Commercial and public spectral libraries provide broad coverage for LC-MS/MS identification, but they cannot contain every compound that matters to a specific laboratory. Proprietary products, metabolites, intermediates, impurities, degradation products, biomarkers, and internally characterized compounds may be highly relevant even if they are absent from standard reference collections. NIST26 allows laboratories to build their own MS/MS user libraries and integrate them directly into routine search workflows, creating a focused resource tailored to their analytical needs.<h4>Why Create a User MS/MS Library?</h4>User libraries are usually much smaller than commercial or public spectral databases, but their value is not determined by size alone.A laboratory-specific library may contain exactly the compounds most important for a particular application. These can include:<ul><li>proprietary products,</li><li>known metabolites,</li><li>synthesis intermediates,</li><li>impurities,</li><li>degradation products,</li><li>biomarkers,</li><li>compounds associated with specific industrial or environmental samples.</li></ul>Such libraries can therefore provide highly relevant identifications in pharmaceutical development, industrial R&amp;D, medical laboratories, environmental analysis, and other specialized fields. A relatively small collection of carefully characterized compounds may be more useful for a particular laboratory than a much larger general-purpose database.&nbsp;<h4>What Information Can Be Stored with Each Spectrum?</h4>Creating a useful library entry involves more than importing an MS/MS spectrum.A complete record can combine several types of information, including the experimental spectrum, chemical structure, instrumental parameters, ionization information, sample history, and additional user-defined metadata.Spectra can be transferred from vendor software into NIST Library Search, or they can be sent from the Chromatogram tab directly to the Library Search environment in NIST26. Chemical structures can be imported through the Windows clipboard from a molecular drawing program, while standard experimental parameters and sample-history information can be prepared separately and added to the entry.&nbsp;The ability to keep analytical metadata together with the spectrum is particularly important for internally generated libraries because it preserves the context in which the reference spectrum was acquired.<h4>Using Tags to Organize LC-MS/MS Metadata</h4>NIST26 supports a range of structured tags for LC-MS/MS spectra.These can describe parameters such as:<ul><li>spectrum type,</li><li>compound type,</li><li>ion name,</li><li>precursor type,</li><li>precursor m/z,</li><li>collision energy,</li><li>instrument type,</li><li>sample identifier,</li><li>ionization mode,</li><li>ion polarity,</li><li>collision gas,</li><li>pressure,</li><li>mass range,</li><li>maximum intensity,</li><li>cone voltage,</li><li>charge,</li><li>molecular weight,</li><li>known impurities,</li><li>related CAS numbers,</li><li>peptide sequence and peptide modifications.</li></ul>This provides a convenient way to attach searchable and standardized experimental information to spectra rather than leaving all metadata in an unstructured comment field.&nbsp;Tags can be entered individually through the Additional Info section in the Librarian interface, but when many spectra are being added, a grouped approach can be considerably faster.&nbsp;<h4>Adding Groups of Tags Efficiently</h4>For repetitive workflows, metadata can be prepared in advance and pasted into NIST26 as a group.The presentation recommends maintaining frequently used tag sets in a simple text document, then copying them into the synonym field and using Add to List to convert them into structured information.This is especially useful when the vendor software already transfers some parameters automatically. Users can then add only the missing information, such as ion adduct or polarity, rather than duplicating metadata already imported with the spectrum.&nbsp;Care is required because entering information that is already present may create duplicate metadata.This workflow can substantially accelerate library creation when many spectra share the same instrument configuration or acquisition parameters.<h4>Preserving Sample History</h4>A spectral match is more useful when the origin of the reference spectrum is known.NIST26 therefore allows detailed sample information to be stored in the comment field. For batches of related samples, the text can be prepared in Notepad or another editor and pasted into multiple records.Examples of useful information include sampling location, sampling date and time, analyst name, organization, internal sample identifier, project information, or other relevant context.