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91 results for “raman spectroscopy”
Dataset: Label-free detection of methicillin resistance in Staphylococcus aureus using different Raman-spectroscopy approaches
<p>This is the dataset accompanying the submission of the manuscript: Label-free detection of methicillin resistance in Staphylococcus aureus using different Raman-spectroscopy approaches in the journal Microbiology Spectrum.</p> <p>The data description is the following:</p> <p>Strains<br> 16859MRSA= Strain AUSTR-07-16859 MRSA<br> 16859MSSA= Strain AUSTR-07-16859 MSSA<br> CC8MRSA= Strain 08V15773<br> CC8MSSA= Strain MRSA2010-174<br> AUSTR05MRSA= Strain AUSTR-05-15441 MRSA<br> AUSTR05MSSA= Strain AUSTR-05-15441 MSSA<br> CC361MRSA= Strain UAE-Abu Dhabi-020<br> CC361MSSA= Strain UAE-Dubai-80-MS 1368.9/09</p> <p>Datasets<br> UVRR: UV-Resonance Raman with 244 nm excitation on bulk samples, calibration standard Polystyrene, measurements were time series of 10 consecutive spectra, for each strain and batch 25 time series were collected from 3 different slides<br> 532nm: Single cell analysis with 532nm excitation, calibration standard 4AAP, one spectrum per bacterial cell was collected<br> 785nm: Bulk analysis of bacterial colonies using 785 nm excitation and a Raman fibre probe, calibration standard 4AAP, bulk analysis, individual spectra of colonies were collected</p> <p>Data structure is in the metadata files.<br> Individual spectra are in the folders sorted by the date they were measured.</p>
Detection of Submicron- and Nanoplastics Spiked in Environmental Fresh- and Saltwater with Raman Spectroscopy
<p>ABSTRACT</p> <p>Detection of small plastic particles in environmental water samples has been a topic of increasing interest in recent years. A multitude of techniques, such as variants of Raman spectroscopy, have been employed to facilitate their analysis in such complex sample matrices. However, these studies are often conducted for a limited number of plastic types in matrices with relatively little additional materials. Thus, much remains unknown about what parameters influence the detection limits of Raman spectroscopy for more environmentally relevant samples. To address this, this study utilizes Raman spectroscopy to detect six plastic particle types; 161 and 33 nm polystyrene, < 450 nm and 36 nm poly(ethylene terephthalate), 121 nm polypropylene, and 126 nm polyethylene; spiked into artificial saltwater, artificial freshwater, North Sea, Thames River, and Elbe River water. Overall, factors such as plastic particle properties, water matrix composition, and experimental setup were shown to influence the final limits of detection.</p>
Carbon x-ray Raman scattering mapping and spectroscopy of a fragment of Lepidodendron trunk from the Upper Carboniferous
<p>Carbon x-ray Raman scattering mapping and spectroscopy of a fragment of Lepidodendron trunk from the Upper Carboniferous (ca. 305 Mya) of Noyelles-lez-Lens, France</p>
Data for: Two-dimensional infrared-Raman spectroscopy as a probe of water's tetrahedrality
<p>Data for publication: T. Begusic and G. A. Blake, Two-dimensional infrared-Raman spectroscopy as a probe of water’s tetrahedrality (2022).</p> <p>Contains raw data, processed data, and processing and plotting scripts for the results presented in the manuscript. See README files enclosed in the dataset for details about the files and directories. Main results were produced with codes available at https://github.com/tbegusic/i-pi and https://github.com/tbegusic/encorr.</p>
Dataset: Correlative Light, Electron Microscopy and Raman Spectroscopy Workflow to Detect and Observe Microplastic Interactions with Whole Jellyfish
<p>ABSTRACT</p> <p>Many researchers have turned their attention to understanding microplastic interaction with marine fauna. Efforts are being made to monitor exposure pathways and concentrations, and to assess the impact such interactions may have. To answer these questions, it is important to select appropriate experimental parameters and analytical protocols. This study focuses on medusae of <em>Cassiopea andromeda</em> jellyfish: a unique benthic jellyfish known to favor (sub-)tropical coastal regions which are potentially exposed to plastic waste from land-based sources. Juvenile medusae were exposed to fluorescent poly(ethylene terephthalate) and polypropylene microplastics (< 300 µm), resin embedded, and sectioned before analysis with confocal laser scanning microscopy as well as transmission electron microscopy and Raman Spectroscopy. Results show the fluorescent microplastics were stable enough to be detected with the optimized analytical protocol presented, and that their observed interaction with medusae occurs in a manner which is likely driven by the microplastic properties (<em>e.g.</em> density, hydrophobicity).</p>
Biochemical Characterization of Mouse Retina of an Alzheimer's Disease Model by Raman Spectroscopy
