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.

A team of researchers led by the University of Tokyo Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU, WPI) Project Assistant Professor Elisa Ferreira has shown that a discrepancy in a key cosmic measurement in the early universe originates from a subtle statistical interplay between measurements of the cosmic microwave background (CMB) and baryon acoustic oscillations (BAO).

A new Maths study from the University of Bath in the UK finds that adopting a neutral stance – such as abstaining in a vote – can speed up and stabilise group decision-making. By reducing the pool of active decision-makers, neutrality helps new consensus positions emerge faster.