Measuring the Charge of Electrons in a High-Temp Superconductor
Brookhaven National LaboratoryThe measurements could inform the search for new materials that perfectly conduct electricity at relatively higher temperatures.
The measurements could inform the search for new materials that perfectly conduct electricity at relatively higher temperatures.
ExaStar aims to create simulations for comparison with experiments and observations to help answer a variety of questions: Why is there more iron than gold in the universe? Why is anything rarer than anything else? Why is finding transuranic elements on the face of the earth difficult?
A team of scientists led by Fermilab has prototyped a method to use machine learning to analyze data from the Large Hadron Collider.
In independent studies, two research teams report important advances in understanding how charge stripes might interact with superconductivity. Both studies were carried out with X-rays at the Department of Energy’s SLAC National Accelerator Laboratory.
The Institute for Advanced Computational Science (IACS) at Stony Brook University has received a $6.3 million anonymous donation to advance data-driven research that will improve understanding of some of the world’s most pressing challenges, including climate change, machine learning and next generation nuclear energy, among others.
A $5 million grant from the National Science Foundation (NSF) to the Institute of Advanced Computational Science (IACS) will enable researchers nationwide to test future supercomputing technologies and advance computational and data-driven research on the world’s most pressing challenges.
As part of the Department of Energy’s role in the fight against cancer, scientists are building tools that use supercomputers to solve problems in entirely new ways.
The National Microbiome Data Collaborative (NMDC), a new initiative aimed at empowering microbiome research, is gearing up its pilot phase after receiving $10 million from the U.S. Department of Energy Office of Science.
The Department of Energy (DOE), National Nuclear Security Administration (NNSA) and Lawrence Livermore National Laboratory (LLNL) today announced the signing of contracts with Cray Inc. to build the NNSA’s first exascale supercomputer, “El Capitan.” When delivered in late 2022, El Capitan will have a peak performance of more than 1.5 exaflops (1.5 quintillion calculations per second), about 10 times faster than LLNL’s current most powerful supercomputer, Sierra. The total contract award is valued at $600 million.
An international team of researchers, including scientists from the Department of Energy’s SLAC National Accelerator Laboratory, has demonstrated a potentially much brighter electron source based on plasma that could be used in more compact, more powerful particle accelerators.
A team devised a way to better model water’s properties. They developed a machine-learning workflow that offers accurate and computationally efficient models.
A new study led by a physicist at Berkeley Lab details how a quantum computing technique called “quantum annealing” can be used to solve problems relevant to fundamental questions in nuclear physics about the subatomic building blocks of all matter. It could also help answer other vexing questions in science and industry, too.
ORNL story tips: Training next-generation sensors to “see,” interpret live data; 3D printing tungsten could protect fusion reactor components; detailed study estimated how much more, or less, energy U.S. residents might consume by 2050 based on seasonal weather shifts; astrophysicists used ORNL supercomputer to create highest-ever-resolution galactic wind simulations; new solar-thermal desalination method improves energy efficiency.
The National Science Foundation has awarded the San Diego Supercomputer Center (SDSC) at UC San Diego a two-year grant worth almost $400,000 to deploy a new system called CC* Compute: Triton Stratus as an enhancement to the existing Triton Shared Computing Cluster (TSCC) campus High-Performance Computing (HPC) platform.
Globus, the leading research data management service, today announced the general availability of Globus for Box, a new solution for seamlessly connecting Box with an organization’s existing research storage ecosystem.
A team of researchers led by Bill Tang of the US Department of Energy's (DOE's) Princeton Plasma Physics Laboratory (PPPL) and Princeton University recently tested its Fusion Recurrent Neural Network (FRNN) code, a novel artificial intelligence (AI) resource designed to predict plasma instabilities, on various high-performance computing (HPC) systems. A reliable way to predict and mitigate disruptions could accelerate the adoption of fusion as an environmentally friendly, virtually unlimited source of energy.
