- Email: [email protected]
A low cost, easy to build, portable, and universal autosampler for liquids
Methods in Oceanography 8 (2014) 23–32
Contents lists available at ScienceDirect
Methods in Oceanography journal homepage: www.elsevier.com/locate/mio
Full length article
A low cost, easy to build, portable, and universal autosampler for liquids Matheus C. Carvalho ∗ , Bradley D. Eyre Centre for Coastal Biogeochemistry Research, Southern Cross University, PO box 157, Lismore, 2480, NSW, Australia
graphical
abstract
highlights • A low cost and easy to build autosampler for water analysis. • No knowledge of electronics is necessary to set-up and use the autosampler. • The autosampler can be used for analysing multiple water parameters.
article
info
Article history: Received 17 February 2014 Received in revised form
∗
abstract Autosamplers are ubiquitous tools in laboratories, and an integral part of many analytical instruments. However, most autosamplers are expensive, and as such they are not used in all laboratories. One
Corresponding author. Tel.: +61 0488990092. E-mail address: [email protected] (M.C. Carvalho).
http://dx.doi.org/10.1016/j.mio.2014.06.001 2211-1220/© 2014 Elsevier B.V. All rights reserved.
24 20 May 2014 Accepted 11 June 2014
Keywords: Automation Water analysis Carbon Nitrogen Stable isotopes Alkalinity pH
M.C. Carvalho, B.D. Eyre / Methods in Oceanography 8 (2014) 23–32
option is to purchase an analytical instrument without its autosampler, and integrate an autosampler from another supplier. Using scripting, it is possible to couple any autosampler with any analytical instrument, as long as both have a graphical user interface (GUI). Here we show that it is possible to integrate an inexpensive robotic arm kit, which has a GUI, to any analytical device that also has a GUI. The coupling is simple and does not require any electronic knowledge. We demonstrated that the robotic arm worked as an autosampler with 3 different analytical instruments for 8 different chemical measurements: total alkalinity, pH, total carbon, total organic carbon (including isotopic composition), total inorganic carbon (including isotopic composition) and total nitrogen in water samples. The setup is an economical alternative to the common liquid autosamplers. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Water analyses are essential for most oceanographic and limnological investigations. Many of these analyses can be done directly in the field, enabling real-time monitoring of the parameter(s) of interest. However, some analyses need to be done in the laboratory after water collection from the field. Water analyses in laboratory can be either manual or automatic, with the latter becoming the standard. Autosamplers are the core of laboratory automation, and are ubiquitous tools in any modern laboratory, enabling significant gains in productivity. Autosamplers are often purchased together with the analytical instruments, and can comprise a significant portion of the total instrument cost. However, in some cases autosamplers are among the least complex parts of an analytical setup and, therefore, it is difficult sometimes to justify the cost of a unit. This reality is quickly changing, as the price of electronic units substantially decreases and, at the same time, new technologies become available enabling people without deep knowledge of electronics to build their own electronic devices (Pearce, 2014a,b; Zhang et al., 2013). Importantly, it is necessary that the improvised autosampler and the measuring equipment are synchronized in time, which is not easily achievable unless the measuring equipment allows this kind of communication, or if the person doing the adaptation has good knowledge of communication protocols and low level programming. However, this is also changing and it is possible to integrate equipments from different suppliers using scripting provided that the integrated devices have user graphical interfaces (GUI) (Carvalho, 2013). Using GUIs the integration of any improvised autosampler with a measuring device becomes possible without the need of knowledge of the communication protocols involved, which is a significant factor to enable the use of even more devices as a substitute for purposely designed autosamplers. Automated potentiometric titration is an example of a case in which the autosampler can be the most expensive component of the analytical system (for example, in our laboratory the autosampler for a titration unit would cost US$80,000, compared to the analytical instrument which costs US$12,000). As such, automated titration systems are often purchased without the autosampler, making them semi-automated units relying on the constant presence of an operator. This can be translated in indirect costs, as this person could be employing his/her time in more productive tasks. Here we present a low cost (less than U$500), easy to build, portable, and universal autosampler for potentiometric titrations (alkalinity) and other water analyses (total carbon, total organic carbon, total inorganic carbon and total nitrogen). It consists of a robotic arm kit integrated to the titration software using computer scripting. It is demonstrated that the set-up generates reliable results, and thus can be an attractive option for researchers and laboratories with a limited budget.
M.C. Carvalho, B.D. Eyre / Methods in Oceanography 8 (2014) 23–32
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Fig. 1. The robotic arm AL5A and the rotation planes for each articulation. Arrows indicate −90° and 90° positions on each plane. The rotation plane for the base is parallel to the ground. Figure modified from original available at www.lynxmotion.com.
