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At least 307 records · Page 17

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Evolution of AISI 304L stainless steel part properties due to powder recycling in laser powder-bed fusion

Selective laser melting (SLM) is a powder-bed fusion process in Additive Manufacturing (AM) that uses a laser beam to selectively fuse layers of powder into near net-shape components with little porosity. However, inconsistencies in the part properties due to the presence of defects in as-built components has hindered the widespread adoption of SLM for industrial applications forcing researchers to study the sources of variation for quality control purposes. A critical area suspected of creating variation in the part properties is the feedstock, where batch-to-batch differences as well as changes in the powder properties with reuse have the potential to affect performance. During processing, laser spatter and condensate eject from the melt pool and deposit into the powder-bed surrounding the parts. These particulates, more commonly known as ejecta, differ morphologically and chemically from the virgin powder compromising its reusability. In this study, 304L stainless steel powder was recycled for a total of 5 times through a systematic approach aimed at accelerating powder degradation to reveal the influence on both the tensile and impact toughness properties. Through analysis of variance (ANOVA), it was found that tensile properties did not change with reuse, while the impact toughness showed a steady decline illustrating the differences in static and dynamic part properties due to powder recycling.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Comparison on the properties of ITZs in fly ash-based geopolymer and Portland cement concretes with equivalent flowability

Highlights: • Modelled ITZs can effectively avoid the effects caused by different factors and test locations of ITZ. • ITZ properties of PC and geopolymer concretes are compared based on equivalent flowability of binders. • Geopolymer ITZ exhibits stronger bonding than that of PC, and higher mechanical properties than geopolymer paste. • Strong ITZs in geopolymer concrete are attributed to the layer of gel-rich paste with dense microstructures. • Elastic modulus and hardness properties of ITZs in PC concrete are increased due to the CH crystals. This paper aims to compare the properties of interfacial transition zones (ITZs) in Portland cement (PC) concrete and geopolymer concrete. Portland cement and geopolymer pastes were designed with the equivalent flowability to provide similar mix and casting condition of ITZs. Two types of modelled ITZs were prepared to facilitate the nanoindentations across ITZs, microstructural characterization, and comparison on the properties of ITZs with less influential factors. The results showed that the interfacial bonding of ITZs between geopolymer matrix and aggregate is relatively stronger than the counterpart in the PC concrete. There is a high amount of crystalline hydration products in the ITZs of PC concrete, but a layer gel-rich paste with denser microstructures in the ITZs of geopolymer concrete. Additionally, the interface morphology and nanoindentation analysis indicate that the property of ITZs in the modelled geopolymer concrete is not poorer than that of the corresponding geopolymer paste.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Analysis of structure-property gradients in orthogonally machined chips and workpiece subsurface

Production of machined surfaces with optimized mechanical properties requires fundamental process-structure-property knowledge. In this paper, we focus on structure-property gradients in orthogonally cut OFHC Copper chips and the workpiece subsurface. We utilize orientation imaging microscopy and statistical spatial correlation metrics to quantify the microstructure. Constitutive elastic-plastic properties of the workpiece subsurface and chips are measured using spherical nanoindentation. Analysis of the data reveals significant structure and property gradients in both regions. Differences and similarities in structure and property gradients near the workpiece surface and tool-chip interface, and in the chip middle are discussed and explained.

42 ENGINEERING↗

DOE OSTI2025

A structured framework for predicting sustainable aviation fuel properties using liquid-phase FTIR and machine learning

Sustainable aviation fuels have the potential to improve efficiency, reduce emissions, and enhance energy security. To help identify viable sustainable aviation fuels and accelerate research, machine learning models have been developed to predict relevant physicochemical properties. However, many models have limited applicability, leverage data from complex analytical techniques with confined spectral ranges, or use feature decomposition methods that offer limited interpretability. Using liquid-phase Fourier Transform Infrared (FTIR) spectra, this study presents a structured method for creating accurate and interpretable property prediction models for neat molecules, aviation fuels, and blends. Liquid FTIR spectra can be collected quickly and consistently, offering high reliability, sensitivity, and component specificity using less than 2 ml of sample. The method first decomposes FTIR spectra into fundamental building blocks using non-negative matrix factorization (NMF) to enable scientific analysis of FTIR spectra attributes and fuel properties. The NMF features are then used to create five ensemble models for predicting final boiling point, flash point, freezing point, density at 15°C, and kinematic viscosity at -20°C. All models were trained using experimental property data from neat molecules, aviation fuels, and blends. The models accurately predict key properties across a broad range of neat molecules and representative fuels and blends, while enabling interpretation of relationships between compositional elements, such as functional groups or chemical classes, and their resulting properties. This demonstrates strong potential to support sustainable aviation fuel research and development. The models and data are available on an interactive web tool.

