This data set contains the spectral data associated with the collection of EC-SERS spectra using mainly a nontargeted drug identification approach, with several samples using a targeted fentanyl identification approach. The data set contains the replicate measurements and averaged Raman spectra used in the characterization of the analytes (drugs of abuse and adulterant compounds) to allow for forensic library formation. The data set also contains spectra of analytes collected at varying concentrations and additional fentanyl analog data collected using a targeted method.

A mass spectral database for organic compounds. The spectra included in the database are: electron impact Mass spectrum (EI-MS), Fourier transform infrared spectrum (FT-IR), 1H nuclear magnetic resonance (NMR) spectrum, 13C NMR spectrum, laser Raman spectrum, and electron spin resonance (ESR) spectrum.

• Comprehensive and curated list of openly accessible online Raman databases with information about their content and origin. Their FAIRness level has also been evaluated.
• A tab with some relevant propietary Raman databases is also included as complementary information on the availability of Raman data
• This is a living document, check for the latest version in Zenodo https://doi.org/10.5281/zenodo.15268225! If you are aware of new databases or want to suggest modifications to the table, please let us know and we will update it.
• Disclaimer: This list of Raman spectroscopy databases is provided solely for informational purposes. Users are advised to evaluate each database individually to determine its suitability for specific needs. We provide a rough FAIRness indicator based on our best efforts. The FAIRness level of each database has not been independently assessed, and no guarantee is made regarding their adherence to FAIR standards. Additional informational fields, such as data format, licensing terms, method of access, etc., are included where available but are not guaranteed to be accurate, complete, or up to date. These attributes are based on publicly available information and may change over time. The compilers of this list do not take responsibility for the content, accuracy, availability, or usability of the databases listed, nor for any decisions made based on this information. Users should consult the original sources for the most current and authoritative details.

Establishment of nanoplastic dataset. The spectra included in the nanoplastic database were obtained directly from the plastic samples. To establish the internal Raman spectral dataset, a total of 1,000 individual nanoparticles were examined, encompassing five common plastic contaminants, namely Polyethylene (PE), polytetrafluoroethylene (PTFE), Polystyrene (PS), polymethyl methacrylate (PMMA) and Polyvinyl chloride (PVC). For each specific plastic category, 200 nanoparticles were selected for subsequent analysis.

Content In each txt file corresponding to a Raman spectrum, the first two columns are the corresponding X and Y coordinates, respectively. The columns are: X-coordinate - wavenumber, Y-coordinate - Raman signal intensity.

More data are available upon request for research purposes only. Please send an email to zhanglw@fudan.edu.cn with a brief description of the purpose of use and your request for more data.

Raman spectroscopy is a rapid, non-invasive, and non-destructive method, featuring high chemical specificity for different biological materials and low sensitivity to water. This makes it ideal for natural medicines, as it offers a relatively objective and comprehensive characterization for their complicated material basis. Therefore, Raman spectroscopy plays a crucial role in the identification of medicinal properties, authentication of authenticity, and quality control of TCMs. At present, TCMRSD stands as the only downloadable, comprehensive Raman spectral database for TCMs, which encompasses spectra of 327 Chinese medicines collected through rigorous methodological validation. The selection of TCMs for database development is based on the considerations of diversity of medicines, medicinal importance and variety of medicinal properties, in order to guarantee a comprehensive range and representation of substances used in Chinese medicine.

The RamanLab database system consists of two primary pickle files that store comprehensive mineral spectroscopic data. The main database file RamanLab_Database_20250602.pkl contains the core spectral library with reference Raman spectra for hundreds of minerals, including their wavenumber positions, relative intensities, and associated metadata such as chemical formulas, crystal systems, and space groups. This database serves as the primary reference for the correlation-based search and match functionality, enabling identification of unknown minerals through spectral comparison algorithms. The database is structured to support both individual mineral identification and complex mixed-mineral analysis workflows.The complementary mineral_modes.pkl file focuses specifically on vibrational mode assignments and implements the complete Hey-Celestian classification system with all 15 mineral groups, including Sheet Silicates, Simple Oxides, Octahedral Framework minerals, various Silicate chains (Single and Double), Ring Silicates, Complex Oxides, Hydroxides, and Mixed Modes. This database provides detailed vibrational mode information for each mineral, including fundamental frequencies, overtones, combination bands, and their structural origins. The classification system includes chemical constraints and scoring mechanisms that provide 2.0x boosts when sample chemistry matches expected mineral compositions, enabling more accurate phase identification in complex samples. Together, these databases form an integrated system that supports both spectral matching and crystallographic interpretation of Raman spectroscopic data.

