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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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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Machine learning-based ethylene and carbon monoxide estimation, real-time optimization, and multivariable feedback control of an experimental electrochemical reactor

Electrochemical reduction of CO 2 gas is a novel CO 2 utilization technique that has the potential to mitigate the global climate crisis caused by anthropogenic CO 2 emissions, and enable the large-scale storage of energy generated from renewable sources in the form of carbon-based chemicals and fuels. However, due to the complexity of the electrochemical reactions, the explicit first-principles models for CO2 reduction are not available yet, and there has been a limited effort to develop process modeling, optimization and control of CO 2 electrochemical reactors. To this end, a rotating cylinder electrode (RCE) reactor has been constructed at UCLA to understand the mass transfer and reaction kinetics effects separately on the productivity. In the RCE reactor, the applied potential strongly influences the reaction energetics and the electrode rotation speed affects the hydrodynamic boundary layer and modifies the film mass transfer coefficient, which involves convective and diffusive transport. Further, the present work aims to develop a multi-input multi-output (MIMO) control scheme for the RCE reactor that integrates techniques from artificial and recurrent neural network modeling, nonlinear optimization, and process controller design. Specifically, production rates of two products from the experimental reactor, ethylene and carbon monoxide, are controlled by manipulating two inputs, applied potential and catalyst rotation speed. Process dynamics and controllability are analyzed, a feedback control strategy is designed and the controllers are tuned accordingly. The experimental electrochemical cell is employed to gather data for process modeling and implement the multivariable control system. Finally, the experimental results are presented which demonstrate excellent closed-loop performance by the control system and regulation of the outputs at three different set-points including an economically-optimal set-point.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Machine learning-based ethylene concentration estimation, real-time optimization and feedback control of an experimental electrochemical reactor

With the increase in electricity supply from clean energy sources, electrochemical reduction of carbon dioxide (CO 2 ) has received increasing attention as an alternative source of carbon-based fuels. As CO 2 reduction is becoming a stronger alternative for the clean production of chemicals, the need to model, optimize and control the electrochemical reduction of the CO 2 process becomes inevitable. However, on one hand, a first-principles model to represent the electrochemical CO 2 reduction has not been fully developed yet because of the complexity of its reaction mechanism, which makes it challenging to define a precise state-space model for the control system. On the other hand, the unavailability of efficient concentration measurement sensors continues to challenge our ability to develop feedback control systems. Gas chromatography (GC) is the most common equipment for monitoring the gas product composition, but it requires a period of time to analyze the sample, which means that GC can provide only delayed measurements during the operation. Moreover, the electrochemical CO 2 reduction process is catalyzed by a fast-deactivating copper catalyst and undergoes a selectivity shift from the product-of-interest at the later stages of experiments, which can pose a challenge for conventional control methods. To this end, machine learning (ML) techniques provide a potential approach to overcome those difficulties due to their demonstrated ability to capture the dynamic behavior of a chemical process from data. Motivated by the above considerations, we propose a machine learning-based modeling methodology that integrates support vector regression and first-principles modeling to capture the dynamic behavior of an experimental electrochemical reactor; this model, together with limited gas chromatography measurements, is employed to predict the evolution of gas-phase ethylene concentration. The model prediction is directly used in a proportional-integral (PI) controller that manipulates the applied potential to regulate the gas-phase ethylene concentration at energy-optimal set-point values computed by a real-time process optimizer (RTO). Specifically, the RTO calculates the operation set-point by solving an optimization problem to maximize the economic benefit of the reactor. Finally, suitable compensation methods are introduced to further account for the experimental uncertainties and handle catalyst deactivation. The proposed modeling, optimization, and control approaches are the first demonstration of active control for a CO 2 electrolyzer and contribute to the automation and scale-up efforts for electrified manufacturing of fuels and chemicals starting from CO 2 .