The Department of Energy has fueled TAE Technologies' quest for commercially viable nuclear fusion energy with awards of computer time through the INCITE program
The San Diego Supercomputer Center (SDSC) at the University of California San Diego, has been awarded a five-year grant from the National Science Foundation (NSF) valued $10 million to deploy Expanse, a new supercomputer designed to advance research that is increasingly dependent upon heterogeneous and distributed resources.
Researchers at the U.S. Department of Energy’s (DOE) Argonne National Laboratory and Los Alamos National Laboratory, along with researchers at Clemson University and Fujitsu Laboratories of America, have developed hybrid algorithms to run on size-limited quantum machines and have demonstrated them for practical applications.
The High Performance Computing for Energy Innovation program (HPC4EI) today announced the nine public/private projects awarded more than $2 million in Department of Energy funding, with aims of improving energy production, enhancing or developing new material properties and reducing energy usage in manufacturing.
Globus, the leading research data management service, today announced the largest single file transfer in its history: a team led by Argonne National Laboratory scientists moved 2.9 petabytes of data as part of a research project involving three of the largest cosmological simulations to date.
Bladder cancer, one of the most common cancers in the U.S., may be soon helped by a novel non-invasive diagnostic method thanks to advances in machine learning research at the San Diego Supercomputer Center (SDSC), Moores Cancer Center, and CureMatch Incorporated.
The Sherlock Division at the San Diego Supercomputer Center (SDSC) at the University of California San Diego has announced the launch of Innovation Accelerator Platforms within its Sherlock Cloud infrastructure and its newest offering
Researchers have discovered that terahertz light --light at trillions of cycles per second -- can act as a control knob to accelerate supercurrents. That can help open up the quantum world of matter and energy at atomic and subatomic scales to practical applications such as ultrafast computing.
Capacitors, given their high energy output and recharging speed, could play a major role in powering the machines of the future, from electric cars to cell phones. However, the biggest hurdle for capacitors as energy storage devices is that they store much less energy than a similar-sized battery. Researchers at Georgia Institute of Technology are tackling that problem by using supercomputers and machine learning techniques to ultimately find ways to build more capable capacitors.
Argonne researchers are beginning to employ Bayesian methods in developing optimal models of thermodynamic properties. Research available online for the September 2019 issue of the International Journal of Engineering Science focused on hafnium (Hf), a metal emerging as a key component in computer electronics.
Multi-fault earthquakes can span fault systems of tens to hundreds of kilometers, with ruptures propagating from one segment to another. During the last decade, seismologists have observed several cases of this complicated type of earthquake rupture, and are now relying on supercomputers to provide detailed models to better understand the fundamental physical processes that take place during these events, which can have far reaching effects.
As he prepared to head to ISC19 to give a keynote address on the future of HPC beyond Moore's Law, John Shalf – who leads the Computer Science Department in Lawrence Berkeley National Laboratory’s Computational Research Division – shared his thoughts on what computing technologies and architectures may look like in the post-exascale era.
The National Science Foundation (NSF) has awarded a second round of funding for the country’s four Big Data Innovation Hubs – organizations where academics, community leaders, regional business, and local and state government representatives collaborate to help solve grand challenges of regional importance.
UC San Diego mechanical and aerospace engineering graduate student Tao Wang recently demonstrated how an extremely strong magnetic field, similar to that on the surface of a neutron star, can be not only generated but also detected using an x-ray laser inside a solid material.
With the assistance of artificial intelligence, researchers at Argonne are developing new ways to extract insights about the electric grid from mountains of data, with the goal of ensuring reliability and efficiency. The work combines Argonne's long-standing grid expertise with its advanced computing facilities and experts.
Researchers demonstrated record accelerating cavity performance using a technique that could lead to significant cost savings.
The U.S. Department of Energy announced that it will invest $32 million over the next four years to accelerate the design of new materials through use of supercomputers.
