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Technical Note

In-Oleo Microgasometry of Nanoliter-Scale Gas Volumes with Image-Based Detection Gurpur Rakesh D. Prabhu, and Pawel L Urban Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.6b03634 • Publication Date (Web): 31 Oct 2016 Downloaded from http://pubs.acs.org on November 6, 2016

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Analytical Chemistry

Technical Note

In-Oleo Microgasometry of Nanoliter-Scale Gas Volumes with Image-Based Detection

Gurpur Rakesh D. Prabhu, Pawel L. Urban*

Department of Applied Chemistry, National Chiao Tung University 1001 University Rd., Hsinchu, 300, Taiwan

Word count: 3990 + (4 figures × 250) = 4990 (∼ 5 pages)

* Corresponding author: P.L. Urban ([email protected])

1 ACS Paragon Plus Environment


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ABSTRACT Gasometric assays involve measurements of the amounts of gases that are released during physical or chemical processes. The available instrumentation for gasometric analysis is generally difficult to use, and requires large sample volumes. In some cases, toxic materials (mercury) are involved in the analysis process. Here we propose a microscale gasometric assay using mineral oil as matrix. Microliter-volume (~ 2.5 µL) aqueous droplets, containing sample and reagent and/or catalyst, are introduced to the oil matrix, and merged. Nanoliters of gaseous products are released to the surrounding oil matrix forming tiny spherical bubbles. Due to the huge differences between refractive indices of the released gas and the surrounding liquids (aqueous assay solution, oil), the gas bubbles are clearly visible from the top, when the assay reservoir is illuminated from the bottom with light-emitting diodes. The released gas bubbles are documented by recording videos of the assay reservoir. Individual frames within these videos are then analyzed by a graphical software to obtain diameters of every gas bubble at each time point. Following a fixed period of time (typically, 560 s) after the sample/reagent droplet merger, the volume of the released gas scales with the amount of the substrate (analyte) present in the sample droplet. For example, hydrogen peroxide can be decomposed to oxygen by 0.44 U catalase enzyme, and semi-quantified in the range up to ~ 1.0 µmol. Glutathione can be detected in a twostep procedure ((1) oxidation of glutathione by hydrogen peroxide; (2) decomposition of the hydrogen peroxide residue by catalase).


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INTRODUCTION

Gasometry encompasses measurements of quantities of gaseous substances released in chemical or physical processes.1 Early gasometric measurements were demonstrated by JeanBaptiste Dumas in the first half of the 19th century.2 The apparatus and the method for gasometric analyses were further developed and applied in clinical studies by Donald Van Slyke in the beginning of the 20th century.3 In the early version of the Van Slyke apparatus, gas was liberated from liquid samples by mechanically vibrating the sample vessel, and collected above the sample. The overpressure exerted by the released gas was then determined by recording the displacement of mercury in the classical manometer.4 Typically, the volume of the sample was in the order of a few milliliters. Due to the pressing need to analyze small volumes of samples, and to reduce the expenditure of expensive chemicals, efforts were made to miniaturize gasometric measurements. In 1954, Samuel Natelson patented the design of a microgasometer that enabled measurements of gas volumes in the order of a few tens of microliters.5 In fact, the experimental setup proposed by Natelson was a down-sized version of the original Van Slyke’s apparatus. The microgasometry instrumentation was further mechanized to reduce manual labor.6 In the 1970s, efforts were made to simplify the designs of gasometers.7,8 In the 1980s, the progress in the development of gasometric methods slowed down – probably because of the proliferation of spectroscopic, electrochemical, and chromatographic methods, and the inability to cope with various technical challenges imposed by gasometric measurements. One such challenge is the requirement to confine the assay mixture into close (gas-tight) space, so that the volume of the released gas can be accurately



