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Modifying QuEChERS for complicated matrices- Dry Samples

Before getting in to this discussion, I recommend reading my previous blog post first regarding classical applications for methods based on Quechers. https://blog.restek.com/quechers-dspe-selection-which-one-is-best/

QuEChERS methods were originally written to analyze pesticides in fruit and vegetable matrices, most of which have high water content and low fat content. More recently, the technique has been used for a greater variety of food and agricultural products, as well as other environmental matrices. It has also been adapted for analytes other than pesticides in some cases. We will discuss some of the possible modifications you may need to make for complicated matrices. For all of the sample types we will discuss, the best general references I can give are from the official QuEChERS website (quechers.com), maintained by CVUA Stuttgart, these specific documents:

For Extraction (Stage 1): https://www.quechers.com/pdf/reality.pdf

For dSPE Cleanup (Stage 2): https://www.quechers.com/pdf/cleanup.pdf

For greater detail, I found this reference useful: https://www.degruyter.com/view/journals/chem/open-issue/article-10.1515-chem-2015-0109/article-10.1515-chem-2015-0109.xml

For many samples, particularly food products, you may find it helpful to use the USDA database at https://fdc.nal.usda.gov/ to obtain a listing of content for water (as well as protein, total lipids, fatty acids, carbohydrates, sugars, and cholesterol).  We will discuss techniques for dry sample matrices in this blog post. Other types of sample matrices will be discussed in subsequent posts.

For samples with little or no water content, water must be added before using Quechers extraction salts. For these samples, reduce the sample weight from 10 g to 5 g or less and add 10 mL of water prior to adding acetonitrile and QuEChERS extraction salts. (For those using the AOAC QuEChERS method, the sample size is reduced from 15 g to 7.5 g or less and 15 mL of water is added.)  The sample weight should be adjusted according to the amount of chromatographic interference anticipated (or how “dirty” the matrix is perceived to be). Here are several examples of this technique. In some cases, such as cannabis, you might see total water volumes less than or greater than 10 ml, but the sample weights are adjusted accordingly as well.

For samples that contain a little bit of water but less than 80%, the amount of water can be adjusted accordingly to estimate a combined water content of 10 mL.  Some good examples of this technique are shown below.

Additional Resources:

This concludes discussion of dry sample matrices. Please look for the next post on samples containing high amounts of lipids and waxes.

Terpene Analysis Approaches – Part IV

We are back at it with another blog about terpene analysis! If you did not catch my previous post, be sure check it out here before moving on. Last time, I finished up by discussing how we would move away from analyzing terpenes in standards and dive into in-matrix analysis. Well…I lied. I’m sorry, but I PROMISE, we will get there because we did get there. First, I need to cover a couple important things.

I had the opportunity to visit a cannabis lab in Santa Rosa, CA, and they let me run their GC’s for a week. Since Restek is located in PA, we are unable to currently bring cannabis into our Innovations Lab, so in order to get our hands on this sticky material we look for collaborations. Having done the preliminary work at Restek and figuring out which sampling approach I wanted to test, I could really get cracking on further method development with their team. The first thing I wanted to complete was a calibration using DI-SPME, which initially started out as a pain, but once we optimized some of the sampling parameters, we were able to gather some great data!

Under the sampling conditions that we were used in the previous blog post (see Table 1 below), we obtained the results shown in Figure 2.

Table 1. DI-SPME Parameters

It would be cumbersome to show you the results for all of the targeted terpenes, so Figure 1 gives a representation of some the terpenes of interest over the volatility range of the entire list.

Figure 1. DI-SPME Calibration Curves

The calibration range was 20 – 1280 ng/mL (ppb) and as you can see, we did not get the best results. I should note, that we were using naphthalene-d8 as an internal standard and the results were generated off of the compounds’ response factors. So, what is going on here? It looks like we’re saturating our detector, right? Guess again! We are not saturating the detector, it’s the fiber! When we analyze the data, the peaks do not have flat tops. Peaks with flat tops are indicative of saturating your mass spectrometer. So, pressed for time in the lab, we made a couple of quick changes to our sampling parameters seen in bold below (Table 2).

Table 2. Optimized DI-SPME Parameters

Under these new conditions and shifting the calibration range from 20 – 1280 ng/mL (ppb) down to 10 – 320 ng/mL (ppb), we obtained the following results (see Figure 2 below) for those same four compounds displayed previously in Figure 1.

Figure 2. DI-SPME Calibration with Optimized Parameters

Dang! Look at that improvement! We went from some embarrassing r2 values in Figure 1 to some r2 values that we can actually work with in Figure 2. Optimizing your sampling parameters and selecting an appropriate calibration range is critical for developing SPME methods. Fiber saturation is a common occurrence when doing SPME, but if you understand the parameters, you are able to overcome this issue. By changing our extraction time from 4 min to 1 min and increasing the split ratio to 250:1, we were able to go from calibration curves that were plateauing to linear curves. To see the rest of the calibration data for our terpenes of interest, refer to Table 3 below!

