Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
111
datasets available to search
ShareScore release 0.9.0
Dataset results
111 results for “geothermal”
Data for Hydrogeochemical constraints shape hot spring microbial community compositions: Evidence from acidic, moderate-temperature springs and alkaline, high-temperature springs, southwestern Yunnan geothermal areas, China
<p>Original data for <strong>Hydrogeochemical constraints shape hot spring microbial community compositions: Evidence from acidic, moderate-temperature springs and alkaline, high-temperature springs, southwestern Yunnan geothermal areas, China. </strong></p>
Data from: Simultaneous removal of fluoride and arsenic in geothermal water in Tibet using modified yak dung biochar as an adsorbent
Fluoride (F) and arsenic (As) are two typical and harmful elements that are found in high concentrations in geothermal water in Tibet. In the present work, yak dung, an abundant source of biomass energy in Tibet, was made into biochars (BC1, BC2 and BC3) by pyrolysis under different conditions, and the better biochar was modified by FeCl2 (Fe-BC3). The adsorption conditions were optimized to adsorb F and As in geothermal water. The results showed that BC3 can remove 90% F- and 20% As(V), which is the best effect of the three initial biochars. Fe-BC3 could remove 94% F- and 99.45% As(V) under the same conditions as BC3, which was an adsorbent dosage 10 g/L, pH 5-6 and temperature of 25 °C. It was also demonstrated that the removal rate did not decrease at 80 °C. A quasi-second-order kinetic model best described the adsorption behavior of ions on the surface of the biochar. The maximum adsorption capacity of F- and As(V) on Fe-BC3 was 3.928 mg/g and 2.926 mg/g, respectively. The features of Fe-BC3 were characterized by X-Ray Diffraction (XRD), Fourier Transform Infrared (FTIR), Brunauer-Emmett-Teller (BET), Energy Dispersive Spectrometer (EDS), and Scanning Electron Microscopy (SEM) to understand the adsorption process.
FIGURES 1–7 in A taxonomic revision of two local endemic Radix spp. (Gastropoda: Lymnaeidae) from Khodutka geothermal area, Kamchatka, Russian Far East
FIGURES 1–7. Radix auricularia (Linnaeus, 1758) from Russian Far East. Figs. 1-4. Shell and proximal part of the female genitalia. Scale bar 2 mm. Fig. 1. Holotype of Lymnaea (R.) hadutkae Kruglov & Starobogatov, 1989 syn. n. (shell photo: M.V. Vinarski; genitalia redrawn from the protologue, Fig. 2.7). Fig. 2. Holotype of L. (R.) thermokamtschatica Kruglov & Starobogatov, 1989 syn. n. (shell photo: M.V. Vinarski; genitalia redrawn from the protologue, Fig. 2.9). Fig. 3. Newly collected specimen from the Khodutka geothermal area, Kamchatka (photos: O.V. Aksenova). Fig. 4. Specimen from Malkinskie hot springs, Kamchatka (photos: O.V. Aksenova). Fig. 5. Bayesian phylogram of haplotypes based on mitochondrial COI gene dataset (Appendixes 1 & 2). The scale bar indicates the branch length. Asterisks: Posterior probabilities ≥0.95; other significant node support values are mentioned in the figure. Haplotypes exclusively from NCBI's Genbank are marked with circumflex accents (˄). The well-supported clade with two haplotypes from the Khodutka geothermal area is highlighted in blue. Fig. 6. General view of the Khodutka warm lake. Fig. 7. Map of observed localities on the Russian Far East. The red circles represent species records. Locality codes are given in Appendix 1. The digital elevation model and other layers of the map were added from Esri Data & Maps 10 dataset (Map: M.Yu. Gofarov).
