(ORNL: Oak Ridge, TN) -- Researchers at Oak Ridge National Laboratory use specialized tools to study materials at the atomic scale and analyze defects at the materials’ surface. Results of their research help to better understand these materials used for advanced electronics, enabling innovative data storage and computation methods.

The team modified a commercial atomic force microscope with artificial intelligence to precisely assemble and detect patterns in bismuth ferrite. This method avoids invasive electrode deposition, which complicates the process and restricts how small the structures can be.

“With AI, we can use the atomic force microscopy tip to align the electric polarization at the nanoscale, so we can write, read, and erase these patterns—known as topological structures—on demand,” says ORNL’s Marti Checa, the study’s leader.

Published in ACS Nano, this proof of concept highlights how multistate information manipulation boosts information storage potential. Building on ORNL’s work in nanoscale materials, this research aligns with ongoing innovations enhancing memory technologies.