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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Sandwiching of MOF nanoparticles between graphene oxide nanosheets among ice grains

Current strategies to tailor the formation of nanoparticle clusters require specificity and directionality built into the surface functionalization of the nanoparticles by involved chemistries that can alter their properties. Here, we describe a non-disruptive approach to place nanomaterials of different shapes between nanosheets, i.e., nano-sandwiches, absent any pre-modification of the components. We demonstrate this with metal-organic frameworks (MOFs) and silicon oxide (SiO 2 ) nanoparticles sandwiched between graphene oxide (GO) nanosheets, MOF-GO and SiO 2 -GO, respectively. For the MOF-GO, the MOF shows significantly enhanced conductivity and retains its original crystallinity, even after one-year exposure to aqueous acid/base solutions, where the GO effectively encapsulates the MOF, shielding it from polar molecules and ions. The MOF-GOs are shown to effectively capture CO 2 from a high-humidity flue gas while fully maintaining their crystallinities and porosities. Similar behavior is found for other MOFs, including water-sensitive HKUST-1 and MOF-5, promoting the use of MOFs in practical applications. The nanoparticle sandwich strategy provides opportunities for materials science in the design of nanoparticle clusters consisting of different materials and shapes with predetermined spatial arrangements.

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

Valence-free open nanoparticle superlattices

A cornerstone of advanced materials design is establishing a framework for assembling nanoparticle superstructures with tailored symmetries. A longstanding challenge has been assembling diamond-like superstructures for photonic devices. Traditionally, such open superstructures require functionalized nanoparticles with directional or anisotropic interactions, reminiscent of valence bonding in a diamond. Here, we present a robust strategy for assembling valence-free nanoparticles into a broad array of cubic superstructures. By grafting nanoparticles with oppositely charged, end-functionalized water-soluble polymers of adjustable molecular weight, we gain control over electrostatic interactions and conformational constraints. This unified approach yields lattices analogous to rock salt, CsCl, zinc-blende, diamond, and the rare simple cubic phase, with tunable lattice constants. Theoretical models and simulations elucidate the underlying interactions, providing a framework for engineering valence-free nanoparticle superlattices.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Flow synthesis of iron oxide nanoparticles: using multiple precursor additions to improve size control

Controlling the size of iron oxide nanoparticles while maintaining uniformity in flow-based synthesis systems has been a great challenge in nanoparticle synthesis. Using an extended LaMer mechanism, we improve both the size and shape uniformity as compared to a conventional flow synthesis. The key to this approach is the injection of additional Fe precursor during the flow reaction, providing extra precursor during the growth process leading to a size focusing step. This approach has also allowed for the systematic variation of the nanoparticle size produced in the flow reaction. This work represent a new synthetic concept for improving the size uniformity of iron oxide nanoparticles in flow-based synthesis and has potential for application across a wide range of nanoparticle systems.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Morphological descriptors of nanoparticles: The link between atomistic structures and x-ray absorption spectra

Understanding and quantifying the morphology of nanoparticles are essential for linking their atomic structure to diverse applications and verifying theoretical models. While experimental information on the structure of nanoparticles in the size range below ∼5 nm can be extracted from x-ray absorption spectroscopy using a small number of descriptors—most commonly coordination numbers—developing an understanding of morphology descriptors from experimental data remains a challenge. Here, in this study, we introduce NanoGene, a genetic algorithm-based method for generating structurally diverse nanoparticle models guided by user-defined descriptors. We establish correlations among structural, size-related, and morphological descriptors and demonstrate how experimentally accessible parameters, such as coordination numbers, can be leveraged to infer otherwise inaccessible ones, such as the generalized coordination number or particle oblateness. Principal component and clustering analyses reveal the relative importance of descriptors, with the number of atoms emerging as a key discriminant of the nanoparticle structure. By providing both the methodology and an extensive dataset of nanoparticle geometries, this work offers a practical foundation for descriptor-based analysis and interpretation of experimental observations, bridging the gap between local atomic coordinates and global morphological characterization.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Quantifying dispersity in size and shape of nanoparticles from small-angle scattering data using machine learning based CREASE

