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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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26 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Pt Nanoparticles on Atomic-Metal-Rich Carbon for Heavy-Duty Fuel Cell Catalysts: Durability Enhancement and Degradation Behavior in Membrane Electrode Assemblies

Proton exchange membrane fuel cells (PEMFCs) are a promising zero-emission power source for heavy-duty vehicles (HDVs). However, long-term durability of up to 25,000 h is challenging because current carbon support, catalyst, membrane, and ionomer developed for traditional light-duty vehicles cannot meet the stringent requirement. Therefore, understanding catalyst degradation mechanisms under the HDV condition is crucial for rationally designing highly active and durable platinum group metal (PGM) catalysts for high-performance membrane electrode assemblies (MEAs). Herein, we report a PGM catalyst consisting of platinum nanoparticles with a high content (40 wt %) on atomic-metal-site (e.g., MnN 4 )-rich carbon support. MEAs with the Pt (40 wt %)/Mn–N–C cathode catalyst achieved significantly enhanced performance and durability, generating 1.41 A cm –2 at 0.7 V under HDV conditions (0.25 mgPt cm –2 and 250 kPa abs pressure) and retaining 1.20 A cm –2 after an extended and accelerated stress test up to 150,000 voltage cycles. Electron microscopy studies indicate that most fine Pt nanoparticles are retained on or/and in the carbon support covered with the ionomer throughout the catalyst layer at the end of life. During the long-term stability test, the observed electrochemical active surface area reduction and performance loss primarily result from Pt depletion in the catalyst layer due to Pt dissolution and redeposition at the interface of the cathode and membrane. Importantly, the first-principle density functional theory calculations further reveal a support entrapment effect of the Mn–N–C, in which the MnN 4 site can specifically adsorb the Pt atom and further retard the Pt dissolution and migration, therefore enhancing long-term MEA durability.

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

Rational Design and Synthesis of Hierarchical Porous Mn–N–C Nanoparticles with Atomically Dispersed MnNx Moieties for Highly Efficient Oxygen Reduction Reaction

Developing transition-metal excluding iron and cobalt–nitrogen–carbon (M–N–C) electrocatalysts for the oxygen reduction reaction (ORR) is critical to substantially promote the development of precious-metal-free metal–air batteries and fuel cells. In the work, Mn–N–C nanoparticles with atomically dispersed MnNx moieties were synthesized by pyrolyzing Mn-ion–dual-pyridine coordinated complex, which was obtained via a simple condensation reaction between 2,6-diamino-pyridine and 2,6-diacetyl-pyridine with MnCl 2 as the Mn source. The precursor features with a characteristic structure of dual-pyridine ligand, which possesses a strong coordinating capability for Mn 2+ , facilitating the formation of highly dispersed nitrogen-coordinated Mn sites (MnN x ). Attributed to the highly active atomic MnN x sites, hierarchical pore structure, and high surface area of the Mn–N–C derived from the new precursor, it exhibits outstanding ORR performance in 0.1 M KOH with an almost direct four-electron reaction path and high selectivity of O 2 into H 2 O (low H2O2 production <3.5%). The half-wave potential of Mn–N–C is 0.88 V vs RHE, which is 20 mV higher than that of commercial Pt/C catalyst and reaches to the level of Fe–N–C catalyst obtained by the same method. Meanwhile, the feasibility of Mn–N–C for practical application is validated by its higher-performance power output in Zn–air battery with a maximum power density of 132 mW cm –2 compared to that of Pt/C (121 mW cm –2 ) using the same catalyst loading of 1.0 mg cm –2 . This work develops a convenient route to develop non-Fe or Co–N–C electrocatalyst for the ORR.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Regulating Catalytic Properties and Thermal Stability of Pt and PtCo Intermetallic Fuel-Cell Catalysts via Strong Coupling Effects between Single-Metal Site-Rich Carbon and Pt

