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TRACER Carbonaceous Aerosols Thrust – University of California, Davis Field Campaign Report
The broader U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s TRacking Aerosol Convection interactions ExpeRiment (TRACER) campaign aims to increase our understanding of convective cloud life cycles and aerosol-convection interactions. Our TRACER Carbonaceous Aerosols Thrust-University of California, Davis (TRACER-CAT-UCDavis) study complemented these broader aims by characterizing and quantifying the optical properties and composition of carbonaceous aerosols during part of the TRACER intensive sampling period (July 1- July 31, 2022) at the first ARM Mobile Facility (AMF1) main site (M1) in La Porte, Texas. Our measurements complemented the suite of instrumentation already provided by the AMF1, expanding the capabilities through deployment of unique, state-of-the-science instrumentation. The instrumentation included: (i) two cavity-attenuated phase shift spectroscopy single-scatter albedo (CAPS-SSA) instruments operating at 530 nm and 630 nm, and that were modified to characterize particle light absorption, extinction, and scattering at elevated humidities; (ii) the UC Davis dual-wavelength cavity ringdown-photoacoustic spectrometer (CRD-PAS), which characterizes dry particle extinction and absorption at 405 nm and 532 nm; (iii) a soot particle aerosol mass spectrometer (SP-AMS) that operated in “laser only” mode that characterized the size-dependent compositions of black carbon (BC)-containing particles; (v) a thermal denuder, to remove coatings on particles; and (vi) a scanning electrical mobility sizer (SEMS), to characterize particle mobility diameters from 10-1300 nm. Our measurements occurred alongside complementary observations made by Los Alamos National Laboratory (LANL) during the TRACER-CAT-LANL study, including a humidified CAPS-SSA instrument operating at 450 nm. Our primary scientific interest is in understanding the relationship between particle composition and light absorption, with a particular focus on the influence of water uptake. While it is known that coatings on BC can enhance absorption, the extent to which this occurs in the atmosphere and the specific role that water plays as a coating remain unclear. The TRACER-CAT-UCDavis measurements were made with near-complete coverage for the CRD-PAS, SP-AMS, and SEMS throughout the intensive period. The UC Davis humidified CAPS-SSA instruments had significant challenges with operation owing to the demanding conditions (large temperature fluctuations, high humidity), exacerbated by supply chain issues that delayed resolution of these challenges. However, the humidified CAPS-SSA instrument operated by LANL operated throughout the intensive period with near-complete coverage. The dry light extinction measurements from the CRD-PAS measurements and the LANL CAPS-SSA exhibited a good correlation, although the CAPS-SSA systematically measured greater extinction values than expected. While all instruments, with the exception of an aerodynamic particle sizer (APS), measured behind a common particulate matter (PM)2.5 μm cyclone, the greater extinction measured by the LANL CAPS-SSA compared to the CRD-PAS may have resulted from different losses of larger particles in the sampling lines from the cyclone to the instruments; the tubing length was shorter from the cyclone to the LANL CAPS-SSA, consistent with this idea. A summary of the TRACER-CAT-UCDavis measurements, along with some of the TRACER-CAT-LANL measurements, are shown in the figure below. Notably, there were periods when the contributions of presumed dust were substantial and even dominated the observed light extinction and absorption. Also, there was a clear shift in the behavior of submicron particles from before July 16, 2022 to after, with the prior period exhibiting regular episodes of new particle formation and the latter period exhibiting rapid variations in the concentrations of small particles.
