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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 OSTI2023

Influencing Bonding Interactions of the Neptunyl (V, VI) Cations with Electron-donating and -withdrawing Groups

Neptunium makes up the largest percentage of minor actinides found in spent nuclear fuel, yet separations of this element have proven difficult due to its rich redox chemistry. Developing new reprocessing techniques should rely on understanding how to control the Np oxidation state and its interactions with different ligands. Designing new ligands for separations requires understanding how to properly tune a system toward a desired trait through functionalization. Emerging technologies for minor actinide separations focus on ligands containing carboxylate or pyridine functional groups, which are desirable due to their high degree of functionalization. So we use DFT calculations to study the interactions of carboxylate and polypyridine ligands with the neptunyl cation [Np(V/VI)O2] +/2+ . A systematic study is performed by varying the electronic properties of the carboxylate and polypyridine ligands through the inclusion of different electron-withdrawing and electron-donating R groups. We focus on how these groups can affect geometric properties, electronic structure, and bonding characterization as a function of the metal oxidation state and ligand character and discuss how these factors can play a role in neptunium ligand design principles.

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

Atomic Orbital Energy Matching vs Overlap in Actinide-Ligand Dative Bonding

Prebonding conditions and dative bond formation in actinide(IV)hexachloride complexes with U, Np, and Pu are studied by density functional theory (DFT) calculations, focusing on the interplay of atomic orbital (AO) overlap and AO energy matching in the formation of molecular orbitals (MOs) and the subsequent identification of dative bonds. The extent of donation is tracked via population analysis, MO localization, and bond-order criteria. DFT Fock matrices are used to setup models in which varying numbers of valence AOs interact to form dative bonds. The results confirm, among other effects, a contribution to metal−ligand covalency from the actinide (An) 6p shell. Better matching of An(5f) and Cl(3p) energies occurs as the An(5f) level stabilizes with increasing An effective nuclear charge. A near-degeneracy occurs in the case of the α-spin orbitals of the Pu system, but it is inconsequential. Altogether, better AO energy matching for An(5f) and Cl(3p) along the series U, Np, Pu is counter-balanced by decreasing AO overlap and decreasing availability of 5f acceptor orbitals, leading to similar bond orders and extents of donation in the three systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Substrate-Mediated Evaporation and Stochastic Evolution of Supported Au Nanoparticles

Here, we use in situ transmission electron microscopy with automated tracking to study supported gold nanoparticles (NPs) during high-temperature vacuum annealing. The average mass loss per NP is governed by a flat, nearly size-independent substrate-mediated evaporation profile. On top of this mean shrinkage, individual NPs show significant fluctuations in apparent growth or shrinkage, and NP volume follows a random-walk-like trajectory. To rationalize both the ensemble-mean behavior and the particle-resolved variability, we develop a self-consistent theory that couples substrate-mediated evaporation to collective 2D Ostwald-type mass exchange through a shared adatom field, described in terms of a renormalized screening length and background concentration. In the experimentally relevant regime, the theory predicts an approximately size-independent mean shrinkage rate and clarifies how net mass loss suppresses classical coarsening. Superimposed on this deterministic drift, we quantify stochastic volume trajectories and capture their fluctuation spectrum with a minimal Langevin description consistent with intermittent adatom attachment and detachment events. In addition, we characterize the lateral diffusive motion of NPs, which is responsible for their coalescence. Altogether, our results highlight that stochasticity is intrinsic at the nanoscale and that predicting the evolution of supported NPs at early and intermediate times requires a unified framework combining substrate-mediated evaporation, collective mass exchange, and stochastic fluctuations.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Light-Controlled Nanoparticle Collision Experiments

