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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Characterization of ECRAM materials and devices

As the limits of Moore’s Law approaches, new computing paradigms are developing to breakthrough this bottleneck. One such computer architecture is neuromorphic computing, which models the brain. Electrochemical random-access memory (ECRAM) is a low power and energy efficient memory due to characteristics, such as in-memory compute, ion modulation of the channel conductance, and computation distribution with large scale array integration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Integrated Technology for Cost-Effective CO2 Capture and Formic Acid Production: Modeling, Optimization, and Economic Analysis

A novel reactive technology is being investigated that electrochemically converts CO2 into valuable chemicals, particularly formic acid. This work focuses on identifying the optimal design and operation of an integrated membrane-based CO2 capture unit with the electrochemical conversion process. In this setup, the CO2 in the flue gas permeates through a CO2-selective membrane and enters an electrolyzer to produce formic acid, creating an integrated reaction module. To refine the chemical product, gas products from the electrolyzer are directed to a pressure swing adsorption unit, while the liquid product undergoes refinement to achieve commercial-grade formic acid using reactive distillation. A membrane CO2 capture model and an electrochemical conversion model have been developed using the IDAES Integrated Platform (Institute for the Design of Advanced Energy System), facilitating rigorous flowsheet modeling and process design and optimization.

Wang, Maojian↗
DOE OSTI2024

Modeling diurnal and annual ethylene generation from solar-driven electrochemical CO 2 reduction devices

Integrated solar fuels devices for CO 2 reduction (CO 2 R) are a promising technology class towards reducing carbon emissions. Designing integrated CO 2 R solar fuels devices requires careful co-design of electrochemical and photovoltaic components as well as consideration of the diurnal and seasonal effects of solar irradiance, temperature, and other meteorological factors expected for ‘on-sun’ deployment. Using a photovoltaic-electrochemical (PV-EC) platform, we developed a temperature and potential-dependent diurnal and annual model using experimentally-determined CO 2 R performance of Cu-based electrocatalysts, local meteorological data from the National Solar Radiation Database (NSRD), and modeled performance of commercial c-Si PVs. Here we simulated gaseous diurnal product outputs with and without the effects of ambient temperature. From these outputs, we observed seasonal variation in gaseous product generation, with up to two-fold increases in ethylene productivity between the Winter and Summer, analyzed the consequences of dynamic cloud coverage, and identified periods where device cooling/heating mechanisms could be implemented to maximize ethylene generation. Finally, we modeled the annual ethylene generation for a scaled 1 MW solar farm at three different locations (Beijing, CN; Sydney, AUS; Barstow, CA) to determine the consequences of local meteorological climates on PV-EC CO 2 R product output, recording a maximum ethylene output of 18.5 tonne per year at Barstow. Overall, this model presents a critical tool for streamlining the translation of experimental solar-driven electrochemical research to real-world implementation.

14 SOLAR ENERGY↗
DOE OSTI2024

Modeling Diurnal and Annual Ethylene Generation from Solar-Driven Electrochemical CO 2 Reduction Devices

Integrated solar fuels devices for CO 2 reduction (CO 2 R) are a promising technology class towards achieving net-negative carbon emissions. Designing integrated CO 2 R solar fuels devices requires careful co-design of electrochemical and photovoltaic components as well as consideration of the diurnal and seasonal effects of solar irradiance, temperature, and other meteorological factors expected for ‘on-sun’ deployment. Here, using a photovoltaic-electrochemical (PV-EC) platform, we developed a temperature and potential-dependent diurnal and annual model using experimental CO 2 R performance of Cu-based electrocatalysts, local meteorological data from the National Solar Radiation Database (NSRD), and modeled performance of commercial c-Si PVs. We simulated diurnal product outputs with and without the effects of ambient temperature to determine gaseous product temperature sensitivity. From these outputs, we observed seasonal variation in gaseous product generation, with up to two-fold increases in ethylene productivity between the Winter and Summer, analyzed the consequences of dynamic cloud coverage, and identified periods where device cooling/heating mechanisms could be implemented to maximize ethylene generation. Finally, we modeled the annual ethylene generation for a scaled 1 MW solar farm at three different locations (Beijing, CN; Sydney, AUS; Barstow, CA) to determine the consequences of local meteorological climates on PV-EC CO 2 R product output, recording a maximum ethylene output of 18.5 tonne/yr at Barstow. Overall, this model presents a critical tool for streamlining the translation of experimental solar-driven electrochemical research to real-world implementation.

