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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Understanding the unique optical and vibrational signatures of sequential infiltration synthesis derived indium oxyhydroxide clusters for CO 2 absorption

Sequential infiltration synthesis (SIS) is a vapor phase synthesis technique with potential to exert precise control over metal oxyhydroxide incorporation into polymer scaffolds. Here, we observe strong size-dependent properties of InO x (OH) y few-atom clusters deposited with variable SIS cycle numbers within a polymethylmethacrylate (PMMA) matrix. Infrared spectroscopy and ultraviolet-visible absorption spectroscopy reveal that the metal atom coordination and optical properties of the clusters depend on the number of SIS cycles performed as well as the choice of processing parameters. The incorporation of indium oxyhydroxide in PMMA via SIS presents an opportunity to improve the CO 2 absorption capacity and gas selectivity of inexpensive polymers.

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

Probing Basal and Prismatic Planes of Graphitic Materials for Metal Single Atom and Subnanometer Cluster Stabilization

Abstract Supported metal single atom catalysis is a dynamic research area in catalysis science combining the advantages of homogeneous and heterogeneous catalysis. Understanding the interactions between metal single atoms and the support constitutes a challenge facing the development of such catalysts, since these interactions are essential in optimizing the catalytic performance. For conventional carbon supports, two types of surfaces can contribute to single atom stabilization: the basal planes and the prismatic surface; both of which can be decorated by defects and surface oxygen groups. To date, most studies on carbon‐supported single atom catalysts focused on nitrogen‐doped carbons, which, unlike classic carbon materials, have a fairly well‐defined chemical environment. Herein we report the synthesis, characterization and modeling of rhodium single atom catalysts supported on carbon materials presenting distinct concentrations of surface oxygen groups and basal/prismatic surface area. The influence of these parameters on the speciation of the Rh species, their coordination and ultimately on their catalytic performance in hydrogenation and hydroformylation reactions is analyzed. The results obtained show that catalysis itself is an interesting tool for the fine characterization of these materials, for which the detection of small quantities of metal clusters remains a challenge, even when combining several cutting‐edge analytical methods.

Vidal, Mathieu↗
DOE OSTI2023

Real-time insight into the multistage mechanism of nanoparticle exsolution from a perovskite host surface

In exsolution, nanoparticles form by emerging from oxide hosts by application of redox driving forces, leading to transformative advances in stability, activity, and efficiency over deposition techniques, and resulting in a wide range of new opportunities for catalytic, energy and net-zero-related technologies. However, the mechanism of exsolved nanoparticle nucleation and perovskite structural evolution, has, to date, remained unclear. Herein, we shed light on this elusive process by following in real time Ir nanoparticle emergence from a SrTiO 3 host oxide lattice, using in situ high-resolution electron microscopy in combination with computational simulations and machine learning analytics. We show that nucleation occurs via atom clustering, in tandem with host evolution, revealing the participation of surface defects and host lattice restructuring in trapping Ir atoms to initiate nanoparticle formation and growth. These insights provide a theoretical platform and practical recommendations to further the development of highly functional and broadly applicable exsolvable materials.

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

Effect of Sn microalloying on the nucleation of L1 2 Al 3 Zr precipitates in a dilute aluminum-zirconium alloy

While L1 2 -Al 3 Zr nanoprecipitates provide a balance between strengthening and good electrical conductivity, the precipitation of L1 2 -Al 3 Zr in aluminum requires aggressive heat treatments. An improved age-hardening response was observed during isochronal aging of an Al-0.24Zr (wt%) alloy when microalloyed with Sn. A new mechanism termed Low melting point Element-Assisted Nucleation (LEAN) is proposed to explain the lower temperature nucleation of L1 2 -Al 3 Zr precipitates observed in this alloy based on the addition of a low melting point element, such as Sn. Characterization verified the first-principles density functional theory prediction that Zr and Sn atoms cluster during homogenization owing to the favorable binding energy of Zr-Sn-vacancy triplets. Direct microstructural observations revealed these clusters form Sn nanoprecipitates that assist the nucleation of L1 2 -Al 3 Zr at 200°C, where L1 2 -Al 3 Zr precipitation is not expected due to the low diffusivity of Zr atoms in Al. At higher temperatures (≳350°C), the acceleration of L1 2 -Al 3 Zr precipitation is driven by faster Zr diffusion in Al with Sn microalloying and the nuclei formed via the LEAN mechanism. In conclusion, this combination of mechanisms explains the improvement in age hardening through L1 2 -Al 3 Zr precipitation with Sn microalloying.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Interpreting the Operando X-ray Absorption Near-Edge Structure of Supported Cu and CuPd Clusters in Conditions of Oxidative Dehydrogenation of Propane: Dynamic Changes in Composition and Size

