News from LabRulezGCMS Library - Week 16, 2025

Our Library never stops expanding. What are the most recent contributions to LabRulezGCMS Library in the week of 14th April 2025? Check out new documents from the field of the gas phase, especially GC and GC/MS techniques!

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This week we bring you application notes by Agilent Technologies, Shimadzu and poster by University of Copenhagen / MDCW!

1. Agilent Technologies: Purity Analysis of N-Methyl Pyrrolidone (NMP) Using an Agilent 8850 GC

• Application note
• Full PDF for download

Analysis of organic solvents to determine purity is a ubiquitous laboratory task that is well suited for gas chromatography (GC). Purity testing is an important part of process monitoring and provides key quality metrics for both feedstocks and products, as well as insights into process conditions by monitoring intermediate streams. The highly used solvent NMP is critical in many industries, including semiconductors, coatings and adhesives, and pharmaceuticals. The role of NMP in the manufacturing process of lithium-ion batteries (LiB) is of particular interest. 

Within the LiB market, NMP is analyzed at both gross and residual levels. NMP as a bulk solvent must be screened for impurities that may affect performance in the battery electrodes. High-purity NMP is employed in creating the slurry applied to the LiB electrodes.1 NMP dissolves the polymer binder to apply the slurry to the aluminum foils, resulting in a functional LiB cathode. Once that application is complete, the residual NMP is removed, usually by drying the product. Two quantitation approaches to determine residual NMP on electrodes have been evaluated in recent publications.2,3 To complement the detection of low-level NMP, this work will address the purity of NMP as a starting material. 

NMP is a highly polar, aprotic solvent with a relatively high boiling point of more than 200 °C. The pure solvent has an alkaline pH of approximately 10, and has a low vapor pressure and high flash point, which lend to its success in manufacturing environments. These characteristics also make NMP more challenging than volatile solvents when performing routine solvent purity analysis on GC systems. Solvents with lower volatility and higher viscosity require more frequent maintenance of both the GC inlet and the autosampler to manage carryover and repeatability quality checks. 

The two most common impurities associated with NMP are N-methyl succinimide (NMS) and 2-pyrrolidinone (2PYR), shown in Figure 1. As there are similarities in both structure and properties among the three compounds, a robust purity analysis using an 8850 GC can be achieved by combining appropriate column selection, GC oven temperature control, and inlet pressure control. While this would be more simply executed if all compounds were present at the same level, the expectation of a solvent purity method is that it can perform well for both the highest and lowest concentration in the mixture.

Experimental 

All data were generated on an 8850 GC with a split/splitless (S/SL) inlet and flame ionization detector (FID). Samples were introduced to the GC inlet using a 7650 ALS. Agilent OpenLab CDS software, version 2.7, was used for data acquisition and analysis. The GC flow path is shown in Figure 2, and the method conditions are provided in Table 1. NMP samples were sourced from both a commercial vendor and a customer production facility, summarized in Table 2.

Results and discussion

The separation study evaluated several columns, and the following criteria were considered: void time, peak shape, baseline consistency, and operating temperature range. While NMP, NMS, and 2PYR all have boiling points exceeding 200 °C, they also have favorable vapor pressures to consider higher polarity columns with lower maximum operating temperatures. Single-component standards were prepared at 0.1% (w/v) from neat NMS (≥ 99%) and 2PYR (99%), both from Sigma-Aldrich (Milwaukee, WI, U.S.) to verify compound identification and retention time. 

The evaluated column chemistries included polyethylene-glycol-based columns such as the Agilent DB-WAX Ultra Inert (UI) and Agilent J&W HP-INNOWax, cyanopropyl columns such as the Agilent J&W DB-624 and DB-23, and apolar columns such as the Agilent J&W DB-5. The data were most consistent and comprehensive with a 30 m × 320 µm, 0.5 µm DB-23. Most column selections eventually resulted in an adequate separation under optimized conditions, but the DB-23 was selected because the separation demonstrated less void time, better peak shape for NMS and 2PYR, and lower baseline bleed over time. Although both DB-624 and DB-WAX UI column chemistries are typically used to quantify residual NMP, the injections in this study contained NMP as the primary component of the injection, which impacts the separation. The unidentified impurity that eluted at 18 minutes under the conditions in Table 1 was used as a marker for the end of the GC run, as this compound was highly retained on some columns. 

