skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Available online 12 November 2020 1364-0321/  2020 Elsevier Ltd. All rights reserved. State of the art in composition, fabrication, characterization, and modeling methods of cement-based thermoelectric materials for low-temperature applications
Award ID(s):
1805893
PAR ID:
10260026
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ; ; ;
Date Published:
Journal Name:
Renewable sustainable energy reviews
Volume:
137
ISSN:
1364-0321
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. null (Ed.)
  2. null (Ed.)
  3. null (Ed.)
    Abstract Editors note: For easy download the posted pdf of the State of the Climate in 2020 is a very low-resolution file. A high-resolution copy of the report is available by clicking here . Please be patient as it may take a few minutes for the high-resolution file to download. 
    more » « less
  4. null (Ed.)
  5. {"Abstract":["Data provided by the Integrating Data science with Trees and Remote Sensing (IDTReeS) research group for use in the IDTReeS Competition.<\/p>\n\nGeospatial and tabular data to be used in two data science tasks focused on using remote sensing data to quantify the locations, sizes and species identities of millions of trees and on determining how these methods generalize to other forests.<\/p>\n\nVector data are the geographic extents of Individual Tree Crown boundaries that have been identified by researchers in the IDTReeS group. The data were generated primarily by Sarah Graves, Sergio Marconi, and Benjamin Weinstein, with support from Stephanie Bohlman, Ethan White, and members of the IDTReeS group.<\/p>\n\nRemote Sensing and Field data were generated by the National Ecological Observatory Network (NEON, Copyright © 2017 Battelle). Data were selected, downloaded, and packaged by Sergio Marconi. The most recent available data of the following products are provided:<\/p>\n\nNational Ecological Observatory Network. 2020. Data Product DP1.30010.001, High-resolution orthorectified camera imagery. Provisional data downloaded from http://data.neonscience.org on March 4, 2020. Battelle, Boulder, CO, USA NEON. 2020.<\/p>\n\nNational Ecological Observatory Network. 2020. Data Product DP1.30003.001, Discrete return LiDAR point cloud. Provisional data downloaded from http://data.neonscience.org on March 4, 2020. Battelle, Boulder, CO, USA NEON. 2020.<\/p>\n\nNational Ecological Observatory Network. 2020. Data Product DP1.10098.001, Woody plant vegetation structure. Provisional data downloaded from http://data.neonscience.org on March 4, 2020. Battelle, Boulder, CO, USA NEON. 2020.<\/p>\n\nNational Ecological Observatory Network. 2020. Data Product DP3.30015.001, Ecosystem structure. Provisional data downloaded from http://data.neonscience.org on March 4, 2020. Battelle, Boulder, CO, USA NEON. 2020.<\/p>\n\nNEON has the following data policy:<\/p>\n\n\u2018The National Ecological Observatory Network is a program sponsored by the National Science Foundation and operated under cooperative agreement by Battelle Memorial Institute. This material is based in part upon work supported by the National Science Foundation through the NEON Program.\u2019<\/p>\n\nTHE NEON DATA PRODUCTS ARE PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, TITLE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR ANYONE DISTRIBUTING THE NEON DATA PRODUCTS BE LIABLE FOR ANY DAMAGES OR OTHER LIABILITY, WHETHER IN CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE NEON DATA PRODUCTS.<\/p>"],"Other":["This data is supported by the National Science Foundation through grant 1926542 and by the Gordon and Betty Moore Foundation's Data-Driven Discovery Initiative through grant GBMF4563 to E.P. White, and the NSF Dimension of Biodiversity program grant (DEB-1442280) and USDA/NIFA McIntire-Stennis program (FLA-FOR-005470)."]} 
    more » « less