Search NASA⌕ Search

SEARCH · Search NASA

Results for “Physicochemical properties”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Probing degradation at solid-state battery interfaces using machine-learning interatomic potential

Solid-state batteries featuring fast ion-conducting solid electrolytes are promising next-generation energy storage technologies, yet challenges remain for practical deployment due to electro-chemo-mechanical instabilities at solid-solid interfaces. These interfaces, which include homogeneous/internal interfaces such as grain boundaries (GBs) and heterogeneous/external interfaces between solid-electrolyte and electrode materials, can impede Li-ion transport, deteriorate performance, and eventually lead to cell failure. Here, in this study, we leverage large-scale molecular simulations, enabled by validated machine-learning interatomic potentials, to directly probe the onset of interfacial degradation at the garnet Li 7 La 3 Zr 2 O 12 (LLZO) solid-electrolyte/LiCoO 2 (LCO) cathode interface. By surveying different interfacial geometries and compositions, it is found that Li-deficient interfaces can lead to severe interfacial disordering with cation mixing and Co interdiffusion from LCO into LLZO. By contrast, Li-sufficient interfaces are less disordered, although elemental segregation with local ordering is observed. As a consequence of Co interdiffusion, Co-rich regions are formed at the GBs of LLZO due to cation segregation and trapping effects. This behavior is independent of the GB tilting axis, degree of disorder at the GBs, and Co concentration, which implies Co clustering at GBs is a general phenomenon in polycrystalline LLZO and can dictate its overall transport and mechanical properties. Our findings elucidate the underlying fundamental mechanisms that give rise to experimentally observed physicochemical properties and provide guidelines for interface design that can mitigate interfacial degradation and improve cycling performance.

25 ENERGY STORAGE↗
DOE OSTI2020

Structural Anomalies and Electronic Properties of an Ionic Liquid under Nanoscale Confinement

Ionic liquids (ILs) promise far greater electrochemical performance compared to aqueous systems, yet key physicochemical properties governing their assembly at interfaces within commonly used graphitic nanopores remain poorly understood. Here, we combine synchrotron X-ray scattering with first-principles molecular dynamics simulations to unravel key structural characteristics of 1-alkyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([TFSI] – ) ionic liquids confined in carbon slit pores. X-ray scattering reveals selective pore filling due to size exclusion, while filled pores exhibit disruption in the IL intermolecular structure, the extent of which increases for narrower slit pores. First-principles simulations corroborate this finding and quantitatively describe how perturbations in the local IL structure, particularly the hydrogen-bond network, depend strongly on the degree of confinement. Despite significant deviations in structure under confinement, electrochemical stability remains intact, which is important for energy storage based on nanoporous carbon electrodes (e.g., supercapacitors).

36 MATERIALS SCIENCE↗
DOE OSTI2020

Surface functionality and formation mechanisms of carbon and graphene quantum dots

Graphene quantum dots (GQDs) and Carbon dots (C-dots) have been widely studied in recent years due to their structural and optoelectrical properties. These properties have prompted the exploration of the role of these carbon-based materials in many potential applications. This includes solar cells, photodetectors, bioimaging, sensors, batteries and drug delivery. These properties and applications of GQDs and C-dots are highly dependent on their size, shape and surface functionality. In this work, GQDs and C-dots mixtures have been synthesized by an inexpensive wet chemical method by varying the synthesis temperature from 85°, 100° to 115 °C. The surface functionalities of the synthesized carbon-based materials were investigated by several analytical methods. We discovered a higher degree of oxidation at higher temperatures. The mechanism of formation of different sized GQDs and C-dots with different functionalities have been explained with the help of XPS and NEXAFS analysis. The influence of size and surface functionalities on the optical properties of these nanomaterials is analyzed by UV–Vis and PL spectroscopic techniques. Furthermore, this study demonstrates that physicochemical properties of GQDs and C-dots can be controlled by changing the synthesis temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Molecular property prediction for very large databases with natural language processing: a case study in ionic liquid design