2. Materials and methods 2.1. The robotic arm kit The robotic arm kit was the Lynxmotion AL5A (Fig. 1). Full details about the assembly and its technical specifications can be found at www.lynxmotion.com. Briefly, it is a relatively small robotic arm, with arm measuring 9.5 cm, forearm measuring 14.3 cm, and a gripping hand measuring 4 cm. It has 5 degrees of freedom (articulations): base, shoulder, elbow, fist and grip. Each of these articulations is controlled by a servo-motor able to rotate 180° (for the grip, this rotation means an opening of 4 cm). These motors are controlled by a microcontroller (Lynxmotion SSC32 servo controller), connected to the computer with a serial cable (or a serial USB converter). The software that controls the microcontroller is the Lynxmotion RIOS. This setup enabled precise (2 mm of variation in repeated movements) control of the robotic arm. Details about SCSC32 and RIOS can also be obtained from www.lynxmotion.com. Robotic arms like the AL5A have articulations that produce circular movements (except for the grip, which has a linear movement). Therefore, the easiest geometric figure to work with is a circle, and not a straight line. Also, it is easier to use angles, instead of linear dimensions, to determine the movements. It is possible to overcome these characteristics and use linear coordinates after calibrating the robotic arm by measuring its dimensions. However, here we opted not to do this and defined the movements of the arm based solely on angles after trial and error sequences. This approach enabled the setup of the robotic arm movements without the need for calibration. The coordinate system used for the robotic arm is shown in Fig. 1. Notice that the angles are defined in relation to an arbitrary plane for each articulation. Also notice that the angles for the grip represent the movement of the servo motor, which in practice translates to linear movement of the gripper. 2.2. Autosampler setup The robotic arm was not developed with the specific purpose of being used as an autosampler for water analysis; instead, it is a general-purpose device. This means that in order to be used as an autosampler significant effort and time were spent to set up the movements. However, once these steps were done, it worked flawlessly.
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M.C. Carvalho, B.D. Eyre / Methods in Oceanography 8 (2014) 23–32
Fig. 2. Scheme of the autosampler. Upper figure: top view of the autosampler; lower figure: vertical dimensions of some components. White circles on the large semi-circles in the upper figure are the sample holders. Black circle marks the horizontal position of the measuring station. Robotic arm is not shown. Notice that the semicircles containing the sample holders are not parallel to the horizontal axis of the plywood. This was because the horizontal axis of the robot base was not parallel to this direction. The photo in the inset shows the actual robotic arm with the sample holders, dump station and measuring station.
The first step to set up the autosampler was to position the robotic arm on a plywood board (90 × 60 cm, Fig. 2). The position was chosen so that the arm could move entirely over the board, and not outside it. A 6 cm support was used below the robotic arm in order to increase its reach for the vials used here (8 cm in height). Below the subsequent steps to set up the autosampler are described in detail. Before starting that description, it is worth mentioning that setting up the robotic arm to work as an autosampler is a lengthy and time consuming process. An alternative approach that can save a lot of time is to download the files that control the robot from http://100dollarautosampler.comli. com/ScriptsAndOthers.zip and upload them to RIOS. These files contain all the instructions for the movements of the robotic arm that are described subsequently. Once that is done, it is possible to observe the programmed movements for the predetermined positions. Then, it is possible to fixate the sample holders, dump and measuring stations (items described in detail below) at the appropriate positions. This saves considerable time and effort, and still allows complete subsequent adjustment of movements. An explanation for each movement is in the Readme.txt file on the provided weblink. The next step is to determine the position for the titration probe and acid dispenser (or for example the sampling tube), that is, the measuring station. This position was set at 90° relative to the centre of the base of the robotic arm, at a distance reachable by the arm at a relatively elevated position. The elevated position was chosen so that the retort stand used to hold the titration apparatus would not be taking up space that could be used for sample positions.
M.C. Carvalho, B.D. Eyre / Methods in Oceanography 8 (2014) 23–32
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The next step was to determine the first position for water samples. The water samples were contained in flasks measuring 8 × 3 cm and being able to hold more than 30 ml. Therefore, trapezoidal sample holders measuring 4.2 cm of diameter in their opening, 3.2 cm in their base and 4 cm in height (Fig. 2) were used. The larger opening at the mouth was useful to make it easier for the robotic arm to remove and return the vials inside the sample holders. For the first position, the sample holder was glued to the plywood at 90° in the horizontal axis and at a distance of 20.5 cm from the centre of the arm base. All movements necessary to pick a vial from this position and to return it, as well as to pick from it up and bring it to the sensor were defined, and the angles for each stopping point were determined and recorded using the RIOS software. Importantly, it was necessary to record a ‘‘pause’’ of at least 100 ms for each step, thus ensuring that the movement would be reproducible. It was also important to set-up reasonable movement speeds for each component of the arm so that water would not spill due to acceleration at the start and the end of the movement. A third step was to set-up a ‘‘dump’’ station to throw vials after the samples were measured. This station was chosen to be at −90° on the horizontal axis, with its border reaching nearly 25 cm from the centre of the base. The dump operation consisted of getting the vial and taking it to an elevated position over the dump station, where, with a quick movement, it would throw the vial into it. This dumping always originated from the measuring station, and not from each sample, so that only a single movement was defined, and not one for each sample position. A fourth step was to add a series of movements to knock off a lid on a vial standing on the sample position. This enabled the use of vials covered with lids, which reduced losses due to evaporation. Overall, the vial handling sequence was: (1) knock off the lid of the vial; (2) bring the vial from the sample position to the measuring station; (3) bring the vial from the measuring station to the dump station; and (4) dump the vial. Each of these movements described were composed by several sub-movements. If it is opted for using the movements pre-set and available at http://100dollarautosampler.comli.com/ ScriptsAndOthers.zip, it will be observed that some of them consist in apparently useless steps. For example, before going to the sample holder, the arm was set to go to a ‘‘zero’’ position. The reason for this is that in devices using simple servo motors like the robotic arm the initial position matters for the reproducibility of movements. Once these movements were determined, it was necessary to determine the movements for more samples. As detailed before, the basic movement for the robotic arm is the circle. Thus, samples positioned on a circle can be dealt in the same way as the original sample as long as only their base angle differs. This made it easy to set up the movements to deal with the new samples: the