Linear calibrations were achieved for all compounds with an average r2 value of 0.983 in an average range of 10 – 320 ng/mL (ppb). This is a great improvement from what I have seen in published literature where an average r2 value of 0.942 was achieved for 31 terpenes in a calibration range of 50 – 1000 ng/mL (ppb) using liquid injection.[1] While our results were an improvement, we did experience some difficulties with the higher molecular weight terpenes, as well as with terpenes containing an alcohol functional group. The lower values for the heavier terpenes may be due to the SPME phase, while the terpenes containing alcohols most likely favored the water solution, making it more difficult to getting them onto the phase.

 

Overall, things are starting to look pretty good with the DI-SPME method. We still have more to come though, so stay tuned for our next blog in this series!

 

Reference

  1. Brown, A. K., Xia, Z., Bulloch, P., Idowu, I., Francisco, O., Stetefeld, J., Tomy, G. (2019). Validated quantitative cannabis profiling for Canadian regulatory compliance – Cannabinoids, aflatoxins, and terpenes. Analytica Chimica Acta. https://doi.org/10.1016/j.aca.2019.08.042

ProEZGC Chromatogram Modeler – there is much more to the program than just the Welcome Screen

When you log into the ProEZGC Chromatogram Modeler software, you will see the screen below, which is what I refer to as the Welcome Screen. This is the starting point for all, and unfortunately all some customers will think there is to the ProEZGC software.

 

For those of you who have used ProEZGC, you know that all you need to do is to add a compound name or CAS# into the box titled Search by Name or CAS# to get started (remember, only one compound name or CAS# per line).

For this post, I would like you all to see that there is more to ProEZGC than just the screen above and the screen below. In this example, I typed in the names of four common compounds/solvents and clicked the blue Solve button.

 

After reviewing the search results for all stationary phases, I selected the results for the Rtx-502.2 column.

 

I then clicked on the Conditions tab (the dark blue tab between Compounds and My EZGC) and were presented with a new page (see below).

 

From this page you can choose different dimensions of the same column (in this case, the Rtx-502.2), modify the GC oven temperature program, and if you select Custom at the bottom of the page in the Results section, you can change carrier gas flow rates (see screen below) and a few other parameters.

 

Notice the blue arrow under Control Parameters and to the right of Column Flow in the screen above?  So what does the arrow represent? It allows you to change the remaining top parameters (Column Flow, Average Velocity, Holdup Time and/or Inlet Pressure – whichever parameters the arrow is not pointing to) in the Control Parameters section without affecting the parameter the arrow is pointing to.  See example below.  Notice that I moved the arrow from Column Flow to Average Velocity by double-clicking in the empty space to the left of 39.70 cm/sec.

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By keeping the Average Velocity the same and changing the length of the capillary column, notice how the Column Flow (carrier gas flow rate value) increases, as do the Holdup Time* and Inlet Pressure.

  • Holdup Time is the time it takes for a non-retained compound to travel through the column.

 

One last comment; under Results you have three selections to pick from.  The default is Speed, and for most analysis this is fine.  As the name implies, when this button is selected, analysis times are minimized.  I showed you all how to select the Custom button for the most control of carrier gas parameters.  My favorite button, however, is Efficiency.  Analysis times may be a little longer, but separations are usually improved, and that is my goal, to show a customer maximum compound separation with reasonable analysis times.

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If you have never seen or tried changing conditions by selecting the Conditions tab, I encourage you to do so. To learn more about Pro EZGC, visit the Help Section and the Restek Video Library. Let us know if you have any questions.

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Tips on the analysis of pesticides and mycotoxins in cannabis products: Matrix matters! (Part II)

In part I of this blog series, we learned about matrix effects, how to assess them, and how to address them (you can check the blog here). One of the main conclusions of part I was the importance of using matrix matched calibration as the means to account for possible ionization effects in LC-MS/MS, and to minimize bias in GC-MS/MS due to chromatographic response enhancement. In part II, I want to talk about important points to keep in mind when evaluating recoveries and performing a matrix matched calibration. The first aspect, which was discussed previously in part I, is to ensure that your surrogate matrix reflects the composition of your sample matrix. Additionally, this surrogate matrix should be a blank (or free of your target analytes, in our case pesticides and mycotoxins). Once you source your surrogate matrix and decide on the sample prep conditions, it is very important to investigate your analytes recoveries.

