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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 91 records · Page 5

Phonon-Assisted Intervalley Scattering Determines Ultrafast Exciton Dynamics in MoSe 2 Bilayers

While valleys (energy extrema) are present in all band structures of solids, their preeminent role in determining exciton resonances and dynamics in atomically thin transition metal dichalcogenides (TMDC) is unique. Using two-dimensional coherent electronic spectroscopy, we find that exciton decoherence occurs on a much faster timescale in MoSe 2 bilayers than that in the monolayers. We further identify two population relaxation channels in the bilayer, a coherent and an incoherent one. Our microscopic model reveals that phonon-emission processes facilitate scattering events from the K valley to other lower-energy Γ and Λ valleys in the bilayer. Our combined experimental and theoretical studies unequivocally establish different microscopic mechanisms that determine exciton quantum dynamics in TMDC monolayers and bilayers. Understanding exciton quantum dynamics provides critical guidance to the manipulation of spin-valley degrees of freedom in TMDC bilayers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Tunable Magnetic and Optical Anisotropy in ZrO 2 ‐Co Vertically Aligned Nanocomposites

Abstract Metamaterials have gained great research interest in recent years owing to their potential for property tunability, multifunctionality, and property coupling. As a new group of self‐assembled thin films, vertically aligned nanocomposite (VAN)‐based hybrid metamaterials have been demonstrated with significant anisotropic physical properties and a broad range of property tailorability, such as optical anisotropy, magnetic anisotropy, hyperbolic dispersion, and enhanced second harmonic generation properties. Herein, self‐assembled ZrO 2 ‐Co nanocomposite films, with high epitaxial quality and ultra‐fine vertically aligned Co nanopillars (with an average diameter of ≈2 nm) embedded in a ZrO 2 matrix, are fabricated using a pulsed laser deposition (PLD) method. The Co pillar density can be effectively tuned by varying the Co concentration in the target, which results in tunable optical properties and magnetic properties. Specifically, a high saturation magnetization of 100 emu cm −3 , strong out‐of‐plane magnetic anisotropy and tailorable magnetization properties are achieved via tuning the Co nanopillar density. Coupled with hyperbolic dispersion of dielectric constant from 950 to 1500 nm in wavelength, plasmonic Co metal nanopillars, and the unique dielectric ZrO 2 matrix, this new nanoscale hybrid metamaterial shows great potential for future integrated optical and magnetic device designs.

36 MATERIALS SCIENCE↗

Calcium-Ion Binding Mediates the Reversible Interconversion of Cis and Trans Peroxido Dicopper Cores

Coupled dinuclear copper oxygen cores (Cu 2 O 2 ) featured in type III copper proteins (hemocyanin, tyrosinase, catechol oxidase) are vital for O 2 transport and substrate oxidation in many organisms. μ-1,2-cis peroxido dicopper cores ( C P) have been proposed as key structures in the early stages of O 2 binding in these proteins; their reversible isomerization to other Cu 2 O 2 cores are directly relevant to enzyme function. Furthermore, despite the relevance of such species to type III copper proteins and the broader interest in the properties and reactivity of bimetallic C P cores in biological and synthetic systems, the properties and reactivity of C P Cu 2 O 2 species remain largely unexplored. Herein, we report the reversible interconversion of μ-1,2-trans peroxido ( T P) and C P dicopper cores. Ca II mediates this process by reversible binding at the Cu 2 O 2 core, highlighting the unique capability for metal-ion binding events to stabilize novel reactive fragments and control O 2 activation in biomimetic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bimetallic Copper/Ruthenium/Osmium Complexes: Observation of Conformational Differences Between the Solution Phase and Solid State by Atomic Pair Distribution Function Analysis

Abstract High‐energy X‐ray scattering and pair distribution function analysis (HEXS/PDF) is a powerful method to reveal the structure of materials lacking long‐range order, but is underutilized for molecular complexes in solution. We demonstrate the application of HEXS/PDF with 0.26 Å resolution to uncover the solution structure of five bimetallic Cu I /Ru II /Os II complexes. HEXS/PDF of each complex in acetonitrile solution confirms the pairwise distances in the local coordination sphere of each metal center as well as the metal⋅⋅⋅metal distances separated by over 12 Å. The metal⋅⋅⋅metal distance detected in solution is compared with that from the crystal structure and molecular models to confirm that distortions to the metal bridging ligand are unique to the solid state. This work presents the first example of observing sub‐Ångström conformational differences by direct comparison of solution phase and solid‐state structures and shows the potential for HEXS/PDF in the determination of solution structure of single molecules.