movements for the initial position were exported as a CSV file using the RIOS software. Then, using a spreadsheet program, the CSV file was edited by adding more positions, which all had parameters equal to the original except for the base angle, which was modified from −90° to 90° enabling the set-up of 12 positions on this semicircle. A similar approach was done for samples positioned 27 cm from the centre of the robotic arm base. These samples needed to be placed 8 cm above the base so that they could be reached by the arm even if other samples were present at the positions on the inner circle of samples. Therefore, the sample holders for those samples were sampling vials glued upside down to the sample holders used for the inner circle (Fig. 2). As for the inner circle, all movements were firstly set for the initial position at 90°, and subsequently copied to the other positions on the semicircle, enabling the setup of 14 positions (although more positions could be made, it was necessary to leave space for the dump station). Despite the expectation of perfect equivalency of movements at each position, the truth is that slight variations in vial position can lead to accidents in sample handling. It was observed that instead of taking samples directly from their position to the measuring station (a movement that needed great precision due to the dimensions of the pH probe), it was better to pick up the sample, bring it to the initial inner circle position (a movement that did not need extreme precision), and from there do the movement to the measuring station. This ensured that every time the vials would be lifted so that the probes would be inside them. In order to avoid contamination between samples, a total of 5 rinsing positions were determined (thus reducing the sample positions from 26 to 21). For the vials in these rinsing positions, the
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procedure was to bring them to the initial inner circle position, then to the measuring station, and then back to the position, and not the dump. Notice that the movements described in the last two paragraphs made it necessary that the first position at the inner circle were empty. This was accomplished by always doing the measurement for this sample before any other action. 2.3. Integration with analytical equipments The equipments integrated to the robotic arm were: for potentiometric titration, the Metrohm 888 titrando automated titrator, controlled with the software tiamo (Bradshaw and Brewer, 1988; Stumm and Morgan, 1981); for total organic and inorganic carbon, including carbon stable isotopes, the OI Scientific Aurora 1030 TOC analyser, coupled to an Isotope Ratio Mass Spectrometer, Thermo Fisher Delta V plus (St-Jean, 2003; van Geldern et al., 2013); for total nitrogen, and also total carbon and total inorganic carbon, a Shimadzu TOC analyser including a total nitrogen analysis module (APHA, 1996; Shimadzu, 2010; Williams, 1992). Integration of the robotic arm and the measuring equipment was entirely achieved by scripting using the AutoIt V3 language; no physical connection (cable) between the robotic arm and the analytical devices was necessary (Fig. 3). Generically, the scripts consisted of several sub-functions that were called by a main routine in the appropriate order. The sub-functions for the RIOS software consisted in telling the software to do a determined set of movements (described in the previous section). Those for the analytical devices consisted of instructions for starting or finishing measurements in a predefined sequence. The main script ordered these sub-functions in the appropriate sequence and timing, also determining how many repetitions would be done. Scripts with comments are available for download at http://100dollarautosampler.comli.com/ScriptsAndOthers.zip, as well as the files for controlling the robotic arm. Videos demonstrating that the robotic arm kit worked in synchrony with the equipment are available on http://www.youtube.com/channel/UC6X_viFhqGovGtWIedEUSkA. 2.4. Evaluation of the autosampler A main issue in the operation of the robotic arm as an autosampler was the possibility of carryover effects between samples. This was tested for all measurements. In the case of potentiometric case, repeated measurements of a single sample (each repetition in a different vial) were done. Initial pH and total alkalinity of the samples were measured and compared; if a drop in these parameters occurred from a sample to the next, it would mean that there was contamination from a sample to the next, because the alkalinity titration consists in the addition of acid to the water sample. The carryover effect test for the other analyses consisted in measuring the samples with high and low concentrations of carbon and/or nitrogen alternately. If the sample following a high concentration sample showed higher values than the same sample after a low concentration sample, then the carryover effects would be apparent. 3. Results and discussion There was no systematic change in pH or alkalinity in 15 repeated measurements (Fig. 4A), and the observed variation (±3 µe L−1 for alkalinity) was near the normal operation of the titrator (±2 µe L−1 for alkalinity). Better results could have been achieved if the volume of the water samples had been better determined beforehand by, for example, weighing the water volume and converting to volume. Variation was higher for pH: the specification predicts variation of only 0.001 units, but our variation was of almost 0.1 units. However, these values were obtained from 30 s measurements and may demonstrate that a longer measurement time is probably needed. For the concentration measurements (Fig. 4B and C) blanks showed low values before and after concentrated samples, demonstrating that no contamination existed in the procedure for any of the
M.C. Carvalho, B.D. Eyre / Methods in Oceanography 8 (2014) 23–32
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Fig. 3. Scheme showing the connections between the devices employed for the chemical analyses. Notice that there is no physical electronic connection between the analytical instrument and the robotic arm, and that its integration is entirely done by AutoIt, the scripting language.
parameters evaluated. Error for non-blank measurements was smaller than 1% for TC and IC, and 2% for TN on the Shimadzu TOC analyser, which is in accordance with the equipment specification (1.5% for TC and IC, and 3% for TN) with the Shimadzu TOC analyser. Error was 1.6% for TOC and 0.4% for IC with the Aurora TOC analyser, for which expected values would be 1.5% according to its manual. For the isotope measurements (Fig. 4D), it was not possible to compare the dissolved inorganic carbon values as the blanks were below the detection limits. However, it was clear that the dissolved organic carbon values for the blank were quite different from those of the sample. The large scatter in the blanks was due to poor sensitivity of the sensor for very low concentration samples. Values for
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Fig. 4. Automated measurements done with the robotic arm kit as an autosampler. (A) pH and alkalinity measured using a Metrohm 888 titrando. (B) Total carbon (TC), inorganic carbon (IC) and total nitrogen (TN) measured using a Shimadzu TOC analyser equipped with a total nitrogen analysis module. (C) Dissolved inorganic carbon (DIC) and dissolved organic carbon (DOC) measured using an Aurora TOC analyser coupled to a Thermo-Fisher Delta V plus isotope ratio mass spectrometer. (D) DIC and DOC carbon stable isotope ratios (δ 13 C) measured with the Aurora and the Delta V plus. Blank was Milli Q water, and sample was a solution of bicarbonate and urea dissolved in Milli Q water, for (B)–(D), and tap water for (A).
non-blank samples had a variation of 0.4h (DIC) and 0.05h (DOC), which are commonly reported for these measurements (St-Jean, 2003; van Geldern et al., 2013).
