Publication date: 15th April 2025
In recent decades, studies on molecular electronics have made significant advances and single molecular transistors have been demonstrated. Such investigations, however, have not directly led to actual molecular-scale electronic devices, due to the lack of effective technologies for wiring between molecules. Beyond single molecular transistors, the exploration of device architecture is a central issue in molecular-scale electronics. One of the attractive directions is the realization of neural networks that utilize self-assembled molecular systems.
We focus self-doped water-soluble polyaniline sulfonate (SPAN) exhibiting high conductivity and nanoscale network structure. In our previous work, we found that SPAN ultrathin films show ohmic conduction from 10 K to room temperature. However, SPAN indicates nonlinear I-V characteristics in microscale and humid condition at room temperature. These nonlinearities in SPAN network are useful for a physical reservoir computing (RC) by spoken-digit classification realized with 70 % accuracy [1].
Polyoxometalates (POMs) are generic designation for condensed transition metal oxyanions used for catalysis, electrode and other applications related with electron transfer. Recently, POMs attracted much attention for the molecular devices due to their multiple redox states including pentavalent and hexavalent Mo atoms. The I-V characteristics show strong memristor-type hysteresis with long time constant suggesting charging effect of mixed-valence system. Such phenomena is useful for classification tasks like a MNIST with 90 %.