Xie, Zhu‐Lin↗

Recent Progress in Electrochemical Nitrogen Reduction on Transition Metal Nitrides

Distributed electrochemical nitrogen reduction reaction (ENRR) powered by renewable energy for the on-site production of ammonia is an attractive alternative to the industrial Haber–Bosch process, which is responsible for roughly 2 % of global energy consumption. Here, in this Review, we summarize recent progress in the ENRR catalyzed by transition metal nitrides (TMNs). The unique electronic structures of TMNs make them promising ENRR catalysts for active and selective ammonia production, which have been predicted theoretically and demonstrated experimentally. Reaction pathways and deactivation mechanisms of the ENRR on different TMNs are surveyed, and current understanding of structure-activity relations is discussed. To develop highly active, selective, and stable TMN catalysts for industrial-scale ENRR, membrane electrode assembly configuration is recommended in catalyst evaluation. Furthermore, we highlight the importance of developing mechanistic understanding on ENRR with different operando spectroscopic techniques.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Laser Additive Manufacturing Process Development for Bismuth Telluride Thermoelectric Material

Thermoelectric generators have strong potential for aerospace and aircraft applications. However, traditional manufacturing methods for thermoelectric devices severely limit device adaptability and consequently marketability. Laser powder bed fusion is an additive manufacturing method which shows promising potential for producing thermoelectric devices. Thermoelectric materials pose unique challenges compared to metals because of low thermal conductivity, brittle fracture characteristics, and irregular powder particle morphologies. Herein, we communicate processing procedures to fabricate thermoelectric parts of Bi 2 Te 3 through laser powder bed fusion. In this study, we identify the successful combination of key process parameters—laser power, scan speed, hatch distance, and powder layer thickness—to achieve high-quality parts in terms of density and physical properties, and we demonstrate the impact of process parameter variation on built part quality. While it cannot exclusively determine part quality, the volumetric energy density is a useful guide in deciding process parameters for thermoelectric materials, and the optimal value is between 9 and 11 J/mm 3 for Bi 2 Te 3 . We demonstrate successful fabrication of different freeform geometries of Bi 2 Te 3 powders. The results suggest it is possible to extend this method more broadly to other semiconductor materials, including thermoelectric power generation materials applicable for space applications.

36 MATERIALS SCIENCE↗

Synthesis of High-Quality Mg-MOF-74 Thin Films via Vapor-Assisted Crystallization

The unique features of metal-organic frameworks (MOFs), such as their large surface areas and diversity of structures, makes them suitable to a broad range of applications. One of the most critical enabling technologies for implementing MOF films is the preparation of dense and continuous films that would maximize the performance of the configurations. While formation of crystalline Mg-MOF-74 thin films presents significant challenges, demonstrating large-scale coatings of the MOF, which exhibits the highest CO2 uptake among MOFs at 1 bar and 25 °C, would be particularly beneficial for CO2- related sensing applications. In this work, we demonstrate for the first time high-quality Mg-MOF-74 films synthesized via a vapor-assisted crystallization (VAC) process. The VAC process described herein produces dense and highly crystalline layers of Mg-MOF-74 with a low coefficient of variation (COV) of film thickness below 7%. We first optimized a precursor solution for the VAC process, and then investigated the effects of synthesis temperature, time and droplet volume on the growth, crystallinity and thickness of Mg-MOF-74 films. The porosity of the film was assessed by measuring the CO2 uptake at room temperature and 1 bar. The obtained Mg-MOF-74 films possess a well-defined microporosity, as deduced from CO2 adsorption studies via quartz crystal microbalance (QCM) and comparison with bulk Mg MOF-74 reference data. Furthermore, CO2 cyclic adsorption-desorption experiments on the Mg-MOF-74

