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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 OSTI2026

Non-equilibrium reducing flame aerosol process to create supported high-entropy alloy nanoparticles

High-entropy alloy (HEA) nanomaterials provide opportunities and property combinations for energy and electronic applications, but their practical synthesis faces challenges of elemental immiscibility, metal reducibility, and particle aggregation during their synthesis. Herein, we report a broadly applicable non-equilibrium, scalable, and in-situ reducing flame aerosol process for synthesis of supported HEA nanoparticles. This versatile process can directly load a high concentration of 2 ~ 4 nm HEA nanoparticles on various 1- to 3-dimensional supports. Notably, simultaneous formation of HEA nanoparticles and a mesoporous silica support was successfully realized in a single step. Exploration of this process demonstrates the role of kinetics and entropy on decreasing alloy particle size and altering the reducibility of elements. We propose an entropy-induced reduction mechanism to incorporate oxidizable elements into HEAs, which extends the compositional space of HEA nanoparticles. As a representative catalytic application, we present a RuPdOsIrPt/graphene electrocatalyst with high activity and stability for hydrogen oxidation reaction. Our findings open horizons for high-performance HEA design and applications in diverse fields such as catalysis, electrochemistry, and sensing.

organic↗
DOE OSTI2026

Image processing pipeline for AI-driven nanoparticle megalibrary characterization

Recent innovations have made it possible to produce megalibraries, millions of structurally and compositionally distinct nanoparticles on a chip. These megalibraries yield vast volumes of data that are impossible to analyze manually, necessitating the development of automated tools. In previous work, we created a binary classification machine learning model to select quality nanoparticle images for downstream analysis. In this work, we show that adding a custom image processing step before training can produce significantly higher-performing models in a fraction of the time and make them more robust to different image noise levels and microscope acquisition settings. The image processing pipeline proposed here effectively cleans raw nanoparticle images, enhances key features, and allows us to use much lower resolution images and simpler neural network model architectures. These features result in higher performance and significant cost savings. Experiments demonstrate superior performance relative to baseline, including an 18.2% improvement in recall and a 13.1% increase in accuracy. Given the high cost of downstream analysis, it is critical to minimize false positives, and our best-performing model reaches a precision of 95.9% and a weighted F-score of 95.1% on an unseen test set. Additionally, model training time is reduced from hours to less than a minute. We also show that, using this custom image processing pipeline, model performance is significantly improved at lower pixel resolutions compared to downsizing alone. We expect that adopting this pipeline for AI-driven automated nanoparticle characterization will allow researchers to rapidly and accurately analyze much greater volumes of data, thereby accelerating materials discovery.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Oxidation and recharge of reactive structural Fe( II ) in titanomagnetite (Fe 3− x Ti x O 4 ) nanoparticles

Mixed-valent iron oxide minerals, such as magnetite (Fe(II)(Fe(III)) 2 O 4 ), are an important source of solid-state ferrous iron (Fe(II)) that can impact the speciation and transport of electron accepting contaminants in the Earth’s subsurface, such as radioactive pertechnetate ( 99 Tc(VII)O 4 − ). However, when oxidizing conditions are encountered, structural Fe(II) at the mineral surface is consumed yielding a maghemite (γ-Fe(III) 2 O 3 )-like layer that limits further electron transfer. This oxidized surface layer can be recharged back to the original Fe(II)/(III) ratio by re-exposure to reducing conditions, i.e., aqueous solutions containing Fe 2+ . However, for substituted magnetite (Fe 3−x M x O 4 , M = transition metal cation), the extent of this redox recyclability is unclear. Here, we examine oxidation and recharge for titanomagnetite (Fe 3−x Ti x O 4 ) nanoparticles, where the Fe(II)/Fe(III) ratio varies by the amount of Fe(II) required to charge balance the titanium (Ti(IV)) substituted into the structure. The nanoparticles were synthesized by aqueous precipitation from a solution containing ferrous, ferric and titanium chloride at room temperature. Transmission electron microscopy combined with electron energy loss spectroscopy revealed that rapid precipitation formed core–shell-like nanoparticles consisting of a hyperstoichiometric magnetite core, with Ti(IV) and charge balancing Fe(II) enriched at the surface. This surface enrichment made Fe(II) more available for electron transfer reactions with redox active solution species. Examination of oxidation by H 2 O 2 followed by recharge with aqueous Fe 2+ indicates recyclability of reducing equivalents in the nanoparticles, yielding a core recrystallized to stoichiometric magnetite and a shell bearing excess Fe(II) to charge balance the substituted Ti(IV). The recharged particles are shown to have restored redox reactivity with 99 Tc(VII)O 4 − resulting in reduction to 99 Tc(IV)O 2 and oxidation of the structural Fe(II) to Fe(III).