<p>Raman raw data for the paper "Biochemical Characterization of Mouse Retina of an Alzheimer’s Disease Model by Raman Spectroscopy"</p> <ul> <li>two datasets of Raman images from cross-sectional and en face mouse retinas without processing</li> </ul>
Research data supporting "Online quantitative monitoring of live cell engineered cartilage growth using diffuse fiber-optic Raman spectroscopy"
<p>Research data supporting the publication:</p> <p>M. Bergholt, 2017, Online quantitative monitoring of live cell engineered cartilage growth using diffuse fiber-optic Raman spectroscopy, Biomaterials, Volume 140, September 2017, Pages 128–137, DOI: 10.1016/j.biomaterials.2017.06.015</p>
Data for: Raman microspectroscopy and laser-induced breakdown spectroscopy for the analysis of polyethylene microplastics in human soft tissues
<p>Data from Raman microspectrometry, LIBS, XRF, and particle sizer analysis supports the findings in the published article named Raman microspectroscopy and laser-induced breakdown spectroscopy to analyze polyethylene microplastics in human soft tissues. The aim of this research is to present the optimized protocol for the detection and analysis of microplastics in biological samples.</p> <p><strong> </strong></p> <p>The tonsil tissue is used for this experiment, and the workflow consists of a few steps: 1. digestion, 2. filtration, 3. analysis. </p> <p>The presented dataset includes the data for verifying the validity of this proposed protocol and the data from clinical experiments done on tonsils where the protocol is applied. We are focusing only on PE microplastics as they are one of the most frequent plastic types in the environment. </p> <p>Firstly, the data from the particle sizer show the size distribution before and after KOH treatment, which is necessary for digestion. We are testing if the particles are not affected by the KOH solution. The data are listed in an Excel sheet where the individual detected PE particle size [µm] and their frequencies [%] are annotated. The data are separated into 2 tables in one sheet - 1st represents data collected before KOH and the 2nd after KOH treatment. </p> <p>To test the limits of our selected systems for microplastic detection, we included the data from Raman and LIBS under the file ‘limitations.’ The different sizes of PE particles, from tens to 1 µm, were analyzed, and the spectra can be retrieved in the folders. The signal intensity can be observed to see the detection limits. For the Raman analysis, the particles were located on the filter. For LIBS, the particles were embedded in epoxy to enable the detection of PE particles in tens of microns. The Raman data are in .txt files and can be opened in any adequate software (Matlab, R, Python, etc.). LIBS data are in specific .libsdata format, which can be opened by LibsAnalyzer software by Lightigo. </p> <p><strong> </strong></p> <p>The clinical experiment was done on tonsil tissue. The tissue was disgusted and filtered. Then, the filters were analyzed. The dataset presents two sample groups: 1. control-native tissue and 2. test-spiked tissue with PE particles. The data from Raman analysis include both, with the aim to confirm the presence of PE particles in the test sample and to exclude the contamination in the control sample. The spectra are again in .txt files. In the case of control, spectra from unclassified particles are presented. For these reasons, the LIBS and XRF were run to exclude the possibility of the presence of polymeric material on the filter of the control sample. The analyzed chemical elements by LIBS for both samples are in the ASC file. Furthermore, individual PE particles were also analyzed on LIBS to obtain reference results for test samples with added PE microplastics. In the case of XRF, data from the empty filter, control, and test samples are included, each in a .txt file. Individual detected chemical elements and their intensities can be retrieved in the tables. </p> <p> </p>
Atrial Fibrillation Designation with Micro-Raman Spectroscopy and Scanning Acoustic Microscopy
<p>This repository was constructed tp provide the <strong>Raman Spectroscopy</strong> data and figure files related to the manuscript “Atrial Fibrillation Designation with Micro-Raman Spectroscopy and Scanning Acoustic Microscopy”. </p>
Quantification of salt stress in wheat leaves by Raman spectroscopy and machine learning
<p>Train and test datasets used in the manusicript "Quantification of salt stress in wheat leaves by Raman spectroscopy and machine learning". Trained models are included.</p>
Research data supporting "Raman spectroscopy imaging reveals interplay between atherosclerosis and medial calcification in human aorta"
<p>Research data supporting the publication:</p> <p>You, A. Y. F. <em>et al.</em>, 2017, "Raman spectroscopy imaging reveals interplay between atherosclerosis and medial calcification in human aorta", Science Advances, DOI: 10.1126/sciadv.1701156.</p>
Dataset of Raman spectroscopy responses for over-the-counter drugs in Paraguay, including acetylsalicylic acid, paracetamol, and ibuprofen.
