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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Surface Charge and Electrostatic Spin Crossover Effects in CoN 4 Electrocatalysts

Carbon materials doped with nitrogen and 3d transition metals have attracted a great deal of interest for catalyzing electrochemical reactions such as water splitting, oxygen reduction, and carbon dioxide reduction. Here, we employed density functional theory to study Co–N-doped carbon as electrocatalysts for the oxygen reduction and oxygen evolution reactions. Specifically, we investigated the interplay among adsorption energies, the spin state of the CoN 4 active center, and the applied potential. We found that adsorption energies strongly depend on both the applied potential and the spin state of the Co center. Furthermore, spin state transitions induced by the applied potential also play an important role in determining the adsorption energies. Here, this effect originates from a different potential of zero charge and capacitance of each spin state.

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

Smarter building start – A distributed solution

A significant focus of research and new technologies for reducing energy use in buildings is on operating the systems more efficiently during the times when the systems are active. However, there is a large potential for energy savings in determining the periods when the systems should or should not be active. This scheduling aspect of operation is often overlooked even though relatively simple solutions can unlock substantial energy savings. In this paper we describe a smart building start (SBS) algorithm that considers multiple zones in a building to determine individual schedules for room controllers as well as the central systems based on solving a simple optimization problem. Application of the SBS algorithm to multiple interconnected systems enables a staggered start-up that minimizes peak loads and also ensures comfort is within a target range with minimal system run time. The SBS algorithm extends the capability of traditional optimal start and is designed to be simple to deploy and robust. Simulation results as well as results from tests in a real building with a VAV system are presented. The presented algorithm is applicable to any type of building with a zonal or multi-zone HVAC system. To function, it needs to be able to change setpoints in rooms and monitor room temperatures, as well as, if desired, turn the central system on or off.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Kinetic Probes of the Origin of Activity in MOF-Based C–H Oxidation Catalysis

The development of homogeneous catalysis is enabled by the availability of a rich toolkit of kinetics experiments, such as the Hgdrop test, that differentiate catalytic activity at ligand-supported metal complexes from potential heterogeneous catalysts derived from decomposition of molecular species. Metal-organic frameworks (MOFs) have garnered significant attention as platforms for catalysis at site-isolated, interstitial catalyst sites. Unlike homogeneous catalysis, relatively few strategies have been advanced to evaluate the origin of catalytic activity in MOF-promoted reactions. Many of the MOFs that have been examined as potential catalysts are comprised of molecular constituents that represent viable catalysts in the absence of the extended MOF lattice, and thus interfacial sites and leached homogeneous species represent potential sources of catalyst activity. Here, we demonstrate that analysis of deuterium kinetic isotope effects (KIEs) and olefin epoxidation diastereoselectivity provides probes of the origin of catalytic activity in MOF-promoted oxidation reactions. These analyses support involvement of lattice-based Fe sites in the turnover-limiting step of C–H activation with Fe-MOF-74-based materials (i.e., the MOF functions as a bona fide catalyst) and evidence that Cu 2 -based MOF MIL-125-Cu 2 O 2 functions as a solid-state initiator for solution-phase oxidation chemistry and is not involved in the turnover limiting step (i.e., the MOF does not function as a catalyst for substrate functionalization). furthermore, we anticipate that the simple experiments described here will provide a valuable tool for clarifying the role of MOFs in C–H oxidation reactions.

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

Activation and Assembly of Plasmonic-Magnetic Nanosurfactants for Encapsulation and Triggered Release

Multifunctional surfactants hold great potentials in catalysis, separation, and biomedicine. Highly active plasmonic-magnetic nanosurfactants are developed through a novel acid activation treatment of Au–Fe 3 O 4 dumbbell nanocrystals. The activation step significantly boosts nanosurfactant surface energy and enables the strong adsorption at interfaces, which reduces the interfacial energy one order of magnitude. Mediated through the adsorption at the emulsion interfaces, the nanosurfactants are further constructed into free-standing hierarchical structures, including capsules, inverse capsules, and two-dimensional sheets. The nanosurfactant orientation and assembly structures follow the same packing parameter principles of surfactant molecules. Furthermore, nanosurfactants demonstrate the capability to disperse and encapsulate homogeneous nanoparticles and small molecules without adding any molecular surfactants. The assembled structures are responsive to external magnetic field, and triggered release is achieved using an infrared laser by taking advantage of the enhanced surface plasmon resonance of nanosurfactant assemblies. Finally, solvent and pH changes are also utilized to achieve the cargo release.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