The prospect of using artificial intelligence (AI) to accurately screen very large databases of compounds for multiple properties has yet to be realized. Here, we explore this possibility using ionic liquids (ILs) which offer unique physicochemical properties and excellent tunability, making them highly versatile solvents for various research applications. Screening millions of potential ILs for the best perfomance for use in specific tasks with experimental methods alone however, is impractical. Further, traditional’ physics-based computational chemistry is hindered by high computational cost. To address this challenge, we leverage a natural language processing (NLP)-based molecular embedding technique with advanced machine learning (ML) models to predict seven key IL properties: viscosity, density, ionic conductivity, surface tension, melting temperature, toxicity, and water solubility. Comprehensive datasets for these properties are obtained, then NLP featurization with Mol2vec is compared with other featurization techniques such as 2D Morgan fingerprints, and 3D quantum chemistry-derived sigma profiles. NLP-based featurization exhibited the best predictive performance, achieving the highest R 2 and lowest RMSE values for all the studied IL properties. Further, we present case studies of how ILs might be screened using combined property criteria for practical cases – lignocellulosic biomass processing, CO 2 capture, and optimal electrolytes for batteries – screening a novel database of ∼10.6 million generated feasible ILs. The results introduce NLP as a powerful tool for engineering many designer solvents with desirable properties for task specific applications.

Mohan, Mood [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2021

Comparative Studies of the Structural and Transport Properties of Molten Salt FLiNaK Using the Machine-Learned Neural Network and Reparametrized Classical Forcefields

Despite surging interest in molten salt reactors and thermal storage systems, knowledge of the physicochemical properties of molten salts are still inadequate due to demanding experiments that require high temperature, impurity control, and corrosion mitigation. Therefore, the ability to predict these properties for molten salts from first-principles computations is urgently needed. Herein, we developed and compared a machine-learned neural network force field (NNFF) and a reparametrized rigid ion model (RIM) for a prototypical molten salt LiF–NaF–KF (FLiNaK). We found that NNFF was able to reproduce both the structural and transport properties of the molten salt with first-principles accuracy and classical-MD computational efficiency. Furthermore, the correlation between the local atomic structures and the dynamics was identified by comparing with RIMs, suggesting the significance of polarization of anions implicitly embedded in the NNFF. Furthermore, this work demonstrated a computational framework that can facilitate the screening of molten salts with different chemical compositions, impurities, and additives, and at different thermodynamic conditions suitable for the next-generation nuclear reactors and thermal energy storage facilities.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Preparation of illite coated geomaterial microfluidic surfaces: Effect of salinity and heat treatment

Unique characteristics of clay (e.g., high surface area, deficiency in positive charges) make any clay abundant shales a good source of adsorbed gas. However, the presence of clay in porous media can also affect shale rock's producibility. The clay-water interaction can cause significant swelling and fines migration in the formation and impair the overall hydrocarbon recovery from shale. Geomaterial micromodels, developed by functionalizing traditional glass or PDMS surfaces with geomaterials (e.g., calcite, Quartz, clay), can represent the physicochemical properties of the natural porous media and have been used during the last few years to understand and evaluate the solid-fluid physicochemical interactions. Here, this study focuses on developing a clay-coated geomaterial surface and investigates the effect of base fluid's salinity on clay adsorption to the glass surface. Glass capillary tubes and straight channel borosilicate glass micromodels are coated with Illite clay to represent the pore-scale clay chemistry of Caney Shale, a Mississippian unconventional play in Southern Oklahoma, USA. 10 wt% of Illite clay slurries made with brines of four different salinities are used to coat the glass-capillary tubes to understand the effect of salinity in clay adsorption on the glass surface and overall coating quality. To achieve a stable coating and evaluate the impact of heat treatment on coating's stability, straight channel glass flow cells coated with Illite clay are heat-treated at low (25 °C) and high temperature (125 °C), and the results are compared with an untreated coated surface. Flooding tests were carried out with brines of different salinities on the coated surface to evaluate the stability of the coating. The experimental results indicated a strong relationship between the brine's salinity and the adsorption of clay particles on the glass surface. An increase in brine concentration resulted in improved adsorption of clay particles on the glass surface. Experiments involving heat treating the glass surface following the coating demonstrated significant improvement in the stability of the coating.

02 PETROLEUM↗
DOE OSTI2020

Chemical and Structural Changes in Corn Stover After Ensiling: Influence on Bioconversion

