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DOE OSTI2022

Creating ground truth for nanocrystal morphology: a fully automated pipeline for unbiased transmission electron microscopy analysis

Control over colloidal nanocrystal morphology (size, size distribution, and shape) is important for tailoring the functionality of individual nanocrystals and their ensemble behavior. Despite this, traditional methods to quantify nanocrystal morphology are laborious. New developments in automated morphology classification will accelerate these analyses but the assessment of machine learning models is limited by human accuracy for ground truth, causing even unsupervised machine learning models to have inherent bias. Herein, we introduce synthetic image rendering to solve the ground truth problem of nanocrystal morphology classification. By simulating 2D images of nanocrystal shapes via a function of high-dimensional parameter space, we trained a convolutional neural network to link unique morphologies to their simulated parameters, defining nanocrystal morphology quantitatively rather than qualitatively. An automated pipeline then processes, quantitatively defines, and classifies nanocrystal morphology from experimental transmission electron microscopy (TEM) images. Using improved computer vision techniques, 42,650 nanocrystals were identified, assessed, and labeled with quantitative parameters, offering a 600-fold improvement in efficiency over best-practice manual measurements. Further, a classification algorithm was trained with a prediction accuracy of 99.5%, which can successfully analyze a range of concave, convex, and irregular nanocrystal shapes. The resulting pipeline was applied to differentiating two syntheses of nominally cuboidal CsPbBr 3 nanocrystals and uniquely classifying binary nickel sulfide nanocrystal phase based on morphology. This pipeline provides a simple, efficient, and unbiased method to quantify nanocrystal morphology and represents a practical route to construct large datasets with an absolute ground truth for training unbiased morphology-based machine learning algorithms.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2023

DNA-caged nanoparticles via electrostatic self-assembly

DNA-modified nanoparticles enable DNA sensing and therapeutics in nanomedicine and are also crucial for nanoparticle self-assembly with DNA-based materials. However, methods to conjugate DNA to nanoparticle surfaces are limited, inefficient, and lack control. Inspired by DNA tile nanotechnology, we demonstrate a new approach to nanoparticle modification based on electrostatic attraction between negatively charged DNA tiles and positively charged nanoparticles. This approach does not disrupt nanoparticle surfaces and leverages the programmability of DNA nanotechnology to control DNA presentation. We demonstrated this approach using a variety of nanoparticles, including polymeric micelles, polystyrene beads, gold nanoparticles, and superparamagnetic iron oxide nanoparticles with sizes ranging from 5–20 nm in diameter. DNA cage formation was confirmed through transmission electron microscopy (TEM), neutralization of zeta potential, and a series of fluorescence experiments. DNA cages present “handle” sequences that can be used for reversible target attachment or self-assembly. Handle functionality was verified in solution, at the solid–liquid interface, and inside fixed cells, corresponding to applications in biosensing, DNA microarrays, and erasable immunocytochemistry. Finally, these experiments demonstrate the versatility of the electrostatic DNA caging approach and provide a new pathway to nanoparticle modification with DNA that will empower further applications of these materials in medicine and materials science.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Optimizing dicyandiamide pretreatment conditions for enhanced structure and electronic properties of polymeric graphitic carbon nitride

Graphitic carbon nitride, a polymeric semiconductor, possesses a distinctive electronic band structure and exceptional chemical stability, making it a highly promising material for various catalytic applications such as electrocatalysis, photocatalysis, and photo-electrocatalysis. However, its practical applications remain limited due to its low active site density and poor electrical conductivity. In this study, to overcome such limitations, we have conducted a thorough investigation to explore the impact of dicyandiamide (DCDA) precursor pretreatment prior to thermal polymerization to graphitic carbon nitride. The DCDA precursor was subjected to various pretreatment methods including grinding using mortar and pestle, recrystallization through stirring or probe sonication after dissolving in deionized water, and freeze drying, prior to thermal polymerization at 550 °C for 2 hours. The structural and morphological properties of the catalysts prepared were compared and characterized by X-ray diffraction (XRD), attenuated total reflectance–Fourier transform infrared (ATR-IR) spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS) analysis while the electronic band gap properties were determined based on density functional theory (DFT) calculations for a set of crystalline systems having C/N ratios similar to those identified experimentally. In comparison to direct thermal polymerization, pretreated samples rendered the same product yield, diverse morphologies with flat or wrinkle structures, and reduced electrochemical resistance, making them suitable for use in various catalytic processes.

