LIBS is an emerging material-composition analytical technique based on spectroscopic analysis of light emitted by the laser spark induced in a sample of interest. It allows stand-off and real-time analysis capabilities in the field with no sample preparation.

This dataset contains spectral data obtained from scanning data of recycled building materials using Laser-Induced Breakdown Spectroscopy (LIBS). The research objective was to accurately distinguish various components within recycled construction materials. Data collection involved scanning RCA samples with LIBS, which produces detailed emission spectra from the breakdown of material components. The resulting data includes spectral signatures corresponding to the elemental composition of the materials, providing a foundation for analyzing the quality and composition of recycled concrete. The dataset supports efforts to improve the efficiency of recycling processes in construction.

The MSL ChemCam LIBS RDR data set contains calibrated spectra and higher level products derived from raw data collected by the ChemCam Laser Induced Breakdown Spectrometer on the Mars Science Laboratory rover. Standard derived products include summed calibrated spectra (RDR), Intermediate Clean Calibrated Spectra (CCS), and Multivariate Prediction of Oxide Composition (MOC) tables. Special products, which may be generated as needed and as resources permit, are Univariate Prediction of Elemental Composition (UEC) tables, Univariate Prediction of Oxide Composition (UOC) tables, Multivariate Prediction of Elemental Composition (MEC) tables, and Sammon's Map (RSM) tables.

NIST peptide libraries are comprehensive, annotated mass spectral reference collections from various organisms and proteins useful for the rapid matching and identification of acquired MS/MS spectra. Spectra were produced by tandem mass spectrometers using liquid chromatographic separations followed by electrospray ionization. Unlike the NIST small molecule electron ionization library which contains one spectrum per molecular structure, there are several different modes of fragmentation (ion trap and ?beam-type? collision cells are currently the most commonly used fragmentation devices) that result in spectra with different, energy dependent, patterns. These result in multiple spectral libraries, distinguished by ionization mode, each of which may contain several spectra per peptide. Different libraries have also been assembled for iTRAQ-4 derivatized peptides and for phosphorylated peptides. Separating libraries by animal species reduces search time, although investigators may elect to include several species in their searches.

This repository contains data (LIBS spectra) measured from a unique sample set with a certified composition. The set contains 11 samples, covering the transition from pure iron to pure cobalt with a step of 10% (composition change). Samples were measured on several distinct systems under selected conditions. The dataset was designed as a benchmark to test and compare distance metrics.

Due to plasma quenching caused by the dense water medium, laser-induced breakdown spectroscopy (LIBS) faces challenges such as strong continuous background radiation, weak and broadened characteristic spectral lines when directly detecting metal elements in liquids. In this work, we introduced a simple approach to improve underwater LIBS signal with solid substrate-assisted method, which requires no sample pre-treatment and simple operation, thus has potential for in-situ marine application. In this method, four submerged solid substrates (Zn, Cu, Ni, Si) were employed to investigate the breakdown characteristics of underwater LIBS and the mechanism of spectral enhancement by using a CaCl2 solution. The results demonstrated significant improvement in the detection sensitivity of Ca with these substrates even at a short laser pulse with a relative low laser energy (10 mJ). Among them, the semiconductor Si substrate exhibited the best enhancement effect, with an enhancement factor over 75 for the Ca ionic lines at 393.4 nm and 396.8 nm, and an enhancement factor of 29 for the Ca atomic line at 422.7 nm, respectively. This mainly because the presence of substrate decreases the breakdown threshold of liquid sample, and higher plasma excitation temperature and electron density are obtained, accordingly leading to higher signal intensity. Furthermore, significant plasma emission enhancements for a wide range of elements are also achieved from seawater. These findings can contribute to the development of compact underwater in-situ LIBS sensors with low power consumption meanwhile ensuring high detection sensitivity.

This composition appears in the B-Li-S region of phase space. It's relative stability is shown in the B-Li-S phase diagram (left). The relative stability of all other phases at this composition (and the combination of other stable phases, if no compound at this composition is stable) is shown in the relative stability plot (right)

Laser Induced Breakdown Spectrometer (LIBS) Market Outlook

The global market size for Laser Induced Breakdown Spectrometer (LIBS) was estimated at USD 250 million in 2023 and is projected to reach USD 580 million by 2032, growing at a CAGR of 9.7% during the forecast period. The rapid growth of this market is primarily driven by the increasing need for real-time, in-situ elemental analysis across various industries, as well as advancements in laser and spectrometer technologies.