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

In situ transmission electron microscopy observations of CaCO 3 crystallization onto polysaccharide-coated nanoparticles

Polysaccharides and proteoglycans are widely associated with the organic matrix at sites of CaCO 3 biomineralization, and previous studies indicate that these macromolecules may confer greater roles in mineral nucleation than previously recognized. This investigation uses in situ liquid-phase transmission electron microscopy (LP-TEM) to observe CaCO 3 nucleation onto aminated silica (SiO 2 –NH 3 + ) nanoparticles treated with a layer of chitosan (near-neutral derivative of chitin) or heparin (a carboxylated and highly sulfated glycosaminoglycan). In the absence of polysaccharides, few CaCO 3 particles formed and exhibited mobility. However, the SiO 2 –NH 3 + nanoparticles were enveloped in a region of higher mass density relative to the bulk solution, suggesting the development of a local solute-rich environment that surrounds the charged NH 3 + groups. The heparin- or chitosan-coated silica particles also exhibited regions of higher mass density around the nanoparticles. In the presence of these polysaccharide coatings, we observed the nucleation of abundant CaCO 3 particles whereby the polyanionic heparin promoted more nucleation than the weakly cationic chitosan. Many crystallites appeared to form at the polysaccharide–TEM cell membrane–solution interface, further indicating interfacial and macromolecule-specific control on crystallization. The combined results demonstrate that chitosan and heparin have an appreciable effect on the timing, size, and location of CaCO 3 nucleation compared to the polysaccharide-free nanoparticles.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Cross-reactive sarbecovirus antibodies induced by mosaic RBD nanoparticles

Broad immune responses are needed to mitigate viral evolution and escape. To induce antibodies against conserved receptor-binding domain (RBD) regions of SARS-like betacoronavirus (sarbecovirus) spike proteins that recognize SARS-CoV-2 variants of concern and zoonotic sarbecoviruses, we developed mosaic-8b RBD nanoparticles presenting eight sarbecovirus RBDs arranged randomly on a 60-mer nanoparticle. Mosaic-8b immunizations protected animals from challenges from viruses whose RBDs were matched or mismatched to those on nanoparticles. Here, we describe neutralizing mAbs isolated from mosaic-8b-immunized rabbits, some on par with Pemgarda, the only currently FDA-approved therapeutic mAb. Deep mutational scanning, in vitro selection of spike resistance mutations, and single-particle cryo-electron microscopy structures of spike–antibody complexes demonstrated targeting of conserved RBD epitopes. Rabbit mAbs included critical D-gene segment RBD-recognizing features in common with human anti-RBD mAbs, despite rabbit genomes lacking an equivalent human D-gene segment, thus demonstrating that the immune systems of humans and other mammals can utilize different antibody gene segments to arrive at similar modes of antigen recognition. These results suggest that animal models can be used to elicit anti-RBD mAbs with similar properties to those raised in humans, which can then be humanized for therapeutic use, and that mosaic RBD nanoparticle immunization coupled with multiplexed screening represents an efficient way to generate and select broadly cross-reactive therapeutic pan-sarbecovirus and pan-SARS-CoV-2 variant mAbs.