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determined. In most cases, the amount of the released gas is known only at the end of the assay, while real-time monitoring of gas release is not possible. Moreover, gasometric apparatuses are almost non-existent in standard chemical laboratories. Gasometry is used primarily as a niche technique (for example, in the wine-making industry), where largevolume samples can be supplied. The modern version of the Van Slyke apparatus still uses mercury – a highly toxic material. There is a need to develop miniature green analytical methods, which do not use toxic materials, and do not produce large volumes of waste.9 Gasometric analysis shall not be excluded from this trend. In order to limit production of chemical waste, there is a need to devise microscale analytical formats, which could compete with the conventional microtiter plate format. Along these lines, Hernandez-Perez et al. recently proposed evaporation-driven assays in microlitervolume droplets suspended on plastic pillars.10 In other work, Bwambok et al. used bubble wrap as an inexpensive carrier for storing liquids and performing assays.11 Mineral and organic oils are occasionally used as matrixes for chemical reactions. For example, reactions can be performed in micrometer-scale emulsion droplets.12-16 However, individual droplets in an emulsion cannot readily be addressed and monitored. Micro- and milli-meter scale droplets containing samples and reagents can be processed on microfluidic devices.17,18 In fact, digital microfluidics facilitates processing microscale samples, and delivering them to detectors in the form of microdroplets.19 The principles of electrowetting on dielectric can be used to manipulate microscale droplets as well as microscopic air bubbles.20 Nonetheless, the microfluidic technology is not yet available in many chemical laboratories.


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Here we propose a real-time microgasometric method capable of determining nanoliterrange volumes of gases liberated during reactions carried out on microliter-range volumes of samples and reagents. This method relies on formation of microscopic gas bubbles within an oil matrix, which can be photographed and sized. It can be executed using widely available and inexpensive consumables and pieces of equipment (Petri dish, silicone oil, micropipette, CMOS microscope). It does not use mercury, and it generates only sub-milliliter volumes of waste.

EXPERIMENTAL SECTION

Materials Acetic acid (49-51%, for HPLC), ammonium acetate, catalase from bovine liver (2000-5000 U mg-1), gum arabic, hydrogen peroxide, L-glutathione (reduced form), sodium hydrogen carbonate, and starch were all purchased from Sigma-Aldrich (St. Louis, MO, USA). Silicone oil (type: AR 20) was obtained from Uni-Onward (Taipei, Taiwan). Difco YM agar was from BD (Sparks, MD, USA). Water (for chromatography) was from Merck (Darmstadt, Germany). Tissue paper was from Kimwipes (Roswell, GA, USA). Filter paper was from Advantec (Toyo Roshi Kaisha, Japan). Pre-coated TLC-sheets (Alugram Sil G/UV254) were from Macherey-Nagel (Düren, Germany). Cotton wool and glass wool were obtained from local suppliers (Hsinchu, Taiwan). Polytetrafluoroethylene (Teflon) tape was from TBL.



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Apparatus and procedure In our previous work, droplet assays in oil matrix were combined with optical detection.21 In the current work, apart from replacing the optical detection with microgasometric detection, a few more technical modifications of the assay procedure were made. Briefly, a plastic Petri dish (∅ = 9 cm; assay reservoir) was filled with silicone oil (depth: 0.6 cm), and placed on top of an acrylic stand coated with tracing paper (Figure 1). A light-emitting-diode (LED) array (white, 6 × 8; Yi Yang, Hsinchu, Taiwan) was installed under an acrylic stand to illuminate the assay reservoir. When the LED array was powered with 8.8 V, the illuminance above the Petri dish was ~ 1940 Lux. A CMOS camera (UPG626; Upmost, Taipei, Taiwan) was mounted ~ 1 cm above the silicone oil. Two aqueous droplets (2.5 µL) were introduced consecutively to the oil matrix by micropipette. Unlike in the previous work,21 the second solution was directly injected to the first droplet without waiting for spontaneous droplet fusion. This minimized the time required to prime the reaction. The produced gas bubbles were instantly imaged by the CMOS camera during 1-2 minutes. The experiment was performed at room temperature (25 ± 1 °C).