36 MATERIALS SCIENCE↗

DOE OSTI2024

The effect of low temperature on poly(3-methyl- N -vinylcaprolactam)- b -poly( N -vinylpyrrolidone) diblock copolymer nanovesicles assembled from all-aqueous media

Nanosized polymeric vesicles (polymersomes) self-assembled from double hydrophilic copolymers of poly(3-methyl-N-vinylcaprolactam) n -b-poly(N-vinylpyrrolidone) m (PMVC n -b-PVPON m ) using all aqueous media are a promising platform for biomedical applications, because of their superior stability over liposomes in vivo and high loading capacity. Herein, we explored the temperature-sensitive behavior of PMVC 58 -b-PVPON 65 vesicles using transmission electron microscopy (TEM), dynamic light scattering (DLS), atomic force microscopy (AFM), and small-angle neutron scattering (SANS) in response to lowering the solution temperature from 37 to 25, 20, 14 and 4 °C. The copolymer vesicles with an average size of 350 nm at 37 °C were assembled from the diblock copolymer dissolved in aqueous solution at 4 °C. We show that while the polymersome's size gradually decreases upon the temperature decrease from 37 to 4 °C, the average shell thickness increases from 17 nm to 25 nm, respectively. SANS study revealed that the PMVC 58 -b-PVPON 65 vesicle undergoes a gradual structure evolution from a dense-shell vesicle at 37–25 °C to a highly-hydrated shell vesicle at 20–14 °C to molecular chain aggregates at 4 °C. From SANS contrast matching study, this vesicle behavior is found to be driven by the gradual rehydration of PMVC block at 37–14 °C. The shell hydration at 20–14 °C also correlated with the 4.4-fold decrease in the relative fluorescence intensity from vesicle-encapsulated fluorescent dye, indicating ~80% of the dye release within 12 hours after the vesicle exposure to 14 °C. No significant (<5%) dye release was observed for the vesicle solutions at 37–20 °C, indicating excellent cargo retention inside the vesicles. Our study provides new fundamental insights on temperature-sensitive polymer vesicles and demonstrates that the copolymer assembly into polymersomes can be achieved by decreasing a copolymer aqueous solution temperature below 14 °C followed by solution exposure to ≥20 °C. This type of all-aqueous assembly, instead of nanoprecipitation from organic solvents or solvent exchange, can be highly desirable for encapsulating a wide range of biological molecules, including proteins, peptides, and nucleic acids, into stable polymer vesicles without a need for organic solvents for dissolution of the copolymers that are amphiphilic at physiologically relevant temperatures of 20–37 °C.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Effect of solvothermal synthesis parameters on the crystallite size and atomic structure of cobalt iron oxide nanoparticles

We here investigate how the synthesis method affects the crystallite size and atomic structure of cobalt iron oxide nanoparticles. By using a simple solvothermal method, we first synthesized cobalt ferrite nanoparticles of ca. 2 and 7 nm, characterized by Transmission Electron Microscopy (TEM), Small Angle X-ray scattering (SAXS), X-ray and neutron total scattering. The smallest particle size corresponds to only a few spinel unit cells. Nevertheless, Pair Distribution Function (PDF) analysis of X-ray and neutron total scattering data shows that the atomic structure, even in the smallest nanoparticles, is well described by the spinel structure, although with significant disorder and a contraction of the unit cell parameter. These effects can be explained by the surface oxidation of the small nanoparticles, which is confirmed by X-ray near edge absorption spectroscopy (XANES). Neutron total scattering data and PDF analysis reveal a higher degree of inversion in the spinel structure of the smallest nanoparticles. Neutron total scattering data also allow magnetic PDF (mPDF) analysis, which shows that the ferrimagnetic domains correspond to ca. 80% of the crystallite size in the larger particles. A similar but less well-defined magnetic ordering was observed for the smallest nanoparticles. Finally, we used a co-precipitation synthesis method at room temperature to synthesize ferrite nanoparticles similar in size to the smallest crystallites synthesized by the solvothermal method. Structural analysis with PDF demonstrates that the ferrite nanoparticles synthesized via this method exhibit a significantly more defective structure compared to those synthesized via a solvothermal method.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2024

Influence of gadolinium doping on structural, optical, and electronic properties of polymeric graphitic carbon nitride

