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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Improved analytic modeling of the linear Rayleigh–Taylor instability with plasma transport

The Rayleigh–Taylor (R–T) instability with transport effects has long been studied analytically in the neutral fluid regime. How this picture may differ in plasmas has been given less consideration, however. Leveraging previous numerical simulations with plasma viscosity and diffusion of R–T at a binary plasma interface, we show how plasma transport and kinetic effects alter the linear R–T dispersion relation. Our insight informs a much improved analytical dispersion relation, which better matches the simulation data than previously established models. Additionally, we demonstrate the importance of employing asymptotically correct viscosity coefficients in fluid codes for accurately capturing plasma R–T growth.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Modification and analysis of context-specific genome-scale metabolic models: methane-utilizing microbial chassis as a case study

ABSTRACT Context-specific genome-scale model (CS-GSM) reconstruction is becoming an efficient strategy for integrating and cross-comparing experimental multi-scale data to explore the relationship between cellular genotypes, facilitating fundamental or applied research discoveries. However, the application of CS modeling for non-conventional microbes is still challenging. Here, we present a graphical user interface that integrates COBRApy, EscherPy, and RIPTiDe, Python-based tools within the BioUML platform, and streamlines the reconstruction and interrogation of the CS genome-scale metabolic frameworks via Jupyter Notebook. The approach was tested using -omics data collected for Methylotuvimicrobium alcaliphilum 20Z R , a prominent microbial chassis for methane capturing and valorization. We optimized the previously reconstructed whole genome-scale metabolic network by adjusting the flux distribution using gene expression data. The outputs of the automatically reconstructed CS metabolic network were comparable to manually optimized i IA409 models for Ca-growth conditions. However, the CS model questions the reversibility of the phosphoketolase pathway and suggests higher flux via primary oxidation pathways. The model also highlighted unresolved carbon partitioning between assimilatory and catabolic pathways at the formaldehyde-formate node. Only a very few genes and only one enzyme with a predicted function in C1 metabolism, a homolog of the formaldehyde oxidation enzyme ( fae1-2 ), showed a significant change in expression in La-growth conditions. The CS-GSM predictions agreed with the experimental measurements under the assumption that the Fae1-2 is a part of the tetrahydrofolate-linked pathway. The cellular roles of the tungsten (W)-dependent formate dehydrogenase ( fdhAB ) and fae homologs ( fae1-2 and fae3 ) were investigated via mutagenesis. The phenotype of the f dhAB mutant followed the model prediction. Furthermore, a more significant reduction of the biomass yield was observed during growth in La-supplemented media, confirming a higher flux through formate. M. alcaliphilum 20Z R mutants lacking fae1-2 did not display any significant defects in methane or methanol-dependent growth. However, contrary to fae1, the fae1-2 homolog failed to restore the formaldehyde-activating enzyme function in complementation tests. Overall, the presented data suggest that the developed computational workflow supports the reconstruction and validation of CS-GSM networks of non-model microbes. IMPORTANCE The interrogation of various types of data is a routine strategy to explore the relationship between genotype and phenotype. An efficient approach for integrating and cross-comparing experimental multi-scale data in the context of whole-genome-based metabolic network reconstruction becomes a powerful tool that facilitates fundamental and applied research discoveries. The present study describes the reconstruction of a context-specific (CS) model for the methane-utilizing bacterium, Methylotuvimicrobium alcaliphilum 20Z R . M. alcaliphilum 20Z R is becoming an attractive microbial platform for the production of biofuels, chemicals, pharmaceuticals, and bio-sorbents for capturing atmospheric methane. We demonstrate that this pipeline can help reconstruct metabolic models that are similar to manually curated networks. Furthermore, the model is able to highlight previously overlooked pathways, thus advancing fundamental knowledge of non-model microbial systems or promoting their development toward biotechnological or environmental implementations.

Kulyashov, M. A.↗
DOE OSTI2026

Degradation Mode Identification by Photocarrier Lifetime Spectroscopy on Devices and Test Structures

In this presentation, I examine the basic concepts of the device physics that can be used to distinguish various degradation and recovery modes on a cell level. The known degradation modes (bulk LeTID and LID, UVID, etc.) are due to defects and impurities that cause the photocarrier recombination according to Shockley-Reed-Hall (SRH) statistics. The SRH recombination rate strongly depends on the balance of electron and hole capture rates into the defects, which in turn, are governed by their local concentrations. The strongest recombination takes place at approximately equal concentrations of electrons and holes, while at low injection conditions (when one type of carrier dominates) the SRH recombination is suppressed. For cell degradation modes that affect the passivated interface (UVID, H-induced TOPCon contact degradation) the defects are at the interface under low-injection conditions due to either high local doping or the adjacent built-in charge in the dielectric. This mode is characterized by changes in the "diode prefactor" J01 slope in the inverse lifetime-injection level curve. In contrast, bulk degradation (LeTID, LID) affects bulk lifetime, with J01 slope unchanged. Carrier lifetime - injection level plots therefore serve as clear indicators of different degradation modes and are shown by experimental examples.

