{"paper_id":"3af9f0bf-795c-471c-8293-a49cf2976d54","body_text":"Morphological and functional complexity of fluidic proteinoid microspheres | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Morphological and functional complexity of fluidic proteinoid microspheres Saksham Sharma, Adnan Mahmud, Andrew Adamatzky, Panagiotis Mougoyannis, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8117715/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Proteinoids are fluidic gels made from poly(amino acids) based polymers that exhibit oscillatory electrical activity. It has been proposed that proteinoids are capable of performing analog computing as their electrical activity can be converted into a series of Boolean gates. The current article focuses on decrypting the morphological and functional complexity of the ensembles of proteinoid microspheres prepared in the laboratory. We identify two different protocols (one with and one without SEM) to prepare and visualize proteinoid microspheres. To quantify the complexity of proteinoid ensembles, we measure nine complexity metrics (to name a few: average degrees $\\textrm{Deg} {av}$, maximum number of independent cycles $u$, average connections per node $\\textrm{Conn} {av}$, resistance $\\textrm{res} {\\textrm{eff}}$, percolation threshold $\\textrm{perc} {\\textrm{t}}$) which shine light on the morphological, functional complexity of the proteinoids, and the information transmission that happens across the undirected graph abstraction of the proteinoid microspheres ensembles. We identify the complexity metrics that can distinguish two different protocols of preparation and also the most dense, complex, and less power consuming proteinoid network among all tested. With this work, we hope to provide a complexity toolkit for hardware designers of analog computers to design their systems with the right set of complexity ingredients guided one-to-one by the protocol chosen at the first place. On a more fundamental note, this study also sets forth the need to treat gels, microspheres, and fluidic systems as fundamentally proto-cognitive computational in nature, rather than continuum mechanical, a perspective emerging out from recent program by Tao to treat fluids as potentially Turing-complete and thus, programmable. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-8117715\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":560245227,\"identity\":\"18209609-8218-4805-adcb-d751cca879aa\",\"order_by\":0,\"name\":\"Saksham 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We identify the complexity metrics that can distinguish two different protocols of preparation and also the most dense, complex, and less power consuming proteinoid network among all tested. With this work, we hope to provide a complexity toolkit for hardware designers of analog computers to design their systems with the right set of complexity ingredients guided one-to-one by the protocol chosen at the first place. 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