Reservoir Computing with Colloidal Mixtures of ZnO and Proteinoids
Raphael Fortulan, Noushin Raeisi Kheirabadi, Panagiotis Mougkogiannis,, Alessandro Chiolerio, Andrew Adamatzky

TL;DR
This paper demonstrates experimental liquid computer prototypes using colloids of ZnO nanoparticles and proteinoids, showing their ability to perform various logic functions and paving the way for future hybrid liquid computing devices.
Contribution
It introduces a novel colloidal system combining ZnO and proteinoids for liquid computing, demonstrating their capacity to perform multiple logic functions.
Findings
Successful extraction of 2-, 4-, and 8-bit logic functions
Distinct logic function sets for each material
Complexity of expressions depends on material composition
Abstract
Liquid computers use incompressible fluids for computational processes. Here we present experimental laboratory prototypes of liquid computers using colloids composed of zinc oxide (ZnO) nanoparticles and microspheres containing thermal proteins (proteinoids). The choice of proteinoids is based on their distinctive neuron-like electrical behaviour and their similarity to protocells. In addition, ZnO nanoparticles are chosen for their non-trivial electrical properties. Our research demonstrates the successful extraction of 2-, 4- and 8-bit logic functions in ZnO proteinoid colloids. Our analysis shows that each material has a distinct set of logic functions, and that the complexity of the expressions is directly related to each material present in a mixture. These findings provide a basis for the development of future hybris liquid devices capable of general purpose computing.
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Taxonomy
TopicsNeural Networks and Reservoir Computing · Neural dynamics and brain function · Advanced Memory and Neural Computing