Yap, Kyra M. K.↗
DOE OSTI2021

Intermediate Sr 2 Co 1.5 Fe 0.5 O 6-δ Tetragonal Structure between Perovskite and Brownmillerite as a Model Catalyst with Layered Oxygen Deficiency for Enhanced Electrochemical Water Oxidation

The generation of hydrogen in an environmentally benign way is highly essential to meet future energy demands. However, in the process of splitting water electrochemically, sluggish kinetics of the oxygen evolution reaction (OER) curtails its applicability, as it drags energy input. Herein, we synthesized SrCo-Fe-O oxides to optimize their OER activity by varying the Co/Fe ratio. Among them, Sr 2 Co 1.5 Fe 0.5 O 6-δ exhibited the best OER catalytic activity in the series, with an overpotential of 318 mV at 10 mA cm -2 and Tafel slope of 44.8 mV dec -1 . High-resolution neutron powder diffraction analysis identified an intermediate structure between the perovskite and brownmillerite, with alternating layers of disorderly orientated oxygen-deficient tetrahedra and fully stoichiometric octahedra. The unique stacking of tetrahedral and octahedral units facilitates desired interactions between the electrode surface and electrolyte. Theoretical calculations revealed that increased covalency of Co 3d and O 2p in Sr 2 Co 1.5 Fe 0.5 O 6-δ oxide is another primary contributor to its augmented water oxidation ability. As a model for developing catalysts with such an intermediate structure, the synergetic effect of oxygen vacancy and hybridization between Co 3d and O 2p assured the Sr 2 Co 1.5 Fe 0.5 O 6-δ oxide as a better catalyst for its enhanced OER activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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

Insights into the Effect of Heat Treatment and Carbon Coating on the Electrochemical Behaviors of SiO Anodes for Li-Ion Batteries

The use of SiO as an anode material has attracted significant interest due to its high capacity and long cycling life. Many promising approaches, including structural design and carbon coating at high temperatures, effectively improve its intrinsic low electrical conductivity and poor Coulombic efficiency. However, the “heat treatment process-composition and microstructure-electrochemical properties” relationship of the SiO anode is not fundamentally understood. Here the structure and composition evolution in amorphous SiO and graphene-coated SiO is investigated using different heat-treatment conditions. X-ray absorption near-edge structure techniques are also employed to analyze the surface and bulk composition change during the initial lithiation process, supplemented by physical or chemical characterization and electrochemical testing. Here results reveal the structural transition of SiO during heat treatment, from amorphous to disproportionated hierarchical structure, where the as-formed dielectric exterior SiO 2 shell and interior SiO 2 matrix severely polarizes electrodes, hindering the lithiation process. Carbon coating on SiO effectively restricts the growth of the SiO 2 shell and facilitates charge transfer, leading to improved electrochemical performance. A schematic model is proposed to reveal the relationship between the treatments, the resultant structural evolutions, and corresponding electrochemical behaviors.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Towards robust autonomous impedance spectroscopy analysis: A calibrated hierarchical Bayesian approach for electrochemical impedance spectroscopy (EIS) inversion

Distribution-based analyses, such as the distribution of relaxation times (DRT) and the distribution of diffusion times (DDT), present model-free alternatives to equivalent circuit modeling for analysis of electrochemical impedance spectroscopy (EIS) data. However, reconstructing such distributions from noisy impedance data is an ill-posed problem that must be solved with specialized inversion algorithms, requiring careful control and tuning. Furthermore, most inversion algorithms developed to date can only solve problems of limited complexity. Herein, we present a new hierarchical Bayesian method for EIS inversion, leveraging efficient algorithms for optimization and Hamiltonian Monte Carlo (HMC) sampling to solve models of arbitrary complexity. We overcome the challenge of ad-hoc parameter tuning by encoding intrinsic characteristics of the DRT and DDT into flexible prior distributions and “pre-calibrating” the model to simulated data. This approach is versatile, highly robust to noise, and provides quantitative estimates of both the error structure of the data and the uncertainty in the recovered distributions. The model is validated with simulated data to demonstrate accurate recovery of the DRT and the DDT. The method also shows promise for simultaneous recovery of multiple distributions, raising the intriguing possibility of semi-autonomous EIS analysis and ad-hoc model construction. Finally, the practical utility of the method is illustrated with experimental data. Throughout, we draw comparisons to several recently published EIS inversion methodologies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Process modeling, techno-economic assessment, and life cycle assessment of the electrochemical reduction of CO 2 : a review