&nbsp;For environmental, clinical, pharmaceutical, and industrial laboratories, this information can become an important part of data traceability.<h4>Adding Molecular Structures</h4>A user library becomes considerably more useful when spectra are linked to molecular structures.Structures can be created from scratch in a chemical drawing program. Alternatively, a similar structure can be located in NIST Search and sent to the default structure editor, where it can be modified as needed.Once completed, the structure can be copied to the Windows clipboard and inserted into the NIST Librarian spectrum-information window. NIST26 can then calculate the molecular formula and molecular weight from the imported structure.&nbsp;This linkage between spectrum and structure supports more informative library displays and structure-based searching.<h4>Creating Custom User-Defined Tags</h4>In addition to the standard LC-MS/MS tags, laboratories can define their own metadata fields.Examples shown include identifiers such as:<ul><li>chemist,</li><li>laboratory notebook number,</li><li>analyst.</li></ul>The information can be prepared in a text editor and added using the appropriate tag syntax. Once configured in the Comment Field Display settings, these values are displayed as separate structured lines rather than remaining embedded in the general comments.&nbsp;This flexibility makes the library more suitable for laboratories with established internal documentation systems or quality-management requirements.NIST can also automatically add information such as the InChIKey and an estimated retention index when appropriate structural information is available.&nbsp;<h4>High-Resolution and Low-Resolution Libraries Should Be Kept Separate</h4>User libraries do not have to contain only high-resolution spectra.Low-resolution MS/MS spectra may also be valuable, including spectra generated by:<ul><li>in-source collision on single-quadrupole instruments,</li><li>triple-quadrupole MS/MS,</li><li>other nominal-mass workflows.</li></ul>The recommendation is to maintain separate high-resolution and low-resolution user libraries, because the appropriate search strategies and handling can differ.&nbsp;Low-resolution spectra can still generate strong library-search results and may be particularly useful when laboratories want to preserve historical data or incorporate spectra from multiple instrument types.<h4>Important Software Considerations When Importing Spectra</h4>The presentation also highlights several practical software issues that users should be aware of.One concerns the Intensity Threshold setting in the Spectrum Import Options window. When an intensity threshold is applied during import from vendor software, high-resolution spectral values may be converted to nominal mass rather than preserving the expected decimal precision.For laboratories building high-resolution user libraries, this is an important detail because accurate-mass information is one of the main advantages of HRMS data.Another issue affects some library-search modes after high-resolution spectra are added to a user library.<h4>HiRes No Precursor and Hybrid Search Limitations</h4>After adding high-resolution spectra, certain HiRes NoPrecursor and Similarity Hybrid MS/MS searches may not function correctly.A workaround involves exporting the affected library using Lib2NIST into MSP ASCII files together with the associated molecular structure files, then importing the data back into NIST library format.&nbsp;The presentation specifically warns against attempting the problematic MS/MS Hybrid Search under these conditions because it may cause the software to crash.An EI Normal search can mimic some of the functionality of HiRes No Precursor and may work effectively when high- and low-resolution libraries are searched together. HiRes NoPrecursor can also operate with presearch disabled, although this can make searching considerably slower.&nbsp;<h4>Display Issues in the Chromatogram Window</h4>Another software behavior concerns how spectral values are displayed in the Chromatogram tab.Values from Spectrum Import Options are reflected in the head-to-head spectral display. If settings are adjusted for low-resolution spectra, the displayed masses may appear truncated.Importantly, this visual behavior does not affect the results in the accurate-mass deconvolution and library-searching table; it affects only the spectral display at the top of the Chromatogram window.