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At least 1,063 records · Page 59

Optical constants measurements of liquids for modeling aerosolized threats

Spectroscopic identification of aerosolized chemical threats is challenging due to the complex nature of the photon/particle interaction, as well as the diversity of possible particle sizes, morphologies, and compositions. Constructing a database of laboratory - measured transmittance spectra that covers each permutation is not practical. However, calculation of the spectra using the measured optical constants as a function of wavenumber, n(?) and k(?), for each of the liquids and/or solids composing the aerosol particles provides a viable alternative. These synthetic spectra (vis-à-vis laboratory-measured spectra) can be used to identify chemicals of interest and subtract out background interferents in field measurements. Using a well-established multiple pathlength approach, we measure the optical constants n/k for liquids that may be found as chemical species of interest or common background interferents aerosolized in plumes. These measurements are also used to generate several test case aerosol synthetic spectra.

Lockwood, Schuyler↗

Absorber Column CFD model validation against PNNL’s device-scale absorber column on the LCFS unit

Absorber column has been widely used for CO 2 capture in the coal-fired power plants. High-fidelity CFD models play an important role in absorber column design and solvents optimization, which help enhance the CO 2 capture efficiency and reduce the operation cost. This report provides a comprehensive description of the development of CFD absorber models at two different levels, the design and implementation of PNNL’s device-scale absorber column experiment, and the methodology to combine the CFD results, experiment data, and Aspen model for a better understanding of the interface area in packed column. A composite model is firstly proposed in the Discrete Element Method (DEM) packing process, which can model the complex geometry of various packing elements. This generates a realistic packing pattern and accurate packing porosity ε and specific area a p compared to the actual values for absorber column used in LCFS. Two level of CFD absorber models were developed, namely the full-size column model (FCM) to simulate the entire packed column with a focus on the wall/entrance effects, and the representative column model (RCM) to simulate a section of column with a focus on the sensitivity study of interface area. A Design of Experiment (DoE) plan was developed to guide the collection of 100 run CFD data and 12 experiment runs. The 100 CFD runs were carried out in the RCM with Pro-Pak packing and cover a wide operation range and solvent properties. Impact of influential factors on the interface area in packed column were investigated in details. The CFD interface area was then combined with the experimental data and Aspen model to infer some information of the effective contact angle in the column. The accuracy and uncertainties in the interface area and contact angle can be quantified.

01 COAL, LIGNITE, AND PEAT↗

Measuring the Interfacial Chemistry of Micro- and Nano-Plastics Using Matrix Assisted Laser Desorption Ionization

Micro- and nano-plastics (MNPs) pose a significant hazard to both environmental and human health due to their complex interfacial interactions with their surroundings, however there is a lack of techniques available to study the composition of MNPs at their surface. To fill this gap, representative MNPs were coated with matrix that enabled detection via matrix-assisted laser desorption ionization mass spectrometry (MALDI), a technique that has been shown to be surface specific but had not been applied to MNPs previously. Three different coating techniques were tested; evaporation and condensation, drop-casting, and mixed nebulization. Mixed nebulization provided the best balance of results, which was a strong MALDI signal in combination with even coating on the MNP surface from MNPs ≥20 µm. This work provides a new technique for the measurement of MNP surface composition that will help advance the field and enable more thorough studies of the chemical transformations that MNPs undergo in the environment.

36 MATERIALS SCIENCE↗

Prediction of Silicon Content in a Blast Furnace via Machine Learning: A Comprehensive Processing and Modeling Pipeline

Silicon content plays an important role in determining the operational efficiency of blast furnaces (BFs) and their downstream processes in integrated steelmaking; however, existing sampling methods and first-principles models are somewhat limited in their capability and flexibility. Current data-based prediction models primarily rely on a limited set of manually selected furnace parameters. Additionally, different BFs present a diverse set of operating parameters and state variables that are known to directly influence the hot metal’s silicon content, such as fuel injection, blast temperature, and raw material charge composition, among other process variables that have their own impacts. The expansiveness of the parameter set adds complexity to parameter selection and processing. This highlights the need for a comprehensive methodology to integrate and select from all relevant parameters for accurate silicon content prediction. Providing accurate silicon content predictions would enable operators to adjust furnace conditions dynamically, improving safety and reducing economic risk. To address these issues, a two-stage approach is proposed. First, a generalized data processing scheme is proposed to accommodate diverse furnace parameters. Second, a robust modeling pipeline is used to establish a machine learning (ML) model capable of predicting hot metal silicon content with reasonable accuracy. The method employed herein predicted the average Si content of the upcoming furnace cast with an accuracy of 91% among 200 target predictions for a specific furnace provisioned by the XGBoost model. This prediction is achieved using only the past shift’s operating conditions, which should be available in real time. This performance provides a strong baseline for the modeling approach with potential for further improvement through provision of real-time features.

