Dimethyl carbonate (DMC) plays a critical role in lithium-ion battery electrolytes, where solvent purity directly impacts performance, safety, and lifetime. Even trace-level impurities can contribute to degradation of solid electrolyte interfaces, consumption of lithium ions, or gas formation—effects that compromise both efficiency and safety.As battery materials continue to evolve, analytical approaches must provide both high sensitivity and high-confidence identification. A recent LECO application study demonstrates how combining two GC-MS platforms enables a more complete characterization of DMC impurities than either approach alone.<h3>Why Impurity Characterization in DMC Is Challenging</h3>Battery-grade solvents demand detection of contaminants across a wide concentration range, starting from major byproducts to trace-level species. In DMC, impurities may include oxygenated compounds, hydrocarbons, and nitriles, many of which arise from synthesis or handling processes.These compounds can co-elute or exist at levels below typical detection thresholds, making comprehensive analysis difficult with a single analytical technique. In addition, electron ionization (EI) spectra do not always provide a clear molecular ion, complicating compound confirmation.<h3>A Complementary Analytical Strategy: Sensitivity + Confidence</h3>The application note demonstrates a combined workflow using the approach:<ul><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/1097">Pegasus BTX (GC-TOFMS)</a>&nbsp;for high-sensitivity detection</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/38">Pegasus HRT (high-resolution GC-MS)</a>&nbsp;for accurate mass confirmation</li></ul>The Pegasus BTX enables detection of impurities at below parts-per-billion levels, ensuring that even low-abundance analytes are captured.Following detection, the Pegasus HRT provides high-resolution, accurate mass data in both EI and positive chemical ionization (PCI) modes. PCI is particularly valuable when EI spectra lack a clear molecular ion, allowing confirmation through common adduct species such as protonated molecular ions [M+H]⁺.Because both ionization modes can be accessed without hardware changes, the workflow supports efficient, multi-dimensional confirmation of analyte identity.<h3>Observations</h3>Using this combined approach, multiple classes of impurities were identified in the DMC sample. These included:<ul><li>Oxygenated reaction byproducts</li><li>Alcohols, carbonates, and ethers</li><li>Hydrocarbons and aromatic species</li><li>Additional low-level analytes detected with high library match scores</li></ul>Importantly, the high sensitivity of the Pegasus BTX revealed a broader set of low-concentration compounds, while the Pegasus HRT increased confidence in compound identification through accurate mass measurements and confirmation of molecular formulas. &nbsp;The study also highlights cases where co-eluting compounds were successfully deconvoluted, allowing individual components to be identified even without complete chromatographic separation.<h3>Why This Matters for Battery Materials Analysis</h3>This work illustrates a key principle for advanced materials characterization: detection and identification are distinct challenges that often require complementary solutions.<ul><li>Detection alone&nbsp;is insufficient without confident identification</li><li>High-resolution confirmation&nbsp;is limited if low-level species are not first detected</li></ul>By combining these capabilities, laboratories can gain deeper insight into solvent purity, production processes, and potential performance risks in battery systems.<h3>Explore the Complete Study</h3>This short overview highlights only a portion of the findings. The full application note provides:<ul><li>Detailed acquisition parameters and workflows</li><li>Chromatographic and spectral data examples</li><li>Confirmed impurity lists with retention times and similarity scores</li><li>Examples demonstrating EI/PCI complementarity and accurate mass confirmation</li></ul>To better understand how complementary GC-MS techniques can improve confidence in battery solvent analysis, download the full application note: <a target="_blank" rel="noopener noreferrer" href="https://www.leco.com/documents/203-821-731/">“Battery Solvent Characterization: Identifying Impurities in Dimethyl Carbonate”.</a>

 Confident Identification of Battery Solvent Impurities Using Complementary GC-MS Techniques