Production of biofuels, bioproducts, and bioenergy requires a well-characterized, stable, and reasonably uniform biomass supply and well-established supply chains for shipping biomass from farm fields to biorefineries, while achieving year-round production targets. Preserving and stabilizing biomass feedstock during storage is a necessity for cost-effective and sustainable biofuel production. Ensiling is a common storage method used to preserve and even improve forage quality; however, the impact of ensiling on biomass physical and chemical properties that influence bioconversion processes has been variable. Our objective in this work was to determine the effects of ensiling on lignocellulosic feedstock physicochemical properties and how that influences bioconversion requirements. We observed statistically significant decreases (p < 0.05) in the content of two major structural carbohydrates (glucan and xylan) of 5 and 8%, respectively, between the ensiled and non-ensiled materials. We were unable to detect differences in sugar yields from structural carbohydrates after pretreatment and enzymatic hydrolysis of the ensiled materials compared to non-ensiled controls. Based on this work, we conclude that ensiling the corn stover did not change the bioconversion requirements compared to the control samples and incurred losses of structural carbohydrates. At the light microscopy level, ensiled corn stover exhibited little structural change or relocation of cell wall components as detected by immunocytochemistry. However, more subtle structural changes were revealed by electron microscopy, as ensiled cell walls exhibit ultrastructural characteristics such as wall delimitation intermediate between non-ensiled and dilute-acid-pretreated cell walls. These findings suggest that alternative methods of conversion, such as deacetylation and mechanical refining, could take advantage of lamellar defects and may be more effective than dilute acid or hot water pretreatment for biomass conversion of ensiled materials.

09 BIOMASS FUELS↗
DOE OSTI2025

Unraveling the solvation phenomena of Ln 3+ cations in room-temperature ionic liquids: A computational study

Rare-earth elements (REEs), classified as critical materials, are difficult to separate due to their similar chemical properties and slight differences in ionic radius. Room-temperature ionic liquids (RTILs) have gained significant attention for REE separation because of their unique physicochemical properties and environmental advantages. In this study, we have investigated the solvation mechanisms of two RE cations (Ln 3+ ), Nd 3+ (light REE) and Yb 3+ (heavy REE), in two 1-butyl-3-methylimidazolium ([BMIM] + )-based RTILs using bis(trifluoromethylsulfonyl)imide ([NTf 2 ] − ) and acetate ([OAc] − ) as the respective anions, employing classical molecular dynamics (MD) simulations and density functional theory (DFT) techniques. From MD simulations, it is evident that Ln 3+ cations are primarily solvated by RTIL anions in the first solvation shell, while [BMIM] + cations form the second solvation shell with their numbers depending on the size and composition of the first solvation shell. The neutralizing [NO 3 − ] counterions are mainly solvated by [BMIM] + cations in their first solvation shell. Relative free energy change of solvation calculations using thermodynamic integration (TI) method indicate that Yb 3+ is more strongly solvated than Nd 3+ in both RTILs, a trend further supported by DFT calculations. While both methods predict consistent qualitative behavior, differences in models and energy evaluations lead to variations in absolute values. Overall, this study provides a comprehensive understanding of the solvation behavior of Ln 3+ cations in RTILs, demonstrating a stronger solvation preference for the heavy Ln 3+ cation (Yb 3+ ). In conclusion, these findings have implications for the design of RTIL-based separation processes for REEs.

Ash, Tamalika [Ames Lab., and Iowa State Univ., Am↗
DOE OSTI2025

AquaMEND: Reconciling multiple impacts of salinization on soil carbon biogeochemistry

Soil salinization, exacerbated by climate change, poses a global threat to coastal ecosystem function and soil quality. Salinity influences carbon cycling through direct effects on microbial activity and indirect alterations to soil physicochemical properties including cation exchange, pH, and soil organic carbon availability. Current models inadequately represent these complexities, relying on linear reduction functions that overlook specific physicochemical changes induced by salinity. To address this gap, we propose an integrated model framework, AquaMEND, that combines microbial-explicit carbon decomposition and geochemical models. This model allows cation exchange and surface complexation processes to capture solute chemistry and nutrient availability in soils upon saltwater intrusion. Using response functions that capture salinity impacts on both salt-sensitive and salt-resistant microbial processes, AquaMEND simulates how the abiotic and biotic mechanisms work individually and collectively to regulate organic and inorganic pools and fluxes. Here, the parallel structure of aqueous and non-aqueous phases, together with microbial functions, result in a versatile model for solving dynamic coupling of organics, minerals and microbes under various environmental settings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Elucidating lipid nanoparticle properties and structure through biophysical analyses

