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Data for 3D Printed Organisms Enabled by Aspiration-Assisted Adaptive Strategies

Dataset

Description

Devising an approach to deterministically position organisms could impact various fields such as bioimaging, cybernetics, cryopreservation, and organism-integrated devices. This requires continuously assessing the locations of randomly distributed organisms to collect and transfer them to target spaces without harm. Here we developed an aspiration-assisted adaptive printing system that tracks, harvests, and relocates living and moving organisms on target spaces via a pick-and-place mechanism that continuously adapts to updated visual and spatial information about the organisms and target spaces. These adaptive printing strategies successfully positioned a single static organism, multiple organisms in droplets, and a single moving organism on target spaces. Their capabilities were exemplified by printing vitrification-ready organisms in cryoprotectant droplets, sorting live organisms from dead ones, positioning organisms on curved surfaces, organizing organism-powered displays, and integrating organisms with materials and devices in customizable shapes. These printing strategies could ultimately lead to autonomous biomanufacturing methods to evaluate and assemble organisms for a variety of single and multi-organism-based applications.

This data set includes the supporting data for the article, 3D Printed Organisms Enabled by Aspiration-Assisted Adaptive Strategies. Images may be viewed with Origin Viewer (https://www.originlab.com/viewer), an open software for viewing the OPJU files.
Date made availableJun 17 2024
PublisherData Repository for the University of Minnesota

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