Supported subnano-cluster catalysts are highly dynamic, developing true active sites only under the pressures and temperatures of reaction conditions. Operando X-ray absorption near-edge structure (XANES) spectroscopy can track changes in the oxidation state and the local environment of cluster atoms, providing insight into the development of these active sites. While bulk metal, oxide, and hydroxide standards are often used for fitting experimental XANES spectra to obtain average oxidation states, we recently showed that computed cluster standards of relevant compositions are a more suitable basis, producing more accurate fits. Here, we theoretically interpret the operando XANES of supported Cu 3 Pd and Cu 4 clusters during temperature-programmed reaction (TPRx) of oxidative dehydrogenation of propane. We use an expanded basis set including both globally optimized computed clusters and bulk standards. Not only can we track reversible composition/oxidation state change with temperature, but also the irreversible growth of the bulk fraction upon heating, which we attribute to cluster sintering. This has important implications for the mechanism of the catalyzed reaction and the nature of the available active sites. Here, we propose that operando XANES provides most significant insight into the nature of supported cluster catalysts in reaction conditions when interpreted using mixed computed cluster and bulk standards.

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

Accuracy, transferability, and computational efficiency of interatomic potentials for simulations of carbon under extreme conditions

Large-scale atomistic molecular dynamics (MD) simulations provide an exceptional opportunity to advance the fundamental understanding of carbon under extreme conditions of high pressures and temperatures. However, the fidelity of these simulations depends heavily on the accuracy of classical interatomic potentials governing the dynamics of many-atom systems. Here, this study critically assesses several popular empirical potentials for carbon, as well as machine learning interatomic potentials (MLIPs), in their ability to simulate a range of physical properties at high pressures and temperatures, including the diamond equation of state, its melting line, shock Hugoniot, uniaxial compressions, and the structure of liquid carbon. Empirical potentials fail to accurately predict the behavior of carbon under high pressure–temperature conditions. In contrast, MLIPs demonstrate quantum accuracy, with Spectral Neighbor Analysis Potential (SNAP) and atomic cluster expansion (ACE) being the most accurate in reproducing the density functional theory results. ACE displays remarkable transferability despite not being specifically trained for extreme conditions. Furthermore, ACE and SNAP exhibit superior computational performance on graphics processing unit-based systems in billion atom MD simulations, with SNAP emerging as the fastest. In addition to offering practical guidance in selecting an interatomic potential with a fine balance of accuracy, transferability, and computational efficiency, this work also highlights transformative opportunities for groundbreaking scientific discoveries facilitated by quantum-accurate MD simulations with MLIPs on emerging exascale supercomputers.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Cluster Expansion Analysis of Atomic Order in Li-Ion Battery Cathode Material LiCo y Ni 1-y O 2

A modified cluster-expansion treatment was developed recently to analyze atomic order in LiCo y Ni 1-y O 2 , a model cathode material for Li-ion batteries. In this treatment, referred to as a “spin-atom” cluster expansion, the occupant of a lattice site is identified by its spin state as well as its atomic species. Further, Effective Cluster Interaction (ECI) coefficients are derived from a large training data set (i.e., the set of atomic arrangements for which DFT calculations are performed) which is filtered by an anomaly detection algorithm to eliminate poorly converged DFT calculations. The cluster expansion incorporates Li-Ni (LN) exchange as well as intralayer Co-Ni (CN) exchange. Monte Carlo simulations based on the cluster expansion were applied to the Ni-rich part of the phase diagram. The simulations predict a miscibility gap between y = 0.05 and y = 0.65.

