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Illinois Data Bank Dataset Search Results
Dataset Search Results
published: 2023-07-31
Zhang, Yue; Hossain, Mohammad Abir; Hwang, Kelly; Ferrari, Paolo; Maduzia, Joe; Pena, Tera; Wu, Stephen; Ertekin, Elif; van der Zande, Arend (2023): Dataset for Design and Pattern Strain in 2D materials. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-2595358_V1
published: 2023-04-06
Yao, Lehan; Lyu, Zhiheng; Li, Jiahui; Chen, Qian (2023): Data for Unsupervised Sinogram Inpainting for Nanoparticle Electron Tomography (UsiNet) for missing wedge correction. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-7963044_V1
Example data for https://github.com/chenlabUIUC/UsiNet The data contains computer simulated and experimental tilting series (or sinograms) of gold nanoparticles. Two training data examples are provided: 1. simulated_data.zip 2. experimental_data.zip In each zip folder, we include an image_data.zip and a training_data.zip. The former is for viewing and only the latter is needed for model training. For more details, please refer to our GitHub repository.
keywords:
electron tomography; deep learning
published: 2016-12-12
Zhang, Qian; Chunyan, Li; Braud, Dewitt (2016): LIDAR data for the Wax Lake delta. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-3764213_V1
This dataset is about a topographic LIDAR survey (saved in “waxlake-lidar.img”) that was conducted over the Wax Lake delta, between longitudes −91.5848 to −91.292 degrees, and latitudes 29.3647 to 29.6466 degrees. Different from other elevation data, the positive value in the LIDAR data indicates land elevation, while the zero value implies riverbed without identifying specific water depth.
keywords:
LIDAR; Wax Lake delta
published: 2023-01-05
Tonks, Adam (2023): Data for the paper "Forecasting West Nile Virus with Graph Neural Networks: Harnessing Spatial Dependence in Irregularly Sampled Geospatial Data". University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-3628170_V1
This is the data used in the paper "Forecasting West Nile Virus with Graph Neural Networks: Harnessing Spatial Dependence in Irregularly Sampled Geospatial Data". A preprint may be found at https://doi.org/10.48550/arXiv.2212.11367 Code from the Github repository https://github.com/adtonks/mosquito_GNN can be used with the data here to reproduce the paper's results. v1.0.0 of the code is also archived at https://doi.org/10.5281/zenodo.7897830
keywords:
west nile virus; machine learning; gnn; mosquito; trap; graph neural network; illinois; geospatial
published: 2023-03-24
Zhang, Jun (2023): Potential Impacts on Ozone and Climate from a Proposed Fleet of Supersonic Aircraft. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-0038951_V1
This datasets provide basis of our analysis in the paper - Potential Impacts on Ozone and Climate from a Proposed Fleet of Supersonic Aircraft. All datasets here can be categorized into emission data and model output data (WACCM). All the model simulations (background and perturbation) were run to steady-state and only the datasets used in analysis are archived here.
keywords:
NetCDF; Supersonic aircraft; Stratospheric ozone; Climate
published: 2021-11-23
Riemer, Nicole; Yao, Yu; Dawson, Matthew; Dabdub, Donald (2021): Data for: Evaluating the impacts of cloud processing on resuspended aerosol particles after cloud evaporation using a particle-resolved model. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-8367769_V2
This dataset contains simulation results from PartMC-MOSAIC-CAPRAM used in the article ”Eval- uating the impacts of cloud processing on resuspended aerosol particles after cloud evaporation using a particle-resolved model”. In this V2, there are eight folders: one for urban plume simulation to provide the initial particle population for cloud processing, the other four folders are for the four cloud cycles simulated and the last two are for the coagulation cases. Within the urban plume simulation, there are 25 NetCDF files hourly output from PartMC-MOSAIC simulations containing the gas and particle information. Within the four cloud cycle folders, there are 25 subdirectories that contain the cloud processing results for aerosol population from urban plume environment. For each subdirectory, there are 31 NetCDF files out- put every minute from PartMC-MOSAIC-CAPRAM simulations containing aerosol and gas information after aqueous chemistry. Another two folders are for the cases considering Brownian coagulation and sedimentation coalescence. Each contained 93 NetCDF files, produced from repeating the 30-minutes simulations for three times to consider the coagulation randomness. The low polluted case folder includes the simulated cloud processing results for 25 urban plume cases with less aerosol number concentration. This dataset was used to investigate the effects of cloud processing on aerosol mixing state and CCN properties.
