Data Fusion-Based Approach for the Investigation of Reaction Networks in Hydrous Pyrolysis of Biomass

Abstract

In this work, we present and validate a methodology for generating reaction networks from spectroscopic data using data-driven methods by applying it to the hydrothermal liquefaction (HTL) of Monterrey pine biomass and its constituents, viz., cellulose and lignin. This work is presented as a step toward automated inference of chemistry of the hydrothermal liquefaction process, thus limiting the need for human expertise. Bayesian hierarchical clustering of spectra and selfmodeling multivariate spectral curve resolution are used to generate groups of chemically similar species, the reaction networks among which have been developed using Bayesian networks. Fourier transform infrared spectroscopy and proton nuclear magnetic resonance spectroscopy-based measurements are used as input data. The data-driven reaction network includes pathways representing decomposition of the biomass components, large molecule hydrolysis, and reformation of produced molecules and is consistent with the literature. Furthermore, the comparison of the networks generated for biomass and its components (levoglucosan, representing cellulose, and 2-phenoxy-ethyl benzene, representing lignin) reveals the relationship between the biomass HTL reaction network and the reaction networks of the components. The data-driven approach provides a diagnostic tool to identify the most probable reaction chemistry for complex biomass feedstocks and can be used for process understanding, design, and control.

Identification of Reaction Network Hypotheses for Complex Feedstocks from Spectroscopic Measurements with Minimal Human Intervention

“…It is important to note here that the networks presented in this work have been filtered from all generated hypotheses based on domain knowledge of the process regarding molecular scaffold information. These networks also seemed to match with the general trend noticed in the hydrolysis of biomass. ,, It is also interesting to note that the candidate molecules identified in each step closely resemble model compounds presented in the literature for the thermal pyrolysis of biomass. , …”

“…We have discussed the generation of a reaction network hypothesis for the HTL process of biomass by incorporating human expertise in transforming the PC network to real-life chemistries in our previous work. ,, In this work, we present methods to automate these routines with some added human intuition by way of using 1-D CNNs as well as reaction templating and fingerprinting schemes.…”

“…14,15,83 It is also interesting to note that the candidate molecules identified in each step closely resemble model compounds presented in the literature for the thermal pyrolysis of biomass. 6,84 4.2. Discussion.…”