Polymeric graphitic carbon nitride (gCN) materials have received great attention in the fields of photo and electrocatalysis due to their distinct properties in metal-free systems with high physicochemical stability. Nevertheless, the activity of undoped gCN is limited due to its relatively low specific surface area, low conductivity, and poor dispersibility. Doping Gd atoms in a gCN matrix is an efficient strategy to fine-tune its catalytic activity and its electronic structure. Herein, the influence of various wt% of gadolinium (Gd) doped in melon-type carbon nitride was systematically investigated. Gadolinium-doped graphitic carbon nitride (GdgCN) was synthesized by adding gadolinium nitrate to dicyandiamide during polymerization. The X-ray diffraction (XRD) and transmission electron microscopy (TEM) results revealed that the crystallinity and the morphological properties are influenced by the % of Gd doping. Furthermore, X-ray photoelectron spectroscopy (XPS) studies revealed that the gadolinium ions bonded with nitrogen atoms. Complementary density functional theory (DFT) calculations illustrate possible bonding configurations of Gd ions both in bulk material and on ultrathin melon layers and provide evidence for the corresponding bandgap modifications induced by gadolinium doping.

36 MATERIALS SCIENCE↗

DOE OSTI2025

MultiTaskDeltaNet: change detection-based image segmentation for operando ETEM with application to carbon gasification kinetics

Transforming in situ transmission electron microscopy (TEM) imaging into a tool for spatially-resolved operando characterization of solid-state reactions requires automated, high-precision semantic segmentation of dynamically evolving features. However, traditional deep learning methods for semantic segmentation often face limitations due to the scarcity of labeled data, visually ambiguous features of interest, and scenarios involving small objects. To tackle these challenges, we introduce MultiTaskDeltaNet (MTDN), a novel deep learning architecture that creatively reconceptualizes the segmentation task as a change detection problem. By implementing a unique Siamese network with a U-Net backbone and using paired images to capture feature changes, MTDN effectively leverages minimal data to produce high-quality segmentations. Furthermore, MTDN utilizes a multi-task learning strategy to exploit correlations between physical features of interest. In an evaluation using data from in situ environmental TEM (ETEM) videos of filamentous carbon gasification, MTDN demonstrated a significant advantage over conventional segmentation models, particularly in accurately delineating fine structural features. Notably, MTDN achieved a 10.22% performance improvement over conventional segmentation models in predicting small and visually ambiguous physical features. This work bridges key gaps between deep learning and practical TEM image analysis, advancing automated characterization of nanomaterials in complex experimental settings.

08 HYDROGEN↗

DOE OSTI2026

Expanding the Zinc Precursor Toolbox: A Comparative Study of Precursors for Thermal ALD of ZnO Thin Films

Atomic layer deposition (ALD) of zinc oxide (ZnO) has been widely researched using diethyl zinc (DEZ)-based methods. The significant importance of thin films of ZnO as transparent conductive oxides (TCO) in optoelectronic devices and photovoltaics warrants examining alternative Zn precursors for ZnO ALD as potential replacements for the pyrophoric DEZ. In this study, we investigated three alternative Zn precursors: Zn(EEKI)2, Zn(DMP)2, ZnEt(HMDS), in the process development for high-quality ZnO thin films and compared them to DEZ. The ALD processes were studied using in situ spectroscopic ellipsometry. The properties of the ALD ZnO films were characterized using ex situ X-ray photoelectron spectroscopy (XPS), Rutherford backscattering spectrometry and nuclear reaction analysis (RBS/NRA), X-ray diffraction (XRD), atomic force microscopy (AFM), transmission electron microscopy (TEM), and ultraviolet-visible (UV/Vis) spectrophotometry. These measurements confirmed the formation of pure, stoichiometric, and polycrystalline ZnO films using all four Zn precursors. Although the selected precursors are chemically diverse Zn compounds, they all yielded saturating ALD processes and high-quality ZnO thin films at 200 °C. This study highlights the potential benefits of alternative zinc precursors in designing ALD processes for ZnO thin films.

Obenlüneschloß, Jorit↗

DOE OSTI2025

Charges on a suspended silicon nitride membrane under a high-energy electron beam

