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At least 235 records · Page 13

Machine Learning Interatomic Potentials for Modeling Framework Flexibility and Water Uptake in NbOFFIVE-1-Ni Metal–Organic Framework

Metal–organic frameworks (MOFs), with their distinctive porous structures and tunable chemical properties, have shown immense promise in the separation and storage of gases. Currently, the accurate simulation of their adsorptive properties remains challenging, especially for systems where the molecules fit very tightly into the pores. Traditional simulation methods often approximate the frameworks as rigid and do not account for the framework flexibility seen in materials such as NbOFFIVE-1-Ni. First-principles molecular dynamics (FPMD) simulations offer the desired accuracy in modeling this flexibility but are limited by their extensive computational demands, rendering them impractical for long simulations. Conversely, classical force field-based simulations offer computational efficiency but lack the necessary accuracy. Here, to break this accuracy-efficiency trade-off, we have developed machine learning interatomic potentials trained on energies and forces from FPMD to model the framework flexibility of NbOFFIVE-1-Ni in the presence of water over nanosecond time scales. Furthermore, by integrating MLIP-driven molecular dynamics (MLIP-MD) with grand canonical Monte Carlo (GCMC) simulations, we further incorporated framework flexibility into adsorption predictions, yielding water adsorption isotherms that better align with experimental data compared to those of conventional GCMC simulations. These advances offer new opportunities for the design and optimization of MOFs in gas storage and separation applications.

adsorption↗

Surface oxygen exchange kinetics of mixed conducting oxides: Dilatometric vs electrical conductivity relaxation study

The surface oxygen exchange kinetics of mixed ionic-electronic conducting (MIEC) oxides play a crucial role in a variety of applications, including solid oxide fuel/electrolysis cells (SOFCs/SOECs), permeation membranes and sensors. To date, a variety of methods, including isotope exchange, electrical conductivity, optical absorptivity and thermogravimetry relaxation, and impedance spectroscopy have been used to measure the oxygen exchange coefficient of MIEC oxides. Each of these methods have their advantages and limitations, depending on the physical and chemical properties of the investigated materials and their sample dimensions and densities. Here, we demonstrate the ability to precisely measure the surface oxygen exchange coefficient (k chem ) of MIEC model material Pr 0.1 Ce 0.9 O 2-δ (PCO) by use of dilatometric relaxation measurements, particularly of interest for materials that exhibit larger chemical expansion coefficients. This is achieved by use of porous bulk specimens to ensure that the contribution of oxygen exchange to the overall kinetics is dominant. We demonstrate that k chem values extracted from chemical expansion relaxation measurements on PCO are nearly identical to those derived from electrical conductivity relaxation measurements. As a result, this provides the opportunity to precisely investigate the oxygen exchange and chemical expansion kinetics of a wide range of materials used in high-temperature applications, particularly where more conventional methods are difficult or inappropriate to apply.

(Pr,Ce)O2-x↗

Understanding the interplay between pilot fuel mixing and auto-ignition chemistry in hydrogen-enriched environment

The diesel-piloted dual-fuel compression ignition combustion strategy is well-suited to accelerate the decarbonization of transportation by adopting hydrogen as a renewable energy carrier into the existing internal combustion engine with minimal engine modifications. Despite the simplicity of engine modification, many questions remain unanswered regarding the optimal pilot injection strategy for reliable ignition with minimum pilot fuel consumption. The present study uses a single-cylinder heavy-duty optical engine to explore the phenomenology and underlying mechanisms governing the pilot fuel ignition and the subsequent combustion of a premixed hydrogen-air charge. The engine is operated in a dual-fuel mode with hydrogen premixed into the engine intake charge with a direct pilot injection of n-heptane as a diesel pilot fuel surrogate. Optical diagnostics used to visualize in-cylinder combustion phenomena include high-speed IR imaging of the pilot fuel spray evolution as well as high-speed HCHO* and OH* chemiluminescence as indicators of low-temperature and high-temperature heat release, respectively. Three pilot injection strategies are compared to explore the effects of pilot fuel mass, injection pressure, and injection duration on the probability and repeatability of successful ignition. The thermodynamic and imaging data analysis supported by zero-dimensional chemical kinetics simulations revealed a complex interplay between the physical and chemical processes governing the pilot fuel ignition process in a hydrogen containing charge. Hydrogen strongly inhibits the ignition of pilot fuel mixtures and therefore requires longer injection duration to create zones with sufficiently high pilot fuel concentration for successful ignition. Results show that ignition typically tends to rely on stochastic pockets with high pilot fuel concentration, which results in poor repeatability of combustion and frequent misfiring. In conclusion, this work has improved the understanding on how the unique chemical properties of hydrogen pose a challenge for maximization of hydrogen’s energy share in hydrogen dual-fuel engines and highlights a potential mitigation pathway.

