Controlling curvature of self-assembling surfaces via patchy particle design
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866910839209984000 |
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| author | Gnidovec, Andraž Čopar, Simon |
| author_facet | Gnidovec, Andraž Čopar, Simon |
| contents | Curved structures in soft matter and biological systems commonly emerge as a result of self-assembly processes where building blocks aggregate in a controlled manner, giving rise to specific system structure and properties. Learning how to precisely tune the curved geometry of these assemblies can in turn elucidate new ways of controlling their functionality. We discuss how one can target self-assembly into surfaces with specified Gaussian curvature in a one-component system of model patchy particles. Given the vast design space of potential patch distributions, we address the problem using an inverse design approach based on automatic differentiation and develop an optimization scheme which solves the exploding gradients problem that arises when we differentiate through long molecular dynamics trajectories. We discuss the model requirements for successful optimization, determine the significant hyperparameter choices influencing algorithm performance and, finally, we demonstrate that we can consistently design patch patterns for assembly into clusters with different target curvature radii. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_15668 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Controlling curvature of self-assembling surfaces via patchy particle design Gnidovec, Andraž Čopar, Simon Soft Condensed Matter Computational Physics Curved structures in soft matter and biological systems commonly emerge as a result of self-assembly processes where building blocks aggregate in a controlled manner, giving rise to specific system structure and properties. Learning how to precisely tune the curved geometry of these assemblies can in turn elucidate new ways of controlling their functionality. We discuss how one can target self-assembly into surfaces with specified Gaussian curvature in a one-component system of model patchy particles. Given the vast design space of potential patch distributions, we address the problem using an inverse design approach based on automatic differentiation and develop an optimization scheme which solves the exploding gradients problem that arises when we differentiate through long molecular dynamics trajectories. We discuss the model requirements for successful optimization, determine the significant hyperparameter choices influencing algorithm performance and, finally, we demonstrate that we can consistently design patch patterns for assembly into clusters with different target curvature radii. |
| title | Controlling curvature of self-assembling surfaces via patchy particle design |
| topic | Soft Condensed Matter Computational Physics |
| url | https://arxiv.org/abs/2502.15668 |