Myron L Meters also carries pen style meterss for dip or scoop sampling. The ULTRAPEN PT1 delivers stable, lab-accurate readings of Conductivity, TDS, Salinity and Temperature. The PT2 pH and Temperature pen is also available for spot checks and pretreatment screening. Both pens are waterproof, durable, and easy to use with one-button functioning.

Visit us here to save 10% on any of our Myron L meters: http://www.myronlmeters.com/Digital-Multiparameter-Meters-s/48.htm

Myron L Meters Thanks Dalscorp of Brunswick, Maine!

Tweet Myron L Meters thanks Dalscorp engineering consultants of Brunswick, Maine, proud owners of a new Ultrapen PT1 conductivity/TDS/salinity pen. ULTRAPEN PT1 Conductivity/TDS/Salinity Pen. This instrument is designed to be extremely accurate, fast and simple to use in diverse water quality applications. Advanced features include the ability to select from 3 different solution types that [...]

Myron L Meters thanks Dalscorp engineering consultants of Brunswick, Maine, proud owners of a new Ultrapen PT1 conductivity/TDS/salinity pen.

ULTRAPEN PT1 Conductivity/TDS/Salinity Pen. This instrument is designed to be extremely accurate, fast and simple to use in diverse water quality applications. Advanced features include the ability to select from 3 different solution types that model the characteristics of the most commonly encountered types of water; proprietary temperature compensation and TDS conversion algorithms; highly stable microprocessor-based circuitry; user-intuitive design; and waterproof housing. A true, one-handed instrument, the PT1 is easy to calibrate and easy to use. To take a measurement, you simply press a button then dip the pen in solution. Results display in seconds.       ULTRAPEN – PT1    1. Push Button – turns instrument on in saved measurement mode; selects mode and unit preferences. 2. Pen Cap – provides access to battery for replacement. 3. Clip – holds pen to shirt pocket for secure storage. 4. Battery Indicator – indicates charge left in battery. 5. Display – displays measurements, mode options and battery indicator. 6. LED Indicator Light – indicates when to dip instrument in solution, when measurement is in progress, and when to remove instrument from solution. 7. Electrodes – measure electric current of solution. 8. Cell – contains flux field in defined area for accurate current measurement. 9. Scoop – contains sample solution for measurement when sampling from a vertical stream. To use, slide the open end of the scoop over the bottom of the pen until the neck of the scoop is flush with the top of the cell. Hold pen with scoop end under stream. Rinse and fill with sample solution 3 times. Fill with solution again, then take measurement. We recommend you recalibrate the pen using the scoop to retain accuracy of ±1%.

	Features PT1 Comes with: PT1 Pocket Tester Pen – battery installed Scoop Pocket Clip Holster Lanyard Operating Instructions Myron L Meters is proud to do business with Dalscorp. Please visit us on the web at: http://www.myronlmeters.com Facebook:   http://www.facebook.com/pages/Myron-L-Meters/147455608645777 Google +:     https://plus.google.com/112342237119950323462 Twitter:       http://twitter.com/MyronLMeters Linkedin:     http://www.linkedin.com/profile/view?id=98473409&trk=tab_pro Pinterest:     http://pinterest.com/myronlmeters/ YouTube:     http://www.youtube.com/myronlmeters News:           http://waterindustrynews.com