Science & Technology - Other Topics↗
DOE OSTI2025

Robust measurement of microbial reduction of graphene oxide nanoparticles using image analysis

ABSTRACT Shewanella oneidensis ( S. oneidensis ) has the capacity to reduce electron acceptors within a medium and is thus used frequently in microbial fuel generation, pollutant breakdown, and nanoparticle fabrication. Microbial fuel setups, however, often require costly or labor-intensive components, thus making optimization of their performance onerous. For rapid optimization of setup conditions, a model reduction assay can be employed to allow simultaneous, large-scale experiments at lower cost and effort. Since S. oneidensis uses different extracellular electron transfer pathways depending on the electron acceptor, it is essential to use a reduction assay that mirrors the pathways employed in the microbial fuel system. For microbial fuel setups that use nanoparticles to stimulate electron transfer, reduction of graphene oxide provides a more accurate model than other commonly used assays as it is a bulk material that forms flocculates in solutions with a large ionic component. However, graphene oxide flocculates can interfere with traditional absorbance-based measurement techniques. This study introduces a novel image analysis method for quantifying graphene oxide reduction, showing improved performance and statistical accuracy over traditional methods. A comparative analysis shows that the image analysis method produces smaller errors between replicates and reveals more statistically significant differences between samples than traditional plate reader measurements under conditions causing graphene oxide flocculation. Image analysis can also detect reduction activity at earlier time points due to its use of larger solution volumes, enhancing color detection. These improvements in accuracy make image analysis a promising method for optimizing microbial fuel cells that use nanoparticles or bulk substrates. IMPORTANCE Shewanella oneidensis ( S. oneidensis ) is widely used in reduction processes such as microbial fuel generation due to its capacity to reduce electron acceptors. Often, these setups are labor-intensive to operate and require days to produce results, so use of a model assay would reduce the time and expenses needed for optimization. Our research developed a novel digital analysis method for analysis of graphene oxide flocculates that may be utilized as a model assay for reduction platforms featuring nanoparticles. Use of this model reduction assay will enable rapid optimization and drive improvements in the microbial fuel generation sector.

Bennett, Danielle T. (ORCID:0009000188748827)↗
DOE OSTI2024

Science Driven Discovery of Nanoparticle Photocatalysts

Photocatalytic water splitting using suspensions of nanoparticle photocatalysts is a promising route to economically sustainable production of green hydrogen. The principal challenge is to develop photocatalysts with overall solar-to-hydrogen conversion efficiency that exceeds 10 percent. In this project we have developed a new platform for investigating candidate materials for photocatalytic water splitting. Our platform consists of patterned Au electrodes and a Ag/AgCl reference electrode on an insulating substrate onto which we disperse nanoparticle photocatalysts. We then cover the substrate with a thin layer of ionogel containing a protic ionic liquid that dissolves water from the ambient. Using this platform we have demonstrated photoelectrochemical activity mapping for single and small clusters of BiVO 4 nanoparticle photocatalysts and correlated these results to their Raman and photoluminescence spectra. The preliminary results suggest a strong correlation for low efficiency nanoparticles, followed by saturation for those with higher activities, indicating that interface reaction or electrolyte transport become the limiting factor. We anticipate that further application of this platform to investigation of candidate photocatalyst materials will provide useful insights into the mechanisms that limit their performance.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Multi‐Scale Model‐Informed Deep Learning for Plasma‐Nanoparticle Interaction

The Overarching Goal of this proposed research is to understand and quantitively determine the interactions between non-thermal plasma (hot electrons, reactive radicals, vibrationally excited species) and surface reactions on influencing the activity and selectivity of the desired reactions via developing multi-scale model informed deep learning algorithm. Investigating non-thermal plasma-surface interaction is feasible due to the low bulk temperature in the discharge region. To investigate the role of plasma-nanoparticle interaction on enhancing the reaction kinetics, we will focus on ammonia cracking to generate clean hydrogen over earth-abundant, non-critical metallic nanoparticles, which is of great significance for decarbonization. We hypothesize that (1) reactive radicals interacting with surface reaction species via Eley–Rideal mechanism will significantly lower the energetics of the potential rate-limiting step of nitrogen formation; (2) the surface will be charged heterogeneously under non-thermal plasma conditions and the charged site will lower the energetics of ammonia cracking through Langmuir– Hinshelwood mechanism; (3) vibrationally excited ammonia will further promote the initial N-H bond cleavage. To access the hypothesis, we will (1) reveal the surface charge effects on tunning the reaction energetics via interpretable, physics-informed deep learning accelerated density functional theory (DFT) calculations; (2) determine the reactive radicals interacting with surface reaction species on tuning the reaction energetics via DFT; (3) reveal the surface charge effects on tunning the reaction energetics via DFT and deep learning models, (4) quantify how vibrationally excited species, reactive radicals, and surface charging effects on enhancing the catalysis via developing DFT-based microkinetic modeling (MKM) and active learning. Deep and active learning of plasma-nanoparticle interactions effects on enhancing ammonia cracking to generate hydrogen represents a new paradigm for designing high performance plasma materials. The fundamental science of how plasma-nanoparticle interactions will change the plasma kinetics and will improve the energy efficiency for decarbonization and sustainability. The interpretable and physics-informed machine learning model will accelerate low temperature plasma chemistry and material discovery with physics rules and model interpretation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Multiscale Modeling of Nanoparticle Precipitation in Oxide Dispersion-Strengthened Steels Produced by Laser Powder Bed Fusion