<p>Spectra of three over-the-counter pharmaceuticals—acetylsalicylic acid, paracetamol, and ibuprofen—were collected at the Faculty of Exact and Natural Sciences of the National University of Asuncion, with the aim of creating a dataset that serves as a reference for Raman responses from different drug manufacturers. This dataset will also provide the scientific community with data that can be used for multivariate analysis and model training.</p> <p>In the data collection phase, spectra were obtained using a Raman spectroscopy system (iRaman 785s model from BWTEK) equipped with a 785 nm excitation laser. Samples were collected from diverse sales points such as pharmacies, shopping centers, and street vendors. Each spectrum was captured at 50% laser power with a measurement time of 1 second and an accumulation of 10 spectra over a range of 150 to 3200 cm-1. This method preserved the integrity of the raw data, which includes a common column for Raman shifts and additional columns for intensities and labels, detailing the activation modes in the Raman spectrum.</p> <p>The data is structured into specific xlsx files for each drug, such as "Paracetamol.xlsx", "acetylsalicylic-acid .xlsx", and "Ibuprofen .xlsx", each containing 50 spectra categorized by the type of pharmaceutical but not by brand. Brand-specific categorization is detailed in separate files like "Paracetamol-trademark .xlsx", where samples are classified using codes such as "Par-A" for different brands. This organization aids the scientific community in using clustering methods to analyze the spectral data and differentiate pharmaceutical brands based on their excipients or binders, with consistent codes across different drugs suggesting common manufacturers for various medications.</p> <p> </p>
Analysis of heritage stones and model wall paintings by pulsed laser excitation of Raman, laser-induced fluorescence and laser-induced breakdown spectroscopy signals with a hybrid system
<p>Analysis of heritage stone samples, alabaster, gypsum, limestone and marble, and model wall paintings was carried out with a laboratory, hybrid system based on the pulsed laser excitation of Raman, laser-induced fluorescence and laser-induced breakdown spectroscopy signals. The system is based on a nanosecond Q-switched Nd:YAG laser operating at its second (532 nm), third (355 nm) and fourth (266 nm) harmonics and a spectrograph coupled to a time-gated intensified charge coupled device for spectral analysis allowing detection with temporal resolution. For the stone samples, Raman spectra display the characteristic vibration modes of SO<sub>4</sub><sup>2-</sup> of calcium sulfate, in alabaster and gypsum, and of free CO<sub>3</sub><sup>2- </sup>of calcium carbonate, in limestone and marble. Simultaneously acquired laser-induced fluorescence spectra reveal characteristic bands that help to distinguish between heritage stone types. The elemental composition of stone samples is obtained by laser-induced breakdown spectroscopy upon excitation at 355 nm. Spectra of all stone samples reveal their elemental composition that includes Ca, Na, Mn and Sr and the presence of molecular species, such as CN, C<sub>2</sub> and CaO. Additional emission lines, ascribed to Mg, Si, Al and K, appear with different intensities according to the nature of the stone material. Model wall paintings, based on a red pigment, prepared as fresco or mixed with two different binders, were also studied. The complementary information provided by the three spectroscopic modes allows the identification of the pigment as red vermillion and of the different preparations based on the pigment alone or in mixtures with linseed oil and egg yolk binders.</p>
Dataset of "Identifying Active Oxygen and Copper Species in Cu/CeO2 Catalysts using Raman and UV-Vis Modulation Excitation Spectroscopy"
<p>This zip file contains the dataset of the publication "Identifying Active Oxygen and Copper Species in Cu/CeO2 Catalysts using Raman and UV-Vis Modulation Excitation Spectroscopy" (<span><a href="https://doi.org/10.1021/acs.jpcc.4c05826">https://doi.org/10.1021/acs.jpcc.4c05826</a></span>). The authors are Henrik Hoyer and Christan Hess*. The zip file includes the data for figures 2 and 3 in the manuscript and the data for figures S1-S12 in the SI. For more detailed information on the dataset, please refer to the description file. </p> <p>*email: christian.hess@tu-darmstadt.de</p>
