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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Optimization and Multimachine Learning Algorithms to Predict Nanometal Surface Area Transfer Parameters for Gold and Silver Nanoparticles

Interactions between gold metallic nanoparticles and molecular dyes have been well described by the nanometal surface energy transfer (NSET) mechanism. However, the expansion and testing of this model for nanoparticles of different metal composition is needed to develop a greater variety of nanosensors for medical and commercial applications. In this study, the NSET formula was slightly modified in the size-dependent dampening constant and skin depth terms to allow for modeling of different metals as well as testing the quenching effects created by variously sized gold, silver, copper, and platinum nanoparticles. Overall, the metal nanoparticles followed more closely the NSET prediction than for Förster resonance energy transfer, though scattering effects began to occur at 20 nm in the nanoparticle diameter. To further improve the NSET theoretical equation, an attempt was made to set a best-fit line of the NSET theoretical equation curve onto the Au and Ag data points. An exhaustive grid search optimizer was applied in the ranges for two variables, 0.1≤C≤2.0 and 0≤α≤4, representing the metal dampening constant and the orientation of donor to the metal surface, respectively. Three different grid searches, starting from coarse (entire range) to finer (narrower range), resulted in more than one million total calculations with values C=2.0 and α=0.0736. The results improved the calculation, but further analysis needed to be conducted in order to find any additional missing physics. With that motivation, two artificial intelligence/machine learning (AI/ML) algorithms, multilayer perception and least absolute shrinkage and selection operator regression, gave a correlation coefficient, R2, greater than 0.97, indicating that the small dataset was not overfitting and was method-independent. This analysis indicates that an investigation is warranted to focus on deeper physics informed machine learning for the NSET equations.

Demers, Steven M. E. (ORCID:0000000192213246)↗
DOE OSTI2025

Exploring Atomic-Scale Interactions at the Interface of Reducible Oxide and Ruthenium Nanocatalyst for Ammonia Decomposition

Restructuring atomic-scale interfaces between noble metal nanoparticles and metal oxides provides a promising approach to enhancing catalytic properties. In this study, Ru nanoparticles were supported on CeO 2 , ZrO 2 , and HfO 2 via pyrolysis of MOFs under oxygen-suppressed high-temperature conditions. Despite its nearly ideal particle size (∼2.3 nm), the Ru–CeO 2 /C catalyst exhibited the lowest ammonia decomposition activity. X-ray absorption spectroscopy and DFT calculations revealed that electron transfer from Ru to CeO 2 formed positively charged Ru and partially reduced Ce 4+ , weakening the catalytic performance. In contrast, oxygen-deficient ZrO 2 and HfO 2 support donated electrons to Ru, preserving its metallic state. These findings demonstrate that the reducibility of oxide supports governs the direction and magnitude of interfacial charge transfer, directly tuning catalytic behavior. This study provides insights into the design of oxide-supported Ru catalysts for ammonia decomposition.

Catalysts↗
DOE OSTI2025

Nature-inspired lotus-shaped fins combined with hybrid nanoparticles and metal foam for high-performance latent heat thermal energy storage

Latent heat thermal energy storage (LHTES) systems play a critical role in renewable energy integration by providing high energy density and nearly isothermal operation during phase transitions. However, their performance is often limited by slow melting/charging rates, which motivates the search for enhanced heat transfer designs. This study investigates the melting behavior of RT-82 phase change material (PCM) using novel lotus-shaped fins combined with copper metal foam and conductive graphene nanoparticles and carbon nanotubes. A two-dimensional enthalpy-porosity model in ANSYS Fluent was developed to simulate the charging/melting process, capturing non-thermal equilibrium between the foam and PCM/nano-PCM. In this study, effects of fin geometry, nanoparticle concentration, and foam porosity on melting dynamics and cost-performance trade-offs were investigated. Results showed that natural convection accelerated melting by ~12% compared to conduction-only scenarios. Optimized lotus-shaped fins with higher fin density (T3F4 and T3F10) achieved up to 63% faster melting relative to sparse configurations. Graphene nanoparticles improved thermal conductivity, with a 6% volume fraction, by reducing melting time by ~6.9%, while their combination with 75% porosity foam achieved a maximum reduction in the melting time of ~51% compared to pure PCM. Cost-performance analysis identified T3F4 as the most balanced design, offering rapid thermal response without excessive material costs, while moderate-density designs like T3S6 provided economical alternatives with acceptable performance. These results highlight the performance enhancement that can be achieved by integrating bio-inspired fins, nanoparticles, and foams, into compact and efficient LHTES for solar heating, building thermal management, and industrial waste-heat recovery applications.