Electrochemical monitoring of catalytically amplified collisions of individual metal nanoparticles (NP) with ultramicroelectrodes (UME) has been extensively used to study electrocatalysis, mass-transport, and charge-transfer processes at the single NP level. More recently, photoelectrochemical collision experiments were carried out with semiconductive NPs. Here we introduce two new types of light-controlled nano-impact experiments. The first experiment involves localized photodeposition of catalyst (Pt) on TiO 2 NPs with a glass-sheathed carbon fiber simultaneously serving as the light guide and collector UME. The collisions of in situ prepared Pt@TiO 2 NPs with the carbon surface produced blips of water oxidation current, while the activity of pristine TiO 2 NPs was too low to yield measurable signal. In another experiment, collisions of catalytic (Ir oxide) NPs with the semiconductor (Nb doped n-type TiO 2 rutile single crystal) electrode are monitored by measuring the photocurrent of water oxidation.

14 SOLAR ENERGY↗
DOE OSTI2020

Photoinduced Charge Carrier Dynamics and Electron Injection Efficiencies in Au Nanoparticle-Sensitized TiO 2 Determined with Picosecond Time-Resolved X-ray Photoelectron Spectroscopy

Progress in the development of plasmon-enabled light-harvesting technologies requires a better understanding of their fundamental operating principles and current limitations. In this work, we employ picosecond time-resolved X-ray photoemission spectroscopy to investigate photoinduced electron transfer in a plasmonic model system composed of 20 nm sized gold nanoparticles (NPs) attached to a nanoporous film of TiO 2 . The measurement provides direct, quantitative access to transient local charge distributions from the perspectives of the electron donor (AuNP) and the electron acceptor (TiO 2 ). On average, approximately two electrons are injected per NP, corresponding to an electron injection yield per absorbed photon of 0.1%. Back electron transfer from the perspective of the electron donor is dominated by a fast recombination channel proceeding on a time scale of 60 ± 10 ps and a minor contribution that is completed after ~1 ns. The findings provide a detailed picture of photoinduced charge carrier generation in this NP–semiconductor junction, with important implications for understanding achievable overall photon-to-charge conversion efficiencies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Long-Term Aging in Miscible Polymer Nanocomposites

Here we find that the initial, solvent-cast state of nanoparticles (NPs) in a polymer matrix temporally evolves during thermal annealing such that, at steady state, NPs maximize their distance from each other subject to mass balance constraints. The observed timescales for this unexpected structural reorganization, as probed by small-angle X-ray scattering, are temperature-dependent and can be prohibitively large, especially at temperatures around and below 1.2Tg. X-ray photon correlation spectroscopy measurements during reorganization reveal that the collective NP dynamics slow down with annealing at constant temperature; this is accompanied by changes in the low-frequency regime in macroscopic viscoelastic measurements in equilibrated materials. By ruling out other potential sources for these effects (i.e., electrostatic interactions, adsorbed layers), we attribute these results to a long-ranged repulsive force between the NPs caused by fluctuations in the polymer phase, i.e., the "anti-Casimir" effect proposed by Obhukhov and Semenov [Long-range interactions in polymer melts: The anti-Casimir effect. Phys Rev Lett 2005, 95 (3), 038305]. Thus, our results highlight the important role of long-term, slow NP reorganization on the structure and, subsequently, the properties of polymer nanocomposites (PNCs), even in the case of nominally miscible polymer nanoparticle hybrids.

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

Neptunium Pyridine Dipyrrolide Complexes

Two pyridine dipyrrolide neptunium(IV) complexes, ( Mes PDP Ph )NpCl 2 (THF) and Np( Mes PDP Ph ) 2 , where ( Mes PDP Ph ) 2– is the doubly deprotonated form of 2,6-bis(5-(2,4,6-trimethylphenyl)-3-phenyl-1H-pyrrol-2-yl)pyridine, have been prepared. Characterization of the complexes has been performed through a combination of solid- and solution-state methods, including single-crystal X-ray diffraction and electronic absorption and nuclear magnetic resonance spectroscopies. Collectively, these data confirm the formation of the mono- and bis-ligated species. Electrochemistry of a series of bis-ligated actinide complexes, An( Mes PDP Ph ) 2 (An = Th, U, Np), is presented.

