Celignis creates novel methodology for biomass analysis

In Belgium, Celignis’s founder discovered that although feedstock composition was a critical factor for the success of biomass transformation processes, precise data was missing for a wide range of feedstocks. To address this issue, and avoid future problems in conversion processes, companies used to subcontract laboratories to chemically analyze biomass samples. This process is time consuming and expensive: taking approximately two weeks per sample, and costing hundreds of euros. Looking for solutions to improve this process, Celignis created a novel methodology for biomass analysis, modelling samples’ composition according to the results of a near infrared spectroscopy analysis. Their method uses infrared light to determine the presence and quantity of important constituents in biomass materials. Following the analysis of hundreds of samples of different feedstocks across the world, Celignis developed unique algorithms to predict with high accuracy and precision the composition of biomass samples. In that way, up to 13 different parameters, including type and amount of sugars, lignin and ash, can be analyzed for various types of biomass. And this in only one day, for less than a hundred euros per sample.