Laser Powder Bed Fusion (LPBF) enables the efficient production of near-net-shape oxide dispersion-strengthened (ODS) alloys, which possess superior mechanical properties due to oxide nanoparticles (e.g., yttrium oxide, Y-O, and yttrium-titanium oxide, Y-Ti-O) embedded in the alloy matrix. To better understand the precipitation mechanisms of the oxide nanoparticles and predict their size distribution under LPBF conditions, we developed an innovative physics-based multiscale modeling strategy that incorporates multiple computational approaches. These include a finite volume method model (Flow3D) to analyze the temperature field and cooling rate of the melt pool during the LPBF process, a density functional theory model to calculate the binding energy of Y-O particles and the temperature-dependent diffusivities of Y and O in molten 316L stainless steel (SS), and a cluster dynamics model to evaluate the kinetic evolution and size distribution of Y-O nanoparticles in as-fabricated 316L SS ODS alloys. The model-predicted particle sizes exhibit good agreement with experimental measurements across various LPBF process parameters, i.e., laser power (110–220 W) and scanning speed (150–900 mm/s), demonstrating the reliability and predictive power of the modeling approach. The multiscale approach can be used to guide the future design of experimental process parameters to control oxide nanoparticle characteristics in LPBF-manufactured ODS alloys. Additionally, our approach introduces a novel strategy for understanding and modeling the thermodynamics and kinetics of precipitation in high-temperature systems, particularly molten alloys.

Wang, Zhengming (ORCID:0000000241627112)↗
DOE OSTI2025

Synthesis of Solid-Solution Mn x Zn 1– x O Nanoparticles and their Electrochemical Oxidation of Furfural

Electrochemical valorization of biomass-derived substrates has become a prominent area of research due to its potential to produce value-added products from renewable feedstocks in a more sustainable way. First-row transition metal electrodes are compelling candidates for these conversions due to their stability, abundance, and cost-effectiveness. Herein, we report on the colloidal synthesis of Mn x Zn 1– x O (x = 0.3-0.7) nanoparticles and their electrocatalytic activity towards furfural oxidation. We find that the hindrance of a MnO impurity can be achieved by leveraging the oxidation state of the Mn precursor. The Mn x Zn 1– x O composition closely follows the ratio of precursors, with all the nanoparticles having a wurtzite structure as determined by ICP-MS and PXRD, respectively. XANES and XPS revealed the presence of Mn in different oxidation states with the ratio of these varying based on the composition. When comparing the electrocatalytic activity of the monometallic and bimetallic oxides for furfural oxidation, a decrease in current density was observed with increasing Zn content. We find the Mn x Zn 1– x O nanoparticles favor the formation of the 6 e - oxidation product 5-hydroxy-2(5H)-furanone, while both monometallic oxides primarily yield CO 2 and other deeply oxidized products as the majority pathway. Furthermore, these findings can contribute towards the design and synthesis of more active and selective electrocatalyst.