Developing low platinum-group-metal (PGM) catalysts for the oxygen reduction reaction (ORR) in proton-exchange membrane fuel cells (PEMFCs) for heavy-duty vehicles (HDVs) remains a great challenge due to the highly demanded power density and long-term durability. Here, this work explores the possible synergistic effect between single Mn site-rich carbon (Mn SA -NC) and Pt nanoparticles, aiming to improve intrinsic activity and stability of PGM catalysts. Density functional theory (DFT) calculations predicted a strong coupling effect between Pt and MnN 4 sites in the carbon support, strengthening their interactions to immobilize Pt nanoparticles during the ORR. The adjacent MnN 4 sites weaken oxygen adsorption at Pt to enhance intrinsic activity. Well-dispersed Pt (2.1 nm) and ordered L1 2 -Pt 3 Co nanoparticles (3.3 nm) were retained on the Mn SA -NC support after indispensable high-temperature annealing up to 800 °C, suggesting enhanced thermal stability. Both PGM catalysts were thoroughly studied in membrane electrode assemblies (MEAs), showing compelling performance and durability. The Pt@Mn SA -NC catalyst achieved a mass activity (MA) of 0.63 A mg Pt –1 at 0.9 V iR-free and maintained 78% of its initial performance after a 30,000-cycle accelerated stress test (AST). The L1 2 -Pt 3 Co@Mn SA -NC catalyst accomplished a much higher MA of 0.91 A mg Pt –1 and a current density of 1.63 A cm –2 at 0.7 V under traditional light-duty vehicle (LDV) H 2 –air conditions (150 kPa abs and 0.10 mg Pt cm –2 ). Furthermore, the same catalyst in an HDV MEA (250 kPa abs and 0.20 mg Pt cm –2 ) delivered 1.75 A cm –2 at 0.7 V, only losing 18% performance after 90,000 cycles of the AST, demonstrating great potential to meet the DOE targets.

25 ENERGY STORAGE↗
DOE OSTI2021

Learning curves for drug response prediction in cancer cell lines

Motivated by the size and availability of cell line drug sensitivity data, researchers have been developing machine learning (ML) models for predicting drug response to advance cancer treatment. As drug sensitivity studies continue generating drug response data, a common question is whether the generalization performance of existing prediction models can be further improved with more training data. We utilize empirical learning curves for evaluating and comparing the data scaling properties of two neural networks (NNs) and two gradient boosting decision tree (GBDT) models trained on four cell line drug screening datasets. The learning curves are accurately fitted to a power law model, providing a framework for assessing the data scaling behavior of these models. The curves demonstrate that no single model dominates in terms of prediction performance across all datasets and training sizes, thus suggesting that the actual shape of these curves depends on the unique pair of an ML model and a dataset. The multi-input NN (mNN), in which gene expressions of cancer cells and molecular drug descriptors are input into separate subnetworks, outperforms a single-input NN (sNN), where the cell and drug features are concatenated for the input layer. In contrast, a GBDT with hyperparameter tuning exhibits superior performance as compared with both NNs at the lower range of training set sizes for two of the tested datasets, whereas the mNN consistently performs better at the higher range of training sizes. Moreover, the trajectory of the curves suggests that increasing the sample size is expected to further improve prediction scores of both NNs. These observations demonstrate the benefit of using learning curves to evaluate prediction models, providing a broader perspective on the overall data scaling characteristics. A fitted power law learning curve provides a forward-looking metric for analyzing prediction performance and can serve as a co-design tool to guide experimental biologists and computational scientists in the design of future experiments in prospective research studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Synthesis and Physical Properties of Manganese Chromium Nitride Thin Films Grown via Molecular Beam Epitaxy

Here, we demonstrate the ability to grow epitaxial thin films of manganese–chromium nitride (Mn x Cr 1–x N) across the entire composition range on magnesium oxide (MgO) (1 0 0) surfaces by molecular beam epitaxy. By independently controlling the ratio of the atomic fluxes of manganese and chromium, the compositional dependence of structural and electrical transport properties is determined. Soft X-ray absorption shows that the valence states of Cr( 3+ ) and Mn( 3+ ) remain identical among these MnCrN epitaxial films. The metallic transport behavior of binary manganese nitride (MnN) and chromium nitride (CrN) is suppressed in the ternary alloys. Changes in room temperature electrical resistivity of up to 100 times and 5 orders of magnitude at cryogenic temperatures are observed. This work expands the variety of nitride compounds available for epitaxial integration and could provide additional flexibility for the development of metal–semiconductor–insulator junctions for spintronic devices.