Chemistry↗

Homopiperazine-based catalysts for neutralization of organophosphorus-based compounds

Novel compositions of matter based on homopiperazine precursor materials and forming a homopiperazine-based ligand are disclosed, along with suitable techniques and materials for the synthesis and utilization thereof. In particular various synthetic schemes and techniques for applying the disclosed compositions of matter as a decontaminating agent. The decontaminating agents include homopiperazine-based ligand-metal complexes that are particularly effective at neutralizing toxicity of nerve agents, pesticides, and other toxic organophosphorus-based compounds. In preferred approaches, the homopiperazine-based ligand-metal complexes act as catalysts to facilitate substitution of a leaving group of the organophosphorus-based compound with a functional group that does not permit the organophosphorus-based compound to inactivate acetylcholinesterase upon introduction of the organophosphorus-based compound to a living organism such as insects and mammals. Advantageously, the catalytic homopiperazine-based ligand-metal complexes are formed using inexpensive, readily-available precursor materials, and may be utilized to neutralize toxins without relying on damaging caustic reactants or environmentally unfriendly organic solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Homopiperazine-based catalysts for neutralization of organophosphorus-based compounds

Novel compositions of matter based on homopiperazine precursor materials and forming a homopiperazine-based ligand are disclosed, along with suitable techniques and materials for the synthesis and utilization thereof. In particular various synthetic schemes and techniques for applying the disclosed compositions of matter as a decontaminating agent. The decontaminating agents include homopiperazine-based ligand-metal complexes that are particularly effective at neutralizing toxicity of nerve agents, pesticides, and other toxic organophosphorus-based compounds. In preferred approaches, the homopiperazine-based ligand-metal complexes act as catalysts to facilitate substitution of a leaving group of the organophosphorus-based compound with a functional group that does not permit the organophosphorus-based compound to inactivate acetylcholinesterase upon introduction of the organophosphorus-based compound to a living organism such as insects and mammals. Advantageously, the catalytic homopiperazine-based ligand-metal complexes are formed using inexpensive, readily-available precursor materials, and may be utilized to neutralize toxins without relying on damaging caustic reactants or environmentally unfriendly organic solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Measuring accurate optical constants of uranium minerals for use in optical modeling of infrared spectra

Knowledge of the bulk optical constants n and k of solids or liquids allows researchers to accurately predict the absorption, reflection, and scattering properties of materials for different physical forms. Indeed, chemically complex materials such as minerals can have an almost limitless variety of morphologies, particle sizes, shapes, and compositions, but the optical properties of such species can be predicted if the optical constants are known. For species such as minerals, however, there can be additional challenges due to e.g. hydration or dehydration during the course of the optical constants measurement. Here, we describe the protocols to obtain the bulk optical constants n and k of uranium-bearing minerals and ores such as uraninite or autunite. If quality n and k data are at hand, the (infrared) reflectance spectra can be predicted for different particle sizes and morphologies and the modeling results for various scenarios can be derived.

