Dataset Search Results

This dataset supports the analysis presented in the study on curbside electric vehicle (EV) charging infrastructure planning in San Francisco and the published paper titled "Urban electric vehicle infrastructure: Strategic planning for curbside charging." It includes spatial data layers and tabular data used to evaluate location suitability under multiple criteria, such as demand, accessibility, and environmental benefits. This dataset can be used to replicate the multi-criteria decision-making framework, perform additional spatial analyses, or inform policy decisions related to EV infrastructure siting in urban environments.

This dataset describes an analysis of research documents about the debate between hydrogen fuel cells and lithium-ion batteries within the context of electric vehicles. To create this dataset, we first analyzed news articles on the topic of sustainable development. We searched for related science using keywords in Google Scholar. We then identified subtopics and selected one specific subtopic: electric vehicles. We started to identify positions and players about electric vehicles [1]. Within electric vehicles, we started searching in OpenAlex for a topic of reasonable size (about 300 documents) related to a scientific or technical debate. We narrowed to electric vehicles and batteries, then trained a cluster model [2] on OpenAlex’s keywords to develop some possible search queries, and chose one. Our final search query (May 7, 2024) returned 301 document in OpenAlex: Title & abstract includes: Electric Vehicle + Hydrogen + Battery filter is Lithium-ion Battery Management in Electric Vehicle We used a Python script and the Scopus API to find missing abstracts and DOIs [3]. To identify relevant documents, we used a combination of Abstractkr [4] and manual screening. As a starting point for Abstractkr [4], one person manually screened 200 documents by checking the abstracts for “hydrogen fuel cells” and “battery comparisons”. Then we used Abstractkr [4] to predict the relevance of the remaining documents based on the title, abstract, and keywords. The settings we used were single screening, ordered by most likely to be relevant, and 0 pilot size. We set a threshold of 0.6 for the predictions. After screening and predictions, 176 documents remained

This is the raw topographies (without linear background subtraction) related to the publication: https://www.nature.com/articles/s41586-024-07519-5

Dataset with numerical routines and laboratory testing data associated with the manuscript: Bondarenko, N., Podladchikov, Y., Williams‐Stroud, S., & Makhnenko, R. (2025). Stratigraphy‐induced localization of microseismicity during CO2 injection in Illinois Basin. Journal of Geophysical Research: Solid Earth, 130, e2024JB029526. https://doi.org/10.1029/2024JB029526

This dataset contains all the raw and processed data used to generate the figures presented in the main text and the supplementary information of the paper "Operation of a high frequency, phase slip qubit." It also includes code for data analysis and code for generating the figures.

This is a set of topographies to study the magnetic field response of RbV3Sb5 (related to Fig.4 of https://www.nature.com/articles/s41586-024-07519-5)

This dataset contains all raw and processed data used to generate the figures in the main text and supplementary material of the paper "High dynamic-range quantum sensing of magnons and their dynamics using a superconducting qubit." The data can be used to reproduce the plots and validate the analysis. Accompanying Jupyter notebooks provide step-by-step analysis pipelines for figure generation. The dataset also includes drawings for the mechanical samples used to perform the experiment. In addition, the dataset provides ANSYS HFSS electromagnetic simulation files used to design and analyze the resonator structures and estimate field distributions.