Data treatment Videos were acquired using the UM5 software (version 2.306.4DAs; MicroLinks Technology Corporation, Kaohsiung, Taiwan), saved to AVI files, and converted to MP4 files using YTD software (version 5.7) before further treatment. Individual snapshots were obtained from the MP4 files using the VLC Media Player (version 2.1.2; Free Software Foundation, Boston,


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MA, USA). Unless otherwise stated, the diameters of the individual gas bubble footprints were manually determined for different time points with the aid of CorelDraw X6 software (version 16.1.0.843; Corel Corporation, Ottawa, ON, Canada). Alternatively, Matlab software (version R2014a 8.3.0.532 32-bit; MathWorks, Natick, MA, USA) with the circleFinder function could be used for automatic measurement of the diameters. The volume of the released gas was estimated based on the measured diameters of the bubble footprints using the Excel software (version 2010; Microsoft, Redmond, WA, USA).

RESULTS AND DISCUSSION

Proof of concept In the previously demonstrated micro-assay, aqueous droplets, containing samples and reagents, were introduced to an oil matrix by pipette, and fused, prior to optical measurement by spectrophotometry, fluorimetry, or chemiluminescence detection.21 While performing that assay, we noticed that small gas bubbles occasionally appeared in the matrix – probably because they were accidentally introduced to the oil or were formed due to an uncontrolled temperature increase of the experimental system. We then rationalized that the water-in-oil reactions producing gas could be monitored by a simple optical detection system without the need to measure light intensity (Figure 1). The size of the released gas bubbles could be correlated with the progress of the reaction. In order to prove the feasibility of such a microgasometric assay with image-based detection, we tested two reactions:



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NaHCO3 + CH3COOH CH3COONa + H2O + CO2↑ ,

2H2O2 2H2O + O2↑ .

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(eq. 1) (eq. 2)

In the first reaction, 2.5-µL aliquots of NaHCO3 and CH3COOH were sequentially introduced by micropipette into the silicone oil matrix, forming one 5-µL droplet. In the second reaction, the enzyme solution was introduced first, followed by injection of H2O2 substrate solution. The processes were filmed by the CMOS microscope until the reactions approached their completion. Figures 2A and 2B show typical images after the start of the reactions shown in eqs. 1 and 2, respectively. The gas bubbles had spherical shape, what can be inferred from both top view (Figures 2A and 2B) and side view (Figure 2C) images of the reaction chamber (see also Movie S1). In most cases, nanoliter-volume bubbles containing the product gases (CO2, O2), could be seen immediately after the injection of the second solution. In some cases, one bubble was observed, while in other cases, the reactions led to formation of multiple bubbles (< 50). Notably, the released bubbles showed some dynamics. Only few bubbles stayed on top of the reaction droplet. Most of the bubbles detached from the surface of the reaction droplet, moved up toward the oil surface, and disappeared from the video frames. Some of the smaller bubbles grew over few seconds, and merged with the neighboring bubbles (cf. Figure S1).

), released until any time point (ta), was The volume of the product gas (

determined according to the formula:

= ∑ + ∑ ,

(eq. 3)


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where n is the number of the bubbles present in the given time point (ta), m is the number of the bubbles that have left the oil matrix before that time point, while ri and rj are the corresponding radii. Please note that the refractive indices and diffraction may influence perception of the bubble radii. However, this would have negligible effect on quantification if calibration plots are acquired for specific gases. Importantly, the assay reaction needs to be slow enough in order to enable reliable recording of the early bubbles. Overall, the repeatability (RSD) of the in-oleo microgasometric assay (for the reaction in eq. 1) was ~ 5%,

while the reproducibility (6 days) was ~ 9% (Table S1). The uncertainty of depends

on the uncertainties of radius determination for each bubble. If many small bubbles are

formed during one assay, then the combined uncertainty ( ) will be higher than if one

or very few bubbles are formed:

$

= !∑ " # + ∑ " #

$

.

(eq. 4)

Clearly, the combined uncertainty is proportional to the square root of the total bubble number (i + j). The bubble number must depend on the reaction rate and the type of the product gas. The measurements of radii of small bubbles are also associated with greater relative error than the measurements of radii of large bubbles (Figure S2). This is because the dark rim in the footprints of small bubbles occupies a larger fraction of the area than the dark rim in the footprints of large bubbles. Considering the limited resolution of the imaging system (~ 20 µm pixel-1, or ~ 23 line pairs mm-1 based on the 1951 USAF target; Figure S3), measuring radii of small bubbles (< 100 µm) will be associated with a considerable error due to pixelation. Thus, a high precision of gas volume determination can only be achieved if



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relatively few (< 10) bubbles with large radii (≥ 100 µm) are shown in the acquired images. Despite our efforts to optimize the automated measurements based on image recognition, some of the bubbles were occasionally missed (Figure S4), thus the results presented in this report are based on manual sizing of the bubbles based on digital images.