The international standard ISO/IEC 17025 [1] clause 7.7.2 with regards to ensuring the validity of results, requires a laboratory to participate in proficiency testing (PT) and/or to participate in interlaboratory comparisons (ILCs) other than PT. However, no guidance as to what these other ILCs might be, or indeed how they might compare in relation to PT, is provided. This leaflet aims to outline other ILCs available, pointing out some of the limitations as compared to PT.&nbsp;There are three major types of ILCs in which a group of laboratories analyses identical portions from a homogeneous, stable test sample, with each type being characterized by its intended purpose [2,3]:<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_Interlaboratory_comparisons_other_than_proficiency_testing_2_d9263807fb.jpg" alt="Eurachem: Interlaboratory comparisons other than proficiency testing" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_Interlaboratory_comparisons_other_than_proficiency_testing_2_d9263807fb.jpg 245w," sizes="100vw" width="1507" height="607">A key point is that PT is an ILC that is designed to specifically evaluate the performance of participants, providing them with an infrastructure to monitor and assess the validity of their results. This is not the key purpose of the two other ILCs, and thus depending on their intended purpose they have a number of limitations that laboratories need to be aware of when using them rather than PT. Only proficiency testing should have been conducted in full compliance to the competency standard ISO/IEC 17043 [4].&nbsp;<h4>Evaluation of measurement procedure performance&nbsp;</h4>These ILCs, are designed to assess how a particular measurement procedure performs and whether it is fit for its intended purpose. These ILCs are often referred to as a ‘method performance study’ or a ‘collaborative study’ [2]. Some limitations of using such ILCs for monitoring laboratory performance as an alternative to PT are:&nbsp;<ul><li>All participants use the same measurement procedure i.e. the measurement procedure that is being validated. Unless the measurement procedure is being routinely used by the participating laboratory such an ILC will not assess the routine performance of the laboratory using their own routine measurement procedure. Nor does it enable them to compare their performance with other laboratories using alternative measurement procedures.&nbsp;</li><li>The measurement procedure is likely to be new, so participants may not have established stable procedures and quality control, so performance may not reflect routine use.&nbsp;</li><li>The report from such an ILC would not provide information on the performance of the participant, if the statistical model used makes the assumption that all laboratories perform with equal variability.</li><li>The design of the study may require the participants to assess multiple samples and/or to undertake multiple replicate analysis on the test materials. This may not be representative of the routine measurements or tests undertaken by the laboratory.&nbsp;</li><li>The conclusion of the ILC might be that the measurement procedure being assessed is not valid.&nbsp;</li></ul><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_Interlaboratory_comparisons_other_than_proficiency_testing_3_a53ecd2f5d.jpg" alt="Eurachem: Interlaboratory comparisons other than proficiency testing" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_Interlaboratory_comparisons_other_than_proficiency_testing_3_a53ecd2f5d.jpg 157w," sizes="100vw" width="570" height="566"><h4>Characterisation of candidate reference materials&nbsp;</h4>These are ILCs that assign a property value to a candidate reference material, usually with a stated measurement uncertainty. These are often referred to as a ‘material certification study’ [2]. Limitations of using such ILCs as an alternative to PT are:&nbsp;<ul><li>The analysis of the candidate reference material is likely to require additional care in exercising the routine measurement procedure, such as substantially more replication, and/or may require quite different reporting formats (e.g. all valid replicates instead of a mean result). Thus, such an ILC will not necessarily provide an evaluation of the performance of the laboratory based on the routine use of their measurement procedures.&nbsp;</li><li>The report from such an ILC may include the results from the participating laboratories but would not provide information on the performance of each laboratory.&nbsp;</li><li>Participating laboratories may be required to assess multiple samples and/or to undertake multiple replicate analysis on the candidate reference materials. Thus this may not be representative of the routine measurements or tests undertaken by the laboratory.&nbsp;</li></ul><h4>Other ILCs&nbsp;</h4>Some other ILCs, whilst not being conducted in full compliance of the requirements of ISO/IEC 17043, may be designed to evaluate participant performance. These would include small ILCs as defined by EA‑2/21 [5] or split sample ILCs i.e. where a portion of a single sample is sent to two or three laboratories. Whilst these ILCs are specifically designed to evaluate participant performance, they may not provide a comprehensive comparison that a PT might provide. In such cases the laboratory needs to evaluate carefully the competence of the organization managing the ILC and the suitability of the service externally provided (ISO/IEC 17025 clause 6.6).

Interlaboratory comparisons other than proficiency testing

RI Calibration in NIST26 Chromatogram and Applying to Calculating RI in Samples

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Application

Academy

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Eurachem is a European network promoting international traceability of chemical measurements and good analytical practice. It provides expert guidance, supports method validation, uncertainty evaluation, proficiency testing, and facilitates discussion on technical and policy issues in analytical quality.

Eurachem

In 1936, the Laboratory Equipment Company introduced the first rapid carbon determinator for the American iron and steel industry.  Today, almost 80 years later, LECO is recognized globally as a leader in the development of high-quality analytical instrumentation, mass spectrometers, comprehensive two-dimensional chromatography, metallography & optical equipment as well as consumables.