33 ADVANCED PROPULSION SYSTEMS↗

Enhanced polymorph metastability drives glycine nucleation in aqueous salt solutions

Crystal nucleation from aqueous solutions influences countless geological, biochemical, astrophysical, environmental, and materials science–related phenomena, including ice formation, the manufacturing of active pharmaceutical ingredients, development of diseases such as Alzheimer’s and the origin of life itself. Understanding and controlling nucleation is essential for designing materials with specific properties, developing strategies to inhibit or promote crystallization in various contexts and preventing pathological aggregation in neurodegenerative diseases. Similar to the protein structure prediction problem—where a single amino acid sequence can in theory adopt one most stable conformation but in practice may sample multiple competing conformations—crystal nucleation faces a parallel challenge: the same chemical species can form diverse polymorphs under different environmental conditions (e.g., temperature, pressure, solvent). Each polymorph presents its own set of physical and chemical properties, highlighting the importance of understanding and controlling polymorph selection in fields ranging from pharmaceuticals to materials design. Despite advances in experimental and computational methods for studying phase transitions and polymorph stability, nucleation remains challenging due to its nanoscale nature. Furthermore, in practical settings, salts and impurities can further influence crystal nucleation in diverse contexts, from scaling in pipelines and desalination plants to the durability of concrete and the efficiency of battery materials. This can lead to the formation of polymorphs that may differ from the most stable phase in pure solutions. Or, even though the final structure might appear same irrespective of whether the environment contained impurities or not, the mechanism through which it was formed might be completely different and not intuitive.

Wang, Ruiyu [University of Maryland, College Park,↗

Lignin-based jet fuel and its blending effect with conventional jet fuel

Sustainable aviation fuels (SAFs) must demonstrate specific physical and chemical properties as well as material compatibility (i.e., seal swell) to be used as an aviation turbine fuel. Several alternative jet fuels incorporated in ASTM D7566 are comprised mainly of n/iso-alkanes and can only be blended up to 50 vol% due to material compatibility and density issues. Prior work illustrated the ability of cycloalkanes to replace aromatics’s role in material compatibility. Here, we report the first archival documentation of a feedstock and chemical process to yield a product composition able to complement existing SAF ASTM D7566 annexes. A lignin-based jet fuel (LJF) blend components is generated and composed of mostly C7-C18 mono, di, and tri-cycloalkanes. The neat LJF was blended with conventional jet fuel at 10 vol% (LJF blend) to simulate an ASTM “Fast Track” evaluation process. Fuel properties that are critical to engine operability (ATSM D4054 Tier 3 & 4) were either predicted or experimental tested based on the volume availability. All LJF blend’s critical properties fall within the experience range of conventional jet fuel, with o-ring swelling exceeding the typical range of conventional fuels. Here, these results in total support the potential use of this LJF pathway to complement other SAF pathways and achieve 100% drop-in SAF.

09 BIOMASS FUELS↗

Assessment and Non-Destructive Evaluation of the Influence of Residual Solvent on a Two-Part Epoxy-Based Adhesive Using Ultrasonics

Polymers are increasingly being used in higher demanding applications due to their ability to tailor the properties of structures while allowing for a weight and cost reduction. Solvents play an important role in the manufacture of polymeric structures since they allow for a reduction in the polymer’s viscosity or assist with the dispersion of fillers into the polymer matrix. However, the incorrect removal of the solvent affects both the physical and chemical properties of polymeric materials. The presence of residual solvent can also negatively affect the curing kinetics and the final quality of polymers. Destructive testing is mainly performed to characterize the properties of these materials. However, this type of testing involves using lab-type equipment that cannot be taken in-field to perform in situ testing and requires a specific sample preparation. Here, a method is presented to non-destructively evaluate the curing process and final viscoelastic properties of polymeric materials using ultrasonics. In this study, changes in longitudinal sound speed were detected during the curing of an aerospace epoxy adhesive as a result of variations in polymer chemistry. To simulate the presence of residual solvent, samples containing different weight percentages of isopropyl alcohol were manufactured and tested using ultrasonics. Thermogravimetric analysis was used to show changes in the decomposition of the adhesive due to the presence of IPA within the polymer structure. Adding 2, 4, and 6 wt.% of IPA decreased the adhesive’s lap shear strength by 40, 58, and 71%, respectively. Ultrasonics were used to show how the solvent influenced the curing process and the final sound speed of the adhesive. Young’s modulus and Poisson’s ratio were determined using both the longitudinal and shear sound speeds of the adhesive. Using ultrasonics has the potential to non-invasively characterize the quality of polymers in both an in-field and manufacturing settings, ensuring their reliability during use in demanding applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Direct Discontinuous Galerkin methods for the reacting multi-component flow equations