infrared (IR) spectroscopy, optical constants, ura↗

Exploring gasoline oxidation chemistry in jet stirred reactors

Recent decades have seen increasingly restrictive regulations applied to gasoline engines. Gasoline combustion chemistry must be investigated to achieve a better understanding and control of internal combustion engine efficiency and emissions. In this work, several gasoline fuels, namely the FACE (Fuel for Advanced Combustion Engines) gasolines, were selected as targets for oxidation study in jet-stirred reactors (JSR). The study is facilitated by formulating various gasoline surrogate mixtures with known hydrocarbon compositions to represent the real gasolines. Surrogates included binary mixtures of n-heptane and iso-octane, as well as more complex multi-component mixtures. Here, the oxidation characteristics of FACE gasolines and their surrogates were experimentally examined in JSR-1 and numerically simulated under the following conditions: pressure 1 bar, temperature 500–1050 K, residence time 1.0 and 2.0 s, and two equivalence ratios (Φ= 0.5 and 1.0). In the high temperature region, all real fuels and surrogates showed similar oxidation behavior, but in the low temperature region, a fuel’s octane number and composition had a significant effect on its JSR oxidation characteristics. Low octane number fuels displayed more low temperature reactivity, while fuels with similar octane number but a larger number of n-alkane components were more reactive. A gasoline surrogate kinetic model was examined with FACE gasoline experiments either measured in JSR-2, or taken from previous work under the following conditions: pressure 10 bar, temperature 530–1200 K, residence time 0.7 s, and three equivalence ratios (Φ = 0.5, 1.0 and 2.0). Comparison between FACE gasoline experimental results with surrogate model predictions showed good agreement, demonstrating considerable potential for surrogate fuel kinetic modeling in engine simulations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Localized High Concentration Electrolytes for High Voltage Lithium-Metal Batteries: Correlation between the Electrolyte Composition and Its Reductive/Oxidative Stability

We demonstrate a first-principles screening methodology as an effective tool to explore electrolyte formulations for the new generation of high energy density rechargeable batteries. We study the liquid structure and electronic properties in dilute electrolytes, high concentration electrolytes (HCE), and localized high concentration electrolytes (LHCE), with focus on electrolyte formulations based on lithium bis(fluorosulfonyl)imide (LiFSI), dimethyl carbonate (DMC), and bis(2,2,2-trifluoroethyl) ether (BTFE) as a diluent. We describe the solvation complexes in the dilute electrolyte and explore structural changes triggered by the increase in lithium salt concentration for HCEs and the diluent effects in LHCEs. In HCE formulations, there is a 4-fold coordination environment of lithium-ions as in the dilute electrolyte, but the number of lithium-ion interactions with O atoms from FSI- anions dominates. In these solutions, the ability of the FSI- anions to interact with multiple lithium-ions allows complex 3D network formation and influences the reductive/oxidative behavior of the electrolyte. Interestingly, in LHCEs, the BTFE diluent molecules do not change the 3D solution structure when diluting the HCE formulation from 5.49 to 3.83 M. However, there is a composition threshold where the structural and electronic behavior may change. We show that diluting the HCE electrolyte with BTFE down to 1.77 M breaks the three-dimensional solution structure into an island-like solvation complex. We relate these structural changes to the electronic properties of the electrolytes finding a causal relationship between the reductive/oxidative behavior and the lithium-oxygen interaction mechanisms in the solvated complexes. The coordination with lithium-ions lowers the electrolyte LUMO and HOMO levels: the higher is the number of interactions with lithium-ions, the more likely the solvent molecule, FSI- anion, or diluent molecule is to be reduced and the less likely it is to become oxidized. The evolution of the solvated ion structure in HCE and LHCE suggests a close connection to a corresponding change in the lithium-ion transport mechanisms for these electrolytes.

anions, molecules, oxygen, solvents, electrolytes↗

Coprecipitation of Fe/Cr Hydroxides with Organics: Roles of Organic Properties in Composition and Stability of the Coprecipitates

Iron hydroxides are important scavengers for dissolved chromium (Cr) via coprecipitation processes; however, the influences of organic matter (OM) on Cr sequestration in Fe/ Cr-OM ternary systems and the stability of the coprecipitates are not well understood. Here, Fe/Cr-OM coprecipitation was conducted at pH 3, and Cr hydroxide was undersaturated. Acetic acid (HAc), poly(acrylic acid) (PAA), and Suwannee River natural organic matter (SRNOM) were selected as model OMs, which showed different complexation capabilities with Fe/Cr ions and Fe/Cr hydroxide particles. HAc had no significant effect on the coprecipitation, as the monodentate carboxyl ligand in HAc did not favor complexation with dissolved Fe/Cr ions or Fe/Cr hydroxide nanoparticles. Contrarily, PAA and SRNOM with polydentate carboxyl ligand had strong complexation with Fe/Cr ions and Fe/Cr hydroxide nanoparticles, leading to significant amounts of PAA/SRNOM sequestered in the coprecipitates, which caused the structural disorder and fast aggregation of the coprecipitates. In comparison with that of PAA, preferential complexation of Cr ions with SRNOM resulted in higher Cr/Fe ratios in the coprecipitates. This study advances the fundamental understanding of Fe/Cr-OM coprecipitation and mechanisms controlling the composition and stability of the coprecipitates, which is essential for successful Cr remediation and removal in both natural and engineered settings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optical tags comprising rare earth metal-organic frameworks