14 SOLAR ENERGY↗
DOE OSTI2025

Concurrent two-way coupling of global and local models across internal boundaries with non-matching discretizations

Coupling local and global models enables efficient simulation of multiscale systems, where global models capture large-scale behavior and local models, with enhanced physics, resolve finer details over a smaller region. Here, this paper presents a mathematically consistent method for coupling physics-based models of varying fidelity across adjacent, non-overlapping subdomains, even when discretizations do not match at the immersed interdomain interfaces. Incompressible Navier-Stokes equations (NSE) constitute the global model while residual-based turbulence model serves as the local high-fidelity model. In addition, a scalar advection-diffusion equation that models the convection of an active scalar field is appended to the turbulence model in the local domain. This scalar field does not have its complement in the global model, giving rise to unequal number of equations at the immersed boundary between local and global models. Interdomain coupling terms are derived via the Variational Multiscale Discontinuous Galerkin (VMDG) method with new developments in scale representation and efficient fine-scale estimation. While transient laminar flows modeled with NSE in the global domain can be resolved with relatively coarse mesh, turbulent flow calculations in the local model require much finer spatial discretizations as well as smaller time-step for appropriately resolving the turbulent flow physics. The proposed framework also accommodates non-matching meshes at the immersed boundaries. Test problems in 2D and 3D numerically showcase the concurrent two-way coupling of unknown fields across the immersed boundaries. The 3D test presents a case with an unequal number of equations, where the scalar field represents the convection of contaminant concentration. This provides more detailed physics in the local region and highlights its application in climate modeling and atmospheric sciences.

Variational Multiscale Discontinuous Galerkin (VMD↗
NASA NTRS2015

Parabolic Flight Investigation for Advanced Exercise Concept Hardware Hybrid Ultimate Lifting Kit (HULK)

Long-duration space flight poses many hazards to the health of the crew. Among those hazards is the physiological deconditioning of the musculoskeletal and cardiovascular systems due to prolonged exposure to microgravity. To combat this erosion of physical condition space flight may take on the crew, the Human Research Program (HRP) is charged with developing Advanced Exercise Concepts to maintain astronaut health and fitness during long-term missions, while keeping device mass, power, and volume to a minimum. The goal of this effort is to preserve the physical capability of the crew to perform mission critical tasks in transit and during planetary surface operations. The HULK is a pneumatic-based exercise system, which provides both resistive and aerobic modes to protect against human deconditioning in microgravity. Its design targeted the International Space Station (ISS) Advanced Resistive Exercise Device (ARED) high level performance characteristics and provides up to 600 foot pounds resitive loading with the capability to allow for eccentric to concentric (E:C) ratios of higher than 1:1 through a DC motor assist component. The device's rowing mode allows for high cadence aerobic activity. The HULK parabolic flight campaign, conducted through the NASA Flight Opportunities Program at Ellington Field, resulted in the creation of device specific data sets including low fidelity motion capture, accelerometry and both inline and ground reaction forces. These data provide a critical link in understanding how to vibration isolate the device in both ISS and space transit applications. Secondarily, the study of human exercise and associated body kinematics in microgravity allows for more complete understanding of human to machine interface designs to allow for maximum functionality of the device in microgravity.

countermeasures↗
NASA NTRS2017

Exploration Medical System Technical Development

The Exploration Medical Capability (ExMC) Element systems engineering goals include defining the technical system needed to implement exploration medical capabilities for Mars. This past year, scenarios captured in the medical system concept of operations laid the foundation for systems engineering technical development work. The systems engineering team analyzed scenario content to identify interactions between the medical system, crewmembers, the exploration vehicle, and the ground system. This enabled the definition of functions the medical system must provide and interfaces to crewmembers and other systems. These analyses additionally lead to the development of a conceptual medical system architecture. The work supports the ExMC community-wide understanding of the functional exploration needs to be met by the medical system, the subsequent development of medical system requirements, and the system verification and validation approach utilizing terrestrial analogs and precursor exploration missions.

