Journal article
Geopolymer memristor-based physical reservoir computing for digit recognition
AIP advances, Vol.15(10), 105005
10/2025
DOI: 10.1063/5.0285689
Abstract
Memristors are solid-state devices that share many information processing capabilities of biological synapses, allowing brain-inspired memory and computing. Among memristor-based neuromorphic computing systems, physical reservoir computing has gained significant attention in recent years due to its low computational cost and suitability in handling multiple tasks by leveraging the short-term memory property of artificial synapses. In our previous studies, we developed geopolymer (GP)-based low-cost memristors and demonstrated their activity-dependent behaviors, such as short-term plasticity behaviors [including Paired-Pulse Facilitation (PPF) and Paired-Pulse Depression (PPD)] and long-term plasticity behaviors [including spike-timing-dependent plasticity and Spike-Rate-Dependent Plasticity (SRDP)]. GPs are a class of inorganic polymers formed by the alkali activation of aluminosilicate precursors. In this study, we present an efficient and low-cost geopolymer-based reservoir computing system capable of recognizing a computer-generated 5 × 5 binary digit set and a handwritten Modified National Institute of Standards and Technology digit dataset with up to an accuracy of 89%, combining both experimental- and simulation-based approaches. The pattern recognition capability of GP memristors suggests their potential application in integrated energy-efficient and real-time structural health monitoring.
Details
- Title: Subtitle
- Geopolymer memristor-based physical reservoir computing for digit recognition
- Creators
- Mahmudul Alam Shakib - University of IowaJoshua J. Maraj - United States Air Force Research LaboratoryZhaolin Gao - University of IowaMaedeh Ahmadipour - Iowa State UniversityReza Montazami - Iowa State UniversityStephen A. Sarles - University of Tennessee at KnoxvilleCaterina Lamuta - University of Iowa
- Resource Type
- Journal article
- Publication Details
- AIP advances, Vol.15(10), 105005
- DOI
- 10.1063/5.0285689
- ISSN
- 2158-3226
- eISSN
- 2158-3226
- Publisher
- AIP Publishing
- Number of pages
- 12
- Grant note
- FA9550-21-1-0416 / Air Force Office of Scientific Research (https://doi.org/10.13039/100000181) W911NF-23-2-0020 / Army Research Office (https://doi.org/10.13039/100000183)
- Language
- English
- Date published
- 10/2025
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Mechanical Engineering
- Record Identifier
- 9984969106802771
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