Pathways to national-scale adoption of enhanced geothermal power through experience-driven cost reductions: Supplementary Data
<p>Dataset containing inputs, results, and code referenced in "Pathways to national-scale adoption of enhanced geothermal power through experience-driven cost reductions."</p> <ul> <li>"Central_Cases.zip", "NoEGS.zip", "Policy_Sensitivities.zip", "EGS_Sensitivities_Learning.zip", "EGS_Sensitivities_Other.zip", "OtherTech_Sensitivities.zip", and "IRA_Repeal_Cases.zip" contain the full set of capacity expansion model results referenced in the paper</li> <li>"GenX_EGS_HalfTimeSeries.zip" contains the source code for the modified version of the GenX electricity system capacity expansion model used in this work</li> <li>"GenX_Input_Files.zip" contains the full set of GenX inputs used in this work, including customized run files that apply inter-planning-period linkages, conditional policies, and endogenous learning-by-doing, which may be used alongside the model source code to replicate the results</li> <li>"PowerGenome_Inputs_and_Processing.zip" contains the settings files used to create GenX inputs in the PowerGenome tool, as well as post-processing scripts used to modify certain technologies and implement 2-hourly resolution</li> <li>"Costing_and_Supply_Curves.zip" contains the source code for the EGS cost model used in this work, as well as input temperature-at-depth data from Aljubran and Horne (2024). Temperature-at-depth data from Blackwell et al. (2011) is available for purchase from the SMU Geothermal Laboratory.</li> <li>"EGS_GenX_Inputs.zip" contains other EGS performance data and scripts used to build final GenX inputs</li> </ul> <p> </p>
Dataset from the paper "Viruses from geothermal springs have ancient origins reflecting long-term interactions with extremophilic red algal mats"
<p>Dataset of viral operational taxonomic units (vOTUs) and viral metagenome-assembled genomes (vMAGs) from the Lemonade Creek, Yellowstone National Park (YNP), USA, from the paper "Viruses from geothermal springs have ancient origins reflecting long-term interactions with extremophilic red algal mats".</p><p>L. Felipe Benites1*, Timothy G. Stephens1, Julia Van Etten1,2, Timeeka James1, William C. Christian4, Kerrie Barry5, Igor V. Grigoriev5,6, Timothy R. McDermott3 and Debashish Bhattacharya1</p><p>1Department of Biochemistry and Microbiology, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, United States of America</p><p>2Graduate Program in Ecology and Evolution, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901 United States of America</p><p>3Department of Land Resources and Environmental Sciences, Montana State University, Bozeman, Montana, United States of America</p><p>4Department of Chemistry and Biochemistry, Montana State University, Bozeman, Montana, United States of America</p><p>5U.S. Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, United States of America</p><p>6Department of Plant and Microbial Biology, University of California Berkeley, Berkeley, CA 94720, United States of America</p>
Supporting data for geothermal exploration in North Singapore by Bai et al.
<p>Supporting seismic data for Bai et al. (submitted).</p> <p>Information on seismic stations (SBW_station.dat)<br>Station code, longitude and latitude are included.</p> <p>Receiver function data (SBW_RF.zip)<br>The data is organized as xxx/yyyy.jjj.hh.mm.ss_P_r.sac, where xxxx is station code. yyyy, jjj, hh, mm and ss denote year, Julian day, hour, minute and second of the event origin time (e.g., AD01/2023.134.10.11.35_P_r.sac).</p> <p>Inter-station Rayleigh-wave phase velocity data (SBW_DISP.dat)<br>For each dispersion measurement, names of source and receiver, period (s), distance (km) and phase velocity (km/s) are present.</p> <p>Nov 21, 2024</p>
Plasticity and evolution shape the scaling of metabolism and excretion along a geothermal temperature gradient
<p>Physiological rates are heavily dependent on temperature and body size. Most current predictions of organisms' response to environmental warming are based on the assumption that key physiological rates like metabolism and excretion scale independently with body size and temperature and will not evolve. However, temperature is a significant driver for phenotypic variability in the allometric scaling and thermal sensitivity of physiological rates within ectotherm species, suggesting that evolution may play a role in shaping these parameters.</p> <p>We common-reared six populations of western mosquitofish that have recently established (~100 years ago) in geothermal springs along a broad thermal gradient (19-33°C) to determine whether these scaling parameters are affected by evolutionary and/or plastic responses to warming over ecological timescales. Each population was reared at four different temperatures (23, 26, 30 and 32°C). We measured routine metabolic and nitrogen excretion rates on mosquitofish across a wide body size range.</p> <p>We found evidence for plasticity, but not evolution, increasing the allometric scaling of metabolic rate with temperature. Plasticity in metabolism allometry reflected a decrease in thermal sensitivity at smaller body sizes.</p> <p>We found evidence for evolution of phenotypic plasticity on the allometry of excretion rate, reflecting evolutionary differences in how thermal sensitivity varies with body size across different populations.</p> <p>Evolutionary differences in excretion rate scaling did not influence the relationship between excretion and metabolism across rearing temperatures, suggesting that warming does not affect the balance between mosquitofish energy demands and nutrient recycling rates.</p>
