Using computing resources at the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory (Berkeley Lab), researchers at Argonne National Laboratory have succeeded in exploring important materials science questions and demonstrated progress using machine learning to solve difficult search problems. By adapting a machine-learning algorithm from board games such as AlphaGo, the researchers developed force fields for nanoclusters of 54 elements across the periodic table, a dramatic leap toward understanding their unique properties and proof of concept for their search method. The team published its results in Nature Communications in January. Depending on their scale--bulk systems of 100 nanometers versus nanoclusters of less than 100 nanometers--materials can display dramatically different properties, including optical and magnetic properties, discrete energy levels, and enhanced photoluminescence. These properties may lend themselves to new scientific and industry applications, and scientists can learn about them by developing force fields--computational models that estimate the potential energies between atoms in a molecule and between molecules--for each element or compound.

Near the end of the Georgia Senate runoff debate Sunday night, moderators asked Sen. Kelly Loeffler, who was ultimately cleared in her insider trading investigation earlier this year, whether members of Congress should be barred from trading stocks. "What's at stake here, in this election, is the American Dream." Loeffler is trying to grind out a win against Rev. Raphael Warnock more on the strength of QAnon than on that of the suburban women whom Gov. Brian Kemp felt she could appeal to when he appointed her earlier this year to the seat left empty by the retirement of Sen. Johnny Isakson. She has nothing to offer the center, now, other than parodic--which isn't to say "unsuccessful"--efforts to slam her opponent as a radical communist who wants to defund the police. Her debate performance Sunday night was more a mockery of this medium of voter-informing than the legendary train-wreck of a first debate between Donald Trump and Joe Biden in September.