25 ENERGY STORAGE↗
NASA NTRS1997

Surface Plasmon Resonance Evaluation of Colloidal Metal Aerogel Filters

Surface plasmon resonance imaging has in the past been applied to the characterization of thin films. In this study we apply the surface plasmon technique not to determine macroscopic spatial variations but rather to determine average microscopic information. Specifically, we deduce the dielectric properties of the surrounding gel matrix and information concerning the dynamics of the gelation process from the visible absorption characteristics of colloidal metal nanoparticles contained in aerogel pores. We have fabricated aerogels containing gold and silver nanoparticles. Because the dielectric constant of the metal particles is linked to that of the host matrix at the surface plasmon resonance, any change 'in the dielectric constant of the material surrounding the metal nanoparticles results in a shift in the surface plasmon wavelength. During gelation the surface plasmon resonance shifts to the red as the average or effective dielectric constant of the matrix increases. Conversely, formation of an aerogel or xerogel through supercritical extraction or evaporation of the solvent produces a blue shift in the resonance indicating a decrease in the dielectric constant of the matrix. From the magnitude of this shift we deduce the average fraction of air and of silica in contact with the metal particles. The surface area of metal available for catalytic gas reaction may thus be determined.

Smith, David D.↗
DOE OSTI2025

Cryogenic Carbon Monoxide Oxidation on Cuprous Oxide

Performing oxidation reactions at low temperatures using earth-abundant materials is crucial for advancing solutions for sustainable chemistry. CO oxidation serves as a benchmark reaction to characterize oxidation and to advance fundamental concepts in surface chemistry. While there are several examples of CO oxidation occurring on metal oxides at low temperatures, from 300 K to ∼200 K, reactivity in the cryogenic temperature regime typically requires a metal nanoparticle on a metal oxide. Here, we show oxygen atoms on the (111) facet of Cu 2 O react with CO to form CO 2 at temperatures below 100 K. Combining spectroscopic experimental evidence with calculations, we propose a low barrier path for CO oxidation at reconstructed surface sites on Cu 2 O(111). This finding is a rare example of an earth-abundant metal oxide, in this case copper, that can provide highly reactive multifunctional sites, enabling both adsorption and reaction fundamental steps toward the efficient heterogeneous oxidation of chemicals.

36 MATERIALS SCIENCE↗
DOE OSTI2024

High-Temperature Ferrofluids Based on Molten Salts

Molten metal chloride salts are promising candidates for advanced heat transfer fluids in generation IV nuclear reactors and beyond. However, research on the magnetic properties of suspended metallic nanoparticles at elevated temperatures is scarce, and there have been no attempts to develop a high-temperature, molten salt based ferrofluid. Such a ferrofluid would enable in situ manipulation of both the physical and thermal properties of the fluid via an external magnetic field. This study examines molten salt based ferrofluids comprised of metallic cobalt nanoparticles dispersed in molten metal chloride salts. High-temperature magnetometry and magneto-thermogalvometric measurements were conducted to evaluate the magnetic characteristics of the ferrofluid. Further analysis was conducted through a combination of microscopy, spectroscopy, solubility tests, and diffraction measurements. Furthermore, the metallic cobalt nanoparticles exhibited a notable degree of chemical stability and sustained magnetism from 25 to 800 °C when suspended in NaCl–MgCl 2 and KCl–ZnCl 2 mixtures.

