Electrical properties of proteinoids for unconventional computing architectures

Mougkogiannis, Panagiotis; Adamatzky, Andrew

Abstract

Proteinoids are peptide-like molecules that arise from the combination of amino acids in pre-biotic environments. Recent studies have revealed distinctive electrical characteristics of proteinoids, such as the presence of voltage-gated ion channels, electrical switching capabilities, and the ability to modulate conductivity. Proteinoids possess properties that render them highly favourable as fundamental components for unconventional computing architectures inspired by biological systems. This study involved the synthesis of multiple proteinoids and the subsequent characterisation of their electrical properties through the use of impedance measurements. Proteinoids-based computing logic gates were developed through the integration of proteinoids and electrodes. We developed proteinoid neural networks capable of learning fundamental patterns by adjusting the proteinoid conductivity through training stimuli. Additionally, we have shown that a proteinoid mixture displays rudimentary capabilities for learning and memory. Our findings demonstrate the versatility of proteinoids as nanomaterials that can be utilised in innovative and unconventional computing systems. The utilisation of bio-derived electrical properties and self-assembly of proteinoids has the potential to facilitate the development of environmentally friendly and sustainable neuromorphic or evolutionary computing architectures. Our objective is to improve the complexity and performance of proteinoid computing systems for practical use in the future.

Citation

Mougkogiannis, P., & Adamatzky, A. (2023). Electrical properties of proteinoids for unconventional computing architectures. In NANOARCH '23: Proceedings of the 18th ACM International Symposium on Nanoscale Architectures (1-4). https://doi.org/10.1145/3611315.3633264

• Conference Name: NANOARCH '23: 18th ACM International Symposium on Nanoscale Architectures
• Conference Location: Dresden Germany
• Start Date: Jan 18, 2024
• End Date: Jan 21, 2024
• Acceptance Date: Nov 15, 2023
• Online Publication Date: Jan 25, 2024
• Publication Date: Dec 31, 2023
• Deposit Date: Jan 26, 2024
• Publicly Available Date: Jan 30, 2024
• Publisher: Association for Computing Machinery (ACM)
• Pages: 1-4
• Book Title: NANOARCH '23: Proceedings of the 18th ACM International Symposium on Nanoscale Architectures
• ISBN: 9798400703256
• DOI: https://doi.org/10.1145/3611315.3633264
• Keywords: thermal proteins, proteinoids, microspheres, unconventional computing
• Public URL: https://uwe-repository.worktribe.com/output/11628541
• Publisher URL: https://dl.acm.org/doi/10.1145/3611315.3633264
• Additional Information: Published: 2024-01-25