25 ENERGY STORAGE↗
DOE OSTI2025

Nature of molybdenum carbide surfaces for catalytic hydrogen dissociation using machine-learned potentials: an ensemble-averaged perspective

Molybdenum carbides with an electronic structure similar to noble metals have gained attention as a promising low-cost catalyst for biomass valorization and the hydrogen evolution reaction. However, our fundamental understanding of the catalyst surface and how different phases of these catalysts behave at varying reaction conditions is limited to ground state density functional theory calculations as ab initio molecular dynamics (AIMD) is computationally prohibitive at relevant length and time scales. Here, in this work, we train a multi-atomic cluster expansion (MACE) machine-learned interatomic potentials (MLIP) to study hydrogen dissociation and dynamics over Mo, δ-MoC, α-Mo 2 C, and β-Mo 2 C surfaces at varying temperatures and hydrogen partial pressures. Our simulations identify unique and different molecular and atomic hydrogen adsorption sites on different surfaces that do not depend on the temperature. At low hydrogen pressures, the surface coverage is monolayer, which transitions to two-layer adsorption at higher pressures. We find that atomic hydrogen diffusion and recombinations are preferred over molybdenum atom hollow sites, while the diffusion over carbon-terminated facets was negligible, signifying particularly strong C–H interactions. In contrast, molecular hydrogen adsorption occurs mostly atop Mo or the bridging sites. At a comparable hydrogen loading, β-Mo 2 C (001) is the most active surface for hydrogen dissociation reaction. This work provides insights into the dynamic nature of the hydrogen dissociation chemistry and the diversity of hydrogen adsorption sites on molybdenum carbides.

08 HYDROGEN↗
DOE OSTI2023

Size-Dependent Energy and Adhesion of Pd Nanoparticles on Graphene on Ni(111) by Pd Vapor Adsorption Calorimetry

Carbon-supported late transition-metal nanoparticles are promising catalysts and electrocatalysts for wide-ranging applications. However, experimental investigations of the bonding energetics of metal nanoparticles on carbon supports are very limited. Here, in this work, we report heats of adsorption of Pd vapor deposited onto single-layer graphene(0001) supported on Ni(111) at 100 and 300 K as Pd grows particles of well-defined size in the range from three atom clusters to 6 nm diameter. Sizes were determined from He + low-energy ion scattering (LEIS). In this size range, the differential heat of Pd adsorption increases from 228 kJ/mol to within 10 kJ/mol of the heat of sublimation of bulk Pd (377 kJ/mol). The chemical potential of metal atoms in these nanoparticles as a function of average particle size was determined from these results. The adhesion energy at the Pd/graphene(0001)/Ni(111) interface was extracted from these data and found to be 3.5 J/m 2 for the largest Pd particles. For the three metal elements that have now been studied (Pd, Ni, and Ag), we found an increase in metal/graphene(0001)/Ni(111) adhesion energy with metal carbophilicity, which we defined here as the heat of C atom adsorption on that metal’s (111) surface estimated from published density functional theory calculations.

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

Gold–Thiolate Nanocluster Dynamics and Intercluster Reactions Enabled by a Machine Learned Interatomic Potential

Monolayer protected metal clusters comprise a rich class of molecular systems and are promising candidate materials for a variety of applications. While a growing number of protected nanoclusters have been synthesized and characterized in crystalline forms, their dynamical behavior in solution, including prenucleation cluster formation, is not well understood due to limitations both in characterization and first-principles modeling techniques. Recent advancements in machine-learned interatomic potentials are rapidly enabling the study of complex interactions such as dynamical behavior and reactivity on the nanoscale. Here, we develop an Au-S-C-H atomic cluster expansion (ACE) interatomic potential for efficient and accurate molecular dynamics simulations of thiolate-protected gold nanoclusters (Au n (SCH 3 ) m ). Trained on more than 30,000 density functional theory calculations of gold nanoclusters, the interatomic potential exhibits ab initio level accuracy in energies and forces and replicates nanocluster dynamics including thermal vibration and chiral inversion. Long dynamics simulations (up to 0.1 μs time scale) reveal a mechanism explaining the thermal instability of neutral Au 25 (SR) 18 clusters. Specifically, we observe multiple stages of isomerization of the Au 25 (SR) 18 cluster, including a chiral isomer. Additionally, we simulate coalescence of two Au 25 (SR) 18 clusters and observe series of clusters where the formation mechanisms are critically mediated by ligand exchange in the form of [Au-S] n rings.

