Scientific American
The U.S. Needs a National Strategic Computing Reserve
One year after supercomputers worked together to fight COVID, it’s time to broaden the partnership to prepare for other crises
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Last spring, as the world was coming to grips with the frightening scale and contagion of the COVID pandemic, scientists started to make rapid progress in understanding the disease. For many discoveries, progress was aided by world-class supercomputers and data systems, and research results advanced with unprecedented efficiency from understanding the structure of the SARS-CoV-2 virus to modeling its spread, from therapeutics to vaccines, from medical response to managing the virus’s impacts.
A team at the NYU Tandon School of Engineering has advanced a critical step in fabrication of Perovskite solar cells: p-type doping of organic hole-transporting materials within the cells. The research, CO2 doping of organic interlayers for perovskite solar cells, appears in Nature.
Scientists used laser and drone technology to measure glaciers’ rocky beds
Researchers measure Castleguard Glacier in the Rocky Mountains of Alberta, Canada.
June 2, 2021
Photos show the hard, rough country some glaciers slide over: rocky domes and bumps in granite, rocky steps and depressions in limestone. The glaciers beds often dwarf the researchers and their instruments.
During research in places exposed by retreating glaciers in the Swiss Alps (Rhone, Schwarzburg and Tsanfleuron glaciers) and the Canadian Rockies (Castleguard Glacier), four glaciologists used laser and drone technology to precisely measure the glaciers rocky beds and record their contours.
The scientists then turned their measurements into high-resolution digital models of the glacier beds. They worked with subunits of the models to study how glaciers slide along bedrock bases.
Published: June 1, 2021
Scientists have begun the search for extraterrestrial life in the Solar System in earnest, but such life may be subtly or profoundly different from Earth-life, and methods based on detecting particular molecules as biosignatures may not apply to life with a different evolutionary history. A new study by a joint Japan/US-based team, led by researchers at the Earth-Life Science Institute (ELSI) at the Tokyo Institute of Technology, has developed a machine learning technique which assesses complex organic mixtures using mass spectrometry to reliably classify them as biological or abiological.
Figure 1. It is not life as we know or understand it.