Proper optimization of peak capacities of analytical HPLC methods is unavoidable in the anal-ysis of samples containing large number of compounds. A well optimized method can of-fer the same peak capacity in much less analysis time, consuming much less solvents than a non-optimized procedure. Before any method optimization, the analyst should minimize extra column volumes by changing connection capillaries and detector cell, especially if ultra-high performance columns are used. In this Chapter the construction and application of Poppe plots were demonstrated in analytical method development. Poppe plots are suitable tools in opti-mization of peak capacities. In isocratic runs, one can optimize the width of retention window and column plate count separately. At the same time, gradient elution needs a holistic optimiza-tion. The parameters affecting the peak capacity generated by the chromatographic system are not mutually independent. Change of one parameter changes the optimal value of other pa-rameters as well. Fortunately, Poppe plots offer a general approach for the optimization of both isocratic and gradient separations. By the use of Python codes shared in this chapter, nomograms can be constructed that allow the determination of most of the optimal separation conditions. The use of Poppe plots in method development provide the analyst a simple and effective tool for optimization of HPLC analyses.
fi0 = 0.05 #initial eluent composition, ϕ0
k0, S = 1e6, 20 #parameters of linear solvent strength model dp, dP = 1.7e-6, 1200e5 #particle diameter and max. pressure drop
#retention factor of the last eluting compound at the beginning of analysis kfi0 = k0*np.exp(-S*fi0)
#---CONSTRUCTION OF ISO-∆ϕ LINES---#
ls = np.logspace(np.log10(0.05),0,100) #definition of range of column lengths
#iterate through different ∆ϕ values for dfi in [0.4, 0.5, 0.6, 0.7, .75, 0.8]:
u0s = dP*dp**2/(fi*eta*ls) #eluent linear velocities Hs = h(u0s*dp/dm, A, B, C)*dp #plate heights
t0s = ls/u0s #column hold-up times
tgs = kfi0*S*dfi*t0s/(np.exp(S*dfi)-1) #gradient times, see Eq. (1.40)
pcs = peakcap(tgs, fi0, dfi, t0s, Hs, ls, S, k0) #peak capacities, see Eq. (1.19)
plt.loglog(pcs, (tgs+t0s)/pcs, 'r--', linewidth=0.5) #plot iso-∆ϕ lines in log-log scale
#---PLOTTING OF CONSTANT tg+t0 LINES---#
pcs = np.logspace(1,3.4,100) #definition of range of peak capacities
#iterate through different t0+tG values for tgt0 in [1e1, 1e2, 1e3, 1e4, 1e5]:
#at each t0+tG, plot (t0+tG)/n with blue dashed line plt.loglog(pcs, tgt0/pcs, 'b--', linewidth=0.5)
#---CONSTRUCTION OF GRADIENT POPPE CURVES FOR DIFFERENT COLUMN LENGTHS---#
dfis = np.linspace(0.05, 1-fi0, 100) #definition of range of column lengths
#iterate through different column lengths that has practical relevance for length in [0.05, 0.1, 0.15, 0.3, 0.5, 1.0]:
u0 = dP*dp**2/(fi*eta*length) #eluent linear velocities H = h(u0*dp/dm, A, B, C)*dp #plate heights
t0 = length/u0 #column hold-up times
tgs = kfi0*S*dfis*t0/(np.exp(S*dfis)-1) #gradient times, see Eq. (1.40)
pcs = peakcap(tgs, fi0, dfis, t0, H, length, S, k0) #peak capacities, see Eq. (1.19) plt.loglog(pcs, (tgs+t0)/pcs) #plot curves in log-log scale
plt.xlim(2e1, 2e3) #set x limits
plt.ylim(1e-1,1e2) #set y limits
plt.xlabel('Gradient peak capacity, $n$') #label of x axis plt.ylabel(r'$(t_G + t_0) / n$') #label of y axix
plt.show() #show plot
Listing 1.6: Python code for generating nomorgram-like gradient Poppe plot.
Acknowledgement
The author acknowledges the financial support of the János Bolyai Research Scholarship of the Hungarian Academy of Sciences.
References
[1] J. C. Giddings, Maximum number of components resolvable by gel filtration and other elution chromatographic methods, Anal. Chem. 39 (1967) 1027–1028.
[2] U. D. Neue, Peak capacity in unidimensional chromatography, J. Chromatogr. A 1184 (2008) 107–130.