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

SiO 2 Is Wasted Space in Single-Nanometer-Scale Silicon Nanoparticle-Based Composite Anodes for Li-Ion Electrochemical Energy Storage

The electrode processing conditions of silicon-based composite anodes play a pivotal role in the resulting interfacial chemical speciation and, thus, the electrochemical cycling behavior of the electrode. Systematically investigating how small chemical changes to the surface of the silicon nanoparticle (NP) affect larger, electrode-level properties is a strategy that will inform design principles to maximize electrode energy density and extend electrode lifetime. Here, we incorporate silicon nanoparticles (NPs) with an average diameter of 5.5 nm synthesized from the gas phase through a nonthermal plasma method into composite anode half-cell coin cells. We perform chemistry to functionalize the native hydride-terminated silicon NP surface with N-methylpyrrolidone (NMP) to improve slurry properties and reduce the silicon reactivity prior to composite electrode fabrication. We construct composite electrodes from these silicon NPs and observe an 86% capacity retention over 100 cycles at a rate of C/5, with an initial silicon specific capacity of 2600 mAh/g. We expose the same Si NPs to water that completely oxidizes these small-diameter NPs to SiO 2 and find that the SiO 2 NPs in the same electrode configuration exhibit no obvious lithium alloying capacity in the electrochemical potential range of lithium silicide alloy formation. As this result stands in contrast to existing literature, we provide a discussion on the origin of the discrepancies.

25 ENERGY STORAGE↗
DOE OSTI2023

Single Ion Conducting Hairy Nanoparticle Additive to Improve Cycling Stability of Solid Polymer Electrolytes

The development of a solid electrolyte that can impede dendrite growth while still maintaining an appropriate level of conductivity is essential for improving performance of solid-state Li-ion battery. In this paper, we report the synthesis of single Li-ion conducting hairy nanoparticle (NP) materials that improved the cycling stability of lithium bis(trifluoromethanesulfonyl)imide (LiTFSI)-doped poly(ethylene oxide) (PEO) solid electrolyte without significant reduction in conductivity. To unveil mechanisms leading to improved cycling stability, several characterization techniques including broadband dielectric spectroscopy, differential scanning calorimetry, small angle X-ray scattering, transmission electron microscopy, and shear rheology were used to study properties of polymer composites (PC) with added hairy NPs. It was found that hairy NPs influenced the Li/electrolyte interface and improved mechanical properties of bulk composites, all of which contributed to homogenous Li plating and stripping. The improved performance has been found in composites with concentrations of 4.8 and 9.1 weight % of added hairy NPs, which enabled Li cycling stability at 0.2 mA cm–2 critical current density (>300 h) that was otherwise not possible in either PEO-LiTFSI alone or PEO-LiTFSI composites containing a polymer identical to that attached to hairy NPs. Based on the discovered ability of hairy NP to influence bulk and interfacial properties of solid electrolyte, their use as additives is expected to be equally effective in reducing dendrite formation in other electrolytes relevant for the design of solid-state battery.

25 ENERGY STORAGE↗
DOE OSTI2024

A First-Principles Approach to Modeling Surface Site Stabilities on Multimetallic Catalysts

