Autonomous closed-loop exploration of composition-spread films for the anomalous Hall effect

Abstract Autonomous high-throughput combinatorial experimentation is a key approach for accelerating materials discovery. However, achieving a fully closed-loop system remains a challenge due to the lack of effective optimization strategies for combinatorial experimentation. Here, we developed a Bayesian optimization method specifically designed for composition-spread films, enabling the selection of promising composition-spread films and identifying which elements should be compositionally graded. Using this approach, we demonstrated an autonomous closed-loop exploration of composition-spread films to enhance the anomalous Hall effect (AHE). Our method optimized the composition of a five-element alloy system consisting of three 3 d ferromagnetic elements of Fe, Co, and Ni and two 5 d heavy elements from Ta, W, or Ir to maximize the AHE. Through our autonomous exploration, we achieved a maximum anomalous Hall resistivity of 10.9 µΩ cm in Fe 44.9 Co 27.9 Ni 12.1 Ta 3.3 Ir 11.7 amorphous thin film on thermally oxidized Si substrates deposited at room temperature.