The Direct Discontinuous Galerkin (DDG (Liu and Yan, 2008)) method and a counterpart with Interface Correction (DDGIC (Danis and Yan, 2022)) are extended to compute diffusion terms that arise when solving the compressible multi-component flow equations in thermochemical nonequilibrium. Thermodynamic properties, transport properties, chemical reaction rates, and energy exchange terms are computed using Mutation++ (Scoggins et al., 2020). The DG method is applied on unstructured grids, where the accuracy and convergence rates can be sensitive to the numerical method chosen for parabolic terms. A method for determining the homogeneity tensor of the flow equations required for DDGIC is shown. The convergence properties of the DDG methods are studied and compared to the Interior Penalty (IP) method. A number of numerical experiments are conducted to assess the accuracy and performance of the method. The numerical results and convergence studies indicate that DDG and DDGIC provide accurate solutions and perform well for general flows in thermochemical nonequilibrium.

Diffusion↗

Two-dimensional perovskite heterostructures for single crystal semiconductor devices

Two-dimensional (2D) perovskites have gained much attention lately owing to their excellent optoelectronic properties, chemical tunability, and environmental stability. Multiple methods have been devised to synthesize high quality 2D perovskite single crystals, and recent progress in fabricating its heterostructures is notable as well. In particular, with growing interest in 2D van der Waals heterostructures, 2D perovskites have become a strong candidate as a new building block for heterostructures to reveal unique physical properties across different interfaces. Until now, various heterostructure devices of 2D perovskite single crystals with other types of 2D materials such as transition metal dichalcogenides (TMDs) and graphene have been studied, which have shown intriguing results including interlayer excitons and enhanced electronic properties. Here, we introduce various synthetic approaches to realize 2D perovskite single crystals and unique characteristics of their single crystal heterostructures fabricated with precision, possessing sharp interfaces. Moreover, recent studies of semiconductor devices based on 2D perovskite single crystal heterostructures are discussed in-depth. New perspectives to further the horizon in the field of 2D perovskite heterostructures are suggested in this work including the consideration of metal–2D material van der Waals contact, application of dry transfer techniques, electric bias driven ion diffusion studies, and nanocrystal array fabrication. 2D perovskite heterostructure single crystal devices factoring in these novel perspectives will further uncover the true potential of these materials for highly efficient and stable semiconductor devices.

Physics↗

Fundamental Studies of Tritium Formation and Diffusivity in Pure and Defective Zircaloy-4 Getters

Zirconium (Zr) and its alloys are used as fuel cladding in nuclear reactors. These materials have their low absorption cross-section for thermal neutrons and have good mechanical and thermal properties. In addition, they are used as tritium getters in tritium-producing burnable absorber rods (TPBARs), in the form of nickel-plated Zircaloy-4 tubes. To produce 3 H, the breading blankets such as lithium aluminate are irradiated in pressurized water. 3 H produced in this process is captured by the getter and 3 H reacts chemically with Zr to form metal hydride (ZrTx). The precipitation of metal hydride results in not only the volume increase and hydrogen embrittlement of zircaloy but also changes in getter’s chemical properties. This degrades the getter’s performance. Therefore, understanding the behavior of 3 H (such as diffusion and solubility) in zircaloy is important to understand getter performance.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Biocompatible Electrostatic Layered Systems for Viral Elimination in the Nose/Throat

An anti-viral coating for the nose & throat is needed to quickly address the spread of COVID-19 infections and to aid future pandemics. Current nasal delivery systems are typically a 1-spray homogenous solution, which is convenient but may not be as efficient or durable as a multi-spray solution that contains a binding layer to anchor the anti-viral components. Many of the current nasal solutions being investigated to aid in pandemic response have solution-based mechanisms of action and are quickly cleared from the nose/mouth limiting their efficacy lifetime. A multi-spray approach utilizing strong intermolecular forces between polymeric materials and anti-viral agents to provide a robust biocompatible coating is expected to have increased physical and chemical properties to combat viral infection. This work evaluated which tailored biocompatible materials are needed to generate a layered system to combat viral infection. This layered system takes advantage of electrostatic interactions to bind anti-viral components, shown in Figure 1. Proof of concept success was demonstrated through cell toxicity studies and anti-viral assays on both the individual layer components and the complete layered system. Project work began with chemical modifications of Xantham Gum to hydrolyzing xanthan gum to give a negatively charged polymer with varying degrees of ionic character and investigate bonding efficiencies. However, this was abandoned in favor of comparing COTS available materials listed in Table 1 (Results section). Concentration and adhesion studies were performed on layers created using the listed polymeric materials and anti-viral agents. Finally, biocompatibility of materials, layers, and coating system were confirmed through cytotoxicity studies and the efficacy of the anti-viral properties tested with phi6 bacteriophage as a SARS-CoV2 surrogate.

