Even with decades of unprecedented development in computational power, the human brain still holds many advantages over modern computing technologies. Our brains are extremely efficient for many cognitive tasks and do not separate memory and computing, unlike standard computer chips.
In the last decade, the new paradigm of neuromorphic computing has emerged, inspired by neural networks of the brain and based on energy-efficient hardware for information processing.
To create devices that mimic what occurs in our brains’ neurons and synapses, researchers need to overcome a fundamental molecular engineering challenge: how to design devices that exhibit controllable and energy-efficient transition between different resistive states triggered by incoming stimuli.
In a recent study, scientists at the Pritzker School of Molecular Engineering (PME) at the University of Chicago were able to predict design rules for such devices.
Published November 10 in npj Computational Materials, the study predicted new ways of engineering and triggering changes in electronic properties in several classes of transition metal oxides, which could be used to form the basis of neuromorphic computing architectures.
“We used quantum mechanical calculations to unravel the mechanism of the transition, highlighting exactly how it happens at the atomistic scale,” said Giulia Galli, Liew Family Professor at Pritzker Molecular Engineering, professor of chemistry, and co-author of the study. “We further devised a model to predict how to trigger the transition, showing good agreement with available measurements.”
The impact of defects on electronic properties
The researchers investigated oxide materials that exhibit a change of electronic properties from a metal, which conducts electricity, to an insulator, which does not allow electricity to pass through, with various concentrations of defects. Defects can be missing atoms or some impurities that substitute for the atoms present in a perfect crystal.
To understand how defects change the state of the material from a metal to an insulator, the authors calculated the electronic structure at different defect concentrations using methods based on quantum mechanics.