Thin silicon nitride (SiN x ) membranes are widely used in gas and liquid phase transmission electron microscopy (TEM) and as phase plates to enhance imaging contrast. SiN x contains trap sites for both positive and negative charges, which can be manipulated by high-energy electron irradiation, external potential biasing, or light exposure. Charge accumulation on the membrane can significantly affect in situ TEM processes, including chemical and electrochemical reactions, nanoparticle dynamics, and catalytic activity, or introduce unwanted phase shifts when used as a phase plate. Here, in this study, charge accumulation on suspended SiN x membranes was investigated using off-axis electron holography combined with model-free charge analysis, supported by custom finite element analysis (FEA) simulations. An average residual positive charge density of approximately 2.8 × 10 −4 C m −2 was measured. Localized and stable regions of both positive and negative charges were identified on the membrane. The global positive and localized positive/negative charges give rise to strong electric fields and electroosmotic slip velocities at the membrane surface, which are sufficient to induce non-Brownian particle behavior and directional fluid flow, offering a physical explanation for previously observed anomalies in particle dynamics, nucleation, and growth during gas and liquid phase TEM experiments. These results provide a benchmark for understanding charge behavior at SiNx interfaces in gas and liquid phase TEM. Furthermore, the FEA simulations establish a framework for future investigations into charge distribution, electrostatic potentials, and electrical double layers at solid–liquid interfaces, particularly in complex geometries and chemically dynamic environments.

Suspended silicon↗

DOE OSTI2026

Strong Effect of Nonpolar Solvent Molecular Structure on CdSe Nanoplatelet Stacking

We report a drastic difference in stacking behavior of oleic acid-stabilized 4-monolayer (4 ML) CdSe nanoplatelets (NPLs) in toluene and methylcyclohexane (MCH), two nonpolar solvents that differ in the conformational flexibility of their molecules. Using liquid cell transmission electron microscopy (TEM) and small angle scattering (SAXS) techniques, we show that NPLs form microns-long ribbons consisting of 4 ML CdSe NPLs in toluene, the solvent widely used to form stable colloidal solutions of a broad range of quasi-spherical nanoparticles. In contrast, 4 ML CdSe NPLs are well dispersed in MCH. The difference in stacking behavior of NPLs in toluene and MCH suggests that the conformational flexibility of the solvent molecules, such as the ability to adopt multiple chair conformations, modulates nanoplatelet interactions. Molecular dynamics (MD) simulations reveal that solvent molecules subtly alter the structure of the organic ligand shell. These solvent-dependent changes propagate to the inorganic core, modulating the degree of CdSe nanoplatelet (NPL) twisting and, consequently, the properties of the nanoparticles. We show that toluene better solvates oleate ligands while MCH induces a bimodal oleate span distribution, which can lead to increased solubility of CdSe NPLs. In addition, the solvent can also influence the inorganic core, which, in turn, can modify the nanoparticle properties. We demonstrate that destabilization of toluene solution containing ribbons of 4 ML CdSe NPLs without CdS shells results in the formation of NPL assemblies with amplified spontaneous emission (ASE) with a low threshold of 14 µJ cm−2 that is comparable with that of CdSe/CdS core/shell NPLs. Our results emphasize that the solvent plays a major role in mediating interactions between NPLs and hence their processability for fabrication of functional structures.

CdSe↗

DOE OSTI2021

Prospects for sub-nanometer scale imaging of optical phenomena using electron microscopy

Imaging of optical phenomena at the sub-nanometer scale can offer fundamental insights into the electronic or vibrational states in atomic-scale defects, molecules, and nanoparticles, which are important in quantum information, heterogeneous catalysis, optoelectronics, and structural biology. Several techniques have surpassed the traditional Abbe diffraction limit and attained spatial resolutions down to a few nanometers, but sub-nanometer scale optics has remained elusive. Here, we propose an approach that combines spectrally specific photoabsorption with sub-nanometer scale resolution transmission electron microscopy (TEM) of photoexcited electrons. We first estimate the signal level and conditions required for imaging nanoscale optical phenomena in core-shell quantum dots (QDs) like CdS/CdTe. Furthermore, we show the possibility of imaging photoexcited states of atomic-scale defects in a monolayer hexagonal boron nitride (h-BN) using ab initio and high resolution (HR)TEM simulations. The ability to directly visualize photoexcited states at the sub-nanometer scale opens opportunities to study properties of individual quantum dots and atomic defects.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2022

Comprehensive characterization of irradiation induced defects in ceria: Impact of point defects on vibrational and optical properties