Fourier transform infrared spectroscopy↗

DOE OSTI2026

Quantifying market volume sensitivity to material property modifications in polyhydroxybutyrate: A parametric analysis approach

Polyhydroxybutyrate (PHB), a biodegradable biopolymer, represents a promising alternative to petroleum-based thermoplastics. However, despite consistent market growth, PHB faces persistent commercialization challenges that limit widespread adoption. Existing research has focused predominantly on optimizing PHB production processes, leaving a critical gap in understanding which material property modifications would most effectively enhance market competitiveness. This study addresses this gap by systematically analyzing the relationship between polymer material properties and market performance using U.S. market data from 2008 to 2021 for 21 thermoplastic polymers across 19 material properties. We employed principal component regression to identify property modifications that could maximize market volume while reducing CO 2 emissions. Our parametric analysis revealed that two specific material properties – Hardness Shore A and Sheet Extrusion Temperature – significantly influence PHB marketability across different price points. Market simulations demonstrated that a 10% increase in Hardness Shore A could increase PHB market volume by 431.5 million kg while reducing emissions by 188.7 kg CO 2 . A similar 10% increase to Sheet Extrusion Temperature could yield a 297.5 million kg volume increase and a 99.2 kg CO 2 reduction in emissions. Critically, this approach is agnostic to the specific methods required to achieve these property changes, instead providing material scientists with quantitative, data-driven targets for R&D prioritization. Here, this framework offers a novel methodology for evaluating biopolymer competitiveness and supporting strategic decisions to accelerate PHB market adoption and contribute to decarbonization of the plastics industry.

09 BIOMASS FUELS↗

DOE OSTI2023

First-principles-derived transport properties of Molten chloride salts

Molten salts have many applications ranging from a heat transfer medium in both generation IV nuclear reactor designs and the solar industry to thermal storage systems. While molten salts show promising properties for these applications, there still exists a knowledge gap for the transport properties of molten salts at elevated temperatures. This work uses ab initio Molecular Dynamics to investigate the transport properties of KCl, LiCl, KCl-LiCl eutectic, NaCl, MgCl 2 , and NaCl-MgCl 2 eutectic molten salt systems. Further, the properties presented here are the diffusion coefficient, viscosity, and isochoric heat capacity. These properties are compared to experimental data where available and other computational work in cases where no experimental data is available. This is the first work to explore timescales over 100 ps via AIMD for the determination of transport properties in molten salts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Modeling the interfacial failure and resulting mechanical properties of z-pinned additively manufactured composites

The mechanical properties of Fused Filament Fabrication (FFF) parts are limited in the build direction, albeit advantages such as design flexibility and in-house customization. Here, in this paper, a novel z-pinning approach that enhances mechanical properties in the build direction by depositing material across multiple layers within the part was investigated through numerical simulations and validated experimentally. A finite element model for z-pinned composite structures was developed by assigning fiber-orientation dependent material properties obtained using a micromechanics approach to beads and pins. The bead-to-bead and pin-to-pin adhesions within the z-pinned structures were modeled using a cohesive traction separation law. The properties of cohesive elements for carbon fiber-reinforced polylactic acid (CF-PLA) z-pinned composites were calibrated using tensile experiments. The elastic modulus and tensile strength of CF-PLA z-pinned composites in the build direction were predicted with the developed numerical model. The numerical investigation on various geometrical parameters revealed that the largest pin volume increases the stiffness and tensile strength by 40% and thus, has the greatest influence on the mechanical properties of the z-pinned composites. The effect of z-pin geometrical parameters on the mechanical properties was summarized to aid in the design of z-pinned additively manufactured composite structures.

