The fluidic memristor as a collective phenomenon in elastohydrodynamic networks
Abstract Fluid flow networks are ubiquitous and can be found in a broad range of contexts, from human-made systems such as water supply networks to living systems like animal and plant vasculature. In many cases, the elements forming these networks exhibit a highly non-linear pressure-flow relations...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-04-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-47110-0 |
| _version_ | 1797209233400266752 |
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| author | Alejandro Martínez-Calvo Matthew D. Biviano Anneline H. Christensen Eleni Katifori Kaare H. Jensen Miguel Ruiz-García |
| author_facet | Alejandro Martínez-Calvo Matthew D. Biviano Anneline H. Christensen Eleni Katifori Kaare H. Jensen Miguel Ruiz-García |
| author_sort | Alejandro Martínez-Calvo |
| collection | DOAJ |
| description | Abstract Fluid flow networks are ubiquitous and can be found in a broad range of contexts, from human-made systems such as water supply networks to living systems like animal and plant vasculature. In many cases, the elements forming these networks exhibit a highly non-linear pressure-flow relationship. Although we understand how these elements work individually, their collective behavior remains poorly understood. In this work, we combine experiments, theory, and numerical simulations to understand the main mechanisms underlying the collective behavior of soft flow networks with elements that exhibit negative differential resistance. Strikingly, our theoretical analysis and experiments reveal that a minimal network of nonlinear resistors, which we have termed a ‘fluidic memristor’, displays history-dependent resistance. This new class of element can be understood as a collection of hysteresis loops that allows this fluidic system to store information, and it can be directly used as a tunable resistor in fluidic setups. Our results provide insights that can inform other applications of fluid flow networks in soft materials science, biomedical settings, and soft robotics, and may also motivate new understanding of the flow networks involved in animal and plant physiology. |
| first_indexed | 2024-04-24T09:51:27Z |
| format | Article |
| id | doaj.art-ca6ff22a0e3f4d0ca4442bfbbb1c4ff6 |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-04-24T09:51:27Z |
| publishDate | 2024-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-ca6ff22a0e3f4d0ca4442bfbbb1c4ff62024-04-14T11:21:36ZengNature PortfolioNature Communications2041-17232024-04-0115111110.1038/s41467-024-47110-0The fluidic memristor as a collective phenomenon in elastohydrodynamic networksAlejandro Martínez-Calvo0Matthew D. Biviano1Anneline H. Christensen2Eleni Katifori3Kaare H. Jensen4Miguel Ruiz-García5Princeton Center for Theoretical Science, Princeton UniversityDepartment of Physics, Technical University of DenmarkDepartment of Physics, Technical University of DenmarkDepartment of Physics and Astronomy, University of PennsylvaniaDepartment of Physics, Technical University of DenmarkDepartamento de Estructura de la Materia, Física Térmica y Electrónica, Universidad Complutense MadridAbstract Fluid flow networks are ubiquitous and can be found in a broad range of contexts, from human-made systems such as water supply networks to living systems like animal and plant vasculature. In many cases, the elements forming these networks exhibit a highly non-linear pressure-flow relationship. Although we understand how these elements work individually, their collective behavior remains poorly understood. In this work, we combine experiments, theory, and numerical simulations to understand the main mechanisms underlying the collective behavior of soft flow networks with elements that exhibit negative differential resistance. Strikingly, our theoretical analysis and experiments reveal that a minimal network of nonlinear resistors, which we have termed a ‘fluidic memristor’, displays history-dependent resistance. This new class of element can be understood as a collection of hysteresis loops that allows this fluidic system to store information, and it can be directly used as a tunable resistor in fluidic setups. Our results provide insights that can inform other applications of fluid flow networks in soft materials science, biomedical settings, and soft robotics, and may also motivate new understanding of the flow networks involved in animal and plant physiology.https://doi.org/10.1038/s41467-024-47110-0 |
| spellingShingle | Alejandro Martínez-Calvo Matthew D. Biviano Anneline H. Christensen Eleni Katifori Kaare H. Jensen Miguel Ruiz-García The fluidic memristor as a collective phenomenon in elastohydrodynamic networks Nature Communications |
| title | The fluidic memristor as a collective phenomenon in elastohydrodynamic networks |
| title_full | The fluidic memristor as a collective phenomenon in elastohydrodynamic networks |
| title_fullStr | The fluidic memristor as a collective phenomenon in elastohydrodynamic networks |
| title_full_unstemmed | The fluidic memristor as a collective phenomenon in elastohydrodynamic networks |
| title_short | The fluidic memristor as a collective phenomenon in elastohydrodynamic networks |
| title_sort | fluidic memristor as a collective phenomenon in elastohydrodynamic networks |
| url | https://doi.org/10.1038/s41467-024-47110-0 |
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