  1. Spiking procedure and recoveries

Assessment of recoveries (% of analyte extracted/total amount of analyte spiked) is critical to ensure reliable quantitative data in typical pesticide analysis methodologies. This is important because matrix-matched calibrations are commonly prepared by post-spiking blank extracts with target analytes and internal standards at different concentration levels using the same dilution factor as used in real samples/extracts. A key assumption made when preparing the calibration curve is that the extraction efficiency is assumed to be 100%. Unfortunately, as we already showed in our technical article (here), there are some cases (e.g. daminozide in brownies) where getting close to exhaustive recoveries (close to 100% recoveries) is very difficult. Hence, the use of the right internal standard can be very critical to account for those variations. Alternatively, calibrators can be prepared by spiking matrix blanks at different concentration levels and running them through the entire extraction process to construct the calibration curve. I know that this can be tedious, especially when dealing with multiple matrices and many different pesticides, but if you are having difficulties with a particular cannabis matrix, this is in an option that you may want to consider. Undoubtedly, this approach in combination with the use of isotopically labeled standards will give you the best results in terms of accuracy and precision.

Typically, recoveries are tested by spiking the surrogate matrix with the analytes of interest and then performing your extraction procedure. Then you compare the amount of analyte recovered to analyte spiked in post-extraction blank assuming 100% extraction efficiency. How do we effectively use this approach? First, you need to pick the concentrations at which you want to test your method. Testing your method at a low (close to LOQ), medium, and a high concentration is a good idea. In our brownies workflow, we chose a concentration of 100 ng/g to test our methodology. This concentration was chosen because it is the lowest action level regulated for some of the California pesticides. Then, you need to spike your analytes in the surrogate matrix. Here I would like to bring a very interesting finding to your attention. A chemist from a cannabis testing lab shared with me that he first adds the extraction solvent to his sample, and subsequently spikes the samples with target analytes. In my case, I normally spike my analytes in the blank matrix, wait for the analytes to equilibrate with the sample, and then proceed to perform the extraction. In order to check whether the order of addition impacts the results, we evaluated the effect of spiking our target analytes (California list of pesticides and mycotoxins) before and after adding the extraction solvent. I know that this experiment may sound trivial, but please don’t forget that the devil is in the details. This experiment was performed in two matrices: brownies and dark chocolate. Although both matrices are delicious and have chocolate as one of their main ingredients, their compositions are very different. Figure 1 summarizes the results of the comparison for the three most impacted analytes.

Figure 1. Relative responses obtained in A) brownies and B) dark chocolate after comparing the effect of spiking our target analytes before and after adding the extraction solvent. Responses were normalized by the results obtained when spiking first our analytes and then adding solvent (n=3). Brownies samples were prepared as described in our technical article (here). Dark chocolate samples (0.5 g) were extracted by using isopropyl alcohol (0.5 mL) and acetonitrile acidified with acetic acid at 1% (2.5 mL); subsequently, 2 mL of the extract were passed through a Restek Resprep C18 cartridge (Restek Cat.#26030).

 

To better visualize our data, the responses (area counts) were normalized according to the response obtained for the samples where analytes were spiked first and solvent was added later. Interestingly, the effect depends on the compound and on the matrix type (and of course, it also depends on your extraction conditions). Daminozide (I guess that at this point you may think that it is our favorite analyte) displays 3-fold better recoveries when it is spiked in brownies after adding the extraction solvent vs. when it is spiked in the dry matrix. Conversely, in the case of dark chocolate, there is only a 10% difference between spiking daminozide before vs. after the extraction solvent. The main reason for this difference is that daminozide, a highly polar pesticide (logP=-1.5), displays a much higher affinity for a matrix like brownie compared to a more fatty sample such as dark chocolate. Such affinity can be modified when solvent is added to the matrix, meaning that the recovery of a surrogate matrix spiked by adding solvent and then the analytes won’t always be representative of a real sample. In the case of acephate, another polar pesticide (logP=-0.85), the spiking order results in a 17% difference in brownie whereas in dark chocolate the difference is negligible. Ochratoxin A, on the other hand, showed differences of 39% and 24% in brownies and chocolate, respectively. Based on these results, it is clear that the safer way to assess recoveries (also method accuracy and precision, which will be discussed in part III) is to spike your analytes and isotopically labeled analogues directly in the matrix before adding the extraction solvent. If you intend to use your isotopically labeled analogues to correct only for matrix effects, instrumental response drift, or injection variations, you can add them to your final extract. However, if you need to account for extraction variations, internal standards should be added directly to the sample matrix (before the extraction process).