References - Jeong, Gangwon, Umberto Villa, and Mark A. Anastasio. "Revisiting the joint estimation of initial pressure and speed-of-sound distributions in photoacoustic computed tomography with consideration of canonical object constraints." Photoacoustics (2025): 100700. - Park, Seonyeong, et al. "Stochastic three-dimensional numerical phantoms to enable computational studies in quantitative optoacoustic computed tomography of breast cancer." Journal of biomedical optics 28.6 (2023): 066002-066002. Overview - This dataset includes 80 two-dimensional slices extracted from 3D numerical breast phantoms (NBPs) for photoacoustic computed tomography (PACT) studies. The anatomical structures of these NBPs were obtained using tools from the Virtual Imaging Clinical Trial for Regulatory Evaluation (VICTRE) project. The methods used to modify and extend the VICTRE NBPs for use in PACT studies are described in the publication cited above. - The NBPs in this dataset represent the following four ACR BI-RADS breast composition categories: > Type A - The breast is almost entirely fatty > Type B - There are scattered areas of fibroglandular density in the breast > Type C - The breast is heterogeneously dense > Type D - The breast is extremely dense - Each 2D slice is taken from a different 3D NBP, ensuring that no more than one slice comes from any single phantom. File Name Format - Each data file is stored as a .mat file. The filenames follow this format: {type}{subject_id}.mat where{type} indicates the breast type (A, B, C, or D), and {subject_id} is a unique identifier assigned to each sample. For example, in the filename D510022534.mat, "D" represents the breast type, and "510022534" is the sample ID. File Contents - Each file contains the following variables: > "type": Breast type > "p0": Initial pressure distribution [Pa] > "sos": Speed-of-sound map [mm/μs] > "att": Acoustic attenuation (power-law prefactor) map [dB/ MHzʸ mm] > "y": power-law exponent > "pressure_lossless": Simulated noiseless pressure data obtained by numerically solving the first-order acoustic wave equation using the k-space pseudospectral method, under the assumption of a lossless medium (corresponding to Studies I, II, and III). > "pressure_lossy": Simulated noiseless pressure data obtained by numerically solving the first-order acoustic wave equation using the k-space pseudospectral method, incorporating a power-law acoustic absorption model to account for medium losses (corresponding to Study IV). * The pressure data were simulated using a ring-array transducer that consists of 512 receiving elements uniformly distributed along a ring with a radius of 72 mm. * Note: These pressure data are noiseless simulations. In Studies II–IV of the referenced paper, additive Gaussian i.i.d. noise were added to the measurement data. Users may add similar noise to the provided data as needed for their own studies. - In Study I, all spatial maps (e.g., sos) have dimensions of 512 × 512 pixels, with a pixel size of 0.32 mm × 0.32 mm. - In Study II and Study III, all spatial maps (sos) have dimensions of 1024 × 1024 pixels, with a pixel size of 0.16 mm × 0.16 mm. - In Study IV, both the sos and att maps have dimensions of 1024 × 1024 pixels, with a pixel size of 0.16 mm × 0.16 mm.

Data and code supporting the paper titled "Leveraging electric vehicles as a resiliency solution for residential backup power during outages" by Shanshan Liu, Alex Vlachokostas, and Eleftheria Kontou. The data and the code enable spatiotemporal analytics and assessment of electric vehicle charging demand, remaining driving range, residential energy use, and vehicle-to-home (V2H) energy system resilience metrics.

Simulation data used to generate plots in the associated paper ("Strain rate controls alignment in growing bacterial monolayers").

Data accompanying the article "Physics of Unraveling and Micromechanics of Hagfish Threads". Abstract of the article: Hagfish slime is a unique biological material composed of mucus and protein threads that rapidly deploy into a cohesive network when deployed in seawater. The forces involved in thread deployment and interactions among mucus and threads are key to understanding how hagfish slime rapidly assembles into a cohesive, functional network. Despite extensive interest in its biophysical properties, the mechanical forces governing thread deployment and interaction remain poorly quantified. Here, we present the first direct in situ measurements of the micromechanical forces involved in hagfish slime formation, including mucus mechanical properties, skein peeling force, thread–mucus adhesion, and thread–thread cohesion. Using a custom glass-rod force sensing system, we show that thread deployment initiates when peeling forces exceed a threshold of approximately 6.8 nN. To understand the flow strength required for unraveling, we used a rheo-optic setup to impose controlled shear flow, enabling us to directly observe unraveling dynamics and determine the critical shear rate for unraveling of the skeins, which we then interpreted using an updated peeling-based force balance model. Our results reveal that thread–mucus adhesion dominates over thread–thread adhesion and that deployed threads contribute minimally to bulk shear rheology at constant flow rate. These findings clarify the physics underlying the rapid, flow-triggered assembly of hagfish slime and inform future designs of synthetic deployable fiber–gel systems.

This dataset includes experimental data supporting the findings in the manuscript "Magnetostriction and Temperature Dependent Gilbert Damping in Boron Doped Fe80Ga20 Thin Films". It contains raw data for X-Ray diffraction, high resolution transmission electron microscopy, magnetic hysteresis loop measurement, magnetostriction measurement, and temperature dependent magnetic damping measurement.