LECO

My main interest is the identification of organic compounds by mass spectrometry in organic mixtures.

James Little/Mass Spec Interpretation Services

LECO ChromaTOF Identification Grading System

ChromaTOF Identification Grading System assigns confidence scores to GC×GC-HRTOFMS identifications using accurate mass, spectra, fragments, and retention indices for faster, defensible results.

<h3>Bring the power of accurate mass and confidence to compound identification</h3>The LECO Identification Grading System™ (IGS™) is designed to simplify and accelerate data review by clearly indicating how confident you can be in each compound identification. By consolidating all available chemical evidence into a single, intuitive grading metric, IGS enables users to quickly justify identifications, report results with confidence, and make informed decisions on next analytical steps.IGS is tightly integrated with data generated by the Pegasus GC-HRT 4D platform and is especially powerful for non-targeted workflows, where large numbers of unknown or partially known compounds must be evaluated efficiently and objectively.<h3>Key Features</h3>The Identification Grading System leverages the full chemical information content produced by GC×GC-HRTOFMS to strengthen confidence in “unknown unknown” identification.Each compound identification is assigned a grade based on four independent criteria:<ul><li>Presence and accurate mass of the molecular ion</li><li>Presence and strong spectral similarity score from a curated reference library</li><li>Accurate mass agreement of chemically reasonable fragment ion formulae associated with the library hit</li><li>Retention index agreement with the corresponding library entry</li></ul>The resulting numerical grade provides an immediate, transparent indicator of identification confidence—the higher the grade, the stronger the supporting evidence.<h3>Theory of Operation</h3>The full potential of confident identification is realized through the combined capabilities of comprehensive two-dimensional gas chromatography (GC×GC) and high-resolution time-of-flight mass spectrometry (TOFMS).GC×GC separates co-eluting species that would otherwise interfere with spectral interpretation, producing significantly cleaner mass spectra. High-resolution TOFMS delivers accurate, unskewed mass spectra across the entire chromatographic peak, including extremely narrow second-dimension peaks. When combined with advanced deconvolution, this results in exceptionally high-quality spectral information.Developed in response to the challenges highlighted by the U.S. EPA’s Non-Targeted Analysis Collaborative Trial (ENTACT), IGS directly addresses the time-consuming and subjective nature of traditional data review. It provides a systematic, evidence-based approach to filtering large result sets and focusing attention on the most reliable identifications.<h4>Practical Impact in Non-Target Analysis</h4>In GC×GC-TOFMS datasets from the EPA ENTACT challenge, unfiltered deconvolution can yield thousands of tentative identifications. Applying the IGS filter dramatically reduces this number, immediately highlighting the most confident matches and allowing analysts to focus on true unknowns with high priority.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/LECO_Identification_Grading_System_3_9b33a4d091.jpg" alt="LECO: Identification Grading System" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_LECO_Identification_Grading_System_3_9b33a4d091.jpg 245w," sizes="100vw" width="513" height="120">In blind ENTACT samples, IGS correctly identified approximately 80% of known compounds introduced into the sample, demonstrating that the combination of GC×GC separation and high-resolution TOFMS is essential for high-confidence non-target identification.

LECO ChromaTOF® Tile analytical software

ChromaTOF Tile enables rapid, statistically robust GC×GC-TOFMS data comparison using tiled heatmaps, reducing false positives and cutting data mining from days to minutes.