Microgasometric monitoring of reaction progress We hypothesized that the volume of all gas bubbles released by the reaction droplet to the oil matrix represents the progress of that reaction. This hypothesis was verified by monitoring the total volume of the gas released to oil over time (Figure 3). To obtain the time-dependent data sets, individual frames from the video record of the in-droplet reaction (eq. 1) were analyzed using a graphical software. The measured diameters of individual bubbles were converted to volumes of CO2. The bubbles that disappeared during the reaction monitoring were measured shortly (~ 1 s) before they left the oil matrix, and they were included in the gas product volume (cf. eq. 3). As expected, the released gas volume depended on monitoring time as well as the concentration of the limiting reactant. When the concentration of one substrate is much lower than the concentration of the other substrate, the kinetics can be regarded as pseudofirst-order. The apparent rate constant (kapp = 0.024 ± 0.005 s-1) and the limiting volume of the

% released gas ( = 0.00836 mm3 ≈ 8 nL) could be obtained by fitting the collected data

sets (cf. Figure 3, open circles, 0.040 M NaHCO3 and 1.000 M CH3COOH), using the SPSS software (version 19; IBM, Armonk, NY, USA), with the equation:

% = (1 − ) *++ )

,

(eq. 5)


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% where is the accumulated momentary volume of the released gas, while is

the total volume of the released gas.

Enhancement of bubble production The measured product volume reflects the fraction of the product loaded to the bubbles. However, in the droplet-in-oil system, the release of gas-phase product is hindered by the interfacial pressure. The gas-phase product has little contact area with the liquid-dissolved product. It would be desirable to transfer much of the gaseous product from the reaction droplet to the bubbles within the oil matrix. In the case of slow reactions, a considerable share of the gaseous product may remain in the reaction droplet. Some of the product may even be lost due to the diffusion across the water/oil interface. The transfer of the gaseous product from the reaction droplet to the bubbles can also be promoted by providing gas nucleation sites. The gas bubbles that associate with the water/oil interface can themselves fulfill the role of nucleation sites. However, formation of the first bubbles in the slow reactions may be hindered by the lack of such nucleation sites. Some of the early points in the inset of Figure 3 are below the fitted first-order curve because much of the produced CO2 did not leave the solution phase, thus causing underestimation of the reaction rate constant. In order to promote formation of gas bubbles, we supplied various solid materials and solution additives to the reaction environment (Figure S5): cotton wool, glass wool, agar, filter paper, tissue paper, graphite powder, packing fiber, silica particles, starch powder, polytetrafluoroethylene tape, and gum arabic. Unfortunately, most of these materials have irregular structure, and introduce structural heterogeneities to the assay system, thus rendering



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the imaging process cumbersome. However, gum arabic (added to the catalase solution) did not have that disadvantage. It completely dissolved in the aqueous solution, and promoted the release of the product gas (Figure 4). It is known that gum arabic reduces the surface tension of water, thus liberating the dissolved gas.22,23 Although the reaction droplet does not contact atmospheric air, the interfacial tension at the border of the reaction droplet may still be reduced due to the presence of gum arabic.

Quantification of hydrogen peroxide The microgasometric method can readily be used in quantitative analysis of one of the substrates involved in the gas-releasing reactions. For example, in the case of the catalasecatalyzed decomposition of hydrogen peroxide (eq. 2), the main substrate can be quantified. From Figure S6 it is clear that the volume of the released oxygen scales with the concentration of hydrogen peroxide. In this case, different reaction times were used in order to generate acceptable numbers of bubbles with desired radii (see the discussion above). The linear fit to the data set obtained for catalase concentration of 0.050 g L-1 (0.44 U for a 2.5µL droplet) and reaction time of 20 s is particularly good. Hence, these conditions can be used for semi-quantitative determination of hydrogen peroxide. The tested dynamic range of this assay is 0.083-0.415 M (or 0.21-1.04 µmol, for a 2.5-µL droplet).

