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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Structural Tuning of Self‐Conductive Polymer as Gas Diffusion Layer for Electrocatalytic Reactions at High Current

Electrocatalytic conversions offer a promising route for sustainable chemical production using renewable energy. Gas diffusion layers (GDLs) enable selective product formation at high current densities but suffer from electrolyte flooding, and polytetrafluoroethylene (PTFE)-based GDLs typically require metal conductive layers, which constrain catalyst development. A recently developed GDL configuration, electropolymerized poly(3,4-ethylenedioxythiophene) (PEDOT)-coated PTFE, demonstrates notable flooding resistance, but suffers from gas diffusion limitations at elevated currents due to limited gas diffusion through the PEDOT layer. Here, different dopants in PEDOT are exploited to modify the physical properties and enhance gas transport. ClO 4 − -doped PEDOT exhibits superior performance due to optimized physical structure, leading to increased gas permeance and faradaic efficiency (FE) for CO production during electrocatalytic CO 2 reduction. Further optimization of coverage and thickness achieved by adjusting charge density led to an optimal configuration at 33 mC cm −2 . This GDL supports various metal electrocatalysts and demonstrates FE CO of > 90% for over 150 h at −200 mA cm −2 using a commercial silver electrocatalyst. This work highlights the importance of GDL engineering in enhancing performance and durability for long-term electrocatalytic processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Anode-Design Strategies for Improved Performance of Polymer-Electrolyte Fuel Cells with Ultra-Thin Electrodes

Here, we report results of systematic, holistic, diagnostic, and cell studies to elucidate the mechanistic role of the experimentally determined influence of the anode gas-diffusion layer (GDL) on the performance of ultra-thin electrode polymer-electrolyte fuel cells, which can further enable fuel-cell market penetration. Measurements of product water balance and in situ neutron imaging of operational membrane-electrode-assembly water profiles demonstrate how improved performance is due to a novel anode GDL fiber-density modulated structure at the micrometer scale that removes water preferentially out of the anode, a key strategy to manage water in these cells. The banded structure results in low transport-resistance pathways, which affect water-droplet removal from the GDL surface. This interfacial effect is unexpectedly shown to be critical for decreasing overall water holdup throughout the cell. Finally, these studies demonstrate a new material paradigm for understanding and controlling fuel-cell water management and related high-power technologies or electrodes where multiphase flow occurs.

25 ENERGY STORAGE↗
DOE OSTI2024

Differentiable modeling and optimization of non-aqueous Li-based battery electrolyte solutions using geometric deep learning

Electrolytes play a critical role in designing next-generation battery systems, by allowing efficient ion transfer, preventing charge transfer, and stabilizing electrode-electrolyte interfaces. In this work, we develop a differentiable geometric deep learning (GDL) model for chemical mixtures, DiffMix, which is applied in guiding robotic experimentation and optimization towards fast charging battery electrolytes. In particular, we extend mixture thermodynamic and transport laws by creating GDL-learnable physical coefficients. We evaluate our model with mixture thermodynamics and ion transport properties, where we show improved prediction accuracy and model robustness of Diff-Mix than its purely data-driven variants. Furthermore, with a robotic experimentation setup, Clio, we improve ionic conductivity of electrolytes by over 18.8% within 10 experimental steps, via differentiable optimization built on DiffMix gradients. By combining GDL, mixture physics laws, and robotic experimentation, DiffMix expands the predictive modeling methods for chemical mixtures and enables efficient optimization in large chemical spaces.

