Polymer sequencing via unsupervised learning of pyrolysis-mass spectra

22 August 2022, Version 2
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

A sequence—an arrangement of monomers—dominates polymer properties, as best exemplified by proteins; however, an efficient sequencing method for synthetic polymers has not been established yet. Herein, we propose a polymer sequencer based on mass spectrometry of pyrolyzed oligomeric fragments. By interpreting an observed fragment pattern as one generated from a mixture of sequence-defined copolymers, sequencing can be simplified to compositional analysis. Our key development is a reference-free quantitative mass spectrometry. The reference spectra of the hardly synthesizable sequence-defined copolymers were not actually measured but virtually inferred via unsupervised learning of the spectral dataset of easily synthesizable random copolymers. The polymer sequencer quantitatively evaluates complex sequence distribution in versatile multi-monomer systems, which would allow sequence–property correlation studies and practical sequence-controlled polymerization.

Keywords

machine learning
quantitative mass spectrometry
pyrolysis mass spectrometry
sequencing
vinyl copolymer
sequence controlled polymerization
Non-negative matrix factorization

Supplementary materials

Title
Description
Actions
Title
Supplementary Materials
Description
Materials and methods, supplementary figures and supplementary tables
Actions
Title
Data_S1_to_S5
Description
Formatted spectra used in this study. If unformatted original spectra in CDF files are necessary, please contact us.
Actions

Comments

Comments are not moderated before they are posted, but they can be removed by the site moderators if they are found to be in contravention of our Commenting Policy [opens in a new tab] - please read this policy before you post. Comments should be used for scholarly discussion of the content in question. You can find more information about how to use the commenting feature here [opens in a new tab] .
This site is protected by reCAPTCHA and the Google Privacy Policy [opens in a new tab] and Terms of Service [opens in a new tab] apply.