Ambient noise tomography of Gran Canaria island (Canary Islands) for geothermal exploration
<p>This file contains the 3-D S-wave velocity model of Gran Canaria island.</p> <p><strong>Abstract</strong></p> <p>Ambient noise tomography (ANT) has proved to be efficient in resolving crustal structures for different purposes. Despite the numerous studies carried out in Gran Canaria in the past for purposes of geothermal exploration, ANT had never been used before on this island. We applied this technique to understand Gran Canaria island's shallow structure, determining the 3-D S-wave velocity model of the island and focusing on its implications for geothermal exploration. We used data from 30 seismic stations installed between October 2019 and February 2020. Our findings revealed five relevant velocity anomalies helpful in understanding the island's geology and its geothermal potential. In particular, we identified two high-velocity anomalies in the central part of the island aligned with the primary northwest-southeast structural trends of Gran Canaria. We interpret them as evidence of intrusive volcanic bodies emplaced during the early stages of the island's geological history. We also identified three low-velocity zones located in different parts of the island. We maintain that these anomalies could be associated with porous and highly fractured materials produced during the more recent volcanic episodes. In addition, we observed a spatial correlation of anomalies in the electric conductivity identified in previous studies and strong lateral gradients in our S-wave velocity model. We interpret them as evidence of hydrothermal circulation and thermal anomalies in correspondence of lateral contacts between different geological units and/or faults.</p> <p> </p>
Dataset and R-script for Article: Increased heat tolerance of geothermal plants at the cost of reduced performance under cooler conditions
Open the record for dataset details and reuse information.
Equipment Design for a Small Binary System Power Plant Using Geothermal Heating Fluid A Case Study
<p>This material has presented on 2nd International Conference on Advanced Research in Engineering and Technology in October 25, 2023.</p>
Geological Structure Interpretation for Delineation of Waste Storage Ponds Area in the Ungaran Geothermal Mining Working Area, Semarang
<p>This material has presented on 2nd International Conference on Advanced Research in Engineering and Technology in October 25, 2023.</p>
Geochemical Characteristic and Subsurface Temperature Calculation by Analyzing Cation & Anion at Guci Geothermal Prospect Area, Bumijawa, Tegal District, Central Java
<p>This material has presented on 2nd International Conference on Advanced Research in Engineering and Technology in October 25, 2023.</p>
Data Tables and figures for "Quantification of 3D thermal anomalies from surface observations of an orogenic geothermal system (Grimsel Pass, Swiss Alps)"
<p>Tables and figures containing the data used in the manuscript called</p> <p><strong>"Quantification of 3D thermal anomalies from surface observations of an orogenic geothermal system (Grimsel Pass, Swiss Alps)", </strong></p> <p>which was submitted to JGR:Solid Earth</p>
Derived seismic data products from paper: "Seismic Imaging of the Reykjanes Peninsular, Iceland: Crustal-scale context of geothermal areas and ongoing volcano-tectonic unrest"
<p>Receiver Functions (RF) and Dispersion Curves derived from seismic stations throughout the Reykjanes Peninsular SW Iceland. </p> <p>RF are in Smurfpy python3 PICKLE format - details on format and scripts to read in here: https://github.com/sannecottaar/smurfpy. Folder <strong> </strong>has the following file structure:</p> <p><strong>RF_Data_Zenodo</strong> --> contains station folders: <strong>Network.Station</strong> --> contains folders <strong>goodRF_crust2</strong> and <strong>goodRF_crust6 </strong>where 2 and 6 refer to Gaussian pulse widths used to produce RF via iterative deconvolution --> contains RF files in format <strong><em>NETWORK.STATION_BAZ_EPIDIST_EVTIME.PICKLE</em></strong> and subfolders of identified highly similar waveform subsets in the format <strong>BAZ_NNN_NNN </strong>used in data inversions<strong><br></strong></p> <p>Dispersion curves are in Fast Marching Surfacewave Tomography FMST input format (Rawlinson and Sambridge, 2005), details on format in FMST manual: https://iearth.edu.au/codes/FMST/instructions.pdf. Folder <strong>FMST_Dispersion_Inputs_Zenodo </strong>contains the following files:</p> <ul> <li>otimes0.25Hz.dat</li> <li>otimes0.2Hz.dat</li> <li>otimes0.35Hz.dat </li> <li>otimes0.3Hz.dat</li> <li>otimes0.45Hz.dat</li> <li>otimes0.4Hz.dat</li> <li>otimes0.5Hz.dat</li> <li>sources.dat </li> <li>receivers.dat</li> </ul> <p> </p> <p><em>References</em>:</p> <div>Rawlinson, Nick. "FMST: fast marching surface tomography package–Instructions." <em>Research School of Earth Sciences, Australian National University, Canberra</em> 29 (2005): 47.</div>