25 - ENERGY STORAGE↗
DOE OSTI2023

Local microenvironment tuning induces switching between electrochemical CO 2 reduction pathways

Gas diffusion layers (GDL) have become a critical component in electrochemical CO 2 reduction (CO 2 R) systems because they can enable high current densities needed for industrially relevant productivity. Besides this function, it is often assumed that the choice of catalyst and electrolyte play much more important roles than the GDL in influencing the observed product selectivity. Here, we show that tuning of the GDL pore size can be used to control the local microenvironment of the catalyst and hence, effect significant changes in catalytic outcomes. This concept is demonstrated using sputtered Ag films on hydrophobic PTFE substrates with 6 different pore sizes. Although Ag is known to be a predominantly CO generating catalyst, we find that smaller pore sizes favor the generation of formate up to a faradaic efficiency of 43%. Combined experimental and simulation results show that this is due to the influence of the pore size on CO 2 mass transport, which alters the local pH at the electrode, resulting in reaction pathway switching between CO and formate. Importantly, our results highlight the importance of the local microenvironment as an experimental knob that can be rationally tuned for controlling product selectivity: a key consideration in the design of CO 2 R systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Genus-wide assessment of lignocellulose utilization in the extremely thermophilic Caldicellulosiruptor by genomic, pan-genomic and metagenomic analysis

Metagenomic data from Obsidian Pool (Yellowstone National Park, USA) and thirteen genome sequences were used to re-assess genus-wide biodiversity for the extremely thermophilic Caldicellulosiruptor . The updated core-genome contains 1,401 ortholog groups (average genome size for thirteen species = 2,516 genes). The pan-genome, which remains open with a revised total of 3,493 ortholog groups, encodes a variety of multi-domain glycoside hydrolases (GH). These include three cellulases with GH48 domains that are co-located in the Glucan Degradation Locus (GDL) and are specific determinants for microcrystalline cellulose utilization. Three recently sequenced species, Caldicellulosiruptor sp. str. Rt8.B8 (re-named here Caldicellulosiruptor morganii ), Thermoanaerobacter cellulolyticus str. NA10 (re-named here Caldicellulosiruptor naganoensis NA10), and Caldicellulosiruptor sp. str. Wai35.B1 (re-named here Caldicellulosiruptor danielii ) degraded Avicel and lignocellulose (switchgrass). C. morganii was more efficient than C. bescii in this regard and differed from the other twelve species examined here, both based on genome content and organization and in the specific domain features of conserved GHs. Metagenomic analysis of lignocellulose-enriched samples from Obsidian Pool revealed limited new information on genus biodiversity. Enrichments yielded genomic signatures closely related to Caldicellulosiruptor obsidiansis , but there was also evidence for other thermophilic fermentative anaerobes ( Caldanaerobacter , Fervidobacterium , Caloramator , and Clostridium ). One enrichment, containing 89.7% Caldicellulosiruptor and 9.7% Caloramator , had a capacity for switchgrass solubilization comparable to C. bescii . These results refine the known biodiversity of Caldicellulosiruptor and indicate that microcrystalline cellulose degradation at temperatures above 70°C, based on current information, is limited to certain members of this genus that produce GH48 domain-containing enzymes. The genus Caldicellulosiruptor contains the most thermophilic bacteria capable of lignocellulose deconstruction and are promising candidates for consolidated bioprocessing for the production of biofuels and bio-based chemicals. The focus here is on the extant capability of this genus for plant biomass degradation and the extent to which this can be inferred from the core and pan-genomes, based on analysis of thirteen species and metagenomic sequence information from environmental samples. Key to microcrystalline hydrolysis is the content of the Glucan Degradation Locus (GDL), a set of genes encoding glycoside hydrolases (GH), several of which have GH48 and family 3 carbohydrate binding module domains, that function as primary cellulases. Resolving the relationship between the GDL and lignocellulose degradation will inform efforts to identify more prolific members of the genus and to develop metabolic engineering strategies to improve this characteristic

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Development of Innovative Gas Diffusion Layers for Polymer Electrolyte Membrane Fuel Cells: Final Technical Report

This phase 1 program accomplished its primary goal of reducing the mass transport resistance (MTR) within the gas diffusion layer (GDL). The improvement in MTR was achieved by (1) the reduction of carbonaceous binder content, (2) reduced penetration of the microporous layer (MPL) into the substrate, and (3) a controlled size and frequency of micro-cracks within the MPL. Of these factors, (1) the amount of carbonaceous binder within the GDL substrate showed the greatest potential for a reduction of MTR and should be the focus for future development, preferably in concert with a commercial partner to ensure the material can meet the market requirements.

