Flow rate optimization

For one off separations flow rate optimization is not strictly necessary. However, it does offer an additional level of optimization for long-term projects and ongoing manufacture. The ideal flow rate often determined for small molecules on stationary phases with 10 [xm particle size and 60-300 A pores is approximately 120 cm/h, where for the majority of peptides and proteins the figure is typically in the region of 100 cm/h. 

In order to accumulate the data for a van Deemter plot (described above) it is necessary to carry out a series of separations on a preparative column of at least 50 mm diameter. This can be done isocratically or using the gradient and optimum load conditions selected above. However, if the study is done using gradient elution the gradient length should be reduced in proportion to increased flow rate. Suggested linear flow rates for this study are 60, 75, 90, 105, 120 and 135 cm/h. These flow rates correspond to approximately 20, 25, 30, 35, 40 and 45 cm3/min for a 50 mm diameter column. 

Although it is not strictly valid to determine column efficiency using plate count theory under gradient elution the actual benefit 

Calculate the effective number of theoretical plates, N, and subsequently the value of H for each separation using the following formulae  

Time (minutes) Concentration of buffer B (% v/v) Flow rate (cm3/min) 

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Some kinds of chromatography require relatively little optimization. In gel permeation chromatography, for example, once the pore size of the support and number of columns is selected, it is only rarely necessary to examine in depth factors such as solvent composition, temperature, and flow rate. Optimization of affinity chromatography is similarly straightforward. In RPLC or IEC, however, retention is a complex and sensitive function of mobile phase composition column type, efficiency, and length flow rate gradient rate and temperature. 

Helium is the most common carrier gas and is compatible with most detectors. For a flame ionization detector, N2 gives a lower detection limit than He. Figure 24-11 shows that H2, He, and N2 give essentially the same optimal plate height (0.3 mm) at significantly different flow rates. Optimal flow rate increases in the order N2 < He < H2. Fastest separations can be achieved with H, as carrier gas, and H2 can be run much faster than its optimal velocity with little penalty in resolution.11 Figure 24-12 shows the effect of carrier gas on the separation of two compounds on the same column with the same temperature program. 

Solutions of 1.0 M hydrogen peroxide in acetonitrile and 4.45 mM trichlorophenol (TCP) in ethyl acetate were used as postcolumn reagents, with the flow rates optimized at 1.0 ml/min each. The chromatographic eluent ranged from 70 to 80% acetonitrile-4 mM sodium phosphate buffer at apparent pH 7.5. The absorbance and fluorescence wavelengths for coumarin tags were as follows ... 

The simplest and often the most cost effective way to combat friction is to reduce flow rate to a minimum. By no coincidence, this often leads to an increase in the efficiency of a separation since in many circumstances for preparative purifications, the less experienced have followed a linear scale-up from analytical column flow rates. In an ideal world each separation should, at some stage, involve a flow rate optimization. The fundamental principles behind this are discussed by JJ van Deemter[52 in what is probably the most cited paper in the history of chromatography. In summary, this suggests doing a graphical plot of separation efficiency versus flow rate and is particularly important for peptide purification where mass transport is comparatively slow. The van Deemter equation in simplified form can be represented as ... 

P. S. Williams, M. Zborowski, and J. J. Chalmers, Flow rate optimization for the quadrupole magnetic cell sorter. Anal Chem. (1999). 

Mode b is used mainly for flame AA and ICP spectrometric systems, which require specific sample uptake rates for achieving optimum sensitivities. The exit flow-rates of the separated phase are normalh too low to meet the demands of the detector, particularly when large phase ratios are used to achieve high EF values. For this reason a supplementary interface, composed of an additional sampling valve, is used to collect a defined volume of the separated phase (concentrate) under the low flow-rates optimized for the extraction and separation. The collected concentrate is then injected into a carrier and delivered to the detector at the required flow-rates for obtaining optimum detection signals. 

Coolant temperature and flow rate Optimizes coolant can eliminate need to chill coolant. 

The task of designing of extractive distillation columns, besides calculation of section trajectories, includes a number of subtasks. These are the same subtasks as for two-section columns and additional subtasks of determination of minimum entrainer flow rate and of choice of design entrainer flow rate. Optimal designing of extractive or autoextractive distillation includes optimization by two parameters - by entrainer flow rate and by reflux number. Figure 7.14 shows influence of entrainer flow rate on section trajectories at fixed value of parameter a = LfV)mlK j (as is shown in Section 6.4 (L/y) = K j). 