2D-Raman-THz Spectroscopy with Single-Shot THz Detection
<p>We present a 2D-Raman-THz setup with multichannel (single-shot) THz detection, utilizing two crossed echelons, in order to reduce the acquisition time of typical 2D-Raman-THz experiments from days to a few hours. This speed-up is obtained in combination with a high repetition rate (100 kHz) Yb-based femtosecond laser system and a correspondingly fast array detector. The wavelength of the Yb-laser (1030 nm) is advantageous, since it assures almost perfect phase matching in GaP for THz generation and detection, and since dispersion in the transmissive echelons is minimal. 2D-Raman-THz test measurements on liquid bromoform (CHBr3) are reported. An enhancement of ∼5.8 times in signal-to-noise ratio is obtained for single-shot detection when comparing to conventional step scanning measurements in the THz time-domain, corresponding to speed up of acquisition time of 34.</p>
Evaluating the use of Fourier transform Raman spectroscopy for pollen chemical characterization
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Supporting data files for "Binding of Biologically Relevant Divalent Cations to Aqueous Carboxylates: Molecular Simulations Guided by Raman Spectroscopy"
<p>Parameter files and typical simulation input files that allow replication of the computational work presented in the paper "Binding of Biologically Relevant Divalent Cations to Aqueous Carboxylates: Molecular Simulations Guided by Raman Spectroscopy", authored by Denilson Mendes de Oliveira, Samual R. Zukowski, Vladimir Palivec, Jérôme Hénin, Hector Martinez Seara, Dor Ben Amotz, Pavel Jungwirth and Elise Duboué-Dijon</p>
Confocal Raman spectroscopy data from native and polyethylene glycol-containing wood
<p>Confocal Raman mapping data from native pine wood and pine wood with polyethylene glycol (PEG) of three different molecular weights in deuterated water.</p> <p>The spectroscopic data consists of 4 text files, each of which contains in total 1600 2D arrays of Raman intensity corresponding to different wavenumber values. Each of these 2D arrays consists of 175 rows with 175 comma-separated values on each row. The 2D arrays corresponding to different wavenumbers are separated by a line starting with '#' and specifying the wavenumber of the subsequent 2D array (unit inverse cm). The wavenumber axis is also given in a separate file. The image size is 45 µm x 45 µm (175 x 175 pixels) and the wavenumber axis consists of 1600 points.</p> <p>For further details on the samples and data collection, see the following reference:<br> Paavo A. Penttilä, Michael Altgen, Muhammad Awais, Monika Österberg, Lauri Rautkari, & Ralf Schweins. Bundling of cellulose microfibrils in native and polyethylene glycol-containing wood cell walls revealed by small-angle neutron scattering. <em>Scientific Reports</em> <strong>10, </strong>20844 (2020). https://doi.org/10.1038/s41598-020-77755-y</p>
Data from: Pushing Raman spectroscopy over the edge: purported signatures of organic molecules in fossil animals are instrumental artefacts
<p>Widespread preservation of fossilized biomolecules in many fossil animals has recently been reported in six studies, based on Raman microspectroscopy. Here, we show that the putative Raman signatures of organic compounds in these fossils are actually instrumental artefacts resulting from intense background luminescence. Raman spectroscopy is based on the detection of photons scattered inelastically by matter upon its interaction with a laser beam. For many natural materials, this interaction also generates a luminescence signal that is often orders of magnitude more intense than the light produced by Raman scattering. Such luminescence, coupled with the transmission properties of the spectrometer, induced quasi-periodic ripples in the measured spectra that have been incorrectly interpreted as Raman signatures of organic molecules. Although several analytical strategies have been developed to overcome this common issue, Raman microspectroscopy as used in the studies questioned here cannot be used to identify fossil biomolecules.</p>
Research data supporting "Raman spectroscopy reveals new insights into the zonal organization of native and tissue-engineered articular cartilage"
<p>This file contains the raw research data supporting the publication above.</p>
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