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4. Conclusions We demonstrated that a robotic arm kit can be an inexpensive, easy to build and universal autosampler for water samples in diverse kinds of analyses. No knowledge of electronics was needed to build the autosampler, and repeatable measurements without significant carryover effects were possible for alkalinity, pH, total carbon, total nitrogen, total organic carbon and total inorganic carbon (including carbon stable isotopes for the last 2). The set-up should also work for other kinds of water analyses, and thus it can be a very attractive option for laboratories in a limited budget. By using the files provided in http://100dollarautosampler.comli.com/ScriptsAndOthers.zip, anyone who acquires the robotic arm kit should be able to build an autosampler identical to the one described here at a very low cost. By using the scripts provided as examples, the robotic arm can be integrated to any laboratory instrument, provided it has a GUI. Some improvements in the setup are possible. The configuration presented here allows for a maximum of only 21 samples measured automatically. The sample tray, however, has 26 positions. If an automated rinsing device was used together with the robotic arm, 26 samples could be measured. This and other possible solutions can easily be incorporated by the setup, as it relies only on computer scripting to integrate its different parts. People with knowledge on electronics would be able to make a robotic arm themselves, and, with microcontrollers like arduino (Zhang et al., 2013), and using scripting (Carvalho, 2013), could make personalized devices with virtually unlimited applications (Pearce, 2014a). The approach described in this paper can be seen under the broader light of ‘‘open source laboratory’’, in which alternative equipment, not primarily designed for being employed in laboratories, or equipment fabricated in the laboratory itself, are adapted for laboratory tasks enabling significant reduction in costs. Several examples can be found, including micro-centrifuges, orbital shakers and colorimeters (Anzalone et al., 2013; Pearce, 2012, 2014b). Other examples are the adaptation of 3D printers to perform laboratory tasks (Gross et al., 2014; Symes et al., 2012). It can be expected that the applications of such alternative technologies will become more common with the popularization of accessible, easy-to-use microcontrollers, and scripting. Acknowledgement This work was funded by an Australian Research Council Linkage Grant (LP110200975) awarded to BDE. Appendix A. Supplementary data Supplementary material related to this article can be found online at http://dx.doi.org/10.1016/j. mio.2014.06.001. References Anzalone, G.C., Glover, A.G., Pearce, J.M., 2013. Open-source colorimeter. Sensors 13, 5338–5346. APHA, AWWA, WEF, 1996. Total organic carbon. Standard methods for Examination of water and waste water, 5.19–15.25. Bradshaw, A.L., Brewer, P.G., 1988. High precision measurements of alkalinity and total carbon dioxide in seawater by potentiometric titration — 1. Presence of unknown protolyte(s)? Marine Chem. 23, 69–86. Carvalho, M.C., 2013. Integration of analytical instruments with computer scripting. J. Lab. Automat. 18, 328–333. Gross, B.C., Erkal, J.L., Lockwood, S.Y., Chen, C., Spence, D.M., 2014. Evaluation of 3D printing and its potential impact on biotechnology and the chemical sciences. Anal. Chem. 86, 3240–3253. Pearce, J.M., 2014a. Cut costs with open-source hardware. Nature 505, 618. Pearce, J.M., 2014b. Open-Source Lab: How to Build Your Own Hardware and Reduce Research Costs. Elsevier, Waltham. Pearce, J.M., 2012. Building research equipment with free, open-source hardware. Science 337, 1303–1304. Shimadzu, 2010. Total Organic Carbon Analyzer TOC-L CSH/CSN User’s Manual. Shimadzu corporation, Kyoto. St-Jean, G., 2003. Automated quantitative and isotopic (13 C) analysis of dissolved inorganic carbon and dissolved organic carbon in continuous-flow using a total carbon analyser. Rapid Commun. Mass Spectrom. 17, 419–428. Stumm, W., Morgan, J.J., 1981. Aquatic Chemistry, an Introduction Emphasizing Chemical Equilibria in Natural Waters. John Wiley and Sons, New York. Symes, M.D., Kitson, P.J., Yan, J., Richmond, C.J., Cooper, G.J.T., Bowman, R.W., Vilbrandt, T., Cronin, L., 2012. Integrated 3D-printed reactionware for chemical synthesis and analysis. Nature Chem. 4, 349–354.
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van Geldern, R., Verma, M.P., Carvalho, M.C., Grassa, F., Huertas, A.D., Monvoisin, G., Barth, J.A.C., 2013. Stable carbon isotope analysis of dissolved inorganic carbon (DIC) and dissolved organic carbon (DOC) in natural waters – Results from first worldwide proficiency test. Rapid Commun. Mass Spectrom. 27, 2099–2107. Williams, P.M., 1992. Measurement of dissolved organic carbon and nitrogen in natural waters. Oceanography 5, 107–116. Zhang, C., Anzalone, N.C., Faria, R.P., Pearce, J.M., 2013. Open-source 3D-printable optics equipment. PLoS_One 8, e59840.