Optimal addition profile. Arzamendi etal. (1989) developed a so-called optimal monomer addition strategy. By using this method they demonstrated that within a relatively short period of time homogeneous vinyl acetate (VAc)-methyl acrylate (MA) emulsion copolymers can be prepared in spite of the large difference between the reactivity ratios. The reactor was initially charged with all of the less reactive monomer (viz., VAc) plus the amoimt of the more reactive monomer (viz., MA) needed to initially form a copolymer of the desired composition. Subsequently, the more reactive monomer (MA) was added at a computed (time variable) flow rate (optimal addition profile) in such a way as to ensure the formation of a homogeneous copolymer. 

As with distillation, no attempt should be made to carry out any optimization of liquid flow rate, temperature, or pressure at this stage in the design. The separation in absorption is sometimes enhanced by adding a component to the liquid which reacts with the solute. 

The most common alternative to distillation for the separation of low-molecular-weight materials is absorption. Liquid flow rate, temperature, and pressure are important variables to be set, but no attempts should be made to carry out any optimization at this stage. 

Figure 4.9 shows a plot of Eq. (4.12). As the purge fraction a is increased, the flow rate of purge increases, but the concentration of methane in the purge and recycle decreases. This variation (along with reactor conversion) is an important degree of freedom in the optimization of reaction and separation systems, as we shall see later. 

Thus loops, utility paths, and stream splits offer the degrees of freedom for manipulating the network cost. The problem is one of multivariable nonlinear optimization. The constraints are only those of feasible heat transfer positive temperature difference and nonnegative heat duty for each exchanger. Furthermore, if stream splits exist, then positive bremch flow rates are additional constraints. 

A variable-size simplex optimization of a gas chromatographic separation using oven temperature and carrier gas flow rate as factors is described in this experiment. 

This experiment describes a fixed-size simplex optimization of a system involving four factors. The goal of the optimization is to maximize the absorbance of As by hydride generation atomic absorption spectroscopy using the concentration of HCl, the N2 flow rate, the mass of NaBH4, and reaction time as factors. 

Duarte and colleagues used a factorial design to optimize a flow injection analysis method for determining penicillin potentiometricallyd Three factors were studied—reactor length, carrier flow rate, and sample volume, with the high and low values summarized in the following table. 

These factors make it necessary to reduce the amount of solvent vapor entering the flame to as low a level as possible and to make any droplets or particulates entering the flame as small and of as uniform a droplet size as possible. Desolvation chambers are designed to optimize these factors so as to maintain a near-constant efficiency of ionization and to flatten out fluctuations in droplet size from the nebulizer. Droplets of less than 10 pm in diameter are preferred. For flow rates of less than about 10 pl/min issuing from micro- or nanobore liquid chromatography columns, a desolvation chamber is unlikely to be needed. 

Finally, we note that the size and shape of the particles of the packing, the packing technique, and column dimensions and configuration are additional factors which influence a GPC experiment. In addition, the flow rate, the sample size, the sample concentration, the solvent, and the temperature must all be optimized. Details concerning these considerations are found in analytical chemistry references, as well as in the technical literature of instrument manufacturers. 

One of the conveniences afforded by curing PPS is that a single uncured feedstock can give rise to an entire family of cured polymers. The flow rates, ie, the extent of cure, of the cured polymers are optimized for specific appHcations. Table 1 shows typical melt flow values of cured PPS polymers for various types of appHcations. 

In the context of chemometrics, optimization refers to the use of estimated parameters to control and optimize the outcome of experiments. Given a model that relates input variables to the output of a system, it is possible to find the set of inputs that optimizes the output. The system to be optimized may pertain to any type of analytical process, such as increasing resolution in hplc separations, increasing sensitivity in atomic emission spectrometry by controlling fuel and oxidant flow rates (14), or even in industrial processes, to optimize yield of a reaction as a function of input variables, temperature, pressure, and reactant concentration. The outputs ate the dependent variables, usually quantities such as instmment response, yield of a reaction, and resolution, and the input, or independent, variables are typically quantities like instmment settings, reaction conditions, or experimental media. 

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