The goal here is to study the voltage and expansion response of lithium-ion batteries at different charging rates. Specifically, the goal is to capture the observation of the smoothing of the peaks in dV/dQ and retention of the peaks in d^2 (backslash)delta/dQ^2 at higher C-rates. The retention of the peaks at higher charging rates enables better estimation of the cell capacity. To achieve this goal a reduced order electrochemical and mechanical model with multiple particles with a size distribution is developed. This allows us to capture the smoothing and preservation of the phase transitions in the voltage and expansion measurements at high C-rates, respectively. The model is written in Matlab software.
Mohtat, P., Lee, S., Sulzer, V., Siegel, J. B., & Stefanopoulou, A. G. (2020). Differential Expansion and Voltage Model for Li-ion Batteries at Practical Charging Rates. Journal of The Electrochemical Society, 167(11), 110561. https://doi.org/10.1149/1945-7111/aba5d1
Data used in the paper "Theory of Magnetic Switchbacks Fully Supported by Parker Solar Probe Observations" by G. Toth, M. Velli and B. van der Holst, ApJ 2023.
The Observations directory contains the PSP observations as simple text files that can be easily read by the IDL macros in the BATSRUS/share/IDL/General/ or any other plotting software.
The Simulations directory contains BATSRUS simulations including input and output files. The runlog files show the Git references. The output files are in binary format that can be read by the IDL macros in the BATSRUS/share/IDL/General/ or with the SpacePy software.
The BATSRUS directory contains the source code that can be used to reproduce the simulations.
G. Toth, M. Velli, B. van der Holst, 2023, Theory of Magnetic Switchbacks Fully Supported by Parker Solar Probe Observations, The Astrophysical Journal, in press
As part of the Flaring & Fossil Fuels: Uncovering Emissions & Losses (F3UEL) project, in 2022 the aircraft measurement platform sampled offshore oil & gas facilities in the US Gulf of Mexico to quantify facility-level emissions using the approach detailed in Conley et al. (2017). Vertical profiles were conducted on each flight to capture the vertical structure and mixing depths of the atmosphere. The data file contains all merged flight data from each flight day.
Reference: Conley, S., Faloona, I., Mehrotra, S., Suard, M., Lenschow, D. H., Sweeney, C., Herndon, S., Schwietzke, S., Pétron, G., Pifer, J., Kort, E. A., and Schnell, R.: Application of Gauss’s theorem to quantify localized surface emissions from airborne measurements of wind and trace gases, Atmos. Meas. Tech., 10, 3345 – 3358, 2017.
This data set is my analysis of data management plans (DMPs) that were written by researchers at the University of Michigan for awards made between March 2020 and February 2021. I conducted this analysis to explore the potential utility of DMPs as a tool to aid data curators in understanding and working with the associated data set. Variables collected include: the types and formats of the expected data sets, information about the metadata and documentation to be generated, the anticipated methods for making the data set publicly available, references to Intellectual Property allowances or concerns, and the stated duration for preserving the data sets.
Carlson, J. (2023) Untapped Potential: A Critical Analysis of the Utility of Data Management Plans in Facilitating Data Sharing. Journal of Research Administration. Fall 2023. Forthcoming.
Single molecule data and analysis code for Figure4 in the paper titled: "A rhythmically pulsing leaf-spring DNA-origami nanoengine that drives a passive follower".
Follow the readme file for deiails.
This research was completed to statistically validate that a data-model refinement technique could integrate real measurements to remove bias from physics-based models via changing the forcing parameters such as the thermal conductivity coefficients.
Ponder, B. M., Ridley, A. J., Goel, A., & Bernstein, D. S. (2023). Improving forecasting ability of GITM using data-driven model refinement. Space Weather, 21, e2022SW003290. https://doi.org/10.1029/2022SW003290
This is a collection of mostly short documentary-style videos related to linguistic fieldwork in southwestern Burkina Faso. The initial batch consists of videos produced in 2023, and others will be added. Versions of some of these videos overdubbed in native languages will also be produced for local consumption in Burkina. Most of the videos document everyday practical activities; some also feature useful native plants and insects. This collection is parallel to collections of videos from neighboring Mali: see "Central Mali documentary videos" (with documentaries produced up to 2018) and "Mali documentary videos from 2023 on" for the newer ones. A small collection from north-central Côte d'Ivoire is also in the works. Within each collection, the videos are organized into "works" based on the general type of activity documented.
Each "work" in this collection is a set of documentary-style videos in mp4 (m4v) format. The initial (2023) set of works is as follows: "farming and plant gathering (Mali mp4)", "construction and boatbuilding (Mali mp4)", "fishing (Mali mp4)", "food and beverage preparation (Mali mp4)", metalwork and woodwork (Mali mp4)", "cultural events (Mali mp4)", "firearms and gunpowder (Mali mp4)", "pottery (Mali mp4)", and "weaving and dyeing (Mali mp4)". Funding: National Science Foundation, Documenting Endangered Languages program. The readme's for each work give further details. Additional works with new videos may be added in the future.
See also the Deep Blue Data collections "Burkina Faso documentary videos" and "Central Mali documentary videos". The latter contains Mali videos archived in 2018.
This is the model and observational data referenced in our manuscript entitled “surface and sub-subsurface internal gravity wave kinetic energy spectra from global ocean models and observations.” The model data for the 7 regions from the two global simulations (HYCOM and MITgcm) can be found here.
These files contain the raw data and processing parameters to go with the paper "Hierarchical structure guides rapid linguistic predictions during naturalistic listening" by Jonathan R. Brennan and John T. Hale. These files include the stimulus (wav files), raw data (BrainVision format), data processing parameters (matlab), and variables used to align the stimuli with the EEG data and for the statistical analyses reported in the paper (csv spreadsheet).
and Updates in Version 2:
- data in BrainVision format
- added information about data analysis
- corrected prePROCessing information for S02
Brennan, J. R., & Hale, J. T. (2019). Hierarchical structure guides rapid linguistic predictions during naturalistic listening. PLoS ONE 14(1). e0207741