[3] J. W. Dolan, L. R. Snyder, N. M. Djordjevic, D. W. Hill, T. J. Waeghe, Reversed-phase liquid chromatographic separation of complex samples by optimizing temperature and gradient time: I. peak capacity limitations, J. Chromatogr. A 857 (1999) 1 – 20.
[4] J. C. Giddings, Comparison of theoretical limit of separating speed in gas and liquid chromatography, Anal. Chem. 37 (1965) 60–63.
[5] J. H. Knox, M. Saleem, Kinetic conditions for optimum speed and resolution in column chromatography, J. Chromatogr. Sci. 7 (1969) 614–622.
[6] G. Guiochon, Comparison of the theoretical limits of separating speed in liquid and gas chromatography, Anal. Chem. 52 (1980) 2002–2008.
[7] H. Poppe, Some reflections on speed and efficiency of modern chromatographic methods, J. Chromatogr. A 778 (1997) 3–21.
[8] G. Desmet, D. Clicq, P. Gzil, Geometry-independent plate height representation methods for the direct comparison of the kinetic performance of lc supports with a different size or morphology, Anal. Chem. 77 (2005) 4058–4070.
[9] X. Wang, D. R. Stoll, P. W. Carr, P. J. Schoenmakers, A graphical method for understand-ing the kinetics of peak capacity production in gradient elution liquid chromatography, J.
Chromatogr. A 1125 (2006) 177–181.
[10] L. R. Snyder, Linear elution adsorption chromatography. VII. Gradient elution theory, J.
Chromatogr. 13 (1964) 415–434.
[11] Cs. Horváth, S. R. Lipsky, Peak capacity in chromatography, Anal. Chem. 39 (1967) 1893.
[12] E. Grushka, Chromatographic peak capacity and the factors influencing it, Anal. Chem.
42 (1970) 1142–1147.
[13] H. Poppe, J. Paanakker, M. Bronckhorst, Peak width in solvent-programmed chromatog-raphy. i. general description of peak broadening in solvent-programmed elution, J. Chro-matogr. A 204 (1981) 77–84.
[14] L. R. Snyder, D. L. Saunders, Optimized solvent programming for separations of complex samples by liquid-solid adsorption chromatography in columns, J. Chromatogr. Sci. 7 (1969) 195–208.
[15] L. R. Snyder, J. W. Dolan, J. R. Gant, Gradient elution in high-performance liquid chro-matography: I. theoretical basis for reversed-phase systems, J. Chromatogr. A 165 (1979) 3–30.
[16] F. Gritti, G. Guiochon, Performance of columns packed with the new shell kinetex-c18 particles in gradient elution chromatography, J. Chromatogr. A 1217 (2010) 1604–1615.
[17] F. Gritti, C. A. Sanchez, T. Farkas, G. Guiochon, Achieving the full performance of highly efficient columns by optimizing conventional benchmark high-performance liquid chro-matography instruments, J. Chromatogr. A 1217 (2010) 3000–3012.
[18] S. Fekete, J. Fekete, The impact of extra-column band broadening on the chromatographic efficiency of 5cm long narrow-bore very efficient columns, J. Chromatogr. A 1218 (2011) 5286–5291.
[19] L. R. Snyder, J. J. Kirkland, J. W. Dolan, Introduction to Modern Liquid Chromatography, John Wiley & Sons, Inc., 2010.
[20] K. Horváth, F. Gritti, J. N. Fairchild, G. Guiochon, On the optimization of the shell thick-ness of superficially porous particles, J. Chromatogr. A 1217 (2010) 6373–6381.
[21] T. J. Causon, E. F. Hilder, R. A. Shellie, P. R. Haddad, Probing the kinetic performance limits for ion chromatography. ii. gradient conditions for small ions, J. Chromatogr. A 1217 (2010) 5063–5068.
[22] X. Wang, W. E. Barber, W. J. Long, Applications of superficially porous particles: High speed, high efficiency or both?, J. Chromatogr. A 1228 (2012) 72–88.
[23] S. Fekete, D. Guillarme, Possibilities of new generation columns packed with 1.3µm core-shell particles in gradient elution mode, J. Chromatogr. A 1320 (2013) 86–95.
time in current liquid chromatographic practice for monoclonal antibody separations, J.
Pharmaceut. Biomed. 141 (2017) 59–69.