One of the primary growth factors for the LIBS market is the expanding application of LIBS technology in environmental monitoring. Governments and environmental agencies are increasingly adopting LIBS for the rapid detection of pollutants and hazardous materials in air, water, and soil. This technology's ability to provide comprehensive, real-time data is critical for monitoring and mitigating environmental risks. Furthermore, the growing consciousness about environmental sustainability and stringent regulations on emissions and waste management are propelling the demand for LIBS systems.

Another significant factor contributing to the market's growth is the rising adoption of LIBS in the mining and metallurgy sectors. These industries require precise and efficient methods for analyzing the composition of ores and metals to ensure quality and optimize extraction processes. LIBS offers a non-destructive and rapid analysis solution, which is highly advantageous in these contexts. The increasing investment in mining activities and the demand for high-purity metals are further boosting the adoption of LIBS technology in these sectors.

Additionally, the pharmaceutical industry is emerging as a crucial application area for LIBS technology. LIBS is being used for the quality control and verification of pharmaceutical products, helping companies meet regulatory standards and ensure product safety. The ability of LIBS to detect contaminants and verify material composition without the need for extensive sample preparation makes it an attractive option for pharmaceutical companies looking to streamline their quality assurance processes. This expanding application scope is expected to significantly drive the market forward.

Regionally, North America holds a prominent position in the LIBS market, driven by significant investments in research and development, and the presence of key market players. The Asia Pacific region is expected to witness the fastest growth over the forecast period, attributed to increasing industrial activities and environmental monitoring initiatives. Europe also represents a substantial market share due to stringent regulatory requirements and advanced industrial sectors. Latin America and the Middle East & Africa, though smaller in market size, are showing promising growth potential, driven by increasing mining activities and environmental concerns.

Component Analysis

The LIBS market can be segmented by components into hardware, software, and services. Hardware constitutes the largest segment in terms of market share. This includes the laser sources, spectrometers, detectors, and other optical components. The advancements in laser technology and the development of compact, portable LIBS systems are positively impacting the hardware segment. Companies are focusing on enhancing the precision and efficiency of their hardware components, leading to increased adoption across various industries.

Software is another critical component of the LIBS market, playing a key role in data analysis and interpretation. Advanced software solutions are being developed to provide more accurate and detailed elemental analysis, which is crucial for applications that require high precision, such as pharmaceuticals and metallurgy. The integration of artificial intelligence and machine learning algorithms into LIBS software is further enhancing its capabilities, allowing for more sophisticated data processing and interpretation.

The services segment includes installation, maintenance, training, and consulting services related to LIBS systems. As more industries adopt LIBS technology, the demand for comprehensive support services is increasing. Service providers are focusing on offering tailored solutions to meet the specific needs of different industries, ensuring optimal performance and reliability of LIBS systems. This segment is expected to witness steady growth, driven by the need for continuous support and upgradation of LIBS systems.

Report Scope

The data for MSnLib are divided into several Zenodo records due to size constraints.

raw positive: 10966404raw negative: 10967081mzml positive and negative: 10966280spectral libraries: 11163380

This record includes the automatically generated spectral libraries (MSnLib) within mzmine, acquired using a flow injection method on an Orbitrap ID-X instrument, for all compound libraries. There are multiple files for each compound library containing MS2 only or MSn in two data formats (.mgf or .json) for both polarities.

MS2 contains next to all MS2 spectra all pseudo MS2 spectra (a full MSn tree merged into one spectrum per compound ion). MSn contains all individual MSn stages additionally. The first number for each file highlights the library building date.

