Column breakthrough

Vq is the column holdup volume (including the extra column breakthrough curve is the thick volume)... 

Aluminum oxides As(V) and As(lll) adsorption on activated alumina pH dependence, kinetics, and column breakthrough. Regeneration by desorbing with NaOH. Modeling with pH-dependent Langmuir isotherm (for As) and surface complexation model (for protons) Ghosh and Yuan (1987)... 

The LDF model is a realistic representation of the system with a surface barrier. Otherwise, k can be treated as an apparent mass transfer coefficient irrespective of the true transport mechanism which can be directly used in the design and optimization of adsorbers. This concept has been successfully used to analyze column breakthrough data for practical non-isothermal systems [18-20]. It substantially... 

Other parameters characterizing a PFAR are the column breakthrough capacity, Bc, the column saturation capacity, Sc, and the column efficiency, E, of the PFIEBR, which are calculated with the following equations [105] ... 

Other phenomena besides conformational processes can also lead to multizoning effects with polypeptides and proteins when they interact with adsorptive HPLC sorbents. The so-called split peak effect is probably the easiest of these phenomena to be identified and steps taken to remedy. The split peak effect is very often seen in HP-BAC, RP-HPLC, and HP-HIC and to a lesser extent in the HP-IEX of proteins.325-327 This effect is manifested by the presence of a weakly retained (or occasionally as a nonretained peak) and a more strongly retained peak with the bound-to-free ratio between the weakly retained to strongly retained species dependent on the diffusion and adsorption kinetics. An extreme case of the split peak effect involves the weakly interacting component elution in or near to the column breakthrough volume. In this case, the amount of protein in the breakthrough zone is influenced by the nominal pore diameter and ligand density of the sorbent, the flow rate, and the injection volume. This effect can be circumvented by... 

In a breakthrough experiment, the superficial velocity may be obtained by dividing the volume V of water collected in t time by the superficial area of the experimental column. Breakthrough experiments are invariably conducted in stationary beds. Thus, from the previous equations this superficial velocity is actually the relative velocity of the flowing water with respect to the bed, with Vj equal to zero. This relative velocity must be maintained in the actual column design, if the data collected in the breakthrough experiment are to be applicable. 

TABLE 23 Effect of pH on the Column Breakthrough Time for Organic Compounds Adsorbed on a Commercial Activated Carbon ... 

Figure 9.38. Schematic representation of the response of the chromatographic column for different adsorption isotherms (top). The column breakthrough of a step concentration change without disperson effects is shown (below) for different isotherms (a) linear and (b) convex. The abscissa tItQ is equivalent to the number of pore volumes eluted. (Adapted from Biirgisser et al., 1993.)...

To decompact, and relax the resin bed thereby reducing pressure drop and eliminating any tendency towards encouraging preferential flow paths, or channelling, which would otherwise lead to a reduced utilization of resin exchange capacity and premature column breakthrough. 

The overall result is that at column breakthrough ( exhaustion ) a qualitative description of the column is as illustrated, purely schematically, in Figure 7.3 where the hatched area represents exhausted resin... 

Figure 7.3 Distribution profiles (schematic) of exhausted and regenerated resin at column breakthrough...

In practice the exchange reactions depicted above are not complete owing to the leakage of residual ions as described previously in Chapter 7 (Column Breakthrough and Leakage ). 

Figure 6. Nonisothermal column breakthrough curve for water (37 % R.H.) from air on Laporte alumina at 26° C.

Table 7.6 Data from pilot column breakthrough test. Example 7.2.

A typical representation of column performance plots removal of the species from solution against the volume of effluent passed through the column. When measurable quantities of the cation to be removed exceed a predetermined level in the solution exiting the column, breakthrough is said to have occurred. 

Laboratory column experiments were used to identify potential rate-controlling mechanisms that could affect transport of molybdate in a natural-gradient tracer test conducted at Cape Cod, Mass. Column-breakthrough curves for molybdate were simulated by using a one-dimensional solute-transport model modified to include four different rate mechanisms equilibrium sorption, rate-controlled sorption, and two side-pore diffusion models. The equilibrium sorption model failed to simulate the experimental data, which indicated the presence of a ratecontrolling mechanism. The rate-controlled sorption model simulated results from one column reasonably well, but could not be applied to five other columns that had different input concentrations of molybdate without changing the reaction-rate constant. One side-pore diffusion model was based on an average side-pore concentration of molybdate (mixed side-pore diffusion) the other on a concentration profile for the overall side-pore depth (profile side-pore diffusion). 

Many one-dimensional solute-transport models have been developed and used to analyze column data. For a recent review, see Grove and Stollenwerk (13). Four different models were used in the study discussed in this article to simulate the shape of the column-breakthrough curves. All four models contain a one-dimensional solute-transport equation and use the Freundlich equation to describe sorption. They differ in the rate mechanism that is assumed to control transport of Mo(VI) from flowing phase to solid surface. The essential features of each model are summarized in Table III. 

Finite-difference techniques were used to compute numerical solutions as column-breakthrough curves because of the nonlinear Freundlich isotherm in each transport model. Along the column, 100 nodes were used, and 10 nodes were used in the side-pore direction for the profile model. A predictor-corrector calculation was used at each time step to account for nonlinearity. An iterative solver was used for the profile model whereas, a direct solution was used for the mixed side-pore and the rate-controlled sorption models. 

The four potential rate mechanisms were evaluated by calculating column-breakthrough curves for various parameter sets to obtain the most accurate correlation between observed column-breakthrough curves and calculated concentration data. The parameters pbf and pbs for the mixed side-pore and profile side-pore diffusion models were estimated from the 0.043 mmol/1 breakthrough curves. Simulations at other concentrations were made by changing only the solution concentration value in the Freundlich equation. Physical and chemical parameters common to all four models are listed in Table II. Results are for 0.096-, 0.043-, 0.01- and 0.0016-mmol/l columns. 

Table III. Comparison of the Four Transport Models Used to Simulate Column Breakthrough of Mo(VI)...

---