42 ENGINEERING↗
DOE OSTI2022

Digitalization of an experimental electrochemical reactor via the smart manufacturing innovation platform

The exponential increase in data produced over the last two decades has revolutionized the way we collect, store, process, analyze, model, and interpret information to improve profitability. Manufacturing is no exception. How- ever, Smart Manufacturing, the digital practice, organization, workforce, and infrastructure transformation for collection and deployment of data and models at scale and at all levels of manufacturing, is a complex, costly, and labor-intensive journey that is still seeing slow adoption. The Clean Energy Smart Manufacturing Innovation Institute (CESMII), a national Manufacturing USA public-private partnership sponsored by the Department of Energy, is addressing this scaled use of data and modeling in manufacturing. CESMII has focused on how to col- lect and use operating data for numerous applications that improve productivity, precision, and performance of manufacturing operations from factory floor to supply chain using process simulation, predictive analytics, mon- itoring and control, and real-time optimization. Because contextualized data are key, CESMII has developed the Smart Manufacturing Innovation Platform (SMIP) to lower the barriers to the data that are needed to accelerate data-based model building, improve data visualization, and more quickly gain insights. Reusable, standards-based ways of doing data collection, ingestion, and contextualization are particularly important for scaling access and use of data. The SMIP uses a standards-based definition and construct for reusable information models called an SM Profile. When an SM Profile is used in conjunction with the SMIP, the SMIP ensures the availability of contextualized, operational data for model building. The present work demonstrates Smart Manufacturing and the application of the SMIP for building several data-centered models for the operation and control of an ex- perimental electrochemical reactor that reduces carbon dioxide (CO 2 ) gas to valuable liquid and gas chemicals, such as alcohols, olefins, and syngas. We describe how the SMIP plays a central role in more effective model building and we demonstrate how the electochemical reactor can be controlled and optimized for the desired products. Use of the SMIP involves the transmission of real-time sensor measurements to a cloud resource so that the operating data are available to all model building experts. The data collection and transmission process is fully automated to greatly reduce the need for manual manipulation of the data. Data-driven machine learning models are used for advanced real-time state estimation, real-time optimization, and model-based feedback control for the reactor. The application models are implemented as a system to monitor the data flow and control the electrochemical reactor with a single visualization interface. SM Profiles are used to demonstrate reusability of the information models for the reactor and the instrumentation. The application packages, algorithms, and user interfaces developed are cast as Docker images in a library to facilitate reusability of the application models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Scalable and Highly-Efficient Microbial Electrochemical Reactor for Hydrogen Generation from Wastes

The overall goal of this project was to develop a scalable and highly efficient hybrid microbial electrochemical reactor for hydrogen recovery from waste streams at a cost of less than $\$$2/kg H₂. The specific objectives were: (1) to design and fabricate a scalable and highly efficient microbial electrochemical cell (MEC) reactor, and (2) to determine the techno-economic feasibility of the system for H₂ generation from organic-rich waste streams. We achieved the first objective by (a) developing low-cost electrode materials, (b) synthesizing a highly efficient cathode catalyst in a scalable manner, (c) evaluating and validating the developed electrode material and catalyst in MEC reactors, and (d) designing and fabricating a larger reactor that incorporates (a) to (c). We met the second objective by (a) identifying the impacts of wastewater composition and operational conditions on H₂ production, and (b) developing a cost-performance model that identified critical parameters affecting the system's performance and cost, providing a pathway for further improvement.

08 HYDROGEN↗
DOE OSTI2024

Separation and conversion of carbon dioxide to syngas using a porous ceramic dual membrane in a thermo-electrochemical reactor

A thermo-electrochemical reactive capture apparatus includes an anode and a cathode, wherein the anode includes a first catalyst, wherein the cathode includes a second catalyst, a porous ceramic support positioned between the anode and the cathode, an electrolyte mixture in pores of the ceramic support, and a steam flow system on an outer side of the cathode. The outer side of the cathode is opposite an inner side of the cathode and the inner side of the cathode is adjacent to the ceramic support. In addition, the electrolyte mixture is configured to be molten at a temperature below about 600° C.

