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599 results for “Volatile”
Data for: Climate warming and drought effects on volatile organic compound emissions from Solidago altissima
Volatile organic compounds (VOCs) were collected from Solidago altissima in drought and warming treatments in the KBS-LTER Rain Exclusion Experiment (REX). This sampling took place in July 2022 when the plants had been experiencing warming (via open-top chambers) for 20 months, and drought (via rainout shelters) for 3 weeks. The data presented here are the final data files used for analysis, and contain VOC abundance values per plant across the four climate treatments: ambient, warmed, drought, and warmed + drought. Code is available at: https://github.com/dobsonk2/REX_VOCs (https://doi.org/10.5281/zenodo.15169943)
Dataset: Volatile organic compound fluxes in a subarctic peatland and lake
<p>Dataset used in the article "Volatile organic compound fluxes in a subarctic peatland and lake" published in the journal Atmospheric Chemistry and Physics 20: 13399–13416 (2020) <a href="https://doi.org/10.5194/acp-20-13399-2020">https://doi.org/10.5194/acp-20-13399-2020</a> .</p> <p>The tab-delimited file contains direct surface-atmosphere Volatile Organic Compound fluxes, measured by Eddy Covariance with a Proton Transfer Reaction -Time of Flight- Mass Spectrometer (PTR-ToF-MS) at a subarctic fen and a subarctic lake during 2018. It also contains PAR Photosynthetic Active Radiation, air temperature, and vegetation surface temperature.</p>
Data for "Hydroclimate Volatility on a Warming Earth"
<p><strong>The data archived here represents data files and code used in the publication “Hydroclimate Volatility on a Warming Earth” by Swain et al. 2025. </strong>Here, we include the derived "hydroclimate whiplash" variable used in the summary analysis described in the published paper as calcuated for the historical period (ending in 2023) the ERA5 reanalysis (ERA5), and the NOAA-CIRES-DOE 20CRv3 reanalysis (NCD20C), as well as the future period (2014-2100 using SSP3-7.0 forcing) from the CESM2 Large Ensemble (CESM2-LE). Additionally, code used in the analysis discussed in the associated published manuscript is also available in this repository.</p>
Resistive switching in benzylammonium-based Ruddlesden–Popper layered hybrid perovskites for non-volatile memory and neuromorphic computing
<p><span>Structural, optoelectronic, and supplementary characterisation data for “</span><span>Resistive Switching in Benzylammonium-Based Ruddlesden-Popper Layered Hybrid Perovskites for Non-Volatile Memory and Neuromorphic Computing ”</span><span>, DOI:</span><span>10.1039/d3ma00618b</span><span>.</span></p>
Data of emission of floral volatiles and damage induced emissions of plants
<p>The file Emissiondata_plants_GCIMS contains a broad data set on the emissions of plant volatile organic compounds from different taxa. This allows cross species comparison of recorded emission pattern. Furthermore, distribution of identified (or unidentified) compounds can be traced for diferent species. </p> <p>All measurements were conducted performed with a mobile ppq-tec-GC-IMS (ION-GAS GmbH, Dortmund, Germany) based on hardware provided by STEP GmbH (Pockau-Lengefeld, Germany). GC pre-separation was performed under isothermal conditions (80°C) for 1500 s on a MXT-200 capillary column (30 m x 0.53 mm, 1.5 µm coating) with a carrier gas flow (filtered air from internal gas circuit) of 21 mL min<sup>-1</sup>. Ionization of pVOCs for mobility separation was performed using a tritium source of β-radiation (100 MBq). Mobility separation and subsequent detection were performed with a drift-tube IMS (drift length of 5.61 cm) at 70 °C and at a field strength of 300 V cm<sup>-1</sup>.