Posts tagged CU study
CU study: Graphene membranes may lead to enhanced natural gas production, less CO2 pollution
Oct 8th
The findings are a significant step toward the realization of more energy-efficient membranes for natural gas production and for reducing carbon dioxide emissions from power plant exhaust pipes.
Mechanical engineering professors Scott Bunch and John Pellegrino co-authored a paper in Nature Nanotechnology with graduate students Steven Koenig and Luda Wang detailing the experiments. The paper was published Oct. 7 in the journal’s online edition.
The research team introduced nanoscale pores into graphene sheets through ultraviolet light-induced oxidative “etching,” and then measured the permeability of various gases across the porous graphene membranes. Experiments were done with a range of gases including hydrogen, carbon dioxide, argon, nitrogen, methane and sulphur hexaflouride — which range in size from 0.29 to 0.49 nanometers — to demonstrate the potential for separation based on molecular size. One nanometer is one billionth of a meter.
“These atomically thin, porous graphene membranes represent a new class of ideal molecular sieves, where gas transport occurs through pores which have a thickness and diameter on the atomic scale,” said Bunch.
Graphene, a single layer of graphite, represents the first truly two-dimensional atomic crystal. It consists of a single layer of carbon atoms chemically bonded in a hexagonal “chicken wire” lattice — a unique atomic structure that gives it remarkable electrical, mechanical and thermal properties.
“The mechanical properties of this wonder material fascinate our group the most,” Bunch said. “It is the thinnest and strongest material in the world, as well as being impermeable to all standard gases.”
Those characteristics make graphene an ideal material for creating a separation membrane because it is durable and yet doesn’t require a lot of energy to push molecules through it, he said.
Other technical challenges will need to be overcome before the technology can be fully realized. For example, creating large enough sheets of graphene to perform separations on an industrial scale, and developing a process for producing precisely defined nanopores of the required sizes are areas that need further development. The CU-Boulder experiments were done on a relatively small scale.
The importance of graphene in the scientific world was illustrated by the 2010 Nobel Prize in physics that honored two scientists at Manchester University in England, Andre K. Geim and Konstantin Novoselov, for producing, isolating, identifying and characterizing graphene. Scientists see a myriad of potential for graphene as research progresses, from making new and better display screens and electric circuits to producing tiny biomedical devices.
The research was sponsored by the National Science Foundation; the Membrane Science, Engineering and Technology Center at CU-Boulder; and the DARPA Center on Nanoscale Science and Technology for Integrated Micro/Nano Electromechanical Transducers at CU-Boulder.
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CU study says Romney will be Pres
Oct 4th
still points to Romney win,
University of Colorado study says
An update to an election forecasting model announced by two University of Colorado professors in August continues to project that Mitt Romney will win the 2012 presidential election.
According to their updated analysis, Romney is projected to receive 330 of the total 538 Electoral College votes. President Barack Obama is expected to receive 208 votes — down five votes from their initial prediction — and short of the 270 needed to win.
The new forecast by political science professors Kenneth Bickers of CU-Boulder and Michael Berry of CU Denver is based on more recent economic data than their original Aug. 22 prediction. The model itself did not change.
“We continue to show that the economic conditions favor Romney even though many polls show the president in the lead,” Bickers said. “Other published models point to the same result, but they looked at the national popular vote, while we stress state-level economic data.”
While many election forecast models are based on the popular vote, the model developed by Bickers and Berry is based on the Electoral College and is the only one of its type to include more than one state-level measure of economic conditions. They included economic data from all 50 states and the District of Columbia.
Their original prediction model was one of 13 published in August in PS: Political Science & Politics, a peer-reviewed journal of the American Political Science Association. The journal has published collections of presidential election models every four years since 1996, but this year the models showed the widest split in outcomes, Berry said. Five predicted an Obama win, five forecast a Romney win, and three rated the 2012 race as a toss-up.
The Bickers and Berry model includes both state and national unemployment figures as well as changes in real per capita income, among other factors. The new analysis includes unemployment rates from August rather than May, and changes in per capita income from the end of June rather than March. It is the last update they will release before the election.
Of the 13 battleground states identified in the model, the only one to change in the update was New Mexico — now seen as a narrow victory for Romney. The model foresees Romney carrying New Mexico, North Carolina, Virginia, Iowa, New Hampshire, Colorado, Wisconsin, Minnesota, Pennsylvania, Ohio and Florida. Obama is predicted to win Michigan and Nevada.
In Colorado, which Obama won in 2008, the model predicts that Romney will receive 53.3 percent of the vote to Obama’s 46.7 percent, with only the two major parties considered.
While national polls continue to show the president in the lead, “the president seems to be reaching a ceiling at or below 50 percent in many of these states,” Bickers said. “Polls typically tighten up in October as people start paying attention and there are fewer undecided voters.”