Here, we use machine learning (ML) enhanced computational reverse engineering analysis of scattering experiments (CREASE) to interpret small-angle X-ray scattering (SAXS) data obtained from a system of nanoparticles without a priori knowledge of their exact shapes (e.g. spheres or ellipsoids), sizes (0.5–50 nm) and distributions. The SAXS measurements yielded three categories of scattering profiles exhibiting 'strong', 'weak' and 'no' features. Diminishing features (e.g. broadening or disappearing peaks) in scattering profiles have always been attributed to the presence of significant dispersity in the system. Such featureless SAXS data are not suitable for traditional analysis using analytical models. If one were to fit a relevant analytical model (e.g. the lmfit analytical model for polydisperse spheres) to these 'weak' and 'no' SAXS profiles from our nanoparticle systems, one would obtain non-unique interpretations of the data. Relying on electron microscopy to identify the distributions of nanoparticle shapes and sizes is also unfeasible, especially in high-throughput synthesis and characterization loops. In such situations, to identify the distributions of particle sizes and shapes that could be present in the sample, one must rely on methods like ML-CREASE to interpret the data quickly and output all relevant interpretations about the structure present in the system. The ML-CREASE optimization loop takes the experimental scattering profile as input and outputs multiple candidate solutions whose computed scattering profiles match the SAXS profile input. The ML-CREASE method outputs distributions of relevant structural features, such as the volume fraction of the nanoparticles in the system and the mean and standard deviation of the particle size and aspect ratio, assuming a type of distribution (e.g. normal, log-normal) for size and aspect ratio. We find that, for the SAXS profiles analyzed here, accounting for the shape dispersity along with size dispersity of the nanoparticles using ML-CREASE improved the match between the computed scattering profiles and input experimental profiles.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Signal Differentiation of Moving Magnetic Nanoparticles for Enhanced Biodetection and Diagnostics

Magnetic nanoparticles are extensively utilized as markers/signal labelling in various biomedical applications. Detecting and distinguishing magnetic signals from similarly sized moving magnetic nanoparticles in microfluidic systems is crucial yet challenging for biosensing. In this study, we have developed an original method to detect and differentiate magnetic signals from moving superparamagnetic (SPM) and ferrimagnetic (FM) nanoparticles of comparable sizes. Our approach utilizes a highly sensitive magnetic-coil-based sensor that harnesses the combined effects of giant magnetoimpedance (GMI) and an LC-resonance circuit, offering performance superior to that of conventional GMI sensors. Iron oxide nanoparticles, which have similar particle sizes but differing coercivities (zero for SPM and non-zero for FM) or similar zero coercivities but differing particle sizes, flow through the magnetic coil at controlled velocities. Their distinct effects are analyzed through changes in the complex impedance of the sensing system. Our findings provide a unique pathway for utilizing SPM and FM nanoparticles as innovative magnetic markers to identify specific biological entities, thereby expanding their potential applications.

Hwang, Kee Young↗
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

Annealing-Driven Phase Control Enables Plasmonic Tunability in Alloy Nanoparticles

A critical aspect of designing and realizing useful solid state materials is controlling phase and structure to tailor physical properties. While common for semiconductor and quantum materials, plasmonic materials have inhabited a narrow phase space typically comprising one or two elements, e.g., face-centered cubic metals. While this simplicity has enabled robust use and understanding of Au and Ag nanoparticles, it has also limited the design and manipulation of solid state properties. Here, we show that by tuning the phase and elemental composition of binary Au−Sn nanoparticles, the steady-state absorbance and ultrafast thermalization properties of plasmonic nanoparticles can be controlled. Solid state characterization suggests this is due to the dealloying of Sn and destabilization of the AuSn phase, leading to higher quality Au 5 Sn intermetallic phases alongside Au. Consequently, this work shows that phase control can profoundly influence the properties of plasmonic nanoparticles, providing important tunability for applications in catalysis, photothermal heating, and sensing.