cAMP binding to closed pacemaker ion channels is non-cooperative

Electrical activity in the brain and heart depends on rhythmic generation of action potentials by pacemaker ion channels (HCN) whose activity is regulated by cAMP binding. Previous work has uncovered evidence for both positive and negative cooperativity in cAMP binding, but such bulk measurements suffer from limited parameter resolution. Efforts to eliminate this ambiguity using single-molecule techniques have been hampered by the inability to directly monitor binding of individual ligand molecules to membrane receptors at physiological concentrations. Here we overcome these challenges using nanophotonic zero-mode waveguides4 to directly resolve binding dynamics of individual ligands to multimeric HCN1 and HCN2 ion channels. We show that cAMP binds independently to all four subunits when the pore is closed, despite a subsequent conformational isomerization to a flip state at each site. The different dynamics in binding and isomerization are likely to underlie physiologically distinct responses of each isoform to cAMP and provide direct validation of the ligand-induced flip-state model. Furthermore, this approach for observing stepwise binding in multimeric proteins at physiologically relevant concentrations can directly probe binding allostery at single-molecule resolution in other intact membrane proteins and receptors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Geospatial assessment of the economic opportunity for reforestation in Maryland, USA

Afforestation and reforestation have the potential to provide effective climate mitigation through forest carbon sequestration. Strategic reforestation activities, which account for both carbon sequestration potential (CSP) and economic opportunity, can provide attractive options for policymakers who must manage competing social and environmental goals. In particular, forest carbon pricing can incentivize reforestation on private land, but this may require landholders to forego other profits. Here, we utilize an ambitious geospatial approach to quantify economic opportunities for reforestation in the state of Maryland (USA) based on high-resolution remoting sensing, ecosystem modeling, and economic analysis. Our results identify spatially-explicit areas of economic opportunity where the potential revenue from forest carbon outcompetes the expected profit of existing cropland at the hectare scale. Specifically, we find that under a baseline economic scenario of 20 dollars per ton of carbon (5% rental rate) and decadal average crop profitability, a transition to forest on agricultural land would be more profitable than 23.2% of cropland in Maryland under a 20-year land-use commitment. Accounting for variations in carbon and crop pricing, 5.5% to 55.4% of cropland would be immediately outcompeted by expected forest carbon revenue, with the potential for an additional 0.5% to 10.6% of outcompeted cropland within 20 years. Under the baseline economic scenario, an annual allocation of $5.8 million towards a carbon rental program could protect 6.93 Tg C (2.2% of the state’s total CSP) on reforested croplands. This moderate yearly cost is equal to 9.7% of Maryland’s average annual auction proceeds from participation in the Regional Greenhouse Gas Initiative (between 2014-2018), and 19.3% of the average annual subsidy payments for corn, soy, and wheat allocated over the same period. This methodological approach may be useful for state governments, not-for-profit organizations, or regional climate initiatives interested in identifying strategic areas for reforestation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Tunable Oxygen Reduction Electrocatalysis by Phenazine-Modified Carbons (Final Report)

This project aims to systematically investigate the fundamental interfacial chemistry that underlies the four-electron, four-proton oxygen reduction reaction (ORR) mediated by heteroatom-doped graphitic carbon electrodes. Heteroatom-doped (Fe, N, etc.) graphitic carbons have emerged as a rich class of materials that are promising ORR catalysts in low temperature fuel cells because of their earth-abundant elements, extremely low cost, environmental harmlessness, and high tolerance to impurities in the fuel stream. However, despite decades of research, systematic efforts to improve the activity, selectivity, and durability of these catalysts has been hampered both by a complex heterogeneous distribution of potential N- and Fe-dopant active sites and by the inability to tune the local electronic structure and environment of the active site with molecular precision. Understanding the fundamental chemistry that influences the turnover-limiting and selectivity determining steps for ORR and other multielectron/multiproton electrocatalytic transformations requires new and innovative methods to prepare heteroatom active sites with molecular precision on carbon surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Geographic Shift and Environment Change of U.S. Tornado Activities in a Warming Climate