Contents lists available at ScienceDirect
Methods in Oceanography journal homepage: www.elsevier.com/locate/mio
Full length article
A low cost, easy to build, portable, and universal autosampler for liquids Matheus C. Carvalho ∗ , Bradley D. Eyre Centre for Coastal Biogeochemistry Research, Southern Cross University, PO box 157, Lismore, 2480, NSW, Australia
graphical
abstract
highlights • A low cost and easy to build autosampler for water analysis. • No knowledge of electronics is necessary to set-up and use the autosampler. • The autosampler can be used for analysing multiple water parameters.
article
info
Article history: Received 17 February 2014 Received in revised form
∗
abstract Autosamplers are ubiquitous tools in laboratories, and an integral part of many analytical instruments. However, most autosamplers are expensive, and as such they are not used in all laboratories. One
Corresponding author. Tel.: +61 0488990092. E-mail address: [email protected] (M.C. Carvalho).
http://dx.doi.org/10.1016/j.mio.2014.06.001 2211-1220/© 2014 Elsevier B.V. All rights reserved.
24 20 May 2014 Accepted 11 June 2014
Keywords: Automation Water analysis Carbon Nitrogen Stable isotopes Alkalinity pH
M.C. Carvalho, B.D. Eyre / Methods in Oceanography 8 (2014) 23–32
option is to purchase an analytical instrument without its autosampler, and integrate an autosampler from another supplier. Using scripting, it is possible to couple any autosampler with any analytical instrument, as long as both have a graphical user interface (GUI). Here we show that it is possible to integrate an inexpensive robotic arm kit, which has a GUI, to any analytical device that also has a GUI. The coupling is simple and does not require any electronic knowledge. We demonstrated that the robotic arm worked as an autosampler with 3 different analytical instruments for 8 different chemical measurements: total alkalinity, pH, total carbon, total organic carbon (including isotopic composition), total inorganic carbon (including isotopic composition) and total nitrogen in water samples. The setup is an economical alternative to the common liquid autosamplers. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Water analyses are essential for most oceanographic and limnological investigations. Many of these analyses can be done directly in the field, enabling real-time monitoring of the parameter(s) of interest. However, some analyses need to be done in the laboratory after water collection from the field. Water analyses in laboratory can be either manual or automatic, with the latter becoming the standard. Autosamplers are the core of laboratory automation, and are ubiquitous tools in any modern laboratory, enabling significant gains in productivity. Autosamplers are often purchased together with the analytical instruments, and can comprise a significant portion of the total instrument cost. However, in some cases autosamplers are among the least complex parts of an analytical setup and, therefore, it is difficult sometimes to justify the cost of a unit. This reality is quickly changing, as the price of electronic units substantially decreases and, at the same time, new technologies become available enabling people without deep knowledge of electronics to build their own electronic devices (Pearce, 2014a,b; Zhang et al., 2013). Importantly, it is necessary that the improvised autosampler and the measuring equipment are synchronized in time, which is not easily achievable unless the measuring equipment allows this kind of communication, or if the person doing the adaptation has good knowledge of communication protocols and low level programming. However, this is also changing and it is possible to integrate equipments from different suppliers using scripting provided that the integrated devices have user graphical interfaces (GUI) (Carvalho, 2013). Using GUIs the integration of any improvised autosampler with a measuring device becomes possible without the need of knowledge of the communication protocols involved, which is a significant factor to enable the use of even more devices as a substitute for purposely designed autosamplers. Automated potentiometric titration is an example of a case in which the autosampler can be the most expensive component of the analytical system (for example, in our laboratory the autosampler for a titration unit would cost US$80,000, compared to the analytical instrument which costs US$12,000). As such, automated titration systems are often purchased without the autosampler, making them semi-automated units relying on the constant presence of an operator. This can be translated in indirect costs, as this person could be employing his/her time in more productive tasks. Here we present a low cost (less than U$500), easy to build, portable, and universal autosampler for potentiometric titrations (alkalinity) and other water analyses (total carbon, total organic carbon, total inorganic carbon and total nitrogen). It consists of a robotic arm kit integrated to the titration software using computer scripting. It is demonstrated that the set-up generates reliable results, and thus can be an attractive option for researchers and laboratories with a limited budget.
M.C. Carvalho, B.D. Eyre / Methods in Oceanography 8 (2014) 23–32
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Fig. 1. The robotic arm AL5A and the rotation planes for each articulation. Arrows indicate −90° and 90° positions on each plane. The rotation plane for the base is parallel to the ground. Figure modified from original available at www.lynxmotion.com.