36 MATERIALS SCIENCE↗

DOE OSTI2022

In-plane and through-plane dielectric properties of graphene oxide membrane: Effect of Al 3 + modification

A graphene oxide (GO) membrane can be used in structural dielectric capacitors and planar micro-supercapacitors as a dielectric separator material due to its excellent through-plane and in-plane dielectric properties. The ability to tailor the dielectric properties of the GO membrane is crucial for dielectric applications. We believe this to be the first demonstration describing how Al 3+ ions impact the dielectric properties of the GO membrane through cation to oxygenated functional groups interactions. In this work, the Al 3+ -modification to the GO membrane was realized through a facile pre-coordination method followed by layer-by-layer assembling. The influence of Al 3+ on the GO membranes’ through-plane and in-plane dielectric properties (dielectric constant and dielectric loss) was investigated in the frequency range from 0.01 Hz to 10 5 Hz. Plane-to-plane and edge-to-edge Al 3+ coordination with the functional group on the basal plane or edge of the GO sheets was proposed to understand the metal ion's impact on the dielectric properties. The results demonstrated that the Al 3+ modification was an effective strategy to tailoring the GO membranes’ dielectric properties in a low frequency regime and further suggested the possibility of designing dielectric GO membranes with controllable dielectric performance. At a low frequency range (0.01–1 Hz), the addition of Al 3+ increased the through-plane dielectric constant and decreased the in-plane dielectric constant. In terms of dielectric loss, unmodified GO membranes exhibited a higher in-plane dielectric loss than the through-plane dielectric loss. Al 3+ -modified GO membranes exhibited increased through-plane dielectric loss and decreased in-plane dielectric loss compared to the unmodified GO membranes.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Influence of living grass Roots and endophytic fungal hyphae on soil hydraulic properties

Soil hydraulic properties are often estimated based on laboratory data or pedotransfer functions dependent on soil physical properties, which often do not consider potential impacts of soil roots or fungal hyphae. Here, we first review current knowledge of how these soil biotic components affect hydraulic properties, then we conducted laboratory experiments to specifically test if the presence of roots and mycorrhizal fungi had a significant effect on the hydraulic properties of two soils with contrasting textures: Flint sand and Hamblen silt loam. Soil cores were seeded with (Panicum virgatum) and grown in a greenhouse over three separate growth periods. The endophytic fungus Serendipita indica was injected as liquid inoculant into designated mycorrhizal cores. Saturated hydraulic conductivity (K sat ) measurements were made with a constant head permeameter, and soil water retention curves were obtained by the evaporation method, supplemented at the dry end for Hamblen silt loam with water activity meter data. Retention curve parameters were obtained by fitting the van Genuchten equation to the resulting measurements. Mean root volume ratios were higher in the mycorrhizal inoculated treatment than in the uninoculated treatment for both soils. For Flint sand, analysis of variance revealed that K sat was reduced by the presence of roots as compared to bare soil. This was likely due to roots clogging soil pores. Results also indicated the presence of roots changed the shape of the water retention curve for Flint sand by increasing water content at saturation and by reducing the slope of the curve. These changes suggested roots created additional porosity and broadened the pore-size distribution. The presence of mycorrhizal fungi accentuated the root effects. The influence of roots and mycorrhizal fungi on hydraulic properties was less obvious for the Hamblen silt loam, as none of the treatments differed from each other at p < 0.05. The results highlight the necessity to consider the impact of root and fungal structures on models of soil hydraulic properties.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Target Configuration Effect on Microstructures and Properties of Vertically Aligned Nanocomposites

Vertically aligned nanocomposites (VANs) are unique thin films with vertical nanostructures embedded in a matrix material, allowing for the integration of two distinct materials. These nanocomposites offer novel combined physical properties, such as nanocomposite-based multiferroics and strongly coupled physical properties, such as magneto-optic coupling. Much work has been conducted in exploring different two-phase combinations and various processing conditions to achieve novel tunable properties that cannot be obtained by any single-phase material alone. Here, in this work, the target configuration effects are explored for the growth of LaFeO 3 –CoNi 2 O 4 VANs. Both mixed and pie-shaped targets are utilized to compare the target configuration effects on the phase separation, morphology tuning, and their resulting physical properties, including optical and magnetic properties. This work suggests that the target configuration is another important parameter for achieving the desired VAN morphology and can be used to design different two-phase VANs with tailorable properties.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Photophysical Properties and Electronic Structure of Hydroporphyrin Dyads Exhibiting Strong Through-Space and Through-Bond Electronic Interactions

