University of South Florida Showcase

Bulk modulus versus temperature data from equilibrium molecular dynamics simulations of a model neat elastomer. Dataset for Kawak, Bhapkar, Simmons. Origin of Heating-Induced Softening and Enthalpic Reinforcement in Elastomeric Nanocomposites. ACS Macro Letters 2025, 14, 12, 1867–1873 DOI:10.1021/acsmacrolett.5c00442

Young's modulus and Poisson's ratio versus temperature data from uniaxial extension molecular dynamics simulations of model neat and filled elastomers. Dataset for Kawak, Bhapkar, Simmons. Origin of Heating-Induced Softening and Enthalpic Reinforcement in Elastomeric Nanocomposites. ACS Macro Letters 2025, 14, 12, 1867–1873 DOI:10.1021/acsmacrolett.5c00442

(a) Young's modulus E versus temperature T in LJ units for model neat elastomers and filled elastomers at 150 parts per hundred rubber (PHR) loading or 0.415 filler volume fraction calculated using finite difference of extensional stress between strains of 4.5% and 5.5%. The solid green curve is the prediction of the composite modulus temperature dependence from Equation (5), with f =1.19. The solid blue curve is the prediction of the neat modulus temperature dependence from classical theory of rubber elasticity (i.e., proportionality to temperature) (b) Bulk modulus Ke versus T in LJ units for a model neat elastomer at zero pressure. Ke is computed via the fluctuation-dissipation relation as T〈V〉/〈δV2〉, where V is the volume, 〈V〉 is the NPT ensemble average of the volume, and 〈δV2〉 is the NPT ensemble variance of the volume. The solid curve is a fit to the Tait equation (Equation (2)). (c) Poisson’s ratio ν versus T computed by finite difference of extensional strain to normal strain between 4.5% and 5.5% extensional strain. d) Ec from panel a) versus theoretical prediction from Equation (1). Error bars reflect standard errors of the mean over 100 (a), 5 (b), and 100 (c) independent replicates. Dataset for Kawak, Bhapkar, Simmons. Origin of Heating-Induced Softening and Enthalpic Reinforcement in Elastomeric Nanocomposites. ACS Macro Letters 2025, 14, 12, 1867–1873 DOI:10.1021/acsmacrolett.5c00442

Relaxation times of interfacial and bulk polymer segments (distance less than 1 σ and greater than 3 σ away from filler surface, respectively) versus temperature in Lennard-Jones (LJ) units (εLJ is LJ energy scale and kB is the Boltzmann constant). Dataset for Kawak, Bhapkar, Simmons. Origin of Heating-Induced Softening and Enthalpic Reinforcement in Elastomeric Nanocomposites. ACS Macro Letters 2025, 14, 12, 1867–1873 DOI:10.1021/acsmacrolett.5c00442

Rendering of a configuration of model filled elastomer with loading of 150 parts per hundred rubber (PHR) or 0.415 filler volume fraction. Polymers are rendered in green (with bonds shown); beads that comprise filler particles are rendered in pale yellow. Rendered by OVITO. Dataset for Kawak, Bhapkar, Simmons. Origin of Heating-Induced Softening and Enthalpic Reinforcement in Elastomeric Nanocomposites. ACS Macro Letters 2025, 14, 12, 1867–1873 DOI:10.1021/acsmacrolett.5c00442

Raw physiological data and pump characteristics data.

This dataset contains three subsets. First is the Point Cloud folder, which holds the point clouds that were used for the analysis. This includes a set of point cloud tiles, which were used for the tree characteristic analysis. Second is the raster data. These are outputs from the raster and tree analysis. Last is the tree data gathered during the September 2025 ground survey.

This repository contains individual-level measurements of millipedes and their associated mite loads, including site metadata, host traits (length, mass, segments), derived segment mass, developmental stage, and mite abundance/presence.

This dataset contains the detailed Methods and Results for the following paper: “Sargassum Watch System: an online tool to address societal needs” by the same authors of this dataset. Specifically, the dataset contains the following files: SaWS_Google_Analysitcs_Methods.docx SaWS_Google_Analysitcs_Results.xlsx These are the methods of using Google Analytics to generate Web access statistics, and the corresponding statistics. SaWS_Literature_Review_Methods.docx SaWS_Literature_Review_Results.xlsx These are the methods of conducting literature review, and the corresponding review results including the publication title and author names as well as how they are related to SaWS. SaWS_Media_Coverage_Methods.docx SaWS_Media_Coverage_Results.xlsx These are the methods of searching for relevant public media coverage (both online and print, in both English and Spanish), and the corresponding search results on how SaWS or the personnel behind SaWS were cited by the public media. SaWS_Survey_Questions.docx SaWS_Survey_Answers_anonymized.xlsx SaWS_Survey_User_Quotes_anonymized.docx These are the methods to conduct an online survey, along with the survey questions. The Excel file contains all detailed answers to the survey questions, with names and email addresses anonymized to protect privacy. The last file contains user narratives on how SaWS was used by them or by their organizations. To protect privacy, all user names are anonymized.

Reproduces all tables and figures in: "Racial Self-Classification, Group Consciousness, and Public Employment Representation," by Diogo Baerlocher & Rodrigo Schneider published at the Journal of Development Economics.