Cars, internet, airplanes, people, everything is getting faster, including chromatography. The ultimate goal for chromatographers is to be able to achieve analyses in shorter run times without compromising the resolution, efficiency, and sensitivity that is strived for during method development. The wide availability of modern stationary phase packing materials and column dimensions makes this goal achievable to all chromatographers without, necessarily, the need for expensive UHPLC equipment.
There are a few modifications which can be easily made, to both the HPLC system and column, which will achieve the desired goal of reduced analysis time. This article will provide some tips and tricks as well as detailing the theory behind the chromatography
Figure 1: Original chromatographic method to be optimized.
L = column length, dc = column diameter, dp = particle size
Sensitivity, or signal to noise ratio, is related to the concentration at the peak apex (Equation 1).
Sensitivity can be increased by reducing column length, reducing internal diameter, and increasing efficiency (i.e. smaller particle size, minimize extra system/column volume, increase flow rate etc.).
Ultimately the most effective way to maximize sensitivity is to reduce background noise.
N = efficiency
Vi = injection volume
L = column length
dc = column internal diameter
k = retention factor
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Simply shortening the HPLC column reduces separation time; however, resolution will also be reduced due to a decrease in the plate number (available stationary phase surface). In general column length is directly proportional to retention time, column efficiency, and backpressure. Reduction of column length is acceptable as long as column efficiency remains sufficient for separation; therefore, when decreasing the column length as a means to decreasing analysis time the efficiency of the peaks must be considered and improved if necessary.
« Figure 4: Effect of reducing column I.D. and decreasing
flow rate (maintain constant linear velocity).
Achieving increased linear velocity can be achieved in several ways, however the combination of eluent flow rate and column internal diameter ultimately define the achievable linear velocity with any particular column.
Lc = column length
t0 = hold up time
A decrease in column internal diameter will result in an increase in back pressure.
η = viscosity
F = flow rate
L = length
K° = specific permeability
r = column radius
dp = particle diameter
Where any of the numerators increase, flow (F) or column length (L) for instance, a resultant increase in back pressure will be observed. Where any of the denominators decrease, column radius (r) or particle size (dp) for instance, an increase in back pressure is also observed. Note that the radius and particle size functions are raised to the second power, thus, causing their impact on back pressure to be much more dramatic.
Larger diameter HPLC columns require higher flow rates; therefore, larger volumes of mobile phase will be used. Changing from a 4.6 mm (1) to a 3.2 mm (2) ID column can reduce the flow rate and solvent volume required to reach the same optimum linear velocity without increasing the run time. The new flow rate can be calculated using Equation 5.
F = flow rate (mL/min)
dc = column diameter (mm)
dp = particle diameter (μm)
Note: For columns with the same particle size the last term becomes obsolete.
When column internal diameter is decreased an increase in sensitivity (2-3 fold) can be expected when injecting the same analyte mass. This is due to there being an increased analyte concentration in the mobile phase.
HPLC instrumentation may need to be adapted for columns with very narrow internal diameters to minimize band broadening effects which result from extra column effects i.e. mixing volumes out with the column; these can be reduced by reducing tubing length and diameter, using a microvolume detector flow cell etc. Instrument manufacturers will be able to aid in recommendations for these types of alterations.
A change in column diameter (and particle size) will reduce the amount of stationary phase in the column which will affect the loading capacity, both the volume of sample and the mass of analyte which can be injected onto the column, along with the flow rates which can be used. Any loss of sensitivity obtained by reducing the injection volume is more than offset by the increase in sensitivity achieved by the other changes. Some guidelines for these parameters are listed in Table1.
Internal Diameter (mm)
Typical Injection Volume (µL)
Loading Capacity (mg)
Typical Flow Rates
Table 1: HPLC column dimensions, capacities, and flow rates.
Step 3: Reduce particle size and increase flow rate
« Figure 5: Effect of reducing particle size and increasing flow rate.
By reducing the particle size diameter, not only is the efficiency of the column increased (plate height (H) is reduced), but the optimum linear velocity at which minimum plate height achieved is also increased. More efficient peaks can be achieved at elevated flow rates, leading to a reduction in analysis time accompanied, potentially, by an increase in resolution. Shorter diffusion paths and, hence, increased mass transfer kinetics (C term from the Van Deemter equation) are one reason behind this reduction in plate height. Figure 6 and 7 show the relationship between particle size, flow rate (linear velocity), and plate height for columns packed with various silica particle diameters.
Figure 6: Effect of changing particle size on mass transfer.
Figure 7: Effect of changing particle size on chromatography.
It may seem that the smallest diameter particles will be the obvious choice for high efficiency separations; however, this benefit does come at a substantial price, that of increased back pressure. The pressure increase is inversely proportional to the square of the particle diameter as shown in Equation 6. Note the increase in backpressure when decreasing particle size in Figure 7.
It can be seen that reducing particle size when using traditional porous silica can result in high back pressures which may not be tolerated by traditional HPLC instruments. The use of superficially porous materials allows the use of particle sizes which produce lower back pressures (i.e. 2.6-2.7 µm) while still increasing efficiency and allowing the use of increased flow rates, which ultimately results in faster analyses. This is due to the increased mass transfer kinetics associated with superficially porous particles (C term of the van Deemter equation) for larger molecules (biomolecules) and an increase in packing efficiency and reduction in multiple path lengths through the column (A term of the van Deemter equation) for small molecules, which is demonstrated by the very flat van Deemter curves produced by this packing material type (Figure 8).
Increasing temperature can be used to speed up the HPLC analysis for several reasons. First, an increase in column temperature reduces the viscosity of the mobile phase and, therefore, the column backpressure is reduced, permitting faster flow rates. An increase in column temperature enhances analyte mass transfer (increasing efficiency). The use of high temperatures is limited by the boiling point of the mobile phase (although this will be affected by the system pressure as an increase in pressure increases solvent boiling point) and the thermal stability of the analyte. It should also be noted that increasing temperature may change the selectivity of a separation.
Figure 10: Effect of temperature. »
Gradient Elution Considerations
One of the most important parameters in gradient HPLC is the gradient steepness or rate of change of mobile phase composition over time. Gradient steepness is given by the mobile phase starting and ending composition and the gradient time. The steepness of the mobile phase gradient can have a significant effect on the separation. If gradient steepness is kept constant from run-to-run then peaks will elute in the same relative pattern. There are a number of simple equations which can assist with translating gradient HPLC methods to faster equivalents and some of these are explained alongside the simple method translator below.
Figure 11: Gradient method translator.
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