After selecting the concentrations at which you want to test your recoveries and spiking analytes in your surrogate matrix, you need to prepare your post-spiked extract, which is the solution you will compare against your pre-spiked extracts. As we learned in part I, it is very important to have the same matrix components present in the solutions used to assess recoveries in order to account for matrix effects. To prepare a post-spiked extract, you simply perform your whole extraction procedure using blank matrix and then spike your post-extraction blanks with analytes assuming 100% recovery. Here it is worth  emphasizing that it is critical to ensure that your dilution factors are correct. For example, when using SPE cartridges to clean-up your extract, your final extract volume is going to be lower (~2.6 mL) than the original volume of extraction solvent used (3 mL). In that case, you may need to pool extracts collected from at least two replicates and then measure the volume you need to keep the same dilution factor. For instance, in our case, to prepare a post-spiked extract we added 50 µL of a 1 ppm analyte mix (same volume added to 0.5 g of surrogate matrix to attain 100 ng/g) in 3 mL of matrix blank extract (3 mL was the total volume of extraction solvent used for our brownies workflow). Recoveries are then estimated using the following equation:

% Recovery = (analyte response in pre-spiked extract/analyte response in post-spiked extract)*100

It is very important to emphasize that you can have amazing accuracy and precision results without having exhaustive recoveries. An example of this is the quantitation approach we used for daminozide in our technical article (here). In other words, recoveries and accuracy are two different things. We will talk more about this in Part III, so please stay tuned!

Optimizing Splitless Injections: Inlet Temperature

One of the key parameters that requires optimization for splitless injections is inlet temperature.  With liquid injections, the analyst is relying on the volatilization of the sample upon introduction into the inlet.  The analytes can then be efficiently transferred to the column in a vapor state, where they are refocused, prior to beginning the chromatographic separation.  Since analytes have different boiling points, it’s important to monitor the least volatile compounds.  These higher boiling compounds will require more thermal energy to efficiently vaporize and transfer to the column.  Increasing inlet temperature will generally lead to increased responses for compounds with high boiling points, although at a certain point the gains may become insignificant and possibly deleterious.

As with most things in chromatography, though, there is always a trade-off.  As we increase inlet temperature, we provide thermal energy which can also drive chemical reactions.  Many analytes are thermally labile, that is, they tend to react or degrade at high temperatures.  This creates a problem, as we compromise the integrity of the analysis by forming new products in the inlet that are non-representative of the sample being injected.

So my advice when setting up a new method is to try several different inlet temperatures and observe both the behavior of your compounds with the highest boiling points, as well as behavior of thermally labile compounds.  You may have to compromise, as the temperature at which the high boiling compounds have the best responses may lead to lower responses for sensitive compounds or vice versa.  Keep in mind that some analytes may have both high boiling points and be thermally labile, such as the pesticide deltamethrin.

A good initial inlet temperature is 250 °C, which works well over a wide range of compound boiling points.  If you have a lot of higher molecular weight analytes though, you may want to experiment with higher temperatures.  For instance, start at 250 °C, then try 275 °C, then 300 °C.  Observe the effects on your last eluting compounds, and if there are any active compounds that lose response as you increase temperature.  From here you can choose the best overall temperature for your analysis or further experiment within a range, such as trying temperatures between 275 °C and 300 °C.

The examples below illustrate the effect of changing inlet temperature on a high boiling point PAH, Benzo[ghi]perylene, as well as a thermally labile chlorinated pesticide, endrin.  Benzo[ghi]perylene, which has a boiling point of 500 ⁰C, shows increasing response as inlet temperature increases; however, notice that the gains are not linear and become less significant as inlet temperature continues to increase.  For instance, you don’t gain much sensitivity by increasing the inlet temperature from 275 ⁰C to 300 ⁰C.  On the other hand, notice that endrin continues to experience increased degradation as inlet temperature increases, compromising the quality of the analysis.

Benzo[ghi]perylene, a PAH with a high boiling point, shows increasing response with increasing inlet temperature. Notice that the gains are not linear, however, and increases in peak response become less significant as temperature increases.

Endrin, a thermally labile chlorinated pesticide, shows increased degradation as inlet temperature increases. This compromises the analysis, as new products are being formed in the inlet.

In the introduction to this series, I said that I wouldn’t discuss liners, since I have already blogged on the topic; however, it’s impossible to completely ignore liners in a discussion about inlet temperature.  Using a liner that has wool or some obstruction like a cyclo, increases the surface area and allows for retainment of more heat within the inlet.  Therefore, when you use a liner with wool, you can achieve better vaporization of heavier compounds at lower temperatures compared to a liner without wool.

Along these same lines, the inlet temperature set point is not equal across the entire inlet.  Often this temperature is measured near the center of the inlet; the top and bottom of the inlet are cooler, sometimes significantly so.  Because of this, it’s possible for a sample to vaporize upon introduction into the inlet, but then condense as it reaches the bottom and not effectively transfer to the column.  Selecting a liner with an obstruction, like wool, at the bottom will help prevent this, as it not only prevents the sample from contacting the bottom of the inlet, but holds heat to help with volatilization.