2. Materials and methods 2.1. The robotic arm kit The robotic arm kit was the Lynxmotion AL5A (Fig. 1). Full details about the assembly and its technical specifications can be found at www.lynxmotion.com. Briefly, it is a relatively small robotic arm, with arm measuring 9.5 cm, forearm measuring 14.3 cm, and a gripping hand measuring 4 cm. It has 5 degrees of freedom (articulations): base, shoulder, elbow, fist and grip. Each of these articulations is controlled by a servo-motor able to rotate 180° (for the grip, this rotation means an opening of 4 cm). These motors are controlled by a microcontroller (Lynxmotion SSC32 servo controller), connected to the computer with a serial cable (or a serial USB converter). The software that controls the microcontroller is the Lynxmotion RIOS. This setup enabled precise (2 mm of variation in repeated movements) control of the robotic arm. Details about SCSC32 and RIOS can also be obtained from www.lynxmotion.com. Robotic arms like the AL5A have articulations that produce circular movements (except for the grip, which has a linear movement). Therefore, the easiest geometric figure to work with is a circle, and not a straight line. Also, it is easier to use angles, instead of linear dimensions, to determine the movements. It is possible to overcome these characteristics and use linear coordinates after calibrating the robotic arm by measuring its dimensions. However, here we opted not to do this and defined the movements of the arm based solely on angles after trial and error sequences. This approach enabled the setup of the robotic arm movements without the need for calibration. The coordinate system used for the robotic arm is shown in Fig. 1. Notice that the angles are defined in relation to an arbitrary plane for each articulation. Also notice that the angles for the grip represent the movement of the servo motor, which in practice translates to linear movement of the gripper. 2.2. Autosampler setup The robotic arm was not developed with the specific purpose of being used as an autosampler for water analysis; instead, it is a general-purpose device. This means that in order to be used as an autosampler significant effort and time were spent to set up the movements. However, once these steps were done, it worked flawlessly.
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Fig. 2. Scheme of the autosampler. Upper figure: top view of the autosampler; lower figure: vertical dimensions of some components. White circles on the large semi-circles in the upper figure are the sample holders. Black circle marks the horizontal position of the measuring station. Robotic arm is not shown. Notice that the semicircles containing the sample holders are not parallel to the horizontal axis of the plywood. This was because the horizontal axis of the robot base was not parallel to this direction. The photo in the inset shows the actual robotic arm with the sample holders, dump station and measuring station.
The first step to set up the autosampler was to position the robotic arm on a plywood board (90 × 60 cm, Fig. 2). The position was chosen so that the arm could move entirely over the board, and not outside it. A 6 cm support was used below the robotic arm in order to increase its reach for the vials used here (8 cm in height). Below the subsequent steps to set up the autosampler are described in detail. Before starting that description, it is worth mentioning that setting up the robotic arm to work as an autosampler is a lengthy and time consuming process. An alternative approach that can save a lot of time is to download the files that control the robot from http://100dollarautosampler.comli. com/ScriptsAndOthers.zip and upload them to RIOS. These files contain all the instructions for the movements of the robotic arm that are described subsequently. Once that is done, it is possible to observe the programmed movements for the predetermined positions. Then, it is possible to fixate the sample holders, dump and measuring stations (items described in detail below) at the appropriate positions. This saves considerable time and effort, and still allows complete subsequent adjustment of movements. An explanation for each movement is in the Readme.txt file on the provided weblink. The next step is to determine the position for the titration probe and acid dispenser (or for example the sampling tube), that is, the measuring station. This position was set at 90° relative to the centre of the base of the robotic arm, at a distance reachable by the arm at a relatively elevated position. The elevated position was chosen so that the retort stand used to hold the titration apparatus would not be taking up space that could be used for sample positions.
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The next step was to determine the first position for water samples. The water samples were contained in flasks measuring 8 × 3 cm and being able to hold more than 30 ml. Therefore, trapezoidal sample holders measuring 4.2 cm of diameter in their opening, 3.2 cm in their base and 4 cm in height (Fig. 2) were used. The larger opening at the mouth was useful to make it easier for the robotic arm to remove and return the vials inside the sample holders. For the first position, the sample holder was glued to the plywood at 90° in the horizontal axis and at a distance of 20.5 cm from the centre of the arm base. All movements necessary to pick a vial from this position and to return it, as well as to pick from it up and bring it to the sensor were defined, and the angles for each stopping point were determined and recorded using the RIOS software. Importantly, it was necessary to record a ‘‘pause’’ of at least 100 ms for each step, thus ensuring that the movement would be reproducible. It was also important to set-up reasonable movement speeds for each component of the arm so that water would not spill due to acceleration at the start and the end of the movement. A third step was to set-up a ‘‘dump’’ station to throw vials after the samples were measured. This station was chosen to be at −90° on the horizontal axis, with its border reaching nearly 25 cm from the centre of the base. The dump operation consisted of getting the vial and taking it to an elevated position over the dump station, where, with a quick movement, it would throw the vial into it. This dumping always originated from the measuring station, and not from each sample, so that only a single movement was defined, and not one for each sample position. A fourth step was to add a series of movements to knock off a lid on a vial standing on the sample position. This enabled the use of vials covered with lids, which reduced losses due to evaporation. Overall, the vial handling sequence was: (1) knock off the lid of the vial; (2) bring the vial from the sample position to the measuring station; (3) bring the vial from the measuring station to the dump station; and (4) dump the vial. Each of these movements described were composed by several sub-movements. If it is opted for using the movements pre-set and available at http://100dollarautosampler.comli.com/ ScriptsAndOthers.zip, it will be observed that some of them consist in apparently useless steps. For example, before going to the sample holder, the arm was set to go to a ‘‘zero’’ position. The reason for this is that in devices using simple servo motors like the robotic arm the initial position matters for the reproducibility of movements. Once these movements were determined, it was necessary to determine the movements for more samples. As detailed before, the basic movement for the robotic arm is the circle. Thus, samples positioned on a circle can be dealt in the same way as the original sample as long as only their base angle differs. This made it easy to set up the movements to deal with the new samples: the movements for the initial position