&nbsp;Distinguishing display behavior from actual processing results is important to avoid misinterpreting valid search results as corrupted data.<h4>Updating the Library After Adding New Entries</h4>User-library maintenance does not end when a spectrum has been added.Whenever a new entry containing a molecular structure is introduced, the structure index should be updated so that the new compound can be included properly in structure searching.The InChIKey appears to update with the structure, but if duplicate records are not being handled correctly, the InChIKey index may also need to be rebuilt.&nbsp;If a new library folder is added to the NIST26 MSSEARCH directory while the software is already running, users should also update the library list so that the newly added collection becomes available without restarting the entire environment.&nbsp;<h4>Using Lib2NIST to Repair High-Resolution User Libraries</h4>The Lib2NIST utility plays an important role in resolving some high-resolution library-search issues.The workflow involves exporting the problematic high-resolution library to an MSP file together with its molecular structure files and then re-importing the data into NIST library format.The corrected library can then be placed back into the NIST26 MSSEARCH directory. It is advisable to preserve the original library under a different name until the repaired version has been tested successfully.&nbsp;The presentation also recommends closing NIST Search while performing Lib2NIST conversions.<h4>Small Libraries Can Deliver High Analytical Value</h4>The central message is straightforward: a user library does not need to contain hundreds of thousands of compounds to be useful.A carefully curated collection of spectra from compounds that repeatedly appear in a laboratory's own samples can dramatically improve identification relevance. This is especially valuable for compounds that are proprietary, newly synthesized, application-specific, or otherwise poorly represented in public and commercial databases.By combining MS/MS spectra with structures, acquisition metadata, sample history, tags, and internally defined information, NIST26 can become more than a search engine for commercial databases. It can serve as a laboratory-specific knowledge base built around compounds that genuinely matter to the user's work.For specialized LC-MS/MS workflows, that may be one of the most valuable ways to extend the capabilities of spectral library searching.

Creating MS/MS User Libraries in NIST26

Wiley announces the expansion of its spectral libraries across IR and Raman, adding empirical and computed reference data spanning forensics, pigments and dyes, mineralogy, materials, polymers, and pharmaceuticals. This release adds over a thousand new empirical reference spectra, plus more than 429,000 new SmartSpectra records, across dozens of updated and new databases. This brings the combined collections to over 1.4 million IR spectra and 230,000 Raman spectra.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Wiley_Wiley_continues_to_expand_its_IR_Raman_and_Smart_Spectra_spectral_libraries_806b34cdc1.jpg" alt="Wiley: Wiley continues to expand its IR, Raman, and SmartSpectra spectral libraries" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Wiley_Wiley_continues_to_expand_its_IR_Raman_and_Smart_Spectra_spectral_libraries_806b34cdc1.jpg 245w," sizes="100vw" width="1600" height="838">“Scientific discoveries and business decisions depend on trustworthy analytical results,” said Graeme Whitley, senior director, data science solutions at Wiley. “The value of a spectral library expansion is not simply that it adds more records. It gives analysts more relevant reference candidates when they encounter unfamiliar materials, whether they are verifying a polymer, investigating a pharmaceutical sample, examining a mineral, or screening a forensic specimen.”<h4>Highlights include:</h4><ul><li>Forensics: A new Raman forensics database adds reference spectra for colorant and dye identification on textiles, drawn from real fiber-evidence research, useful for investigators working on dye and textile analysis.</li><li>Pigments and dyes: New Raman and IR data significantly broadens pigment and dye coverage, including historic artists' pigments, supporting art conservation and cultural-heritage authentication work.