Quantification of glutathione To further confirm applicability of the microgasometric assay in detection of various analytes, we applied it in quantification of glutathione. The samples of glutathione (2.5 µL) were first


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reacted with hydrogen peroxide (2.5 µL 0.166 M) in microcentrifuge tubes. In this reaction, glutathione molecules are oxidized to form a product with disulfide bridge:24

2GSH + H2O2 GSSG + 2H2O.

(eq. 6)

The product solution (2.5 µL) was then introduced to the oil matrix, and merged with a catalase droplet (2.5 µL, 0.050 g L-1). The volume of the released oxygen was inversely proportional to the quantity of glutathione in the original samples (Figure S7). This result shows that the in-oleo microgasometric assay can be used for off-line detection of hydrogen peroxide residues following another redox reaction of hydrogen peroxide.

CONCLUSIONS

Using mineral oil matrix and a very simple imaging system, it is possible to perform microscale gasometric measurements. Arguably, the proposed method is the inverse of headspace hanging drop liquid phase microextraction, in which gases diffuse into microscale liquid droplets prior to analysis. Here, the nanoliter-volume gas bubbles released from microliter-volume droplets of reaction mixtures can readily be visualized using an inexpensive optical system operated in the light-transmission mode. Radii of the produced bubbles can be determined accurately based on the captured images. Such assays do not require test tubes or flasks. The oil matrix can be used for a long time because the postreaction droplets can readily be removed by pipette. The only required consumables are pipette tips. Importantly, unlike most other optical assays (spectrophotometry, fluorimetry,



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chemiluminescence detection), the optical microgasometric analyses are not affected by light intensity fluctuations: the images can be taken almost at any lighting condition using very simple light source and low-sensitivity camera. The cost of the entire apparatus is ~ 1000 USD (including the computer). Although precision of the assay does not depend much on the intensity, quality, and stability of the light source, it is strongly affected by the resolution of the digital camera used. Taking into account the decreasing prices of digital cameras with good resolution (e.g. in smartphones), we believe the method will find application in quick determinations performed in chemical laboratories – whenever, a suitable reaction leading to formation of a gas product can be found. The solubility of product gases in the reaction mixture and oil matrix leads to underestimation of the reaction yield. Thus, the microgasometric assays need to be calibrated using a series of standard solutions with different concentrations. While the operation of the experimental system used in this study is manual, the assay is amenable to automation – for example, by implementing pipetting robots, which are available commercially. In order to achieve full automation, it would be desirable to improve the image recognition algorithm for unsupervised sizing of the recorded gas bubbles.

ASSOCIATED CONTENT Supporting Information Available: - video file (S1); - additional table (S1);


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- additional figures (S1-S7). This material is available free of charge via the Internet at http://pubs.acs.org.

ACKNOWLEDGEMENTS We thank Ms Ssu-Ying Chen and Ms Ting-Ru Chen for conducting preliminary experiments and for discussions. We acknowledge the Ministry of Science and Technology, Taiwan (MOST 104-2628-M-009-003-MY4) for the financial support of this work. G.R.D.P. also acknowledges the National Chiao Tung University for PhD scholarship.



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REFERENCES

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Bunsen, R. Gasometry Comprising the Leading Physical and Chemical Properties of Gases. 2015, Forgotten Books, London.

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Dumas, J. B. A. Ann. Chim. Phys. 1831, 247, 198-213.

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van Slyke, D. D. Ber. d. Deut. Chem. Ges. 1910, 43, 3170-3181.

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van Slyke, D. D.; Stadie, W. C. J. Biol. Chem. 1921, 49, 1-42.

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Natelson, S. US Patent No. 2,680,060, filed 21/08/1951.

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O’Mara, T. F.; Faulkner, W. R. Am. J. Clin. Pathol. 1959, 31, 34-37.

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Phillips, R. US Patent No. 3,756,782, filed 22/02/1972.

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Trafton, J. E.; Nichols, P. E.; Haynes, R. US Patent No. 3,973,912, filed 10/08/1976.

