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| Main Authors: | , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2404.17115 |
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| _version_ | 1866910424336695296 |
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| author | Bearden, Samuel Abramyan, Tigran M. Gil, Dmitry Johnson, Jessica Murashko, Anton Makaev, Sergei Mai, David Baranchikov, Alexander Ivanov, Vladimir Reukov, Vladimir Zhang, Guigen |
| author_facet | Bearden, Samuel Abramyan, Tigran M. Gil, Dmitry Johnson, Jessica Murashko, Anton Makaev, Sergei Mai, David Baranchikov, Alexander Ivanov, Vladimir Reukov, Vladimir Zhang, Guigen |
| contents | The movement of small particles and molecules through membranes is widespread and has far-reaching implications. Consequently, the development of mathematical models is essential for understanding these processes on a micro level, leading to deeper insights. In this endeavour, we suggested a model based on a set of empirical equations to predict the transport of substances through a solid-state nanopore and the associated signals generated during their translocation. This model establishes analytical relationships between the ionic current and electrical double-layer potential observed during ana-lyte translocation and their size, charge, and mobility in an electrolyte solution. This framework allows for rapid interpretation and prediction of the nanopore system's behaviour and provides a means for quantitatively determining the physical properties of molecular analytes. To illustrate the analyt-ical capability of this model, ceria nanoparticles were investigated while undergoing oxidation or reduction within an original nanopore device. The re-sults obtained were found to be in good agreement with predictions from physicochemical methods. This developed approach and model possess transfer-able utility to various porous materials, thereby expediting research efforts in membrane characterization and the advancement of nano- and ultrafiltra-tion or electrodialysis technologies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_17115 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Resolving the size and charge of small particles: a predictive model of nanopore mechanics Bearden, Samuel Abramyan, Tigran M. Gil, Dmitry Johnson, Jessica Murashko, Anton Makaev, Sergei Mai, David Baranchikov, Alexander Ivanov, Vladimir Reukov, Vladimir Zhang, Guigen Chemical Physics Atomic Physics The movement of small particles and molecules through membranes is widespread and has far-reaching implications. Consequently, the development of mathematical models is essential for understanding these processes on a micro level, leading to deeper insights. In this endeavour, we suggested a model based on a set of empirical equations to predict the transport of substances through a solid-state nanopore and the associated signals generated during their translocation. This model establishes analytical relationships between the ionic current and electrical double-layer potential observed during ana-lyte translocation and their size, charge, and mobility in an electrolyte solution. This framework allows for rapid interpretation and prediction of the nanopore system's behaviour and provides a means for quantitatively determining the physical properties of molecular analytes. To illustrate the analyt-ical capability of this model, ceria nanoparticles were investigated while undergoing oxidation or reduction within an original nanopore device. The re-sults obtained were found to be in good agreement with predictions from physicochemical methods. This developed approach and model possess transfer-able utility to various porous materials, thereby expediting research efforts in membrane characterization and the advancement of nano- and ultrafiltra-tion or electrodialysis technologies. |
| title | Resolving the size and charge of small particles: a predictive model of nanopore mechanics |
| topic | Chemical Physics Atomic Physics |
| url | https://arxiv.org/abs/2404.17115 |