McGuire, K.↗
NASA NTRS2020

Medics: Medical Decision Support System for Long-Duration Space Exploration

The Autonomous Medical Operations (AMO) group at NASA Ames is developing a “medical decision support system” to enable astronauts on long-duration exploration missions to operate autonomously. The system will support clinical actions by providing medical interpretation advice and procedural recommendations during emergent care and clinical work performed by crew. The current state of development of the system, called MedICS (Medical Interpretation Classification and Segmentation) includes two separate aspects: a set of machine learning diagnostic models trained to analyze organ images and patient health records, and an interface to ultrasound diagnostic hardware and to medical repositories. Three sets of images of different organs and medical records were utilized for training machine learning models for various analyses, as follows: 1. Pneumothorax condition (collapsed lung). The trained model provides a positive or negative diagnosis of the condition. 2. Carotid artery occlusion. The trained model produces a diagnosis of 5 different occlusion levels (including “normal”). 3. Ocular retinal images. The model extracts optic disc pixels (image segmentation). This is a precursor step for advanced autonomous fundus clinical evaluation algorithms to be implemented in FY20. 4. Medical health records. The model produces a differential diagnosis for any particular individual, based on symptoms and other health and demographic information. A probability is calculated for each of 25 most common conditions. The same model provides the likelihood of survival. All results are provided with a confidence level. Item 1 images were provided by the US Army and were part of a data set for the clinical treatment of injured battlefield soldiers. This condition is relevant to possible space mishaps, due to pressure management issues. Item 2 images were provided by Houston Methodist Hospital, and item 3 health records were acquired from the MIT laboratory of computational physiology. The machine learning technology utilized is deep multilayer networks (Deep Learning), and new models will continue to be produced, as relevant data is made available and specific health needs of astronaut crews are identified. The interfacing aspects of the system include a GUI for running the different models, and retrieving and storing data, as well as support for integration with an augmented reality (AR) system deployed at JSC by Tietronix Software Inc. (HoloLens). The AR system provides guidance for the placement of an ultrasound transducer that captures images to be sent to the MedICS system for diagnosis. The image captured and the associated diagnosis appear in the technician’s AR visual display.

Colombano, Silvano↗
NASA NTRS2018

An “EPIIC” Vision to Evolve Project Integration, Innovation, and Collaboration with Broad Impact for How NASA Executes Complex Projects

Evolving Project Integration, Innovation, and Collaboration (EPIIC) is a vision defined to transform the way projects manage information to support real-time decisions, capture best practices and lessons learned, perform assessments, and manage risk across a portfolio of projects. The foundational project management needs for data and information will be revolutionized through innovations on how we manage and access that data, implement configuration control, and certify compliance. The embedded intelligence of new interactive data interfaces integrate technical and programmatic data such that near real time analytics can be accomplished to more efficiently and accurately complete systems engineering and project management tasks. The system-wide data analytics that are integrated into customized data interfaces allows the growing team of engineers and managers required to develop and implement major NASA missions the ability to access authoritative source(s) of system information while greatly reducing the labor required to complete system assessments. This would allow, for example, much of what is accomplished in a scheduled design review to take place as needed, between any team members, at any time. An intelligent data interface that rigorously integrates systems engineering and project management information in near real time can provide substantially greater insight for systems engineers, project managers, and the large diverse teams required to complete a complex project. System engineers, programmatic personnel (those who focus on cost, schedule, and risk), the technical engineering disciplines, and project management can realize immediate benefit from the shared vision described herein. Implementation of the vision also enables significant improvements in the performance of the engineered system being developed.

Moreland, Robert J.↗
NASA NTRS2022

Hybrid Kinetic Model of the Interaction Between the Dense Plasma Clouds and Magnetospheric Plasma on Large Time and Spatial Scales, and Comparison With MMS Observations

We present a new simulation results of the cloud dynamics in the ambient magnetospheric plasma on the large time and spatial scales. It was assumed that these impulsive structures observed by the MMS spacecraft originally were created because of the reconnection at the magnetopause. Our new 3-D hybrid kinetic modeling on the large time and spatial scales captures several of these processes: an excitation of the electromagnetic waves (whistler and shear-Alfvén waves) and plasma instabilities (mirror and flute); a formation of shock waves, and collapsing diamagnetic cavity; particle acceleration. A strong overshoot in plasma density profile was observed in the modeling and MMS observation at the interface between the cloud and magnetospheric plasma. The cloud expansion into ambient magnetospheric plasma causes the flute waves connected with excitation of the Rayleigh-Taylor instability observed at the overshoot in plasma density profile across the external magnetic field. The modeling demonstrates a formation of the whistler waves at the initial stage which propagate in the external magnetic field direction. At the later stage, a formation of shear-Alfvén waves was observed

