Interpretable Machine Learning-based Automated HPLC/MS ² Platform using Ion-Molecule Reactions for the Identification of Functionalities in Analytes

Armen G. Beck; Ruth Anyaeche; Prageeth Wijewardhane; Sanjay Iyer; Yue Fu; Judy Kuan‐Yu Liu; Jifa Zhang; Kawthar Alzarieni; Erlu Feng; Ryan T. Hilger; Christopher J. Welch; Hilkka I. Kenttämaa; Gaurav Chopra

doi:10.1039/d5sc07324c

January 1, 2026Chemical ScienceOpen Access

Interpretable Machine Learning-based Automated HPLC/MS ² Platform using Ion-Molecule Reactions for the Identification of Functionalities in Analytes

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Key Points

This research aims to improve the identification of unknown compounds in complex mixtures using an automated machine learning platform.
Developed an interpretable machine learning-based automated platform using HPLC and MS2 techniques.
Applied ion-molecule reactions to enhance the identification process.
Evaluated the platform's effectiveness compared to traditional methods.
Achieved a significant reduction in identification time compared to conventional techniques.
Demonstrated improved accuracy in identifying functionalities in complex mixtures.
Reduced manual intervention requirement, streamlining the analytical process.

Implication

Identifies functionalities in analytes using machine learning and HPLC/MS2, suggesting improved analytical efficiency.

Abstract

Identification of unknown compounds in complex mixtures is a time-consuming and challenging problem in several areas of chemistry. High-performance liquid chromatography (HPLC) coupled to tandem mass spectrometry (MS2) based on...

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Cite This Study

Beck et al. (2026) studied this question.

synapsesocial.com/papers/6a2116fad499ed480b16fca3 https://doi.org/10.1039/d5sc07324c

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Interpretable Machine Learning-based Automated HPLC/MS ² Platform using Ion-Molecule Reactions for the Identification of Functionalities in Analytes

Key Points

Implication

Abstract

Discussion

Cite This Study

Interpretable Machine Learning-based Automated HPLC/MS ² Platform using Ion-Molecule Reactions for the Identification of Functionalities in Analytes

Key Points

Implication

Abstract

Discussion

Cite This Study

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