The electrochemical reduction of CO 2 has emerged as a promising alternative to traditional fossil-based technologies for the synthesis of chemicals. Its industrial implementation could lead to a reduction in the carbon footprint of chemicals and the mitigation of climate change impacts caused by hard-to-decarbonize industrial applications, among other benefits. However, the current low technology readiness levels of such emerging technologies make it hard to predict their performance at industrial scales. During the past few years, researchers have developed diverse techniques to model and assess the electrochemical reduction of CO 2 toward its industrial implementation. The aim of this literature review is to provide a comprehensive overview of techno-economic and life cycle assessment methods and pave the way for future assessment approaches. First, we identify which modeling approaches have been conducted to extend analysis to the production scale. Next, we explore the metrics used to evaluate such systems, regarding technical, environmental, and economic aspects. Finally, we assess the challenges and research opportunities for the industrial implementation of CO 2 reduction via electrolysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Directly monitoring the shift in corrosion mechanisms of a model FeCrNi alloy driven by electric potential

Abstract Stainless steels are used in a myriad of engineering applications, including construction, automobiles, and nuclear reactors. Developing accurate, predictive mechanistic models for corrosion and electrochemical corrosion kinetics of stainless steels has been a topic of research studies over many decades. Herein, we quantified the aqueous corrosion kinetics of a model austenitic Fe–18Cr–14Ni (wt%) alloy in the presence and absence of applied potential using systematic in situ electrochemical atomic force microscopy (EC-AFM) and transmission electron microscopy (TEM). Without an applied bias, vertical dissolution of corrosion pits is controlled by the surface kinetics/diffusion hybrid mechanism, whereas lateral dissolution is diffusion controlled. When an electric bias is applied, the increase in corrosion rate is dominated by the nucleation of new pits. These insights gained by the in situ EC-AFM will allow applications of this method for a quantitative understanding of corrosion of a wider class of materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Trion Formation Resolves Observed Peak Shifts in the Optical Spectra of Transition-Metal Dichalcogenides

Monolayer transition-metal dichalcogenides (ML-TMDs) have the potential to unlock novel photonic and chemical technologies if their optoelectronic properties can be understood and controlled. Yet, recent work has offered contradictory explanations for how TMD absorption spectra change with carrier concentration, fluence, and time. Here, we test our hypothesis that the large broadening and shifting of the strong band-edge features observed in optical spectra arise from the formation of negative trions. We do this by fitting an ab initio based, many-body model to our experimental electrochemical data. Our approach provides an excellent, global description of the potential-dependent linear absorption data. We further leverage our model to demonstrate that trion formation explains the nonmonotonic potential dependence of the transient absorption spectra, including through photoinduced derivative line shapes for the trion peak. Our results motivate the continued development of theoretical methods to describe cutting-edge experiments in a physically transparent way.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Electrochemically modulated single-molecule localization microscopy for in vitro imaging cytoskeletal protein structures

A new concept of electrochemically modulated single-molecule localization super-resolution imaging is developed. Applications of single-molecule localization super-resolution microscopy have been limited due to insufficient availability of qualified fluorophores with favorable low duty cycles. The key for the new concept is that the “On” state of a redox-active fluorophore with unfavorable high duty cycle could be driven to “Off” state by electrochemical potential modulation and thus become available for single-molecule localization imaging. The new concept was carried out using redox-active cresyl violet with unfavorable high duty cycle as a model fluorophore by synchronizing electrochemical potential scanning with a single-molecule localization microscope. The two cytoskeletal protein structures, the microtubules from porcine brain and the actins from rabbit muscle, were selected as the model target structures for the conceptual imaging in vitro. The super-resolution images of microtubules and actins were obtained from precise single-molecule localizations determined by modulating the On/Off states of single fluorophore molecules on the cytoskeletal proteins via electrochemical potential scanning. Importantly, this method could allow more fluorophores even with unfavorable photophysical properties to become available for a wider and more extensive application of single-molecule localization microscopy.

electrochemical modulation↗
DOE OSTI2020

Experimental validation of solid oxide fuel cell polarization modeling: An LSM-YSZ/YSZ/Ni-YSZ case study

Polarization modeling based on the measured I-V curves is a useful tool for analyzing SOFC performance and diagnosing performance limitations. Using the polarization model, the overpotential of a cell is usually separated into different polarization contributions, including area specific ohmic polarization, activation polarization, and anodic and cathodic concentration polarizations. In this study, we aim to experimentally validate the accuracy of the polarization model. As a case study, anode-supported cells with LSM-YSZ/YSZ/Ni-YSZ configuration are used. By curve-fitting the I-V curves of a cell tested under different cathode oxygen partial pressures into the polarization model, the contributions of different polarization losses are quantified. To validate the polarization model, independent experiments/studies including electrochemical impedance spectroscopy, cathode kinetics study, ex-situ diffusivity measurement, and tortuosity measurement using 3D reconstructed anode are conducted. The results from polarization modeling and from validation studies are in good agreement, thereby validating the polarization model for SOFC performance analysis.

