DOI: 10.5061/dryad.3bk3j9kxr
title: Maximizing long-term biohydrogen production with Clostridium thermocellum in high solids lignocellulosic biomass fermentations

description: Biological hydrogen production from lignocellulosic biomass sustainably
 couples organic waste reduction with renewable energy generation.
 Efficient conversion is challenged by the structural complexity of
 lignocellulose and resulting recalcitrance to enzymatic degradation.
 Clostridium thermocellum natively breaks down biomass with some of the
 most effective hemi-/cellulases systems (i.e., cellulosomes) and generates
 hydrogen in anaerobic cultivation, creating a compelling platform for
 lignocellulosic biohydrogen production. Achieving commercially viable
 production rates requires balancing high biomass loading and throughput
 against uniform mixing conditions required for enzyme dispersion, pH and
 temperature control, and efficient hydrogen and metabolite removal in
 continuous operation. To address these barriers to process
 intensification, we implemented novel reactor and process designs for
 high-solids lignocellulosic biomass fermentations using the C.
 thermocellum KJC19-9 strain, genetically engineered for co-utilization of
 cellulose and hemicellulose sugars (i.e., xylose). Via computational fluid
 dynamics (CFD) modeling and experimental validation, we achieved a
 &gt;50% improvement in biohydrogen production with an improved
 anchor-type impeller morphology, coupled to a threefold reduction in
 agitation rate. To further reduce rheological constraints and accumulation
 of toxic metabolites, we then transitioned the process to sequencing
 fed-batch operation. The resulting process generated 24.87 L H2/L from 480
 g/L of deacetylated and mechanically refined (DMR)-pretreated corn stover
 biomass over 16 days while converting &gt;95% of influent cellulose
 and hemicellulose, setting a new performance benchmark for continuous
 production of biohydrogen from lignocellulose.
description: # Dryad dataset Dataset DOI:
 [10.5061/dryad.3bk3j9kxr](10.5061/dryad.3bk3j9kxr) ## Description of the
 data and file structure This dataset contains raw and processed data
 supporting the study of hydrogen production from DMR-treated corn stover.
 It includes results from CFD simulations, biomass compositional analyses,
 bioreactor experiments (Batch, Fed-batch, F-S-D-RE process), HPLC
 analyses, and toxicity assays. The data are intended to facilitate
 reproducibility, secondary analysis, and process optimization in
 biohydrogen research. ### Files and variables #### File:
 dataset\_Biohydrogen.zip **Raw Data:** * **CFD velocity field outputs:**
 Time-resolved velocity and pressure data from simulations of bioreactor
 mixing using different impeller types. * **Batch HPLC results:**
 Quantitative analysis of sugars, acids, and aromatic compounds in
 fermentation samples. * **Fed-batch hydrogen production data:**
 Time-course measurements of hydrogen production in fed-batch bioreactor
 runs. * **Long-term hydrogen production data:** Extended hydrogen
 production trends from the F-S-D-RE process. * **Toxicity assay results:**
 Microbial growth (OD600) under various concentrations of organic acids and
 ethanol. * **Compositional analysis:** Detailed chemical composition of
 DMR-treated corn stover, including glucan, xylan, lignin, and ash content
 **Summarized Data**: * **Comparative hydrogen production:** Batch
 experiment results comparing anchor and Rushton impellers under various
 conditions1. **Supplementary Media**: * CFD video showing the
 visualization of particle velocity distribution and motion by the
 different agitation and impeller types in bioreactor. All files are
 provided in CSV or video format for accessibility and reproducibility. ##
 **File Descriptions and Variables** | File Name | Description | |
 :----------------------------------------------- |