Integrated Design of Ultradurable, Low CO 2 Alternative Binder Systems via Machine Learning
This ARPA-E project developed a machine learning tool to use in formulation design of cementitious binders for concrete having 50% less embodied CO 2 and possessing twice the durability compared to concrete based on ordinary portland cement (OPC) binders. The technical focus was on limestone/calcined clay cement (LC3), the leading replacement for OPC. Here, hierarchical machine learning (HML) was used to model the flowability, set time, strength, and durability of LC3 concrete. This methodology identifies latent variables derived from domain knowledge and empirical models that develop an accurate model for a response surface from small datasets. For the flowability metric, particle packing was a dominant factor, while strength and durability were both strongly determined by the fraction of metakaolin and the water:solids ratio. Under constraints of water:binder ratio, material performance metrics, embodied CO 2 , and cost per tonne of OPC, multi-objective optimization was used to design binders parameterized by the mineral composition replacing OPC, particle size distributions, and water:solids ratio. The trained algorithm was able to predict multiple mixes met these performance criteria, and experimental testing validated the predictions. The model demonstrated here is relevant for North America, where pure kaolin deposits are found broadly. The approach is being taken forward into commercial application by Ansatz AI, a materials informatics company founded by PI Washburn and co-PI Poczos. Through collaborations with the cement and concrete industry, and funding from SBIR programs, a commercial software will be developed in future research.
Aluminum/SmCo 5 composites for structural and magnetic applications
Metal-bonded magnetic composites (MBMCs) present a promising alternative to dense sintered magnets, particularly for intricate components. Compared to polymer-based bonded magnets, MBMCs have wider applicability in harsh environments. In this paper, we demonstrate a solid-state shear-based manufacturing technique to introduce localized magnetization into a paramagnetic aluminum matrix by embedding SmCo5 permanent magnet particles. Our magnetic composites display hard magnetic behavior with a coercivity of 13 kOe and a remanent magnetization of 4.32 emu/g. In addition to magnetization, we also report a 9% improvement in Young’s modulus. Despite the local temperature rise during processing, the magnetic phases didn’t decompose into unwanted phases, preserving the composite's hard magnetic properties. Creation of an interfacial metallurgical bond with the matrix ensured the suitability of the composites for structural applications. Our study investigates the mechanical, and functional properties of composites, paving the way for lightweight structural magnetic composites with a transformative potential in the aerospace, nuclear, and automotive applications. This work underscores the potential for further optimization and development to drive innovations in magnet and equipment design.
Diversifying Composition Leads to Hierarchical Composites with Design Flexibility and Structural Fidelity
Although significant progress has been made in the self-assembly of nanostructures, present successes heavily rely on precision in building block design, composition, and pair interactions. These requirements fundamentally limit our ability to synthesize macroscopic materials where the likelihood of impurity inclusion escalates and, more importantly, to access molecular-to-nanoscopic-to-microscopic-to-macroscopic hierarchies, since the types and compositions of building blocks vary at each stage. Inspired by biological blends and high-entropy alloys, we hypothesize that diversifying the blend’s composition can overcome these limitations. Increasing the number of components increases mixing entropy, leading to the dispersion of different components and, as a result, enhances interphase miscibility, weakens the dependence on specific pair interactions, and enables long-range cooperativity. This hypothesis is validated in complex blends containing small molecules, block copolymer-based supramolecules, and nanoparticles/colloidal particles. Hierarchically structured composites can be obtained with formulation flexibility in the filler selection and blend composition. It is worth noting that, by adding small molecules, we can solve the size constraint that plagues traditional block copolymer/nanoparticle blends. Detailed characterization and simulation further confirm that each component is distributed to locally mediate unfavorable interactions, cooperatively mitigate composition fluctuations, and retain structural fidelity. Furthermore, the blends have sufficient mobility to access tunable microstructures without compromising the order of the nanostructure. Besides establishing a kinetically viable pathway to release current constraints in the composite design and to navigate uncertainties during structure formation over multiple length scales, the present study demonstrates that entropy-driven behaviors can be realized in systems beyond high-entropy alloys despite inherent differences between metal alloys and organic/inorganic hybrids.