were exported as a CSV file using the RIOS software. Then, using a spreadsheet program, the CSV file was edited by adding more positions, which all had parameters equal to the original except for the base angle, which was modified from −90° to 90° enabling the set-up of 12 positions on this semicircle. A similar approach was done for samples positioned 27 cm from the centre of the robotic arm base. These samples needed to be placed 8 cm above the base so that they could be reached by the arm even if other samples were present at the positions on the inner circle of samples. Therefore, the sample holders for those samples were sampling vials glued upside down to the sample holders used for the inner circle (Fig. 2). As for the inner circle, all movements were firstly set for the initial position at 90°, and subsequently copied to the other positions on the semicircle, enabling the setup of 14 positions (although more positions could be made, it was necessary to leave space for the dump station). Despite the expectation of perfect equivalency of movements at each position, the truth is that slight variations in vial position can lead to accidents in sample handling. It was observed that instead of taking samples directly from their position to the measuring station (a movement that needed great precision due to the dimensions of the pH probe), it was better to pick up the sample, bring it to the initial inner circle position (a movement that did not need extreme precision), and from there do the movement to the measuring station. This ensured that every time the vials would be lifted so that the probes would be inside them. In order to avoid contamination between samples, a total of 5 rinsing positions were determined (thus reducing the sample positions from 26 to 21). For the vials in these rinsing positions, the
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procedure was to bring them to the initial inner circle position, then to the measuring station, and then back to the position, and not the dump. Notice that the movements described in the last two paragraphs made it necessary that the first position at the inner circle were empty. This was accomplished by always doing the measurement for this sample before any other action. 2.3. Integration with analytical equipments The equipments integrated to the robotic arm were: for potentiometric titration, the Metrohm 888 titrando automated titrator, controlled with the software tiamo (Bradshaw and Brewer, 1988; Stumm and Morgan, 1981); for total organic and inorganic carbon, including carbon stable isotopes, the OI Scientific Aurora 1030 TOC analyser, coupled to an Isotope Ratio Mass Spectrometer, Thermo Fisher Delta V plus (St-Jean, 2003; van Geldern et al., 2013); for total nitrogen, and also total carbon and total inorganic carbon, a Shimadzu TOC analyser including a total nitrogen analysis module (APHA, 1996; Shimadzu, 2010; Williams, 1992). Integration of the robotic arm and the measuring equipment was entirely achieved by scripting using the AutoIt V3 language; no physical connection (cable) between the robotic arm and the analytical devices was necessary (Fig. 3). Generically, the scripts consisted of several sub-functions that were called by a main routine in the appropriate order. The sub-functions for the RIOS software consisted in telling the software to do a determined set of movements (described in the previous section). Those for the analytical devices consisted of instructions for starting or finishing measurements in a predefined sequence. The main script ordered these sub-functions in the appropriate sequence and timing, also determining how many repetitions would be done. Scripts with comments are available for download at http://100dollarautosampler.comli.com/ScriptsAndOthers.zip, as well as the files for controlling the robotic arm. Videos demonstrating that the robotic arm kit worked in synchrony with the equipment are available on http://www.youtube.com/channel/UC6X_viFhqGovGtWIedEUSkA. 2.4. Evaluation of the autosampler A main issue in the operation of the robotic arm as an autosampler was the possibility of carryover effects between samples. This was tested for all measurements. In the case of potentiometric case, repeated measurements of a single sample (each repetition in a different vial) were done. Initial pH and total alkalinity of the samples were measured and compared; if a drop in these parameters occurred from a sample to the next, it would mean that there was contamination from a sample to the next, because the alkalinity titration consists in the addition of acid to the water sample. The carryover effect test for the other analyses consisted in measuring the samples with high and low concentrations of carbon and/or nitrogen alternately. If the sample following a high concentration sample showed higher values than the same sample after a low concentration sample, then the carryover effects would be apparent. 3. Results and discussion There was no systematic change in pH or alkalinity in 15 repeated measurements (Fig. 4A), and the observed variation (±3 µe L−1 for alkalinity) was near the normal operation of the titrator (±2 µe L−1 for alkalinity). Better results could have been achieved if the volume of the water samples had been better determined beforehand by, for example, weighing the water volume and converting to volume. Variation was higher for pH: the specification predicts variation of only 0.001 units, but our variation was of almost 0.1 units. However, these values were obtained from 30 s measurements and may demonstrate that a longer measurement time is probably needed. For the concentration measurements (Fig. 4B and C) blanks showed low values before and after concentrated samples, demonstrating that no contamination existed in the procedure for any of the
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Fig. 3. Scheme showing the connections between the devices employed for the chemical analyses. Notice that there is no physical electronic connection between the analytical instrument and the robotic arm, and that its integration is entirely done by AutoIt, the scripting language.
parameters evaluated. Error for non-blank measurements was smaller than 1% for TC and IC, and 2% for TN on the Shimadzu TOC analyser, which is in accordance with the equipment specification (1.5% for TC and IC, and 3% for TN) with the Shimadzu TOC analyser. Error was 1.6% for TOC and 0.4% for IC with the Aurora TOC analyser, for which expected values would be 1.5% according to its manual. For the isotope measurements (Fig. 4D), it was not possible to compare the dissolved inorganic carbon values as the blanks were below the detection limits. However, it was clear that the dissolved organic carbon values for the blank were quite different from those of the sample. The large scatter in the blanks was due to poor sensitivity of the sensor for very low concentration samples. Values for
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Fig. 4. Automated measurements done with the robotic arm kit as an autosampler. (A) pH and alkalinity measured using a Metrohm 888 titrando. (B) Total carbon (TC), inorganic carbon (IC) and total nitrogen (TN) measured using a Shimadzu TOC analyser equipped with a total nitrogen analysis module. (C) Dissolved inorganic carbon (DIC) and dissolved organic carbon (DOC) measured using an Aurora TOC analyser coupled to a Thermo-Fisher Delta V plus isotope ratio mass spectrometer. (D) DIC and DOC carbon stable isotope ratios (δ 13 C) measured with the Aurora and the Delta V plus. Blank was Milli Q water, and sample was a solution of bicarbonate and urea dissolved in Milli Q water, for (B)–(D), and tap water for (A).
non-blank samples had a variation of 0.4h (DIC) and 0.05h (DOC), which are commonly reported for these measurements (St-Jean, 2003; van Geldern et al., 2013).
