NERSCPowering Scientific Discovery Since 1974

Science Vignettes

SNe Iax Progenitor Scenario

Detection of Helium in Sub-luminous Thermonuclear Supernovae

Connecting Explosion Composition Models with Progenitor Channels Science Achievement Researchers at the University of California Santa Cruz have used the elemental composition of a peculiar supernova explosion to understand its complex origins. Using the NERSC supercomputers at Lawrence Berkeley Laboratories, the UCSC team modeled the material ejected in a new class of thermonuclear explosion called a Type Iax supernova (SN Iax). This recently discovered class of stellar explosion is… Read More »

image

Binding Preferences Predictions Across the Actinide Series

Researchers from the Institute for Nuclear Security and Radiochemistry Center of Excellence at the University of Tennessee, University of North Texas, U.S. Army Nuclear and Countering Weapons of Mass Destruction Agency, Stony Brook University, Brookhaven National Laboratory, and Y-12 National Security Complex evaluated method dependence in binding preferences across the actinide series. NERSC supercomputers allowed for accurate targets to be established – essential to evaluate less expensive methods to be applied in binding of elements of interest in nuclear security and fundamental research of lesser-known actinide compounds. Read More »

Figure NMGC ALCC m2835

New Methodology for Simulating Nanoporous Materials

Researchers at the Nanoporous Materials Genome Center (NMGC) at the University of Minnesota have developed new molecular simulation methodology that allows for the highly accurate computation of material properties for a fraction of the computational cost. This new methodology can calculate the adsorption energies of small molecules in nanoporous materials such as zeolites and metal-organic frameworks (MOFs). Thanks to large benchmarking simulations run on NERSC supercomputers, the team was able to validate the new methodology for hydrogen adsorption. Read More »

bias

Quantifying Systematic Error in Monte Carlo Simulations

Scientific Achievement Quantifying the potential bias in Monte Carlo eigenvalue simulations due to undersampling (too few particles per fission generation) has been difficult historically because of the computational resources required to obtain reference solutions. Using an ALCC grant on the Cori supercomputer, we obtained finely discretized flux solutions to a small modular reactor (SMR) problem with extremely small statistical error that has allowed us to definitely quantify undersampling… Read More »

Twopanel fig

Magnetic Reconnection: A bridge to Plasma Kinetic Scales

Researchers from Los Alamos National Laboratory (LANL) used Cori to show that magnetic reconnection in a collisional plasma current sheet generates electric forces that overcome the collisional friction, leading to the spontaneous formation of current sheets and magnetic flux-ropes at the kinetic micro-scales. Read More »