 :------------------------------------------------------------------------------------------ | | Hydrogen-production-trend-by-impellers.csv | Hydrogen yields for different impeller types, agitation rates, and substrate concentrations | | HPLC-Raw-data.csv | Integrated peak areas for sugars, acids, and aromatics from HPLC analysis | | *Anchor or Rushton\_Fluid\_XXX*.csv | CFD simulation outputs: velocity, pressure, kinetic energy, etc., at various time points | | raw-data-of-hydrogen-production-on-fed-batch.csv | Time-resolved hydrogen production in fed-batch experiments | | Raw-data-of-hydrogen-production-trend.csv | Long-term hydrogen production rates and cumulative yields (F-S-D-RE process) | | composition-analysis-of-DMR-corn-stover.csv | Chemical composition of DMR-treated corn stover samples | | raw-data\_toxicity.csv | OD600 measurements for toxicity assays with various inhibitors | **Key Variables:** * *Hydrogen-production-trend-by-impellers.csv*: * Concentration (g/L), Agitation (RPM), Hydrogen production (L/L) for Avicel and DMR corn stover substrates, separated by impeller type. * *HPLC-Raw-data.csv*: * Glucose, Cellobiose, Xylose, Galactose, Arabinose, Fructose, Lactic Acid, Citric Acid, Succinic Acid, Formic Acid, Glycerol, Acetic Acid, Ethanol, PCA, p-coumarate, 4-HBA, Ferulate, Vanillate (all as integrated area or concentration). * *Anchor or Rushton_Fluid_XXX.csv*: * Time (s), Domain Volume (m³), Fluid Volume (m³), Kinetic Energy (J), Max Velocity (m/s), Mean Pressure (Pa), Mean Velocity (m/s), Potential Energy (J), LB Density Max/Min. * *raw-data-of-hydrogen-production-on-fed-batch.csv*: * Time (hrs), hydrogen production (L/L) for different substrate concentrations. * *Raw-data-of-hydrogen-production-trend.csv*: * Time (day), Production rate (ml/L/day), Cumulative hydrogen (ml/L). * *composition-analysis-of-DMR-corn-stover.csv*: * S % Ash, S % Lignin, S % Glucan, S % Xylan, S % Galactan, S % Arabinan, S % Fructan, S % Mannan, S % Acetyl, S % Total. * *raw-data_toxicity.csv*: * OD600 at 0, 24, 48 hr for different concentrations (0–200 mM) of acetate, ethanol, formate, and lactate. ## Experimental and Analytical Methods **CFD Simulations:** * Conducted with M-Star CFD software. Simulated reactors included IKA LR-2 ST  ([https://abpdu.lbl.gov/capabilities/our-equipment/deconstruction-equipment/ika-reactors-lr-2-st/](https://abpdu.lbl.gov/capabilities/our-equipment/deconstruction-equipment/ika-reactors-lr-2-st/)) and Sartorius 2L vessels ([https://abpdu.lbl.gov/capabilities/our-equipment/fermentation-equipment/sartorius-biostat-b-twin-tower/](https://abpdu.lbl.gov/capabilities/our-equipment/fermentation-equipment/sartorius-biostat-b-twin-tower/)). Velocity was measured in the impeller region **HPLC Analysis:** * Liquid samples were collected every 24 hours, centrifuged, and filtered (0.2 µm). Supernatants were analyzed by HPLC (Ultimate 3000, Thermo Fisher) equipped with a refractive index detector and Aminex HPX-87H column at 40°C. The mobile phase was 4 mM H₂SO₄ at 0.4 mL/min. Sugars, organic acids, alcohols, and aromatic compounds were quantified using external standards. **Hydrogen production analysis** * Off-gas (H₂, CO₂, N₂, O₂) was monitored in real time using a magnetic sector mass spectrometer (Prima BT, Thermo Fisher). Hydrogen production rates were normalized to off-gas flow rates and N₂ input. **Biomass Preparation and Characterization** * Corn stover was pretreated using the Deacetylation and Mechanical Refining (DMR) process, following NREL protocols. The processed biomass was analyzed for glucan, xylan, lignin, ash, and other components using wet chemistry and HPLC, as detailed in the supplementary information. * Refernce: [https://doi.org/10.1039/C5EE03718B ](https://doi.org/10.1039/C5EE03718B "Link to landing page via DOI") **Data Collection and Processing** * All raw and processed data—including HPLC results, CFD outputs, hydrogen production trends, compositional analyses, and toxicity assays—are provided in CSV format. * Video files illustrate CFD-simulated velocity fields under different impeller and agitation conditions. **Software** * Data analysis was performed using Microsoft Excel. - CFD simulations were performed using M-Star CFD. - No custom code is required to access the data. ## **Usage Notes** * All CSV files are comma-delimited and can be opened in Excel, LibreOffice, or imported into R/Python. * Missing values are denoted as “NA” or left blank. * Units are specified in the column headers or above.