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4. Conclusions We demonstrated that a robotic arm kit can be an inexpensive, easy to build and universal autosampler for water samples in diverse kinds of analyses. No knowledge of electronics was needed to build the autosampler, and repeatable measurements without significant carryover effects were possible for alkalinity, pH, total carbon, total nitrogen, total organic carbon and total inorganic carbon (including carbon stable isotopes for the last 2). The set-up should also work for other kinds of water analyses, and thus it can be a very attractive option for laboratories in a limited budget. By using the files provided in http://100dollarautosampler.comli.com/ScriptsAndOthers.zip, anyone who acquires the robotic arm kit should be able to build an autosampler identical to the one described here at a very low cost. By using the scripts provided as examples, the robotic arm can be integrated to any laboratory instrument, provided it has a GUI. Some improvements in the setup are possible. The configuration presented here allows for a maximum of only 21 samples measured automatically. The sample tray, however, has 26 positions. If an automated rinsing device was used together with the robotic arm, 26 samples could be measured. This and other possible solutions can easily be incorporated by the setup, as it relies only on computer scripting to integrate its different parts. People with knowledge on electronics would be able to make a robotic arm themselves, and, with microcontrollers like arduino (Zhang et al., 2013), and using scripting (Carvalho, 2013), could make personalized devices with virtually unlimited applications (Pearce, 2014a). The approach described in this paper can be seen under the broader light of ‘‘open source laboratory’’, in which alternative equipment, not primarily designed for being employed in laboratories, or equipment fabricated in the laboratory itself, are adapted for laboratory tasks enabling significant reduction in costs. Several examples can be found, including micro-centrifuges, orbital shakers and colorimeters (Anzalone et al., 2013; Pearce, 2012, 2014b). Other examples are the adaptation of 3D printers to perform laboratory tasks (Gross et al., 2014; Symes et al., 2012). It can be expected that the applications of such alternative technologies will become more common with the popularization of accessible, easy-to-use microcontrollers, and scripting. Acknowledgement This work was funded by an Australian Research Council Linkage Grant (LP110200975) awarded to BDE. Appendix A. Supplementary data Supplementary material related to this article can be found online at http://dx.doi.org/10.1016/j. mio.2014.06.001. References Anzalone, G.C., Glover, A.G., Pearce, J.M., 2013. Open-source colorimeter. Sensors 13, 5338–5346. APHA, AWWA, WEF, 1996. Total organic carbon. Standard methods for Examination of water and waste water, 5.19–15.25. Bradshaw, A.L., Brewer, P.G., 1988. High precision measurements of alkalinity and total carbon dioxide in seawater by potentiometric titration — 1. Presence of unknown protolyte(s)? Marine Chem. 23, 69–86. Carvalho, M.C., 2013. Integration of analytical instruments with computer scripting. J. Lab. Automat. 18, 328–333. Gross, B.C., Erkal, J.L., Lockwood, S.Y., Chen, C., Spence, D.M., 2014. Evaluation of 3D printing and its potential impact on biotechnology and the chemical sciences. Anal. Chem. 86, 3240–3253. Pearce, J.M., 2014a. Cut costs with open-source hardware. Nature 505, 618. Pearce, J.M., 2014b. Open-Source Lab: How to Build Your Own Hardware and Reduce Research Costs. Elsevier, Waltham. Pearce, J.M., 2012. Building research equipment with free, open-source hardware. Science 337, 1303–1304. Shimadzu, 2010. Total Organic Carbon Analyzer TOC-L CSH/CSN User’s Manual. Shimadzu corporation, Kyoto. St-Jean, G., 2003. Automated quantitative and isotopic (13 C) analysis of dissolved inorganic carbon and dissolved organic carbon in continuous-flow using a total carbon analyser. Rapid Commun. Mass Spectrom. 17, 419–428. Stumm, W., Morgan, J.J., 1981. Aquatic Chemistry, an Introduction Emphasizing Chemical Equilibria in Natural Waters. John Wiley and Sons, New York. Symes, M.D., Kitson, P.J., Yan, J., Richmond, C.J., Cooper, G.J.T., Bowman, R.W., Vilbrandt, T., Cronin, L., 2012. Integrated 3D-printed reactionware for chemical synthesis and analysis. Nature Chem. 4, 349–354.
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van Geldern, R., Verma, M.P., Carvalho, M.C., Grassa, F., Huertas, A.D., Monvoisin, G., Barth, J.A.C., 2013. Stable carbon isotope analysis of dissolved inorganic carbon (DIC) and dissolved organic carbon (DOC) in natural waters – Results from first worldwide proficiency test. Rapid Commun. Mass Spectrom. 27, 2099–2107. Williams, P.M., 1992. Measurement of dissolved organic carbon and nitrogen in natural waters. Oceanography 5, 107–116. Zhang, C., Anzalone, N.C., Faria, R.P., Pearce, J.M., 2013. Open-source 3D-printable optics equipment. PLoS_One 8, e59840.