Structural evolution and magnetic hardness of (Sm,Zr)(Fe,Co,Ti) 12 alloy particles via reduction-diffusion
The quest for achieving high coercivity in Sm(Fe,Co,Ti) 12 alloys, despite their inherent strong magnetocrystalline anisotropy, has posed significant challenges. Recently, (Sm,Zr)(Fe,Co,Ti) 12 monocrystalline particles have exhibited coercivity μ 0 H c > 1.2 T, showcasing promising prospects and significant potential for both manufacturing and research endeavors. This study delves into the structural evolution of (Sm,Zr)(Fe,Co,Ti) 12 (1:12) alloy particles made via the calciothermic reduction-diffusion synthesis process as influenced by the molar ratios of Ca atoms to O 2- ions (Ca/O), annealing time and annealing temperature. Critical insight that informs conditions to optimize the magnetic response is gained via systematic experimentation and advanced electron microscopy. Complex structural features, including core-shell morphologies and intricate multiphase compositions within individual particles, are unveiled. An optimal Ca/O ratio of 1.30 produces particles with a coercivity up to μ 0 H c = 1.63 T, while higher Ca/O ratios induce the formation of a Sm-rich TbCu 7 -type (1: 7 ) phase, which only partially transforms into the desired 1:12 phase during annealing. Persistent remnants of the 1:7 phase locally impact atomic structure, particle morphology, and coercivity. Furthermore, these findings underscore the complex interplay between synthesis parameters, resulting structures, and magnetic properties, informing the design and optimization of high-performance permanent magnets comprised of the (1:12) compound.
Quantum Composites with Charge-Density-Wave Fillers
Here, a unique class of advanced materials—quantum composites based on polymers with fillers composed of a van der Waals quantum material that reveals multiple charge-density-wave quantum condensate phases—is demonstrated. Materials that exhibit quantum phenomena are typically crystalline, pure, and have few defects because disorder destroys the coherence of the electrons and phonons, leading to collapse of the quantum states. The macroscopic charge-density-wave phases of filler particles after multiple composite processing steps are successfully preserved in this work. The prepared composites display strong charge-density-wave phenomena even above room temperature. The dielectric constant experiences more than two orders of magnitude enhancement while the material maintains its electrically insulating properties, opening a venue for advanced applications in energy storage and electronics. The results present a conceptually different approach for engineering the properties of materials, extending the application domain for van der Waals materials.
Thermal stability of filler‐based ethylene/vinyl acetate/vinyl alcohol terpolymer in nitroplasticizer oxidative environment
Abstract To study the thermal stability of ethylene/vinyl acetate/vinyl alcohol (EVA‐OH) composite with filler particles, systematic thermogravimetric analysis (TGA) investigation was conducted in both nonisothermal and isothermal modes. The effect of polymer concentration on the aging behavior of EVA‐OH was investigated in the nitroplasticizer (NP) environment. Fourier transform infrared spectroscopy was used to probe chemical structural changes in the EVA‐OH polymer before and after thermal aging. The results suggest that filler addition accelerates the rate of NP exudation out of the EVA‐OH composites and deteriorates the thermal stability of NP at moderate temperatures (up to 70°C). The degradation of NP, in turn, accelerates the degradation of EVA‐OH polymer in its composite form through oxidation and hydrolysis indicating the importance of antioxidants in such phase blends.
The characterization of wear-causing particles and silica sand in particular
Erodants and abradants are two types of wear-causing particles (WCP). Despite their effects on the severity and rate of wear, WCP are inadequately characterized in a surprising number of publications, especially those involving impingement erosion and three-body abrasion. That shortfall makes it difficult to correlate features of WCP with the details of worn surfaces, or to develop wear models that account for those features. It is argued that the documentation of WCP should go beyond simply reporting their composition and mean particle size. In late 1985, ASTM Committee G2 on Wear and Erosion established a task group on the characterization of WCP. At that time, image analysis was slower and less sophisticated than it is today. While that ASTM task group failed to produce a consensus standard, computerized particle characterization methods were developing in fields other than tribology, fields like geoscience, heavy sand mining, materials processing, and pharmaceuticals. A notable exception to this is ferrography, which is a widely-used diagnostic for lubricated tribosystems. In the context of dry wear, it is useful to identify which features of WCP would be beneficial to document, and to identify some techniques and scales of detail appropriate to particular tribosystems. In this paper, examples are presented for the morphological and mechanical characterization of silica sand grains, as prompted by a triboanalysis of the abrasive and erosive wear of biomass pre-processing equipment. The authors propose a minimum level of documentation for WCP, one that can enrich tribosystem analysis both in laboratory tests and field studies.
