DILUTION MODULE continued References
1. Bristow, T.W.T.; Ray, A.D. et al. J. Am. Soc. Mass Spectrom. 2014, 25(10), 1794–1802.
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Figure 4 – Dependence of diluted solution on stock solution concentration.
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Figure 5 – Automatic dilution with different stock solution solvents.
curve (from stock solution 2) and blue curve (from stock solution 1).
Similar tests were performed using different solvents, such as ACN/H2
O (40%/60%) and pure
ACN. For each solvent, similar stock concentra- tions were prepared (solution 1: 91 mg/L OS + 45.5 mg/L 4-MOS; solution 2: 182 mg/L OS + 91 mg/L 4-MOS; solution 3: 273 mg/L OS + 136.5 mg/L 4-MOS). ACN/H2
O (40%/60%) and pure
ACN were used as diluents by both the dilution pump and compensation pump. Figure 5 shows the plots for 182 mg/L octanoic acid in different solvents (MeOH, ACN, ACN/H2
O). The effect of
different solvents (with characteristics such as specific conductance, surface tension and vis- cosity) on the ionization efficiency of analytes is not remarkable since the three curves are not significantly separated. As expected, the dilution module can dilute different solvents. Decreasing the dilution ratio from 1:500 to 1:50 increases the peak areas of the diluted solution. In addition, there is an increase in peak area at each dilution ratio as the concentration of stock
solution increases, which results in different slopes of the diluted solutions (not shown).
It is possible to reduce the dilution flow rate to achieve dilution ratios such as 1:2 or 1:5. However, laboratory experiments showed a signal reduction when the dilution flow was below 0.3 mL/min. Therefore, the lowest dilu- tion ratio that can be achieved with this method is around 1:10.
Conclusion
A dilution module based primarily on a mass rate attenuator solves the problem of high concentration solution to the mass spectrom- eter. The low-flow compensation approach was used to circumvent the strong dependence of diluted solutions on the low flow rate of the microreactor. Although there are high standard deviations due to the effects from different flow rates and device performance, the process is automated and able to perform dilution ratios starting from 10.
AMERICAN LABORATORY 40 JANUARY/FEBRUARY 2017
12. Browne, D.L.; Wright, S. et al. Rapid Com- mun. Mass Spectrom. 2012, 26(17), 1999– 2010.
13. Toribio, A.; Destandau, E. et al. Rapid Com- mun. Mass Spectrom. 2009, 23(12), 1863–70.
14. Leister, W.; Strauss, K. et al. J. Comb. Chem. 2003, 5(3), 322–9.
15. Jeurissen, S.M.F.; Claassen, F.W. et al. J. Chro- matogr. A. 2007, 1141(1), 81–9.
16. Fleischer, H.; Hoffmann, D. et al. IEEE I2MTC 2015, 1561–6.
17. Do, V.Q.; Hoffmann, D. et al. PET ACECS 2016, 528–34.
Vinh Quang Do and Kerstin Thurow are with the Center for Life Science Automation (celisca), Fried- rich-Barnewitz-Str., 818119 Rostock, Germany; tel.: +49 (381) 498-7810; e-mail: vinh.quang@
celisca.de;
www.celisca.de. Heidi Fleischer and Dany Hoffmann are with the Institute of Automa- tion, University of Rostock, Germany. The authors wish to thank the Vietnam Ministry of Education and Training for the Project 911 Scholarship for financial support of this study, and the Federal Ministry of Education and Research Germany (FKZ: 03Z1KN11).
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