Cobalt↗
DOE OSTI2024

Structural Studies of Alloyed and Nanoparticle Transition Metal Dichalcogenides by Selenium-77 Solid-State Nuclear Magnetic Resonance Spectroscopy

Layered transition metal dichalcogenides (TMDCs) such as MoS 2 , MoSe 2 , and WSe 2 are under intense investigation because they are atomically thin semiconductors with photophysical properties that can be tuned by changing their composition or morphology. Mechanochemical processing has been proposed as a method to obtain alloyed TMDCs in the series Mo 1–x W x S y Se 2–y (x = 0–1; y = 0–2). However, elucidating the chemical transformations occurring at the atomic scale following mechanochemical processing can be challenging because the products are often amorphous or microcrystalline. To address this challenge, we probe TMDC mixing and alloying by using a combination of powder X-ray diffraction, Raman spectroscopy, diffuse reflectance spectroscopy, 77 Se solid-state nuclear magnetic resonance (SSNMR) spectroscopy, and planewave density functional theory (DFT) calculations. The nature of the milling material and reaction atmosphere are shown to be essential factors in limiting the formation of undesired oxide byproducts. We demonstrate acquisition of 77 Se SSNMR spectra using different combinations of Carr-Purcell Meiboom-Gill acquisition (CPMG) pulse sequences, magic angle spinning (MAS), and MAS dynamic nuclear polarization. Further, the combination of SSNMR with the other characterization methods clearly demonstrates that high energy impact ball milling induces molecular level alloying of Mo, W and chalcogen atoms in the family Mo 1–x W x S y Se 2–y . Gauge including projector augmented wave DFT calculations yield accurate 77 Se chemical shift (CS) tensor components. 77 Se SSNMR spectroscopy was also applied to study the structure of WSe 2 nanocrystals intercalated with ethylenediamine. The intercalated WSe 2 nanocrystals exhibit a more positive isotropic 77 Se CS as compared to bulk WSe 2 , however, the 77 Se CS anisotropy is the same, confirming the WSe 2 layers have a similar structure as in their bulk counterparts.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Locating the atoms at the hard-soft interface of gold nanoparticles

Surface structure affects the growth, shape and properties of nanoparticles. In wet chemical syntheses, metal additives and surfactants are used to modify surfaces and guide nanocrystal growth. To understand this process, it is critical to understand how the surface structure, and hence its energy, is modified. However, measuring the type and arrangement of atoms at hard-soft interfaces on nanoscale surfaces, especially in the presence of surfactants, is extremely challenging. Here, we determine the atomic structure of the hard-soft interface in a metallic nanoparticle by developing low-dose imaging conditions in four-dimensional scanning transmission electron microscopy that are preferentially sensitive to surface adatoms. By revealing experimentally the copper additives and bromide surfactant counterion at the surface of a gold nanocuboid and quantifying their interatomic distances, our direct, low-dose imaging method provides atomic-level understanding of chemically sophisticated nanomaterial surface structures. These measurements of the atomic structure of the hard-soft interface provide the information necessary to understand and quantify surface chemistries and energies and their pivotal role in nanocrystal growth.