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

Unveiling the mechanism of phase and morphology selections during the devitrification of Al-Sm amorphous ribbon

The complex interplay between energetic and kinetic factors that governs the phase and morphology selections can originate at the earliest stage of crystallization in the amorphous parent phases. Because of the extreme difficulties in capturing the microscopic nucleation process, a detailed picture of how initial disordered structures affect the transformation pathway remains unclear. Here, we report the experimental observation of widely varying phase selection and grain size evolution during the devitrification of a homogeneous melt-spun glassy ribbon. Two different crystalline phases, θ-Al 5 Sm and ε-Al 60 Sm 11 , are found to form in the different regions of the same metallic glass ribbon during the devitrification. The grain size of ε-Al 60 Sm 11 phase shows a strong spatial heterogeneity. Coarse-grained ε-Al 60 Sm 11 phase coupled with the small volume fraction of θ-Al 5 Sm phase is preferably formed close to wheel side of the melt-spun ribbon. Combining experimental characterization and computational simulations, we show that phase selection and microstructure evolution can be traced back to different types and populations of atomic clusters that serve as precursors for the nucleation of different crystalline phases. Inhomogeneous cooling rates cause different structure orders across the glass sample during the quenching process. Our findings provide direct insight into the effect of structural order on the crystallization pathways during the devitrification of metallic glass. It also opens an avenue to study the detailed nucleation process at the atomic level using the metallic glass as a platform and suggests the opportunity of microstructure and property design via controlling the cooling process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

The influence of nitrogen and nitrides on the structure and properties of proton irradiated ferritic/martensitic steel

The 12Cr1MoWV (wt%) ferritic/martensitic steel HT9 is a candidate material for fuel cladding in advanced nuclear reactors, such as the Versatile Test Reactor currently under development. As such, understanding the relationship between microstructure and mechanical properties in the context of irradiation environments for these steels is critical. N content, and more specifically interstitial N, has been hypothesized to be detrimental to irradiated properties at lower temperatures (less than 0.3T m ) to a total of 6 dpa; however, in this work at a dose of 1 dpa the irradiated microstructure was improved with added N, leading to less irradiation hardening. Three variants of HT9 were irradiated with 1.5 MeV protons to a dose of 1 dpa at 300°C. The HT9 variants included Low (10 ppm), Mid (190 ppm), and High (440 ppm) N alloys that were otherwise nearly identical. Changing the N content had a variety of effects on the irradiated defect structures. As N content increased, the average dislocation loop diameter decreased, while the number density of loops increased. Additionally, extensive Ni clustering was observed on dislocations and interfaces. The Mid and High N specimens exhibited significantly less hardening (ΔHV≃100) relative to the Low N specimen (ΔHV≃160). The decrease in hardening is attributed to vanadium carbonitride acting as a sink for Ni clusters that would otherwise form on dislocations. Under the irradiation conditions used, these results suggest increasing the N content in HT9 may have a desirable effect on the irradiated structure and properties at the dose studied, as well as the swelling resistance at higher doses. In other words, N content appears to be a powerful tool for tailoring the self-interstitial atom cluster mobility in F/M steels for different temperature and dose applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Impacts of Focused Ion Beam Processing on the Fabrication of Nanoscale Functionalized Probes

Herein, we examine the impact of Ga + ion kinetic energy and the target material type on the extent of ion implantation and structural damage in atomic force microscopy probes made of Al 2 O 3 and ZnO manufactured by focused ion beam (FIB) using scanning transmission electron microscopy and energy-dispersive X-ray mapping. Penetration of Ga into the Al 2 O 3 lattice induced structural distortions and amorphization. For ZnO probes, Ga is uniformly dispersed across the surface, resulting in the formation of distinct clusters. Atom probe tomography further validates the Ga distributions in Al 2 O 3 and ZnO nanoprobes. Complementary Monte Carlo simulations with the transport of ions in the matter program indicated that the introduction of Ga + prompts the generation of cation and anion vacancies, an occurrence more pronounced in Al 2 O 3 compared to ZnO. In conclusion, this study not only enriches the knowledge of ion-matter interactions, but also serves as a practical guide for the fabrication of nanoscale functionalized AFM probes.