A. S. Lipatov↗
DOE OSTI2024

Meshfree Methods

Meshfree methods have undergone substantial development and have received much attention in the last two decades. This new family of numerical methods is designed to inherit the main advantages of the finite element method such as compact supports of shape functions and good approximation properties while, at the same time, overcome the main disadvantages of the finite element method caused by the mesh dependence. The meshfree methods share a common feature that no mesh is needed and shape functions are constructed from sets of points, thus eliminating the need for time consuming mesh generation. The most significant advantage of meshfree methods is the flexibility in customizing approximation functions for desired regularity and for capturing essential physics and features of the particular problems of interest. Adaptivity formulation and multiple-scale solution strategies also can be implemented with relative ease. It has become clear that the meshfree methods provide considerable advantages over the conventional finite element methods in solving problems involving moving discontinuities, evolving material interfaces, multiple-scale phenomena, large material distortion and structural deformation, and fracture and damage processes. This Chapter gives an overview of many classes of meshfree methods, with more detailed discussions on Smoothed Particle Hydrodynamics (SPH), the Reproducing Kernel Particle Method (RKPM), Peridynamics (PD), the Material Point Method (MPM), as well as their applications in various challenging engineering problems.2

Chen, Jiun-Shyan↗
DOE OSTI2023

Visual Style Elements in Human–System Interface Design for Nuclear Power Operations: Does Style Affect Performance and Preference?

As the world increasingly adopts renewable and sustainable energy systems, transitionary solutions include nuclear power, which currently provides 20% of the United States’ electricity and is the largest single source of carbon-free electricity generation. Advanced reactors are a critical component of a carbon-free mixed energy portfolio that require careful design of first-of-a-kind control rooms. The application of Human Factors Engineering (HFE) is essential for scientific and iterative testing of novel human–system interface (HSI) concepts to ensure effective, efficient, and safe plant operations. Microworlds are simulators that use simplified physics models and control systems to distill nuclear power operations into essential functions. HFE scientists used the Rancor Microworld Simulator to obtain preference and performance metrics for novel and traditional static HSI design styles. Participants comprised advanced reactor company employees and nuclear industry consultants. A mixture of quantitative and qualitative data was captured. There was a preference for the basic graphical style that included high contrast and traditional color scheme elements. No single HSI design outperformed the others, and the participants did not perform better using their preferred HSI style. We report this experiment is the first in a series of HFE testing for HSIs in advanced reactor control room development. Clear user preferences emerged for elements within static displays. The cutting-edge neumorphic style was the least preferred. Future directions include tests of dynamic displays. HFE is used in evaluating and designing HSI devices that will improve the efficiency and safety of advanced nuclear power operations.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Microscopic and Macroscopic Characterization of Grain Boundary Energy and Strength in Silicon Carbide via Machine-Learning Techniques

Predicting the properties of grain boundaries poses a challenge because of the complex relationships between structural and chemical attributes both at the atomic and continuum scales. Grain boundary systems are typically characterized by parameters used to classify local atomic arrangements in order to extract features such as grain boundary energy or grain boundary strength. The present work utilizes a combination of high-throughput atomistic simulations, macroscopic and microscopic descriptors, and machine-learning techniques to characterize the energy and strength of silicon carbide grain boundaries. Additionally, a diverse data set of symmetric tilt and twist grain boundaries are described using macroscopic metrics such as misorientation, the alignment of critical low-index planes, and the Schmid factor, but also in terms of microscopic metrics, by quantifying the local atomic structure and chemistry at the interface. These descriptors are used to create random-forest regression models, allowing for their relative importance to the grain boundary energy and decohesion stress to be better understood. Results show that while the energetics of the grain boundary were best described using the microscopic descriptors, the ability of the macroscopic descriptors to reasonably predict grain boundaries with low energy suggests a link between the crystallographic orientation and the resultant atomic structure that forms at the grain boundary within this regime. For grain boundary strength, neither microscopic nor macroscopic descriptors were able to fully capture the response individually. However, when both descriptor sets were utilized, the decohesion stress of the grain boundary could be accurately predicted. These results highlight the importance of considering both macroscopic and microscopic factors when constructing constitutive models for grain boundary systems, which has significant implications for both understanding the fundamental mechanisms at work and the ability to bridge length scales.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Insight into pseudo-film-boiling in supercritical water under simplified interfacial conditions