The study of multimetallic alloys and the multitude of possible surface compositions have sparked a tremendous interest in engineering low-cost materials with high activity and selectivity in heterogeneous catalysis. Multimetallic systems provide complementary functionalities and an unprecedented tunability when designing catalyst formulations. However, due to their immense structural and compositional complexity, the investigation and identification of an optimal catalyst is a tedious and time-consuming process, both experimentally and theoretically. Therefore, theoretical design principles are highly desirable to accelerate the screening of catalyst structures across the vast compositional space. In this paper, we introduce a simple and general model for predicting the site stability of multimetallic surfaces and nanoparticles, which is based on physical principles. The model requires only a small set of density functional theory (DFT) calculations of metal atom binding energies on monometallic and dilute alloy surface slabs to optimize the parameters in the simple model. The resulting model allows for the quantification of the stability of any particular atom site in any conceivable chemical environment across a wide range of morphologies, sizes, and arrangements by interpolating the derived parameters from a monometallic system to a completely diluted alloyed system. Herein, we demonstrate the robustness of the model across an extensive data set of transition metal alloy surfaces and 147-atoms cuboctahedral nanoparticles (NPs) composed of IrRhRu and PtPdRu. In conclusion, our approach yields mean absolute errors of ≈0.15 (IrRhRu), 0.20 (PtPdRu), 0.19 (IrRhRu NP), and 0.26 (PtPdRu NP) eV relative to site binding energies calculated using DFT.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Hydrogen Adsorption, Reactivity, and Catalysis on Colloidal Iron Carbide Nanoparticles

Supported iron carbide particles have long served as catalysts for CO hydrogenation (the Fischer Tropsch synthesis, FTS) and continue to be attractive. Despite this, little is known about their chemistry. Reported here is a colloidal Fe x C nanoparticle (NP) model system that allows direct observation of surface hydrogen and CO, as well as quantification of the surface H. Dodecylamine-capped Fe x C NPs (DDA-Fe x C NPs) were synthesized through solution-phase carburization of Fe NPs and form stable colloids in low-polarity organic solvents. Treatment of these colloids with H 2 or D 2 produced highly hydrogenated materials, and FTIR spectra of DDA-Fe x C-D n showed that most of the D binds to carbides, with at least four distinct v(C-D) modes. The surface C-H(D) bonds were all reactive, transferring hydrogen to alkenes and other reagents in solution. Titration and ICP measurements showed a 0.17:1 ratio of added H:total Fe, or roughly. 40 H per 1.8 nm DDA-Fe x C NP. Conversely, CO was preferentially bound to surface Fe sites, with FTIR spectra showing a single broad v(CO) that shifted with CO coverage or co-adsorption of H 2 . The DDA-Fe x C NPs were active catalysts for both olefin hydrogenation and the FTS, under mild conditions and without catalyst pre-treatment. The CO hydrogenation reactions yielded a broad distribution of long-chain linear paraffins and olefins. Though quantitative comparisons with typical FTS results are not possible because of our use of sealed batch reactors and other factors, the observations of high catalytic reactivity demonstrate the relevance of this model system to iron-carbide catalysis. DFT calculations on model slab surfaces with varying iron carbide stoichiometries revealed that the thermodynamically preferred surface adsorption sites are C for H ads and Fe for CO ads . A variety of binding sites and binding energies were found for each adsorbate. We are unaware of previous studies indicating that a diverse array of C-H bonds is the primary source of reactive H on iron carbides. Experimentally, the diversity of *C-H sites was evident in reactions with H-atom donors and abstractors of different strengths, from both the reaction stoichiometries and IR spectra. The different surface–H binding energies correlate with the v(C-D) stretching frequencies. Furthermore, these insights into complex iron carbide surfaces and catalysis could assist catalyst design, and they showcase the importance of stoichiometric studies of reaction intermediates.

08 HYDROGEN↗
DOE OSTI2025

Unraveling Adsorbate-Induced Structural Evolution of Iron Carbide Nanoparticles

Iron carbide (Fe x C y ) nanoparticles (NPs) are promising candidates for replacing platinum group metals in industrial applications, such as high-temperature Fischer–Tropsch synthesis. However, due to their amorphous nature, characterization of the active sites has been challenging experimentally and computationally. Here, using a combined density functional theory (DFT), neural network interatomic potential-assisted global optimization, and ensemble learning study, we evaluate dynamic surface changes associated with syngas (H and CO) interactions. For this purpose, we have developed a general procedure that we use to model an experimentally relevant 270-atom Fe 182 C 88 NP using the neural network-assisted stochastic surface walk global optimization algorithm (SSW-NN). Once generated, the Fe 182 C 88 NP active sites and particle morphology are thoroughly characterized before the effects of syngas adsorbate interactions are explored by using DFT and molecular dynamics simulations. Lastly, we explore correlations between geometric and electronic features of the active sites and the adsorption of H (H ads ), using a regularized random forest machine learning algorithm. In doing so, we identified the Fe–C coordination number and p orbital occupancy as the most important descriptors affecting H ads . Furthermore, using a combined ML and quantum chemistry approach, our work demonstrates a general and efficient procedure for generating and probing complex surface phenomena on binary nanoparticles.