</li><li>Minerals: New Raman and IR data extends coverage to minerals from different localities and Martian mineral analogs. This release includes new Raman additions from our ongoing collaboration with the American Museum of Natural History, now cross-referenced with DANA Classification Numbers and Mindat IDs, giving mineralogists and gemologists an easier way to identify entries against established references.</li><li>Materials and semiconductors: New Raman and IR data covers crystal growth relevant to battery materials, rare-earth-doped magnetic crystals, and flexible and 2D semiconductor materials, useful for researchers in battery, magnetic materials, and electronics work.</li><li>Polymers: New Raman and IR data spans 3D-printed, MOF-integrated microlattices, environmental plastic aging and recycled PET materials, and food packaging plastics. New Raman reference spectra also cover more than two dozen synthetic polymer types for identifying microplastics in environmental samples.</li><li>Clinical and pharma: New Raman and IR data covers antibiotic classes, including beta-lactams, and the WHO's essential antibiotic list, plus bone mineralization studies in clinical models. A new IR dataset also adds spectra for common over-the-counter medications, including aspirin, ibuprofen, and paracetamol, helping quality control teams confirm formulations faster.</li><li>SmartSpectra: Our SmartSpectra IR, Raman, and vapor-phase IR collections continue to grow, adding 243,000+ IR, 67,000+ Raman, and 119,000+ vapor-phase IR computed reference spectra to support broad, high-throughput identification.</li></ul><blockquote><a target="_blank" rel="noopener noreferrer" href="https://sciencesolutions.wiley.com/spectral-databases/">Learn more about Wiley Spectral Databases</a><a target="_blank" rel="noopener noreferrer" href="https://sciencesolutions.wiley.com/how-to-update-knowitall-databases/">Existing subscribers can find guidance on updating their databases here</a></blockquote><h4>Wiley Spectral Databases</h4>Wiley's spectral databases are consistently evolving to meet today's research demands, covering multiple spectral techniques across a wide range of applications including polymers, materials, environmental, forensics, toxicology, pharmaceutical, biotech, automotive, aerospace, food, cosmetics, and more. Built on rigorous quality protocols, Wiley delivers industry-leading spectral data and intelligent tools to accelerate analysis and deliver deeper insights — making it the authoritative, trusted source that analytical labs worldwide rely on.&nbsp;

Wiley continues to expand its IR, Raman, and SmartSpectra spectral libraries

Per- and polyfluoroalkyl substances (PFAS)&nbsp;analysis is no longer&nbsp;defined by&nbsp;a fixed list of known compounds.As regulatory frameworks evolve and scientific understanding deepens, laboratories are being asked to go beyond routine testing. In addition to quantifying known PFAS, they must also investigate unknown, unexpected, and emerging compounds that fall outside predefined target lists.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Fisher_Scientific_PFAS_Analysis_Beyond_the_Target_List_Connecting_Quantitation_and_Discovery_in_a_Single_Workflow_509ce49fc2.webp" alt="Thermo Fisher Scientific: PFAS Analysis Beyond the Target List: Connecting Quantitation and Discovery in a Single Workflow" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Fisher_Scientific_PFAS_Analysis_Beyond_the_Target_List_Connecting_Quantitation_and_Discovery_in_a_Single_Workflow_509ce49fc2.webp 245w," sizes="100vw" width="1024" height="526">This shift introduces a fundamental analytical challenge.Targeted quantitation provides robust and validated concentration data for known PFAS. However, by design, it only answers questions about compounds already included in the method. In contrast, non-targeted analysis,&nbsp;using high-resolution accurate-mass&nbsp;(HRAM)&nbsp;data,&nbsp;enables scientists to explore the broader chemical landscape, revealing&nbsp;additional&nbsp;PFAS&nbsp;that were not included in a targeted quantitation method.For PFAS, where thousands of structurally related compounds and transformation products may be present, neither approach&nbsp;alone provides a complete picture.The&nbsp;real challenge&nbsp;lies in connecting these workflows. Discovery findings must be translated into actionable results that can be reviewed, followed up, and reported within a controlled analytical framework.In a previous&nbsp;<a target="_blank" rel="noopener noreferrer" href="https://labrulez.com/en-us/all/article/7167">blog post</a>, we introduced how <a target="_blank" rel="noopener noreferrer" href="https://labrulez.com/en-us/all/products/1759">Thermo Scientific Compound Discoverer software </a>and <a target="_blank" rel="noopener noreferrer" href="https://labrulez.com/en-us/all/products/76">Thermo Scientific Chromeleon Chromatography Data System&nbsp;(CDS)&nbsp;</a>connect discovery and routine workflows.