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At least 19 records

Optical Properties of Thin Film Molecular Mixtures

Thin films composed of molecular mixtures of metal and dielectric are being considered for use as solar selective coatings for a variety of space power applications. By controlling the degree of molecular mixing, the solar selective coatings can be tailored to have the combined properties of high solar absorptance, alpha, and low infrared emittance, epsilon. On orbit, these combined properties would simultaneously maximize the amount of solar energy captured by the coating and minimize the amount of thermal energy radiated. Mini-satellites equipped with solar collectors coated with these cermet coatings may utilize the captured heat energy to power a heat engine to generate electricity, or to power a thermal bus that directs heat to remote regions of the spacecraft. Early work in this area identified the theoretical boundary conditions needed to operate a Carnot cycle in space, including the need for a solar concentrator, a solar selective coating at the heat inlet of the engine, and a radiator. A solar concentrator that can concentrate sunlight by a factor of 100 is ideal. At lower values, the temperature of the solar absorbing surface becomes too low for efficient heat engine operation, and at higher values, cavity type heat receivers become attractive. In designing the solar selective coating, the wavelength region yielding high solar absorptance must be separated from the wavelength region yielding low infrared emittance by establishing a sharp transition in optical properties. In particular, a sharp transition in reflectance is desired in the infrared to achieve the desired optical performance. For a heat engine operating at 450C, a sharp transition at 1.8 micrometers is desired. The radiator completes the heat flow through the Carnot cycle. Additional work has been done supporting the use of molecular mixtures for terrestrial applications. Sputter deposition provides a means to apply coatings to the tubes that carry a working fluid at the focus of trough-style collectors. Sputtering offers considerable flexibility in coating conditions, including a wide variety of metal and dielectric targets. Coating designs range from simple two or three layer coatings to complex coatings that are purposely graded to be metal-rich at their base and oxide-rich at their surface in order to yield the desired solar selective properties. In these cermet coatings, molecular islands of metal are thought to be embedded in a three dimensional matrix of dielectric. Recent work has identified the use of custom made ion beam sputter deposition targets to produce coatings containing molecular mixtures of metal and dielectric. The targets are cylindrical and the surface consists of a gradually changing composition of metal and dielectric. Rotating the cylinder under the beam during ion beam sputter deposition yields a coating that is a molecular mixture of metal and dielectric, with the composition changing through the thickness of the coating. The optical properties of these coatings are not only dependent on their thickness and chemical composition, but are also dependent on the extent of the through thickness gradient established during deposition. This paper presents a summary of the optical properties of several thin film molecular mixtures designed as solar selective coatings. Optical performance is first identified as a function of wavelength, from the ultraviolet to the visible and infrared. Coating composition, thickness, and gradient from metal to dielectric also play an important role. Additional work for future activities is also identified.

Jaworske, Donald A.↗

Solar Selective Coatings Prepared From Thin-Film Molecular Mixtures and Evaluated

Thin films composed of molecular mixtures of metal and dielectric are being considered for use as solar selective coatings for a variety of space power applications. By controlling molecular mixing during ion-beam sputter deposition, researchers can tailor the solar selective coatings to have the combined properties of high solar absorptance and low infrared emittance. On orbit, these combined properties simultaneously maximize the amount of solar energy captured by the coating and minimize the amount of thermal energy radiated. The solar selective coatings are envisioned for use on minisatellites, for applications where solar energy is used to power heat engines or to heat remote regions in the interior of the spacecraft. Such systems may be useful for various missions, particularly those to middle Earth orbit. Sunlight must be concentrated by a factor of 100 or more to achieve the desired heat inlet operating temperature. At lower concentration factors, the temperature of the heat inlet surface of the heat engine is too low for efficient operation, and at high concentration factors, cavity type heat receivers become attractive. The an artist's concept of a heat engine, with the annular heat absorbing surface near the focus of the concentrator coated with a solar selective coating is shown. In this artist's concept, the heat absorbing surface powers a small Stirling convertor. The astronaut's gloved hand is provided for scale. Several thin-film molecular mixtures have been prepared and evaluated to date, including mixtures of aluminum and aluminum oxide, nickel and aluminum oxide, titanium and aluminum oxide, and platinum and aluminum oxide. For example, a 2400- Angstrom thick mixture of titanium and aluminum oxide was found to have a solar absorptance of 0.93 and an infrared emittance of 0.06. On the basis of tests performed under flowing nitrogen at temperatures as high as 680 C, the coating appeared to be durable at elevated temperatures. Additional durability testing is planned, including exposure to atomic oxygen, vacuum ultraviolet radiation, and high-energy electrons.