keywords:
cloud process; coagulation; aqueous chemistry; aerosol mixing state; CCN
published: 2022-10-22
Madhavan, Vidya; Aishwarya, Anuva (2022): Data for Evidence for a robust sign-changing s-wave order parameter in monolayer films of superconducting Fe(Se,Te)/Bi2Te3. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-6972172_V1
This dataset consists of all the files that are part of the manuscript titled "Evidence for a robust sign-changing s-wave order parameter in monolayer films of superconducting Fe(Se,Te)/Bi2Te3". For detailed information on the individual files refer to the readme file.
keywords:
thin film; mbe; topology; superconductivity; topological insulator; stm; spectroscopy; qpi
published: 2021-05-14
Abbamonte, Peter (2021): Data for Anomalous density fluctuations in a strange metal. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-2888536_V1
This is the complete dataset for the "Anomalous density fluctuations in a strange metal" Proceedings of the National Academy of Sciences publication (https://doi.org/10.1073/pnas.1721495115). This is an integration of the Zenodo dataset which includes raw M-EELS data. <b>METHODOLOGICAL INFORMATION</b> 1. Description of methods used for collection/generation of data: Data have been collected with a M-EELS instrument and according to the data acquisition protocol described in the original PNAS publication and in SciPost Phys. 3, 026 (2017) (doi: 10.21468/SciPostPhys.3.4.026) 2. Methods for processing the data: Raw data were collected with a channeltron-based M-EELS apparatus described in the reference PNAS publication and analyzed according to the procedure outlined both in the PNAS paper and in SciPost Phys. 3, 026 (2017) (doi: 10.21468/SciPostPhys.3.4.026). The raw M-EELS spectra at each momentum have been subject to minor data processing involving: (a) averaging of different acquisitions at the same conditions, (b) energy binning, (c) division of an effective Coulomb matrix element (which yields a structure factor S(q,\omega)), (d) antisymmetrization (which yields the imaginary chi) All these procedures are described in the PNAS paper. 3. Instrument- or software-specific information needed to interpret the data: These data are simple .txt or .dat files which can be read with any standard data analysis software, notably Python notebooks, MatLab, Origin, IgorPro, and others. We do not include scripts in order to provide maximum flexibility. 4. Relationship between files, if important: We divided in different folders raw data, structure factors and imaginary chi. <b>DATA-SPECIFIC INFORMATION</b> There are 8 folders within the Data_public_deposition_v1.zip. Each folder contain data needed to create the corresponding figure in the publication. <b>1. Fig1:</b> This folder contains 21 DAT files needed to plot the theory data in panels C and D, following this naming conventions: [chiA]or[chiB]or[Pi]_q_number.dat With chiA is the imaginary RPA charge susceptibility with a Coulomb interaction of electronically weakly coupled layers chiB is the imaginary RPA charge susceptibility with the usual 4\pi e^2/q^2 Coulomb interaction. Pi is the imaginary Lindhard polarizability. q is momentum in reciprocal lattice units Number is the numerical momentum value in reciprocal lattice units <b>2. Fig2:</b> Files needed to plot Fig. 2 of the PNAS paper. Contains 3 folders as listed below. The files in this folder are named following this convention: Bi2212_295K_(1,-1)_50eV_161107_q_number_2.16_avg.dat, 295K is the sample temperature (1,-1) is the momentum direction in reciprocal lattice units 50 eV is the incident e beam energy 161107 is the start date of the experiment in yymmdd format Q is the momentum Number is the momentum in reciprocal lattice units 2.16 is the energy range covered by the data in eV Avg identifies averaged data ImChi: is the imaginary susceptibility obtained by antisymmetryzing the structure factor Raw_avg_data: raw averaged M-EELS spectra Sqw: Structure factors derived from the M-EELS spectra <b>3. Fig3:</b> Files needed to plot Fig. 3 of the PNAS paper. OP/ OD prefix identifies optimally doped or overdosed sample data, respectively. ImChi: is the imaginary susceptibility obtained by antisymmetryzing the structure factor Raw_avg_data: raw averaged M-EELS spectra Sqw: Structure factors derived from the M-EELS spectra <b>4. Fig4:</b> Files needed to plot Fig. 4 of the PNAS paper. The _fit_parameters.dat file contains the fit