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Our goal of evaluating the Normalized French Environmental Method 12673 required testing the method’s ability to derivatize nitrophenols and alkylphenols in addition to the chlorophenols the method was designed for. Unfortunately, nitrophenols proved challenging to derivatize at low concentrations. In an effort to improve the derivatization of nitrophenols, we experimented with the pH of the reaction mixture.
The original method requires 5 mL of 1 molar potassium carbonate (0.7 g solid potassium carbonate) to be added to 50 mL of water sample, followed by the addition of 1 mL acetic anhydride, then extraction with hexanes. In an attempt to improve the conversion of nitrophenols to acetic acid esters, the amount of potassium carbonate being added to the solution was increased, or replaced with sodium hydroxide. Our hope was that increasing the basicity of the solution would create a better environment for the leaving group, promoting the nucleophilic attack process.
A small experiment was designed in order to evaluate the effect of pH on derivatization of nitrophenol compounds. This experiment included both increasing and decreasing the pH of the derivatization reaction in order to observe the relative response from compounds, which were analyzed on the Rxi-5Sil MS column.
Figure 1: Three overlaid chromatogram showing peaks for (1) 2-nitrophenyl acetate, (2) 3-nitrophenyl acetate, and (3) 4-nitrophenyl acetate. Each overlaid chromatogram represents a derivatization in a different pH solution.
Only nitro-containing phenols were determined in this experiment. Nitrophenyl acetates performed significantly better than dinitrophenyl acetates, and were chosen to reflect to effect of pH. The pH 11.66 derivatization performed best for two of the three nitrophenyl acetates, followed by pH 9, and pH 13.5. The increasing pH, therefore, did not enhance the derivatization process. There appears to be a point at which the pH can impede the derivatization process; the increased pH was also observed to inhibit the derivatization of the alkyl and chlorophenol compounds.
The increased pH had a negative effect on the derivatization of these compounds. Despite being a higher concentration, the responses of the compounds derivatized at pH 13.44 are significantly lower than the responses of those derivatized at pH 11.66.
Peak symmetry is important for determination and quantification of compounds. In order to create a symmetric peak, the compound must be able to elute all at more or less the same time. If a compound interacts with the column itself (ex: by temporarily adsorbing to the fused silica surface), it delays travel and effects peak morphology, causing “tailing”.
When comparing EPA method 525.2 to NF EN 12673 for the extraction of phenols, peak symmetry was notably improved using NF EN 12673.
The hydroxyl group on phenol compounds is highly active and able to hydrogen bond with the silanol groups present to some extent in all fused silica GC columns. This is one possible causes of phenol peak tailing. Phenyl acetates, however, have an acetic acid ester group rather than a hydroxyl group, which greatly reduces compound activity, resulting in cleaner, symmetric peaks.
Relative response factors (RF) were calculated for each of 10 calibration points for pentachlorophenol and 12 calibration points for pentachlorophenyl acetate, to illustrate the effect of peak tailing. Ideally, relative response factors should be equal at each calibration point because they are normalized by concentration. Peak tailing, however, complicates the peak integration, which pushes the RF further from the “ideal”. The relative standard deviation (RSD) shows how close the RFs are to one another. The higher RSD in Figure 1 shows that the RFs deviated more from one another in the pentachlorophenol calibration, than they did in the pentachlorophenyl acetate calibration.
Figure 1: A graphical representation of RRF’s for pentachlorophenol (right) and pentachlorophenyl acetate (left) peaks used for calibration purposes. Concentrations used for calibration represent the concentration of phenols in the original water sample.
Accordingly, the peaks in the pentachlorophenol calibration exhibited more tailing than the peaks in the pentachlorophenyl acetate calibration.
From July 19th – 22nd 2016 Restek Corporation with the collaboration of the German Restek Office (Restek GmbH) attended the 39th ISEAC conference, organized from the “International Association of Environmental Analytical Chemistry” (IAEAC) at the Hamburg School of Food Science, lead by Prof. Dr. Markus Fisher. The central subject of the ISEAC-39 conference is the innovative use of analytical methods for the investigation of environmentally and food relevant questions.