&nbsp;Here, we explore what that connection looks like in practice using PFAS analysis as an example.<h3>Why PFAS&nbsp;requires&nbsp;more than one analytical question</h3>PFAS&nbsp;represent a&nbsp;large&nbsp;and diverse class of compounds,&nbsp;with&nbsp;some&nbsp;estimates exceeding&nbsp;40,000 individual substances. Regulatory methods typically focus on a limited subset, yet environmental and biological samples often&nbsp;contain&nbsp;many more&nbsp;PFAS, including precursors and transformation products.This creates two&nbsp;essential and&nbsp;complementary analytical questions:How much of these known PFAS are present?andWhat other PFAS-related compounds might be present?A complete workflow needs to support both&nbsp;questions.<h3>Starting with targeted quantitation</h3>For known PFAS, targeted quantitation&nbsp;remains&nbsp;the&nbsp;backbone of routine analysis.Chromeleon CDS provides&nbsp;a&nbsp;controlled environment for&nbsp;data acquisition, processing, calibration, and reporting. In a PFAS workflow,&nbsp;this supports routine quantitation of predefined targets using laboratory-specific method and review criteria.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Fisher_Scientific_PFAS_Analysis_Beyond_the_Target_List_Connecting_Quantitation_and_Discovery_in_a_Single_Workflow_2_7ff8eda8fe.jpg" alt="Thermo Fisher Scientific: PFAS Analysis Beyond the Target List: Connecting Quantitation and Discovery in a Single Workflow: Figure 1. Targeted quantitation of known PFAS in Chromeleon CDS.&nbsp;This example is&nbsp;from the analysis of PFAS using a&nbsp;Thermo Scientific&nbsp;Orbitrap Exploris&nbsp;240. Here&nbsp;we are showing&nbsp;the&nbsp;calibration curve (right) and extracted&nbsp;ion chromatogram&nbsp;(left)&nbsp;of 7:3 FTCA&nbsp;at 6 ng/L.&nbsp;The bottom&nbsp;half&nbsp;shows the processing method that&nbsp;contains&nbsp;many target PFAS and&nbsp;isotopically-labelled&nbsp;internal standards." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Fisher_Scientific_PFAS_Analysis_Beyond_the_Target_List_Connecting_Quantitation_and_Discovery_in_a_Single_Workflow_2_7ff8eda8fe.jpg 208w," sizes="100vw" width="794" height="596">This targeted workflow is essential, but it is only part of the story. A sample may contain PFAS-related compounds not included in the original method.<h3>Looking beyond known PFAS</h3>Once HRAM data have been acquired, the same dataset can be explored beyond the target list using Compound Discoverer software. This enables comprehensive analysis of complex datasets, including:<ul><li>Detection and alignment of unknown features</li><li>Statistical comparison across samples and blanks</li><li>Spectral library searching and database annotation</li><li>Evaluation of isotope patterns, fragmentation, and homologous series</li></ul>For PFAS, this is particularly valuable. The software can leverage characteristic properties such as negative mass defect, CF₂-based homologous series, and diagnostic fragment ions to prioritize PFAS-related candidates and assign confidence to putative identifications.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Fisher_Scientific_PFAS_Analysis_Beyond_the_Target_List_Connecting_Quantitation_and_Discovery_in_a_Single_Workflow_3_e523e1cdc9.jpg" alt="Thermo Fisher Scientific: PFAS Analysis Beyond the Target List: Connecting Quantitation and Discovery in a Single Workflow: Figure 2. Discovery of additional PFAS-related components in Compound Discoverer software. Here we show an example of using PFAS fragment libraries, one of many PFAS-specific resources available within Compound Discoverer software, to annotate fragments within acquired MS2 spectra of two unknown compounds and then identify them as PFAS that were outside the targeted quantitation method." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Fisher_Scientific_PFAS_Analysis_Beyond_the_Target_List_Connecting_Quantitation_and_Discovery_in_a_Single_Workflow_3_e523e1cdc9.jpg 233w," sizes="100vw" width="1520" height="1016">The goal of discovery is not simply to generate more data. It is to reduce complexity and identify the most relevant candidates for further investigation with a defined level of confidence.