Supramolecular Control of Ionic Retention in Electrolyte-Gated Synaptic Transistors
Electrolyte-gated transistors with ion-trapping layers offer a promising platform for artificial synapses in neuromorphic computing, yet molecular mechanisms governing ionic retention remain poorly understood. Here, we present a supramolecular approach to modulate ion retention by incorporating a crown ether derivative-based polymer network as an ion-trapping layer on top of a semiconducting monolayer. We show that the balance between ion–host binding and ion–solvent interactions dictates the kinetics of ion capture and release, which in turn controls the memory characteristics of the device. By varying the solvent dielectric constant, we tune the ionic retention time from nearly permanent trapping to rapid relaxation. Intermediate solvent polarity enables programmable short- and long-term synaptic behaviors, including excitatory postsynaptic current, paired-pulse facilitation, and long-term potentiation and depression. These findings establish a direct link between supramolecular ion recognition and synaptic plasticity and provide a generalizable design strategy for ionic–electronic neuromorphic devices.
Authors
- Ashutosh Garudapalli (ORCID: https://orcid.org/0000-0002-2340-2083)
- Yu Zhong (ORCID: https://orcid.org/0000-0001-8631-2213)
- Aoyan Liang (ORCID: https://orcid.org/0000-0001-5100-6232)
- Kaiyang Wang (ORCID: https://orcid.org/0000-0002-1529-0958)
- Satya Butler (ORCID: https://orcid.org/0009-0005-7782-5443)
- Haolei Zhou
- Jingjie Yeo (ORCID: https://orcid.org/0000-0002-6462-7422)
- Ce Liang (ORCID: https://orcid.org/0000-0001-8085-1558)
- Saien Xie (ORCID: https://orcid.org/0000-0002-1723-8598)
- Honghu Zhang (ORCID: https://orcid.org/0000-0003-1784-7825)
- Qiyi Fang (ORCID: https://orcid.org/0000-0001-8435-636X)
- Jie Xu (ORCID: https://orcid.org/0000-0002-8591-8894)
- Jinpeng Tian (ORCID: https://orcid.org/0009-0008-0112-3033)
- Xinyi Ren (ORCID: https://orcid.org/0009-0003-8514-5988)
- Kaushik Chivukula (ORCID: https://orcid.org/0000-0002-0440-9458)
Institutions
- Brookhaven National Laboratory (US)
- Princeton University (US)
- Smith College (US)
- Cornell University (US)
- Smith Family (AU)
- University of Chicago (US)
- Sibley Memorial Hospital (US)
Publication Details
- Journal
- ACS Materials Letters
- Published
- 2025-12-03
- DOI
- https://doi.org/10.1021/acsmaterialslett.5c01336
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00