Source: GEORGIA INSTITUTE OF TECHNOLOGY submitted to
PARTNERSHIP: DATA-DRIVEN CHEMO-SELECTIVE LIGNIN VALORIZATION PROCESS TO BIOCHEMICALS AND AVIATION FUEL
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
ACTIVE
Funding Source
AFRI COMPETITIVE GRANT
Reporting Frequency
Annual
Accession No.
1030529
Grant No.
2023-67021-39596
Cumulative Award Amt.
$800,000.00
Proposal No.
2022-10864
Multistate No.
(N/A)
Project Start Date
Apr 1, 2023
Project End Date
Mar 31, 2026
Grant Year
2023
Program Code
[A1531]- Biorefining and Biomanufacturing
Project Director
Tong, Z.
Recipient Organization
GEORGIA INSTITUTE OF TECHNOLOGY
(N/A)
ATLANTA,GA 30332
Performing Department
(N/A)
Non Technical Summary
The conversion of a low-cost biorefinery byproduct, lignin, to high-value chemicals (e.g., aromatic acids and aviation fuels) provides a viable way toward profitable biorefinery, which can mitigate rising oil prices or chemical supply chain volatility. However, such a process has been greatly hindered by many challenges including low selectivity, low yield, harsh reaction conditions, and lignin heterogeneity.Herein, we hypothesize that a one-pot and two-step benzylic oxidation process can selectively modify the lignin side chain, leading to high yields of aromatic acids (AA) for bioplastics and remaining low molecular weight aromatics (LMWA) to be upgraded to sustainable aviation fuel (SAF). This hypothesis is supported by the preliminary data of unique oxidative lignin depolymerization under mild conditions. The selectivity or yields towards AA or SAF will be further improved by designing the catalysts using a unique data-driven approach that couples inverse molecular design theory. The efficient operation will be achieved by online optimization based on reinforcement learning algorithms to enable a more efficient operation that is adaptive to variable feedstock heterogeneity and operation conditions. The TEA/LCA analysis will be applied to evaluate the technical and economic feasibility and environmental potentials of the entire process.The project resolves the key problems in lignin valorization including selectivity, yield, reaction, and operation stability for profitable lignocellulose-based biorefinery systems. It has the potential to compensate for the aromatic shortage from petroleum resources and contribute to the Biden administration's action to produce 3 billion gallons of SAF/year by 2030 and reduce aviation carbon emissions.
Animal Health Component
30%
Research Effort Categories
Basic
50%
Applied
30%
Developmental
20%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
12504302020100%
Knowledge Area
125 - Agroforestry;

Subject Of Investigation
0430 - Climate;

Field Of Science
2020 - Engineering;
Goals / Objectives
The overall goal of this project is to develop a process to selectively convert lignin to high-value aromatics (LHA) with an emphasis on minimizing process cost, the use of the non-renewables, and energy intensity. In the proposed LHA system, the representative lignin from waste hardwood and agricultural residues will be selectively depolymerized to monomeric aromatics (MA, Mw<250 Da) and other LMWA (Mw>250 Da) in high yield (>95%), using an optimized graphene oxide-metal (GO-M) catalyst derived from data-driven catalyst design, followed by a PO process. The water-soluble aromatic carboxylates in LMWA will be isolated from the organic oil and then hydrolyzed to AA with a high yield (>40%). The remaining LMWA (>55%) resembles the carbon chain of SAF, which will be converted to SAF by a mild hydrodeoxygenation (HDO) process. In the end, an innovative stochastic process control algorithm will be developed to optimize this integrated process with a variety of feedstock heterogeneity. Then, the techno-economic assessment and life cycle analysis (TEA/LCA) will be applied to evaluate the technical and economic feasibility and environmental impacts of the proposed process for converting lignin to high-value and bio-based aromatics (AA and SAF).Our research will pursue the following specific research objectives:Selectively convert lignin to aromatic aldehydes and LMWA in high yield via oxidative lignin depolymerization using a GO-M catalyst.Develop protective oxidation (PO) approach to selectively oxidize aromatic aldehydes to AA.Isolate AA from LMWA and transform the remaining LMWA to SAF via a mild HDO process.Conduct a data-driven catalyst design to optimize the catalysts for both the oxidative lignin depolymerization and HDO processes.Develop a new stochastic process control and optimization algorithm for the integrated LHA system and perform a TEA/LCA assessment to determine the system's feasibility and scalability.
Project Methods
Aim 1: Selectively convert lignin to aromatic aldehydes and LMWA in high yield via oxidative lignin depolymerization using a GO-M catalyst.Subtask 1.1 Preparation/collection of biorefinery lignin from hardwood and agricultural biomassSubtask 1.2 Characterization of the biorefinery ligninSubtask 1.3 Development of a process to selectively depolymerize lignin to aromatic acids and LMWA in high yield under mild reaction conditions using a GO-M catalyst.Subtask 1.4 Elucidation of the chemo-selective lignin depolymerization mechanismAim 2: Develop protective oxidation (PO) approach to selectively oxidize aromatic aldehydes to AA.Subtask 2.1 Optimizing PO reaction conditions.Subtask 2.2 Elucidating reaction mechanisms and optimizing catalysts.Subtask 2.3 Development of kinetic models for process control and optimization.Aim 3: Isolate AA from LMWA and transform the remaining LMWA to SAF via a mild HDO process.Subtask 3.1. Isolation of MA from LMWA and converting MA to AASubtask 3.2. Upgrading LMWA to SAF.Aim 4: Conduct a data-driven catalyst design to optimize the catalysts for both the oxidative lignin depolymerization and HDO processes.Subtask 4.1 Identifying key catalyst descriptorsSubtask 4.2 Search for optimal catalytic systemsSubtask 4.3 Predicting optimal catalyst compositions with machine learning algorithms.Subtask 4.4 Catalyst synthesis, characterization, and regenerationAim 5: Develop a new stochastic process control and optimization algorithm for the integrated LHA system and perform a TEA/LCA assessment to determine the system's feasibility and scalability.Subtask 5.1 Distribution identification of uncertain contents in lignin feedstock.Subtask 5.2 Optimization of the lignin depolymerization process