While this series is focusing on splitless injections, note that the general guidance in this blog will also apply to optimizing inlet temperatures for split injections.

For the next installment of this series, I’m going to talk about splitless hold time, another important splitless injection parameter.  Stay tuned!

Time to make lemonade with your Agilent 1100 – HPLC routine maintenance

They say when life hands you lemons, make lemonade. In this case, the COVID-19 pandemic has handed us all more downtime, so let’s talk about one aspect of a testing lab that tends to get overlooked or given less priority than other daily tasks: routine maintenance. The combination of downtime cannabis labs are experiencing due to the COVID pandemic and a prevalent numbers of Agilent 1100s being used in these labs which not supported for service due to the “End of Guaranteed Support” (EGS) implemented by the manufacturer, it’s now more critical than ever to take advantage of the situation and educate you and your team on this topic.

The COVID-19 pandemic has impacted the cannabis and hemp community in an unprecedented manner. Some of the hardest hit businesses in the cannabis market during these times are the testing labs. Just a couple months ago, labs were running multiple shifts, investing in more personnel and instruments just to keep up with increasing sample volumes and executing on guaranteed turnaround times. Those same thriving labs are now operating with a skeleton of the workforce due to the lack samples. While we all know at some point those flourishing times of insanely high sample volumes will return, the question remains, “when?”. While we’re feeling this hardship and tensions are high due to this uncertainty of “when?”, there are still great opportunities for your lab and team to capitalize on right now.

Not too long ago many labs focused primarily on throughput, improving on sample preparation techniques, and growing their customer base and….rightfully so. There was little time to invest in other things like routine maintenance, creating a proper routine maintenance log book, keeping inventory of replacement parts, etc. And, on a quick note: not just having some inventory, but the right amount of those key replacement parts on hand for when your system went down, so you could quickly get it back up and running again. Most of us, including myself (yes, I was guilty of it too) learned this lesson the hard way. For those of you who can’t relate, I hope you embrace this article and the future literature we publish on these topics to not only prepare, but implement what we preach to avoid the troubles and headaches of instrument down time. The dreadful experience of looking at the calendar and waiting days for that package to arrive with your replacement parts is one of the most helpless moments in your professional career. The amount of business revenue loss from not having replacement parts on hand and not practicing routine maintenance can make a devastating impact on your business. BUT, using this downtime we all have right now to educate yourself along with your colleagues and implement a good routine maintenance schedule, you’ll save yourself money, time, resources, and headaches down the road. The best part….you’ll most likely be able to increase your sample throughput thanks to more instrument up-time!

We’re turning our attention to help you capitalize on the routine maintenance opportunities mentioned above. We’re focusing today’s blog on one of the most commonly used instruments in a cannabis lab; the Agilent HP 1100 series HPLC system. This system is usually equipped with a PDA or DAD for potency testing and known as the potency workhorse. Knowing how prevalent these systems are in the cannabis industry, practicing a routine maintenance schedule is of the utmost importance. Especially, since as of May 31, 2015, 1100 series HPLC systems were categorized “End of Guaranteed Support” (EGS) by Agilent. For those labs that do implement a routine maintenance program, they are most likely using a third party for this service, which can be VERY costly for those services and still leaves a dependency on someone else. It’s doesn’t leave one with a lot of security when you have to rely on someone else to get your system back up and running. So, take action and get educated, equipped and empowered with the right information and consumables. Let us help you gain that independence for these tasks and provide you with a stable supply chain for the consumables you need for routine maintenance schedules.

There’s no excuse not to give your system the love and care it deserves during this downtime you have right now. Make the time and investment now in your systems, it WILL pay off! Once you get in a good routine, it doesn’t take that much time to keep things up and running properly. Remember, the more love and consistent attention you give your system, the less likely you’ll have a surprise on your hands down the road. With that surprise leading to losing money, a back log in samples, etc.

For this blog, let’s start with some literature support to get you going! Here’s a link that provides you scheduling times and replacement parts your system needs https://www.restek.com/Supplies-Accessories/HPLC-Accessories/Instrument-Accessories-Parts?s=ins:ag and a link for our LC accessory routine maintenance parts that we carry https://www.restek.com/pdfs/GNOT3158-UNV.pdf). For those of you starting from scratch, check out these two popular kits that will get you on the right path: Autosampler PM kit (cat.# 25271) http://www.restek.com/catalog/view/9668 and Pump PM kit (cat.# 25270) http://www.restek.com/catalog/view/9669. Don’t forget to take this downtime to check out our video library to educate you and your team on routine maintenance. And, keep in mind if you have any questions or need assistance, just give our Technical Support team a call!