Even with ever-increasing societal interest in tornado activities engendering catastrophes of loss of life and property damage, the long-term change in the geographic location and environment of tornado activity centers over the last six decades (1954–2018), and its relationship with climate warming in the U.S., is still unknown or not robustly proved scientifically. Utilizing discriminant analysis, we show a statistically significant geographic shift of U.S. tornado activity center (i.e., Tornado Alley) under warming conditions, and we identify five major areas of tornado activity in the new Tornado Alley that were not identified previously. By contrasting warm versus cold years, we demonstrate that the shift of relative warm centers is coupled with the shifts in low pressure and tornado activity centers. The warm and moist air carried by low-level flow from the Gulf of Mexico combined with upward motion acts to fuel convection over the tornado activity centers. Employing composite analyses using high resolution reanalysis data, we further demonstrate that high tornado activities in the U.S. are associated with stronger cyclonic circulation and baroclinicity than low tornado activities, and the high tornado activities are coupled with stronger low-level wind shear, stronger upward motion, and higher convective available potential energy (CAPE) than low tornado activities. The composite differences between high-event and low-event years of tornado activity are identified for the first time in terms of wind shear, upward motion, CAPE, cyclonic circulation and baroclinicity, although some of these environmental variables favorable for tornado development have been discussed in previous studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Developing an Active Learning algorithm for learning Bayesian classifiers under the Multiple Instance Learning scenario

In the Multiple Instance Learning scenario, the training data consists of instances grouped into bags, and each bag is labelled with whether it is positive, i.e. contains at least one positive instance. First, Active Learning, in which additional labels can be iteratively requested, has the potential to allow more accurate classifiers to be learned with less labels. Active Learning has been applied to the Multiple Instance Learning under two settings: when bag labels of unlabelled bags can be requested, and when instance labels within bags known to be positive can be requested. Second, Bayesian Active learning methods have the potential to learn accurate classifiers with few labels, because they explicitly track the classifier uncertainty and can thus address its knowledge gaps. Yet, there does not exist any Bayesian Active Learning method for the Multiple Instance Learning Scenario. In this work, we develop the first such method. We develop a Bayesian classifier for the Multiple Instance Learning scenario, show how it can be efficiently used for Bayesian Active Learning, and perform experiments assessing its performance. While its performance exceeds that when no Active Learning is used, it is sometimes better, sometimes worse than the naive baseline of uncertainty sampling, depending on the situation. This suggests future work: building more customizable Bayesian Active Learning methods for the Multiple Instance Scenario, customizable to whether bag or instance label accuracy is targeted, and the labeling budget.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Improved Rate for the Oxygen Reduction Reaction in a Sulfuric Acid Electrolyte using a Pt(111) Surface Modified with Melamine

The feasible commercialization of alkaline, phosphoric acid and polymer electrolyte membrane fuel cells depends on the development of oxygen reduction reaction (ORR) electrocatalysts with improved activity, stability, and selectivity. The rational design of surfaces to ensure these improved ORR catalytic requirements relies on the so-called "descriptors" (e.g., the role of covalent and noncovalent interactions on platinum surface active sites for ORR). Here, we demonstrate that through the molecular adsorption of melamine onto the Pt(111) surface [Pt(111)-M ad ], the activity can be improved by a factor of 20 compared to bare Pt(111) for the ORR in a strongly adsorbing sulfuric acid solution. Additionally, the M ad moieties act as "surface-blocking bodies," selectively hindering the adsorption of (bi)sulfate anions (well-known poisoning spectator of the Pt(111) active sites) while the ORR is unhindered. This modified surface is further demonstrated to exhibit improved chemical stability relative to Pt(111) patterned with cyanide species (CN ad ), previously shown by our group to have a similar ORR activity increase compared to bare Pt(111) in a sulfuric acid electrolyte, with Pt(111)-M ad retaining a greater than ninefold higher ORR activity relative to bare Pt(111) after extensive potential cycling as compared to a greater than threefold higher activity retained on a CN ad -covered Pt(111) surface. We suggest that the higher stability of the Pt(111)-M ad interface stems from melamine's ability to form intermolecular hydrogen bonds, which effectively turns the melamine molecules into larger macromolecular entities with multiple anchoring sites and thus more difficult to remove.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Flash Communication: Flexibility of a Biologically Inspired Ligand Framework for Intramolecular C–H Activation

High-valent iron complexes play a crucial role in the oxidation of organic substrates, especially in C–H bond functionalization reactions in biology. This paper investigates the reactivity of nonporphyrin tripodal ligands featuring a secondary coordination sphere, focusing on their prospective ability to stabilize high-valent iron-oxo species. Using NMR spectroscopy and X-ray crystallography, we detail the formation of an Fe(III)-alkoxide complex through intramolecular C–H bond activation, providing insight into the potential transient formation of a high-valent iron-oxo intermediate. While attempts to observe an Fe(IV)-oxo complex were unsuccessful, our findings underscore the significance of the ligand electronic environment in stabilizing reactive iron species for C–H bond activation.