Adsorption↗
DOE OSTI2023

Colloidal Clusters and Networks Formed by Oppositely Charged Nanoparticles with Varying Stiffnesses

Colloidal clusters and gels are ubiquitous in science and technology. Particle softness has a strong effect on interparticle interactions; however, our understanding of the role of this factor in the formation of colloidal clusters and gels is only beginning to evolve. Here, we report the results of experimental and simulation studies of the impact of particle softness on the assembly of clusters and networks from mixtures of oppositely charged polymer nanoparticles (NPs). Experiments were performed below or above the polymer glass transition temperature, at which the interaction potential and adhesive forces between the NPs were significantly varied. Hard NPs assembled in fractal clusters that subsequently organized in a kinetically arrested colloidal gel, while soft NPs formed dense precipitating aggregates, due to the NP deformation and the decreased interparticle distance. Importantly, interactions of hard and soft NPs led to the formation of discrete precipitating NP aggregates at a relatively low volume fraction of soft NPs. A phenomenological model was developed for interactions of oppositely charged NPs with varying softnesses. Furthermore, the experimental results were in agreement with molecular dynamics simulations based on the model. This work provides insight on interparticle interactions before, during, and after the formation of hard–hard, hard–soft, and soft–soft contacts and has impact for numerous applications of reversible colloidal gels, including their use as inks for additive manufacturing.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Revealing Sintering Kinetics of MoS 2 -Supported Metal Nanocatalysts in Atmospheric Gas Environments via Operando Transmission Electron Microscopy

The decoration of two-dimensional (2D) substrates with nanoparticles (NPs) serve as heterostructures for various catalysis applications. Deep understanding of catalyst degradation mechanisms during service conditions is crucial to improve the catalyst durability. In this work, we studied the sintering behavior of Pt and bimetallic Au-core Pt-shell (Au@Pt core–shell) NPs on MoS 2 supports at high temperatures under vacuum, nitrogen (N 2 ), hydrogen (H 2 ), and air environments by in situ gas-cell transmission electron microscopy (TEM). The key observations are summarized as effect of environment: while particle migration and coalescence (PMC) was the main mechanism that led to Pt and Au@Pt NPs degradation under vacuum, N 2 , and H 2 environments, the degradation of MoS 2 substrate was prominent under exposure to air at high temperatures. Pt NPs were less stable in H 2 environment when compared with the Pt NPs under vacuum or N 2 , due to Pt–H interactions that weakened the adhesion of Pt on MoS 2 . Effect of NP composition: under H 2 , the stability of Au@Pt NPs was higher in comparison to Pt NPs. This is because H 2 promotes the alloying of Pt–Au, thus reducing the number of Pt at the surface (reducing H 2 interactions) and increasing Pt atoms in contact with MoS 2 . Effect of NP size: The alloying effect promoted by H 2 was more pronounced in small size Au@Pt NPs resulting in their higher sintering resistance in comparison to large size Au@Pt NPs and similar size Pt NPs. The present work provides key insights into the parameters affecting the catalyst degradation mechanisms on 2D supports.