Progress 04/01/23 to 03/31/24

Outputs
Target Audience:The research conducted for this project contributes to the training of one Ph.D. student or one post-doctor who has an exciting opportunity to be involved in interdisciplinary research including catalyst design, lignin catalytic conversion, and process control. The target audience we will target includes graduate students or post-doctors, undergraduate students, and the broader academic communities through conference presentations, and published journals. Changes/Problems:There are no major changes/problems in the current stage. What opportunities for training and professional development has the project provided?This project has provided the opportunity to train two graduate students and several undergraduate students in the interdisciplinary areas including catalytic depolymerization of biopolymers, catalyst characterization, computational-aid catalyst design, DFT training, and process control protocol for sustainable processes. How have the results been disseminated to communities of interest?Yes. The results have been disseminated to communities of interest by publishing the journal papers. What do you plan to do during the next reporting period to accomplish the goals? We propose the idea of doping Cu species onto the surface of GO to further enhance its activity and selectivity towards lignin depolymerization, and we will synthesize a series of Cu- Cu-modified GO catalysts by attaching different Cu species to the GO surface. We will screen different Cu-modified GO catalysts using lignin model compounds for the best aldehyde selectivity and elucidate its mechanism. We will apply the selected catalysts to depolymerize lignin in waste lignocellulose (lignin-first approach) under optimized conditions. We will conduct data-driven catalyst design after we obtain some promising data for Cu-based catalysts. We will conduct the process control using reinforcement learning for this lignin depolymerized process after we have selected the correct catalyst for lignin depolymerization.

Impacts
What was accomplished under these goals? We have successfully developed an effective method to depolymerize lignin towards isolated Phenolic Acids (PAs) under mild conditions (<120 °C, ambient pressure). The method includes three steps: lignin acetylation, graphene oxide (GO)-catalyzed lignin depolymerization, and urea hydrogen peroxide (UHP) oxidation. The method exhibits a high selectivity and the total PA yields reached up to 20%. With comparative study in lignin depolymerization and lignin dimer dissociation We have proved that the acetylation step can significantly enhance the selectivity towards PAs by blocking the phenolic hydroxyl groups in lignin. The yield of PAs from pre-acetylated lignin was 5-7 times higher than that from non-acetylated lignin. We compared the catalytic efficiency of GO and two other metal-free catalysts: sodium persulfate (SP) and sodium formate (SF). In this study, GO exhibited the best efficiency and selectivity towards phenolic aldehydes (the precursors of PAs in the third step) among the three catalysts. We have proved that protective oxidation using the UHP oxidizer could convert aromatic aldehydes to a high yield of isolated PAs for both lignin model compounds (85-90%) and depolymerized lignin mixtures (75%), and the pre-acetylation of lignin avoided the undesirable side reaction to quinone due to the electron-withdrawing of the added acetyl groups. We have performed characterizations such as X-ray Photoelectron Spectroscopy (XPS), Scanning Electron Microscopy (SEM), Gas Chromatography-Mass Spectrometry (GC-MS), and High-Performance Liquid Chromatography (HPLC) for both the products and the catalyst. XPS study revealed that GO catalyst was partially reduced during lignin depolymerization, and conspicuous reduction in the epoxy moieties was discerned, which can be attributed to their active involvement in the catalytic reaction. GC-MS analysis indicated the presence of enol ether as a significant intermediate in lignin depolymerization. We have elucidated the mechanism of GO-catalyzed lignin depolymerization by dissociating two lignin dimers (guaiacylglyerol-β-guaiacyl ether and veratrylglycero-β-guaiacyl ether) with GO, and proposed two possible reaction pathways. We have performed density functional theory (DFT) study to calculate the energy levels of all the intermediates, transition states and products in lignin dimer dissociating, and thus obtaining the energy barriers in each step. Moreover, DFT calculations confirmed that the oxygen species of GO surfaces can shift the lignin depolymerization thermodynamics towards aromatic aldehydes when the phenolic -OH groups in lignin are blocked by pre-acetylation.

Publications

  • Type: Journal Articles Status: Accepted Year Published: 2023 Citation: Peng, W., Bao, H., Wang, Y., Cote, E., Sagues, W. J, Hagelin-Weaver, H., Gao, J., Xiao, D.*, Tong, Z.*, (2023) Selective Depolymerization of Lignin Towards Isolated Phenolic Acids Under Mild Conditions. ChemSusChem. e202300750.