microporous layer (MPL)↗
DOE OSTI2021

A review of functions, attributes, properties and measurements for the quality control of proton exchange membrane fuel cell components

Quality control (QC) is an essential part of fuel cell technology industrialization, providing means to reduce cost of components, enhancing the reliability of the final product, and offering specification guidance for new entrants in the supply chain. The membrane electrode assembly (MEA), including membrane, catalyst layer (CL), and gas diffusion layer (GDL), as well as bipolar plate (BP), are key components of a proton exchange membrane (PEM) fuel cell, and the attributes of each component strongly correlate with the cell performance and longevity. To ensure the quality of the fuel cell, it is of great importance to characterize the properties with respect to the standardization of component/sub-component specifications. In collaboration with the fuel cell industry, this work aims at establishing compendiums of attributes, or so-called books of attributes, of key fuel cell components for the QC of PEM fuel cells through reviewing, identifying, categorizing, and prioritizing the main attributes/properties that determine their functionalities. The books of attributes for the major PEM fuel cell components include catalyst coated membrane (CCM) as a sub-assembly, GDL, and BP. To address the full spectrum of fuel cell components, gaskets and sub-gaskets are also included.

25 ENERGY STORAGE↗
DOE OSTI2022

Understanding the E balance for water management in hydroxide exchange membrane fuel cells

As a key challenge for hydroxide exchange membrane fuel cells (HEMFCs), understanding water management deeply is critical for performance and durability improvement. Here, in this work, we show that the balance between water generation and phase-change-induced (PCI) flow is the main factor controlling cell voltage over a wide range of conditions where the cells are vulnerable to severe flooding. The regulation of flooding by heat generation can be reflected by a stable voltage with increase of current density in the polarization curve. This PCI balance voltage (E balance ), which determines the shape of polarization curve, is modeled as a function of cell operating conditions and gas diffusion layer (GDL) properties. Temperature, pressure, and thermal conductivity of GDL were found important for tuning the level of E balance , both in HEMFCs and proton exchange membrane fuel cells. The understanding of E balance will help to generate strategies for resolving flooding in HEMFCs, and it offers a new perspective for polarization curve interpretation.

25 ENERGY STORAGE↗
DOE OSTI2011

Isothermal Ice Crystallization Kinetics in the Gas-Diffusion Layer of a Proton-Exchange-Membrane Fuel Cell

Nucleation and growth of ice in the fibrous gas-diffusion layer (GDL) of a proton-exchange membrane fuel cell (PEMFC) are studied using isothermal differential scanning calorimetry (DSC). Isothermal crystallization rates and pseudo-steady-state nucleation rates are obtained as a function of subcooling from heat-flow and induction-time measurements. Kinetics of ice nucleation and growth are studied at two polytetrafluoroethylene (PTFE) loadings (0 and 10 wt %) in a commercial GDL for temperatures between 240 and 273 K. A nonlinear ice-crystallization rate expression is developed using Johnson–Mehl–Avrami–Kolmogorov (JMAK) theory, in which the heat-transfer-limited growth rate is determined from the moving-boundary Stefan problem. Induction times follow a Poisson distribution and increase upon addition of PTFE, indicating that nucleation occurs more slowly on a hydrophobic fiber than on a hydrophilic fiber. The determined nucleation rates and induction times follow expected trends from classical nucleation theory. Finally, a validated rate expression is now available for predicting ice-crystallization kinetics in GDLs.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Quartet-based inference is statistically consistent under the unified duplication-loss-coalescence model

Abstract Motivation The classic multispecies coalescent (MSC) model provides the means for theoretical justification of incomplete lineage sorting-aware species tree inference methods. This has motivated an extensive body of work on phylogenetic methods that are statistically consistent under MSC. One such particularly popular method is ASTRAL, a quartet-based species tree inference method. Novel studies suggest that ASTRAL also performs well when given multi-locus gene trees in simulation studies. Further, Legried et al. recently demonstrated that ASTRAL is statistically consistent under the gene duplication and loss model (GDL). GDL is prevalent in evolutionary histories and is the first core process in the powerful duplication-loss-coalescence evolutionary model (DLCoal) by Rasmussen and Kellis. Results In this work, we prove that ASTRAL is statistically consistent under the general DLCoal model. Therefore, our result supports the empirical evidence from the simulation-based studies. More broadly, we prove that the quartet-based inference approach is statistically consistent under DLCoal. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Multi-Centrality Graph Spectral Decompositions and Their Application to Cyber Intrusion Detection