parameters extracted according to the fit procedure described in the manuscript and at all momenta. ImChi: is the imaginary susceptibility obtained by antisymmetryzing the structure factor Raw_avg_data: raw averaged M-EELS spectra Sqw: Structure factors derived from the M-EELS spectra <b>5. FigS1:</b> Files needed to plot Fig. S1 of the PNAS paper. There are 5 files in this folder. DAT files are M-EELS data following the prior naming convention, while the two .txt files are digitized data from N. Nücker, U. Eckern, J. Fink, and P. Müller, Long-Wavelength Collective Excitations of Charge Carriers in High-Tc Superconductors, Phys. Rev. B 44, 7155(R) (1991), and K. H. G. Schulte, The interplay of Spectroscopy and Correlated Materials, Ph.D. thesis, University of Groningen (2002). <b>6. FigS2:</b> Files needed to plot Fig. S2 of the PNAS paper. ImChi: is the imaginary susceptibility obtained by antisymmetryzing the structure factor Raw_avg_data: raw averaged M-EELS spectra Sqw: Structure factors derived from the M-EELS spectra <b>7. FigS3:</b> Files needed to plot Fig. S3 of the PNAS paper. There are 2 files in this folder: 20K_phi_0_q_0.dat: is a M-EELS raw intensity at zero momentum transfer on Bi2212 at 20 K 295K_phi_0_q_0.dat: is a M-EELS raw intensity at zero momentum transfer on Bi2212 at 295 K <b>8. FigS4:</b> Files needed to plot Fig. S4 of the PNAS paper. The _fit_parameters.dat file contains the fit parameters extracted according to the fit procedure described in the manuscript and at all momenta. ImChi: is the imaginary susceptibility obtained by antisymmetryzing the structure factor Raw_avg_data: raw averaged M-EELS spectra Sqw: Structure factors derived from the M-EELS spectra
keywords:
Momentum resolved electron energy loss spectroscopy (M-EELS); cuprates; plasmons; strange metal
published: 2022-12-31
Maffeo, Christopher; Wilson, Jim; Quednau, Lauren; Aksimentiev, Aleksei (2022): Simulation Trajectories for "DNA double helix, a tiny electromotor". University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-6770800_V1
Trajectory data for Nature Nanotechnology manuscript "DNA double helix, a tiny electromotor" that demonstrates how an electric field applied along the helical axis of a DNA or RNA molecule will generate an electroosmotic flow that causes the duplex to spin about that axis, much like a turbine.
keywords:
All-atom MD simulation; DNA; nanotechnology; motors and rotors
published: 2023-03-13
Yang, Joyce; Zhao , Lei; Oleson, Keith (2023): Historical and future CESM climate simulations from: Large humidity effects on urban heat exposure and cooling challenges under climate change. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9627482_V1
This dataset contains the historical and future (SSP3 and RCP7.0) CESM climate simulations used in the article "Large humidity effects on urban heat exposure and cooling challenges under climate change" (upcoming). Further details about these simulations can be found in the article. This dataset documents the monthly mean projections of air temperature, wet-bulb temperature, precipitation, relative humidity, and numerous other climatic variables for 2000-2009 (for the historical run) and for 2015-2100 (for the future projection under SSP3-RCP7). This dataset may be useful for urban planners, climate scientists, and decision-makers interested in changes in urban and rural climate under climate change.
keywords:
urban climate; climate change; heat stress; urban heat
published: 2021-01-04
Zhao, Lei; Oleson, Keith; Bou-Zeid, Elie; Krayenhoff, Eric Scott; Bray, Andrew; Zhu, Qing; Zheng, Zhonghua; Chen, Chen; Oppenheimer, Michael (2021): Multi-model urban climate projections data from: Global multi-model projections of local urban climates. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4585244_V1
This dataset contains the emulated global multi-model urban climate projections under RCP 8.5 and RCP 4.5 used in the article "Global multi-model projections of local urban climates" (https://www.nature.com/articles/s41558-020-00958-8). Details about this dataset and the local urban climate emulator are described in the article. This dataset documents the monthly mean projections of urban temperatures and urban relative humidity of 26 CMIP5 Earth system models (ESMs) from 2006 to 2100 across the globe. This dataset may be useful for multiple communities regarding urban climate change, impacts, vulnerability, risks, and adaptation applications.