Validation of multiscale microstructure evolution models can be improved when standard microstructure characterization tools are coupled with methods sensitive to individual point defects. We demonstrate how electronic and vibrational properties of defects revealed by optical absorption and Raman spectroscopies can be used to compliment transmission electron microscopy (TEM) and x-ray diffraction (XRD) in the characterization of microstructure evolution in ceria under non-equilibrium conditions. Experimental manifestation of non-equilibrium conditions was realized by exposing cerium dioxide (CeO2) to energetic protons at elevated temperature. Two sintered polycrystalline CeO2 samples were bombarded with protons accelerated to a few MeVs. These irradiation conditions produced a microstructure with resolvable extended defects and a significant concentration of point defects. A rate theory (RT) model was parametrized using the results of TEM, XRD, and thermal conductivity measurements to infer point defect concentrations. An abundance of cerium sublattice defects suggested by the RT model is supported by Raman spectroscopy measurements, which show peak shift and broadening of the intrinsic T2g peak and emergence of new defect peaks. Additionally, spectroscopic ellipsometry measurements performed in lieu of optical absorption reveals the presence of Ce3+ ions associated with oxygen vacancies. This work lays the foundation for a coupled approach that considers a multimodal characterization of microstructures to guide and validate complex defect evolution models.

Chauhan, Vinay S.↗

DOE OSTI2024

Deep learning-enabled probing of irradiation-induced defects in time-series micrographs

Modeling time-series data with convolutional neural networks (CNNs) requires building a model to learn in batches as opposed to training sequentially. Coupling CNNs with in situ or operando techniques opens the possibility of accurately segmenting dynamic reactions and mass transport phenomena to understand how materials behave under the conditions in which they are used. In this article, in situ ion irradiation transmission electron microscopy (TEM) images are used as inputs into the CNN to assess the defect generation rate, defect cluster density, and saturation of defects. We then use the output segmentation maps to correlate with conventional TEM micrographs to assess the model’s ability to detail nanoscale interactions. Next, we discuss the implications of preprocessing and hyperparameters on model variability, accuracy when expanded to other datasets, and the role of regularization when controlling model variance. Ultimately, we eliminate human bias when extrapolating physical metrics, speed up analysis time, decouple reactions that happen at 100 ms intervals, and deploy models that are both accurate and transferable to similar experiments.

Burns, Kory (ORCID:0000000158019909)↗

DOE OSTI2024

Multi-microscopy characterization of threading dislocations in CVD-grown diamond films

We present site-coincident imaging of a high dislocation density boron-doped chemical vapor deposition-grown homoepitaxial (001) diamond film using electron channeling contrast imaging (ECCI), cathodoluminescence, transmission electron microscopy (TEM), and scanning secondary ion mass spectroscopy (SIMS). With growing interest in large area heteroepitaxial substrates, we show that ECCI is a promising technique to accurately evaluate dislocations in diamond films. We find the electron backscatter yield is sufficient to distinguish individual threading dislocations in ECCI despite the low atomic number of carbon, and we have generally good agreement between dislocations observed in ECCI and TEM of the same region. Importantly, relying on luminescence in the 430 nm dislocation-related A-band alone results in an underestimation of the defect density as we find only 20%–40% of the threading dislocations luminesce. Here, we further show that dislocations do not perturb the spatial uniformity of boron doping measured by SIMS, even when the dislocations are clustered with high density, and we can tentatively rule out strong segregation effects at the dislocations. Our results establish the complementary use of microscopy and microanalysis methods to rapidly characterize and understand the impact of dislocations in diamond thin films.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Mixed-flow design for microfluidic printing of two-component polymer semiconductor systems

The rational creation of two-component conjugated polymer systems with high levels of phase purity in each component is challenging but crucial for realizing printed soft-matter electronics. Here, we report a mixed-flow microfluidic printing (MFMP) approach for two-component π -polymer systems that significantly elevates phase purity in bulk-heterojunction solar cells and thin-film transistors. MFMP integrates laminar and extensional flows using a specially microstructured shear blade, designed with fluid flow simulation tools to tune the flow patterns and induce shear, stretch, and pushout effects. This optimizes polymer conformation and semiconducting blend order as assessed by atomic force microscopy (AFM), transmission electron microscopy (TEM), grazing incidence wide-angle X-ray scattering (GIWAXS), resonant soft X-ray scattering (R-SoXS), photovoltaic response, and field effect mobility. For printed all-polymer (poly[(5,6-difluoro-2-octyl-2H-benzotriazole-4,7-diyl)-2,5-thiophenediyl[4,8-bis[5-(2-hexyldecyl)-2-thienyl]benzo[1,2-b:4,5-b′]dithiophene-2,6-diyl]-2,5-thiophenediyl]) [J51]:(poly{[N,N′-bis(2-octyldodecyl)naphthalene-1,4,5,8-bis(dicarboximide)-2,6-diyl]-alt-5,5′-(2,2′-bithiophene)}) [N2200]) solar cells, this approach enhances short-circuit currents and fill factors, with power conversion efficiency increasing from 5.20% for conventional blade coating to 7.80% for MFMP. Moreover, the performance of mixed polymer ambipolar [poly(3-hexylthiophene-2,5-diyl) (P3HT):N2200] and semiconducting:insulating polymer unipolar (N2200:polystyrene) transistors is similarly enhanced, underscoring versatility for two-component π -polymer systems. Mixed-flow designs offer modalities for achieving high-performance organic optoelectronics via innovative printing methodologies.