Designing lipid nanoparticle (LNP) delivery systems with specific targeting, potency and minimal side effects is crucial for their clinical use. However, traditional characterization methods, such as dynamic light scattering, cannot accurately quantify physicochemical properties of LNPs and how these are influenced by the lipid composition and mixing method. Here, we structurally characterize polydisperse LNP formulations by applying emerging solution-based biophysical methods that have higher resolution and provide biophysical data beyond size and polydispersity. These techniques include sedimentation velocity analytical ultracentrifugation, field-flow fractionation followed by multiangle light scattering and size-exclusion chromatography in line with synchrotron small-angle X-ray scattering. Here, we show that LNPs have intrinsic polydispersity in size, RNA loading and shape, which depend on both the formulation technique and the lipid composition. Lastly, we predict LNP transfection in vitro and in vivo by examining the relationship between mRNA translation and physicochemical characteristics. Solution-based biophysical methods will be essential for determining LNP structure–function relationships, facilitating the creation of new design rules for LNPs.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Small angle X-ray studies of short-range order in non-stoichiometric pseudoprotic ionic liquids: the influence of chemical structure

Mixtures of organic acids and amines have been studied extensively owing to their unusual physicochemical properties and applications as solvents for extraction. In equimolar ratios they represent pseudoprotic ionic liquids, and in other, “nonstoichiometric” ratios they display a range of odd physicochemical behaviors. We report the results of small-angle X-ray scattering studies of a series of such systems with a range of chemical structures chosen to explore the link between molecular geometry and the character of the emergent nanoscale local liquid structure. We find that while the details vary, structure can emerge even when the hydrogen-bonding character of the components is changed significantly, and the character of their hydrocarbon substituents is altered. The consistent emergence of local order in the face of varying chemical structures indicates that the process is robust. Furthermore, this implies that the emergence of such structure may in fact be far more common in liquid mixtures than is currently recognized, and a great many structures may be suitable for the synthesis of pseudoprotic ionic liquids.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Spectro-Microscopic Analysis of Soot Particle Composition and Source Attribution

Ambient soot particles significantly impact Earth’s radiative balance, human health, and atmospheric visibility. Their microstructural properties depend on formation and aging mechanisms, which vary by emission source and atmospheric processes. Hence, accurately identifying sources of soot enhances our understanding of their physicochemical properties and atmospheric implications. This study used a multi-modal approach to characterize and attribute sources of submicron soot particles collected in Israel during new particle formation events, biomass burning episodes, and background atmospheric conditions. Synchrotron-based X-ray microscopy was used to map soot (elemental carbon), organic carbon, and inorganic species. Implemented atomic force microscopy showed highly diverse phase states, with soot consistently exhibiting a solid-like phase. Automated µ-Raman analysis was subsequently performed on ~690 particles, identifying three soot classes based on spectral features corresponding to the "Defect" (D) and "Graphite" (G) bands of soot. We applied two-peak and five-peak fitting approaches to deconvolute the “Defect” peaks (D1, D2, D3, and D4) and G band from average Raman, revealing varying degrees of graphitic order. The degree of graphitic order was determined from metrics such as the D3 peak area, often observed when soot was internally mixed with organic material. Raman spectral features, along with temporal variations in particle classes contributions, suggest that Particle Type 1 corresponds to traffic related soot and Particle Type 2 to less graphitic soot from biomass burning, while Particle Type 3 is associated with more heterogeneous particulate representative of soot-OC mixtures emitted during new particle formation and biomass burning episodes.

Rivera-Adorno, Felipe (ORCID:0000000273557999)↗
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 OSTI2020

Microbially mediated iron redox cycling of subsurface sediments from Hanford Site, Washington State, USA

Iron-bearing clay minerals are predominant in soils and sediments, and they undergo oxidation-reduction cycles as a result of natural processes such as wetting/drying cycles and plant root respiration. However, the kinetics and mechanisms of multiple redox cycles of iron in clay-rich sediments and consequences of such cycling on sediment properties are poorly understood. The objective of this study was to understand how multiple redox cycles of Fe in clay-rich sediment affect the rate and extent of Fe bioreduction and the physicochemical properties of the sediment. A natural sediment sample containing Fe-bearing montmorillonite from Hanford, Washington, USA was size-fractionated [2.0 to 0.5 μm (Hanford-C) and 0.5 to 0.02 μm (Hanford-F)] and redox-cycled for four times. Bioreduction was achieved utilizing Geobacter sulfurreducens and re-oxidization was performed with sparged air. Time-course change of total Fe (II) was monitored to measure the rate and extent of Fe (III) bioreduction. Redox-cycled sediments were characterized to determine the physicochemical changes. Both the initial rate and extent of bioreduction fluctuated across the four redox cycles, but they ultimately decreased from 5.3 μmol g -1 h -1 and 22.9% to nearly zero by the fourth cycle. These fluctuation patterns were likely due to a combined effect of reductive dissolution of small/poorly crystalline clay particles (by 3–5%) and clay mineral structural changes, as evidenced by redox induced changes of aqueous chemistry, surface area, cation exchange capacity, mineralogy, and Mössbauer parameters. Once these small/poorly crystalline clay particles were dissolved, structural Fe in residual larger and more crystalline clay particles was largely reversible across additional redox cycles, as revealed by Mössbauer spectroscopy through the first three cycles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Measurement report: A comparison of ground-level ice-nucleating-particle abundance and aerosol properties during autumn at contrasting marine and terrestrial locations