MOST IMPORTANTLY, Be safe everyone and know we’re here for you! Let’s make the best of things during these tough times and come out of this pandemic better and stronger together. That together includes our instruments.

Spring Cleaning Your GC System

Spring has sprung and now is a good time to give your GC system a thorough going over.  There is routine maintenance that we should perform all the time to keep the GC in tip-top condition like changing the liner, o-ring, septum, using your electronic leak detector and column trimming; but there is also periodic preventative maintenance that takes place less frequently that is equally as important.  This may include cleaning the inlet, refurbishing your FID, and replacing the traps in your system.  Not doing so may have consequences.  Luckily the folks at Restek have you covered with hints, tips and tricks posted over the years in our ChromaBlography and Video Library; and as always you can contact our wonderful friends in Tech Support for help.

Here is just a selection for quick reference:

GC Inlet Maintenance

Replacing a GC Inlet Seal

Don’t forget to change you GC inlet bottom seal and trim your GC column as part of your maintenance routine

Conditioning GC Inlet Parts

Keeping you GC System Clean and Inert

FID Maintenance

Activity of FID detection port: a big problem if underestimated

Split Vent Trap Replacement

It’s all in the split vent trap

Contamination of injection system split vent lines: A maintenance item to underestimate

Annual replacement of cartridge gas filters

What are these o-rings for that I received with my Super-Clean baseplate filters?

Don’t forget about your lab’s moisture traps, especially when it’s summer

Analysis of noble and permanent gases on adsorbent columns

Predicting selectivity characteristics of adsorbent columns is often a wild guess. Yes, we know argon will have less retention than krypton, but how well do adsorbent columns separate noble gases from permanent gases? Can neon and hydrogen be resolved using a porous polymer column or do we have to use more retentive columns, like Molecular Sieves and ShinCarbon? To give the definite answers, we mapped out the selectivity of some of our adsorbent columns for noble gases relative to permanent gases.

The column with the least retention, Q-Bond, separates noble gases from each other, however, helium and hydrogen coelute with neon, and argon elutes at the same time as the main air components oxygen and nitrogen.

Figure 1: Chromatogram showing the noble gases and permanent gases using the Q-Bond column (GC_PC1364).

 

Better performance and resolution was observed on the MSieve 5A column.

Figure 2: Chromatograms generated using the Molesieve 5A column with (A) nitrogen and (B) helium as carrier gases (GC_PC1362).

When developing the analysis method on the MSieve column, krypton exhibited some interesting behavior. When the starting temperature is isothermal at 30°C krypton elutes from the column before the nitrogen. Increasing the starting temperature of the analysis or, like in the above example, using an aggressive oven ramp will switch the elution order of those compounds where krypton elutes after nitrogen. When developing a method on the MSieve column do not allow the starting temperature of the analysis to be your “kryptonite” and be sure to adjust it (see Figure 3).

Figure 3: Three different isothermal starting temperatures illustrating elution order changes between nitrogen and krypton.

 

ShinCarbon columns offer high retention for gases, similar to the MSieve 5A. However, the ShinCarbon column will also elute carbon dioxide. It’s main limitation is the inability to adequately resolve argon from oxygen and methane from krypton.

Figure 4: ShinCarbon column chromatograms using both nitrogen (A) and helium (B) as carrier gases. The limitations of this column are poor resolution of argon/oxygen and methane/krypton (GC_PC1363).

 

Before selecting the column that will fit your analysis needs, lets “change” into a superhero of gas analysis on adsorbent columns with a few very helpful tips previously posted in our blog.

  • Overloading on an adsorbent column will show as tailing, with the overloaded peak starting at earlier retention time. The end of the peak will remain at the same retention time.
    For example, if your analysis goal is to determine impurities in neon and the targeted impurity among others is helium, no matter which column you use, the overloaded neon peak will mask the peak directly preceding neon.
  • Select a carrier gas which is the same as the balance (matrix) gas. This way your balance gas will “not be detected” and lower concentration compounds eluting before the overloaded peak can be seen.
    In the case of the analysis of trace impurities in neon, using neon as carrier gas (1) can be an interesting solution.
  • Are you using a sample loop to transfer the sample onto your column? Optimizing the ratio between the carrier gas flow rate and sample loop size will reduce the time for the sample to be transferred on to the column which will minimize peak broadening. The peak shape of early eluting compounds is strongly affected by sample transfer on to the column. Late eluters spend more time in the column, and therefore, have time to refocus.
    Decreasing sample loop size and increasing column flow are only two obvious solutions. Also, consider using pulsed injection or split injection to decrease the time it takes to transfer the sample from the sample loop onto the column.
  • For gas injections, often the best option are the 0.53mm ID PLOT columns. They allow maximum injection volumes and provide the smallest injection error.