The focus of this paper is the physics of supercritical water film boiling through the simulation of natural convection of supercritical water in a rectangular cavity. It has been widely believed that above a fluid's critical point, only one phase exists. However, recent research has indicated the existence of distinct gas-like and liquid-like regions separated by the Widom line, which is the locus of the maxima of the specific heat. Along the Widom line, density decreases sixfold, viscosity drops by a factor of two, while specific heat spikes by an order of magnitude. These variations, specifically in density and viscosity, produce a thick pseudo-interface and flow dynamics behavior akin to film-boiling, denoted here as pseudo-two-phase flow dynamics. When the cavity is heated from the bottom, a pseudo-film of gas-like fluid is formed at the heated wall, and the flow complexity evolves, characterized by the formation of multiple vortices. Results demonstrate the ability of modern conjugate heat transfer computational fluid dynamics to capture the pseudo two-phase regime, with the formation of a pseudo-film at the heated wall. Further, the boiling curve is studied, showing an increase in heat flux with an increase in the temperature differential between the wall and the pseudo-critical temperature. Furthermore, results also show a previously uncharacterized instability, where the convection cells in the cavity oscillate and can flip directions under certain conditions.

Computational fluid dynamics↗
DOE OSTI2018

Simulation INsight and Analysis

Sina is a tool set for modern scientific data management that provides flexible, light-weight support of non-bulk data capture for retention in and queries against SQL and noSQL data stores. HPC simulations traditionally maintain their data in files. Extracting data of interest for subsequent analysis then requires the time-consuming process of traversing directories and scraping data from files in a variety of formats. Sina facilitates capturing relevant data during execution or post-processing of simulation runs for retention in and queries from a modern data store. The tools are sufficiently general to allow for the inclusion of new fields as scientists learn more about their data. Libraries, currently in C++ and Python, and a command line interface (CLI) are provided. Sina's flexibility starts with a general schema, in JSON, for the collection of non-bulk simulation data. JSON provides a flexible, human-readable representation of the data that of interest. Sina currently has a C++ library for simulations to write data to and read from a schema-compliant file for subsequent ingestion into one of the supported data stores. However, applications are free to write their data directly into a schema-compliant file. Python packages provide data ingestion, management, query, and export capabilities. A command line interface (CLI) provides simplified access to these features. A common application programming interface (API) is used to maintain and query data in any of the supported data stores, which are currently limited to SQL and Apache Cassandra (a column store). Tutorials, demonstrations, and examples illustrate aspects of the process using scripts and Jupyter notebooks.

Pauli, EstebanT↗
DOE OSTI2024

Materials data science using CRADLE: A distributed, data-centric approach

Abstract There is a paradigm shift towards data-centric AI, where model efficacy relies on quality, unified data. The common research analytics and data lifecycle environment (CRADLE™) is an infrastructure and framework that supports a data-centric paradigm and materials data science at scale through heterogeneous data management, elastic scaling, and accessible interfaces. We demonstrate CRADLE’s capabilities through five materials science studies: phase identification in X-ray diffraction, defect segmentation in X-ray computed tomography, polymer crystallization analysis in atomic force microscopy, feature extraction from additive manufacturing, and geospatial data fusion. CRADLE catalyzes scalable, reproducible insights to transform how data is captured, stored, and analyzed. Graphical abstract

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2020

A Deformed Geometry Synthesis Technique for Determining Stacking and Cryogenically Induced Preloads for the Space Launch System

