Adam Bigaj, Dr. Marcello A. Budroni, Prof. Laurence Rongy
Self-organizing behaviors have long been studied in complex chemical systems involving a nonlinear chemical feedback (e. g. the Belousov-Zhabotinsky and Bray-Liebhafsky reactions). Here we explore the emergence of oscillatory dynamics by coupling simpler chemical processes, in the form of a bimolecular reaction, and natural convection (i. e. flows induced by changes in density and surface tension occurring during the reaction). We study and classify different possible scenarios based on the interplay between chemically-driven Marangoni- (surface tension induced) and buoyancy-driven (density induced) flows. This coupling can either be antagonistic, whereby both generated flows are opposing (e. g. a reaction increasing the surface tension and decreasing the density), or cooperative if both flows act in the same direction (e. g. a reaction increasing both surface tension and density). We further investigate the impact of these oscillations on the mixing and reaction rate.
{"title":"Influence of Chemo-Hydrodynamical Oscillations in Bimolecular Reactions on Mixing","authors":"Adam Bigaj, Dr. Marcello A. Budroni, Prof. Laurence Rongy","doi":"10.1002/syst.202400099","DOIUrl":"10.1002/syst.202400099","url":null,"abstract":"<p>Self-organizing behaviors have long been studied in complex chemical systems involving a nonlinear chemical feedback (<i>e. g</i>. the Belousov-Zhabotinsky and Bray-Liebhafsky reactions). Here we explore the emergence of oscillatory dynamics by coupling simpler chemical processes, in the form of a bimolecular reaction, and natural convection (<i>i. e</i>. flows induced by changes in density and surface tension occurring during the reaction). We study and classify different possible scenarios based on the interplay between chemically-driven Marangoni- (surface tension induced) and buoyancy-driven (density induced) flows. This coupling can either be antagonistic, whereby both generated flows are opposing (<i>e. g</i>. a reaction increasing the surface tension and decreasing the density), or cooperative if both flows act in the same direction (<i>e. g</i>. a reaction increasing both surface tension and density). We further investigate the impact of these oscillations on the mixing and reaction rate.</p>","PeriodicalId":72566,"journal":{"name":"ChemSystemsChem","volume":"7 4","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144647812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Research across various disciplines shows the benefits of learning and memory for gaining functionality and improving performance. It is increasingly clear that learning and memory can be found in both physical and virtual systems, from intelligent life forms to machines, simple organisms, and even designed chemical systems. We are interested in understanding to what extent physical embodiments of these processes can be synthesized and engineered from the bottom up by using molecular components. In this perspective, we raise and attempt to answer conceptual questions about supramolecular systems as the smallest units capable of learning. We define learning as a process where a complex system of interacting components modifies itself in response to an applied stress or stimulus, resulting in structural changes and information gain. We highlight the potential of systems chemistry and molecular networks to design systems that meet this definition by encoding, decoding, and storing information as memory within the system′s composition. Understanding the physical basis of molecular memory and learning could inform the development of materials and chemical systems that autonomously acquire new properties in response to their environment. This could also provide insights for next-generation computing and physical, rather than virtual, learning systems.
{"title":"Can Molecular Systems Learn?","authors":"Kübra Kaygisiz, Rein V. Ulijn","doi":"10.1002/syst.202400075","DOIUrl":"10.1002/syst.202400075","url":null,"abstract":"<p>Research across various disciplines shows the benefits of learning and memory for gaining functionality and improving performance. It is increasingly clear that learning and memory can be found in both physical and virtual systems, from intelligent life forms to machines, simple organisms, and even designed chemical systems. We are interested in understanding to what extent physical embodiments of these processes can be synthesized and engineered from the bottom up by using molecular components. In this perspective, we raise and attempt to answer conceptual questions about supramolecular systems as the smallest units capable of learning. We define learning as a process where a complex system of interacting components modifies itself in response to an applied stress or stimulus, resulting in structural changes and information gain. We highlight the potential of systems chemistry and molecular networks to design systems that meet this definition by encoding, decoding, and storing information as memory within the system′s composition. Understanding the physical basis of molecular memory and learning could inform the development of materials and chemical systems that autonomously acquire new properties in response to their environment. This could also provide insights for next-generation computing and physical, rather than virtual, learning systems.</p>","PeriodicalId":72566,"journal":{"name":"ChemSystemsChem","volume":"7 2","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Spatiotemporal patterns, such as spiral waves, can be formed on membranes and are coupled with membrane deformation. The membrane can exhibit no-thermal fluctuations owing to active protein interactions. The Review by Hiroshi Noguchi describes the latest developments in theoretical analyses and simulations on nonequilibrium dynamics of biomembranes under active protein interactions and chemical reactions.