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Tobiszewski, M.; Mechlińska, A.; Namieśnik, J. Chem. Soc. Rev. 2010, 39, 2869-2878.

10. Hernandez-Perez, R.; Fan, Z. H.; Garcia-Cordero, J. L. Anal. Chem. 2016, 88, 7312-7317. 11. Bwambok, D. K.; Christodouleas, D. C.; Morin, S. A.; Lange, H.; Phillips, S. T.; Whitesides, G. M. Anal. Chem. 2014, 86, 7478-7485. 12. Rotman, B. Proc. Natl. Acad. Sci. U. S. A. 1961, 47, 1981-1991. 13. Musyanovych, A.; Mailänder, V.; Landfester, K. Biomacromolecules 2005, 6, 1824-1828. 14. Engberts, J. B. F. N.; Fernández, E.; García-Río, L.; Leis, J. R. J. Org. Chem. 2006, 71, 4111-4117. 15. Bánsági Jr., T.; Vanag, V. K.; Epstein, I. R. Science 2011, 331, 1309-1312. 16. Urban P. L. New J. Chem. 2014, 38, 5135-5141.


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17. Agresti, J. J.; Antipov, E.; Abate, A. R.; Ahn, K.; Rowat, A. C.; Baret, J.-C.; Marquez, M.; Klibanov, A. M.; Griffiths, A. D.; Weitz, D. A. Proc. Natl. Acad. Sci. U. S. A. 2010, 107, 4004-4009. 18. Rakszewska, A.; Tel, J.; Chokkalingam, V.; Huck, W. T. S. NPG Asia Mat. 2014, 6, e133. 19. Abdelgawad, M.; Wheeler, A. R. Adv. Mater. 2009, 21, 920-925. 20. Zhao, Y.; Cho, S. K. Lab Chip 2007, 7, 273-280. 21. Chiu, S.-H.; Urban, P. L. Analyst 2015, 140, 5145-5151. 22. Coffey, T. S. Am. J. Phys. 2008, 76, 551-557. 23. Cao, C.; Zhang, L.; Zhang, X.-X.; Du, F.-P. Food Hydrocolloid. 2013, 30, 456-462. 24. Finley, J. W.; Wheeler, E. L.; Witt, S. C. J. Agric. Food. Chem., 1981, 29, 404-407.



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FIGURE CAPTIONS

Figure 1. Schematic illustration of the microgasometric assay setup and procedure.

Figure 2. Photographs of the water-in-oil droplets during microgasometric assay. (A) Top view (0, 30, 60, 90 s). Droplet 1: 2.5 µL 1 M acetic acid. Droplet 2: 2.5 µL 0.2 M sodium hydrogen carbonate. See Movie S1 for the corresponding video sequence. (B) Top view (5, 30, 60, 85 s). Droplet 1: 2.5 µL 166 mM hydrogen peroxide. Droplet 2: 2.5 µL 0.05 g L-1 catalase. (C) Side view (30, 60 s). Droplet 1: 2.5 µL 166 mM hydrogen peroxide. Droplet 2: 2.5 µL 0.05 g L-1 catalase. Scale bars (A-C): 1.0 mm.

Figure 3. Monitoring the total volume of CO2 released to oil over time (eq. 1). Concentrations of NaHCO3: ( ) 0.00; () 0.04; () 0.08; () 0.12; () 0.16 M. Concentration of CH3COOH: 1.0 M. Reaction time: 90 s. The inset shows the data set for 0.04 M NaHCO3 fitted with pseudo-first-order kinetic equation.

Figure 4. Influence of gum arabic on the volume of released oxygen during decomposition of hydrogen peroxide by catalase. Concentration of catalase: 0.05 g L-1. Concentrations of gum arabic: 0; 1; 2; 3; 4 g L-1. Concentration of hydrogen peroxide: 166 mM. Reaction time: 150 s. The error bars represent standard deviation (n = 3). T-test results: * p < 0.01; ** p < 0.005; *** p < 0.001.


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Figure 1 (one column)



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Graphical abstract


In-Oleo Microgasometry of Nanoliter ... - ACS Publications

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