The interesting concept of this conference series is to show the close connection between Food Safety Analysis and Environmental Analysis, as was mentioned by the vice-president of the Federal Institute for Risk Assessment (Bundesinstitut für Risikobewertung, BfR), Prof. Dr. Reiner Wittkowski, talking about “What goes in must come out – environmental impact on food safety”. In fact, both communities are often facing the same challenges, as shown by the discussion about the Glyphosate issue or about MOSH/MOAH, both of them related to food safety as well as to environmental aspects. The same co-incidence can be recognized in observing polyfluorinated surfactants like Perfluorooctane Sulfonate ((PFOS) or Perfluorooctane Acid (PFOA), widely used to impregnate breathable functional clothing. Prof. Wittkowski used these examples to explain the need and the challenges of proactive consumer protection, a concept which is followed strongly by the European Community.
One of the purposes of the Organizers of this conference series is the idea of “Thinking out of the Box”, an inbuilt series of talks with related topics out of different scientific fields not directly connected to analytical challenges. This interesting part of the conference showed up with talks from Nobel Laureate Prof. Dr. Robert Huber, giving a summary about his work about the “Beauty and Fitness for Purpose of Proteins” as well as Prof. Dr. Christoph Kutter, Director of Fraunhofer Research Institution for Microsystems and Solid State Technologies, talking about “Sensors for the Internet of Things”. As a high light for the Chromatography Community the talk of Prof. Dr. Alexander Makarov gave a short cut about the development of the Orbitrap Mass Spectrometer Technology.
During the conference, Restek could present its innovations in Separation Science. To honor the scientific work of those researchers who showed up with Posters, Restek opened the first poster session with a Champagne Reception to welcome the interested audience.
Restek Corp. especially wants to thank the group of Prof. Markus Fischer, the organizing young scientists are dedicated to make things possible, and the secretary of the IAEAC.
Last Sunday, I was sitting in the garden, recapping the experiences of attending the scientific conferences I had the pleasure to visit during this year. One of the honoring sessions has left a quite inspiring impact on my mind. In the beginning of the year, I had the opportunity to listen to one of the most experienced and successful scientists in our Chromatography Community, Dr. Hernan Cortes, who as one of the first researchers was recognizing the power of hyphenated techniques in Chromatography (he even experienced the LC/GC coupling as a helpful technique in solving practical challenges – Sorry, Dr. Cortes that I couldn’t believe that the evening before). He was honored with the LCGC Europe’s Lifetime Achievement Award during HTC in Ghent/Belgium in January.
Hernan Cortes always has an open heart and an open mind for young Scientists. Therefore his laudation talk had a clear focus on how to help Young Scientists to develop their skills, as they are the future not only for our field of Science. As my daughter is studying Biology at the University of Cologne in the moment, I was electrified by one of his slides, showing some bullet points he called his “Hernanisms”, which he claimed not be developed only by himself, but were taken over from him as some of the keys of his success. So I asked him to provide this slide to me, because I liked to share these ideas with my young daughter.
Re-reading these “Hernanisms”, I thought it would be valuable to share them with you as well, hoping that you may transfer these ideas to your young colleagues as well.
I have copied these Bullet Points below (my explaining comments in Grey, for I cannot recap his complete talk).
- Never stop learning and teaching.
- Normal is a setting on a washing machine
- No set roadmap.
- There is no “normal” path
- Intelligence, hard work, luck.
- –Two out of three don’t make it.
- Continuous improvement.
- Karma, help others and be true to yourself.
- Happiness percentage (in everything you are doing, in the end happiness should win over frustration)
- Time management.
- The only commodity you can never get back (….is wasted time ).
Restek is very aligned with these Short Cuts for our company also is dedicated to the idea of supporting young scientists, as our RASP (Restek Academic Support Program) may show.*
Thank you, Dr. Cortes for your inspiring work and thoughts.