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

A Review of the Multiple-Readout Concept and Its Application in an Integrally Active Calorimeter

A comprehensive multi-jet physics program is anticipated for experiments at future colliders. Key physics processes necessitate detectors that can distinguish signals from W and Z bosons and the Higgs boson. Typical examples include channels with or pairs and processes involving new physics in those cases where neutral particles must be disentangled from charged ones due to the presence of W or Z bosons in their final states. Such a physics program demands calorimetric energy resolution at or beyond the limits of traditional calorimetric techniques. Multiple-readout calorimetry, which aims to reduce fluctuations in energy measurements of hadronic showers, is a promising approach. The first part of this article reviews dual- and triple-readout calorimetry within a mathematical framework describing the underlying compensating mechanism. The second part proposes a potential implementation using an integrally active and total absorption detector. This model serves as the basis for several Monte Carlo studies, illustrating how the response of a multiple-readout calorimeter depends on construction parameters. Among the layouts considered, one configuration operating in triple-readout mode shows the potential to achieve an energy resolution approaching .

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Block Copolymer-Templated Synthesis of Fe–Ni–Co-Modified Nanoporous Alumina Films

Despite intense interest in the catalytic potential of transition metal oxide heterostructures, originating from their large surface area and tunable chemistry, the fabrication of well-defined multicomponent oxide coatings with controlled architectures remains challenging. Here, we demonstrate a simple and effective swelling-assisted sequential infiltration synthesis (SIS) strategy to fabricate hierarchically porous multicomponent metal-oxide electrocatalysts with tunable bimetallic composition. A combination of solution-based infiltration (SBI) of transition metals, iron (Fe), nickel (Ni), and cobalt (Co), into a block copolymer (PS73-b-P4VP28) template, followed by vapor-phase infiltration of alumina using sequential infiltration synthesis (SIS), was employed to synthesize porous, robust, conformal and transparent multicomponent metal-oxide coatings like Fe/AlO x , Fe+Ni/AlO x , and Fe+Co/AlO x . Electrochemical assessments for the oxygen evolution reaction (OER) in a 0.1 M KOH electrolyte demonstrated that the Fe+Ni/AlO x composite exhibited markedly superior catalytic activity, achieving an impressive onset potential of 1.41 V and a peak current density of 3.29 mA/cm 2 . This superior activity reflects the well-known synergistic effect of alloying transition metals with a trace of Fe, which facilitates OER kinetics. Overall, our approach offers a versatile and scalable path towards the design of stable and efficient catalysts with tunable nanostructures, opening new possibilities for a wide range of electrochemical energy applications.

conformal films↗
DOE OSTI2026

CAZyme domain architectures suggest fine-scale functional differentiation among anaerobic fungi and bacteria during lignocellulose conversion to volatile fatty acids

Anaerobic fermentation with microbial communities (microbiomes) is an emerging platform for conversion of lignocellulosic biomass to biofuels and bioproducts. The process relies on diverse anaerobic microbes that interact to deconstruct and convert lignocellulosic biomass into a range of products, such as volatile fatty acids (VFAs), which can be achieved by arresting methanogenesis during fermentation. However, defining the distinct functional roles played by various fungi and bacteria during anaerobic biodegradation remains poorly understood. Here, we performed parallel enrichment experiments from cow faeces, goat faeces, and anaerobic digester sludge, selecting for fungal or bacterial dominated communities that convert sorghum biomass into VFAs. Subsequently we reconstructed metabolic networks across these enrichments based on recovered bacterial metagenome-assembled genomes (MAGs) and fungal isolate genomes and profiled their metabolic activity using metatranscriptomics to identify potential functional niches. Our findings implicate diverse bacteria affiliated with the Bacteroidales and Lachnospiraceae in the direct conversion of lignocellulosic biomass to propionate and butyrate, respectively, whereas Neocallimastix-dominated fungal enrichments converted lignocellulose to lactate, acetate and formate. Analysis of carbohydrate-active enzymes (CAZymes) revealed fine-scale differences between microbes that expressed unique multi-functional enzymes linking two or more CAZymes together with distinct carbohydrate binding motifs, implicating lignocellulose structure as a key driver of selection and niche differentiation. Most of these multi-functional enzymes localized complementary degradation functions together, likely conferring synergistic degradation effects within and between microbiome members. We anticipate that these findings will help inform efforts to develop synthetic microbiomes with tailored functionality for low-cost conversion of lignocellulosic biomass to fuels and bio-based chemicals.

