Research Projects

The growing demand for energy-efficient, brain-inspired computing has exposed fundamental limitations of conventional silicon-based technologies, particularly their reliance on the von Neumann architecture and inability to emulate synaptic plasticity at low power. In contrast, the human brain performs massively parallel computation using ionic and electronic signals with unmatched energy efficiency. Emulating this hybrid signaling is central to the development of neuromorphic hardware, where organic electrochemical transistors (OECTs) based on organic mixed ionic-electronic conductors (OMIECs) have emerged as promising artificial synapses. Among OMIECs, PEDOT:PSS is the most widely studied due to its high conductivity and compatibility with aqueous systems. However, its key limitation lies in short state-retention times, which stem from the rapid diffusion of ions within the polymer matrix, resulting in volatile (short-term) memory behavior. This restricts its utility in long-term memory and learning applications. One potential solution is ion-trapping, wherein mobile ions are selectively localized to stabilize the device's conductance state over time. This proposal aims to test the central hypothesis that crown ethers, macrocyclic compounds with high ion selectivity, can enhance state retention in OMIECs by trapping mobile cations such as K⁺, thereby mimicking long-term memory behavior in organic synaptic transistors. Preliminary data, obtained through collaboration with Prof. Yoeri van de Burgt’s group (TU Eindhoven), confirm that OECTs fabricated using PEDOT:PSS blended with 18-crown-6 exhibit over 90% reduction in current decay rate under both doping and dedoping cycles, demonstrating strong ion-trapping behavior. However, additive-based approaches suffer from phase segregation and long-term instability. Therefore, the project proposes to advance the field through a molecularly engineered OMIEC system, wherein crown ether motifs are covalently integrated into the PEDOT backbone. The project will also explore open-chain and linear chelating architectures to tailor ion selectivity and reduce operating voltages. If successful, this project will deliver a new class of OMIEC materials with built-in ion-trapping functionality, capable of long-term, low-power synaptic emulation. This will represent a major step forward in fundamental understanding of ionic transport in soft semiconductors, and provide a scalable platform for non-volatile neuromorphic memory, bioelectronic interfaces, and AI hardware operating under physiological conditions. The outcomes are aligned with national goals in sustainable electronics through startup integration.