Single-Particle Isotopic Analysis Using the Liquid Sampling-Atmospheric Pressure Glow Discharge Microplasma Coupled to an Orbitrap Mass Spectrometer
Isotope ratio (IR) determinations on individual particles can provide valuable information relative to the sample, including processing and dating, which could be valuable to geological and nuclear material analysis communities. In comparison to “bulk” measurements, in which all particle information is lost and homogenized within a sample, “particle” measurements allow for fingerprinting and can provide unique insights related to the sample’s nano- and micro- compositions. Furthermore, the complex nature of particles, with potential isobaric interferences from either the matrix or other elements within the same particle, poses a significant analytical challenge for conventional mass spectrometry platforms employed for elemental analysis due to their limited mass resolution. Presented here is the first demonstration of an ultrahigh resolution method for single particle (SP) isotopic analysis using the liquid sampling-atmospheric pressure glow discharge (LS-APGD) microplasma ionization source coupled to an Orbitrap mass spectrometer and FTMS Booster X2T acquisition/processing system. For proof of concept, well-characterized CeO 2 microparticles with a nominal diameter of 1.0 μm were analyzed at a mass resolution of ∼330,000. Important instrumental parameters were optimized to enable the detection of single particles. The 142 Ce/ 140 Ce ratio of individual particles and the population average were determined and compared to an SP inductively coupled plasma time-of-flight mass spectrometry (ICP-TOF-MS) analysis. The isotopic accuracy and precision were determined by two methods and found to be in good agreement with the SP-ICP-TOF-MS method, with the linear regression slope method providing a more accurate ratio, showing a ∼1.4% relative difference from the ratio determined from a particle digest. The encouraging performance of the method was further supported by a determined detection limit of 2.9 fg ( 142 Ce). The developed method is anticipated to overcome many of the challenges posed by isobaric interferences encountered in conventional mass spectrometry techniques when analyzing real-world samples for particle isotopic composition.
Probing the meta-stability of oxide core/shell nanoparticle systems at atomic resolution
Hybrid nanoparticles allow exploiting the interplay of confinement, proximity between different materials and interfacial effects. However, to harness their properties an in-depth understanding of their (meta)stability and interfacial characteristics is crucial. This is especially the case of nanosystems based on functional oxides working under reducing conditions, which may severely impact their properties. Here, the in-situ electron-induced selective reduction of Mn 3 O 4 to MnO is studied in magnetic Fe 3 O 4 /Mn 3 O 4 and Mn 3 O 4 /Fe 3 O 4 core/shell nanoparticles by means of high-resolution scanning transmission electron microscopy combined with electron energy-loss spectroscopy. Such in-situ transformation allows mimicking the actual processes in operando environments. A multi-stage image analysis using geometric phase analysis combined with particle image velocity enables direct monitoring of the relationship between structure, chemical composition and strain relaxation during the Mn 3 O 4 reduction. In the case of Fe 3 O 4 /Mn 3 O 4 core/shell the transformation occurs smoothly without the formation of defects. However, for the inverse Mn 3 O 4 /Fe 3 O 4 core/shell configuration the electron beam-induced transformation occurs in different stages that include redox reactions and void formation followed by strain field relaxation via formation of defects. This study highlights the relevance of understanding the local dynamics responsible for changes in the particle composition in order to control stability and, ultimately, macroscopic functionality.
