Prerequisites for creating programmable structures based on stimuli-sensitive hydrophilic polymers

Prerequisites for creating programmable structures based on stimuli-sensitive hydrophilic polymers | 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 Prerequisites for creating programmable structures based on stimuli-sensitive hydrophilic polymers Ibragim Suleimenov, Sherniyaz Kabdushev, Bayana Yermukhambetova, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5280041/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 It has been shown that the neural network properties of systems based on stimuli-sensitive hydrophilic polymers make it possible to raise the question of creating programmable structures based on such materials. It has been shown that the phenomenon of multidimensional hysteresis can occur in systems based on stimulus-sensitive polymers, the behaviour of which significantly depends on more than one thermodynamic variable. In this case, the dependence of the parameters characterising the system's state on the control thermodynamic variables is described by a complex folded surface on which areas corresponding to abrupt phase transitions can be identified. It is shown that the system's state in which multidimensional hysteresis is realised depends not only on the current values of thermodynamic variables but also on the path along which the representing point moves in the space of control parameters. On this basis, it has been proven that analogues of neural networks can be implemented in which information is recorded by submitting the same code sequences to all inputs of the first layer of the network. Physically, this corresponds to the fact that the programming of structures of the type under consideration is carried out using macroscopic influences expressed in the form of changes in thermodynamic variables according to a given law. Simple and illustrative model examples built based on standard stimuli-sensitive polymer systems are considered, proving the possibility of implementing neural networks of this type. stimuli-sensitive hydrophilic polymers neural networks intelligent materials targeting multidimensional hys-teresis phase transitions 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. 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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-5280041","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":368384599,"identity":"7aaacd2a-b62c-46c1-b6ed-3487ab61da20","order_by":0,"name":"Ibragim Suleimenov","email":"","orcid":"","institution":"National Engineering Academy of the Republic of Kazakhstan","correspondingAuthor":false,"prefix":"","firstName":"Ibragim","middleName":"","lastName":"Suleimenov","suffix":""},{"id":368384600,"identity":"716c54ae-eefa-41d2-8f02-a479df6f0dcf","order_by":1,"name":"Sherniyaz Kabdushev","email":"","orcid":"","institution":"National 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hys-teresis, phase transitions","lastPublishedDoi":"10.21203/rs.3.rs-5280041/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5280041/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"It has been shown that the neural network properties of systems based on stimuli-sensitive hydrophilic polymers make it possible to raise the question of creating programmable structures based on such materials. It has been shown that the phenomenon of multidimensional hysteresis can occur in systems based on stimulus-sensitive polymers, the behaviour of which significantly depends on more than one thermodynamic variable. In this case, the dependence of the parameters characterising the system's state on the control thermodynamic variables is described by a complex folded surface on which areas corresponding to abrupt phase transitions can be identified. It is shown that the system's state in which multidimensional hysteresis is realised depends not only on the current values of thermodynamic variables but also on the path along which the representing point moves in the space of control parameters. On this basis, it has been proven that analogues of neural networks can be implemented in which information is recorded by submitting the same code sequences to all inputs of the first layer of the network. Physically, this corresponds to the fact that the programming of structures of the type under consideration is carried out using macroscopic influences expressed in the form of changes in thermodynamic variables according to a given law. 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