Campbell, Patrick↗
DOE OSTI2026

Molten Salt Electrochemical Reactors Outside of a Glovebox

Molten salt electrochemical reduction (MSER) offers an electrified method for the reduction, refining, and recycling of metals such as iron and metallurgical grade silicon at high efficiency and lower temperatures than traditional methods, which use temperatures >1000C and carbon-based reductants. However, salts appropriate for MSER are moisture and air sensitive, necessitating air-free methods of processing and testing which is often acomplished with a glovebox. Glovebox operations are cumbersome and difficult to troubleshoot reactor issues. We have developed a robust method of testing chloride and carbonate salts in molten salt reactors outside of a glovebox for silicon and carbon production and steel carburization. We highlight a practical guide for glovebox-free testing of molten salt electrochemical reactors to reduce the barriers to performing this type of work. Our aim is to enable other research groups to step into this field with simple and repeatable reactor configurations.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Reversible Methane Electrochemical Reactors as Efficient Energy Storage for Fossil Power

The overall objective of the project was to conduct a comprehensive Research & Development (R&D) program to demonstrate the suitability and future advancement and integration of reversible methane protonic ceramic electrochemical reactors (PCERs) as an efficient Energy Storage System (ESS) with fossil fuel power plants. Fundamental process and system models are developed to conduct a preliminary conceptual study and investigate the power plant system integration requirements, performance requirements, and technical and non-technical gaps for eventual implementation at system level. Technology maturation requirements is also investigated through identifying the critical technical elements and networking with industrial technology developers and end-users.

08 HYDROGEN↗
DOE OSTI2025

Benchtop-Scale High Temperature Molten Salt Electrochemical Reactors: Experimental Setup and Considerations

Molten salt electrochemical reduction (MSER) is the dominant production method for aluminum and titanium, and emerging technologies for producing other commodity metals with these highly electrified techniques have demonstrated promising results. However, the scale up of MSER of materials such as iron and silicon are limited by the challenging issues of materials compatibility and impurity control. This work describes an experimental MSER setup using both chloride and carbonate salts. This setup is designed for operations outside of a glovebox, which is practical from an industrial perspective, but creates unique challenges. This work serves as a practical guide to discuss some key operational difficulties such as temperature control, air and humidity, material compatibility, developing strong electrical measurements and techniques, and safety.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Dynamic operation and reaction network coupling in solid oxide electrochemical reactors

Solid oxide cells have traditionally been confined to operation as standalone electrolyzers or fuel cells, with research predominantly focused on materials performance. Here, this Comment highlights opportunities to leverage integrated faradaic and non-faradaic reactions alongside dynamic operation in these electrochemical membrane reactors to maximize energy utilization and expand product scope.

Cho, Yoon Jin [University of Michigan, Ann Arbor, ↗
DOE OSTI2024

Three-chamber electrochemical reactor for selective lithium extraction from brine

Efficient lithium recovery from geothermal brines is crucial for the battery industry. Current electrochemical separation methods struggle with the simultaneous presence of Na + , K + , Mg 2+ , and Ca 2+ because these cations are similar to Li + , making it challenging to separate effectively. We address these challenges with a three-chamber reactor featuring a polymer porous solid electrolyte in the middle layer. This design improves the transference number of Li + (t Li+ ) by 2.1 times compared to the two-chamber reactor and also reduces the chlorine evolution reaction, a common side reaction in electrochemical lithium extraction, to only 6.4% in Faradaic Efficiency. Employing a lithium-ion conductive glass ceramic (LICGC) membrane, the reactor achieved high t Li+ of 97.5% in LiOH production from simulated brine, while the concentrations of Na + K + , Mg 2+ , and Ca 2+ are below the detection limit. Electrochemical experiments and surface analysis elucidated the cation transport mechanism, highlighting the impact of Na + on Li + migration at the LICGC interface.

Science & Technology - Other Topics↗
DOE OSTI2025

Selective and Stable Ethanol Synthesis via Electrochemical CO 2 Reduction in a Solid Electrolyte Reactor

Electrochemical CO 2 reduction to ethanol faces challenges such as low selectivity, a product mixture with liquid electrolyte, and poor catalyst/reactor stability. Here, we developed a grain-rich zinc-doped Cu 2 O precatalyst that presented a high ethanol Faradaic efficiency of over 40% under a current density of 350 mA·cm –2 . Our density functional theory (DFT) simulation suggested that Zn atoms inside the structure have a greater carbophilicity than the Cu atoms to help facilitate *CHCHO formation, a key reaction intermediate toward ethanol instead of other C 2 products. Here, a high Faradaic efficiency ratio between ethanol and ethylene (FE EtOH /FE C2H4 ) reached 2.34 in the zinc-doped Cu 2 O precatalyst, representing an over 4-fold improvement compared to bare Cu 2 O precatalyst. By integrating this Cu-based catalyst into a porous solid electrolyte (PSE) reactor with a salt-managing design, we achieved stable ethanol production for over 180 h under a current density of 250 mA·cm –2 while maintaining ethanol selectivity at ~30%.