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Metal-Coordinated Phthalocyanines as Platform Molecules for Understanding Isolated Metal Sites in the Electrochemical Reduction of CO 2

Single-atom catalysts (SACs) of non-precious transition metals (TMs) often show unique electrochemical performance, including the electrochemical carbon dioxide reduction reaction (CO 2 RR). However, the inhomogeneity in their structures makes it difficult to directly compare SACs of different TM for their CO 2 RR activity, selectivity, and reaction mechanisms. Here, the comparison of isolated TMs (Fe, Co, Ni, Cu, and Zn) is systematically investigated using a series of crystalline molecular catalysts, namely TM-coordinated phthalocyanines (TMPcs), to directly compare the intrinsic role of the TMs with identical local coordination environments on the CO 2 RR performance. The combined experimental measurements, in situ characterization, and density functional theory calculations of TM-Pc catalysts reveal a TM dependent CO 2 RR activity and selectivity, with the free energy difference of ΔG(*HOCO) - ΔG(*CO) being identified as a descriptor for predicting the CO 2 RR performance.

25 ENERGY STORAGE↗

Phonon-exciton Interactions in WSe 2 under a quantizing magnetic field

Strong many-body interaction in two-dimensional transitional metal dichalcogenides provides a unique platform to study the interplay between different quasiparticles, such as prominent phonon replica emission and modified valley-selection rules. A large out-of-plane magnetic field is expected to modify the exciton-phonon interactions by quantizing excitons into discrete Landau levels, which is largely unexplored. Here, we observe the Landau levels originating from phonon-exciton complexes and directly probe exciton-phonon interaction under a quantizing magnetic field. Phonon-exciton interaction lifts the inter-Landau-level transition selection rules for dark trions, manifested by a distinctively different Landau fan pattern compared to bright trions. This allows us to experimentally extract the effective mass of both holes and electrons. The onset of Landau quantization coincides with a significant increase of the valley-Zeeman shift, suggesting strong many-body effects on the phonon-exciton interaction. Our work demonstrates monolayer WSe 2 as an intriguing playground to study phonon-exciton interactions and their interplay with charge, spin, and valley.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Design of lightweight BCC multi-principal element alloys with enhanced hydrogen storage using a machine learning-driven genetic algorithm

Body-centered cubic (BCC) based multi-principal element alloy (MPEA) hydrides have demonstrated significant potential for compact and efficient hydrogen storage. In this work, we first leverage machine learning (ML) models to predict the hydrogen affinity, storage capacity and phase stability of BCC MPEAs, creating a unique hydrogen-to-metal (H/M) predictor for materials with unprecedented performance. We developed a metaheuristic optimizer high-throughput framework by interfacing ML models with a genetic algorithm for the accelerated search of {Mg, Al, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Nb, Mo} based lightweight BCC MPEAs with improved hydrogen storage characteristics. We report five new MPEAs with a predicted gravimetric hydrogen storage capacity of around 3.5 wt% or more, including Cr 0.09 Mg 0.73 Ti 0.18 (4.25 wt% H) and Cr 0.21 Nb 0.11 Ti 0.35 V 0.33 (3.5 wt% H). The electronic structure of the top-performing composition, Cr 0.09 Mg 0.73 Ti 0.18 , was analyzed using density functional theory (DFT) to understand the reasons for its improved hydrogen storage properties compared to TiFe (1.90 wt% H), LaNi 5 (1.37 wt% H) or BCC MPEAs like TiVNbCr (3.70 wt% H). Temperature-dependent molecular dynamics (MD) studies were further performed on optimized BCC MPEAs to qualitatively study hydrogen mobility and analyze the effect of different elemental composition on bulk hydrogen diffusion. Our findings demonstrate how a ML assisted genetic algorithm framework can be used for efficient search of stable, lightweight and cost-effective MPEAs while minimizing the need for expensive ab initio calculations.

