When it comes to error sensitivity, quantum computers are huge divas. Virginia Tech physicists devised a technique that draws on hidden quantum geometry to simplify the problem.

A team of researchers led by the University of Pittsburgh demonstrated a programmable superconducting diode at the LaAlO3/KTaO3 (LAO/KTO) interface as the result of usiung conductive atomic force microscope (c-AFM) lithography.

Self-driving laboratories (SDLs) powered by artificial intelligence (AI) are rapidly accelerating materials discovery, but can they also explain their results? Researchers from the Theory Department of the Fritz Haber Insitute, in collaboration with BASF, and BasCat – UniCat BASF JointLab, show that they can. Their new AI-driven strategy works hand-in-hand with SDLs to identify better catalysts while revealing the chemistry behind their performance. The approach was validated on the industrially crucial conversion of propane into propylene.

A Dartmouth study reports a technique for creating detailed landscape maps of what students know based on their performance on short multiple-choice quizzes. The researchers’ mathematical framework could be used to power a new generation of personalized AI tutors that can identify what individual students do and do not understand, then customize feedback to improve learning. The researchers released a public demo where users can construct an interactive map of their knowledge.