The Space Launch System (SLS) stacking and Core Stage (CS) fueling induce significant preloads that contribute to the liftoff pad separation “twang”. To accurately capture this, an approach is required that can replicate the physics of all SLS physical stacking steps, CS cryogenic shrinkage, associated geometric nonlinearities, and the transient behavior and decay of the preloads with changing boundary conditions as the vehicle separates from the pad. The Deformed Geometry Synthesis (DGS) approach presented here satisfies the above requirements. DGS determines induced preloads by modeling components in their deformed geometry states and then enforcing compatibility by closing the resulting “deadbands”. DGS seamlessly integrates into the multibody modal synthesis framework and does not require the use of artificial external loads to enforce preloads or post-processing steps to remove their influence. Since DGS iterates to solve for the deformed state inclusive of geometric nonlinearities, running linearized parametrics to exercise different potential orientations of ball jointed struts that connect the CS to Boosters for cryo-shrinkage analyses is entirely avoided. Relative to the transient behavior and decay of stacking and cryo-induced preloads with SLS liftoff pad separation, this is an area of considerable interest to the SLS program. To capture this in the most accurate way possible, DGS algorithms are designed to work with Henkel-Mar nonlinear pad separation algorithms which operate on the separating longitudinal and lateral degrees of freedom (DoFs) between the vehicle and the pad. As the separating DoFs release, in whatever manner as dictated by the interface geometries, interface loads and interface flexibilities as well as the external loading on the vehicle, the subject preloads generate a complex twang/decay time-trace as dictated by the physics of the problem. This paper presents DGS numerical verification against the closed-form solution for Timoshenko’s 3 ball-jointed strut preload problem. This problem is then extended by the authors to the geometric nonlinear case where DGS is compared to the Newton-Raphson solution of the nonlinear equations. Next, DGS is utilized to solve the SLS stacking and cryogenic shrinkage coupled loads analyses. Finally, Henkel-Mar pad separation simulations are executed that isolate the impact of the induced preloads’ twang and decay characteristics.

Space Launch System↗
DOE OSTI2020

Reconciling Work Functions and Adsorption Enthalpies for Implicit Solvent Models: A Pt (111)/Water Interface Case Study

Implicit solvent models are a computationally efficient method of representing solid/liquid interfaces prevalent in electrocatalysis, energy storage, and materials science. However, electronic structure changes induced at the metallic surface by the dielectric continuum are not fully understood. To address this, we perform DFT calculations for the Pt(111)/water interface, in order to compare Poisson–Boltzmann continuum solvation methods with ab initio molecular dynamics (AIMD) simulations of explicit solvent. We show that the implicit solvent cavity can be parametrized in terms of the electric dipole moment change at the equilibrated explicit Pt/water interface to obtain the potential of zero charge (PZC). We also compare the accuracy of aqueous enthalpies of adsorption of phenol on Pt(111) using geometry and charge density based dielectric cavitation methods. The ability to parametrize the cavity according to individual atoms, as afforded in the geometry based approach, is key to obtaining accurate enthalpy changes of adsorption under aqueous conditions. Additionally, we show that the electronic structure changes induced by explicit solvent and our proposed implicit solvent parametrization scheme yield comparable density difference profiles and d-band projected density of states. We therefore demonstrate the capability of implicit solvent approaches to capture both the energetics of adsorption processes and the main electronic effects of aqueous solvent on the metallic surface. Therefore, this work provides a scheme for computationally efficient simulations of interfacial processes for applications in areas such as heterogeneous catalysis and electrochemistry.

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

Probing Electrolyte Influence on CO 2 Reduction in Aprotic Solvents

Selective CO 2 capture and electrochemical conversion are important tools in the fight against climate change. Industrially, CO 2 is captured using a variety of aprotic solvents due to their high CO 2 solubility. However, most research efforts on electrochemical CO 2 conversion use aqueous media and are plagued by competing hydrogen evolution reaction (HER) from water breakdown. Fortunately, aprotic solvents can circumvent HER, making it important to develop strategies that enable integrated CO 2 capture and conversion. However, the influence of ion solvation and solvent selection within nonaqueous electrolytes for efficient and selective CO 2 reduction is unclear. In this work, we show that the bulk solvation behavior within the nonaqueous electrolyte can control the CO2 reduction reaction and product distribution occurring at the catalyst-electrolyte interface. We study different tetrabutylammonium (TBA) salts in two electrolyte systems with glyme ethers (e.g., 1,2 dimethoxyethane or DME) and dimethyl sulfoxide (DMSO) as a low and high dielectric constant medium, respectively. Using spectroscopic tools, we quantify the fraction of ion pairs that forms within the electrolyte. Also, we show how ion pair formation is prevalent in DME and is dependent on the anion type. More importantly, we show that as ion pair formation decreases within the electrolyte, CO 2 current densities increase, and a higher CO Faradaic efficiency is observed at low overpotentials. Meanwhile, in an electrolyte medium where the ion pair fraction does not change with the anion type (such as in DMSO), a smaller influence of solvation is observed on CO 2 current densities and product distribution. By directly coupling bulk solvation to interfacial reactions and product distribution, we showcase the importance and utility of controlling the reaction microenvironment in tuning the electrocatalytic reaction pathways. Insights gained from this work will enable novel electrolyte designs for efficient and selective CO 2 conversion to desired fuels and chemicals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