Raman spectroscopy is a widely-used non-destructive material characterization method, which provides information about the vibrational modes of the material and therefore of its atomic structure and chemical composition. Raman spectra can be simulated using atomistic first-principles methods but these are computationally demanding and thus the existing databases of computational Raman spectra are fairly small. We developed an optimized workflow to efficiently calculate the Raman tensors, from which the Raman spectra can be straightforwardly simulated. The workflow was benchmarked and validated by comparison to experiments and previous computational methods for select technologically relevant material systems. Using the workflow, we performed high-throughput calculations for a large set of materials (5099) belonging to many different material classes, and collected the results to a database.

The development of uniform, consistent spectroscopic databases of Raman spectra is important for the community to maximize the value of emerging machine learning techniques. This dataset contains processed and augmented Raman spectra acquired on a variety of common plastics, with variations in manufacturer and properties such as plastic color. The Raman spectra span the frequency window from 300 to 3900 cm-1, were collected using variations in instrumentation settings, were interpolated to 1 cm-1 wavenumber spacing to ensure compatibility, and were augmented 5X by random scaling and artificial noise introduction. Three different versions of the data are provided, each enabling exploration of a different strategy for training machine learning classification models. This data was used to train microplastic classification models using K-nearest neighbor algorithm of the sklearn package in python, as published in the associated manuscript. Python pickle files are included in the dataset, which contain the optimized models and supporting information for the models. The data are being posted in support of this research. The data was created by the authors.

Raman spectra of solidified agarose and Cy 7.5-infused agarose samples

Rozenite (FeSO₄·4H₂O) is a candidate mineral component of the polyhydrated sulfate deposits on the surface and in the subsurface of Mars. In order to better understand its behavior at temperature conditions prevailing on the martian surface and aid its identification in ongoing and future Rover missions we have carried out a combined experimental and computational study of the mineral's structure and properties. We collected neutron powder diffraction data at temperatures ranging from 21 – 290 K, room temperature synchrotron X-ray data and Raman spectra. Moreover, first-principles calculations of the vibrational properties of rozenite were carried out to aid the interpretation of the Raman spectrum. In this work, we demonstrated how combining Raman spectroscopy and X-ray diffraction of the same sample material sealed inside a capillary with complementary first principles calculations yields accurate reference Raman spectra. This workflow enables the construction of a reliable Raman spectroscopic database for planetary exploration, which will be invaluable to shed light on the geological past as well as in identifying resources for the future colonization of planetary bodies throughout the solar system. In this dataset, the self-consistent DFT+U as well as Γ-point phonon calculations, that were compared to the experimentally determined frequencies of the Raman-active modes, are reported, whereas the experimental data was submitted to crystallographic data-bases (i.e., CCSD and ICSD).

This database contains information on Molecular Structure collected by the study of literature about Raman and Infrared Spectroscopy. A search option is available whereby information can be retrieved by entering a term or a description of the topic of interest. The database coveres literature since 1982 to the present time.

Future human missions to the surface of the Moon and Mars will involve scientific exploration requiring new support tools to enable rapid and high quality science decision-making. Here, we provide the PANGAEA Mineralogical Database developed by the European Space Agency: a catalog of petrographic and spectroscopic information on all currently known minerals identified on the Moon Mars, and associated with meteorites. It also includes minerals found in the ESA PANGAEA analog sites to broaden the database coverage. The Mineralogical Database is composed primarly of the Summary Catalog of of Planetary Analog Minerals and the Spectral Archive. The Summary Catalog provides essential descriptive information for each mineral, including name (based on IMA recommendation), chemical formula, mineral group, surface abundance on planetary bodies, geological significance in the context of planetary exploration, number of collected VNIR and Raman spectra, likelihood of detection using different spectral methods, and bibliographic references evidencing their detection in extraterrestrial or terrestrial analog environments. The Spectral Archive provides a standard library for planetary in-situ human and robotic exploration covering Visual-Near-Infrared reflective (VNIR) and Raman spectroscopy (Raman). To populate this library, we collected VNIR and Raman spectra for mineral entries in the Summary Catalog from open-access archives, and analyzed them to select the best. We also supplemented this collection with our own bespoke measurements. Additionally, we compiled the chemical compositions for all minerals based on their empirical formula, to allow identification using the measured abundances provided by LIBS and XRF analytical instruments. This version of the PANGAEA Mineralogical Database available here in Mendeley Data is updated to the 8th of June 2020. Any further update can be downloaded directly from the ESA webpage https://atd.eac.esa.int/sites/PANGAEAMinDB where the newest versions will be stored.