Electronic interactions between tetrapyrroles are utilized in natural photosynthetic systems to tune the light-harvesting and energy/charge-transfer processes in these assemblies. Such interactions also can be employed to tailor the electronic properties of tetrapyrrolic dyads and larger arrays for use in materials science and biomedical research. Here we have utilized static and time-resolved optical spectroscopy to characterize the optical absorption and emission properties of a set of chlorin and bacteriochlorin dyads with varied degrees of through-bond (TB) and through-space (TS) interactions between the constituent macrocycles. The dyads consist of two chlorins or two bacteriochlorins joined by a linker that utilizes a triple-double-triple bond (enediyne) motif in which the double bond portion is a ester-substituted ethylene or o-phenylene unit. The photophysical studies are coupled with density functional theory (DFT) calculations to probe the ground-state molecular orbital (MO) characteristics of the dyads and time-dependent calculations (TDDFT) to elucidate excited-state properties. The latter include electronic characteristics of the singlet excited state manifold and the absorption transitions to these states from the electronic ground state. Comparison of the MO and calculated spectral properties of each dyad with the linker present versus disrupted (by eliminating the double-bond portion) gives insight into the relative contributions of TB versus TS interactions to the electronic properties of the dyads. The results show that the TB and TS contributions are additive (constructively interfere), which is not always the case for molecular dyads. Most of the dyads have shorter lifetimes of the lowest singlet excited state compared to the parent monomer, which derives from increased S 1 → S 0 internal conversion. The enhancement is greater for the dyads in benzonitrile than in toluene. Furthermore, the studies provide insights into the nature of the electronic interactions between the constituents in the tetrapyrrole arrays and how these interactions dictate the spectral properties and excited-state decay characteristics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Analysis of the Amorphous and Interphase Influence of Comononomer Loading on Polymer Properties toward Forwarding Bioadvantaged Copolyamides

In this paper we present an approach for selectively modifying the properties of semicrystalline polymers by introducing “bioadvantaged” counits. With this approach, the unique functionality of biomass can be leveraged to tailor the properties of the amorphous phase of semicrystalline polymers with minimal impact on crystallinity and thermomechanical properties. As a model case, PA 6,6 copolyamides were produced using the bioadvantaged monomer trans-3-hexenedioic acid (t3HDA). The analogous structure of t3HDA to adipic acid, a PA 6,6 monomer, allows for seamless integration. Screening over the entire composition range identified the t3HDA loading (20 mol%) beyond which properties deviate appreciably from Nylon 6,6. Once identified, copolyamides of suitable compositions were upgraded to commercial quality and fully characterized to assess the influence of counit loading and polymer structure on thermal and mechanical properties. Samples were characterized using gel permeation chromatography (GPC), proton nuclear magnetic resonance spectroscopy (1H NMR), heteronuclear single quantum coherence spectroscopy (HSQC), wide-angle X-ray scattering (WAXS), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), dynamic mechanical analysis (DMA), tensile testing, flexural testing, and water absorption testing. t3HDA units were shown to hydrate during the harsh polycondensation to 3-hydroxyhexanedioic acid (3HHDA) and fully incorporate into the polymer backbone. Loading levels up to 20% were shown to have comparable thermal and mechanical properties in the dry state, yet moisture absorption—a known method for improving the toughness, yield strain, and elongation of polyamides—was enhanced by over 100% at 20% loading. This case study on bioadvantaged copolymers elucidates the governing structure-function principles that can be leveraged to forward value-added renewable polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Critical Assessment of Electronic Structure Descriptors for Predicting Perovskite Catalytic Properties

The discovery and design of materials which can efficiently catalyze the oxygen reduction and evolution reactions at reduced temperatures is important for facilitating the widespread adoption of fuel cell and electrolyzer technologies. Numerous studies have produced correlations between catalytic properties, such as oxygen surface exchange or electrode area specific resistance (ASR), and properties of the catalyst material. However, correlations have historically been limited in scope (e.g., using only a few materials or at a single temperature) and it has been difficult to provide detailed assessments of their robustness. Here, in this study, we assess the ability of the O p-band center electronic structure descriptor, obtained from density functional theory (DFT) calculations, to correlate with oxygen surface exchange rates, diffusivities, and area specific resistances for a large database of perovskite oxide catalytic properties. By data mining the literature, we obtain 747 catalytic property value data points spanning 299 unique perovskite compositions from 313 studies. We assess linear correlations of each property with the O p-band center and find generally modest correlations that are qualitatively useful (prediction mean absolute errors of about 0.5 log units are typical), where the correlations are improved at higher temperatures (e.g., 800 °C vs. 500 °C) and significantly improve when considering fits to the subset of materials which have multiple independent measurements. These findings suggest that the spread of property data is significantly influenced by experimental uncertainty, and subsequent measurements of additional materials will likely improve the O p-band center correlations.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2025