keywords:
Urban climate; multi-model climate projections; CMIP; urban warming; heat stress
published: 2020-05-12
Eick, Brian (2020): Acceleration and strain data for free vibration of pre-tensioned, partially-submerged beams. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-7897650_V1
The data provided herein is accelerometer and strain data taken from free vibration response of pre-tensioned, partially submerged steel beam specimens (modulus of elasticity assumed = 29,000 ksi). The specimens were subjected to various levels of pre-tension, and various levels of submersion in water. The purpose of the testing was to quantify the effects of partial submersion on the vibrating frequencies of pretensioned beams. Three specimens were tested, each with different cross section (but identical cross-sectional area). The different cross sections allow investigation of the effects of specimen width as the specimen vibrates through water. The testing procedure was as follows: 1) Apply a specified level of tension in the beam. Measure tension via 3 strain gages. 2) Submerge the specimens to a specified depth of water 3) Excite the beams with either a hammer impact or a pull-and-release method (physically pull the middle of the bar and quickly release) 4) Measure the free vibration of the beam with 2 accelerometers. Schematic drawings of the test setup and the test specimens are provided, as is a picture of the test setup.
keywords:
free vibration; beam; partially-submerged; prestressed;
published: 2022-08-06
Madhavan, Vidya; Aishwarya, Anuva (2022): Data for Spin-selective tunneling from nanowires of the candidate topological Kondo insulator SmB6. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9971603_V1
This dataset consists of all the files and codes that are part of the manuscript (main text and supplement) titled "Spin-selective tunneling from nanowires of the candidate topological Kondo insulator SmB6". For detailed information on the individual files refer to the specific readme files.
keywords:
Topology; Kondo Inuslator; Spin; Scanning tunneling microscopy; antiferromagnetism
published: 2018-08-29
Finlon, Joseph (2018): Matched Radar and Microphysical Properties During MC3E. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-6396968_V1
This dataset contains best estimates of the particle size distribution and measurements of the radar reflectivity factor and total water content for instances where ground-based radar and airborne microphysical observations were considered collocated with each other.
keywords:
MC3E; MCS; GPM; microphysics; radar; aircraft; ice
published: 2020-06-03
Zhang, Jun; Wuebbles, Donald; Kinnison, Douglas; Baughcum, Steven (2020): Potential Impacts of Supersonic Aircraft on Stratospheric Ozone and Climate. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9081595_V1
This datasets provide basis of our analysis in the paper - Potential Impacts of Supersonic Aircraft on Stratospheric Ozone and Climate. All datasets here can be categorized into emission data and model output data (WACCM). All the model simulations (background and perturbation) were run to steady-state and only the datasets used in analysis are archived here.
keywords:
NetCDF; Supersonic aircraft; Stratospheric ozone; Climate
published: 2021-04-29
Jackson, Nicole ; Konar, Megan ; Debaere, Peter; Sheffield, Justin (2021): Data for "Crop-specific exposure to extreme temperature and moisture for the globe for the last half century". University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-5457902_V1
Global assessments of climate extremes typically do not account for the unique characteristics of individual crops. A consistent definition of the exposure of specific crops to extreme weather would enable agriculturally-relevant hazard quantification. We introduce the Agriculturally-Relevant Exposure to Shocks (ARES) model, a novel database of both the temperature and moisture extremes facing individual crops by explicitly accounting for crop characteristics. Specifically, we estimate crop-specific temperature and moisture shocks during the growing season for a 0.25-degree spatial grid and daily time scale from 1961-2014 globally for 17 crops. The resulting database presented here provides annual crop- and event-specific exposure rates. Both gridded and country-level exposure rates are provided for each of the 17 crops. Our results provide new insights into the changes in the magnitude as well as spatial and temporal distribution of extreme events that impact crops over the past half-century. For additional information, please see the related paper by Jackson et al. (2021) in Environmental Research Letters.