DFT↗

Tuning effect of vanadium substitution on the structural and electronic properties of potassium hollandite surfaces

Metal oxide surfaces possess unique properties that are crucial for a wide variety of applications. Herein, density functional theory calculations are performed to study surfaces of potassium hollandite, KMn 8 O 16 , a promising cathode material for electrochemical energy storage, and the vanadium-substituted analog KMn 7 VO 16 . The results show that there is a clear increase in the stability of KMn 8 O 16 with (001) < (110) < (100) or (010), apt to adopt an elongated rod-like morphology. The vanadium (V)-substitution lowers the crystal symmetry and prefers to occupy the surface sites, resulting in electron redistribution and selective tuning of surface energy depending on the surface structures. In particular, the higher stability of substituted V 4+ compared with Mn 4+ ions leads to stabilization of the (001) surface due to the direct interaction of reduced Mn δ+ ions on the surface, while such tuning effect decreases with the increase in surface stability, (110) > (100) and (010). As a result, the KMnO 16 rod is shortened upon V-substitution as observed experimentally, effectively facilitating the ion transport during discharge. The V substituents also introduce stabilization to the defect surfaces resulting from Mn 2+ dissolution during cycling, thereby hindering further structural decay. In conclusion, our study demonstrates the potential tuning effect of V-substitution to promote the ion transport and mitigate the capacity degradation of α-MnO 2 -based materials.

25 ENERGY STORAGE↗

Analysis of SCALE Criticality and Sensitivity Calculations for Reflected HEU Cylinders

The SCALE code package offers multiple nuclear data libraries and sensitivity and uncertainty (S/U) methods supporting and derived from Monte Carlo (MC) transport. The CSAS and TSUNAMI-3D sequences use KENO MC, utilizing either continuous-energy (CE) cross sections or multigroup (MG) cross section libraries. TSUNAMI-3D has two CE calculational methods: the iterated fission probability (IFP) method, and the Contribution-Linked eigenvalue sensitivity/Uncertainty estimation via Tracklength importance CHaracterization (CLUTCH) method. Previous work has shown poor agreement between CLUTCH and confirmatory direct perturbation calculations in specific applications (e.g., fissionable and polyethylene reflectors). The HEU-MET-FAST-084 (HMF-084) International Criticality Safety Benchmark Evaluation Project evaluation consists of 27 cylindrical highly enriched uranium metal cores with 14 unique reflector materials of 0.5 and 1 in. thicknesses. Included in this list of reflector materials are natural uranium and polyethylene. This work utilized SCALE 6.2.4 models of the HMF-084 evaluation, with additional non-physical configurations to test both the MG bias and CLUTCH functionality across a variety of reflector material thicknesses. The evaluation’s use of concentric cylinders allowed for examination of several MG self-shielding methods: infinite homogenous, cylindrical, and spherical. The results indicate that the use of polyethylene reflectors with CLUTCH is not fundamentally impossible but sensitive to geometry. The poor performance of CLUTCH with fissionable reflectors was reaffirmed. The 2 in. and greater polyethylene-reflected calculations demonstrate the necessity of using the 302-group library for fast systems. The nickel MG bias was substantial, as discussed in a companion paper, as were cobalt and iron.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Exploring the physics of cesium lead halide perovskite quantum dots via Bayesian inference of the photoluminescence spectra in automated experiment