Li, Weilun [Monash University, Melbourne, VIC (Aus↗
DOE OSTI2025

Pt Nanoparticle Disintegration at Oxide Interfaces Enhances CO Oxidation Catalysis

Understanding how supported metal nanoparticles dynamically evolve under reaction conditions is critical for controlling their catalytic function. Here, the mechanism behind the dynamic disintegration of Pt nanoparticles (NPs) supported on CeOx-TiO2 (CT) during CO oxidation is elucidated, leading to the formation of single atoms (SAs) and/or sub-nanometer clusters. Density functional theory (DFT) calculations reveal that strong Pt-CO interactions weaken Pt─Pt cohesion, while electronic coupling between Pt and Ce ions stabilizes Pt-CO* intermediates at the oxide interface. Surface oxygen vacancies kinetically trap Pt-CO*, but the vacancies are replenished under oxygen-rich conditions, enabling Pt-CO* surface diffusion and subsequent structural reorganization. In situ spectroscopic analyses confirm the oxygen-driven transformation of Pt NPs, correlating with a threefold increase in mass-specific activity at 150 °C. These findings demonstrate that interfacial oxygen dynamics and metal-support interactions can be leveraged to induce nanoparticle disintegration and optimize catalytic performance, highlighting the catalytic potential of interface-engineered Pt nanostructures.

CO oxidation↗
DOE OSTI2026

Metal Identity and Coordination Environment Modulate Single-Atom Catalyst Stability During Electrocatalysis

A major hurdle to the implementation of single-atom catalysts (SACs) in real-world systems is a poor understanding of their stability under operating conditions, which is particularly relevant due to the high surface free energy of SACs. Here, we evaluated the aggregation behavior of a suite of SACs varied by metal identity (Fe, Co, Ni, and Cu) during electrocatalytic nitrate reduction using in situ X-ray absorption spectroscopy. The metal center had significant influence on reconstruction, where under identical applied reductive potentials, SACs underwent varying levels of reconstruction, ranging from no discernible change to complete reduction into metallic nanoparticles. Such in situ experiments revealed Cu SACs to be the most susceptible to aggregation, prompting a deeper investigation into how coordination environment (O-, B-, and N-graphene) affected Cu SAC aggregation. We further conducted density functional theory calculations to elucidate the relationship between Cu SAC structure and stability. This work deconvolutes the relationship between SAC architecture and stability, which is essential to evaluate and explain for the realization of SACs for electrocatalysis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Controlling the Ru Island Decoration on Ni Nanoparticles to Tune the Activity for 5-Hydroxylmethylfurfural (HMF) Oxidation

Controlling the island decoration on metal nanoparticle supports is a major opportunity for improving the catalytic activity and an attractive synthetic challenge. The structure of the decorating metal determines how it interacts with the metal support and how it effectively catalyzes the reactants and the intermediates. In this work, we demonstrate that a slow-growth method maximizes the formation of Ru islands on faceted, branched Ni nanoparticles, thereby controlling the number of Ru–Ni atomic interactions and improving the catalytic activity. The Ru islands on branched Ni nanoparticles with the highest loading of Ru (9%) exhibited the highest activity for the electro-oxidation of biomass-derived 5-hydroxymethylfurfural (HMF). In conclusion, these results demonstrate the ability to synthetically control the second metal decoration to tune metal–support interactions, thereby enhancing the catalytic activity.

5-hydroxymethylfurfural↗
DOE OSTI2025

Iridium Nanocrystals Enriched with Defects and Atomic Steps to Enhance Oxygen Evolution Reaction Performance

The presence of defects can significantly improve catalytic activity and stability, as they influence the binding of the reactants, intermediates, and products to the catalyst. Controlling defects in the structures of nanocrystal catalysts is synthetically challenging. In this study, we demonstrate the ability to control the growth of Ir nanocrystals, enabling the tuning of both structural and surface defects. The Ir nanocrystals have unique structures that range from single crystals of a few nanometers to twinned nanoparticles and multiply twinned crystallites with a high density of atomic steps. Further, this approach of defect engineering enables us to understand their roles in enhancing the performance of the OER and producing an Ir catalyst with both high activity and stability. Our results show the importance of the concept of using synthetic control of structural and surface defects in metal nanoparticles as a strategy to improve catalytic performance.