Gold↗
DOE OSTI2025

Solution‐Phase Metathesis of Li 3 N and FeCl 3 to Synthesize Fe 2 N/Fe 3 N Nanoparticles

Soft magnetic materials play key roles in the flow of energy in electrically driven machines and power conversion electronics, and there is a great need for improvements in their magnetic properties to provide the right combination of high saturation magnetization, low coercivity, and high permeability. Most phases of iron nitride (Fe x N) are soft magnetic materials with these characteristics, but they exist as numerous phases which are not all stoichiometric compounds. While the production and magnetic properties of the different phases of bulk iron nitride are well known, accessing phase‐pure nanoscale iron nitride consistently remains a challenge. Most methods for the synthesis of iron nitride nanoparticles require complicated apparatus to achieve high‐temperature nitriding of nanoparticle precursors with gaseous nitrogen sources such as ammonia. The first solution‐phase metathesis reaction between FeCl 3 and Li 3 N in oleylamine is developed to directly synthesize Fe 2 N/Fe 3 N nanoparticles, requiring only a fume hood, glove box, standard chemistry laboratory glassware, and equipment. Finally, the ≈10–15 nm spheres display nearly soft magnetic behavior with a saturation magnetization ≈50–60 A m 2 kg −1 , coercivities between 40–50 kA m −1 , and susceptibility values from 0.0001–0.0006 m 3 kg −1 , well within the ranges reported with other published Fe x N nanoparticle synthesis methods.

iron nitride↗
DOE OSTI2024

Nanocompression of 20 nm Silver Nanoparticles: In situ Aberration‐Corrected TEM and Atomistic Simulations

Single‐crystalline nanoparticles play an increasingly important role in a wide variety of fields including pharmaceuticals, advanced materials, catalysts for fuel cells, energy materials, as well as environmental detection and monitoring. Yet, the deformation mechanisms of very small nanoparticles are still poorly understood, in particular the role played by single dislocations and their interaction with surfaces. Here, in this work, silver nanoparticles with particularly small dimensions (≈20 nanometers in diameter) are compressed in situ in an aberration‐corrected transmission electron microscopy (TEM) and molecular dynamics (MD) simulations. During compression, the emergence of both dislocations and nanotwins are observed. However, these defects prove to be unstable and disappear upon removal of the indenter. Atomistic simulations confirm the role played by image stresses associated with the nearby surfaces and the reduction in dislocation line length as it approaches the free surface, thereby supporting the experimental observations. These results provide justification for the frequent observation of the absence of dislocations in nanoparticles of a few nanometers in size during in situ experiments, even after significant deformation. This phenomenon contributes to the self‐healing of samples through dislocation ejection toward the surfaces.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Pressure-Dependent Phase Behavior of Chemically Synthesized Ytterbium Hydride Nanoparticles and Confinement in CMK-3

In this work, we developed a chemical synthesis protocol to prepare both spherical and rod shaped YbH x nanoparticles and infiltrate a mesoporous CMK-3 structure with YbH x nanoparticles. The phase evolution of the YbH x nanoparticles was monitored as a function of the pressure in a diamond anvil cell. The cell volume of the Yb atom showed an unexpected positive deviation from the calculated equation of state (EoS) for the α-phase (space group Pnma) of YbH x . Additionally, the β-phase (space group Fm3̅m) YbH x nanoparticles appeared to become amorphous at approximately 27 GPa, although the same behavior was not observed in the Pnma (α-phase). The Pmna phase remained stable (measured up to 59.3 GPa) and showed a significantly higher than expected volume per Yb atom relative to the calculated EoS. This deviation could be attributed to the nanoscale effect on the thermodynamics of ytterbium hydride formation, which could provide a path forward to accessing higher order ytterbium hydrides (YbH x , x > 3) at pressures much lower than in the bulk metal.

