Argonne National Laboratory is reimagining the lab spaces and scientific careers of the future by harnessing the power of robotics, artificial intelligence and machine learning in the quest for new knowledge.
To engineer proteins for specific functions, scientists change a protein sequence and experimentally test how that change alters its function. Because there are too many possible amino acid sequence changes to test them all in the laboratory, researchers build computational models that predict protein function based on amino acid sequences. Scientists have now combined multiple machine learning approaches for building a simple predictive model that often works better than established, complex methods.
Bone and mollusk shells are composite systems that combine living cells and inorganic components. This allows them to regenerate and change structure while also being very strong and durable. Borrowing from this amazing complexity, researchers have been exploring a new class of materials called engineered living materials (ELMs).
Researchers developed two new methods to assess and remove error in how scientists measure quantum systems. By reducing quantum “noise” – uncertainty inherent to quantum processes – these new methods improve accuracy and precision.
Lanthanum strontium manganite (LSMO) is a widely applicable material, from magnetic tunnel junctions to solid oxide fuel cells. However, when it gets thin, its behavior changes for the worse. The reason why was not known. Now, using two theoretical methods, a team determined what happens.
How an ion behaves when isolated within an analytical instrument can differ from how it behaves in the environment. Now, Xue-Bin Wang at Pacific Northwest National Laboratory devised a way to bring ions and molecules together in clusters to better discover their properties and predict their behavior.
Shape affects how the particles fit together and, in turn, the resulting material. For the first time, a team observed the self-assembly of nanoparticles with tetrahedral shapes.
This study is the first to confirm dust particles pre-dating the formation of our solar system. Further study of these materials will enable a deeper understanding of the processes that formed and have since altered them.
Future fusion reactors will require materials that can withstand extreme operating conditions, including being bombarded by high-energy neutrons at high temperatures. Scientists recently irradiated titanium diboride (TiB2) in the High Flux Isotope Reactor (HFIR) to better understand the effects of fusion neutrons on performance.