Leveraging Natural Language Processing and Generative Models in Molecular Chemistry: Property Prediction and Novel Compound Generation

The accurate prediction of molecular properties is important for the rational design and the advancement of green chemistry and sustainable materials research. However, the predictive power of traditional computational chemistry methods is limited due to computational restrictions. Here, in this study, we examine an alternative approach to the accurate prediction of properties of organic compounds: natural language processing (NLP)-based molecular embedding. Using viscosity, partition coefficient (log P), and enthalpy of vaporization as test properties through a survey of comprehensive datasets comprising 5695 data points for viscosity, 25 870 data points for log P, and 2296 data points for enthalpy of vaporization. These are important properties for the design of greener, safer, and sustainable chemical processes. Models were trained using NLP methods such as Mol2vec and fine-tuned ChemBERTa, and results were compared with traditional input featurization techniques such as Morgan fingerprints and quantum chemistry derived sigma profiles and DFT features. Among the various machine learning models, Mol2vec demonstrated superior predictive capabilities, achieving the highest correlation coefficient (R 2 = 0.945) and lowest RMSE (0.106 mPa s) for viscosity, as well as high accuracy for log P and enthalpy of vaporization predictions. These findings establish the Mol2vec featurization technique, graph-convolutional neural networks (GCNN), and fine-tuned ChemBERTa model as powerful tools for predictive modeling of organic compounds properties, offering a significant improvement over previously used featurization techniques and opening up strategies for very-high-throughput computational screening. Finally, we integrated ML models with hybrid language-model-based generative adversarial networks (LM-GAN) to generate novel molecular sequences with desirable properties for different research applications. The ability to computationally design solvents with lower viscosity, lower log P, and lower enthalpy of vaporization offers a data-driven route to accelerating the discovery of sustainable alternatives to traditionally toxic solvents.

ChemBERTa↗

DOE OSTI2020

Evolution of Elastic and Mechanical Properties During Fault Shear: The Roles of Clay Content, Fabric Development, and Porosity

Phyllosilicates weaken faults due to the formation of shear fabrics. Although the impacts of clay abundance and fabric on frictional strength, sliding stability, and porosity of faults are well studied, their influence on elastic properties is less known, though they are key factors for fault stiffness. We document the role that fabric and consolidation play in elastic properties and show that smectite content is the most important factor determining whether fabric or porosity controls the elastic response of faults. We conducted a suite of shear experiments on synthetic smectite-quartz fault gouges (10–100 wt% smectite) and sediment incoming to the Sumatra subduction zone. We monitored Vp, Vs, friction, porosity, shear and bulk moduli. We find that mechanical and elastic properties for gouges with abundant smectite are almost entirely controlled by fabric formation (decreasing mechanical and elastic properties with shear). Though fabrics control the elastic response of smectite-poor gouges over intermediate shear strains, porosity is the primary control throughout the majority of shearing. Elastic properties vary systematically with smectite content: High smectite gouges have values of Vp ~ 1,300–1,800 m/s, Vs ~ 900–1,100 m/s, K ~ 1–4 GPa, and G ~ 1–2 GPa, and low smectite gouges have values of Vp ~ 2,300–2,500 m/s, Vs ~ 1,200–1,300 m/s, K ~ 5–8 GPa, and G ~ 2.5–3 GPa. We find that, even in smectite-poor gouges, shear fabric also affects stiffness and elastic moduli, implying that while smectite abundance plays a clear role in controlling gouge properties, other fine-grained and platy clay minerals may produce similar behavior through their control on the development of fabrics and thin shear surfaces.