keywords:
Crop-specific; weather extremes; temperature; moisture; global; gridded; time series
published: 2021-04-12
Urco Cordero, Juan M.; Kamalabadi, Farzad; Kamaci, Ulas; Harding, Brian J.; Frey, Harald U.; Mende, Stephen B.; Huba, Joe D.; England, Scott L.; Immel, Thomas J. (2021): Data for Conjugate photoelectron energy spectra derived from coincident FUV and radio measurements. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-2215727_V1
Conjugate photoelectron energy spectra derived from coincident FUV and radio measurements. These are outputs of simulations from the semi-empirical SAMI2-PE (Varney et al. 2012) for the night of January 4, 2020.
keywords:
Conjugate photoelectrons, SAMI2-PE, ICON
published: 2022-04-15
Kim, Hyunbin; Makhnenko, Roman (2022): Data on "Evaluation of CO2 sealing potential of heterogeneous Eau Claire shale". University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-5509498_V1
This dataset is provided to support the statements in Kim, H., and R.Y. Makhnenko. 2022. "Evaluation of CO2 sealing potential of heterogeneous Eau Claire shale". Journal of the Geological Society. In geologic carbon dioxide (CO2) storage in deep saline aquifers, buoyant CO2 tends to float upwards in the reservoirs overlaid by low permeable formations called caprocks. Caprocks should serve as barriers to potential CO2 leakage that can happen through a diffusion loss and permeation through faults, fractures, or pore spaces. The leakage through intact caprock would mainly depend on its permeability and CO2 breakthrough pressure, and is affected by the heterogeneities in the material. Here, we study the sealing potential of a caprock from Illinois Basin - Eau Claire shale, with sandy and shaly fractions distinguished via electron microscopy and grain/pore size and surface area characterization. The direct measurements of permeability of sandy shale provides the values ~ 10-15 m2, while clayey specimens are three orders of magnitude less permeable. The CO2 breakthrough pressure under in-situ stress conditions is 0.1 MPa for the sandy shale and 0.4 MPa for the clayey counterpart – these values are higher than those predicted by the porosimetry methods performed on the unconfined specimens. Sandy Eau Claire shale would allow penetration of large CO2 volumes at low overpressures, while the clayey formation can serve as a caprock in the absence of faults and fractures in it.
keywords:
Geologic carbon storage; Caprock; Shale; CO2 breakthrough pressure; Porosimetry.
published: 2021-10-04
Wang, Justin; Curtis, Jeffrey H; Riemer, Nicole; West, Matthew (2021): Data from: Learning coagulation processes with combinatorially-invariant neural networks. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-3904737_V1
This dataset contains all the necessary information to recreate the study presented in the paper entitled "Learning coagulation processes with combinatorially-invariant neural networks". This consists of (1) the aggregated output files used for machine learning, (2) the machine learning codes used to learn the presented models, (3) the PartMC model source code that was used to generate the simulation data and (4) the Python scripts used construct the scenario library for training and testing simulations. This data was used to investigate a method (combinatorally-invariant neural network) for learning the aerosol process of coagulation. This data may be useful for application of other methods.
keywords:
Machine learning; Atmospheric chemistry; Particle-resolved modeling; Coagulation; Atmospheric Science
published: 2022-05-26
Madhavan, Vidya; Aishwarya, Anuva (2022): Data for Long-lifetime spin excitations near domain walls in 1T-TaS2. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-0883774_V1
The data files are for the paper entitled: Long-lifetime spin excitations near domain walls in 1T-TaS2 to be published in PNAS. The data was obtained on a 300 mK custom designed Unisoku scanning tunneling microscope using the Nanonis module. All the data files have been named based on the Figure numbers that they represent.
