However, with conventional resistance-variable memory devices widely used as artificial synapses, as the filament grows with varying resistance, the electric field increases, causing a feedback phenomenon, resulting in rapid filament growth. Therefore, it is challenging to implement plasticity while maintaining analog (gradual) resistance variation concerning the filament type.

The Korea Institute of Science and Technology, led by Dr. YeonJoo Jeong's team at the Center for Neuromorphic Engineering, solved the limitations of analog synaptic characteristics, plasticity and information preservation, which are chronic obstacles regarding memristors, neuromorphic semiconductor devices. He announced the development of an artificial synaptic semiconductor device capable of highly reliable neuromorphic computing.

The KIST research team fine-tuned the redox properties of active electrode ions to solve small synaptic plasticity issues hindering the performance of existing neuromorphic semiconductor devices. Furthermore, transition metals were doped and used in the synaptic device, controlling the reduction probability of active electrode ions. The engineers discovered that the high reduction probability of ions is a critical variable in the development of high-performance artificial synaptic devices.

Therefore, a titanium transition metal, having a high ion reduction probability, was introduced by the research team into an existing artificial synaptic device. This maintains the synapse's analog characteristics and the device plasticity at the synapse of the biological brain, approximately five times the difference between high and low resistances. Furthermore, they developed a high-performance neuromorphic semiconductor that is approximately 50 times more efficient.