*Please ask for our RASP program
Yesterday’s blog gave an overview of how choosing the wrong scan speed could be detrimental to the tailing factor evaluation. Before someone asks, I thought we’d spend today looking at the impact of scan speed on the decafluorotriphenylphosphine (DFTPP) tune evaluation.
I know I’ve covered this before, but here are the tuning criteria from EPA 8270 D (rev 5) intended for scanning quadrupole instruments:
126.96.36.199 – In the absence of specific recommendations on how to acquire the mass spectrum of DFTPP from the instrument manufacturer, the following approach should be used: Three scans (the peak apex scan and the scans immediately preceding and following the apex) are acquired and averaged. Background subtraction is required, and must be accomplished using a single scan acquired within 20 scans of the elution of DFTPP. The background subtraction should be designed only to eliminate column bleed or instrument background ions. Do not subtract part of the DFTPP peak or any other discrete peak that does not coelute with DFTPP.
To summarize, the tune evaluation consists of a background subtracted average of the 3 apex scans evaluated against the criteria in Table 3. Using the same instrument settings used in the tailing factor evaluation blog, let’s evaluate DFTPP at 3.1 and 5.9 Hz.
First, there is the qualitative chromatographic evaluation. Figure 1 is an extracted ion chromatogram showing the six major ion fragments of DFTPP, collected at 3.1 Hz. Notice that the green trace of m/z = 442 is out of sync with the other mass peaks. This is also the case, but to a lesser degree, in Figure 2, the extracted ion chromatogram of DFTPP collected at 5.9 Hz. This offset of the high mass peak is due to spectral tilting, which is one of the issues experienced when scanning too slow.
Spectral tilt occurs when the amount of an analyte entering the detector increases during an individual scan (mass/second). Temperature programing and constant carrier gas flow combined with high efficiency GC columns yields chromatographic peaks with very steep slopes. The 5975C used here scans from high mass to low mass because it takes less energy to reset from low to high. Using DFTPP as an example, it would stand to reason that if you slowly scan from m/z = 500 to m/z 35 while the amount of DFTPP entering the detector is increasing, the resulting value for m/z = 442 would be biased low, and the m/z = 51 value would be biased high. The opposite would be true for the tailing side of the peak, where the amount of DFTPP entering the detector is dropping over time. 3.1 Hz is slow enough to see these effects when the three scans specified by EPA 8270 (the peak apex scan and the scans immediately preceding and following the apex) are inspected individually (Figure 3, Figure 4 & Figure 5)
Consider that the mass spectrum for each “scan” is just a bar graph showing the response for each ion. In the absence of spectral tilt, there would be no change in the slope of a line drawn from the top of the bar for m/z = 51 to the top of the bar for m/z 442, as shown in Figure 6, when you compared each scan for a given compound.
To perform this tilt evaluation for the 3.1 Hz scan rate, we created an X,Y scatter plot, with the responses for m/z = 51 and m/z = 442 entered for each of the three scans used for the DFTPP evaluation (Figure 7). The slopes are very different.
Nearly doubling the scan rate to 5.9 Hz does not eliminate the spectral tilt, but it does minimize the effects. Looking back at Figure 2, it is clear the 3 scans used for the DFTPP evaluation are all clustered near the actual peak apex, when the 2 adjacent scans from the 3.1 Hz data were a ways down the front and back of the DFTPP peak (Figure 1). This clustering near the apex is reflected in the ion ratios of the 3 individual scans used for the tune evaluation (Figure 8, Figure 9, and Figure 10)
Evaluating the spectral tilt using the same X,Y scatter plot setup used for the 3.1 Hz evaluation shows less variability for the for m/z = 51 and m/z = 442 ions acquired at 5.9 Hz (Figure 11) and a much smaller range of slopes.