diamond anvil cell↗
DOE OSTI2024

Surface Self-Diffusion Induced Sintering of Nanoparticles

Despite the critical role of sintering phenomena in constraining the long-term durability of nanosized particles, a clear understanding of nanoparticle sintering has remained elusive due to the challenges in atomically tracking the neck initiation and discerning different mechanisms. Through the integration of in situ transmission electron microscopy and atomistic modeling, this study uncovers the atomic dynamics governing the neck initiation of Pt–Fe nanoparticles via a surface self-diffusion process, allowing for coalescence without significant particle movement. Real-time imaging reveals that thermally activated surface morphology changes in individual nanoparticles induce significant surface self-diffusion. Further, the kinetic entrapment of self-diffusing atoms in the gaps between closely spaced nanoparticles leads to the nucleation and growth of atomic layers for neck formation. This surface self-diffusion-driven sintering process is activated at a relatively lower temperature compared to the classic Ostwald ripening and particle migration and coalescence processes. The fundamental insights have practical implications for manipulating the morphology, size distribution, and stability of nanostructures by leveraging surface self-diffusion processes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Mitigating Battery Cell Failure: Role of Ag‐Nanoparticle Fillers in Solid Electrolyte Dendrite Suppression

Abstract The development of solid‐state batteries (SSBs) with lithium Li metal anodes holds significant promise for enhancing the energy density and safety of next‐generation energy storage systems. However, their commercialization is hindered by challenges related to Li dendrite formation, which can lead to short circuits and battery failure. In this study, the role of Ag nanoparticles embedded within solid electrolytes (SE) is investigated in suppressing dendrite propagation. The results demonstrate that Ag nanoparticles effectively mitigate two key failure mechanisms: (1) dendrite growth within porous networks at low current densities and (2) stress intensification‐induced SE fracture at higher current densities (12 mA cm −2 ). Ex situ characterization using focused‐ion beam – scanning electron microscopy (FIB–SEM) and energy dispersive X‐ray spectroscopy (EDS,) reveals that Ag nanoparticles migrate alongside advancing Li dendrites, promoting homogeneous dendrite growth and reducing the likelihood of localized stress concentrations. Additionally, the incorporation of Ag nanoparticles is shown to facilitate a more uniform Li distribution toward the anode side, which can potentially enable the use of higher charging rates in SSBs. This study provides a new perspective on Li dendrite suppression and presents new opportunities for enhancing the performance and safety of SSBs.

Diallo, Mouhamad Said↗
DOE OSTI2026

Monolayer Films of Binary Metal Oxide Nanoparticles for Carbon Nanotube Synthesis

Binary metal oxide nanoparticles (biMO-NPs) combining transition and main-group metals with well-organized atomic architectures have unique potential as robust and economical heterogeneous catalysts. Herein, metal oxide nanoparticles (CoAlxOy) using cobalt and aluminum were synthesized, and their structure, morphology, and chemical composition were investigated using various characterization techniques. The biMO-NPs, which had a Gaussian-type size distribution (∼6 nm), were assembled on plain silicon substrates modified chemically with linker molecules bearing suitable end groups. Surface analysis revealed an ordered, uniform, close-packed arrangement of biMO-NPs forming a monolayer architecture with nanoscale thickness (∼12 nm), high surface uniformity, and negligible defects. The nanoparticle monolayer film (NP-MF) was employed as a catalyst to grow carbon nanotube (CNT) forests via the thermal chemical vapor deposition (CVD) method, similar to those grown from catalyst thin films deposited by physical vapor deposition. Structural characterization confirmed the growth of a dense, uniform, high-quality vertically aligned carbon nanotube (VA-CNT) forest with a length of ∼125 µm, which is comparable to the VA-CNTs grown from expensive thin films. Thus, CNT growth was successfully catalyzed by the biMO-NPs, highlighting a simple and inexpensive alternative for catalyst deposition. In this innovative wet-chemistry approach, the catalyst and catalyst support are combined within a single nanoparticle before NP-MF assembly. Interestingly, this approach provides a scalable and cost-effective pathway for CNT growth, eliminating the need for expensive thin deposition techniques.

