m/q Initiative

The m/q Initiative is revolutionizing the efficacy of mass spectrometry by offering a comprehensive, cohesive, and predictive grasp of the chemistry and physics governing all ions throughout a measurement. This understanding is then leveraged to forecast a quantitative multi-property response. m/q is poised to introduce groundbreaking modeling and analysis techniques that will facilitate molecule identification and quantification via mass spectrometry without the need for reference compounds. Additionally, it will enhance the capacity for measuring specific analytes.


m/q leverages PNNL’s expertise in chemical and biomolecular mass spectrometry, as well as coherent computing and analytics incorporating first principle and data-driven models, to address these challenges.

The utilization of mass spectrometry (MS) for molecular analysis and measurement has experienced remarkable growth in the past two decades. Consequently, MS-based methods have found application in areas such as threat detection, forensic inquiries, and the exploration of biological systems, resulting in numerous innovative insights and a wealth of new knowledge. B ecause of the currently implemented molecular measurement paradigm, the knowledge of a sample obtained from a mass spec measurement is incomplete (up to 50-90% of sample constituents remain unidentified), and this is due to a lack of complete and predictive understanding of the fundamental processes underlying a measurement. O ur comprehension of the fundamental processes underlying molecular MS remains limited, impeding the technique's full potential.

The Pursuit of a Reference-Free Measurement Paradigm

Flowchart of work


The m/q Initiative focuses its research activities through the integration of the following technical areas:

  • Ionization and Matrix Effects – ionization chemistry and ion-molecule interactions
  • Separations and Detection – ion physics and manipulation
  • Molecular Modeling – computational approaches for predicting ion properties
  • Statistics and Machine Learning – analysis tools to fully use and gain a deeper understanding of measurement data.
  • Infrastructure and Equipment – use of PNNL’s supercomputing assets

PNNL is uniquely positioned in the scientific community to lead the next paradigm of mass spectrometry measurement systems.