This dataset contains the raw transmission electron microscopy (TEM) and scanning electron microscopy (SEM) images used to calculate the synthesis yield of patchy nanoparticles (NPs), as described in Supplementary Table 1 of the paper “Patchy Nanoparticles by Atomic “Stencilling” (2025).” All the images were taken at the Materials Research Laboratory, University of Illinois at Urbana-Champaign by Qian Chen group. 1. We have 21 subfolders, each with a name corresponding to one of the 21 patchy NPs listed in Supplementary Table 1 of the paper “Patchy Nanoparticles by Atomic “Stencilling” (2025)." 2. In TEM images, the bright and dark regions indicate the polymer patches and NP cores, respectively. 3. In SEM images, the bright and dark regions indicate the NP cores and polymer patches, respectively. 4. Each subfolder contains a “readme (subfolder name).txt” file with more detailed information about each sample.

Data for the publication of Magnetic Fields in the Pillars of Creation (Sarkar et al.). Contains the fits files and python scripts.

This dataset includes analysis code used to analyze the data involved with swapping photons between superconducting qubits in separate modules though a superconducting coaxial cable bus. The dataset includes Python code to model and plot the data, CAD designs of the modules that hold the superconducting qubits, high frequency simulation software files to model the electric fields of the superconducting circuits

This dataset encompasses experimental results supporting the upcoming journal paper, "Laboratory-scale assessment of CO2 sealing potential for heterogeneous caprock", which investigates the sealing potential of heterogeneous caprock. The dataset includes the measurements and analyses conducted under controlled laboratory conditions, capturing sealing potential such as permeability and breakthrough pressure.

ALMA Band 4 and 7 observations of the dust continuum in the Class 0 protostellar system L1448 IRS3B. We include the selfcal script, imaging scripts, fits files, and the python scripts for the figures in the paper.

These data support Ruess et al (2025) "Drought impacts to water footprints and virtual water transfers of counties of the United States", Water Resources Research, 61, e2024WR037715, https://doi.org/10.1029/2024WR037715. The dataset contains estimates for Virtual Water Content (VWC) and Virtual Water Trade (VWT) for nine unique combinations of three crop categories (cereal grains, produce, and animal feed) and three water sources (surface water withdrawals, groundwater withdrawals, and groundwater depletion) for the years 2012 and 2017 within the Continental United States. The VWC is calculated by dividing irrigation withdrawal estimates (m3) by the production (tons) at the county resolution. The VWT is calculated by multiplying the VWC by the estimated county level food flows (tons) from Karakoc et al. (2022). All VWC estimates are provided at the county resolution according to county GEOID and are given in units of m3/ton. All VWT estimates are given in pairs of origin and destination GEOID’s and provided in units of m3. When using, please cite as: Ruess, P.J., Hanley, J., and Konar, M. (2025) "Drought impacts to water footprints and virtual water transfers of counties of the United States", Water Resources Research, 61, e2024WR037715, doi: 10.1029/2024WR037715.

The data and code provided in this dataset can be used to generate plots that show the results of linear prediction algorithm and the amplified modes, supporting the key argument of the manuscript. It is divided into five subfolders, each corresponding to one combination of external condition (magnetic field B, temperature), scan parameter (temperature, magnetic field B), pump laser polarization (linear s, linear p, and circular), and sample orientation ( B parallel to c axis, B perpendicular to c axis): 1) B parallel to c axis, linear pump polarization in s, linear THz emission polarization in s, field dependence (B_parallel_c_linear_spump_sprobe_field). 2) B parallel to c axis, linear pump polarization in s, linear THz emission polarization in s, temperature dependence (B_parallel_c_linear_spump_sprobe_temperature). 3) B perpendicular to c axis, linear pump polarization in s, linear THz emission polarization in s, field dependence (B_perp_c_linear_spump_sprobe_field). 4) B perpendicular to c axis, linear pump polarization in s, linear THz emission polarization in s, temperature dependence (B_perp_c_linear_spump_sprobe_temperature). 5) B parallel to c axis, circular pump polarization (left circularly polarized LCP and right circularly polarized RCP), linear THz emission polarization in s, field dependence (B_parallel_c_LCPRCP_pump_sprobe_field). Each folder contains the raw data (.mat), the oscillator parameters obtained through linear prediction algorithm (.mat), and the plot-generating code (.m). The code plots the raw data, the fit to the processed data, and the amplified modes. Codes are written in MATLAB R2024a; the working directory of each code should be the corresponding subfolder that contains it.

