SmartTrap: Automated Precision Experiments with Optical Tweezers
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arXiv
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| Main Authors: | , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866910932987281408 |
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| author | Selin, Martin Ciarlo, Antonio Pesce, Giuseppe Bengtsson, Lars Camunas-Soler, Joan Rajan, Vinoth Sundar Westerlund, Fredrik Wilhelmsson, L. Marcus Pastor, Isabel Ritort, Felix Smith, Steven B. Bustamante, Carlos Volpe, Giovanni |
| author_facet | Selin, Martin Ciarlo, Antonio Pesce, Giuseppe Bengtsson, Lars Camunas-Soler, Joan Rajan, Vinoth Sundar Westerlund, Fredrik Wilhelmsson, L. Marcus Pastor, Isabel Ritort, Felix Smith, Steven B. Bustamante, Carlos Volpe, Giovanni |
| contents | There is a trend in research towards more automation using smart systems powered by artificial
intelligence. While experiments are often challenging to automate, they can greatly benefit from
automation by reducing labor and increasing reproducibility. For example, optical tweezers are
widely employed in single-molecule biophysics, cell biomechanics, and soft matter physics, but they
still require a human operator, resulting in low throughput and limited repeatability. Here, we
present a smart optical tweezers platform, which we name SmartTrap, capable of performing complex
experiments completely autonomously. SmartTrap integrates real-time 3D particle tracking using
deep learning, custom electronics for precise feedback control, and a microfluidic setup for particle
handling. We demonstrate the ability of SmartTrap to operate continuously, acquiring high-precision
data over extended periods of time, through a series of experiments. By bridging the gap between
manual experimentation and autonomous operation, SmartTrap establishes a robust and open source
framework for the next generation of optical tweezers research, capable of performing large-scale
studies in single-molecule biophysics, cell mechanics, and colloidal science with reduced experimental
overhead and operator bias. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_05290 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | SmartTrap: Automated Precision Experiments with Optical Tweezers Selin, Martin Ciarlo, Antonio Pesce, Giuseppe Bengtsson, Lars Camunas-Soler, Joan Rajan, Vinoth Sundar Westerlund, Fredrik Wilhelmsson, L. Marcus Pastor, Isabel Ritort, Felix Smith, Steven B. Bustamante, Carlos Volpe, Giovanni Biological Physics Soft Condensed Matter Optics There is a trend in research towards more automation using smart systems powered by artificial intelligence. While experiments are often challenging to automate, they can greatly benefit from automation by reducing labor and increasing reproducibility. For example, optical tweezers are widely employed in single-molecule biophysics, cell biomechanics, and soft matter physics, but they still require a human operator, resulting in low throughput and limited repeatability. Here, we present a smart optical tweezers platform, which we name SmartTrap, capable of performing complex experiments completely autonomously. SmartTrap integrates real-time 3D particle tracking using deep learning, custom electronics for precise feedback control, and a microfluidic setup for particle handling. We demonstrate the ability of SmartTrap to operate continuously, acquiring high-precision data over extended periods of time, through a series of experiments. By bridging the gap between manual experimentation and autonomous operation, SmartTrap establishes a robust and open source framework for the next generation of optical tweezers research, capable of performing large-scale studies in single-molecule biophysics, cell mechanics, and colloidal science with reduced experimental overhead and operator bias. |
| title | SmartTrap: Automated Precision Experiments with Optical Tweezers |
| topic | Biological Physics Soft Condensed Matter Optics |
| url | https://arxiv.org/abs/2505.05290 |