January 2019 – July 2022
Researchers studied Antarctic alga and microalgal communities across the globe, finding that polar algae rely on the nutrient zinc to photosynthesize and thrive. Frigid Antarctic waters harbor high levels of this trace metal, but climate change could shift nutrient concentrations. https://jgi.doe.gov/polar-phytoplankton-need-zinc-to-cope-with-the-cold/
Climate researchers at Berkeley Lab plan to heat soil from a meadow in Marin County to temperatures the region won’t experience for decades. They want to see whether global warming will release more atmosphere-heating carbon from the vast stores now sequestered in the earth. https://ucnrs.org/soil-warming-experiment-to-measure-future-carbon-emissions%EF%BF%BC/
With the help of the ALS, JGI, and JBEI, researchers discovered a bacterial enzyme that synthesizes a novel biopolymer that is biodegradable and may be biocompatible, with potential for applications ranging from medical therapeutics to eco-friendly plastic alternatives. https://als.lbl.gov/bacterial-enzyme-produces-biodegradable-polymer/
A new study by a team of scientists and policy analysts suggests multiple pathways to reduce greenhouse gas emissions by 50% in eight years – but big commitments will need to be made. Energy analyst Nikit Abhyankar explains. https://newscenter.lbl.gov/2022/06/02/emissions-reduction-roadmap/
Some analysts say that the end of Moore’s Law is near, but Patrick Naulleau, the director of Berkeley Lab’s Center for X-Ray Optics (CXRO), says that it could be decades before the modern chip runs out of room for improvement thanks to advances in materials and instrumentation enabled by the CXRO. https://newscenter.lbl.gov/2022/06/03/extreme-uv-light-tiny-microchips/
A rechargeable-battery material was imaged at the atomic scale at both the ALS and Molecular Foundry. From the images, a machine-learning algorithm extracted a fundamental material property relevant to battery failure. The revelations could lead to batteries that last much longer. https://als.lbl.gov/a-machine-learning-approach-to-better-batteries/
Over nearly nine years, the Daya Bay Reactor Neutrino Experiment captured 5.5 million interactions from subatomic particles. Now, the international Daya Bay collaboration has reported the most precise measurement yet for a key parameter for understanding how neutrinos change their “flavor.” https://newscenter.lbl.gov/2022/05/31/physicists-announce-first-results-from-daya-bays-final-dataset/
Using computing resources at the National Energy Research Scientific Computing Center (NERSC) at Berkeley Lab, researchers at Argonne National Laboratory have explored important materials-science questions and demonstrated progress using machine learning to solve difficult search problems. https://cs.lbl.gov/news-media/news/2022/machine-learning-fuels-materials-science-and-search-in-continuous-action-spaces/
In partnership with Berkeley Lab, the City and County of San Francisco have released a pioneering new climate study that will provide more detailed information to help San Francisco adapt to changing climate and the extreme storms it will bring. https://cs.lbl.gov/news-media/news/2022/san-francisco-and-berkeley-lab-team-up-on-pioneering-climate-study/
Researchers at the Advanced Quantum Testbed demonstrated the first three-qubit high-fidelity iToffoli native gate doing so in a single step. This demonstration adds a novel easy-to-implement native three-qubit logic gate for universal quantum computing. https://crd.lbl.gov/news-and-publications/news/2022/quantum-breakthrough-a-high-fidelity-itoffoli-gate