Many modern datasets can be represented as graphs and hence spectral decompositions such as graph principal component analysis (PCA) can be useful. Distinct from previous graph decomposition approaches based on subspace projection of a single topological feature, e.g., the centered graph adjacency matrix (graph Laplacian), we propose spectral decomposition approaches to graph PCA and graph dictionary learning that integrate multiple features, including graph walk statistics, centrality measures and graph distances to reference nodes. In this paper we propose a new PCA method for single graph analysis, called multi-centrality graph PCA (MC-GPCA), and a new dictionary learning method for ensembles of graphs, called multi-centrality graph dictionary learning (MC-GDL), both based on spectral decomposition of multi-centrality matrices. As an application to cyber intrusion detection, MC-GPCA can be an effective indicator of anomalous connectivity pattern and MC-GDL can provide discriminative basis for attack classification.

cybersecurity↗
DOE OSTI2021

Understanding Carbon Dioxide Transfer in Direct Methanol Fuel Cells Using a Pore-Scale Model

Abstract The gas flow of carbon dioxide from the catalyst layer (CL) through the microporous layer (MPL) and gas diffusion layer (GDL) has great impacts on the water and fuel management in direct methanol fuel cells (DMFCs). This work has developed a liquid–vapor two-phase model considering the counter flow of carbon dioxide gas, methanol, and water liquid solution in porous electrodes of DMFC. The model simulation includes the capillary pressure as well as the pressure drop due to flow resistance through the fuel cell components. The pressure drop of carbon dioxide flow is found to be about two to three orders of magnitude higher than the pressure drop of the liquid flow. The big difference between liquid and gas pressure drops can be explained by two reasons: volume flowrate of gas is three orders of magnitude higher than that of liquid; only a small fraction of pores (<5%) in hydrophilic fuel cell components are available for gas flow. Model results indicate that the gas pressure and the mass transfer resistance of liquid and gas are more sensitive to the pore size distribution than the thickness of porous components. To buildup high gas pressure and high mass transfer resistance of liquid, the MPL and CL should avoid micro-cracks during manufacture. Distributions of pore size and wettability of the GDL and MPL have been designed to reduce the methanol crossover and improve fuel efficiency. The model results provide design guidance to obtain superior DMFC performance using highly concentrated methanol solutions or even pure methanol.

Electrochemistry↗
DOE OSTI2020

Investigating Liquid Water Transport in Different Pore Structure of Gas Diffusion Layers for PEMFC Using Lattice Boltzmann Method

Proton exchange membrane fuel cells (PEMFC) require a gas diffusion layer (GDL) to aid in the transport of liquid fuel to the catalyst layer. In this work, direct modeling using the Lattice Boltzmann Method (LBM) was applied to X-ray CT scans of four different carbon gas diffusion layers to understand the mass transport properties through the samples. Three injection orientations were used to study local saturation levels, water evolution through the sample, and mass transport behavior at breakthrough conditions. The LBM, combined with computational fluid dynamic modeling techniques, can accurately predict liquid saturation at the macro and micro scale, which provides more insight into the mass transport phenomena through the GDL. The change of pore structure and orientation in both the in-plane and through-plane determines the path that liquid water must take, which could aid or impact PEMFC performance. The outcomes from this work will also benefit any research that needs knowledge of internal mass transport qualities of gas diffusion media.