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

Secondary electron emission measurements from imidazolium-based ionic liquids

The electron-induced secondary electron emission (SEE) yields of imidazolium-based ionic liquids are presented for primary electron beam energies between 30 and 1000 eV. These results are important for understanding plasma synthesis of nanoparticles in plasma discharges with an ionic liquid electrode. Due to their low vapor pressure and high conductivity, ionic liquids can produce metal nanoparticles in low-pressure plasmas through reduction of dissolved metal salts. In this work, the low vapor pressure of ionic liquids is exploited to directly measure SEE yields by bombarding the liquid with electrons and measuring the resulting currents. The ionic liquids studied are [BMIM][Ac], [EMIM][Ac], and [BMIM][BF 4 ]. The SEE yields vary significantly over the energy range, with maximum yields of around 2 at 200 eV for [BMIM][Ac] and [EMIM][Ac], and 1.8 at 250 eV for [BMIM][BF 4 ]. Molecular orbital calculations indicate that the acetate anion is the likely electron donor for [BMIM][Ac] and [EMIM][Ac], while in [BMIM][BF 4 ], the electrons likely originate from the [BMIM] + cation. The differences in SEE yields are attributed to varying ionization potentials and molecular structures of the ionic liquids. These findings are essential for accurate modeling of plasma discharges and understanding SEE mechanisms in ionic liquids.

ionic liquids↗
DOE OSTI2024

Automated Gold Nanorod Spectral Morphology Analysis Pipeline

The development of a colloidal synthesis procedure to produce nanomaterials with high shape and size purity is often a time-consuming, iterative process. This is often due to quantitative uncertainties in the required reaction conditions and the time, resources, and expertise intensive characterization methods required for quantitative determination of nanomaterial size and shape. Absorption spectroscopy is often the easiest method for colloidal nanomaterial characterization. However, due to the lack of a reliable method to extract nanoparticle shapes from absorption spectroscopy, it is generally treated as a more qualitative measure for metal nanoparticles. This work demonstrates a gold nanorod (AuNR) spectral morphology analysis tool, called AuNR-SMA, which is a fast and accurate method to extract quantitative structural information from colloidal AuNR absorption spectra. To demonstrate the practical utility of this model, we apply it to three distinct applications. First, we demonstrate this model's utility as an automated analysis tool in a high-throughput AuNR synthesis procedure by generating quantitative size information from optical spectra. Second, we use the predictions generated by this model to train a machine learning model to predict the resulting AuNR size distributions under specified reaction conditions. Third, we apply this model to spectra extracted from the literature where no size distributions are reported and impute unreported quantitative information on AuNR synthesis. This approach can potentially be extended to any other nanocrystal system where absorption spectra are size dependent, and accurate numerical simulation of absorption spectra is possible. In addition, this pipeline could be integrated into automated synthesis apparatuses to provide interpretable data from simple measurements, help explore the synthesis science of nanoparticles in a rational manner, or facilitate closed-loop workflows.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Influence of Ordered Mesoporous Oxides in Plasma-Assisted Ammonia Synthesis

