Skip to main content
National MagLab logo

The MagLab is funded by the National Science Foundation and the State of Florida.

ICR FAIR Data: MagLab Data Enhances Processing of Dissolved Organic Matter Mass Spectra

Published May 15, 2024

Improved mass resolution and signal-to-noise ratio in mass absorption mode mass spectra leads to more assigned chemical formulas within a complex fluid sample.   Reprinted from citation given below. © American Chemical Society.
Improved mass resolution and signal-to-noise ratio in mass absorption mode mass spectra leads to more assigned chemical formulas within a complex fluid sample. (Reprinted from citation given below. © American Chemical Society.)

Combining new data with an existing MagLab dataset, researchers characterized the millions of unique chemicals found in our waterways, including both natural compounds formed by the decomposition of plant matter and man-made toxic pollutants. 

What is the development?

Natural bodies of water contain many millions of unique chemical compounds, including both man-made pollutants and natural compounds created from the decomposition of dead plants, known as dissolved organic matter. MagLab FAIR data users were able to combine their own data with a dataset originally collected at the MagLab in 2022 to better characterize the millions of unique chemicals found in our waterways.


Why is this important?

Characterizing the highly complex mixtures of chemicals found in natural waterways is critical to understanding how man-made pollutants impact our environment. Scientists rely on highly sensitive analytical techniques like Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS) for this purpose. To understand FT-ICR MS data, it must first be processed into a form that can be interpreted by scientists. There are multiple ways to do this, but a technique - developed at the MagLab - called “broadband absorption mode processing” produces higher quality data by lowering the error and improving the signal, allowing many more chemical compounds to be identified. The authors of this study analyzed data collected in their own lab and reanalyzed a dataset made publicly available by MagLab researcher Amy McKenna in 2022 to prove the superiority of this data processing method, paving the way for future dissolved organic matter studies to benefit from these improvements.


Who did the research?

Qing-Long Fu1, Chao Chen2, Yang Liu1, Manabu Fujii3, Pingqing Fu4

1China University of Geosciences, China; 2Guangdong Academy of Sciences, China; 3Tokyo Institute of Technology, Japan; 4Institute of Surface-Earth System Science, School of Earth System Science, Tianjin University, China


Why did they need the MagLab?

The data that were reused for this study were collected under the MagLab’s FAIR data protocols by the MagLab’s 21 tesla FT-ICR MS, the most capable instrument of its kind on the planet. The high quality of the data collected in 2022, along with the MagLab’s FAIR data protocols, allowed the old data to serve as a benchmark for comparison with the author’s newly-collected data, helping them to demonstrate the validity of their result.


Details for scientists


Funding

This research was funded by the following grants: G.S. Boebinger (NSF DMR-2128556); National Natural Science Foundation of China (no. 42107484);


For more information, contact David Butcher.

Tools They Used

Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) (122-G1323522145)

Facilities and instrumentation used: Ion Cyclotron Resonance User Facility, 21 Tesla Fourier Transform Ion Cyclotron Resonance Mass Spectrometer

magnifying glass icon

Search Science Highlights

Search our library of Science Highlights to see notablr research from all of our facilities.


Last modified on 15 May 2024