The unique optoelectronic properties of metal halide perovskite quantum dots (QDs) make them promising candidates for applications in light-emitting diodes (LEDs), scintillators, and other photonic devices. The automated micropipetting synthesis platform equipped with an optical reader enables the opportunity for high throughput synthesis and photoluminescent (PL) characterization of metal halide perovskite QDs for the first time. Here, we explore the compositional dependence of the PL behavior and stability of the combinatorial library of cesium lead halide (CsPbX 3 ) perovskites QDs via the automated platform. To study the stability of synthesized QDs in the binary and ternary configurations, we study the time-dependent PL properties using previously developed machine learning analysis. Additionally, to systematically explore the PL behavior in the ternary CsPbX 3 QDs system, we introduce the Bayesian inference framework that allows the probabilistic fit of multiple models to the PL data and establishes both optimal model and model parameter robustly. Furthermore, these behaviors can be used as a control parameter for the navigation of the multidimensional compositional spaces in automated synthesis. Furthermore, this analysis shows the nonuniformity of the PL peak behavior in the ternary CsPbX 3 QDs system. Further, the analysis confirms narrow size distribution and good quality of CsPbBr 3 QDs alloyed with low concentrations of iodide and chloride. We note that Bayesian Inference fit parameters can be further used as a control signal for navigation of the chemical spaces in automated synthesis.

36 MATERIALS SCIENCE↗

Intermetallic Nanocatalysts from Heterobimetallic Group 10–14 Pyridine-2-thiolate Precursors

Intermetallic compounds are atomically ordered inorganic materials containing two or more transition metals and main-group elements in unique crystal structures. Intermetallics based on group 10 and group 14 metals have shown enhanced activity, selectivity, and durability in comparison to simple metals and alloys in many catalytic reactions. While high-temperature solid-state methods to prepare intermetallic compounds exist, softer synthetic methods can provide key advantages, such as enabling the preparation of metastable phases or of smaller particles with increased surface areas for catalysis. In this work, we study a generalized family of heterobimetallic precursors to binary intermetallics, each containing a group 10 metal and a group 14 tetrel bonded together and supported by pincer-like pyridine-2-thiolate ligands. Upon thermal decomposition, these heterobimetallic complexes form 10–14 binary intermetallic nanocrystals. Experiments and density functional theory (DFT) computations help in better understanding the reactivity of these precursors toward the synthesis of specific intermetallic binary phases. Using Pd 2 Sn as an example, we demonstrate that nanoparticles made in this way can act as uniquely selective catalysts for the reduction of nitroarenes to azoxyarenes, which highlights the utility of the intermetallics made by our method. Employing heterobimetallic pincer complexes as precursors toward binary nanocrystals and other metal-rich intermetallics provides opportunities to explore the fundamental chemistry and applications of these materials.

10-14 intermetallics↗

Mesoporous metal oxides, preparation and applications thereof

This disclosure provides a unique approach for the synthesis of non-stoichiometric, mesoporous metal oxides with nano-sized crystalline wall. The as-synthesized mesoporous metal oxide is very active and stable (durability >11 h) electocatalyst in both acidic and alkaline conditions. The intrinsic mesoporous metal oxide serves as an electrocatalyst without the assistant of carbon materials, noble metals, or other materials, which are widely used in previously developed systems. The as-synthesized mesoporous metal oxide has large accessible pores (2-50 nm), which are able to facilitate mass transport and charge transfer. The as-synthesized mesoporous metal oxide requires a low overpotential and is oxygen deficient. Oxygen vacancies and mesoporosity served as key factors for excellent performance.

Suib, Steven L.↗

Predicting the superconducting critical temperature in transition metal carbides and nitrides using machine learning

Transition metal carbides and nitrides have unique mechanical and chemical characteristics. At low temperatures many of them also exhibit superconductivity, which can be controlled by substitutions into both the transition metal and carbon/nitrogen sites. To investigate the factors governing the superconducting state, we apply machine learning methods. Here we collected a dataset containing 147 materials, which was used to create a pipeline for predicting their superconducting critical temperature. When this pipeline is applied to a randomly selected test set, it shows a good performance, with of 0.82 and RMSE of 1.9 K. To explore the limits of the machine learning approach, we also use it to predict entire substitution series within the dataset. This represents a realistic test for the predictive models, which can be extremely useful when applied to new substitutions in materials systems. The performance of the pipeline in this case is much more uneven, with good predictions for some series, while for others the model shows minimal predictive power. We discuss possible reasons for these results, as well as methods to estimate the performance of machine learning on new substitution series.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