We present Molecular Vibration Explorer, a freely accessible online database and interactive tool for exploring vibrational spectra and tensorial light-vibration coupling strength of a large collection of thiolated molecules. The Gold' version of the database gathers the results from density functional theory calculations on 2'800 commercially available thiol compounds linked to a gold atom, with the main motivation to screen the best molecules for THz and mid-infrared to visible upconversion. Additionally, theThiol' version of the database contains results for 1'900 unbound thiolated compounds.They both provide access to a comprehensive set of computed spectroscopic parameters for all vibrational modes of all molecules in the database. Infrared absorption, Raman scattering and vibrational sum- and difference frequency generation cross sections can be simultaneously investigated by the user. Molecules can be screened for various parameters in custom frequency ranges, such as large Raman cross-section under specific molecular orientation, or large orientation-averaged sum-frequency generation (SFG) efficiency. The user can select polarization vectors for the electromagnetic fields, set the orientation of the molecule and customize parameters for plotting the corresponding IR, Raman and sum-frequency spectra.

This contains the graphene and hexagonal boron nitride datasets used to train the models described in the paper "Large Scale Raman Spectrum Calculations in defective 2D materials using Deep Learning". They are in the ASE format as described here: https://wiki.fysik.dtu.dk/ase/tutorials/tut06_database/database.html

This dataset is a spectroscopic library structured as a document database. It contains Raman and ATR-FTIR spectra of weathered and biofouled polymers.

The zipped folder contains the .fit and .peaks files, obtained by means of Fityk Software, of the deconvolutions of Augelite Raman and ATR-IR spectra from RRUFF Database. The deconvolutions are obtained defining in Fityk software the q-Gaussian and q-BWF functions. The content of the folder is supplementary material of the paper "Augelite Raman and ATR-IR Fingerprints obtained with q-Gaussian and q-BWF deconvolutions made by means of Fityk Software", https://doi.org/10.5281/zenodo.15007191

LSG size, Raman spectra, XPS spectra, IV characteristic, Gas response

X-ray diffraction (XRD) pattern of the iron substrate sample after electrodeposition.

X-ray photoelectron spectroscopy (XPS) of the synthetic mackinawite deposit for (a) Fe 2p spectrum and (b) S 2p spectrum, confirming the deposited sulfide is mackinawite and not stoichiometric pyrite.

Raman spectrum of iron pyrite nano-particles synthesized by the hot injection method at 200 deg C.

Further technological advancement of both lithium-ion and emerging battery technologies can be catalyzed by an improved understanding of the chemistry and working mechanisms of the solid electrolyte interphases (SEIs) that form at electrochemically active battery interfaces. However, collecting and interpreting spectroscopy results of SEIs is difficult for several reasons, including the chemically diverse composition of SEIs. To address this challenge, we herein present a vibrational spectroscopy and X-ray diffraction data library of ten suggested SEI chemical constituents relevant to both lithium-ion and emerging battery chemistries. The data library includes attenuated total reflectance Fourier transform infrared spectroscopy, Raman spectroscopy, and X-ray diffraction data, collected in inert atmospheres afforded by custom designed sample holders. The data library presented in this work (and online repository) alleviates challenges with locating related work that is either diffusely spread throughout the literature, or is non-existent, and provides energy storage researchers streamlined access to vital SEI-relevant data that can catalyse future battery research efforts.

Raman-ChEMBL-part2-db