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Synthesis of UO 2 nanoparticles via coulometric titration: influence of electrolytes and ligands on synthesized particle properties

Here, this study investigates the controlled synthesis of uranium oxide nanoparticles (UO 2 NPs) via coulometric titration under ambient conditions, focusing on the impact of electrolyte anions, salt concentrations, and strongly complexing ligands on particle formation and properties. Using dilute solutions of mineral acids (HNO 3 , HCl, and HClO 4 ), we demonstrate that the choice of electrolyte anion affects particle size, polydispersity, and surface charge. Particle characterization using dynamic light scattering and transmission electron microscopy shows that particles synthesized in perchlorate are largest and show a high degree of polydispersity. In comparison, particles synthesized in chloride are smaller and more uniform in size. Synthesis in nitrate yields a wide variety of particle sizes, with the major fraction (>65 %) having a smaller size than that obtained in the other two electrolytes. The presence of more strongly coordinating ligands such as sulfate and acetate modulate hydrolysis and condensation reactions, with sulfate suppressing nanoparticle formation across a wide concentration range ([SO 4 2- ] > 5 mM) and acetate enabling stable colloidal suspensions at [HOAc] ≤ 0.1 M. Synthesis in concentrated electrolytes (2 M NaNO 3 , NaCl, or NaClO 4 ) accelerates reaction kinetics but introduces challenges, as particles showed increased polydispersity and aggregation, and were more prone to oxidation. Electrolyte effects on actinide oxide nanoparticle formation are discussed and a short comparison to established nanoparticle syntheses is drawn. This work underscores the importance of tailoring synthesis parameters to achieve desired nanoparticle properties, providing valuable insights for optimizing UO 2 NP production for various applications.

Actinide hydrolysis

Structural Templation of MOF-Derived Zirconia Nanoparticles

Templated synthesis is an important avenue for the development and synthesis of porous materials, as it provides a high level of control over the resulting structure. However, this control is difficult to achieve at the atomic level for poorly crystalline or noncrystalline materials, such as metal–organic framework (MOF)-derived carbons. We report the carbonization of three zirconium-based MOFs with different framework and inorganic building unit structures to form zirconia nanoparticles in a carbon matrix. Using a combination of X-ray diffraction, X-ray total scattering, and transmission electron microscopy, we found that the extended Zr-oxo chains of MIL-140C-bpy facilitate the formation of larger and more ordered zirconia nanoparticles. In contrast, the discrete Zr 6 -oxo clusters of UiO-67-bpy and Zr-ABTC result in smaller and differently structured nanoparticles.

metal-organic framework

Comparison of the Arrhenius parameters between conventional hydrothermal and microwave-assisted synthesis methods for tin oxide nanoparticles

Microwave (MW) irradiation has emerged as a powerful tool for accelerating materials synthesis, yet the origins of its specific influence on reaction kinetics remain elusive. While multiple studies have attributed the observed enhancements in reaction rates under MW heating to reduced activation energies, other accounts have suggested modifications to the Arrhenius pre-exponential factor as the predominant cause. Distinguishing between these parameters in modern applications of MW processing in nanomaterials requires experimental approaches capable of resolving the dynamic and nuanced structural kinetics that govern MW-assisted chemistry. Here, we combine in-situ synchrotron X-ray total scattering with pair distribution function (PDF) analysis to track the structural evolution of SnO 2 nanoparticles synthesized via MW-assisted and conventional hydrothermal conditions. Avrami modeling and Arrhenius analysis suggest that although MW irradiation yields a higher apparent activation energy, the enhanced crystallization is better explained by a pre-exponential factor several orders of magnitude larger than that of conventional heating. These findings suggest that the MW field induces a higher frequency of successful molecular rearrangements rather than lowering the intrinsic activation barrier. The results contribute further insights clarifying the role of the applied MW field for materials design where MW-specific effects can be deliberately harnessed. Furthermore, this work presents a framework promoting the utility of in-situ PDF characterization coupled with kinetic analysis for developing more sophisticated descriptions of nanoscale transformations for MW-driven reaction kinetics.