Rising global temperatures and urban heat island effects challenge environmental health and energy systems at the city level, particularly in summer. Increased heatwaves raise energy demand for cooling, stressing power facilities, increasing costs, and risking blackouts. Heat impacts vary across cities due to differences in urban morphology, geography, land use, and land cover, highlighting vulnerable areas needing targeted heat mitigation. Urban tree canopies, a nature-based solution, effectively mitigate heat. Trees provide shade and cooling through evaporation, improving thermal comfort, reducing air conditioning energy consumption, and enhancing climate resilience. This report focused on the ComEd service area in the Chicago Metropolitan Region and assessed the impacts of population growth, urbanization, climate change, and an ambitious plan to plant 1 million trees. The report evaluated planting 1 million trees to quantify regional cooling effects projected for the 2030s. Afforestation locations were selected to avoid interference with existing infrastructure. Key findings include (i) extreme hot hours (>95°F) will increase from 30 to 200 per year, adding 420 Cooling Degree Days (CCD) by the 2030s, (ii) greener areas can be up to 10°F cooler than less vegetated neighborhoods in summer, (iii) tree canopies can create localized cooling, reducing temperatures by 0.7°F and lowering annual CCD by 60 to 65, and (iv) afforestation can reduce the region’s temperature by 0.7°F, saving 400 to 1100 Megawatt hours of daily power usage during summer. <b>Note: The data is available upon request from <a href="mailto:dpiclimate@uilliois.edu">dpiclimate@uilliois.edu.

This data set includes information on mixing metric values and distances to determine the average length scale, rates and variability of mixing downstream of 43 river confluences for 150 mixing events. The file "pmx_all data.csv" contains confluence names, the number of events per confluence site, and Pmx values measured at various actual and dimensionless downstream distances. The file "pmx_binned data.csv" provides mean Pmx values within 0.5-unit dimensionless distance bins.

Incoherent scatter radar datasets collected during the September 2016 campaign at Arecibo have been deposited in this databank. The lag products of the ISR data are stored as lag profile matrices with 5 minutes of integration time. The data is organized in a Python dictionary format, with each file containing 12 lag profile matrices representing one hour of observation. A sample Python script is provided to illustrate its usage.

Per the authors' request, the data files for this dataset are now suppressed. Please visit this new dataset for the complete and updated data files: Huang, Yijing; Fahad , Mahmood (2025): Data for Observation of a Magneto-chiral Instability in Photoexcited Tellurium. University of Illinois Urbana-Champaign.<a href="https://doi.org/10.13012/B2IDB-1409842_V1">https://doi.org/10.13012/B2IDB-1409842_V1</a> ==================== The data and code provided in this dataset can be used to generate key plots in the manuscript. It is divided into four subfolders (B parallel/perpendicular to the tellurium c axis and field/ temperature dependence), each containing the raw data (saved in .mat format), the oscillator parameters obtained through linear prediction (saved in .mat format), and the plot-generating code (.m files). The code was written using MATLAB R2024a. To run the code, go to each folder, and run the .m file in that folder, which generates two plots.

This dataset provides estimates of total Irrigation Water Use (IWU) by crop, county, water source, and year for the Continental United States. Total irrigation from Surface Water Withdrawals (SWW), total Groundwater Withdrawals (GWW), and nonrenewable Groundwater Depletion (GWD) is provided for 20 crops and crop groups from 2008 to 2020 at the county spatial resolution. In total, there are nearly 2.5 million data points in this dataset (3,142 counties; 13 years; 3 water sources; and 20 crops). This dataset supports the paper by Ruess et al (2024) "Total irrigation by crop in the Continental United States from 2008 to 2020", Scientific Data, doi: 10.1038/s41597-024-03244-w When using, please cite as: Ruess, P.J., Konar, M., Wanders, N., and Bierkens, M.F.P. (2024) Total irrigation by crop in the Continental United States from 2008 to 2020, Scientific Data, doi: 10.1038/s41597-024-03244-w