58 GEOSCIENCES↗

DOE OSTI2025

A Machine Learning Framework for Predicting Microphysical Properties of Ice Crystals From Cloud Particle Imagery

The microphysical properties of ice crystals are important because they significantly alter the radiative properties and spatiotemporal distributions of clouds, which in turn strongly affect Earth's climate. However, it is challenging to measure key properties of ice crystals, such as mass or morphological features. Here, we present a proof-of-concept framework for predicting three-dimensional (3D) microphysical properties of ice crystals from in situ two-dimensional (2D) imagery. First, we computationally generated synthetic ice crystals using 3D modeling software along with geometric parameters estimated from the 2021 Ice Cryo-Encapsulation Balloon (ICEBall) field campaign. Then, we used synthetic crystals to train machine learning (ML) models to predict effective density ($ρ_e$), effective surface area ($A_e$), and number of bullets ($N_b$) from synthetic rosette imagery. On unseen synthetic images, our ML models accurately predicted ice crystal properties. ResNet-18 performed best, achieving $R^2$ values of 0.99 and 0.98 for $ρ_e$ and $A_e$, respectively, and MAE of 0.10 for mathematical equation in single view tasks. Stereo view ResNet-18 further reduced RMSE by 40% for $ρ_e$ and $A_e$ and reduced MAE by 0.08 for $N_b$. This work provides a novel ML-driven framework for estimating ice microphysical properties from in situ imagery, which will allow for downstream constraints on microphysical parameterizations, such as the mass-size relationship.

Ko, J. [Columbia Univ., New York, NY (United State↗

DOE OSTI2021

Structural and physical properties of 99 complex bulk chalcogenides crystals using first-principles calculations

Chalcogenide semiconductors and glasses have many applications in the civil and military fields, especially in relation to their electronic, optical and mechanical properties for energy conversion and in enviormental materials. However, they are much less systemically studied and their fundamental physical properties for a large class chalcogenide semiconductors are rather scattered and incomplete. Here, we present a detailed study using well defined first-principles calculations on the electronic structure, interatomic bonding, optical, and mechanical properties for 99 bulk chalcogenides including thirteen of these crytals which have never been calculated. Due to their unique composition and structures, these 99 bulk chalcogenides are divided into two main groups. The first group contains 54 quaternary crystals with the structure composition (A2BCQ4) (A = Ag, Cu; B = Zn, Cd, Hg, Mg, Sr, Ba; C = Si, Ge, Sn; Q = S, Se, Te), while the second group contains scattered ternary and quaternary chalcogenide crystals with a more diverse composition (AxByCzQn) (A = Ag, Cu, Ba, Cs, Li, Tl, K, Lu, Sr; B = Zn, Cd, Hg, Al, Ga, In, P, As, La, Lu, Pb, Cu, Ag; C = Si, Ge, Sn, As, Sb, Bi, Zr, Hf, Ga, In; Q = S, Se, Te; x=1, 2, 3; y=0, 1, 2, 5; z=0, 1, 2 and n=3, 4, 5, 6, 9). Moreover, the total bond order density (TBOD) is used as a single quantum mechanical metric to characterize the internal cohesion of these crystals enabling us to correlate them with the calculated properties, especially their mechanical properties. This work provides a very large database for bulk chalcogenides crucial for the future theoretical and experimental studies, opening opportunities for study the properties and potential application of a wide variety of chalcogenides.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Microphysical properties of atmospheric soot and organic particles: measurements, modeling, and impacts

Atmospheric soot and organic particles from fossil fuel combustion and biomass burning modify Earth’s climate through their interactions with solar radiation and through modifications of cloud properties by acting as cloud condensation nuclei and ice nucleating particles. Recent advancements in understanding their individual properties and microscopic composition have led to heightened interest in their microphysical properties. This review article provides an overview of current advanced microscopic measurements and offers insights into future avenues for studying microphysical properties of these particles. To quantify soot morphology and ageing, fractal dimension ( D f ) is a commonly employed quantitative metric which allows to characterize morphologies of soot aggregates and their modifications in relation to ageing factors like internal mixing state, core-shell structures, phase, and composition heterogeneity. Models have been developed to incorporate D f and mixing diversity metrics of aged soot particles, enabling quantitative assessment of their optical absorption and radiative forcing effects. The microphysical properties of soot and organic particles are complex and they are influenced by particle sources, ageing process, and meteorological conditions. Furthermore, soluble organic particles exhibit diverse forms and can engage in liquid–liquid phase separation with sulfate and nitrate components. Primary carbonaceous particles such as tar balls and soot warrant further attention due to their strong light absorbing properties, presence of toxic organic constituents, and small size, which can impact human health. Future research needs include both atmospheric measurements and modeling approaches, focusing on changes in the mixing structures of soot and organic particle ensembles, their effects on climate dynamics and human health.

54 ENVIRONMENTAL SCIENCES↗