Aldehydes↗
DOE OSTI2025

Volumetric Shaping of Nanoparticle-DNA Crystals by Light-Induced Milling

DNA-programmable self-assembly enables the formation of nanoparticle crystals with controlled lattice symmetry. While this approach offers the formation of complexly ordered nanostructures for optical, mechanical, and biological applications, a mesoscale control over such nanomaterials is limited. Directing the material formation process through the assembly pathway or external fields allows for modulating crystal morphology, but achieving arbitrary morphology remains challenging. Here, we present a photothermal method for shaping 3D DNA-programmable crystals of gold nanoparticles. Through local heating of nanoparticles due to plasmonic light absorption, we induce targeted volumetric dissolution of specifically defined crystal areas with micron-scale accuracy. This technique effectively prescribes crystal shaping and creates arbitrarily shaped voids within crystals. We further investigate both computationally and experimentally the key factors governing volumetric material subtraction. The developed automated light-milling platform enables the fabrication of nanomaterials exhibiting both DNA-programmable nanoscale order and custom-designed mesoscale architecture.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Plasmonic Hybridization and Near-Field Localization in Gold “Dog Bone” Nanoparticles

Gold nanoparticles with complex anisotropic geometries offer unique opportunities for tailoring plasmonic near-fields beyond the limits of conventional nanorods. Here we combine photon-induced near-field electron microscopy (PINEM) and full-wave simulations to resolve plasmon hybridization and near-field localization in gold dog-bone nanoparticles and their dimers with and without conformal SiO 2 shells. We demonstrate that the dog-bone geometry drives unconventional polarization-dependent field confinement, including pronounced tip-localized near-fields under both longitudinal and transverse excitation. Conformal SiO 2 shells red-shift the plasmon resonances through dielectric screening and prevent charge-transfer coupling in adjacent dimers. Depending on the dimer orientation and excitation polarization, coupled structures exhibit distinct bonding- and antibonding-like hybridized modes as well as interparticle near-field channels. However, weakly interacting dimers retain largely independent particle responses with geometry-governed asymmetries. The close agreement between PINEM measurements and simulations establishes a direct picture of how shape, dielectric environment, and nanoscale coupling together define plasmonic modes in complex anisotropic nanoparticles. These findings provide design principles for engineering localized optical fields in plasmonic nanoscale structures.

hybridization↗
DOE OSTI2025

Solution‐Processed Spin‐Polarized Light‐Emitting Diodes of Colloidal Quantum Wells and Magnetic Nanoparticles

Electrical injection of spin-polarized carriers into semiconductors enables circularly-polarized emission from spin-polarized light-emitting diodes (spin-LEDs). The incredible level of tunability of magnetic and electronic properties in colloidal nanocrystals offers unprecedented opportunities for the modulation of polarization of light in solution-processed spin-LEDs based on magnetic nanoparticles unlike epitaxially grown spin-LEDs restricted by a very limited range of materials for their exploitation, and solution-processed spin-LEDs based on chiral molecules, which do not allow the modulation of polarization in general. Here, it is shown that electrical injection of spin-polarized electrons from magnetic Fe 3 O 4 nanoparticles into CdSe/CdZnS core/shell colloidal quantum wells (CQWs) in solution-processed LEDs that allows for polarization modulation of electroluminescence. In this structure, a monolayer of face-down oriented CQWs is deposited as an active layer to avoid polarization losses due to the hopping of the electrons between the CQWs before the radiative recombination process. In this solution-processed spin-LED, the circular polarization reaches 4.5% at 3 K and survives up to 100 K. A net circular polarization is observed at zero magnetic field up to 100 K because of the remnant magnetization of the Fe 3 O 4 nanoparticles. This new colloidal spin-LED architecture presents significant prospects for future solution-processed advanced opto-spintronic devices.

circularly polarized electroluminescence↗
DOE OSTI2025

Metal–Organic Frameworks at the Edge of Stability: Mediating Node Distortion to Access Metastable Nanoparticle Polymorphs

Metal-organic frameworks (MOFs) are emerging as unconventional precursors for nanoparticle synthesis, with potential to leverage their tunable structures and chemistry to achieve nanomaterials with structures and compositions inaccessible via traditional synthetic routes. Here we use in situ synchrotron X-ray diffraction and pair distribution function (PDF) measurements to investigate how the dynamic structure of MOFs at the edge of stability influences their transformation into different metastable polymorphs. Our study reveals that the local structural features of metal-oxo MOF nodes at elevated temperatures are linked to the resulting nanoparticle structures formed under mild conditions. Focusing on the titanium-based MOF MIL-125, we demonstrate that manipulating the chemical environment to facilitate transformation of the Ti8 node geometry promotes formation of metastable, nanometer-scale TiO2 brookite rather than the more common anatase and rutile TiO2 polymorphs typically produced through MOF pyrolysis at high temperature. These findings highlight the potential to harness the MOF topology and chemical environment to design and control node distortions and enable access to exotic metastable nanoparticle states.

