Optimizing resolution

Motion, and in particular diffiision, causes a further limit to resolution [14,15]. First, there is a physical limitation caused by spins diflfiising into adjacent voxels durmg the acquisition of a transient. For water containing samples at room temperature the optimal resolution on these grounds is about 5 pm. However, as will be seen in subsequent sections, difhision of nuclei in a magnetic field gradient causes an additional... 

A previous study was eairied out to optimize resolution and sean speetroseopie variables in order to improve tlie FT-IR signal. The baseline method was used to quantify tlie 0-H group band. 

In practice, it is more difficult to optimize resolution as a function of the relative retentlvity than to optimize retention. Thus, unless the mixture is very complex or contains components that are particularly difficult to separate it may be possible to optimize a particular separation using the linear equation (1.72) as demonstrated by Bttre [177]. Figure 1.13 illustrates the relative change in peak position for a polarity test mixture with two identical, serially coupled open tubular columns, coated with a poly(dimethylslloxane) and Carbowax 20 M stationary phases, as a function of their relative retentlvity on the second column. The linear relationship predicted by equation (1.72) effectively predicts the relative peak positions and indicates that a nearly... 

For the examination of wet mounts, the light of the microscope must be properly adjusted. To achieve optimal resolution, the condenser should be centered and focused for Kohler illumination (racked up). To achieve contrast of the objects in the field, light intensity is diminished with the iris diaphragm of the condenser rather than by lowering the condenser. 

To optimize resolution in lifetime-based assays, a comparison of relative estimates is always favorable. If the FLIM experiment is carried out in an environment where temperature cannot be tightly controlled, it is also convenient to cycle between different samples during the same experimental session, in order to average out thermal and other instrumental drifts. When applicable, this practice may be useful to suppress any nonrandom variation in the detection. 

Finally, it is important for optimal resolution and thus sensitivity to use a proper decoupling sequence when necessary, during both the evolution and detection... 

Tsuji and Goetz24 developed a quantitative high performance liquid chromatographic method for separating and measuring erythromycins A, B, and C, their epimers and degradation products. This method uses a /iBondapak Ci 8 reverse column with acetonitrile-methanol-O.2m ammonium acetate-water (45 10 10 25) as solvent. The pH and composition of the mobile phase may be adjusted to optimize resolution and elution volume. The authors utilized the procedure on USP reference standard and report a relative standard deviation of 0.64%. 

Finally, optimization means dealing with time and other improvements spanning the overall process. Optimizing the speed of the analysis is obvious, but optimizing resolution can improve the process as well (as we will see later). An economic optimization of individual analyses will result in time improvements throughout the process because it will liberate resources for other tasks. 

Wide range of emulsions commercially available differing in sensitivity and in crystal diameters to achieve optimal resolution. 

All the changes in I and A should be done in order to have negligible self-heating of the thermistor, and an amplifier must be selected having a noise as low as possible in order to obtain an optimal resolution value for the determination of small temperature changes. 

It is illustrative to compare Figure 5-58 with the equivalent result of the ALS analysis in Figure 5-55. The most striking difference is the number of iterations required to reach the outcome. RFA arrives at the optimal resolution, within the constraints, in 10 iterations. ALS, using equivalent constraints results in acceptable matrices C and A but even after 100 iterations the optimum clearly has not been reached. 

Owing to the instability of silica gel based columns at pH values <2.0 or >8.0, mobile phases must have a pH range of 2.1-7.5. Within this range, a large number of solvent systems have been described. Solvent systems are selected on the basis of several criteria optimal resolution, volatility, LTV transparency, biocompatibility, selectivity, viscosity, and cost. 

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