6
The effect of the increased carrier gas flow on the temperature gradient is to effectively decrease the temperature gradient relative to the time the compounds stay on the column. This results in the peak capacity increasing due to the peak widths getting narrower and the temperature gradient effectively being decreased.
Keeping the phase ratio consistentKeeping the phase ratio consistent
If the phase ratio (Equation 3) is kept consistent, then the elution order of compounds will be the same. Table 2 shows that a 0.25 mm x 0.25 μm GC column has the same phase ratio as a 0.15 mm x 0.15 μm column, so will show the same elution order of compounds. However, the efficiency on the 0.15 mm column diameter is greater, allowing for a similar separation to be performed with a shorter column length.
If the phase ratio (Equation 3) is kept consistent, then the elution order of compounds will be the same. Table 2 shows that a 0.25 mm x 0.25 μm GC column has the same phase ratio as a 0.15 mm x 0.15 μm column, so will show ,relatively, the same elution order of the compounds. However, the efficiency on the 0.15 mm column diameter is greater, allowing for a similar separation to be performed with a shorter column length.
Equation 3 df Equation 3
β – Phase ratio of the column dc
– Column diameter (µm) – Film thickness (µm)
β – Phase ratio of the column dc – Column diameter (µm) df – Film thickness (µm)
Table 2: Phase ratio values to ensure correct dimensions are selected for optimising methods. 0.15 0.18 0.25 0.5 1 1.4 1.5 1.8 2.65 3 5
Column diameter, dc
(mm)
Column diameter, dc (mm)
0.15
0.15 0.18 0.25
0.180.32 0.250.53 0.32 0.53
Film thickness, df (µm) 0.15
0.18
It is therefore evident that reducing the column diameter improves the efficiency and will also reduce the amount of carrier gas that is required, however it also reduces the loadability of the stationary phase.
It is therefore evident that reducing the column diameter improves the efficiency and will also reduce the amount of carrier gas that is required, however it also reduces the loadability of the stationary phase.
250 300 417 533 883
533 444180320 160 80 57 53 44 30 27 16 9 883 736250530 265 133 95 88 74 50 44 27 13 320 530
250 347 444 736
90
125 160 265
45 63 80
133
32 45 57 95
30 42 53 88
25 35 44 74
17 24 30 50
13 15 21 27 44
16 27
Conclusion Conclusion
Replacing helium with hydrogen can be performed without any serious safety concerns arising if the appropriate source of hydrogen is used.
Replacing helium with hydrogen can be performed without any serious safety concerns arising if the appropriate source of hydrogen is used. The benefits associated with this are substantial not only in terms of significantly reduced carrier gas costs, but also in the ability to use this as a steppingstone to supercharge the chromatography, by moving to FAST GC. The resulting benefits in reduced analysis times, and even further reductions in carrier gas costs due to the lower flow rates utilised. It is often the case that individuals use the introduction of one change to allow for bigger changes to occur, and in the case of moving to hydrogen, it is not a case of increasing safety issues, but more of improving the separation, reducing costs and reducing analysis times.
250 208 150 75 38 27 25 21 14 13 8 300 250 180 90 45 32 30 25 17 15 9 5 38
417 347 250 125 63 45 42 35 24 21 13 208
0.25 150
0.5 75
1.4 27
1.5 25
1.8 21
2.65 3 14
1 8
= % 4&
Table 2. Phase ratio values to ensure correct dimensions are selected for optimising methods.
Film thickness, df (µm)
The benefits associated with this are substantial not only in terms of significantly reduced carrier gas costs, but also in the ability to use this as a steppingstone to supercharge the chromatography, by moving to FAST GC. The resulting benefits in reduced analysis times, and even further reductions in carrier gas costs due to the lower flow rates utilised. It is often the case that individuals use the introduction of one change to allow for bigger changes to occur, and in the case of moving to hydrogen, it is not a case of increasing safety issues, but more of improving the separation, reducing costs and reducing analysis times.
References 1. F. J. Santos and M. T. Galceran, J. Chromatogr. A., vol. 1000, pp. 125-151, 2003.
2. C. Witschi and E. Doelker, European Journal of Pharmaceutical and Biopharmaceutics, vol. 43, pp. 215-242, 1997.
3. K. Ahang, J. W. Wong, D. G. Hayward and P. Yang, Comprehensive Analytical Chemistry, vol. 61, pp. 55-95, 2013.
4. K. Kimata, K. Iwaguchi, S. Onishi, K. Jinno, R. Eksteen, K. Hosoya, M. Araki and N. Tanaka, J. Chromaogr. Sci., vol. 27, pp. 721-728, 1989.
5. H. Dagdougui, R. Sacile, C. Bersani and A. Ouammi, Hydrogen infrastructure for energy applications, C. 7. -. H. L. S. a. R. Issues, Ed., Academic Press, 2018, pp. 127-148.
