- Number 414 |
- May 26, 2014
DOE's Ames Laboratory has created a faster, cleaner biofuel refining technology that not only combines processes, it uses widely available materials to reduce costs.Ames Lab scientists have developed a nanoparticle that is able to perform two processing functions at once for the production of green diesel, an alternative fuel created from the hydrogenation of oils from renewable feedstocks like algae.
The method is a departure from the established process of producing biodiesel, which is accomplished by reacting fats and oils with alcohols.
Scientists at DOE's SLAC National Accelerator Laboratory and Stanford University have shown for the first time how high-temperature superconductivity emerges out of magnetism in an iron pnictide, a class of materials with great potential for making devices that conduct electricity with 100 percent efficiency.
In experiments at SLAC’s Stanford Synchrotron Radiation Lightsource (SSRL), the team “doped” the material – one of two known types of high-temperature superconductor – by adding or subtracting electrons to enhance its superconducting abilities. Then they used a beam of ultraviolet light to measure changes in the material’s electronic behavior as it was chilled to a temperature where superconductivity becomes possible.
The Continuous Electron Beam Accelerator Facility (CEBAF) at DOE's Jefferson Lab has achieved the final two accelerator commissioning milestones needed for approval to start experimental operations following its first major upgrade. In the early hours of May 7, the machine delivered its highest-energy beams ever, 10.5 billion electron-volts (10.5 GeV) through the entire accelerator and up to the start of the beamline for its newest experimental complex, Hall D. Then, in the last minutes of the day on May 7, the machine delivered beam, for the first time, into Hall D.In addressing staff, Jefferson Lab Director Hugh Montgomery praised the efforts of the many Jefferson Lab staff members who made the accomplishment a reality, “It's really appreciated the way you have worked together and, in particular, the safe way in which you have pulled this off,” he said.
Sandia National Laboratories recently completed the renovation of five large-scale test facilities that are crucial to ensuring the safety and reliability of the nation’s nuclear weapons systems. The work supports Sandia’s ongoing nuclear stockpile modernization work on the B61-12 and W88 Alt, assessments of current stockpile systems and test and analysis for broad national security customers. The renovation of two additional facilities was completed in 2005 during the first phase of the project. The two-phase $100 million project, which was completed ahead of schedule and under budget, renovated Sandia’s major environmental test facilities.
The second and final phase of the project, Test Capabilities Revitalization Phase 2, updated and rebuilt the 10,000-foot Rocket Sled Track, Mechanical Shock, Centrifuge, Vibro-Acoustic and Mass Properties and Aerosciences facilities. The $57.8 million effort was completed on time and the project team was able to return $4.5 million to the National Nuclear Security Administration (NNSA) to address other critical needs. TCR Phase 1, from 2001 to 2005, constructed a new world-class Thermal Test Complex and rebuilt the Aerial Cable Facility.
Application performance modeling is an important methodology for diagnosing performance-limiting resources, optimizing application and system performance, and designing large-scale machines. However, because creating analytical models can be difficult and time-consuming, application developers often forgo the insight that these models can provide. To ease the burden of creating models, computer scientists at DOE’s Pacific Northwest National Laboratory developed the Performance and Architecture Lab Modeling tool, or Palm. Palm simplifies the task of constructing a model by automating common modeling tasks and providing a mechanism for modelers to incorporate human insight. With Palm, reproducing a model—a program that runs on a computer—is straightforward. Given the same input, Palm generates the same model. This is a first step toward enabling the open distribution and cross-team validation of models.