Mixed conductive composites for ‘Low-Temperature’ thermo-chemical CO 2 splitting and syngas generation
An effective strategy to design platinum group metal (PGM) free redox catalysts for “low temperature” CO 2 splitting followed with methane partial oxidation was proposed and validated. Composites of mixed ionic-electronic conductive (MIEC) oxides were found to be highly effective at relatively low temperatures (600–750 °C). Specifically, perovskite structured LaNi 0.35 Fe 0.65 O 3 and rock salt structured Ce 0.85 Gd 0.1 Cu 0.05 O 2–δ , as two compatible yet structurally distinct MIEC oxides, were integrated into composite redox catalyst particles. Resulting from the synergistic effect of the two MIEC phases, 90% CO 2 to CO conversion was demonstrated at 750 °C. Up to 90% methane conversion with 96% CO selectivity was also achieved in the methane POx step. The redox catalysts were characterized in detail to illustrate the underlying mechanisms for the synergistic effects. Electrical conductivity relaxation (ECR) measurements indicated significantly lowered activation energy for lattice oxygen (O 2– ) migration (0.43 eV). The enhanced oxygen migration in turn led to reversible exsolution of active transition metal nanoparticles (Ni–Fe alloy) from the mixed oxide, serving as active sites for methane activation while further enhancing lattice oxygen exchange, as confirmed by in situ X-ray diffraction and transmission electron microscopy. In conclusion, the composite redox catalysts demonstrate superior redox activity, coke resistance, and long term redox stability, making them potentially suitable for CO 2 utilization and methane partial oxidation under a hybrid redox process scheme.
Structural Evolution of Layered Hybrid Lead Iodide Perovskites in Colloidal Dispersions
Controlling the structure of layered hybrid metal halide perovskites, such as the Ruddlesden-Popper (R-P) phases, is challenging because of their tendency to form mixtures of varying composition. Colloidal growth techniques, such as antisolvent precipitation, forms colloidal dispersions with properties that match bulk layered R-P phases, but controlling the composition of these particles remains challenging. Here, we explore the microstructure of particles of R-P phases of methylammonium lead iodide prepared by antisolvent precipitation from ternary mixtures of alkylammonium cations, where one cation can form perovskite phases (CH 3 NH 3 + ) and the other two promote layered structures as spacers (e.g. C 4 H 9 NH 3 + and C 12 H 25 NH 3 + ). We determine that alkylammonium spacers pack with constant methylene density in the R-P interlayer, and exclude interlayer solvent in dispersed colloids, regardless of length or branching. Using this result, we illustrate how the competition between cations that act as spacers between layers, or as grain- terminating ligands, determines the colloidal microstructure of layered R-P crystallites in solution. Optical measurements reveal that quantum well dimensions can be tuned by engineering the ternary cation composition. Transmission synchrotron wide-angle X-ray scattering and small angle neutron scattering reveal changes in the structure of colloids in solvent and after deposition into thin films. In particular, we find that spacers can alloy between R-P layers if they share common steric arrangements, but tend to segregate into polydisperse R-P phases if they do not mix. In conclusion, this study provides a framework to compare the microstructure of colloidal layered perovskites and suggests clear avenues to control phase and colloidal morphology.
Interfacial Reactivity of Silicon Electrodes: Impact of Electrolyte Solvent and Presence of Conductive Carbon
Silicon (Si) is a promising high-capacity material for lithium-ion batteries; however, its limited reversibility hinders commercial adoption. Approaches such as particle and crystallite size reduction, introduction of conductive carbon, and use of different electrolyte solvents have been explored to overcome these electrochemical limitations. Herein, operando isothermal microcalorimetry (IMC) is used to probe the influence of silicon particle size, electrode composition, and electrolyte additives fluoroethylene carbonate and vinylene carbonate on the heat flow during silicon lithiation. In this work, the IMC data are complemented by X-ray photoelectron and Raman spectroscopies to elucidate differences in solid electrolyte interphase (SEI) composition. Nanosized (~50 nm, n-Si) and micrometer-sized (~4 μm, μ-Si) silicon electrodes are formulated with and without amorphous carbon and electrochemically lithiated in ethylene carbonate (EC), fluoroethylene carbonate (FEC), or vinylene carbonate (VC) based electrolytes. Notably, n-Si electrodes generate 53–61% more normalized heat relative to their μ-Si counterparts, consistent with increased surface area and electrode/electrolyte reactivity. Introduction of amorphous carbon significantly alters the heat flow profile where multiple exothermic peaks and increased normalized heat dissipation are observed for all electrolyte types. Notably, the VC-containing electrolyte demonstrates the greatest normalized heat dissipation of the electrode compositions tested showing as much as a 50% increase compared to the EC or FEC counterparts. The results are relevant to the understanding of silicon negative electrode function in the presence of electrolyte additives and provide insight relative to silicon containing cell reactivity and safety.
