Other Integration Issues

The shape of the skim baseline cannot be controlled, as it is a proprietary part of the software. However, the results presented here suggest that further refinements in the skim function, or at least the addition of control to the skim function might provide somewhat better integration results. Such features would be hard to design, and execution by the user would be difficult in the absence of information on the peak shape of the parent peak. But successful implementation of such an algorithm would be a welcome addition to current chromatography software.

The errors described here highlight the difficulty of working with separations where one peak is significantly smaller than the other peaks. As noted earlier, low-level impurities can interfere with peaks of interest in many cases. In other situations, the impurities simply can cause a disturbance in the baseline that results in a change in the location of the peak start and stop points. For most analyses, such a change would not be noticeable, either visually on the chromatogram, or in the resulting data. However, when one peak of interest is small (less than 5% of other peaks), the changes caused by an impurity which is present even at levels below 0.1% can create significant integration errors. The analyst must be very careful in reviewing the baseline and integration points, to ensure that these errors are recognized and minimized.

Figure 5

The cause of this extended tail very near the baseline is not clear. It seems unlikely that this tailing results from the same mechanisms responsible for asymmetry at higher points on the peak. It would be interesting to study whether this tail is unique to the instrument, the column, the analyte, or some combination of them. But regardless of the source, conventional peak symmetry measurements will not detect this tailing, yet it has a significant impact on integration of small peaks that appear on the tail. Ultimately, it might be necessary to report peak symmetry values at 0.1–0.5% of peak height for challenging separation problems such as those described here.

Conclusions

When the second peak is small and resolution is at least 2.0, the skim method with height measurement produces accurate results. When the first peak is small, the drop–height combination provides the least integration error at all peak size ratios and resolutions. At resolution 1.5, with the second peak small and measuring at least 2% of the large peak, the drop–height method is more accurate, although there will be a small positive error in the result. For smaller second peaks and lower resolution, there are no methods that produce accurate results. The exponential skim–height procedure provides the least error, but it has a relatively large negative value. The Gaussian skim–height method also provides accurate results at resolution equal to 1.5, but the errors change significantly with changes in resolution. The drop method for very small second peaks produces a very large positive error. In general for large peak size ratios, resolution less than 1.5 should be avoided.

Most of the integration errors are due to extended tailing from the large peak, at levels very near the baseline. This region of the chromatogram must be examined carefully, and integration baselines must be drawn to follow this tail to minimize integration errors.