Widespread implementation of dielectric barrier discharge (DBD)-assisted NH 3 synthesis, a nascent technology operating under sustainable, ambient conditions, is hindered by low energy yields due to, in part, poor fundamental understanding. Porous oxides used to support metal nanoparticle catalysts have shown significant energy yield contributions for DBD-assisted NH 3 synthesis even without metal. Using an AC-powered, coaxial, single-stage reactor at 16 kV with equimolar (N 2 /H 2 ) feed, we measured NH 3 synthesis rates in the presence of different nonordered oxides, ordered SiO 2 structures (SBA-15 and MCM-41), and ordered Al-incorporated analogues (γ-Al 2 O 3 -coated with varying Al-loadings and Al-substitution, respectively: Al 2 O 3 -SBA-15 and Al-MCM-41). We systematically quantified NH 3 energy yield dependence on pore structures and material identities (i.e., ordered pores and Al incorporation) known to facilitate higher DBD-assisted NH 3 synthesis rates. SBA-15 displayed a higher steady-state energy yield than MCM-41, indicating that framework type is a crucial factor, with both ordered porous systems outperforming fumed SiO 2 . 10 wt % Al maximized in situ NH 3 uptake among the various Al loadings, exhibiting a higher steady-state energy yield and similar power to SBA-15. However, Al-MCM-41 had a similar steady-state energy yield and lower power than MCM-41, likely due to the extended γ-Al 2 O 3 surface that has a dielectric constant higher than that of SiO 2 . Both Al-incorporated analogues benefit from surface acid sites that can adsorb NH 3 in situ, resulting in higher overall NH 3 energy yields than that of their parent ordered SiO 2 . Al 2 O 3 -SBA-15 shielded more NH 3 than Al-MCM-41, likely due to a higher acid site density than the acid site identity. Furthermore, Al incorporation via γ-Al 2 O 3 coating more successfully improves the NH 3 energy yield; together with the high-performing ordered framework, these analogues are potential metal catalyst supports with promising energy yields for DBD-assisted synthesis of NH 3 and other chemicals.

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

A physics informed model for the prediction of surface energies and the shape of metal particles

Surface energies of metal-based systems are important for determining the Wulff-constructed shapes of metal nanoparticles and understanding the stability. We have developed a physics informed method to predict the total energy of metal-based systems across a wide range of configurations. Our method has been tested against density functional theory (DFT) calculations for late transition metals. This method enables on-the-fly surface energy predictions based on the fundamental of materials property and allows for the Wulff construction of metal particles for a random number of elemental atoms and without the need for DFT calculations. By making a division between atoms in the different layers of the model system, we can improve the accuracy of the model, suggesting a dissimilarity between the electronic structure due to an alternating compression and expansion of atomic layers. We find that our model accurately and effectively provides valuable insights into the distribution and stability of nanoparticles.

Mandal, Shyama Charan (ORCID:0000000245882874)↗
DOE OSTI2025

Density Functional Tight Binding Insights into Plasmonic Silver–Platinum Nanoparticles and Alloys for Enhanced Photocatalysis

Developing accurate and efficient Slater-Koster (SK) tight-binding parameter sets is essential for quantum plasmonic studies of alloyed metal nanoparticles, as conventional time dependent density functional theory (TD-DFT) calculations are computationally prohibitive for larger clusters. In this work, we develop and validate density functional tight binding (DFTB) parameter sets for both ground state (GS-SK) and excited state (ES-SK) calculations to study the structural, electronic, and optical properties of silver (Ag), platinum (Pt), and Ag–Pt nanoalloys. Our investigation of the ground state properties demonstrates that the GS-SK parameters enable DFTB to closely reproduce the electronic structures of platinum clusters with diverse sizes and geometries – showing qualitative agreement with DFT for density of states (DOS) profiles and energy levels. The ES-SK parameters accurately describe excited-state properties compared to TD-DFT reference calculations, including the broad, featureless absorption profiles of Pt that are dominated by interband transitions. Using the ES-SK parameters within a real-time TD-DFTB framework, we compute size-dependent optical absorption spectra of Ag, Pt and Ag-Pt nanocubes containing up to 1099 atoms (size ∼4.18 nm). A detailed study of Ag–Pt and Pt-Ag core–shell nanoparticles shows quenching of the Ag plasmon resonance even at monolayer coverage for Ag-Pt, but not for Pt-Ag. We also show how to define submonolayer Ag-core Pt-shell cubic structures that have similar optical properties to those generated experimentally for much larger particles, which offers potential for describing plasmon-enhanced photocatalysis. Collectively, the GS-SK and ES-SK parameter sets provide an accurate, computationally efficient approach for modeling the complex optical and electronic behavior of noble–transition metal nanostructures and their alloys.

SPR↗