7 Compound Libraries:

Short Name: Full name, Provider (Catalog number), total compounds (not all detected during library building)

MCEBIO: Bioactive Compound Library, MedChemExpress (HY-L001), 10,315 compounds

MCESAF: 5k Scaffold Library, MedChemExpress, (HY-L902), 4998 compounds

NIHNP: NIH NPAC ACONN collection of NP, NIH/NCATS, 3988 compounds

OTAVAPEP: Alpha-helix Peptiomimetic Library, OTAVAchemicals (a-helix-Peptido), 1298 compounds

ENAMDISC: Discovery Diversity Set -10, Enamine (DDS-10), 10,240 compounds

ENAMMOL: Carboxylic Acid Fragment Library + Random, Enamine and Molport, 4378 compounds

MCEDRUG: FDA-Approved Drug Library, MedChemExpress (HY-L022), 2610 compounds

Information regarding the SPECTYPE

no SPECTYPE or SINGLE_BEST_SCAN: Best spectrum for each precursor and energy (highest TIC)

'SAME_ENERGY' = Additionally, if a spectrum was acquired multiple times for a precursor with the same energy, they are merged into one spectrum only with the same energy (max. signal height used for each fragment signal).

'ALL_ENERGIES' = merged spectrum of all used energies (in our case 3 for each precursor, using the merged (same energy) if available).

'ALL_MSN_TO_PSEUDO_MS2' = mzmine merges all MSn into one pseudo MS2.

V5 fixed USIs

LIBS is an emerging material-composition analytical technique based on spectroscopic analysis of light emitted by the laser spark induced in a sample of interest. It allows stand-off and real-time analysis capabilities in the field with no sample preparation.

Fast determination of electrolyte elements in human blood plasma using surface-enhanced laser-induced breakdown spectroscopy combined with a gel film method 论文数据集

Biosignature detection is one of the most important goals in Mars missions. Since the Curiosity mission, the laser-induced breakdown spectrometer (LIBS) becomes an essential payload due to its convenience and versatility in profiling elemental chemistry. To test whether LIBS alone could filter potential biosignatures, a clastic quartz stone collected from a Mars analog setting, the western Qaidam Basin, was selected for LIBS analysis. Raman spectroscopy was used as an indicator of organic signals to support the presence of potential hypolithic communities and the dearth of epilithic biomass on the rock. A total of 344 LIBS spectra were determined and statistically analyzed using principal component analysis (PCA). Our results indicate that, with a sufficient sample size, PCA analysis can partially differentiate biotic and abiotic signals based on LIBS measures. This finding is significant since it indicates that multivariate analysis of LIBS data can be useful for biosignatures filtering on Mars exploration. Methods Located on “the roof of the world” Tibetan Plateau, the western Qaidam Basin is a cold, dry, and irradiative environment that shapes itself with landforms (e.g., dunes, yardangs, playas, wind streaks, polygonal terrains, and gullies) commonly found on Mars. A clastic quartz stone was sampled from a Cenozoic gravel deposit (38°35′44″ N, 90°59′6″ E, 3245.17 m altitude) from the hyperarid Dalangtan Playa, western Qaidam Basin, on 29 July 2021. The Cenozoic gravel deposit was likely derived from the weathering of Mesozoic (Pre-Jurassic and Jurassic) rocks, and quartz stones were common in the deposit. Visible light greenish color could be observed at the bottom of the quartz stone. Multiple spots of four vertical lines (11 spots for line 1 Qz-l1, 6 spots for line 2 Qz-l2, 9 spots for line 3 Qz-l3, and 8 spots for line 4 Qz-l4) of the Qaidam quartz stone were selected to stereoscopically investigate the spatial distribution of Raman spectra-based mineralogical or organic/biotic signals. An alpha 300R confocal Raman imaging system (WITec, Germany) incorporated with a 50x objective lens of numerical aperture = 0.55 and an excitation laser source of 532 nm was used for Raman spectral measurements. The laser wavelength was corrected using the Raman peak of a Si wafer. All spectra were acquired in a spectral range of 0-4000 cm−1 with a spectral resolution of 4.8 cm-1. To retain the resolutions of both minerals and organic matter as much as possible, laser power was kept at 3.1 mW for an integration time of 3 s with the number of accumulations of 30. To understand the elemental compositions and spectral features of chosen samples, the SciAps Z-300 Handheld LIBS Analyzer (SciAps Inc, Woburn, MA, USA) was employed for LIBS analysis (excitation source: 5-6 mJ·pulse-1, 50 Hz repetition rate, 1064 nm laser source, argon purge). Z-300 LIBS Analyzer measured the signal intensity every 0.0333 nm from 200 to 900 nm. LIBS Analyzer was equilibrated with an internal standard prior to determining the peak patterns of respective target samples. LIBS was employed to construct a pseudo-three-dimensional geochemical profile of spots on the four vertical lines identical to Raman spectroscopic measurements. The LIBS spectrum of each spot was generated by the LIBS Analyzer in quadruplicate. In addition, 140 spots from 9 oval outlines of the top, side, and bottom faces of the Qaidam quartz were measured using LIBS: 8 spots of inner circle, 16 spots of middle circle, and 15 spots of outer circle on the top face; 16 spots of upper circle, 23 spots of middle circle, and 23 spots of lower circle on the side face; and 8 spots of inner circle, 12 spots of middle circle, and 19 spots of outer circle on the bottom face. Moreover, 68 random spots (20 from the top, 28 from the side, and 20 from the bottom) of the Qaidam quartz were chosen for singlicate LIBS measurements and the downstream statistical analysis.