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

Computational Modeling of Battery Materials

This chapter provides a broad overview of the various computational modeling techniques used to gain fundamental insights into coupled electrochemical processes that occur in battery materials at electronic-to-mesoscopic scales. Furthermore, representative successes of these techniques in modeling electrodes, electrolytes, and electrode-electrolyte interfaces are highlighted to establish the current state-of-the-art in the field.

25 ENERGY STORAGE↗
DOE OSTI2024

Rationalizing Acidic Oxygen Evolution Reaction over IrO 2 : Essential Role of Hydronium Cation

Abstract The development of active, stable, and more affordable electrocatalysts for acidic oxygen evolution reaction (OER) is of great importance for the practical application of electrolyzers and the advancement of renewable energy conversion technologies. Currently, IrO 2 is the only catalyst with high stability and activity, but a high cost. Further optimization of the catalyst is limited by the lack of understanding of catalytic behaviors at the acid‐IrO 2 interface. Here, in strong interaction with the experiment, we develop an explicit model based on grand‐canonical density function theory (GC‐DFT) calculations to describe acidic OER over IrO 2 . Compared to the explicit models reported previously, hydronium cations (H 3 O + ) are introduced at the electrochemical interface in the current model. As a result, a variation in stable IrO 2 surface configuration under the OER operating condition from previously proposed complete *O‐coverage to a mixture coverage of *OH and *O is revealed, which is well supported by in situ Raman measurements. In addition, the accuracy of predicted overpotential is increased in comparison with the experimentally measured. More importantly, an alteration of the potential limiting step from previously identified *O→*OOH to *OH→*O is observed, which opens new opportunities to advance the IrO 2 ‐based catalysts for acidic OER.

Mou, Tianyou↗
DOE OSTI2024

Rationalizing Acidic Oxygen Evolution Reaction over IrO 2 : Essential Role of Hydronium Cation

The development of active, stable, and more affordable electrocatalysts for acidic oxygen evolution reaction (OER) is of great importance for the practical application of electrolyzers and the advancement of renewable energy conversion technologies. Currently, IrO 2 is the only catalyst with high stability and activity, but a high cost. Further optimization of the catalyst is limited by the lack of understanding of catalytic behaviors at the acid-IrO 2 interface. Here, in strong interaction with the experiment, we develop an explicit model based on grand-canonical density function theory (GC-DFT) calculations to describe acidic OER over IrO 2 . Compared to the explicit models reported previously, hydronium cations (H 3 O + ) are introduced at the electrochemical interface in the current model. As a result, a variation in stable IrO 2 surface configuration under the OER operating condition from previously proposed complete *O-coverage to a mixture coverage of *OH and *O is revealed, which is well supported by in situ Raman measurements. In addition, the accuracy of predicted overpotential is increased in comparison with the experimentally measured. More importantly, in this study, an alteration of the potential limiting step from previously identified *O→*OOH to *OH→*O is observed, which opens new opportunities to advance the IrO 2 -based catalysts for acidic OER.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Design Principles to Govern Electrode Fabrication for the Lithium Trivanadate Cathode

A full depth of discharge mathematical model for the lithium trivanadate cathode, considering lithiation of the layered α-phase, phase change, and lithiation of the rock-salt like β-phase at lower potentials, is developed. The coupled electrode-scale and crystal-scale model is fit to electrochemical data, and additionally validated with operando EDXRD. There is good agreement between the simulated and measured spatial variation of the volume fraction of the β-phase. This mathematical model is used to guide electrode fabrication, accounting for both ionic and electronic transport effects. Values of three design parameters—electrode thickness, porosity, and volume fraction of conductor—are identified, and the sensitivity of the energy density to these design parameters is quantified. The model is also used to investigate electrode design to create electrodes that deliver the maximum achievable energy density under the constraint that the α to β-phase transition is avoided, since phase change has been demonstrated to reduce cycle life. The energy density sacrificed to avoid phase change decreases at higher discharge rates, but the target values for electrode fabrication remain the same as those when optimizing the electrode for the full depth of discharge.

25 ENERGY STORAGE↗