Conclusion

The Agilent 8850 GC, 7650 ALS, and J&W DB-23 column together deliver exceptional performance for separating common impurities in NMP solvent. With intelligent features such as Sample Overlap and Peak Evaluation, as well as a compact design that conserves lab space, the 8850 GC is essential for high-throughput labs requiring consistency in results. The DB-23 column's excellent separation capabilities, demonstrated through comparative analysis of customer samples, make it ideal for workflows seeking detailed impurity information alongside the overall solvent purity results.

2. University of Copenhagen / MDCW: The evaluation of GC×GC-QTOF data by pixel-based analysis: A Tutorial 

• Poster
• Full PDF for download

The identification of unknown sample components has become more important as the release of chemicals into the environment steadily increases leading to a high impact of potentially harmful substances. Comprehensive two-dimensional gas chromatography (GC×GC) is a powerful tool for non-targeted analysis (NTA) especially when coupled to high resolution mass spectrometry (QTOFMS). Bottleneck is the high amount of data and required manual corrections after data processing. Herein, we present a NTA workflow for the evaluation of GC×GC-QTOFMS data of 42 effluent samples from two wastewater treatment plants (WWTPs) in Denmark using pixel-based analysis.

METHODS

The effluent samples were analyzed after derivatization with MSTFA using GC×GC-QTOFMS. For data analysis, following steps were conducted: Data was binned to nominal mass and the total ion current (TIC) was used. Chromatograms were aligned using landmark approach (GC Image). Phase shifting and cropping was applied prior baseline correction using Lower Convex Hull Estimate. The influence of blank removal, scaling and normalization on the outcome of principal component analysis (PCA) and pixel prioritization was evaluated.

3. Shimadzu: High Throughput HS-GC Method for Residual Solvent Analysis in Valsartan API 

• Application note
• Full PDF for download

User benefits:

• HS-20 NX features a short transfer line along with continuous isolation gas flow minimizes carryover and enhances precision.
• Active overlapping function, reduces sample analysis cycle time which boosts productivity.
• Multiple solvent analysis in a single method.

According to Guidelines by International Conference on Harmonization (ICH) [1], all residual solvents should be removed to the extent possible, to meet product specifications, good manufacturing practices, or other qualitybased requirements. Testing for residual solvents in raw materials is highly recommended as this solvent may be carried through the process and remain in the finished product. Early in the process, control is usually more effective during initial manufacturing stages compared to remediation which may resultsin even rejection of final product. 

Residual Solvent: Residual solvents in pharmaceuticals are defined as organic volatile chemicals that are used or produced in the manufacturing of drug substances or excipients, or in the preparation of drug products. Residual solvent analysis in pharmaceutical products is necessary not only because they represent a potential risk for human health, due to their toxicity and their undesirable side effects, but also because they may affect the physicochemical properties of pharmaceutical products. Therefore, it is a mandatory requirement for health authorities in the world to accurately determine the levels of residualsolventsthat are present in APIs or finished products. The ICH guideline Q3C(R9)[2] classifies the regularly used solventsinto three different classes based on their toxicity : 

• Class 1 solvents should be avoided due to their known carcinogenic effect on human. Hence, their use should not be employed in the manufacture of drug substances, excipients and drug products. 
• Class 2 solvents should be limited in the drug products because of their inherent toxicity. 
• Class 3 solvents are regarded as less toxic and of a lower risk to human health but those also have specified control threshold.

Analysis of Residual solvents: Gas chromatography is the technique of choice used for the analysis of the residual solvents. Several methods are available for this analysis in pharmacopeial references such as USP, BP, PhEur which are based on headspace technique

Requirement of high throughput GC method: Multiple method are required to analyze all the classified solvents in ICH. Also, these methods are having longer run time which decreases productivity. Further, huge amounts of solvents are consumed during sample and standard preparations. By using high throughput method, maximum number of residual solvents can be analyzed in a single method. Various combinations of residual solvents can be analyzed by preparing standard of desired residual solvents. This method can be optimized for the critically separated residual solvent pair at the time of actual analysis. Hence, it proves to be time efficient and cost effective.

Use of Nexis GC-2030 with HS-20 NX for the high throughput method:

Shimadzu’s Nexis GC with HS-20 NX headspace autosampler provides unique features which helps in rapid chromatographic analysis such as high head pressure capacity enabling fast GC analysis. Also, vial overlapping function decreases cycle time, thereby boosting productivity.

Conclusion

Shimadzu’s Nexis GC-2030 along with HS–20 NX headspace system is suitable for drug discovery and pharmaceutical applications, allowing testing of wide range of residual solvents from low to high boilers in a single method with a short run time.