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

Enhancing the Multifunctional Photocatalytic Activity of Sustainable Magnetic Nanoparticles

The development of efficient photocatalytic materials has intensified in response to increasing emphasis on sustainable energy conversion and environmental restoration. However, the excessive use and indiscriminate release of heavy metals from photocatalytic nanoparticles pose potential environmental risks. This study provides insights into optimizing visible-light-active photocatalysts to enhance their photocatalytic properties and stability. Specifically, cobalt doping and controlled pH modulation are employed on the modified Fe 3 O 4 , forming two distinct samples: Co@Fe 3 O 4 -B (base-treated) and Co@Fe 3 O 4 -A (acid-treated) nanoparticles. Microscopic characterization reveals that Co@Fe 3 O 4 -A undergoes a phase transition to hematite, whereas Co@Fe 3 O 4 -B retains its mixed-phase configuration. Spectroscopic analyses confirm that the cobalt dopants decorate the outskirts of each nanoparticle, forming a core–shell structure. However, Co@Fe 3 O 4 -B exhibit Co 2+ states with a high oxygen vacancy content, whereas Co@Fe 3 O 4 -A contain mixed Co 2+/3+ states. The high density of defect states in the Co@Fe 3 O 4 -B results in superior photocatalytic efficiency, achieving near-complete oxidation of furfuraldehyde (97% conversion) and 5-hydroxymethylfurfural (94% conversion), as well as effective degradation of toluene (78% conversion). This study demonstrates that the combined approach of doping and pH treatment is promising for the surface-defect engineering of photocatalysts, enhancing their multifunctional performance and reusability for sustainable energy conversion.

Fe3 O4 nanoparticles↗
DOE OSTI2025

Innovative use of CaO in combination with amino acid salt to convert CO 2 as CaCO 3 nanoparticles under mild pH and low temperature

The increasing demand for sustainable CO 2 management has driven the development of innovative methods that can convert point source CO 2 into value-added products. In this study, CaO in combination with amino acid salt was used to convert CO 2 into CaCO 3 nanoparticles. Different from the conventional method where CO 2 diffusion presents a major challenge in reacting with CaO to form CaCO 3 , amino acid salt solvent was applied to absorb CO 2 first and then rapidly reacted with CaO to form CaCO 3 nanoparticles (∼50 nm) at a low temperature (e.g., 60 °C). Our experiments showed that at a glycine (Gly)/NaOH ratio of 2:1 or 3:1, the solution pH values during the CO 2 absorption and conversion were about 8–9 at 60 °C, while at a ratio of 1:1, the solution pH values were about 9–11; without Gly, the solution pH values were about 12. Gly-optimized solvent substantially reduced corrosion risk to reactors. In addition, the use of amino acid (i.e., Gly) led to much smaller CaCO 3 particles, distinctly different chemical phases, and fundamentally different chemical reactions. Moreover, in the presence of Gly, the solution pH was completely reversed and the solution was regenerated for cyclic use when CaO was added. The solvent was recyclable and reusable, highlighting the cost-effectiveness and sustainability of this approach. The Gly-modulated CaCO 3 nanoparticles may have significant potential for industrial applications in the biomedicine, construction, plastics, and rubber industries.

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

Luminescent Zn 2 GeO 4 :Mn 2+ Nanoparticles with High Quantum Yield for Salivary Protein Detection

Zinc germanate doped with Mn 2+ (Zn 2 GeO 4 :Mn 2+ ) is known to be a green luminescence phosphor with many applications in biosensing and bioimaging. This study presents a simple method for creating small size Zn 2 GeO 4 :Mn 2+ nanoparticles using a combination of the coprecipitation–molten salt synthesis method. These nanoparticles exhibit bright green luminescence under UV excitation. After surface functionalization, these nanoparticles were then used to develop a fluorescence resonance energy transfer (FRET)-based immunoassay. This immunoassay shows a detection range of 5–20 ng/mL of C-reactive protein (CRP), which suggests its potential for simple solution CRP detection and broader applications in protein biosensing.

biosensing↗