36 MATERIALS SCIENCE↗

Wildfire Smoke Particle Properties and Evolution, from Space-Based Multi-Angle Imaging

Emitted smoke composition is determined by properties of the biomass burning source and ambient ecosystem. However, conditions that mediate the partitioning of black carbon (BC) and brown carbon (BrC) formation, as well as the spatial and temporal factors that drive particle evolution, are not understood adequately for many climate and air-quality related modeling applications. In situ observations provide considerable detail about aerosol microphysical and chemical properties, although sampling is extremely limited. Satellites offer the frequent global coverage that would allow for statistical characterization of emitted and evolved smoke, but generally lack microphysical detail. However, once properly validated, data from the National Aeronautics and Space Administration (NASA) Earth Observing System’s Multi-Angle Imaging Spectroradiometer (MISR) instrument can create at least a partial picture of smoke particle properties and plume evolution. We use in situ data from the Department of Energy’s Biomass Burning Observation Project (BBOP) field campaign to assess the strengths and limitations of smoke particle retrieval results from the MISR Research Aerosol (RA) retrieval algorithm. We then use MISR to characterize wildfire smoke particle properties and to identify the relevant aging factors in several cases, to the extent possible. The RA successfully maps qualitative changes in effective particle size, light absorption, and its spectral dependence, when compared to in situ observations. By observing the entire plume uniformly, the satellite data can be interpreted in terms of smoke plume evolution, including size-selective deposition, new-particle formation, and locations within the plume where BC or BrC dominates.

54 ENVIRONMENTAL SCIENCES↗

Differences in chemical evolution between isolated and embedded prestellar cores

Models of prestellar cores often assume that the cores are isolated from their environment – material outside the core boundary plays no role in the subsequent evolution. This is unlikely to be the case in reality, where cores are located within hierarchically substructured molecular clouds. Here, we investigate the dynamical and chemical evolution of prestellar cores, modelled as Bonnor–Ebert spheres, and show that the density of the ambient medium has a large impact on the resulting chemical properties of the cores. Models embedded in high-density, low-temperature surroundings have greatly enhanced abundances of several molecules, such as CO and CS, compared to models with more diffuse surroundings, corresponding to relatively isolated cores. The predicted intensities and profile shapes of molecular lines are also affected. The density of the ambient medium has a stronger effect on the chemical evolution than whether the cores are initially in or out of equilibrium. This suggests that the impact of environment cannot be neglected when modelling chemistry in prestellar cores; the results of these models are highly sensitive to the assumptions made about the core surroundings.

79 ASTRONOMY AND ASTROPHYSICS↗

Co-optimization of fuel properties, combustion system geometry, and injection strategy for conventional diesel fuel

Here, studies have shown that fuel properties can impact an engine’s operation in several ways, including ignition delay, sooting tendency, mixture formation, and combustion temperature. In mixing-controlled compression ignition (MCCI) engines, the fuel system design and piston bowl geometry significantly affect combustion performance and emissions. Based on current information, it is difficult to draw conclusions about fuel property effects and sensitivities. The central fuel hypothesis approach used in the US Department of Energy Co-Optima program has worked well for spark ignition fuels: identifying critical fuel property ranges is sufficient to screen fuel blends that are expected to maximize efficiency and reduce pollutant emissions. However, for MCCI-relevant fuels, the information gained from past studies is not sufficient to build such a merit function or to allow for performing a similar screening of fuel blends. It is hypothesized that a co-optimization of a fuel’s physical and chemical properties, combustion system geometry, and injection strategy could leverage synergies between the effects of the fuel properties and geometries, resulting in improved performance over state-of-the-art. A machine learning–assisted unconstrained global optimization algorithm was used to explore a design space comprising 23 independent variables. The results show that physical property effects were minimal even for large variations in fuel properties, and the only interaction effect that was observed was the effect of varied fuel density parameters on fuel/air mixture formation. Nevertheless, these interactions were not sufficient in magnitude to significantly affect optimization results. Therefore, analysis of the results suggests that fuel physical properties cannot be leveraged in a co-optimization context to increase engine efficiency.