American ingenuity is providing radical productivity improvements from advanced materials and robotic systems developed at the Department of Energy’s Manufacturing Demonstration Facility at Oak Ridge National Laboratory.
A Brookhaven-hosted hackathon helped teams make use of new features in the OpenMP programming standard to support next-gen supercomputing.
New insights about how to understand and ultimately control the chemistry of ignition behavior and pollutant formation have been discovered in research led by Sandia National Laboratories. The discovery eventually will lead to cleaner, more efficient internal combustion engines.“Our findings will allow the design of new fuels and improved combustion strategies,” said Nils Hansen, Sandia researcher and lead author of the research.
Researchers use advanced nuclear models to explain 50-year mystery surrounding the process stars use to transform elements.
The San Diego Supercomputer Center (SDSC) at the University of California San Diego today announced the appointment of Michael Zentner as director of Sustainable Scientific Software, effective immediately.
According to a release issued in April by Georgia Institute of Technology (Georgia Tech), a serendipitous discovery by graduate student Dylan T. Christiansen has led to materials that quickly change color from completely clear to a range of vibrant hues – and back again.
Titan supercomputer tells origin story of nanoparticle size distributions with large-scale simulations.
Together with the United States Food and Drug Administration and the BioCompute Partnership, the George Washington University is co-sponsoring a workshop, titled “BioCompute Objects: Tools for Communicating Next Generation Sequencing Data and Analysis.”
For more than a decade, a team of international researchers led by Berkeley Lab bioscientists has been studying Photosystem II, a protein complex in green plants, algae, and cyanobacteria that plays a crucial role in photosynthesis. They’re now moving more quickly toward an understanding of this three-billion-year-old biological system, thanks to an integrated superfacility framework established between LCLS, ESnet, and NERSC.
The Health Cyberinfrastructure (CI) Division of the San Diego Supercomputer Center (SDSC) at the University of California San Diego, has partnered with Microsoft Azure Cloud Services (Azure) to expand its portfolio of cloud services.
The San Diego Supercomputer Center (SDSC) at the University of California San Diego announced today the appointment of Melissa Cragin as Chief Strategist for SDSC’s Research Data Services (RDS) group, effective immediately.
The widely used CyberInfrastructure for Phylogenetic REsearch (CIPRES) science gateway, based at the San Diego Supercomputer Center (SDSC), has been awarded a one-year Internet2 grant funded by the NSF to give users AWS cloud access.
In a groundbreaking effort, seismology researchers have conducted a continent-scale survey for seismic signatures of industrial activity in the Amazon Web Services commercial cloud (AWS), then rapidly downloaded the results without storing raw data or needing a local supercomputer.
Researchers in Berkeley Lab's Computational Research Division are applying deep learning and analytics to electronic health record (EHR) data to help the Veterans Administration address a host of medical and psychological challenges affecting many of the nation’s 700,000 military veterans.
Leveraging the power of the Comet supercomputer at the San Diego Supercomputer Center (SDSC) at UC San Diego, campus researchers have demonstrated they can efficiently analyze more than 1,000 EEG 128-channel high-density data sets via the new Open EEGLAB Portal running on SDSC’s Neuroscience Gateway (NSG).
The BISICLES ice sheet model uses high performance computing resources at the National Energy Research Scientific Computing Center (NERSC) to systematically examine where the Antarctic Ice Sheet is vulnerable and the resulting potential for large contributions to sea level rise.
To function properly, proteins must morph into specific 3D shapes through a biophysical phenomenon called protein folding. Researchers at ORNL are using various deep-learning techniques to study the intermediate protein stages between the initial unfolded state and the final folded state, which are notoriously difficult to characterize. These methods could also help identify factors that cause proteins to “misfold” into dysfunctional shapes, a phenomenon often attributed as a leading factor in the development of diseases including Alzheimer’s, cardiovascular disorders, and diabetes.