Turn Your Data into ChemistryThe volume of GC×GC-TOFMS data can quickly become overwhelming. Thousands of analytes across multiple tables may require months of pixel-level data mining, often complicated by false positives caused by normal chromatographic variation.ChromaTOF Tile fundamentally changes how GC×GC data are compared and interpreted. Instead of evaluating individual pixels, the software statistically compares tiled regions of chromatograms. Truly significant differences rise immediately to the surface—allowing you to focus on chemical meaning rather than data hunting.<blockquote>“ChromaTOF Tile is an enabling technology that has reduced our peak picking time from 10 days to 10 minutes.”</blockquote><h3>Designed for Sample Group Differentiation</h3>Integrated heatmap tables provide instant visual feedback on relative intensities and variance. ChromaTOF Tile highlights differences between two or more sample classes, including:<ul><li>Biomarkers distinguishing healthy vs. diseased samples</li><li>Off-odor detection in food quality control</li><li>Environmental samples upstream/downstream of contamination sources</li><li>Petroleum samples from different geographic origins</li><li>Any complex GC×GC comparison where class differentiation matters</li></ul><h3>Key Features</h3><ul><li>Stand-alone software designed to work in conjunction with <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/41">ChromaTOF</a></li><li>Rapid statistical comparison of GC×GC data sets</li><li>Exportable tables and plots for efficient reporting</li><li>Clean, library-searchable spectra generated from tiling</li><li>Approximate trend quantification using tile areas</li><li>Reduced false positives from chromatographic misalignment</li></ul><h3>Theory of Operation</h3>The challenge: Comparing large sets of GC×GC chromatograms is slow and alignment-sensitive, often taking weeks or months even with automated tools.The solution: In collaboration with Robert Synovec, ChromaTOF Tile applies Fisher ratios to partition chromatograms into regions (“tiles”). Instead of pixel-by-pixel comparison, corresponding tiles are averaged and statistically evaluated.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/LECO_Chroma_TOF_Tile_analytical_software_816a8a7705.jpg" alt="LECO ChromaTOF® Tile analytical software" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_LECO_Chroma_TOF_Tile_analytical_software_816a8a7705.jpg 245w," sizes="100vw" width="854" height="462">The result is a set of intuitive heatmaps that immediately direct attention to regions of high variance and high analytical relevance—without altering the underlying data.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/LECO_Chroma_TOF_Tile_analytical_software_2_c3c8abd476.jpg" alt="LECO ChromaTOF® Tile analytical software" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_LECO_Chroma_TOF_Tile_analytical_software_2_c3c8abd476.jpg 245w," sizes="100vw" width="1045" height="566">

LECO Simply GC×GC®

Simply GC×GC from LECO guides users through the steps of creating an optimized GC×GC method or converting an existing 1D GC method for complex samples.

Simply GC×GC from LECO is a free tool designed to walk users through the steps of creating an optimized GC×GC method for complex samples.The tool allows users to create a GC×GC method from scratch or convert an existing 1D GC method to GC×GC.Simply GC×GC provides logical, step-by-step instructions, for example for:<ul><li>setting the secondary oven offset,</li><li>setting the second-dimension column length,</li><li>experimentally evaluating stationary phases and peak capacity.</li></ul>Simply GC×GC takes a simple approach to GC×GC and helps users avoid unnecessary testing while streamlining the method development cycle.

ARC GCxGC Xpansion

ARC’s simple stop-flow modulator can be installed in minutes and turn any GC into a powerful multi-dimensional separation machine. ARC’s modulator emphasizes robustness, simplicity, and ease of use to allow anyone from a novice GC user to a veteran expert to generate valuable chemical data on the most complex samples. 

<h3>No-fuss GCxGC solution</h3>
This affordable package includes free, open-source software (visualization only), and ARC’s lifetime support. For power users we offer GC Image software. 
<h3>Why choose us?</h3>
<ul>
<li>Affordable</li>
<li>Robust design</li>
<li>Simple and easy self-installation or professional installation</li>
<li>Dramatically increased peak capacity</li>
<li>Easily switch between 1D and 2D GC</li>
<li><a href="https://www.activatedresearch.com/gcxgc_vis/">Free visualization software</a></li>
</ul>
<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ARC_ARC_G_Cx_GC_Xpansion_9536cf0985/ARC-ARC-GCxGC-Xpansion.jpg" alt="ARC: ARC GCxGC Xpansion solution"/>
<h3>Why should I use GCxGC?</h3>
The separation of compounds by gas chromatography is typically performed using a single analytical column. As samples become more complex, it can become difficult to separate all the compounds from each other and they can start to overlap, or co-elute. Longer or narrower columns can be used to increase resolving power, but with diminishing returns.
Comprehensive two-dimensional GC, or GCxGC, drastically increases separation power by adding a second analytical column after the first column. A modulator placed between the two columns pulses the analytes from the first column onto the second column. When the columns are orthogonal in separation power, this technique can result in an order of magnitude increase in the number of analytes that can be detected.
ARC’s solution takes advantage of stop-flow modulation to make GCxGC an attainable configuration for any analytical laboratory. It involves continually sampling the effluent from the first column into an accumulator tube and re-injecting it onto a second, smaller column with orthogonal separation. This second separation happens in the time it takes to accumulate the next sample. The pulse time is known as the modulation time.

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RI Calibration in NIST26 Chromatogram and Applying to Calculating RI in Samples

Interlaboratory comparisons other than proficiency testing

Confident Identification of Battery Solvent Impurities Using Complementary GC-MS Techniques