</p> <p> </p> <p>The dataset contains 14 Variables and a total of 1866 observations (status: 10/06/2023, Version 1.0.0)</p> <p>4 variables describe the plant material. This includes the variables Species, Genus, Family and Order </p> <p>4 variables describe the sampled species. This includes plant part (flower or leaves), plant status (damaged or undamaged), the sample location and the Accession (only if the sample was provided by the Bonn University Botanical Gardens)</p> <p>6 variables describe the recorded emission patterns. Compound refers to the substance (unidentified compounds are abbreviated with UNK-n), retention time and relative ion mobility (parameters that allow cross species comparison and identification of substances), signal type (for some substances, ion clusters can be observed at higher concentrations. signal type refers to these ion clusters), and signal intensity (semi-quantitative measure for the abundance of a substance) and relative abundance (rel_abund; proportional contribution of a substance within a species, where the strogest signal is 1). </p> <p> </p> <p>The reference_compounds table is added to this. This contains information on substances that have already been identified (CAS, mass weight, retention time and relative ion mobility, dimerisation). These data were collected by direct injection of pure substances into the GC-IMS used. </p> <p> </p> <p> </p>
volatile organic compounds that were measred in various sites in Israel, available by the Israel Ministry of Environmental Protection
<p>The dataset comprises measurements of volatile organic compounds sampled at multiple sites across Israel from 2010 to 2024, encompassing urban, rural, and suburban locations.</p>
Strawberry volatile organic compounds metabolomic data and QTL study
<p>This dataset contains the supplementary materials of the publication "Multivariate QTL approach reveals a major regulator of terpenoid production and other volatiles in strawberry" of the same authors. In this study we extracted volatile organic compounds from several strawberry samples and analysed their identity and abundance. We used this volatile data to perform an extensive multivariate QTL study, the results of which can be found in this dataset.</p> <p>All analysis, results and figures can be reproduced using the folder included in the <strong>supplementary data 1</strong>. If you want to reproduce part or all of our analysis, only download sup data 1. </p> <p>If you only need one of our results or data table you can download them individually:</p> <ul> <li>Sup data 2: abundances of volatile organic compounds from a biparental and diverse panel (GWAS) population.</li> <li>Sup data 3 and 4: p-value tables for all metabolites as well as multivariate traits (see publication for more information).</li> <li>Sup table 1: Summary of metabolite abundances and heritabilities across both populations.</li> <li>Sup tables 2 and 3: significant QTL signals for each trait individually and summarised per QTL locus.</li> <li>Sup table 4: previously reported VOC QTLs in strawberry, with positions imputed in the Royal Royce genome.</li> <li>Sup table 5: metadata about all the identified compounds on this and previous studies.</li> <li>Sup table 6: SNP array positions imputed in the "Royal Royce" genome assembly.</li> <li>Sup table 7: Number of markers per chromosome in this analysis.</li> </ul> <h3>Update 2025</h3> <p>We updated the underlying code and datasets to reflect several revisions made to this work. Most notably, the QTL results have been reworked. They now do not include Blink or FarmCPU results (only mixed model results, obtained through statgenGWAS). Additionally, heritability estimations, QQ-plots and other figures have been added to the reproducible results code.</p>
Root symbionts alter the volatile profile of herbivore-infested tomato plants and aid the attraction of a predator
<p>Beneficial root microbes are among the most frequently used biocontrol agents in cropping systems, since they have been shown to promote plant growth and crop yield. Moreover, they are able to enhance protection against pathogens and insect herbivores by activating plant resistance mechanisms. Plant defense responses against herbivorous insects include the induction of metabolic pathways involved in the synthesis of defense-related metabolites. These metabolites include volatile organic compounds (VOCs), which attract natural enemies of the herbivores as a form of indirect resistance. Considering that beneficial root microbes may affect direct herbivore resistance, we hypothesized that also indirect resistance may be affected. We tested this hypothesis in a study system composed of tomato, the arbuscular mycorrhizal fungus <em>Rhizophagus irregularis</em>, the growth-promoting fungus <em>Trichoderma harzianum</em>, the generalist chewing herbivore <em>Spodoptera exigua </em>and