33 ADVANCED PROPULSION SYSTEMS↗

Assessment of Fluoropolymer Production and Use With Analysis of Alternative Replacement Materials

This report focuses on fluoropolymers, which are a subgroup of the much larger class of fluorinated chemicals known as per- and polyfluoroalkyl substances (PFAS). Clearly distinguishing fluoropolymers is important to understanding their distinctive chemical properties, associated risks and benefits, and roles in commerce. In this report, the factors that are considered in a lifecycle assessment (LCA) of fluoropolymers will be discussed. These include the manufacturing of fluoropolymers, their use in industry, and available replacement technologies. Emphasis is placed on fluoropolymer plastics because of their extensive use in the commerce sectors considered here, specifically aerospace, automotive, battery, building construction, chemical processing, electronics, infrastructure, semiconductor, solar panel, and wind energy industries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

EPCAPE-Partitioning Thrust-Los Alamos National Laboratory (EPCAPE-PT-LANL) Field Campaign Report

Coastal cities offer a unique environment for studying aerosol-cloud interactions and the effects of urban emissions on aerosol and cloud properties. As part of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM)’s Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE), the Partitioning Thrust by Los Alamos National Laboratory (EPCAPE-PT-LANL) was conducted to complement the science goals of EPCAPE and add additional in-depth measurements of aerosols and clouds at Mt. Soledad. Our campaign focused on measuring the physical, optical, and chemical properties of aerosols, trace gases, and their interactions within marine stratocumulus clouds in La Jolla, California (see Figure 1).

54 ENVIRONMENTAL SCIENCES↗

Machine learning substitutional defect formation energies in ABO 3 perovskites

Perovskite oxides are a promising material platform for use in a wide range of technological applications including electronics, sensors, fuel cells, and catalysis. This is owing to the extraordinary tunability of their physical and chemical properties via defect engineering. The feasibility and the stability of a defect, such as a substitutional dopant, in the host lattice is usually obtained via experiments and/or through detailed quantum mechanical calculations. Both of these conventional routes are expensive and time consuming. An alternative is a data-driven machine learning (ML)-based approach. In this work, we have applied ML techniques to identify the factors that influence defect formation energy, which is an important measure of the stability of the defects, in perovskite oxides. Using 13 elemental properties as features and random forest regression, we demonstrate a systematic approach to down-selecting from the larger set of features to those that are important, establishing a framework for accurate predictions of the defect formation energy. We quantitatively show that the most important factors that control the dopant stability are the dopant ionic size, heat of formation, effective tolerance factor, and oxidation state. Our work reveals previously unknown correlations, chemical trends, and the interplay between stability and underlying chemistries. Hence, these results showcase the efficacy of ML tools in identifying and quantifying different feature-dependencies and provide a promising route toward dopant selection in the perovskites. Herein, we have developed a framework that itself is general and can be potentially applied to other material classes.

36 MATERIALS SCIENCE↗

Impact of Annealing on Superconducting Properties of Tantalum Thin Films

The pursuit for higher-coherence superconducting qubits has led to the adoption of new materials and innovative fabrication techniques. Among the commonly used superconducting materials, tantalum-based or tantalum-capped superconducting qubits have demonstrated the longest lifetimes, outperforming niobium devices even in the presence of their native oxides. Given the losses introduced by the surface oxide, one method to further improve performance is to reduce or eliminate the native oxide on tantalum through UHV annealing. In this work, we examine the effect of dissolved oxygen as a function of annealing temperature on the superconducting properties of tantalum thin films. Dissolved oxygen is quantified using atom probe tomography (APT) and secondary ion mass spectrometry (TOF-SIMS) and correlated with electromagnetic transport measurements performed using a Physical Property Measurement System (PPMS). This study observes that annealing decomposes the native oxide and drives oxygen diffusion into the film matrix. Increasing oxygen content decreases the superconducting transition temperature (Tc) and the residual resistivity ratio (RRR). The critical field decreases with the incorporation of oxygen, while the film’s coherence length decreases relatively by 5%. These results, as well as findings from ongoing studies linking fabrication processes to the structural and chemical properties of the superconducting film and Josephson junction, provide insight into effective strategies for improving the performance of superconducting devices.

Shinde, Maithilee [IIT, Chicago; Fermilab]↗