Supporting Research into Biochar Stability Revealed by FTIR and Machine Learning

Researchers who use Isolab Scientific for sample analysis include commercial and academic organisations and institutions.

MD Mark O-Connor and his team enjoy the variety of clients: “It’s always satisfying to see the lab credited in academic papers published online.”

One such recent paper, published in April this year by Monica A. McCall, Jonathan S. Watson, Jonathan S. W. Tan and Mark A. Sephton explores Biochar Stability Revealed by FTIR and Machine Learning. The abstract reads as follows:

“Biochar is a carbon-rich and environmentally recalcitrant material, with strong potential for climate change mitigation. There is a need for rapid and accessible estimations of biochar stability, the resistance to biotic and abiotic degradation in soil. This study builds on previous work by integrating Fourier-transform infrared spectroscopy (FTIR) data with predictive modeling to estimate standard stability indicators: H:C and O:C molar ratios. Lignocellulosic feedstocks were pyrolyzed at highest treatment temperatures (HTT) ranging from 150–700 °C, and all samples achieved H:C < 0.7 and O:C < 0.4 at HTT of 400 °C and above. Several statistical and machine learning models were developed using FTIR spectra. The random forest (RF) models, which incorporated full data preprocessing, yielded the highest accuracy (R² = 0.96 for both ratios) when tested on an unseen feedstock. Variable importance analysis identified spectral regions linked to aromaticity and inversely correlated to C–O stretches in cellulose and lignin as key predictors. The findings of this study verify that FTIR data can serve as a rapid and accurate tool for estimating biochar stability.”

You can read the paper here. For this research, elemental analysis was conducted by Sercon Analytical Ltd. (as we were known until earlier this year) on a Europa Scientific Elemental Analyzer coupled with Isotope Ratio Mass Spectrometry (EA-IRMS). Twenty percent of samples were duplicated and averaged, and the instrument has a relative standard deviation of 2%.

Interested in how our lab can support your research? Get in touch at sales@isolab-scientific.com or call +44 (0) 203 278 2351 or at. We’ll be straight back to you.

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