the omnivorous predator<em> Macrolophus pygmaeus</em>. Using a Y-tube olfactometer we found that <em>M. pygmaeus</em> preferred plants with <em>S. exigua </em>herbivory, but microbe-inoculated plants more than non-inoculated ones. We used a targeted GC-MS approach to assess the impact of beneficial microbes on the emission of volatiles twenty-four hours after herbivory to explain the choice of <em>M. pygmaeus</em>. We observed that the volatile composition of the herbivore-infested plants differed from that of the non-infested plants, which was driven by the higher emission of green leaf volatile compounds, methyl salicylate, and several monoterpenes and sesquiterpenes. Inoculation with microbes had only a marginal effect on the emission of some terpenoids in our experiment. Gene expression analysis showed that the marker genes involved in the jasmonic and salicylic acid pathways were differentially expressed in the microbe-inoculated plants after herbivory. Our results pinpoint the role of root symbionts in determining plant-microbe-insect interactions up to the third trophic level, and elucidates their potential to be used in plant protection.</p>
Data Set for_Integrating torrefaction of pulp industry sludge with anaerobic digestion to produce biomethane and volatile fatty acids: An example of industrial symbiosis for circular bioeconomy
<p>Industrial symbiosis, which allows the sharing of resources between different industries, could help to improve the overall feasibility of bio-based chemicals production. In that regard, this study focused on integrating the torrefaction of pulp industry sludge with anaerobic digestion. More specifically, anaerobic digestion (AD) of pulp sludge-derived torrefaction condensate (TC) was studied to evaluate the biomethane and volatile fatty acid (VFA) potential. The torrefaction condensate produced at 275 and 300 °C was used in AD. The volatile solid content (VS) was 6.69 and 9.01% for the condensate produced at 275 and 300 °C, respectively. The organic fraction of TC mainly contained acetic acid, 2-furanmethanol, and syringol. The methane yield was in the range of 481–772 mL/g VS for the mesophilic and 401–746 mL/g VS for the thermophilic process, respectively. The VFA yield was in the range of 1.1 to 3.4 g/g VS for mesophilic and from 1.5 to 4.7 g/g VS in thermophilic conditions, when methanogenesis was inhibited. Finally, pulp sludge TC is a feasible feedstock to produce platform chemicals like VFA. However, at higher substrate loading, signs of process inhibition were observed because of the relatively increasing concentration of microbial inhibitors</p>
Dimethylsulfoniopropionate-derived compound concentrations, volatile organic compound concentrations, and microorganism abundances around two corals and a seaweed in the reefs of Moorea (French Polynesia)
<p>These data belong in the paper: </p> <p>M. Masdeu-Navarro, J-F. Mangot, L. Xue, M. Cabrera-Brufau, S.G. Gardner, D.J. Kieber, J.M. González, R. Simó (2022). Spatial and diel patterns of volatile organic compounds, DMSP-derived compopunds and planktonic microorganisms around a tropical scleractinian coral colony. <em>Frontiers in Marine Science</em>.</p> <p>Concentrations of DMSP, acrylate, DMSO, DMS, DMDS, COS, CS2, isoprene, CH3I, CH2ClI, CH2Br2 and CHBr3 in seawater samples around colonies of the corals Acropora pulchra and Pocillopora sp., and the brown seaweed Turbinaria ornata. Abundances of high-DNA and low-DNA bacteria, Prochlorococcus, Synechococcus, picoeukaryotes and nanoeukaryotes in the same samples, as determined by flow cytometry. All samples were collected in April 2018 in the coral reefs of Mo'orea, French Polynesia. </p> <p>The upper set of data contains concentrations at the distance of 0.5 cm from the coral polyps on the branch tips or verrucae, as well as from the seaweed thalli (samples IN), and 2 m away, downcurrent (samples OUT). The second set of data corresponds to A. pulchra only, and contains seawater samples IN, OUT and AL, the latter being sampled at 0.5 cm from the base of the dead branches colonized by a turf alga. IN, OUT and AL samples were collected over an entire diel cycle, every 6 hours for a period of 30 hours.</p>
Data set of "Capacitive and Inductive Characteristics of Volatile Perovskite Resistive Switching Devices with Analog Memory"