Sepe, M.↗
DOE OSTI2022

Study of Cathode Gas Diffusion Architecture for Improved Oxygen Transport in Hydroxide Exchange Membrane Fuel Cells

The high pH environment in hydroxide exchange membrane fuel cells (HEMFCs) has the potential to reach lower costs than the current proton exchange membrane fuel cells (PEMFCs), the incumbent technology. A significant difference between HEMFCs and PEMFCs is the location of water production within the cell. In PEMFCs, the water is produced on the cathode, limiting oxygen transport. In HEMFCs, the water is produced on the anode where the fuel is pure hydrogen. This allows the cathode to be optimized for oxygen transport without the presence of excess liquid water. Limiting current analysis, a technique previously used in PEMFCs, is adopted in HEMFCs to evaluate the oxygen mass transport resistances for different sections of the cathode. Through elimination of the microporous layer (MPL), gas diffusion layer (GDL), and traditional flow field and using porous nickel foam for gas distribution, the transport resistance at an operating condition of 150 kPa(g) and with the cell temperature at 80 °C was decreased from 112 s m −1 to 48 s m −1 , effectively halved. The optimal configuration for performance was found with Ni foam and a GDL, eliminating the MPL and traditional flow field, which vastly improved oxygen transport while maintaining adequate electrical contact with the cathode catalyst layer.

25 ENERGY STORAGE↗
DOE OSTI2012

Tank 26F-2F Evaporator Study

Tank 26F supernate sample was sent by Savannah River Remediation to Savannah River National Laboratory for evaporation test to help understand the underlying cause of the recent gravity drain line (GDL) pluggage during operation of the 2F Evaporator system. The supernate sample was characterized prior to the evaporation test. The evaporation test involved boiling the supernate in an open beaker until the density of the concentrate (evaporation product) was between 1.4 to 1.5 g/mL. It was followed by filtering and washing of the precipitated solids with deionized water. The concentrate supernate (or concentrate filtrate), the damp unwashed precipitated solids, and the wash filtrates were characterized. All the precipitated solids dissolved during water washing. A semi-quantitative X-ray diffraction (XRD) analysis on the unwashed precipitated solids revealed their composition. All the compounds with the exception of silica (silicon oxide) are known to be readily soluble in water. Hence, their dissolution during water washing is not unexpected. Even though silica is a sparingly water-soluble compound, its dissolution is also not surprising. This stems from its small fraction in the solids as a whole and also its relative freshness. Assuming similar supernate characteristics, flushing the GDL with water (preferably warm) should facilitate dissolution and removal of future pluggage events as long as build up/aging of the sparingly soluble constituent (silica) is limited. On the other hand, since the amount of silica formed is relatively small, it is quite possible dissolution of the more soluble larger fraction will cause disintegration or fragmentation of the sparingly soluble smaller fraction (that may be embedded in the larger soluble solid mass) and allow its removal via suspension in the flushing water.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Determination of the crystalline structure of scale solids from the 16H evaporator gravity drain line to tank 38H

August 2015, scale solids from the 16H Evaporator Gravity Drain Line (GDL) to the Tank 38H were delivered to SRNL for analysis. The desired analytical goal was to identify and confirm the crystalline structure of the scale material and determine if the form of the aluminosilicate mineral was consistent with previous analysis of the scale material from the GDL.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Evaluation of The Risk of Solids Formation in the 2H Evaporator System

Savannah River Remediation (SRR) Tank Farm Engineering requested technical assistance from the Savannah River National Laboratory (SRNL) to troubleshoot recent and rapid plugging of the 2H Evaporator gravity drain line (GDL) to the Evaporator Drop Tank (currently Tank 38) with unwanted solids of unknown composition and to evaluate the risk of solids formation in the 2H Evaporator system moving forward. The GDL to Tank 38 recently plugged twice within hours of startup, resulting in a one-month shutdown both times. SRNL was asked to simulate current and historic (2016 to 2017) aqueous feed chemistries in the Evaporator Feed Tank (currently Tank 43) using the OLI Systems software to determine the mass of precipitated salts that would be expected to form under 2H Evaporator operating conditions for a range of concentration factors (i.e., evaporator overhead-to-feed volume ratio). A recommended evaporator concentration factor was determined based on the current Tank 43 feed composition to minimize solids formation and extend the time between shutdowns. Current and historic (2016 to 2017) aqueous chemistries in Tank 38 were also evaluated for completeness.

42 ENGINEERING↗