Is lithium from geothermal brines the sustainable solution for Li-ion batteries?
<p>The rising demand for Li, paramount for energy storage, necessitates expanded supply. As the supply is concentrated in a few countries, this poses supply chain risks for Li-ion battery makers. To diversify suppliers, alternative Li <a title="Learn more about ore deposits from ScienceDirect's AI-generated Topic Pages" href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/ore-deposit">ore deposits</a> such as geothermal brines are being explored. However, Li extraction from geothermal brines is challenging due to the unique chemistry and elevated temperatures. Since Li-extraction from geothermal brines is in its infancy, data availability and quality are still poor, hampering <a title="Learn more about life cycle assessments from ScienceDirect's AI-generated Topic Pages" href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/life-cycle-assessment">life cycle assessments</a>. Hence, this study provides a parametrized life cycle inventory model of Li carbonate production from geothermal brines. The model accounts for site-specific environmental conditions and technological features. Life cycle impacts at the Salton Sea in the US (1686 cases) and the Upper Rhine Graben in Germany (1982 cases) are quantified. The high case numbers are chosen to mitigate the high uncertainties in input parameters. Specifically, the brine chemistry, adsorption yield, drilling required and energy inputs are varied. <a title="Learn more about Climate change impacts from ScienceDirect's AI-generated Topic Pages" href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/climate-change-impact">Climate change impacts</a> of selected cases vary within 18–59 kg CO<sub>2</sub>eq/kg Li carbonate at the Salton Sea and within 5.3–46 kg CO<sub>2</sub>eq/kg Li carbonate at the Upper Rhine Graben, compared to 2.1–11 kg CO<sub>2</sub>eq/kg Li carbonate in existing ecoinvent data sets. The wide range of potential impacts underscore the necessity of early-stage assessments of the technologies. In case of high drilling demand and use of <a title="Learn more about fossil from ScienceDirect's AI-generated Topic Pages" href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/fossil">fossil</a> energy, climate change impacts of Li-ion batteries using Li carbonate from geothermal brines can increase by 30–41 % compared to literature values.</p>
The seismic signature and geothermal potential of the Schwechat Depression in the Vienna Basin, Austria, from ambient noise tomography
<p>This folder contains the cross-correlation functions, the Love and Rayleigh dispersion measurements, the Love and Rayleigh2D group velocity maps, the 3D shear-wave velocity model and a Paraview file for 3D visualization of the Vs model. For further information refer to "C. Esteve, Y. Lu, J. M. Gosselin, R. Kramer, Y. Aiman, G. Bokelmann, 2024, The seismic signature and geothermal potential of the Schwechat Depression in the Vienna Basin, Austria, from ambient noise tomography" published in Geothermics.</p>
Data from: Divergence of gastropod life history in contrasting thermal environments in a geothermal lake
Experiments using natural populations have provided mixed support for thermal adaptation models, probably because the conditions are often confounded with additional environmental factors like seasonality. The contrasting geothermal environments within Lake Mývatn, northern Iceland, provide a unique opportunity to evaluate thermal adaptation models using closely located natural populations. We conducted laboratory common garden and field reciprocal transplant experiments to investigate how thermal origin influences the life history of Radix balthica snails originating from stable cold (6 °C), stable warm (23 °C) thermal environments or from areas with seasonal temperature variation. Supporting thermal optimality models, warm origin snails survived poorly at 6 °C in the common garden experiment and better than cold origin and seasonal snails in the warm habitat in the reciprocal transplant experiment. Contrary to thermal adaptation models, growth rate in both experiments was highest in the warm populations irrespective of temperature, indicating cogradient variation. The optimal temperatures for growth and reproduction were similar irrespective of origin, but cold origin snails always had the lowest performance, and seasonal origin snails often performed at an intermediate level compared to snails originating in either stable environment. Our results indicate that central life-history traits can differ in their mode of evolution, with survival following the predictions of thermal optimality models, whereas ecological constraints have shaped the evolution of growth rates in local populations.