Appendix B. Modal mineralogy results for each LIBS ablation crater.

Data for the characterisation of chemical impurities related to the mineralogy of the perlite ore of the Zeitindag deposit (Turkey). The objective was to characterise the mineralogical content of the perlite ore and find possible correlations between mineralogy and the presence of heavy metals. Mineralogy was studied with infrared spectroscopy (laboratory(ATR) and field (portable ASD) instruments) and the chemistry with XRF and LIBS data.

This dataset is the LIBS data in tcript of Jin et al. submitted to JGR: planets.

The cosmetic modification of hair is a very common procedure used to mask or cover evidence at a crime scene. Deoxyribonucleic acid (DNA) tests are expensive and require good-quality collection of samples and a database profile. To overcome these challenges, direct analysis was performed on a large set of hair strands collected from individuals, denoted original samples, and the data were compared with those of the same samples after cosmetic modification performed by bleaching the samples in the laboratory. A total of 127 samples were evaluated in this study using two analytical techniques, wavelength-dispersive X-ray fluorescence (WDXRF) and laser-induced breakdown spectroscopy (LIBS). Instead of testing many algorithms to develop classification models for the original and bleached samples, a recent method was applied that combines information from 17 classifiers. Data fusion was also evaluated to improve the accuracy of the classification model, which was higher than 99.2%, with no requirements to select eigenvectors or thresholds.

Comprehensive dataset of 168 Libraries in Arizona, United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

LibProbe Artifact

For the sake of the evaluation we preprocessed the CCScanner data to identify all clients of the libraries used in our evaluation and included those in our MongoDB database. This artifact will start by importing this pre-processed dependency information into a docker image which is then used for the evaluation.

Running the docker image

• First load the docker image by running

  • gunzip -c libprobe_latest.tar.gz | sudo docker import - libprobe:latest

  this will load the image in your local docker images.

• Run a container from the image: docker run -it --device /dev/snd --privileged libprobe:latest /bin/bash This will run a docker container which maps the pulseaudio and alsa configurations from your local host to the docker image. This is necessary to get some clients for some target libraries to build correctly. You will need an ubuntu host machine which has pulseaudio and alsa installed.

Validating analysis results

• The docker image provided does not contain any clients due to size limitations on sharing. The Mongo database contains all the results of running this evaluation.
• To get the results it's possible to run python3 libprobe.py analyse all -n from /tmp/libprobe. This will overwrite the JSON files in the json_files directory and overwrite the graphs in the graphs directory.

Running the evaluation for one library (vorbis)

• Download clients: Go to \tmp\libprobe and run python3 libprobe.py download vorbis
• Process the library to get the APIs and the coverage information : python3 libprobe.py processlib vorbis
• Prepare clients for excluding sub directories that might contain vorbis library code: python3 libprobe.py prepclients vorbis
• Get client usages: python3 libprobe.py fetchusages vorbis
• Analyse: python3 libprobe.py analyse vorbis -n
• (optional) Measure differential coverage for improved coverage libs: python3 libprobe.py coverage vorbis

Running the evaluation for all libraries (this requires at least 300GB of disk space)

• Download clients: Go to \tmp\libprobe and run python3 libprobe.py download all
• Process the libraries: python3 libprobe.py processlib all
• Prepare clients: python3 libprobe.py prepclients all
• Get usages: python3 libprobe.py fetchusages all
• Analyse: python3 libprobe.py analyse all -n
• (optional) Measure differential coverage for improved coverage libs: python3 libprobe.py coverage

Getting baseline coverage for libraries

All libraries are cloned in /tmp/data/libraries and clients are cloned in /tmp/data/clients.