Literature:
1. Analysis of trace impurities in neon by a customized gas chromatography, J. Chromatogr. A.,1463 (2016), pp. 144-152

Pesticides are like Siblings, They Don’t Always Get Along part 2 – now with the GC mix!

Last year my colleague Landon publish his blog about pesticide multiresidue LC mix stability in a celery matrix and in a solvent. Today, I’d like to show you what happens when you do this with the GC multiresidue pesticide kit.

On day 0, I prepared stock solutions from all 9 ampules of the GC multiresidue pesticide kit. These ampules contain between 8 – 40 pesticides in toluene and are formulated to be stable before opening and mixing. In my experience, they last a long time in the freezer as long as they are stored separately. The stock solution (containing the nine ampules mixed from the kit) was spiked into the celery matrix at 100 ppb level (final concentration) and split into three aliquots. The second set of samples was prepared from the stock solution in acetonitrile, also at 100 ppb/pesticide and split into three aliquots. Samples were also spiked with the internal standard triphenyl phosphate and the samples were analyzed the first day. After analysis, they were split into three groups based on storage: freezer, fridge, and autosampler tray. Samples were reanalyzed every 2-3 days up to 9 days and then on day 17. Samples were recapped after each analysis to prevent evaporation losses and septa contamination.

Figure 1: Comparison of the number of pesticide residues with a loss greater than 20% of the signal

We were keeping a tally of samples that lost more than 20%, using the peak area ratio of the pesticide peak and internal standard peak (Figure 1).

There were a few unexpected results:

  •  The difference between solvent and matrix-based samples was minimal
  •  Fridge samples had the most pesticides with sample loss
  •  Freezer samples did not fare better than samples left in the autosampler.

In the end, I have to agree with Landon’s conclusions – prepare your stock solutions the day of analysis if you want to avoid overestimating the concentrations of your pesticide residues because even storing them in a freezer won’t stop the degradation.

Cryogenic Cooling for Air Analysis Part 2 – Combining TO-15A and Ethylene Oxide

In my previous blog on cryogenic cooling (https://blog.restek.com/cyrogenic-cooling-for-air-analysis-interferences-from-n2-co2-and-o2/) I touched briefly on ethylene oxide (EtO) and why it may be of interest in ambient air analysis. While OSHA has a time weighted average (TWA) limit for EtO at 1ppm for an 8 hour exposure, recent work by the US EPA has shown that even low doses of ethylene oxide can increase cancer risks over a person’s lifetime (https://cfpub.epa.gov/ncea/iris/iris_documents/documents/toxreviews/1025tr.pdf), which explains the interest in testing for EtO at sub ppb levels. Since this brings EtO testing to similar levels as TO-15A, why not combine the two?

While my previous blog covered the need to separate EtO from the air peaks introduced into the instrument, there are several other potential interferences that have to be managed. Acetaldehyde has an almost identical structure and mass spectrum. It is very common in nature and produced in a wide variety of industries, and it is possible to be present in both lab blanks and samples. Methanol also shares several ions with EtO, and as a common solvent for volatile standards (e.g., 8260 and TO-15A internal standards) it’s likely present in most air labs.

Fig. 1 – Comparison of EtO, Acetaldehyde, and methanol mass spectrum

Fortunately the cryo cooling helps with these separations as well. In addition, I also found that using selected ion monitoring (SIM) produced a cleaner baseline and better signal to noise ratio, allowing for detection of EtO down to 0.05ppb or lower (Fig.2 lower trace).

 

Fig. 2 – Comparison of Scan (top) and SIM (bottom) signals for EtO (RT ~8.72) with acetaldehyde (RT ~7.50) and MeOH (RT ~9.00) interferences. EtO at 0.05ppb

Once the troublesome EtO/acetaldehyde/methanol separations are solved with cryo cooling, I was able to use EZGC to get a working oven program to separate the TO-15A compound list. Without the need for extra sensitivity on the TO-15A compounds I found it helpful to use the combined SIM/Scan capabilities of the Agilent 5977A mass spec, using the SIM data for EtO and the scan data for the TO-15A list. This meant I didn’t have to optimize the SIM parameters for nearly 80 compounds, keeping the method much simpler.

Fig. 3 – Combined TO-15A and EtO chromatogram with EIC for compounds 1-7 (top), SIM for EtO ( compound 8, middle), and TIC (compounds 9-79, bottom). TO-15A compounds at 0.2ppb, EtO at 0.05ppb.