Simulations of the collection of mesospheric dust particles with a rocket instrument
We investigate the collection of dust particles in the mesosphere with the MESS (MEteoric Smoke Sampler) instrument that is designed to fly on a sounding rocket. We assume that the ice particles that form in the polar mesosphere between 80 and 85 km altitude in summer contain meteoric smoke particles; and these should be collected with MESS. The instrument consists of a collection device with an opening and closure mechanism, as well as an attached conic funnel which increases the sampling area in comparison to the collection area. Dust particles are collected either directly after passing through the instrument or indirectly after colliding with and fragmenting on the funnel wall. We calculate the dust and fragment trajectories in the detector to determine the collection efficiency for different particle sizes, rocket velocities, and heights, and we find the final velocities and the temperatures of the particles. The considered design has a sampling area of 62.78 mm diameter and a collection area of 20 mm diameter. For the conditions at the rocket launch site in Andøya, Norway, we estimate the collection of meteoric smoke particles contained in the ice particles to be ~10 12 –10 14 amu mm –2 . The estimated temperatures suggest that the composition of these smoke particles is not affected by the collection. Our calculations also show that keeping the instrument open above 85 km altitude increases the amount of small smoke particles that are directly collected. The directly collected smoke particles are heated as they decelerate, which can affect their composition.
Identifying Sample Provenance From SEM/EDS Automated Particle Analysis via Few-Shot Learning Coupled With Similarity Graph Clustering
Automated particle analysis (APA) provides a vast amount of compositional data via energy-dispersive X-ray spectroscopy along with size and shape data via scanning electron microscopy for individual particles in a sample. In many instances, APA data are leveraged to support identification of the source of a sample based on the detection of particles of a specific composition. Often, the particles that provide context make up a minuscule portion of the sample. Additionally, the interpretation of complex samples can be difficult due to the diversity of compositions both in the mixture and within a particle. In this work, we demonstrate a method to compute and cluster similarity graphs that describe inter-particle relationships within a sample using a multi-modal few-shot learning neural network. Here, as a proof-of-concept, we show that samples known to have been exposed to gunshot residue can be distinguished from samples occasionally mistaken for gunshot residue. Our workflow builds upon standard APA techniques and data processing methods to unveil additional information in a readily interpretable and quantitatively comparable format.
Codelivery of Paclitaxel and Parthenolide in Discoidal Bicelles for a Synergistic Anticancer Effect: Structure Matters
Nanotechnology has long been used to improve the tumor targeting of chemotherapeutics. The structure of these nanocarriers greatly affects their efficacy and toxicity. Herein, structurally stable nanodiscoidal phospholipid bicelles, which are capable of encapsulating anticancer drugs, paclitaxel (PTX) and parthenolide (PTL), are designed. This nanodiscoidal bicelle structure is shown previously to exhibit longer blood circulation, deeper tumor penetration, and increased tumor cell uptake compared with spherical particles of similar compositions. Structural characterization and loading capacity of the PTX‐ and PTL‐ loaded nanodiscs are conducted along with an investigation into the cytotoxicity of the bicelles based on the drug‐to‐lipid ratios of both drugs loaded separately and in combination. A significant synergistic effect between both loaded drugs is also observed in A549 lung cancer and drug‐resistant MDA‐MB‐231 cell lines. An in vivo study using mice bearing subcutaneous A549 tumors shows a long circulation time of the intravenously injected DiR‐loaded bicelles and significant antitumor efficacy of the PTX‐ and PTL‐loaded bicelles. This efficacious self‐assembled nanoparticle system displays great potential as a nanoplatform to codeliver multiple therapeutics or diagnostics for improving cancer therapy.