Optical tags provide a way to identify assets quickly and unambiguously, an application relevant to anti-counterfeiting and protection of valuable resources or information. The present invention is directed to a tag fluorophore that encodes multilayer complexity in a family of heterometallic rare-earth metal-organic frameworks (RE-MOFs) based on highly connected polynuclear clusters and carboxylic acid-based linkers. Both overt (visible) and covert (near infrared, NIR) properties with concomitant multi-emissive spectra and tunable luminescence lifetimes impart both intricacy and security. Tag authentication can be validated with a variety of orthogonal detection methodologies. The relationships between structure, composition, and optical properties of the family of RE-MOFs can be used to create a large library of rationally designed, highly complex, difficult to counterfeit optical tags.

Sava Gallis, Dorina F.↗

Elucidating the role of Cr migration in Ni-Cr exposed to molten FLiNaK via multiscale characterization

Structural materials used in nuclear reactor environments are subjected to coupled extremes such as high temperature, irradiation, and corrosion which act in concert to degrade their functional performance. Connecting alloy microstructure such as grain boundaries, and accumulating point defects with corrosion attack and pore morphology is critical to understanding underlying mechanisms. We uncover the compositional variations and morphology at multiple length scales in corrosion-damaged Ni-Cr alloy after exposure to oxidants in molten fluoride salts. A complex network of dense corrosion pores is detected by surface-level SEM observations. The corrosion pores take on a 1-dimensional morphology and are enriched with Ni and depleted of Cr 1–5 µm from the pore surface. STEM-EDS and 4D-STEM strain maps acquired simultaneously highlight the local variations in composition and structure of a ≤ 200 nm Cr-rich layer identified from a cross-section taken at the bottom of an isolated corrosion pore between the Ni-Cr alloy matrix and the embedded salt. However, the absence of an observed interface between the Ni-Cr alloy matrix and the FCC-structured Cr-rich layer suggests that Cr plating from the salt did not transpire. These findings support a proposed Cr lattice diffusion mechanism rather than Cr-precipitation from the salt to accommodate temperature transient conditions during sample cooling. Through the development of a 1D phase field model, these results are rationalized by formation energies for the Ni- and Cr-oxidation into the molten salt. This study reveals the locally altered microstructure caused by high temperature corrosion in non-steady-state molten salt nuclear reactor environments.

36 MATERIALS SCIENCE↗

Metaproteomics reveals insights into microbial structure, interactions, and dynamic regulation in defined communities as they respond to environmental disturbance

Abstract Background Microbe-microbe interactions between members of the plant rhizosphere are important but remain poorly understood. A more comprehensive understanding of the molecular mechanisms used by microbes to cooperate, compete, and persist has been challenging because of the complexity of natural ecosystems and the limited control over environmental factors. One strategy to address this challenge relies on studying complexity in a progressive manner, by first building a detailed understanding of relatively simple subsets of the community and then achieving high predictive power through combining different building blocks (e.g., hosts, community members) for different environments. Herein, we coupled this reductionist approach with high-resolution mass spectrometry-based metaproteomics to study molecular mechanisms driving community assembly, adaptation, and functionality for a defined community of ten taxonomically diverse bacterial members of Populus deltoides rhizosphere co-cultured either in a complex or defined medium. Results Metaproteomics showed this defined community assembled into distinct microbiomes based on growth media that eventually exhibit composition and functional stability over time. The community grown in two different media showed variation in composition, yet both were dominated by only a few microbial strains. Proteome-wide interrogation provided detailed insights into the functional behavior of each dominant member as they adjust to changing community compositions and environments. The emergence and persistence of select microbes in these communities were driven by specialization in strategies including motility, antibiotic production, altered metabolism, and dormancy. Protein-level interrogation identified post-translational modifications that provided additional insights into regulatory mechanisms influencing microbial adaptation in the changing environments. Conclusions This study provides high-resolution proteome-level insights into our understanding of microbe-microbe interactions and highlights specialized biological processes carried out by specific members of assembled microbiomes to compete and persist in changing environmental conditions. Emergent properties observed in these lower complexity communities can then be re-evaluated as more complex systems are studied and, when a particular property becomes less relevant, higher-order interactions can be identified.