2D materials↗
DOE OSTI2021

Nanoparticle Assembly Induced Ligand Interactions for Enhanced Electrocatalytic CO 2 Conversion

The microenvironment in which the catalysts are situated is as important as the active sites in determining the overall catalytic performance. Recently, it has been found that nanoparticle (NP) surface ligands can actively participate in creating a favorable catalytic microenvironment, as part of the nanoparticle/ordered-ligand interlayer (NOLI), for selective CO 2 conversion. However, much of the ligand–ligand interactions presumed essential to the formation of such a catalytic interlayer remains to be understood. In this study, by varying the initial size of NPs and utilizing spectroscopic and electrochemical techniques, we show that the assembly of NPs leads to the necessary ligand interactions for the NOLI formation. The large surface curvature of small NPs promotes strong noncovalent interactions between ligands of adjacent NPs through ligand interdigitation. This ensures their collective behavior in electrochemical conditions and gives rise to the structurally ordered ligand layer of the NOLI. Thus, the use of smaller NPs was shown to result in a greater catalytically effective NOLI area associated with desolvated cations and electrostatic stabilization of intermediates, leading to the enhancement of intrinsic CO 2 -to-CO turnover. Our findings highlight the potential use of tailored microenvironments for NP catalysis by controlling its surface ligand interactions.

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

Aligning the Induced Anisotropy of Isotropic Nanoparticles with Liquid Crystals

Thermotropic liquid crystals (LCs) present opportunities for synergistic interactions with ligand-functionalized nanoparticles (NPs). Understanding the dynamics and structures of ligand-coated NPs in an anisotropic LC environment allows for better design and control of versatile LC-NP hybrid materials. Here, simulations and experiments yield direct evidence that cyanobiphenyl LCs induce anisotropy in the biphenylalkyl ligand shells of spherical NPs. The ellipsoidal NP aligns with the LC director. Magnetic fields can dictate the directional ordering of mesogens and consequently allow control of the orientation of the nonmagnetic NPs. Further, controlling the alignment and deformation advances the design and engineering of these hybrid nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Covalent bond shortening and distortion induced by pressurization of thorium, uranium, and neptunium tetrakis aryloxides

Covalency involving the 5f orbitals is regularly invoked to explain the reactivity, structure and spectroscopic properties of the actinides, but the ionic versus covalent nature of metal-ligand bonding in actinide complexes remains controversial. The tetrakis 2,6-di- tert -butylphenoxide complexes of Th, U and Np form an isostructural series of crystal structures containing approximately tetrahedral MO 4 cores. We show that up to 3 GPa the Th and U crystal structures show negative linear compressibility as the OMO angles distort. At 3 GPa the angles snap back to their original values, reverting to a tetrahedral geometry with an abrupt shortening of the M-O distances by up to 0.1 Å. The Np complex shows similar but smaller effects, transforming above 2.4 GPa. Electronic structure calculations associate the M-O bond shortening with a change in covalency resulting from increased contributions to the M-O bonding by the metal 6d and 5f orbitals, the combination promoting MO 4 flexibility at little cost in energy.

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

QUBO formulations for training machine learning models

Abstract Training machine learning models on classical computers is usually a time and compute intensive process. With Moore’s law nearing its inevitable end and an ever-increasing demand for large-scale data analysis using machine learning, we must leverage non-conventional computing paradigms like quantum computing to train machine learning models efficiently. Adiabatic quantum computers can approximately solve NP-hard problems, such as the quadratic unconstrained binary optimization (QUBO), faster than classical computers. Since many machine learning problems are also NP-hard, we believe adiabatic quantum computers might be instrumental in training machine learning models efficiently in the post Moore’s law era. In order to solve problems on adiabatic quantum computers, they must be formulated as QUBO problems, which is very challenging. In this paper, we formulate the training problems of three machine learning models—linear regression, support vector machine (SVM) and balanced k-means clustering—as QUBO problems, making them conducive to be trained on adiabatic quantum computers. We also analyze the computational complexities of our formulations and compare them to corresponding state-of-the-art classical approaches. We show that the time and space complexities of our formulations are better (in case of SVM and balanced k-means clustering) or equivalent (in case of linear regression) to their classical counterparts.

97 MATHEMATICS AND COMPUTING↗