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

Methanol tolerance of atomically dispersed single metal site catalysts: mechanistic understanding and high-performance direct methanol fuel cells

Proton-exchange membrane fuel cells (PEMFCs) and direct methanol fuel cells (DMFCs) are promising power sources from portable electronic devices to vehicles. The high-cost issue of these low-temperature fuel cells can be primarily addressed by using platinum-group metal (PGM)-free oxygen reduction reaction (ORR) catalysts, in particular atomically dispersed metal–nitrogen–carbon (M–N–C, M = Fe, Co, Mn). Furthermore, a significant advantage of M–N–C catalysts is their superior methanol tolerance over Pt, which can mitigate the methanol cross-over effect and offer great potential of using a higher concentration of methanol in DMFCs. In this work, we investigated the ORR catalytic properties of M–N–C catalysts in methanol-containing acidic electrolytes via experiments and density functional theory (DFT) calculations. FeN 4 sites demonstrated the highest methanol tolerance ability when compared to metal-free pyridinic N, CoN 4 , and MnN 4 active sites. The methanol adsorption on MN 4 sites is even strengthened when electrode potentials are applied during the ORR. The negative influence of methanol adsorption becomes significant for methanol concentrations higher than 2.0 M. However, the methanol adsorption does not affect the 4e - ORR pathway or chemically destroy the FeN 4 sites. The understanding of the methanol-induced ORR activity loss guides the design of promising M–N–C cathode catalyst in DMFCs. Accordingly, we developed a dual-metal site Fe/Co–N–C catalyst through a combined chemical-doping and adsorption strategy. Instead of generating a possible synergistic effect, the introduced Co atoms in the first doping step act as “scissors” for Zn removal in metal–organic frameworks (MOFs), which is crucial for modifying the porosity of the catalyst and providing more defects for stabilizing the active FeN 4 sites generated in the second adsorption step. The Fe/Co–N–C catalyst significantly improved the ORR catalytic activity and delivered remarkably enhanced peak power densities (i.e., 502 and 135 mW cm -2 ) under H 2 –air and methanol–air conditions, respectively, representing the best performance for both types of fuel cells. Notably, the fundamental understanding of methanol tolerance, along with the encouraging DMFC performance, will open an avenue for the potential application of atomically dispersed M–N–C catalysts in other direct alcohol or ammonia fuel cells.

25 ENERGY STORAGE↗
DOE OSTI2023

Magnetic order in the two-dimensional metal-organic framework manganese pyrazinecarboxylate with Mn-Mn dimers

The magnetic properties of [Mn(pyrazinecarboxylate) 2 ] n , empirical formula C 10 H 6 MnN 4 O 4 , are investigated through susceptibility, heat capacity, and neutron scattering measurements. The structure consists of Mn-Mn dimers linked on a distorted 2D hexagonal structure. The weak out-of-plane interactions create a quasi-2D magnetic material within the larger three-dimensional metal-organic framework structure. Here, we show that this material undergoes a two-stage magnetic transition, related to the low dimensionality of the Mn lattice. First, at 5 K, which is assigned to the initial development of short-range order in the 2D layers. This is followed by long-range order at 3.3 K. Applied field measurements reveal the potential to induce magnetic transitions in moderately small fields of ~2 T. Neutron powder diffraction enabled the determination of a unique magnetic space group P2 1 '/c (No. 14.77) at 1.5 K. This magnetic structure consists of antiferromagnetically coupled Mn-Mn dimers with spins principally along the out-of-plane $a$ axis.

36 MATERIALS SCIENCE↗