42 ENGINEERING↗

DOE OSTI2025

Barrierless nucleation in glassy precursors drives zeolite formation

Zeolites are crystalline, microporous silicates widely used in catalysis and separations, yet the molecular mechanisms of their formation remain unresolved. Experiments indicate that hydrothermal synthesis of silica zeolites from clear solution proceeds through amorphous nanoaggregates that gradually develop zeolite order in an apparently continuous amorphous to crystal transformation. Here, we combine molecular simulations with advanced algorithms that identify zeolite order and computer vision to elucidate the pathway from clear solution to zeolite nanocrystal. We show that at conditions of hydrothermal synthesis of silica zeolites, the transformation of precursor aggregate into zeolite is not limited by nucleation barriers but by the slow dynamics of reorganization in the glassy precursor matrix. The negligible nucleation barriers result in spinodal-like crystallization that leads to a gradual formation of a mosaic of small crystallites that explain the seemingly continuous character of zeolite crystallization and the catalytic activity of X-ray amorphous, protozeolites and embryonic zeolites. We find that zeolite-like porosity and short-range order emerge early within glassy precursors, well before crystallinity is detected in transmission electron microscopy (TEM) images or X-ray diffraction. The nanoaggregate’s temperature-size phase diagram reveals a convergence of the zeolite–amorphous equilibrium and maximum crystallization rate at ~3 nm diameter nanoparticle diameters and ~200 °C. This convergence signals the termination of the first-order amorphous-to-zeolite transition. Our results provide a unifying framework for understanding nucleation of silica zeolites from solution and suggest that barrierless nucleation may govern the formation of other nanoparticle systems, including minerals and oxides synthesized far below their bulk melting points.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Soot Formation and Growth in Toluene/Ethylene Combustion Catalyzed by Ruthenium Acetylacetonate

Ruthenium-based compounds are efficient catalysts to enhance combustion performance and suppress soot emission. However, systematic mechanism and in-situ research on reducing soot are rarely addressed. In this study, ruthenium acetylacetonate (Ru(C 5 H 7 O 2 ) 3 , Ru(acac) 3 ) was utilized as the catalyst precursor in different concentration conditions to investigate its impacts on the size, volume, and morphology of the soot particles in the ethylene flames with central toluene injection. The soot particles were detected by in-situ small-angle X-ray scattering (SAXS) and ex-situ transmission electron microscopy (TEM). This study confirms that Ru(acac) 3 can suppress the surface growth for the primary soot particles, but no significant change of the morphology has been discovered for the aggregates. Compared with the undoped flame, the volume of the soot particles in the Ru(acac) 3 -doped flames is lower and the particle size is smaller, indicating a valid inhibition effect of Ru(acac) 3 on the soot emission by affecting its surface growth and oxidation process. In conclusion, despite the remarkable distinction between the undoped and doped flames, no obvious difference is found between the flames with different catalyst concentrations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Pulsed laser heating of diesel engine and turbojet combustor soot: Changes in nanostructure and implications

Here, carbonaceous particulate produced by a diesel engine and turbojet engine combustor are analyzed by transmission electron microscopy (TEM) for differences in nanostructure before and after pulsed laser annealing. Soot is examined between low/high diesel engine torque and low/high turbojet engine thrust. Small differences in nascent nanostructure are magnified by the action of high-temperature annealing induced by pulsed laser heating. Lamellae length distributions show occurrence of graphitization while tortuosity analyses reveal lamellae straightening. Differences in internal particle structure (hollow shells versus internal graphitic ribbons) are interpreted as due to higher internal sp3 and O-atom content under the higher power conditions with hypothesized greater turbulence and resulting partial premixing. TEM in concert with fringe analyses reveal that a similar degree of annealing occurs in the primary particles in soot from both diesel engine and turbojet engine combustors—despite the aggregate and primary size differences between these sources. Implications of these results for source identification of the combustion particulate and for laser-induced incandescence (LII) measurements of concentration are discussed with inter-instrument comparison of soot mass from both diesel and turbojet soot sources.

42 ENGINEERING↗