59 BASIC BIOLOGICAL SCIENCES↗

Biogeochemistry of the Antrim Shale Natural Gas Reservoir

The Antrim Shale, located in the Michigan Basin, United States (U.S.), is a major U.S. shale play having produced over 2.5 Trillion Cubic Feet (Tcf) of unconventional shale natural gas as of 2010. The shallow nature of this formation sets it apart from other, more characterized unconventional shale gas plays. The depth of gas production of the Antrim ranges from approximately 150 to 600 m and it is typically vertically drilled, contrary to deeper, horizontally drilled shales. A thorough understanding of the biogeochemistry and microbiology of this complex system will be advantageous for improving well performance, produced water management, and potential biocidal treatment as microbial community composition can vary substantially even among closely spaced wells. In this study, we analyzed produced water collected from nine different wells in the Antrim Shale by investigating the geochemical and microbial community composition of the produced water to gain greater insight into the overall biogeochemistry of this unique shale system. The majority of the wells from this study had high total dissolved solids (TDS) primarily composed of chloride and sodium, averaging 86,804 mg/L with a maximum 116,223 mg/L; however, three of the wells sampled along the northern margin of the basin exhibited significantly lower TDS ranging from 4932 to 6496 mg/L. Overall, our microbial community analysis revealed relatively low abundance within our samples and high variability of the microbial community among the sampled wells. The majority of bacterial sequences were identified within Proteobacteria, Firmicutes, and Actinobacteria phyla and metagenomic sequencing revealed the low presence of Methanobacteriaceae within each sample. We also investigated potential microbial community drivers and found that TDS, sodium, chloride, iodide, bromide, ammonium, potassium, and strontium were significantly correlated with the observed microbial community. The varying geochemical conditions between wells demonstrate different subsurface environmental niches, potentially driving the heterogeneous microbial communities we observed from well to well. This analysis suggests an important relationship between both well location and geochemistry and the observed microbial community that can persist in the reservoir. Continued studies of the Antrim Shale will improve our understanding of the complex interdependencies of this ecosystem.

03 NATURAL GAS↗

Microstructure characteristics of LPBF&HIP fabricated graded composite transition joint between ferritic steel and austenitic stainless steel

Graded composite transition joints (GCTJs) offer a promising alternative to conventional dissimilar metal welds (DMWs) by enabling smooth compositional and microstructural transitions. However, GCTJs fabricated solely through additive manufacturing (AM) face challenges such as heat accumulation, complex parameter control, and elemental segregation. In this study, we propose a novel approach that relies on AM to design a spatially graded structure in one alloy and then employs hot isostatic pressing (HIP) as a diffusion bonding method to join it with a second alloy. Here, this method combines the flexibility of AM with the powder net-shaping advantage of HIP. Specifically, a series of closely packed austenitic stainless steel 304 conical structures were printed using laser powder bed fusion (LPBF) and then combined with ferritic steel P91 powder via HIP. By using electron backscatter diffraction (EBSD), electron probe microanalysis (EPMA), and transmission electron microscopy (TEM) techniques, the microstructure characteristics of the GCTJ of 304&P91, especially the interdiffusion zone (IDZ), have been systematically investigated. The microstructure at the interface transitions from austenite-ferrite (A+F) to austenite-martensite-ferrite (A+M+F), and finally to martensite-ferrite (M+F) due to diffusion. Additionally, the diffusion width between 304 and P91 increases with the volume fraction of P91. This unique design also ensures a gradual transition in both hardness and thermal expansion coefficient from 304 to P91, thereby enabling a smooth gradient in functional properties. Overall, this study proposes a novel approach for fabricating GCTJs and contributes to advancing design concepts in the field of dissimilar metal joining.