• MBedtls: Copy the script coverage.sh from /tmp/libprobe/extra into the the build directory of Mbedtls and run ./coverage.sh baseline this will calculate the baseline coverage for mbedtls.
• FFTW: Copy the script coverage.sh from /tmp/libprobe/extra into the the root dir of FFTW and run ./coverage.sh baseline this will calculate the baseline coverage for fftw
• HDF5: Copy the script coverage_hdf.sh from /tmp/libprobe/extra into the the root dir of HDF and run ./coverage_hdf.sh baseline this will calculate the baseline coverage for HDF.
• LMDB: Copy the script coverage_lmdb.sh from /tmp/libprobe/extra into the /tmp/data/libraries/LMDB@@lmdb/libraries/liblmdb and run ./coverage_lmdb.sh baseline this will calculate the baseline coverage for LMDB.
• Zip: Copy the script coverage_zip.sh from /tmp/libprobe/extra into /tmp/data/libraries/kuba--@@zip/build/CMakeFiles/zip.dir/src and run ./coverage_zip.sh baseline this will calculate the baseline coverage for zip.
• Vorbis: Copy the script cal_cov.py from /tmp/libprobe/extra to /tmp/data/libraries/xiph@@vorbis/lib/.libs and then copy all source files in the .libs folder by running cp ../*.c . from the .libs folder. Finally run python3 cal_cov.py ..
• XXhash: Copy the script coverage.sh from /tmp/libprobe/extra into /tmp/data/libraries/Cyan4973@@xxHash and run ./coverage.sh baseline this will calculate the baseline coverage for xxhash

Reproducing increased coverage using clients

• LMDB: The client we will use is Knot DNS.

  • Change directory to /tmp/data/clients/CZ-NIC@@knot and run autogen.sh.
  • Run ./configure --with-lmdb=/usr/local.
  • Then make && make check.

  Now go back to the LMDB directory and run

  • Run ./coverage_lmdb.sh after_knot.

  • Now go /tmp/libprobe and run python3 libprobe.py coverage lmdb

• VORBIS: The client we will use in SFML.

  Go to the vorbis library dir /tmp/data/libraries/xiph@@vorbis and run make clean.

  • Run make && make check && make install.
  • Go to the .libs folder and copy all c files there by doing cp ../*.c ..
  • Copy /tmp/libprobe/extra/cal_cov.py into the .libs folder and run python3 cal_cov.py .. This will show the baseline coverage.

  Go to the SFML directory /tmp/data/clients/SFML@@SFML.

  • Create build directory mkdir build && cd build.
  • Run cmake -DSFML_BUILD_TEST_SUITE=TRUE -GNinja ...
  • Run ninja.
  • Run ctest. You will see some failing tests. Thats normal as we are only interested in the Audio tests for vorbis. All Audio tests should pass.

  Go back to the .libs folder in vorbis and re-run the cal_cov.py script.

  • Now go /tmp/libprobe and run python3 libprobe.py coverage vorbis

The Laser Induced Breakdown Spectrometer (LIBS) market has been experiencing significant growth over the past few years, driven by the instrument's ability to provide rapid and accurate elemental analysis across various industries. LIBS works by using a high-energy laser pulse to create a micro-plasma at the surface

The purpose of this survey was to identify the cooperative library organizations within the United States and to gather information about these organizations. In this survey the Federal/State Cooperative System for Public Library Data collected 32 basic data items and 7 identifying items for each library. The data items include number of service outlets, full-time equivalent staff, income, operational expenditures, capital outlay, library collection, annual public service hours, library services, and inter-library loans. All 50 states and the District of Columbia are included in this file, which encompasses 8,968 libraries.