A box plot of responses for the averaged scans for the 3.1 Hz (Figure 3, Figure 4 and Figure 5) and 5.9 Hz (Figure 8, Figure 9 and Figure 10) evaluations highlights the reduced response variability for virtually all the ions of significance (Figure 12). This is because the faster scan rate allows repeated sampling in a zone where the concentration of analyte in the detector is fairly stable (the pseudo-plateau at the peak apex).
Over the course of two days, I evaluated 40 DFTPP tune verification runs – 20 at 3.1 Hz, and 20 at 5.9 Hz. One of the 20 tune evaluations collected at 3.1 Hz failed because the ratio of m/z = 68 to m/z = 69 exceeded 2.0. All 20 DFTPP runs collected at 5.9 Hz met all tune criteria. The 68:69 ion ratio was interesting because even though the variance for the 5.9 Hz data was larger than that of the 3.1 Hz data, the median was approximately 0.5 for the 5.9 Hz data though greater than 1.5 for the 3.1 Hz (Figure 13).
Overall, average tune performance between the slow and fast acquisition populations was similar (Figure 14 and Figure 15), even though there were zero failures in the 5.9 Hz data set. I suspect the lower scan to scan variability of the faster scan rate highlighted in Figure 12 makes the occurrence of an evaluation failing outlier less likely.
In my last blog (here), I promised an update on the impact of the detector scan speed on the tailing factor. I had speculated that a pentachlorophenol tailing factor value of 0.94 was more likely < 1.0 because of the scan rate, rather than column overload.
The examples I put forward here were collected on a system with a different configuration (Table 1), but the basic principles hold true. While most sources will tell you that you need 6 to 7 scans to accurately define a peak, this is only sufficient for reproducible peak areas. 6 to 7 scans are not necessarily sufficient for evaluating peak symmetry.
Figure 1 and Figure 2 are examples of pentachlorophenol peaks acquired at 3.1 Hz (Slow on Table 1) that show asymmetric peak apex assignment and a resulting bias in the calculated tailing factors. Figure 3 is an overlay of 9 injections that highlights the variability in peak apex assignment when a slow acquisition rate is used.
We can nearly double the acquisition rate by halving the number of samples that are averaged for each data point. Figure 4 is an example pentachlorophenol peak acquired at 5.9 Hz (Fast on Table 1) that shows little bias in the peak apex assignment. Figure 5 is an overlay of 8 injections that highlights the low variability in peak apex assignment when a fast acquisition rate is used.
Figure 6 and Figure 7 are graphical representations of the tailing factors calculated from the overlays in Figure 3 and Figure 5.
EPA 8270D has initial tailing factor criteria of ≤ 2.0 for both Pentachlorophenol (PCP) and Benzidine (BENZ). As we saw in Figures 1 and 2, using a slow scan speed of 3.1 Hz yielded a range of 0.94 to 1.69 for PCP on a new column, inlet liner and inlet seal combination. It is easy to envision a situation where analyzing a few extraction batches may leave the instrument unsuitable for further sample analysis, even after inlet maintenance. Figure 8 and Figure 9 are statistical demonstrations of reduced variability in the tailing factor calculation for both Pentachlorophenol and Benzidine when the faster acquisition speed is used.
I recently received some feedback on the previous posts in this blog series and was asked the question “what kind of carryover am I seeing?” The truth of the matter is that I struggled to answer this question. I believe this question needs to be qualified a little bit in order for me to answer it. So I am going to break the aforementioned general question into the following two specific questions:
- Am I seeing carryover at concentrations typically encountered (i.e., <100 ppbv)?
- Am I seeing carryover at concentrations out of this world (i.e., >500 ppbv)?