keywords:
Mott Insulator; Spins; Charge Density Wave; Domain walls; Long lifetime
published: 2021-11-04
Dawson, Matthew; Guzman Ruiz, Christian; Curtis, Jeffrey H.; Acosta, Mario C.; Zhu, Shupeng; Dabdub, Donald; Conley, Andrew; West, Matthew; Riemer, Nicole; Jorba, Oriol (2021): Data from: Chemistry Across Multiple Phases (CAMP) version 1.0: An integrated multi-phase chemistry model. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-8012140_V1
This dataset contains all the data for the results section in the study presented in the paper entitled "Chemistry Across Multiple Phases (CAMP) version 1.0: An integrated multi-phase chemistry mode" submitted to Geoscientific Model Development (GMD). In this paper, two sets of simulations were run to test CAMP with this results included here. This consists of (1) box model inputs and outputs presented in Section 4.2 for modal, binned and particle-resolved simulations to compare the application of identical chemical mechanisms to different aerosol representations and (2) the 3D Eulerian output presented in Section 4.3.
keywords:
Atmospheric chemistry; Aerosols and particles; Numerical Modeling
published: 2022-02-07
Karakoc, Deniz Berfin; Wang, Junren; Konar, Megan (2022): Data for: Food flows between counties in the Unites States from 2007 to 2017. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9585947_V1
This dataset provides estimates of agricultural and food commodity flows [kg] between all county pairs within the United States for the years 2007, 2012, and 2017. The database provides 206.3 million data points, since pairwise information is provided between 3134 counties, for 7 commodity categories, and 3 time periods. The commodity categories correspond to the Standardized Classification of Transported Goods and are: - SCTG 1: Iive animals and fish - SCTG 2: cereal grains - SCTG 3: agricultural products (except for animal feed, cereal grains, and forage products) - SCTG 4: animal feed, eggs, honey, and other products of animal origin - SCTG 5: meat, poultry, fish, seafood, and their preparations - SCTG 6: milled grain products and preparations, and bakery products - SCTG 7: other prepared foodstuffs, fats and oils For additional information, please see the related paper by Karakoc et al. (2022) in Environmental Research Letters.
keywords:
food flows; high-resolution; county-scale; time-series; United States
published: 2023-10-26
Maffeo, Christopher; Aksimentiev, Aleksei (2023): Simulation trajectories for "A DNA turbine powered by a transmembrane potential across a nanopore". University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-3458097_V1
Simulation trajectory data and scripts for Nature Nanotechnology manuscript "A DNA turbine powered by a transmembrane potential across a nanopore" that demonstrates a rationally designed nanoscale DNA-origami turbine with three chiral blades that uses a transmembrane electrochemical potential across a nanopore to drive a DNA bundle into sustained unidirectional rotations of up to 10 revolutions/s. Driven by the asymmetric mobility of a DNA duplex, the rotation direction of the turbine is set by its designed chirality and the salinity of the solvent.
keywords:
All-atom MD simulation; DNA; nanotechnology; motors and rotors
published: 2020-06-26
Gasparik, Jessica T.; Ye, Qing; Curtis, Jeffrey H.; Presto, Albert A.; Donahue, Neil M.; Sullivan, Ryan C.; West, Matthew; Riemer, Nicole (2020): Data from: Quantifying Errors in the Aerosol Mixing-State Index Based on Limited Particle Sample Size. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-2774261_V1
This dataset contains the PartMC-MOSAIC simulations used in the article "Quantifying Errors in the Aerosol Mixing-State Index Based on Limited Particle Sample Size". The 1000 simulations of output data is organized into a series of archived folders, each containing 100 scenarios. Within each scenario directory are 25 NetCDF files, which are the hourly output of a PartMC-MOSAIC simulation containing all information regarding the environment, particle and gas state. This dataset was used to investigate the impact of sample size on determining aerosol mixing state. This data may be useful as a data set for applying different types of estimators.
keywords:
Atmospheric aerosols; single-particle measurements; sampling uncertainty; NetCDF
published: 2019-05-22
Lao, Yuyang; Schiffer, Peter (2019): Isolated artificial spin ice kinetics. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-0214000_V1
This is the experimental data of isolated nanomagnet islands with or without the presence of large nanomagnet islands. The small islands are made of Permalloy materials with size of 170 nm by 470 nm by 2.5 nm. The systems are measured at a temperature where the small islands are fluctuating around room temperature. The data is recorded as photoemission electron microscopy intensity. More details about the data can be found in the note.txt and Spe_2016.xlsx file. Note: The raw data folders are stored in five volumes during the compression. All five volumes are needed in order to recover the original folder.
keywords:
artificial spin ice; magnetism