36 MATERIALS SCIENCE

Ultrafast Photoflash Synthesis of High-Entropy Oxide Nanoparticles

High-entropy metal oxides (HEOs) have recently received growing attention for broad energy conversion and storage applications due to their tunable properties. HEOs typically involve the combination of multiple metal cations in a single oxide lattice, thus bringing distinctive structures, controllable elemental composition, and tunable functional properties. Many synthesis methods for HEOs have been reported, such as solid-state reactions and carbon thermal shock methods. These methods frequently are energy-intensive or require relatively expensive heating equipment. In this work, we report an ultrafast photoflash synthesis method for HEO nanoparticles on diverse substrates. The energy input is provided by a commercial Xe photoflash unit, which triggers exothermic reactions to convert metal salt precursors to HEO nanoparticles within tens of milliseconds. The formation of HEO nanoparticles is attributed to the ultrafast heating (∼106 K/s) and cooling (∼105 K/s) rates of the photoflash and overall high temperature (>1000 K) during the ultrafast synthesis process. When the synthesized CoNiFeCrMn oxide (HEO) is tested as an oxygen evolution reaction electrocatalyst, it shows similar activity to similar materials prepared by other methods. We believe this photoflash synthesis provides a simple method for many others to synthesize diverse HEOs and explore their properties and potential applications.

exothermic reaction synthesis

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

Surface Nanostructure Control and Thermodynamic Stability Analysis of Femtosecond Laser-Ablated CuCoMn 1.75 NiFe 0.25 Nanoparticles

Surface nanostructure control is the key to functionalizing nanomaterials. This paper presents a characterization with thermodynamic stability analysis of CuCoMn 1.75 NiFe 0.25 high-entropy alloy (HEA) nanoparticles synthesized by femtosecond laser ablation in ethanol and liquid nitrogen (LN2). Using multimodal electron microscopy and spectroscopy, we examine phase, particle size, defect structure, chemical distribution, and surface composition and relate them to HEA stability. Elemental distributions are uniform in both media, but LN2 produces smaller particles with a narrower size distribution and mainly single- or few-domain interiors, whereas ethanol yields larger particles built from 2–4 nm crystallites with domain aggregation. Edge defects appear in both but energy-dispersive X-ray spectroscopy (EDS) is broadly uniform with local fluctuations in ethanol. X-ray photoelectron spectroscopy (XPS), supported by an attenuation model, indicates an ∼1 nm oxide overlayer that suppresses Mn 2p intensity; correcting for it returns Mn toward the bulk value. UV–NIR and photoluminescent spectra independently support a thin oxide shell. Composition-based thermodynamic descriptors place LN2 closer to bulk mixing parameters, while ethanol raises ΔH_mix and lowers Ω. Cooling simulations are consistent (LN2 ∼ 0.1 μs quench, ethanol ∼1 μs). In conclusion, these results connect solvent-controlled kinetics and thermodynamics to crystalline state and surface chemistry, informing surface control of HEA nanoparticles.

Femtosecond Laser Ablation

Experimental Investigation of Uranium and Iron Condensation from High-Temperature Plasma Conditions

We used a plasma flow reactor (PFR) to generate synthetic fallout nanoparticles from vapor-phase condensation of two different input concentrations of uranium and iron analytes (U/Fe = 1:1 and 1:2). Synthetic fallout from complex chemical matrices (e.g., mixtures of U and Fe) has not been generated in this setup before and allows for the observation of relative condensation and fractionation of nuclear debris. Experiments were conducted under two different temperature histories with variations in particle flow patterns along the PFR. Transmission electron microscopy (TEM) observation and analysis of the nanoparticles revealed variations in speciation of uranium oxides (UO 2 and α-UO 3 ) depending on the competition between flow mixing and oxygen sequestration by iron. A ternary metal oxide, UFeO 4 , was observed in addition to iron oxides (e.g., FeO and Fe 3 O 4 ), which suggests that fallout models should account for chemical speciation of ternary metal oxides (i.e., UFeO 4 ) and their relative condensation behaviors in addition to those of singular metal oxides (e.g., FeO and UO 2 ). X-ray Energy Dispersive Spectroscopy (EDS) elemental maps showed that some particles had Fe-rich cores surrounded by U-rich regions. This suggests that either condensed U oxides coagulate onto molten Fe oxides or that the increase in iron analyte concentration might drive the system toward a higher degree of supersaturation, leading to earlier formation of iron oxide particles and providing an energetically favored pathway for nucleation of uranium oxides around iron oxide particles.

