Liquid Chromatography Fundamentals and Separation Theory
Liquid Chromatography Fundamentals and Separation Theory
This domain tests whether you can explain and predict retention. Expect questions on retention factor, selectivity, plate count, resolution, isocratic versus gradient behavior, and how pH, organic modifier, and temperature shift a separation.
The four numbers that describe a separation
- Retention factor k = (tR − t0)/t0. Target roughly 1–10; k < 1 is poorly retained and vulnerable to matrix effects.
- Selectivity α = k2/k1. It reflects chemistry (stationary phase, modifier, pH) and is the fastest lever on resolution.
- Efficiency N = 16(tR/w)² (w = baseline width) or 5.54(tR/w½)². N rises with column length and falls when flow exceeds the optimum.
- Resolution Rs = 2(t2 − t1)/(w1 + w2) = (√N/4)·(α − 1)·(k/(1 + k)). Rs ≥ 2 is baseline; 1.5 is the usual acceptance limit.
Gradient fundamentals
In reversed phase, retention falls roughly linearly with %B (linear solvent strength). Gradient steepness, in %B per column volume, controls peak capacity and sensitivity: shallower gradients resolve close pairs better but dilute peaks and lengthen runs. pH matters most for ionizable analytes - operate at least two units from the pKa, because retention changes sharply near it.
Worked example
A method has N = 10,000, k = 4, and α = 1.05. Rs = (100/4)(0.05)(4/5) = 25 × 0.05 × 0.8 = 1.00 - not acceptable. Because Rs scales with √N, reaching 1.5 needs (1.5/1.0)² = 2.25× the plates, about 22,500. Improving α is cheaper: raising α to 1.075 at the same N gives 25 × 0.075 × 0.8 = 1.5.
Traps
Using t0 where tR belongs in the N equation; reporting Rs without the widths used; assuming a longer column fixes a coelution (α = 1 defeats any N); ignoring extra-column volume on small-ID columns; comparing gradient retention across systems with different dwell volumes.