09 BIOMASS FUELS↗
DOE OSTI2023

Electrochemical Flow Reactor Design Allows Tunable Mass Transport Conditions for Operando Surface Enhanced Infrared Absorption Spectroscopy

Abstract In situ attenuated total reflection surface enhanced infrared absorption spectroscopy (ATR‐SEIRAS) is often used to investigate the near‐surface electrocatalytic reaction environment. However, there is a gap in directly correlating the near‐surface reaction environment with electrocatalytic reaction rates. To that end, we designed an electrochemical flow reactor for operando electrochemical ATR‐SEIRAS and demonstrate its capability with the CO 2 reduction reaction (CO 2 RR). Roughened gold catalyst thin films are prepared on ATR silicon crystals as a model system to probe local species under CO 2 RR conditions in 0.1 M KHCO 3 . We measured changes in the interfacial CO 2 concentration as a function of applied potential and electrolyte flow rate in operando , allowing us to correlate the changes in reaction rates with the observed CO 2 concentration. Including the choice of the catalyst and electrolyte, coupling hydrodynamic control with ATR‐SEIRAS in this platform enables investigations of how the local microenvironment affects the activity and selectivity of electrochemical reactions.

Avilés Acosta, Jaime E.↗
DOE OSTI2022

Electrification and decarbonization of spent Li-ion batteries purification by using an electrochemical membrane reactor

The expanding electric vehicle market brings with it exponential growth in the use of lithium (Li)-ion batteries (LIB) for which a wave of spent LIB is expected to come within the next 5 to 10 years. Due to the economic and strategic value imbedded within the metals contained in LIB, different recycling technologies, including hydrometallurgy, pyrometallurgy and direct recycling, are under development. Being different from previous hydrometallurgical methods, which may have high chemical consumption and negative environmental impact, an electrochemical membrane reactor is designed and validated for the first time, to electrify and decarbonize the impurity removal process. This reactor electroplates copper (Cu) and electrochemically precipitates aluminum (Al) and iron (Fe) from simulated spent LIB leachates, by consuming only air, water, and electricity, and the impurities are reduced to <1 ppm. The purified leachate maintains 99.5 % of the nickel (Ni), 95.4 % of the cobalt (Co) and 99.14 % of manganese (Mn) from the original leachate solution, and then can be directly applied for cathode precursor synthesis. Additionally, the purification process doesn’t introduce extra impurity, and the reactor restoration process generates valuable by-product hydro sulfate (H2SO4). This electrochemical process can reduce the cost, because of the much less chemical consumption and the valuable by-product generation, and mitigates the waste emissions, because of no extra impurity introduced and no greenhouse gas (GHG) produced. In conclusion, the chemical precipitation method uses significant amount of NaOH, which induced GHG emission during the manufacturing process.

25 ENERGY STORAGE↗
DOE OSTI2023

Electrochemical Residence Time Distribution as a Diagnostic Tool for Redox Flow Batteries

The fluid dynamic and electrochemical performance of redox flow batteries (RFBs) stems from the relationship between the flow field and the porous electrode, whose interplay determines how active species move and react during device operation. While characterization techniques, such as residence time distribution, offer insights into species mobility within a reactive volume for a traditional chemical reactor, electrochemical reactors also enable simultaneous measurement of the redox reactions, unlocking another dimension of analysis. Herein, we demonstrate how potentiodynamic measurements, using injections of electrolyte examined through moment analysis, can provide electrode-specific performance scaling relationships across a matrix of carbon paper and cloth electrodes with flow through and interdigitated flow fields. We further combine experimental campaigns with multiphysics simulations to demonstrate how electrode surface area can be estimated with this technique, which we then validate with activated and unactivated commercial carbon cloth electrodes. These studies reveal the multiscale observations that potentiodynamic measurements afford, augmenting existing electrochemical techniques for holistic electrochemical reactor diagnostics.

Electrochemistry↗