and nuclear chemistry

Uncertainty-Aware Machine Learning for Small-Angle X-ray Scattering Analysis in Autonomous Experimentation

Small-angle X-ray scattering (SAXS) is a powerful high-throughput characterization tool for probing nanoscale structure in native sample environments, providing real-time morphological information such as nanoparticle size and shape during synthesis. However, automated SAXS data analysis for extracting meaningful structural parameters is non-trivial and remains a bottleneck in closed-loop experimentation towards autonomous materials discovery, which demands fast, reliable, and uncertainty-aware data analysis. Here, we develop a machine-learning approach for automated SAXS analysis tailored to closed-loop nanoparticle synthesis. A Random Forest (RF) regression model is trained on 100,000 synthetic SAXS curves generated from polydisperse spherical nanoparticles with realistic background contributions. Using normalized one-dimensional SAXS intensity profiles as input, the RF model directly predicts nanoparticle radius, size polydispersity, and background parameters, while the ensemble standard deviation across trees provides built-in uncertainty quantification (UQ). On synthetic data, we show that combining fit-quality metrics (R 2 , MAE) with thresholds on prediction uncertainty reliably identifies accurate parameter estimates without access to ground truth. We then apply the trained model to 365 experimental SAXS profiles of citrate-reduced gold nanoparticles synthesized using an automated droplet-flow microreactor with in situ SAXS at a synchrotron beamline, classifying the results into high- and low-confidence subsets based on UQ metrics. Finally, we integrate RF-based SAXS analysis into a simulated closed-loop optimization campaign using Gaussian process Bayesian optimization to minimize nanoparticle polydispersity, benchmarking against conventional automated Levenberg–Marquardt fitting. The RF-guided campaign exhibits substantially faster convergence and lower relative opportunity cost (∼0.07 vs ∼0.3), demonstrating that uncertainty-aware machine-learning SAXS analysis significantly enhances the efficiency and robustness of autonomous nanomaterials synthesis workflows.

Bayesian optimization

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

End-to-End Automated Segmentation Framework for Four-Dimensional Scanning Transmission Electron Microscopy Data

Four-dimensional scanning transmission electron microscopy (4D-STEM) is powerful for rapidly characterizing arrays of nanoparticles produced via high-throughput synthesis. However, such 4D-STEM datasets typically contain thousands of nanoparticles, each characterized by thousands of diffraction patterns spatially distributed across the nanoparticle, necessitating efficient and comprehensive analysis. We propose an end-to-end segmentation framework to automatically segment each nanoparticle into regions with distinct composition/orientation of crystal grains, using only the 4D-STEM data. Bragg disk information is extracted in a physics-informed manner from the diffraction patterns at each spatial location and combined with the real space coordinates to form feature vectors. These feature vectors are then used as inputs to a Gaussian mixture model (GMM) to segment the nanoparticle into distinct regions. We also develop two visualization tools based on the GMM outputs to infer the interface transition and the degree of superposition. Our framework comprehensively integrates machine learning tools and physics knowledge, and provides a basis for substantially compressing enormous 4D-STEM datasets, e.g., by replacing the full 4D-STEM dataset for each nanoparticle with only a single set of Bragg disk features for each distinct crystal grain identified in the nanoparticle. In this article, we demonstrate the power of our framework by presenting results for real, complex datasets.

47 OTHER INSTRUMENTATION

De Nive Quinquangula: Pentagonal Snowflake Metal Nanocrystals as an Example of Emergence Phenomenon in Nanotechnology Complex Systems

The formation of snowflakes (SFL) is one of the most captivating phenomena in nature. The fabrication of multimetallic gold (Au) nanoparticles containing copper (Cu) and iron (Fe) is reported, which adopt snowflake-like morphology after nanoparticle aggregation. The synthesis of these snowflake-like Au microcrystals occurs mainly by kinetic control. In this process, a surfactant-assisted salt reduction method is employed on a heated substrate. Here, the metal salts react within seconds to form nanoparticles. This process results in a hierarchical structure with pseudo-pentagonal symmetry and chiroptical activity. We discuss how large superstructures emerge from nanoparticle aggregation, resembling natural snowflakes. However, unlike ice snowflakes, which exhibit hexagonal symmetry, the Au snowflakes display pentagonal symmetry. It is proposed that the formation of these snowflake-like microcrystals is the result of the complexity involved in the crystal growth process and represents an example of the phenomenon of emergence, which has become very significant in several fields of modern science, including physics, biology, chemistry, economics, philosophy, and poetry. The term emergent is used to evoke the collective behavior of a large number of microscopic constituents that is qualitatively different than the behaviors of the individual constituents.