Lawson, Christopher E [University of Toronto;]↗
DOE OSTI2025

Multifunctional Catalysts for the Tandem Reactions of Oxygenates

Industrially-relevant catalytic reactions rarely consist of a simple sequence of elementary steps. Moreover, kinetic coupling of multiple reactions on a catalyst surface is highly desired for process intensification and improved energy efficiency for large scale chemical transformations. The shifting landscape of hydrocarbon chemical feedstocks in the US also motivates research on the selective conversion of more complex molecules. One desirable type of catalytic reaction is the reduction of carboxylic acids that are produced from biomass feedstocks to their corresponding alcohols. The proposed research explores the fundamental importance of hydrogen spillover on a multifunctional catalyst for carboxylic acid reduction with H 2 composed of metal particles coupled to metal oxide particles. Recent work has demonstrated the excellent performance of supported tungsten oxide clusters for carboxylic acid reduction, but only after they are promoted with a late transition metal such as palladium. Elucidating the active state of the catalyst and the associated reaction mechanism for acid reduction on that active state are the overall goals of the proposed project and successful completion will enable future design of efficient multifunctional catalysts. The critically important role of the metal promoter is hypothesized to be its ability to dissociate H2 and spillover atomic H to the support. Although hydrogen spillover is a well-recognized phenomenon in catalysis, its role in both catalyst activation and catalytic turnover are still unresolved. The study combined materials synthesis, characterization, reactivity testing, and molecular simulations, to explore the effect of hydrogen chemical potential on the formation of the active catalytic sites and on the steady state catalytic reduction of carboxylic acid. Varying the hydrogen chemical potential through modification of the gas conditions, support composition, and metal loading to modulated the structure and catalytic performance of the reducible metal oxide. Dual function catalysts containing supported Pd and WO x species co-located on a non-reducible carrier (silica) and a reducible carrier (titania) were synthesized and characterized by electron microscopy, temperature-programmed reduction, and chemisorption. Spectroscopic methods such as X-ray absorption and UV-vis were also used to evaluate the catalysts, which were used in the reduction of propionic acid to aldehyde and alcohol. Quantum chemical calculations, including ab initio phase diagrams provided molecular insights into the H spillover phenomenon.

09 BIOMASS FUELS↗
DOE OSTI2022

Towards replacement of animal tests with in vitro assays: a gene expression biomarker predicts in vitro and in vivo estrogen receptor activity

High-throughput transcriptomics (HTTr) has the potential to support efforts to reduce or replace some animal tests. In past studies, we described a computational approach utilizing a gene expression biomarker consisting of 46 genes to predict estrogen receptor (ER) activity after chemical exposure in ER-positive human breast cancer cells including the MCF-7 cell line. We hypothesized that the biomarker model could identify ER activities of chemicals examined by Endocrine Disruptor Screening Program (EDSP) Tier 1 screening assays in which transcript profiles of the same chemicals were examined in MCF-7 cells. For the 62 chemicals examined including 5 chemicals examined in this study using RNA-Seq, the ER biomarker model accuracy was 1) 97% for in vitro reference chemicals, 2) 76–85% for guideline uterotrophic assays, and 3) 87–88% for guideline and nonguideline uterotrophic assays. For the same chemicals, these accuracies were similar or slightly better than those of the ToxCast ER model based on 18 in vitro assays. The performance of the ER biomarker model indicates that HTTr interpreted using the ER biomarker correctly identifies active and inactive ER reference chemicals. Finally, as part of the HTTr screening program the approach could rapidly identify chemicals with potential ER bioactivities for additional screening and testing.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Custom-trained Machine-learning Interatomic Potentials: ZnCl2 Aqueous Solution