The state-by-state economic data used in their model have been available since 1980. When these data were applied retroactively to each election year, the model correctly classifies all presidential election winners, including the two years when independent candidates ran strongly: 1980 and 1992. It also correctly estimates the outcome in 2000, when Al Gore won the popular vote but George W. Bush won the election through the Electoral College.
In addition to state and national unemployment rates, the authors analyzed changes in personal income from the time of the prior presidential election. Research shows that these two factors affect the major parties differently: Voters hold Democrats more responsible for unemployment rates, while Republicans are held more responsible for fluctuations in personal income.
Accordingly — and depending largely on which party is in the White House at the time — each factor can either help or hurt the major parties disproportionately.
In an examination of other factors, the authors found that none of the following had a statistically significant effect on whether a state ultimately went for a particular candidate: The location of a party’s national convention, the home state of the vice president or the partisanship of state governors.
The authors also provided caveats. Their model had an average error rate of five states and 28 Electoral College votes. Factors they said may affect their prediction include the timeframe of the economic data used in the study and that states very close to a 50-50 split may fall in an unexpected direction due to factors not included in the model.
“As scholars and pundits well know, each election has unique elements that could lead one or more states to behave in ways in a particular election that the model is unable to correctly predict,” they wrote.
All 13 election models can be viewed on the PS: Political Science & Politics website at http://journals.cambridge.org/action/displayJournal?jid=PSC.
CU study: Global warming increasing heavy metals in streams
Sep 7th
in Rocky Mountain watershed
tied to warming temperatures
Warmer air temperatures since the 1980s may explain significant increases in zinc and other metal concentrations of ecological concern in a Rocky Mountain watershed, reports a new study led by the U.S. Geological Survey and the University of Colorado Boulder.
Rising concentrations of zinc and other metals in the upper Snake River just west of the Continental Divide near Keystone, Colo., may be the result of falling water tables, melting permafrost and accelerating mineral weathering rates, all driven by warmer air temperatures in the watershed. Researchers observed a fourfold increase in dissolved zinc over the last 30 years during the month of September.
Increases in metals were seen in other months as well, with lesser increases seen during the high-flow snowmelt period. During the study period, local mean annual and mean summer air temperatures increased at a rate of 0.5 to 2.2 degrees Fahrenheit per decade.
Generally, high concentrations of dissolved metals in the Snake River watershed are primarily the result of acid rock drainage, or ARD, formed by natural weathering of pyrite and other metal-rich sulfide minerals in the bedrock. Weathering of pyrite forms sulfuric acid through a series of chemical reactions, and pulls metals like zinc from minerals in the rock and carries these metals into streams.
Increased sulfate and calcium concentrations observed over the study period lend weight to the hypothesis that the increased zinc concentrations are due to acceleration of pyrite weathering. The potential for comparable increases in metals in similar Western watersheds is a concern because of impacts on water resources, fisheries and stream ecosystems. Trout populations in the lower Snake River, for example, appear to be limited by the metal concentrations in the water, said USGS research biologist Andrew Todd, lead researcher on the project.
“Acid rock drainage is a significant water quality problem facing much of the Western United States,” Todd said. “It is now clear that we need to better understand the relationship between climate and ARD as we consider the management of these watersheds moving forward.”
Warmer temperatures and earlier snowmelt runoff have been observed throughout mountainous areas of the western United States where ARD is common, but it is not known if these changes have triggered rising acidity and metal concentrations in other “mineralized” watersheds because of lack of comparable monitoring data, according to the research team.
CU-Boulder Professor Diane McKnight, a collaborator on the project, has generated much of the upper Snake River data through research projects conducted with her students since the mid-1990s. McKnight said students in her environmental engineering and environmental studies class like Caitlin Crouch — a study co-author who received her master’s degree under McKnight — are highly motivated to understand ARD problems.
“Student can see that their research will have direct applications to addressing a critical issue for Colorado,” said McKnight, professor in the civil, environmental and architectural engineering department and a fellow in CU’s Institute of Arctic and Alpine Research.
In cases where ARD is linked directly with past and present mining activities it is called acid mine drainage, or AMD. Another Snake River tributary, Peru Creek, is largely devoid of life due to AMD generated from the abandoned Pennsylvania Mine and smaller mines upstream and has become a target for potential remediation efforts.
The Colorado Division of Reclamation Mining and Safety, in conjunction with other local, state and federal partners, is conducting underground exploration work at the mine to investigate the sources of heavy metals-laden water draining from the mine entrance. The new study by Todd and colleagues has important implications in such mine cleanup efforts because it suggests that establishing attainable cleanup objectives could be difficult if natural background metal concentrations are a “moving target.”
A study on the subject was published in the journal Environmental Science and Technology. Other collaborators include Andrew Manning and Philip Verplanck of USGS. The data analyzed for the study came from INSTAAR, the USGS and the U.S. Environmental Protection Agency.