Abstract. Ice-nucleating particles (INPs) are an essential class of aerosols found worldwide that have far-reaching but poorly quantified climate feedback mechanisms through interaction with clouds and impacts on precipitation. These particles can have highly variable physicochemical properties in the atmosphere, and it is crucial to continuously monitor their long-term concentration relative to total ambient aerosol populations at a wide variety of sites to comprehensively understand aerosol–cloud interactions in the atmosphere. Hence, our study applied an in situ forced expansion cooling device to measure ambient INP concentrations and test its automated continuous measurements at atmospheric observatories, where complementary aerosol instruments are heavily equipped. Using collocated aerosol size, number, and composition measurements from these sites, we analyzed the correlation between sources and abundance of INPs in different environments. Toward this aim, we have measured ground-level INP concentrations at two contrasting sites, one in the Southern Great Plains (SGP) region of the United States with a substantial terrestrially influenced aerosol population and one in the Eastern North Atlantic Ocean (ENA) region with a primarily marine-influenced aerosol population. These measurements examined INPs mainly formed through immersion freezing and were performed at a ≤ 12 min resolution and with a wide range of heterogeneous freezing temperatures (Ts above −31 °C) for at least 45 d at each site. The associated INP data analysis was conducted in a consistent manner. We also explored the additional offline characterization of ambient aerosol particle samples from both locations in comparison to in situ data. From our ENA data, on average, INP abundance ranges from ≈ 1 to ≈ 20 L−1 (−30 °C ≤ T ≤ −20 °C) during October–November 2020. Backward air mass trajectories reveal a strong marine influence at ENA with 75.7 % of air masses originating over the Atlantic Ocean and 96.6 % of air masses traveling over open water, but analysis of particle chemistry suggests an additional INP source besides maritime aerosols (e.g., sea spray aerosols) at ENA. In contrast, 90.8 % of air masses at the SGP location originated from the North American continent, and 96.1 % of the time, these air masses traveled over land. As a result, organic-rich SGP aerosols from terrestrial sources exhibited notably high INP abundance from ≈ 1 to ≈ 100 L−1 (−30 °C ≤ T ≤ −15 °C) during October–November 2019. The probability density function of aerosol surface area-scaled immersion freezing efficiency (ice nucleation active surface site density; ns) was assessed for selected freezing temperatures. While the INP concentrations measured at SGP are higher than those of ENA, the ns(T) values of SGP (≈ 105 to ≈ 107 m−2 for −30 °C ≤ T ≤ −15 °C) are reciprocally lower than ENA for approximately 2 orders of magnitude (≈ 107 to ≈ 109 m−2 for −30 °C ≤ T ≤ −15 °C). The observed difference in ns(T) mainly stems from varied available aerosol surface areas, Saer, from two sites (Saer,SGP > Saer,ENA). INP parameterizations were developed as a function of examined freezing temperatures from SGP and ENA for our study periods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Direct non-oxidative methane coupling on vitreous silica supported iron catalysts

Direct non-oxidative methane coupling (NMC) is one of the promising pathways for methane upgrading into value-added olefin and aromatic hydrocarbons. The silica-supported iron (i.e., Fe/SiO 2 ) catalyst has been reported effective for NMC, but the effects of silica support on the catalyst property and NMC performance have rarely been explored. Here, in this work, we prepared a vitreous silica-supported iron (Fe/SiO 2 -V) catalyst by flame fusion of a mixture of quartz silica and fayalite. The physicochemical properties and NMC performance of the as-prepared catalysts were measured. Compared to crystalline cristobalite support in Fe/SiO 2 catalyst that has been studied previously, vitreous silica support has disordered Si-O bonds and structural defects, enabling better iron dispersion and more vital metal-support interaction. The as-prepared Fe/SiO 2 -V catalyst had a shorter induction period in methane activation and lower coke yield in NMC. The increase in iron concentration in Fe/SiO 2 -V catalysts elongated the catalyst induction period and promoted aromatics and coke formation. The coke type of the spent Fe/SiO 2 -V catalyst is more uniform than the cristobalite-supported iron catalyst.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