Computer Vision Helps Experimentally Monitor Mixing Effects in Deep Eutectic Solvents [machine-readable supporting information]
收藏DataCite Commons2025-08-21 更新2025-09-08 收录
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https://figshare.com/articles/dataset/Computer_Vision_Helps_Experimentally_Monitor_Mixing_Effects_in_Deep_Eutectic_Solvents_machine-readable_supporting_information_/29279894/1
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Machine-readable data outputs from results discussed in the paper. <br>Paper abstract: Deep eutectic solvents (DESs) offer promising sustainable alternatives to petroleum-derived solvents, yet their high viscosities present significant mixing challenges that can impact synthetic outcomes. Here, we demonstrate the application of computer vision as a quantitative, non-contact tool for monitoring and optimizing mixing in DESs. Using Kineticolor video analysis software, we tracked mixing dynamics across three model DES formulations (ChCl/EG, ChCl/G, ChCl/U) under varying temperatures and ves-sel geometries. Our results reveal that mixing completion times span from seconds (for MeOH) to over 60 minutes (for a viscous DES), with temperature elevation from 25 to 60 ◦C reducing mixing times by up to 10-fold. Computational fluid dynamics (CFD) simulations validate experimental observations, showing severe flow field restriction in narrow vessel geometries with highly viscous DES formulations. We demonstrate the practical implications and value of understanding these mixing phenomena through sodium borohydride-mediated aldehyde reduction. This work demonstrates computer vision and video analysis as an essential method for bridging the gap between sustainability goals and practical synthetic implementation when developing methodologies using DES solvents.
提供机构:
figshare
创建时间:
2025-06-12