36 MATERIALS SCIENCE

Molten Salt Synthesis of Increased (100)-Facet and Polycrystalline Nickel Oxide Nanoparticles for the Oxygen Evolution Reaction: Impact of Facet and Crystallinity on Electrocatalysis

Nickel oxide nanocubes with increased (100) surface facet presence (NiO(100)) were synthesized through a molten salt synthesis procedure to probe their oxygen evolution reaction (OER) activity in order to investigate the relationship between the surface facet and OER performance. While altering the synthesis parameters to decrease NiO(100) particle sizes and agglomeration, a polycrystalline NiO nanoparticle system formed from using Li2O as a Lux-Flood base (labelled Li2O-MSS NiO, where MSS stands for molten salt synthesis). This novel synthesis was further elaborated and the obtained materials were also tested for OER activity. After thorough structural characterization to determine crystallinity, lattice spacings, and elemental distribution, their OER activity was compared versus high surface area NiO(111) nanosheets in a three-electrode rotating disk electrode (RDE) system. The activity trend of (111) > Li2O-MSS > (100) was observed. This decrease in activity of the nanocube and polycrystalline samples was explained by differences between theoretical and experimental conditions, differences in ink rheology and resulting catalyst layer properties, and significant agglomeration seen in the imaging of the sample. Methods for improving the OER activity of these samples are discussed in the conclusion of this study.

08 HYDROGEN

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

Nanoscale wetting controls reactive Pd ensembles in synthesis of dilute PdAu alloy catalysts

The performance of bimetallic dilute alloy catalysts is largely determined by the size of minority metal ensembles on the nanoparticle surface. By analyzing the synthesis of catalysts comprising Pd 8 Au 92 nanoparticles supported on silica using surface-sensitive techniques, we report that whether Pd overgrowth occurs before or after Au nanoparticle deposition onto the support controls the surface Pd ensemble size and abundance. These differences in Pd ensembles influence catalytic reactivity in H 2 –D 2 isotope exchange and benzaldehyde hydrogenation, which, in correlation with theoretical calculations, is used to elucidate the active site(s) in each reaction. To clarify how the synthetic sequence controls the formation of Pd ensembles, we combine numerical wetting calculations and molecular dynamics simulations (with a machine-learned force field) to visualize Pd deposition and migration on the nanoparticle surface, respectively. Our results suggest that the nanoparticle–support interface restricts nanoparticle accessibility to Pd deposition, which consequently controls the Pd ensemble size, illustrating the critical role of nanoscale wetting phenomena during bimetallic catalyst preparation.

36 MATERIALS SCIENCE

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

Low-temperature access to active iron and iron/nickel nitrides as potential electrocatalysts for the oxygen evolution reaction

Low-temperature, scalable routes to transition metal nitride (TMN) nanoparticles are desirable for a wide range of applications, yet their synthesis typically requires high temperatures (>350 °C) and reactive gas environments (e.g., NH 3 or H 2 /N 2 ). Here, we report a colloidal synthesis of mono- and bimetallic TMN nanoparticles using preformed metal carbonyl clusters as precursors and urea or diethylenetriamine (DETA) as nitrogen sources. This strategy enables access to size-controlled, phase-pure ε-Fe 3 N x and Fe y Ni 3−y N nanoparticles at temperatures below 300 °C, without the need for flowing reactive gas atmospheres. By systematically varying nitrogen precursor, reaction temperature, and cluster identity, we achieve tunable nitrogen stoichiometry (x) and phase selectivity between N-rich and N-poor TMNs. Structural and magnetic characterization confirms clean decomposition of the precursors and phase formation consistent with controlled nitridation at the nanoscale. Preliminary electrochemical measurements in alkaline media demonstrate that these materials exhibit oxygen evolution reaction (OER) overpotentials comparable to RuO 2 , highlighting their viability for future electrocatalytic applications.

77 NANOSCIENCE AND NANOTECHNOLOGY