Additively manufacturing (AM)↗

Remaining Useful Strength (RUS) Prediction of SiCf-SiCm Composite Materials Using Deep Learning and Acoustic Emission

Prognosis techniques for prediction of remaining useful life (RUL) are of crucial importance to the management of complex systems for they can lead to appropriate maintenance interventions and improvements in reliability. While various data-driven methods have been introduced to predict the remaining useful life (RUL) of machinery systems or batteries, no research has been reported on the remaining useful strength (RUS) prediction of silicon carbide fiber reinforced silicon carbide matrix (SiCf-SiCm) materials with pivotal role in its potential usage as a structural material in nuclear reactors and turbine engines. Knowledge of its degradation process is of the utmost importance to the manufacturers. For this purpose, two approaches based on the machine-learning techniques of random-forest (RF) and convolutional neural network (CNN) are proposed to predict the RUS of SiCf-SiCm using only acoustic emission (AE) signals generated during the material’s stress applying process. Experimental results show that the CNN models achieved better predictive performance than the RF models but the latter with expert-engineered features achieves better prediction for AE signals in the early stage of degradation. Additionally, our results demonstrate that both models can correctly predict the SiCf-SiCm RUS as evaluated by our robust testing method from which the best average root mean square error (RMSE) and Pearson correlation coefficient of 3.55 ksi units and 0.85 were obtained.

36 MATERIALS SCIENCE↗

Detailed Method for the Purification of Rhamnogalacturonan-I (RG-I) in Arabidopsis thaliana

The plant cell wall is a dynamic and complex extracellular matrix that not only provides structural integrity and determines cell shape but also mediates intercellular communication. Among its major components, pectins play essential roles in cell adhesion, wall porosity, hydration, and flexibility. Rhamnogalacturonan-I (RG-I), a structurally diverse pectic polysaccharide, remains one of the least understood components of the plant cell wall. Its backbone is substituted with arabinan, galactan, and arabinogalactan side chains that vary in length, branching, and composition across tissues, species, and developmental stages. In addition, RG-I can undergo modifications such as backbone acetylation, further contributing to its structural complexity and functional diversity. To advance understanding of RG-I, we present a detailed method for isolating RG-I from the model plant Arabidopsis thaliana . Leveraging Arabidopsis as a model system provides major advantages owing to its well-characterized genome and powerful molecular toolkit, enabling deeper investigation into the roles of RG-I in plant development and responses to environmental stress. Our method consists of two major steps: an initial chemical extraction using oxalate, followed by endo-polygalacturonase (EPG) digestion to fragment the pectic domains. An advantage of this approach is that it produces a dry material that can be stored at room temperature without special handling and does not introduce chemicals that may interfere with downstream analyses. The purified RG-I can be used for detailed compositional and structural analyses, as well as for functional studies of enzymes involved in pectin biosynthesis, modification, and degradation. Although this protocol was developed for isolating RG-I from Arabidopsis rosette leaves, it is also applicable to other Arabidopsis organs and other plant species.

25 ENERGY STORAGE↗

Heterobinuclear Molecular Precursors Direct the Formation of Supported Subnanometer Cu–M Clusters with Tunable Catalytic Behavior

Subnanometer bimetallic clusters hold great promise for catalytic applications due to their unique electronic properties and high surface-to-volume ratios. However, precise control over their composition and size remains a major challenge, particularly for immiscible metal pairs. Here, we report a surface-anchored molecular approach for synthesizing ∼0.7–0.8 nm Cu–M (M = Ru, Mo, W, Fe) bimetallic clusters on mesoporous silica supports, using heterobinuclear N-heterocyclic carbene (NHC)-based complexes as precursors. The NHC ligand functionalized with an alkoxysilane anchor enables robust grafting to the silica interface. Controlled calcination and reduction lead to subnanometer clusters with tunable composition, dictated by the metal–metal bond stability in the precursor. In situ transmission electron microscopy reveals cluster growth proceeds via sintering of adjacent surface-bound units, while elevated temperatures above 300 °C triggering diffusion and phase separation. Catalytic testing in ethylene hydrogenation demonstrates composition-dependent activity and kinetics, with CuRu and CuW clusters exhibiting lower apparent activation energy barriers compared with monometallic Cu nanoparticles. This study establishes a generalizable strategy for the interfacial synthesis of alloyed clusters from molecular precursors and provides mechanistic insight into how precursor design governs nanostructure formation and catalytic behavior.

N-heterocyclic carbene↗