Ferroelectric materials boost data storage potential
- Jan 12
- 1 min read
Researchers at Oak Ridge National Laboratory used 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," said 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.
Reference Autonomous Multistate Nanoencoding Using Combinatorial Ferroelectric Closure Domains in BiFeO₃
Marti Checa, Ruben Millan-Solsona, Yongtao Liu, Bharat Pant, Alexander Puretzky, Ye Cao, Puneet Kaur, Jan-Chi Yang, Liam Collins, Neus Domingo, Kyle P. Kelley, Stephen Jesse, and Rama Vasudevan
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