<h3>From discovery to follow-up</h3>One of the most important questions in non-targeted analysis is what happens after candidate identification.Discovery workflows can identify interesting candidates, but those candidates need to move into a practical follow-up process. Scientists may want to monitor them across additional samples, estimate relative or semi-quantitative abundance, trend their presence over time, or include them in a reviewable report.This is where the connection between Compound Discoverer software and Chromeleon CDS becomes especially valuable.After PFAS candidates have been prioritized in Compound Discoverer software, selected components can be transferred back into Chromeleon CDS and incorporated into the Chromeleon processing methods for follow-up analysis. This allows scientists to evaluate these compounds within the same controlled environment used for targeted quantitation.For PFAS analysis, this may support semi-quantitative follow-up for compounds where authentic standards are not yet available. While fully quantitative results require appropriate standards and validated methods, semi-quantitative workflows can provide useful estimates or relative comparisons to help prioritize further investigation.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Thermo_Fisher_Scientific_PFAS_Analysis_Beyond_the_Target_List_Connecting_Quantitation_and_Discovery_in_a_Single_Workflow_4_8ee8ebc2df.jpg" alt="Thermo Fisher Scientific: PFAS Analysis Beyond the Target List: Connecting Quantitation and Discovery in a Single Workflow: Figure 3. Prioritized PFAS candidates brought back into Chromeleon CDS for follow-up. Prioritized PFAS candidates from Compound Discoverer software can be brought back into Chromeleon CDS for follow-up review, semi-quantitative evaluation, and controlled reporting." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Thermo_Fisher_Scientific_PFAS_Analysis_Beyond_the_Target_List_Connecting_Quantitation_and_Discovery_in_a_Single_Workflow_4_8ee8ebc2df.jpg 245w," sizes="100vw" width="1512" height="751">This is the key workflow advantage: discovery does not stop at identification. It can feed directly into a practical analytical process.<h3>Why this matters</h3>PFAS analysis increasingly requires laboratories to balance routine testing with exploratory investigation.A connected workflow between Chromeleon CDS and Compound Discoverer software supports this by:<ul><li>Combining targeted quantitation and non-targeted discovery to characterize samples more completely</li><li>Reducing manual data transfer and workflow fragmentation</li><li>Enabling discovery results to be reviewed and reported within a controlled CDS environment</li><li>Supporting investigation of emerging PFAS investigations without immediate method redevelopment</li><li>Bridging research-driven insights with routine analytical workflows</li></ul>This reflects a broader shift in analytical science, where the value lies not only in generating data, but in connecting workflows and turning data into actionable information.<h3>Moving PFAS analysis forward</h3>PFAS analysis is evolving from a fixed target list toward a more comprehensive understanding of complex chemical mixtures.Laboratories must quantify known compounds while remaining prepared to identify and evaluate what lies beyond them.By connecting Compound Discoverer software with Chromeleon CDS, laboratories can move seamlessly from targeted quantitation to discovery and into structured follow-up. The result is a more complete view of PFAS contamination and a more efficient path from data to insight.<h3>Learn more</h3>Explore how <a target="_blank" rel="noopener noreferrer" href="https://labrulez.com/en-us/all/products/1759">Compound Discoverer software</a> and<a target="_blank" rel="noopener noreferrer" href="https://labrulez.com/en-us/all/products/76"> Chromeleon CDS </a>can help connect targeted quantitation and non-targeted discovery workflows for <a target="_blank" rel="noopener noreferrer" href="https://www.thermofisher.com/content/lifetech/global/en/home/industrial/environmental/environmental-contaminant-analysis/emerging-contaminants/pfas-testing.html">PFAS analysis</a>.<blockquote>Visit us on&nbsp;<a target="_blank" rel="noopener noreferrer" href="https://www.linkedin.com/showcase/72003132/admin/dashboard/">LinkedIn:</a>&nbsp;#PFAS #Chromeleon #CompoundDiscoverer #Environmental</blockquote>

PFAS Analysis Beyond the Target List: Connecting Quantitation and Discovery in a Single Workflow

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James Little/Mass Spec Interpretation Services

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>
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<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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