open access

https://hdl.handle.net/2115/97961

Image-Based Machine Learning Using Inkjet-Printed Chemicals: Mixing Ratio Prediction and Metal Ion Detection

英語

2025-08-15

American Chemical Society

Organic letters

27(32)

8841-8845

Inkjet printing of pi-conjugated organic compounds enabled rapid, low-cost generation of training images for the image-based machine learning (ML) prediction of mixing ratios. ML models with mean absolute errors below 4% were achieved within hours, even for dyes with subtle color differences. Changing the printing surface from filter paper to a polypropylene film extended the method to colorless compounds, including isomeric and macrocyclic systems. This approach also enabled spatial mapping of sub-microgram levels of Zn2+ ions using a weakly responsive colorimetric sensor, without the need for a spectrometer. This work demonstrates a simple, versatile strategy for integrating pi-conjugated materials with ML in colorimetric sensing and mixture analysis.

学術雑誌論文

Accepted Manuscript

This document is the Accepted Manuscript version of a Published Work that appeared in final form in Organic Letters, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://pubs.acs.org/articlesonrequest/AOR-9F3R5K4RBKDS4G5SYDQA.

1523-7060