Why the qualification? Well, the answer is different for both questions. Also, the first scenario (i.e., concentrations <100 ppbv) is going to account 99.9% of ambient air samples a laboratory will encounter. In addition, remember that NJ LL TO-15 states that the calibration range “must be from 0.20 to 40 ppbv.” This means that the >500 ppbv scenario represents a blown-out soil vapor sample, which needs to be diluted and/or injected at a smaller volume so that it falls within the calibration range. In any event, in an attempt to answer these questions I analyzed a series of samples followed by blanks as follows:
- Experiment 1: Blank – 200 ppbv – Blank – 200 ppbv – Blank – 200 ppbv – Blank
- Experiment 2: Blank – 1,000 ppbv – Blank – 1,000 ppbv – Blank – 1,000 ppbv – Blank
I observed an average carryover of 0.03 and 0.17% for experiments 1 and 2, respectively. Refer to figures 1 and 2 (below) for a visual representation of what experiment 2 looks like.
Figure 1: Black trace = 1 ppmv, blue trace = typical blank, red trace = carryover sample analyzed immediately after 1 ppmv.
Refer to Figure 2 for a zoom.
Figure 2: Zoom of Figure 1. Black trace = 1 ppmv, blue trace = typical blank, red trace = carryover sample analyzed immediately after 1 ppmv.
Is this good? IDK… The interesting thing is that I cannot genuinely tell you what % carryover is good or bad, as I have never seen anything published by any of the manufacturers. So if I answered the question like this, I am not sure where this would take us. Personally, I think these numbers look great! Think about it… less than 1% carryover on an instrument expected to meet method criteria of ±30%. BUT…
We should note that these same carryovers correspond to 0.03 and 1.14 ppbv in the carryover runs for experiments 1 and 2, respectively. Now what does this mean? It means that when loading “hot” soil vapor samples onto your system for analysis, it would be wise to run them at the end of the sequence and with blanks/conditioning runs in between. Certainly do not try to analyze sub slab samples from Long Island and then samples from the High Sierras.
So to answer the original question: I would say nothing to speak of at typical concentrations and about what I would expect for a “hot” sample analyzed via a headspace, purge and trap, air preconcentrator, or any other analytical instrument containing a solid sorbent bed.
After coming back from a huge lunch at the Bellefonte Wok, a favorite Restek lunch spot, I’m completely stuffed, but I have to eat my words from a previous blog. In this blog, I made the case against using MS detection for headspace analysis of residual solvents in cannabis concentrates due to interference between the air peak from the headspace injection and propane. It turns out that’s absolutely not the case, as my colleague and Restek air chemist Jason Herrington argued when I first posted the blog.
During a trip to Trace Analytics in Spokane, WA, I had the opportunity to run cannabis residual solvents using the full evaporation technique with headspace GC/MS (FET-HS-GC/MS), and lo and behold, propane is resolved from the air peak as shown in Figure 1.
Figure 1: Propane is Resolved from Air Peak on the Rxi-624Sil MS using FET-HS-GC/MS (25ppm Standard)
Propane is still well-resolved even at higher concentrations where band broadening may become an issue (Figure 2):
Figure 2: Propane is Resolved from Air Peak Even at Higher Concentrations (500ppm Standard)
Given the close proximity of propane to air, the two peaks may co-elute under sub-optimal injection conditions, but the two peaks can be separated from one another easily under the chromatographic conditions published in this protocol.
Although I dismissed the use of MS originally, there are benefits that I failed to mention. In addition to the ability to confirm peak identity using mass spectra, sensitivity is improved over GC-FID for the later eluting compounds like benzene, toluene, and the xylenes (BTX). This is because these compounds produce higher molecular weight fragments (78, 91, 106 m/z), and MS detectors aren’t great at reliably detecting low mass fragments from solvents like propane, methanol, and butane (29, 31, 43 m/z). Luckily, the solvents that produce the lower molecular-weight fragments have much higher regulatory cutoffs than butane, toluene, and xylenes, so detectability via MS isn’t an issue. Figure 3 shows an extracted ion chromatogram of our low standard (0.5ppm) and the signal-to-noise ratio is very good for BTX. Note that this chromatogram was collected in scan mode, so even more sensitivity can be gained from the development of a selected ion monitoring (SIM) method.