# Name Ret Time
1 Propylene 4.17
2 Dichlorodifluoromethane 4.43
3 1,2-Dichlorotetrafluoroethane 5.45
4 Chloromethane 5.62
5 n-Butane 6.52
6 Vinyl chloride 6.54
7 1,3-Butadiene 6.87
8 Ethylene Oxide 8.72
9 Bromomethane 8.75
10 Chloroethane 9.64
11 Vinyl bromide 10.71
12 Trichlorofluoromethane 11.21
13 n-Pentane 11.85
14 Ethanol 13.29
15 Acrolein 13.74
16 1,1-Dichloroethene 13.94
17 1,1,2-Trichlorotrifluoroethane 14.3
18 Carbon disulfide 14.49
19 Acetone 14.55
20 Acetonitrile 15.83
21 Isopropyl alcohol 15.92
22 Methylene chloride 16.5
23 trans-1,2-Dichloroethene 17.6
24 Tertiary butanol 17.67
25 Methyl tert-butyl ether (MTBE) 17.73
26 Hexane 18.8
27 1,1-Dichloroethane 19.35
28 Vinyl acetate 19.65
29 cis-1,2-Dichloroethene 21.49
30 2-Butanone (MEK) 21.62
31 Ethyl acetate 21.9
32 Bromochloromethane 22.29
33 Tetrahydrofuran 22.35
34 Chloroform 22.74
35 1,1,1-Trichloroethane 23
36 Cyclohexane 23.12
37 Carbon tetrachloride 23.35
38 Benzene 23.8
39 1,2-Dichloroethane 23.96
40 Isooctane 24.09
41 Heptane 24.45
42 1,4-Difluorobenzene 24.66
43 Trichloroethylene 24.98
44 1,1,2-Trichloroethane 24.98
45 1,2-Dichloropropane 25.36
46 Methyl methacrylate 25.49
47 1,4-Dioxane 25.49
48 Bromodichloromethane 25.75
49 cis-1,3-Dichloropropene 26.28
50 4-Methyl-2-2pentanone (MIBK) 26.46
51 Toluene 26.64
52 trans-1,3-Dichloropropene 26.91
53 Tetrachloroethene 27.18
54 2-Hexanone (MBK) 27.32
55 Dibromochloromethane 27.49
56 1,2-Dibromoethane 27.6
57 Chlorobenzene-d5 28.02
58 Chlorobenzene 28.04
59 Ethylbenzene 28.11
60 n-Nonane 28.2
61 m- & p-Xylene 28.22
62 o-Xylene 28.55
63 Styrene 28.56
64 Bromoform 28.74
65 Cumene 28.83
66 4-Bromofluorobenzene 28.99
67 1,1,2,2-Tetrachloroethane 29.08
68 n-Propyl benzene 29.16
69 4-Ethyltoluene 29.24
70 2-Chlorotoluene 29.25
71 1,3,5-Trimethylbenzene 29.28
72 1,2,4-Trimethylbenzene 29.57
73 1,3-Dichlorobenzene 29.82
74 1,4-Dichlorobenzene 29.89
75 Benzyl chloride 29.97
76 1,2-Dichlorobenzene 30.17
77 1,2,4-Trichlorobenzene 31.36
78 Hexachlorobutadiene 31.39
79 Naphthalene 31.6

Table 1 – RT for TO-15A and EtO.

GC Agilent 7890B
Injection type On-column
Column 624Sil MS 60m x 0.25mm x 1.4um
Carrier gas He , constant flow
Flow rate 2mL/min
Oven temp 0°C (hold 5 min) to 60°C at 3.5°C/min (hold 0 min) to 260°C at 24°C/min (hold 5 min)
Detector MS (Agilent 5977A)
Acquisition mode SIM/Scan
Scan parameters
Scan range (amu) 29-226
Scan rate (scans/sec) 3.7
SIM parameters
SIM ions 15, 29, 43, 44, 56
Dwell time 50
Transfer line 250°C
Analyzer type Quadruple
Source type Extractor
Source temp 230°C
Quad temp 150°C
Electron energy 70eV
Solvent delay time 0 min
Tune type BFB
Ionization mode EI
Preconcentrator Markes Unity 1+ CIA
Trap 1 settings
Cooling temp 5°C
Desorb temp 300°C
Desorb flow 6 mL/min
Desorb time 180 sec
Internal Standard
Purge flow 50 mL/min
Purge time 60 sec
Volume 50mL
ISTD  flow 50mL/min
Sample
Volume 400mL
Purge flow 50mL/min
Purge time 60 sec
Sample flow 100mL/min

Table 2 – GC/MS and preconcentrator settings

While many labs may be reluctant to use cryogenic cooling due to costs and safety issues, it can be a powerful tool to separate out very volatile compounds. Here it was critical in the separation of EtO from methanol and acetaldehyde. In addition, the ability to acquire both SIM and scan MS data allowed for the increased signal to noise ratio for EtO in SIM mode, while maintaining the simplicity full scan for the TO-15A compounds. Together, cyro cooling and SIM/Scan can allow for the relatively simple addition of EtO down to 50ppt to TO-15A analysis.