Regmi, Bishow [University of Cincinnati]↗
DOE OSTI2025

Tuning transition metal nanoparticles on a non-traditional support via experimental design

The ability to control metal nanoparticle size and morphology on supported catalysts is crucial for optimizing catalytic performance in targeted applications. Here, this work presents a systematic approach for tuning Ni particle and crystallite size on an unconventional, low-porosity silica fume support through select thermal treatments. The catalyst was synthesized via the deposition of nickelocene onto silica fume, resulting in well-dispersed Ni nanoparticles. A face-centered central composite design was employed to systematically assess the effects of time, temperature, and sintering gas environment on metal particle growth. The results demonstrate that the sintering gas environment is the primary factor governing particle and crystallite evolution, with temperature as the next most significant influence. Nickel nanoparticles sintered at temperatures of 650 °C and above under inert conditions exhibited substantial growth and polycrystalline structures, whereas samples treated in oxidative environments formed NiO, restricting particle mobility. Minimally oxidative (500 ppm O₂) environments facilitated rapid sintering while effectively removing residual ligands from the one-step nickelocene deposition process. Extensive structural characterization via a combination of scanning transmission electron microscopy, X-ray diffraction, hydrogen temperature programmed reduction, and small-angle X-ray scattering revealed that oxidative treatments enhanced metal-support interactions, as evidenced by increased reduction temperatures and narrower particle size distributions. These findings establish quantitative relationships between sintering parameters and Ni nanoparticle characteristics, providing a framework for rational catalyst design through controlled thermal treatments. This methodology is broadly applicable to other catalytic systems and provides a quantitative foundation for catalyst design.

CVD↗
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↗
DOE OSTI2024

Chemical state of nickel nanoparticles during the oxygen evolution reaction in a carbonate-bicarbonate buffer solution

The chemical state of nickel anodes during the oxygen evolution reaction can impact their electrocatalytic performance. Here, X-ray photoelectron and absorption spectroscopies reveal the chemical state of nickel nanoparticles under oxygen evolution reaction conditions in amildly alkaline carbonate-bicarbonate buffer solution. Ni 2+ and Ni 3+ species are observed at the reaction onset potential with a 7:4 ratio, with no remaining metallic nickel. These species include NiO, which increasingly converts to other Ni 2+ and Ni 3+ species once the potential is increased above the onset potential. Conversely, when a 20-nm-thick nickel film is used instead of nickel nanoparticles, a significant amount of metallic nickel remains in the inner layers. Nickel nanoparticles also undergo significant morphological and structural changes during the reaction, as evidenced by ex situ transmission electron microscopy. Amorphization of the nanoparticles is attributed to significant H 2 O incorporation, with the oxygen intensity increasing both in operando and ex situ measurements.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Leveraging Hydration Forces for Size-Specific Nanoparticle Enrichment with a Redox-Responsive Silica-Binding Elastin-Like Polypeptide

Elastin-like polypeptides (ELPs) are low-complexity proteins that coacervate above a characteristic lower critical solution temperature (LCST). While the thermoresponsiveness of ELPs has been widely exploited in the biomedical and biomaterials fields, their ability to mediate nanoparticle assembly below their transition temperature remains largely unexplored. Here, we show that unmodified ELPs induce the reversible flocculation of silica nanoparticles (SiNPs) by forming backbone hydrogen bonds with surface silanols. Interparticle bridging is modulated by ELP length and concentration and by the presence of N- and C-terminal anchoring groups such as a cysteine residue and a Car9 silica-binding peptide. Using a redox-responsive fusion protein consisting of disulfide-bonded ELP domains terminated by Car9 segments, we stabilize 20 nm SiNPs under oxidizing conditions while triggering particle flocculation upon addition of reductant. We find that SiNP sedimentation under reducing conditions exhibits a sharp dependency on particle size that arises from the curvature-dependent structure of surface silanols. While the isolated silanols of SiNPs smaller than 30 nm are efficiently engaged by the ELP domains of Car9-anchored proteins, repulsion forces associated with the presence of a layer of molecular water together with increased electrostatic repulsion preclude efficient engagement of H-bonded silanols displayed on the surface of SiNPs larger than 60 nm. We harness these findings to selectively enrich SiNPs based on size and expand the concept to titania (TiO2) by demonstrating that rutile nanoparticles can be stabilized or sedimented with solid-binding ELPs by adjusting the solution pH to promote or discourage the formation of a hydration layer. These strategies should prove broadly useful for the separation of other oxides and their polymorphs and provide a tunable strategy for nanoparticle assembly and bioinspired colloidal design.

ELP↗