This dataset was generated using an iterative active-learning strategy implemented in the ArcaNN software package (https://github.com/arcann-chem/arcann_training) to train machine-learning interatomic potentials for aqueous ZnCl2 solutions. Each active-learning cycle consisted of three stages: training, exploration, and labeling. The initial training set combined configurations generated in this work from enhanced-sampling ab initio molecular dynamics simulations with configurations from a previously reported neural-network-potential study of aqueous ZnCl2. The enhanced-sampling ab initio molecular dynamics simulations involved Zn–Cl separation and the chloride coordination number around Zn²? as collective variables. These configurations served as the seed dataset. Subsequent active-learning cycles expanded the training set by identifying and labeling configurations that were poorly represented by the current models, thereby improving coverage of ion-association states and changes in local coordination and charge-state environments relevant to the solution free-energy landscape. For all selected configurations, single-point calculations of the total energies and atomic forces were performed within density functional theory using the CP2K Quickstep module. Reference calculations employed the revPBE-D3 and r2SCAN exchange-correlation functionals. Motivated by recent work on aqueous Zn²?, the main revPBE calculations omitted D3 dispersion contributions involving Zn²?, while retaining the D3 correction for water and chloride. For comparison, fully dispersion-corrected revPBE-D3 reference calculations were also performed, with D3 applied to all species, including Zn²?. Valence electrons were treated explicitly, while core electrons were represented using norm-conserving Goedecker–Teter–Hutter pseudopotentials. The wave functions were expanded using the mixed Gaussian-and-plane-wave scheme with TZV2P-MOLOPT basis sets for all elements and a 600 Ry auxiliary plane-wave cutoff for the electron density. Self-consistent-field convergence was accelerated using the orbital-transformation and Direct Inversion in the Iterative Subspace algorithms, with a convergence threshold of 10?6. All single-point calculations were performed in periodic orthorhombic cells. The CELL_REF keyword in CP2K was used to define a fixed reference cell with a box length of 25 Å. This treatment ensured a consistent reference for configurations extracted from NpT trajectories with fluctuating cell dimensions. The resulting DFT energies and atomic forces constitute the ground-truth labels used to train the MLIPs. The resulting MLIP was trained for aqueous ZnCl2 solutions spanning concentrations from 0 to 30 molal and a broad pH range, from strongly acidic to strongly basic conditions. Representative examples of configurations included in the MLIP training dataset are provided below. These include 1) Representative configurations from the dataset labeled at the revPBE-D3 level, with D3 dispersion interactions involving Zn2+ excluded (revPBE-wo-D3). 2) Representative configurations from the dataset labeled at the fully dispersion-corrected revPBE-D3 level, with D3 interactions applied to all species, including Zn2+ (revPBE-D3). 3) Representative configurations from the dataset labeled at the r2SCAN level of theory (r2SCAN).

Dinpajooh, Mohammadhasan [Pacific Northwest Nation↗
DOE OSTI2021

Stability of Atomically Dispersed Fe–N–C ORR Catalyst in Polymer Electrolyte Fuel Cell Environment

We have investigated the durability of a platinum group metal (PGM-)free Fe–N–C catalyst in which the Fe sites are atomically dispersed (AD), and found it to be quite stable in standard accelerated stress test (AST) cycles normally used for low-PGM catalysts: a square wave with 0.6 V lower potential limit (LPL)—0.95 V upper potential limit (UPL) with 3-s holds at UPL and LPL in H 2 /N 2 , at 1.5 atm, 80 °C and 100% RH. Considering the metrics normally employed to characterize the durability of the low-PGM catalysts after 30,000 AST cycles, this PGM-free catalyst lost <50% catalyst activity, <50% H 2 /air performance at 0.8 V, and 40 mV at 1.5 A cm -2 . However, it is less stable in H 2 /air, losing ~50% catalyst activity after just 7.5 h of polarization measurements (load cycles). In combined cycles, the majority of the loss in catalyst activity occurred during the load cycles in H 2 /air rather than AST cycles in H 2 /N 2 . We have concluded that, unlike low-PGM catalysts that lose electrochemically active surface area (ECSA) through potential cycling-induced processes, (AD)Fe–N–C catalysts degrade by processes associated with the presence of oxygen.

25 ENERGY STORAGE↗