Electrical conductivity versus temperature in freezing conditions: a field experiment using a basket geothermal heat exchanger
<p>In-situ experiment. Geothermal setup: Five heat exchangers (HE) are arranged in a line and are buried between 1.1 and 3.5 meters. Just two baskets worked: one (HE.5) for a correct functioning of the heat pump and the other (HE1) to freeze the ground. only, this last exchanger (HE1) has been monitored in temperature and electrical resistivity tomography. The basket HE.5 is too far away to have an influence during this experiment, the heat pump was started at 0 hour and worked during 518 hours. The temperature of ground was recorded every minutes, thanks to 41 probes (4 wire Pt100), divided into 7 vertical profils. theses profiles are located at 0, 3, 6, 7, 8, 11, 20, 21 meters (x-distance), and the used heat exchangers are at 7 meters for the HE.1 and at 24 meters for the HE.5, respectively. Electrical Resitivity Tomography (ERT): Before and during the running of the geothermal system, gephysical monitoring was carried out. At the end, nine tomography images were recorded using a SAS-1000 Terrameter (ABEM) associated with 64 electrodes arranged in straigth line (2D acquisition, with a spacing between electrodes of one meter). Apparent resisitivities were inverted with IP4DI software, incorporating spatial and time regularization --Laboratory experiments-- we sampled the soil around the exchanger using an auger. the soil consists of a mixture of clay, silts and some gravels. Two samples are selected in order to conduct some electrical measurement at different temperature. They were dried and then saturated with water from the aquifer (0.117 S/m at 27°C) and put in a thermo-regulated bath (KISS K6 from Huber). At each temperature level, a SIP spectrum was performed with ZSIP, from 0.01 hz to 45 khz.Temperature levels are 20, 15, 10, 5, 2, 0, -2, -4, -6, -8, -10, -14, -18°C. FIles--- Field. Temperature measurements and inverted resitivity: This file contains the temperature measurements and inverted resistivities from geophysical monitoring, presented in the article. Field. Comparaison conductivity vs temperature: This file corresponds to the data extracted from the temperature and inverted resistivity sections in order to attest the resistivity vs temperature relationship. - Laboratory. Comparaison conductivity vs temperature: This file contains the data of the phase and quadrature conductivity as a function of temperature for both samples measured in the laboratory by SIP method.</p>
Data of Thermal Insulation and Shock Absorption Effect for Cross-fault Tunnel in High Geothermal Area
<p>Data of manuscript "Thermal Insulation and Shock Absorption Effect for Cross-fault Tunnel in High Geothermal Area"</p>
Pre-existing Structures and Stress Variations Jointly Control the Induced Seismicity in Enhanced Geothermal System of Gonghe Basin, China
<p>This is the dataset available for the article titled "Pre-existing Structures and Stress Variations Jointly Control the Induced Seismicity in Enhanced Geothermal System of Gonghe Basin, China", including phase information, earthquake catalog, waveforms of earthquakes and resolved focal mechanisms, 1D velocity model.</p>
ScienceDex guides
Understand access before you commit
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.