6. L. Newcomb, M. Marucci and J. Green, “Explosion limits of hydrogen-oxygen mixtures from,” Physical Chemistry Chemical Physics, vol. 30, no. 23, pp. 15746 - 157752, 2018.
7. R. R. Baldwin and R. W. Walker, “The role of radical-radical reactions in hydrocarbon oxidation,” Combustion and flame, vol. 21, no. 1, pp. 55-67, 1973.
8. D. L. Baulch, J. F. Griffiths, W. Kordylewski, R. Richter, S. K. Scott and P. Gray, “Experimental Studies of the Oscillatory Combustion of Hydrogen in a Stirred Flow Reactor,” Philosophical transactions of the Royal Society of London. Series A: Mathematical, physical, and engineering sciences, vol. 337, pp. 199-210, 1991.
9. O. M. Egeiban, J. F. Griffiths, J. R. Mullins and S. K. Scott, “Explosion hazards in exothermic materials: Critical conditions and scaling rules for masses of different geometry,” International Symposium on Combustion,, vol. 19, no. 1, pp. 825-833, 1982.
10. R. S. Zahler and H. J. Sussmann, “Claims and accomplishments of applied catastrophe theory,” Nature, vol. 269, pp. 759-763, 1977.
11. J. B. Rosser, “The rise and fall of catastrophe theory application in economics: Was the baby thrown out with the bathwater?,” Journal of Economic Dynamics and Control, vol. 31, pp. 3255-3280, 2007.
12. B. R. Johnson, J. F. Griffiths and S. K. Scott, “Oscillations and chaos in CO + O2 combustion,” Chaos, vol. 4, no. 1, pp. 387-395, 1991.
13. H. Wang, T. Shen, S. Duan, Z. Chen and X. Xu, “Bistability for CO oxidation: An understanding from extended phenomenological simulations,” ACS Catalysis, vol. 9, pp. 11116 - 11124, 2019.
14. A. T. Winfree, “The prehistory of the Belousov-Zhabotinsky oscillator,” Journal of Chemical Education, vol. 61, pp. 661-663, 1984.
15. M. J. Golay, Gas Chromatography, D. Desty, Ed., London: Butterworths, 1958, pp. 62-64.
16. J. J. van Deemter, F. J. Zuiderweg and A. Klikenberg, “Longitudinal diffusion and resistance to mass transfer as causes of non ideality in chromatography,” Chemical Engineering Science, vol. 5, pp. 271 - 289, 1956. 17. E. Matisová and M. Dömötörová, J. Chromatogr. A. , pp. 199 - 221, 2003.
Read, Share and Comment on this Article, visit:
www.labmate-online.com/article Retention Modelling to Accelerate and Optimise Method Development of Biomolecules
The growing interest in biopharmaceuticals is a trend consistent over the past few years. Biopharmaceuticals are structurally complex and pose numerous challenges in drug development. Globally, R&D companies are working to combat the complicated drug analysis necessary for large molecules, while trying to reduce laborious method development.
Retention modelling has proven to be a successful technique in accelerating method development and optimisation. Pharmaceutical companies (like Novo Nordisk and Merck) are employing variations of this technique to integrate computer-assisted analysis with screening platforms for their chromatographic modelling.
Their method development strategy typically involves screening a wide range of columns and mobile phases that are known to generate large differences in selectivity. From these, the most promising column and mobile phase are selected, and a retention model is built by conducting a limited number of experiments. The retention model is then applied in silico to find the optimal temperature and gradient, assessing method robustness. In silico modelling is an effective tool to conduct fewer experiments and identify optimal conditions, improving the overall screening outcome and generating robust LC methods.
ACD/Labs’ LC Simulator functionality is used by Novo Nordisk and Merck, as part of their screening process to analyse the most comprehensive set of conditions. From there, they determine the best combinations of columns, stationary phases, and chromatographic techniques most suited for the sample. LC Simulator allows the user to define combined custom gradient and 2nd order temperature models (required for proteins) to find optimal selectivity and a suitable retention gradient. The results show the practicality and ease of use of the workflow and the modelling accuracy is shown to be the same for proteins and small molecules.
More information online:
ilmt.co/PL/v1Yn 59745pr@reply-direct.com PES Syringe Filters
One of the best all-around syringe filters for HPLC, LCMS and ICP-MS is the Advanced Quality AQ™ polyether sulfone (PES) membrane syringe filters when the sample size is very small or very precious and sample recovery is required. These filters are available from Microsolv Technology Corporation with either a 0.22 um or 0.45 um porosity, in a 4 mm, 13 mm, and 25 mm polypropylene device.
More information online:
ilmt.co/PL/RN8v 59741pr@reply-direct.com
INTERNATIONAL LABMATE - JULY 2023
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56