<p>The dataset of all data presented in the article published in the virtual special issue of the Journal of Physical Chemistry Letters:</p> <p>"Capacitive and Inductive Characteristics of Volatile Perovskite Resistive Switching Devices with Analog Memory"</p> <p>DOI: <a title="DOI URL" href="https://doi.org/10.1021/acs.jpclett.4c00945">https://doi.org/10.1021/acs.jpclett.4c00945</a></p> <p> </p> <p>The dataset contains the following raw data:</p> <p>## FILE DESCRIPTION<br>--------------<br>### Figure 2<br>- Fig2a.txt : Representative characteristic _I-V_ response of memristor (5 cycles)<br>- Fig2b.txt : Upper vertex-dependent multilevel/multistate analog resistive switching<br>- Fig2c.txt : Characteristic _I-V_ response of 20 distinct devices<br>- Fig2d.txt : Endurance measurements for 1000 cycles of the LRS (ON state) and HRS (OFF state)</p> <p>### Figure 3<br>- Fig3a.txt : Characteristic _I-V_ response with an upper vertex of 0.25 V<br>- Fig3b.txt : Characteristic _I-V_ response with an upper vertex of 0.75 V<br>- Fig3c.txt : Characteristic _I-V_ response with an upper vertex of 1.25 V</p> <p>### Figure 4<br>- Fig4a.txt : IS spectrum under dark conditions at 0 V<br>- Fig4b.txt : IS spectrum under dark conditions at 0.2 V<br>- Fig4c.txt : IS spectrum under dark conditions at 0.3 V<br>- Fig4d.txt : IS spectrum under dark conditions at 0.4 V<br>- Fig4e.txt : IS spectrum under dark conditions at 0.6 V<br>- Fig4f.txt : IS spectrum under dark conditions at 1.0 V</p> <p>### Figure 5<br>- Fig5a.txt : Voltage-dependent transient current response of the perovskite memristor<br>- Fig5b.txt : Magnified view of the transient current response of a single voltage pulse at representative applied voltages<br>- Fig5c.txt : Pulse width-dependent transient current response<br>- Fig5d.txt : Corresponding magnified view of the first and last transient responses<br>- Fig5e.txt : Synaptic potentiation and depression characteristic response of the memristor</p> <p>### Figure 6<br>- Fig6a.txt : Transient current response of the volatile perovskite memristor with a single long pulse vs. a train of short pulses at 0.4 V<br>- Fig6b.txt : Corresponding magnified view of the transient current response of a first voltage pulse at 0.4 V<br>- Fig6c.txt : Transient current response of the volatile perovskite memristor with a single long pulse vs. a train of short pulses at 0.8 V<br>- Fig6d.txt : Corresponding magnified view of the transient current response of a first voltage pulse at 0.8 V<br>- Fig6e.txt : Transient current response of the volatile perovskite memristor with a single long pulse vs. a train of short pulses at 1.2 V<br>- Fig6f.txt : Corresponding magnified view of the transient current response of a first voltage pulse at 1.2 V</p>
Supplementary Data: Fungal biostarter and bacterial occurrence of dry-aged beef: the sensory quality and volatile aroma compounds after 21 days of aging
<p>This dataset contains data generated during realisation of the project Tango-IV-C/0005/2019: Biostarters development for dry aged beef production, funded by National Centre for Research and Development (Poland). These data were used to prepare paper entitled "Fungal biostarter and bacterial occurrence of dry-aged beef: the sensory quality and volatile aroma compounds after 21 days of aging" by Wiesław Przybylski , Danuta Jaworska, Paweł Kresa, Grzegorz Michał Ostrowski, Magdalena Płecha, Dorota Korsak, Dorota Derewiaka, Lech Adamczak, Urszula Siekierko, Julia Pawłowska.</p>
Trade policy announcements can increase price volatility in global food commodity markets (Replication Data)
<p>Replication data for "Trade policy announcements can increase price volatility in global food commodity markets":</p> <ul> <li>Original dataset on trade policy announcements from 2005 to 2017 for wheat and maize (corn) (details in codebook)</li> <li>Daily price ranges based on the highest and lowest price recorded for wheat and corn futures (traded at the Chicago Board of Trade, CBOT)</li> <li>Stocks-to-use data for the United States, which is compiled by the United States Department for Agriculture (USDA) and available at monthly frequency from their World Supply and Demand Estimates report</li> </ul>
Emission of volatile organic compounds from residential biomass burning and their rapid chemical transformations.