Figure 3: Good Sensitivity is Achieved for BTX using FET-HS-GC/MS (XIC of 78, 91, 106m/z, 0.5ppm Level)
All this being said, there is one big caveat to the use of MS for analysis of residual solvents in cannabis concentrates: the limited linear dynamic range of MS detectors when compared to FIDs. Where a FID can produce a linear curve over several orders of magnitude, an MS detector has a dynamic range limited to about three orders of magnitude. This means that one curve covering the entire regulatory range (e.g. 0.5 – 5500ppm) cannot be run using MS. In fact, under the conditions listed in the protocol for this method, BTX ions begin to saturate the detector at 250ppm (Figure 4), and almost all major ions for all analytes are saturated at 500ppm (Figure 5). This results in quadratic calibration curves for our analytes over even this limited range of quantification (Figure 4 inlay). If we tried to extend the curve beyond 500ppm, even a quadratic fit would be inappropriate.
Figure 4: BTX are Saturated at 250ppm, Resulting in a Quadratic Calibration Curve (Inlay)
Figure 5: Almost All Compounds are Saturated at 500ppm
While quadratic curves aren’t inherently bad, most guidance suggests the use of a linear calibration curve if feasible. Since even a quadratic curve wouldn’t cover the full regulatory range, in the cannabis residual solvents analysis protocol I suggest breaking up calibration into high and low segments. These segments will vary by state due to different regulations, but the approach is the same. For some states with very high cutoffs (I’m talking to you, Oregon), a higher split will most likely have to be used for the higher range curves in order to avoid overloading the column. Please note that this protocol has been partially validated, but still needs some work in terms of internal standard choice and extending the range of quantification above 500ppm.
While I learned a lot in the development of this method, I think the most valuable lesson I learned is to never argue with the air chemist when it comes to volatiles analyses.
An introduction to the benefits of using split injection when performing semivolatiles analysis by 8270D – the instrument checkout mix
We have mentioned several times that the reduced residence time resulting from the fast sample transfer that occurs during a split injection reduces in-inlet degradation and adsorptive loss. Proof of this can be seen in the first run of the 8270 analysis batch – the tune, inlet inertness, and column performance verification check.
Section 7.6 of 8270D indicates that a 50 ng/µL solution of decafluorotriphenylphosphine (DFTPP), 4,4’-dichlorodiphenyltrichloroethane (p,p’-DDT), pentachlorophenol and benzidine should be used. Specifically, the total amount for each compound should be 50 ng or less; the concentration can vary.
- DFTPP is used to verify that the detector is properly tuned (more on this subject here).
- Degradation of DDT is not to exceed 20% – by the criteria listed in EPA Method 8081. Thankfully, Linx has already covered this topic in detail here.
- Benzidine and Pentachlorophenol:
- are to be present at their “normal” responses. This is vaguely worded – perhaps the intent was ± 20% like the CCV evaluation.
- should not exceed a tailing factor of 2 as calculated in Figure 1 of EPA Method 8270D (also blog Figure 1). NOTE: AB>BC is a symptom of fronting (i.e., column overload), indicating a need for less mass on column to properly perform the tailing factor check.
Figure 2 is an example of the system suitability check mix (cat# 31615) analyzed at 50 ng/µL (in dichloromethane) by a 1 µL splitless injection. Pentachlorophenol and benzidine tailing factors are 0.75 and 0.53 respectively, indicating column overload. At 50 ng on column, overload is not a surprise, but it could be problematic as the system gets dirty. The tailing factor is supposed to be a helpful metric to indicate when maintenance should be done before client samples are analyzed. Serious overload significantly biases the tailing factor measurement and can result in a value of less than 2.0, even when the inlet is dirty and maintenance should be performed.
Something else to consider: injecting enough material to overload the column not only negates the effectiveness of the tailing factor, but also the DDT degradation check and the pentachlorophenol and benzidine response check. It is likely the active sites in the inlet are also being overloaded, so you are not getting an adequate indication of inlet activity, either.
