Many years ago, when I started my first job as an analyst, I remember being trained on the GC. This was before the typical Chromatographic Data Systems like Chemstation or Chromeleon were prevalent. Most of our GC’s were 5890’s, and in one of the labs, we were still using strip chart recorders. It was amazing to me when my trainer was able to look at the chromatogram and name all the peaks. The CDS was in the Sr. Analyst office that only he had access to, it was DOS based, I never learned how to use it. We just ran the samples and reported the numbers.
My trainer told me stories of how they used to process the data, he showed me a slide rule, a strange ruler that I had no idea how to use. He also showed me a rolling cutting tool nearly the shape of a pencil, as well as an analytical balance, all seemingly unrelated. But before the CDS was commonly available, this is what they used. I never processed the data this way, but it makes sense. To process the data, they would take the cutting tool and trace out the peaks, cutting them from the strip chart. Then they would carefully weigh each peak out and divide the weight of the peak by the sum of the peaks, multiplying each by 100%, and now you have area percentage of each peak! Gives a whole new meaning to “manual integration”. Don’t ask me what the slide rule was for, maybe someone can comment if they know.
Today, when most people think of GC analysis, they only think of the result, not of the chromatogram. They don’t know how this result was calculated, have no concept of integration. Most people know how to calculate an area of a square, could probably do a triangle, maybe a circle, but the area under a curve? Probably not. Cutting out the peaks and weighing them was such a clever solution. And what I love about it the most is how intimate you would have to be with the chromatogram, it wasn’t about just looking at it. Early chromatographers really understood the chromatograms. Chromatograms reveal so much. I remember after working weeks on a challenging GC method and finally getting the resolution I wanted, I showed it to my manager and said, “look how sexy this chromatogram looks!”. She looked at me stunned and confused, so I followed up “curves in all the right places!” Note: I don’t recommend saying that in today’s workplace.
So why does the chromatogram matter?
Well, because it is very revealing. There is information you can’t find in the numbers. For example, I once got a call from an engineer complaining about our D86 distillation results. The initial and final boiling points were too far apart. If you are not familiar with D86, you measure out 100 ml of sample into a distillation flask and heat it up at controlled rate. Then condense the vapor and capture it in the receiver where an electronic sensor tracks the volume. This is a physical test, and it is hard to get wrong. The placement of the temperature sensor is important, but it likely won’t change the data by more than a few tenths. I had heard about this happening before, and the technicians usually would rerun the sample, adjusting the temperature sensor placement. I usually did not have to get involved. This time was different, as sensor placement was not working, and the range was nearly two degrees off. The nice thing about physical tests is that the laws of physics apply, matter can neither be created nor destroyed. When I heard about the problem, I knew there were heavies in the sample. I mentioned this to the engineer and his response was that the GC data looks good, so there is something wrong with the D86.
I immediately looked up the chromatogram of the sample, and what I found was that there were several peaks at the end of the run that were not integrated, meaning they were not included in the GC report. The technician either did not look at the chromatogram, or did not understand that the peaks were not integrated. This problem had persisted for a week, it had become worse, but it could have been caught earlier, had verification with the chromatogram been performed properly.
Today’s laboratory is inundated with samples, and everybody wants their data yesterday. This was a frustrating and costly situation, but it is a self-inflicted wound. Today’s technician is expected to push button and report results, and training programs leave a lot to be desired. Skill requirements are lowered to save money. Procedures are not enough, technology is not enough, the people are who will make or break your quality program, and we need to take the time to learn how to be an analyst, not just a technician. We also need to take the time to communicate with our engineers and operations, everybody holds a piece of the puzzle believing it is the most important piece, never realizing that the piece isn’t important till it’s placed into the puzzle.