<p>Volatile Organic Compounds (VOCs) were monitored during the Ioannina 2022/23 winter campaign, in north-east Greece. The campaign was carried out between December 6th, 2021, and January 10th, 2022. Nitrogen oxides, carbon monoxide, carbon dioxide, methane, PM10 and Black carbon were also monitored, as well as meteorological variables. Ioannina is nested within the Dinaric mountains and suffers from intense winter pollution events, due to the topology which traps the pollution over the city. The instruments deployed included a Proton Transfer Time-of-Flight Mass Spectrometry (PTR-ToF-MS 4000 – Ionicon GmbH, Austria), a greenhouse gas monitor (G2301 – Picarro Inc., USA), a suite of carbon monoxide, ozone, nitrogen oxide analyzers (APMA-360, APNA-360 and APOA-360 – Horiba Ltd., Japan), a PM10 monitor (F-701-20 – DURAG, Germany), an aethalometer (AE33 – Magee Scientific, USA) and a weather station. Radiation, historical temperature data from the University of Ioannina, and PMF analysis results are also submitted.</p>
Data from: Inter-laboratory comparison of plant volatile analyses in the light of intra-specific chemodiversity
<p>Data for: Inter-laboratory comparison of plant volatile analyses in the light of intra-specific chemodiversity</p>
"Outgassing Composition of the Murchison Meteorite: Implications for Volatile Depletion of Planetesimals and Interior-Atmosphere Connections for Terrestrial Exoplanets" Data Repository
<p>This repository contains the data files, analysis Jupyter notebooks and figures from Thompson et al. 2023 "Outgassing Composition of the Murchison Meteorite: Implications for Volatile Depletion of Planetesimals and Interior-Atmosphere Connections for Terrestrial Exoplanets"</p>
DMS measurements dataset for manuscript "Classification of Volatile Organic Compounds by Differential Mobility Spectrometry Based on Continuity of Alpha Curves"
<p>Differential mobility spectrometry dispersion plots collected for the manuscrit "Classification of Volatile Organic Compounds by Differential Mobility Spectrometry Based on Continuity of Alpha Curves". The measurement files are located in the folders that represent certain week and day of measurement. The folders containing measurements are named with the following pattern: [chemical abbreviation]_[dilution rate]. For example "2PEtOH_1o10k" means that the folder contains measurement of 2-phenylethanol diluted with propylene glycol in volumetric proportion 1/10 000. Another example is "nBuOH_1o100" - n-Butanol diluted with propylene glycol in volumetric proportion 1/100. Please find the abbreviations in the article referred.</p> <p>For the first five weeks only 1/100 dilutions were measured. The last two weeks (weeks 6 and 7) 1/10 000 dilutions were measured. However, Carvone 1/100 was measured again on week 6 due to suspicion of faulty measurements during the previous weeks. The faulty measurements were not confirmed, and thus there 25 more samples of Carvone with dilution rate 1/100.</p>
Raw Data for Publication "Desmodium Volatiles in "Push-Pull" Cropping Systems and Protection Against the Fall Armyworm, Spodoptera frugiperda"
<p>This repository contains all raw and processed data related to the publication titled "Desmodium Volatiles in "Push-Pull" Cropping Systems and Protection Against the Fall Armyworm, Spodoptera frugiperda" written by Daria M. Odermatt, Frank Chidawanyika, Daniel M. Mutyambai, Bernhard Schmid, Luiz A. Domeignoz-Horta, Collins O. Onjura, Amanuel Tamiru and Meredith C. Schuman.</p> <p>The data is subdivided in four sections:</p> <ol> <li>Volatile sampling of Desmodium intortum, D. incanum, and maize headspaces</li> <li>Oviposition bioassays comparing moth egg-laying preferences on maize vs. Desmodium (direct and indirect exposure)</li> <li>Choice assays evaluating moth behavior in response to maize alone vs. maize with Desmodium volatiles</li> <li>No-choice assays evaluation moth attraction toward maize alone, maize + D. intortum and maize + D. incanum</li> </ol> <p>More detailed information is available in the README files located within each folder.</p>
Stream sampling for total suspended solids (TSS), volatile suspended solids (VSS), and chemistry during storm events at the Coweeta LTER intensive and hillslope sites in Macon County, NC.
Stream storm samples were collected at 21 streams and rivers in Macon County, NC. Nine intensive sites were monitored in 2010-2011, nine hillslope sites were monitored in 2012-2013, and three river sites were monitored from 2010-2013. An ISCO water sampler was used to collect stream water samples during storm events. Water samples were analyzed at the Coweeta Analytical Lab.
Volatile organic compound analysis, a new tool in the quest for preterm birth prediction – an observational cohort study
<p>Vaginal swabs were taken in pregnancy in high risk asymptomatic women attending a preterm prevention clinic. Women in the study attended the clinical due to a history of preterm birth or midtrimester pregnancy loss, or due to a history of cervical surgery. Individualised management plans were made depending upon individual patient risk factors. During their attendance to the clinic vaginal swabs were taken for VOC analysis. Swabs were taken between 15 and 28 weeks gestation. Women consented to vaginal swabs at each of their visits to the clinic. The dataset contains GC-IMS VOC data from a G.A.S. GC-IMS and includes a Spreadsheet of demographics.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.