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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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6 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Achieving high hydrogen productivities of 20 L/L-day via microbial electrolysis of corn stover fermentation products

Microbial electrolysis cells have the potential to generate renewable hydrogen from underused waste streams, however current devices have not reached very large productivity targets using real waste products at any scale. This study used a waste from fermented corn stover known as corn stover fermentation product to reach performance metrics that could be commercialized, if adequately scaled. Average current densities in MECs with mature biofilms reached 17.9 +/- 1.6 A/m 2 at an organic loading rate of 30 grams of chemical oxygen demand per liter of anode volume per day (g/L-day), reaching a maximum current density of 27.2 +/- 2.9 A/m 2 . Hydrogen productivities reached 20.2 +/- 2.0 L of H 2 per L anode volume per day (L/L-day). These represent the highest current densities and highest hydrogen productivities using a complex feedstock in a microbial electrolysis cell. Organic acids and sugars present in untreated substrate were converted at high percentages in MECs, with most above 90% conversion, at organic loading rates of 10, 20, and 30 g/L-day. The effect of periodic high liquid flow rates through the anode on performance was assessed. These tests, called pulsing, showed that hydrogen productivities and current densities increased most dramatically as flow was pulsed every hour at a baseline flow rate of 0.3 mL/min. These productivities show promise for high performance systems, if adequate scale up can be achieved.

09 BIOMASS FUELS↗
DOE OSTI2019

A two-phase substrate model for enzymatic hydrolysis of lignocellulose: application to batch and continuous reactors

Abstract Background Enzymatic hydrolysis continues to have a significant projected production cost for the biological conversion of biomass to fuels and chemicals, motivating research into improved enzyme and reactor technologies in order to reduce enzyme usage and equipment costs. However, technology development is stymied by a lack of accurate and computationally accessible enzymatic-hydrolysis reaction models. Enzymatic deconstruction of cellulosic materials is an exceedingly complex physico-chemical process. Models which elucidate specific mechanisms of deconstruction are often too computationally intensive to be accessible in process or multi-physics simulations, and empirical models are often too inflexible to be effectively applied outside of their batch contexts. In this paper, we employ a phenomenological modeling approach to represent rate slowdown due to substrate structure (implemented as two substrate phases) and feedback inhibition, and apply the model to a continuous reactor system. Results A phenomenological model was developed in order to predict glucose and solids concentrations in batch and continuous enzymatic-hydrolysis reactors from which liquor is continuously removed by ultrafiltration. A series of batch experiments were performed, varying initial conditions (solids, enzyme, and sugar concentrations), and best-fit model parameters were determined using constrained nonlinear least-squares methods. The model achieved a good fit for overall sugar yield and insoluble solids concentration, as well as for the reduced rate of sugar production over time. Additionally, without refitting model coefficients, good quantitative agreement was observed between results from continuous enzymatic-hydrolysis experiments and model predictions. Finally, the sensitivity of the model to its parameters is explored and discussed. Conclusions Although the phenomena represented by the model correspond to behaviors that emerge from clusters of mechanisms, and hence a set of model coefficients are unique to the substrate and the enzyme system, the model is efficient to solve and may be applied to novel reactor schema and implemented in computational fluid dynamics (CFD) simulations. Hence, this modeling approach finds the right balance between model complexity and computational efficiency. These capabilities have broad application to reactor design, scale-up, and process optimization.

09 BIOMASS FUELS↗
DOE OSTI2020

Kinetics Modeling for Design of Continuous Enzymatic Hydrolysis

Enzymatic hydrolysis of cellulose to monomeric sugars continues to be a limiting step in cost-effectively producing sugar and fermentation-based biofuels from biomass. In particular, the high cost of enzymes coupled with the long time-scale of reaction pose challenges to economic viability. Performing enzymatic hydrolysis in a continuous mode with enzyme recycle may provide a path towards substantially reduced costs for sugar production, but design and analysis are complicated by a lack of suitable kinetics models. Computationally attainable models, such as fractal-based models, require knowledge of the reaction-history of the biomass, and are thus only suitable for describing the batch reactions from which they are derived. Fundamental models, while potentially more generalizable, are often too computationally intensive to use in process or reactor modeling. In this work, a phenomenological rate model is proposed based on a two-phase substrate representation. Good agreement is seen between batch and continuous enzymatic hydrolysis (CEH) experiment data, which validates the model and enables us to solve for reactor design parameters, such as CEH reactor size and stream flow rates, based on process variables like yield. This model is integrated with techno-economic analysis software to explore economic sensitivities. Important design optimizations and tradeoffs are identified and quantified, including the relative cost imposed by rate slowdown from sugar inhibition versus the cost to remove and concentrate sugars at a lower concentration. It also identifies, high-leverage avenues for further exploration, such as increasing the maximum feasible solids concentration, and sustaining high membrane flux and reliability.

09 BIOMASS FUELS↗
DOE OSTI2020

Computational Fluid Dynamics of Bioreactors with Micro-Aeration

Recent work has probed the potential for using Zymomonas mobilis as a flexible platform for the production of advanced fuels and intermediates. One set of recombinant organisms requires a micro-aerobic environment to promote the production of the desired product (2,3-BDO), but the economics and process-control implications of this approach are uncertain at industrial scale. Computational multi-physics models have the potential to describe the fermentation in detail at multiple scales, reducing the risk of scale-up. A two-phase Euler-Euler CFD model is used alongside a simple model of oxygen uptake to describe this bioreaction. A few reactor vessels, including airlift and CSTR bioreactors, are analyzed at multiple scales, regions of oxygen-depletion and over-oxygenation are characterized, and the bioreactors are compared. We show that it is difficult to achieve homogenous oxygen concentrations in industrial-scale CSTR reactors and that advanced bioreactor designs are needed for economical operation.

09 BIOMASS FUELS↗