Billinge and Gang Featured in BNL's Top-10 Science Successes of 2016

Jan 11 2017 | By BNL Newsroom

APAM faculty members, Simon Billinge, Professor of Materials Science and Engineering and Applied Physics and Applied Mathematics, and Oleg Gang, Professor of Applied Physics and Materials Science and Professor of Chemical Engineering, were featured in Brookhaven National Laboratory's Top-10 Science Successes of 2016. For the full article, please see: https://www.bnl.gov/newsroom/news.php?a=112010

Billinge: Computational Tools Help Unlock Nanostructures, Secrets of the Universe, and Untapped Computing Resources

Computational tools play a role in every area of science at Brookhaven. Two standouts of 2016 include sorting out structures at the nanoscale and a new, efficient way to sift through petabytes of data generated at the Large Hadron Collider (LHC). In the first example, scientists used advanced data analytics to make sense of "fuzzy" data generated by x-rays scattering off clusters of gold nanoparticles. The analysis revealed two unique atomic arrangements of the gold particles—somewhat like the differing arrangements of carbon atoms that result in diamond and graphite. The discovery gives engineers a new material to explore, along with the possibility of finding other "polymorphic" nanomaterials with potentially divergent functions. The second example was a demonstration of a "workload management system" that breaks up complex data analysis jobs and simulations for the LHC's ATLAS and ALICE experiments and "feeds" them into untapped pockets of available supercomputing time—similar to the way tiny pebbles can fill empty spaces between larger rocks in a jar. Mobilizing these previously unusable supercomputing capabilities, valued at millions of dollars per year, could quickly and effectively enable cutting-edge science in many data-intensive fields.

Gang: DNA Shaping Up to be Ideal Framework for Rationally Designed Nanostructures

In a series of papers, Brookhaven scientists working at the Lab's Center for Functional Nanomaterials (CFN) used DNA as a programmable nanoscale building material, driving particles measuring just billionths of a meter to self-assemble into a widevariety of three-dimensional lattice structures. The scaffold-like frames made of DNA can even form interconnecting modules, or hold nanoparticles inside with DNA arms as programmable cages. The scientists verified the frame structures and nanoparticle arrangements using cryo-electron microscopy (a type of microscopy conducted at very low temperatures) at the CFN and Brookhaven's Biology Department, and x-ray scattering at the National Synchrotron Light Source II (NSLS-II). In each case, the external and internal binding properties and shapes of the precisely designed DNA frames control the structure of the resulting assemblies. This gives the scientists a way to engineer different lattices and architectures without having to manipulate the individual particles. The method opens up opportunities for rationally designing nanomaterials with optical, electric, and/or magnetic properties that can be enhanced or optimized by precisely organizing functional components. Some examples include targeted light-absorbing materials that harness solar energy, or magnetic materials that increase information-storage capacity.

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