Figure 3 shows the same system suitability check mix analyzed by a 1 µL 10:1 split injection; the system configuration is the same as that used in Figure 2, except the single taper inlet liner with wool has been replaced with a split precision liner. Pentachlorophenol and benzidine now have reasonable tailing factors. The 0.94 for pentachlorophenol could indicate a slight overload, but this value of less than 1 is more likely due to the scan rate and peak apex assignment (read more here).
Finally, some evidence to support the initial claim –the fast sample transfer that occurs during a split injection reduces in-inlet degradation and adsorptive loss. We see improved tailing factors and the DDT breakdown number is significantly better. The improved breakdown number is not due to reduced sensitivity. As summarized in Table 1, the TIC area for DDT was actually higher under split because the gain factor was increased to maintain sensitivity at the low end of the calibration (another future blog topic).
Summer days are my favorite – hot, sunny, and full of fun. But one thing that’s really not fun is trying to track down contamination and/or carryover in your headspace-GC (HS-GC) system. I get questions about this topic pretty regularly, so I thought I would post a blog on the most common culprit for contamination and carryover – cold spots.
When performing HS-GC, the rule of thumb is that your sample vial should be the coolest part of your system prior to the head of your column. The reason for this is that HS-GC depends on the use of heat to drive volatile compounds into the headspace of your sample vial, where they are then sampled. If you’re using a loop-style system employing a transfer line, then your sample has to be transported a long way before it gets to the head of the column. If your sample encounters a sudden drop in temperature while in transit, then some of the less volatile (or more abundant) compounds in the sample may condense in that cooler area, which is known as a ‘cold spot’, even though it could be significantly warmer than room temperature. The term ‘cold’ is relative to the other temperatures present in your sampling system.
When working with systems employing transfer lines that must be plumbed into an existing inlet, the most common cold spot is the area between where the transfer line ends and the heated inlet begins. This area is circled in Figure 1.
Figure 1: Cold Spot between Heated Transfer Line and Injection Port
As you can see, there is a good amount of tubing that is exposed to room temperature between the end of the heating jacket for the transfer line and the heated inlet. Even though your analytes may be volatile enough to make it through a cold spot like this, over time contamination from less-volatile matrix components can build up in this area, and it will eventually bleed over into your inlet, causing ghost peaks during blank runs as shown in Figure 2.
Figure 2: Ghost Peaks from Contaminated Transfer Line
The contamination shown above is really severe, and usually looks like just a few persistent peaks in your sample and blank runs. Normally, contamination can be eliminated by curing the cold spot, then running a bunch of solvent blanks (e.g. DMSO or DMA) using a method with increased transfer line, needle, and valve oven temperatures.
But how can we cure a cold spot? Two relatively easy fixes will cure most cold spots in your system. The first is to reduce the size of the cold spot. Figure 3 shows how I re-plumbed the transfer line, making the tubing going to the inlet as short as I could get it. You might also notice that since I was doing plumbing anyway, I installed an EZ-Twist Top injection port, which is much more convenient than the old-style weldment shown in Figure 1.
Figure 3: Transfer line Re-Plumbed to Reduce Size of Cold Spot
Although the size of the cold spot has been reduced, there’s still a significant length of tubing that’s exposed to room temperature. This brings us to the second part of our cold-spot remedy – an easy way to keep exposed tubing warm: glass wool and aluminum foil. Simply cover all exposed tubing and the injection port with the wool and use the foil to keep everything further insulated and to keep those irritating wool fibers contained. The setup is shown in Figure 4, and while it’s not pretty, it is effective.
Figure 4: Cold Spot Insulated with Glass Wool Insulation (inlay) and Aluminum Foil
Remember to wear gloves when handling the wool; just like fiberglass insulation, it will make you itchy! Also remember that the wool I’m describing in this blog isn’t the same as the wool that’s used in areas of the instrument that come into contact with sample. There’s no need for deactivation of the insulating wool.
I hope that this blog was useful, and make sure to get out of the lab and have some fun this summer!