Al2O3↗
DOE OSTI2023

Top-Down Fabrication of Atomic Patterns in Twisted Bilayer Graphene

Atomic-scale engineering typically involves bottom-up approaches, leveraging parameters such as temperature, partial pressures, and chemical affinity to promote spontaneous arrangement of atoms. These parameters are applied globally, resulting in atomic-scale features scattered probabilistically throughout the material. In a top-down approach, different regions of the material are exposed to different parameters, resulting in structural changes varying on the scale of the resolution. In this work, the application of global and local parameters is combined in an aberration-corrected scanning transmission electron microscope (STEM) to demonstrate atomic-scale precision patterning of atoms in twisted bilayer graphene. The focused electron beam is used to define attachment points for foreign atoms through the controlled ejection of carbon atoms from the graphene lattice. The sample environment is staged with nearby source materials such that the sample temperature can induce migration of the source atoms across the sample surface. Under these conditions, the electron-beam (top-down) enables carbon atoms in the graphene to be replaced spontaneously by diffusing adatoms (bottom-up). Using image-based feedback control, arbitrary patterns of atoms and atom clusters are attached to the twisted bilayer graphene with limited human interaction. Finally, the role of substrate temperature on adatom and vacancy diffusion is explored by first-principles simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Structural origin of disorder-induced ion conduction in NaFePO 4 cathode materials

Diffusion in NaFePO 4 can be enhanced through amorphization. Based on computations using DFT and machine learning potentials, we ascribe this phenomenon to the formation of less constrained Na-ion environments upon disordering. Most modern battery technologies depend on solid-state crystalline cathode materials. However, some of these materials are constrained by the low ionic conductivity of their most stable phases. An example of this is maricite (NaFePO 4 ). Interestingly, experiments have shown that maricite can improve its rate capability through disordering (amorphization). However, experimental characterization of amorphous cathode materials remains a major challenge, hindering a clear understanding of the structural origin of the disorder-induced improvement in sodium-ion mobility. To address this, we here employ molecular dynamics simulations by first training a machine learning potential for NaFePO 4 based on the atomic cluster expansion approach and a batch active learning potential parameterization scheme. This potential is then applied to explore the structural and dynamical properties of NaFePO 4 glasses as cathode materials. Specifically, we investigate the effect of glass structure on sodium-ion diffusion, revealing the relative influences of short-range and medium-range order features. We find significant heterogeneity in sodium-ion diffusivity in the glass, with fast-conducting ions residing in less constrained atomic environments with fewer P and Fe neighbors. These more mobile ions are also surrounded by larger ring-type structures. Overall, the results and developed approach present promising avenues for developing high-performance glassy cathodes for next-generation batteries.

Christensen, Rasmus↗
DOE OSTI2025

Efficient machine learning interatomic potentials robust for liquid and multiple solid polymorphs of NaF and KF

Achieving atomic-level understanding of crystallization of molten salts is of importance to a wide range of technological applications. Recent work [Fan et al., Proc. Natl. Acad. Sci. USA 122, e2425702122 (2025)] revealed that crystal nucleation in molten LiF salt is a multistage process according to the molecular-dynamics (MD) simulations based on an atomic cluster expansion (ACE) machine-learning interatomic potential (MLIP). In order to understand the influence of increasing cation size on nucleation pathways and nucleation rates of molten fluoride salts, here we develop two new ACE MLIPs for NaF and KF. The two ACE MLIPs feature DFT-SCAN-level accuracy for liquid and multiple solid polymorphs over a wide temperature (0–2000 K) and pressure (0–100 GPa) range, and also reproduce well a number of experimental data for solid and liquid equilibrium properties. The efficiency of the two ACE MLIPs enable million-atom-scale or microsecond-scale MD simulations. The two general-purpose ACE MLIPs are expected to be useful for atomistic simulations for different purposes, in addition to studying crystallization of molten NaF and KF salts.

Crystal melting↗