Green Car Congress
MAY 11, 2016
The Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) has selected Pennsylvania State University as the lead institution to establish the University Coalition for Fossil Energy Research.
Green Car Congress
DECEMBER 29, 2014
The global economic recession of 2008—which severely depressed light-duty vehicle sales—resulted in an increase in the age of the light-duty vehicle fleet in the US that likely slowed the rate of decrease of fleet average emissions, according to a study by Gary Bishop and Donald Stedman at the University of Denver.
Green Car Congress
APRIL 3, 2019
Researchers at the University of Oklahoma, in collaboration with the University of Tulsa, have a novel approach for the water-assisted upgrading of the renewable chemical furfural, doubling or tripling the rate of conversion.
Green Car Reports
FEBRUARY 21, 2012
Yesterday, Newt Gingrich mocked the current Administration's promotion of fuel-efficient cars in a speech at Oral Roberts University in Tulsa. It's obvious because slaps at green cars and fuel-economy rules have become a staple of political campaigning among certain candidates.
Green Car Congress
FEBRUARY 7, 2014
Arizona State University. High-Temperature Topping Cells from LED Materials Arizona State University will develop a solar cell that can operate efficiently at temperatures above 450°C, unlike today’s solar cells, which lose efficiency rapidly above 100°C. Arizona State University. The University of Tulsa.
Green Car Congress
AUGUST 2, 2019
Alabama A&M University. Alabama A&M University will receive funds to replace diesel buses that have reached the end of useful life with zero-emission electric buses, including all related electrical charging station infrastructure. Metropolitan Tulsa Transit Authority.
Green Car Congress
JANUARY 4, 2020
The University of Oklahoma (Norman, OK) plans to develop, build, and validate a low-cost, field-installable, remotely-controlled natural gas compressor retrofit kit. University of New Mexico aims to develop advanced gas sensors (mixed potential electrochemical [MPE]) coupled with advanced computation (artificial neural networks).
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