Jaworske, Don A.↗

Optical Properties of Thin Film Molecular Mixtures

Thin films composed of molecular mixtures of metal and dielectric are being considered for use as solar selective coatings for a variety of space power applications. By controlling the degree of molecular mixing, the solar selective coatings can be tailored to have the combined properties of high solar absorptance, , and low infrared emittance, . On orbit, these combined properties would simultaneously maximize the amount of solar energy captured by the coating and minimize the amount of thermal energy radiated. Mini-satellites equipped with solar collectors coated with these cermet coatings may utilize the captured heat energy to power a heat engine to generate electricity, or to power a thermal bus that directs heat to remote regions of the spacecraft. Early work in this area identified the theoretical boundary conditions needed to operate a Carnot cycle in space, including the need for a solar concentrator, a solar selective coating at the heat inlet of the engine, and a radiator.1 A solar concentrator that can concentrate sunlight by a factor of 100 is ideal. At lower values, the temperature of the solar absorbing surface becomes too low for efficient heat engine operation, and at higher values, cavity type heat receivers become attractive. In designing the solar selective coating, the wavelength region yielding high solar absorptance must be separated from the wavelength region yielding low infrared emittance by establishing a sharp transition in optical properties. In particular, a sharp transition in reflectance is desired in the infrared to achieve the desired optical performance. For a heat engine operating at 450 C, a sharp transition at 1.8 micrometers is desired.2 The radiator completes the heat flow through the Carnot cycle.

Jaworske, Donald A.↗

Autonomous Molecular Structure Imaging with High-Resolution Atomic Force Microscopy for Molecular Mixture Discovery

Due to its single-molecule sensitivity, high-resolution atomic force microscopy (HR-AFM) has proved to be a valuable and uniquely advantageous tool to study complex molecular mixtures, which hold promise for developing clean energy and achieving environmental sustainability. However, significant challenges remain to achieve the full potential of the sophisticated and time-consuming experiments. Automation combined with machine learning (ML) and artificial intelligence (AI) is key to overcoming these challenges. Here we present Auto-HR-AFM, an AI tool to automatically collect HR-AFM images of petroleum-based mixtures. In this study, we trained an instance segmentation model to teach Auto-HR-AFM how to recognize features in HR-AFM images. Auto-HR-AFM then uses that information to optimize the imaging by adjusting the probe-molecule distance for each molecule in the run. Auto-HR-AFM is the initial tool that will lead to fully automated scanning probe microscopy (SPM) experiments, from start to finish. This automation will allow SPM to become a mainstream characterization technique for complex mixtures, an otherwise unattainable target.

36 MATERIALS SCIENCE↗

Learning Molecular Mixture Property Using Chemistry-Aware Graph Neural Network

Recent advances in machine learning (ML) are expediting materials discovery and design. One significant challenge facing ML for materials is the expansive combinatorial space of potential materials formed by diverse constituents and their flexible configurations. This complexity is particularly evident in molecular mixtures, a frequently explored space for materials, such as battery electrolytes. Owing to the complex structures of molecules and the sequence-independent nature of mixtures, conventional ML methods have difficulties in modeling such systems. Here, we present MolSets, a specialized ML model for molecular mixtures, to overcome the difficulties. Representing individual molecules as graphs and their mixture as a set, MolSets leverages a graph neural network and the deep sets architecture to extract information at the molecular level and aggregate it at the mixture level, thus addressing local complexity while retaining global flexibility. We demonstrate the efficacy of MolSets in predicting the conductivity of lithium battery electrolytes and highlight its benefits in the virtual screening of the combinatorial chemical space. Published by the American Physical Society 2024

Zhang, Hengrui (ORCID:0000000231831654)↗

Thermodynamics of a solar mixture of molecular hydrogen and helium at high pressure

The thermodynamic properties of a model molecular hydrogen and helium mixture are calculated in the strongly interacting region of 0.005 to 0.3 per cu cm for a range of temperatures that are of interest for the envelopes of the Jovian planets. Computed adiabats fit the gravity data and boundary conditions from model atmospheres of Jupiter.

Slattery, W. L.↗

Evaluating diffusion and the thermodynamic factor for binary ionic mixtures

Molecular dynamics (MD) simulations are a powerful tool for the calculation of transport properties in mixtures. Not only are MD simulations capable of treating multicomponent systems, they are also applicable over a wide range of temperatures and densities. In plasma physics, this is particularly important for applications such as inertial confinement fusion. While many studies have focused on the effect of plasma coupling on transport properties, here we focus on the effects of mixing. We compute the thermodynamic factor, a measure of ideal/non-ideal mixing, for three binary ionic mixtures. Here, we consider mixtures of hydrogen and carbon, hydrogen and argon, and argon and carbon, each at 500 randomly generated state points in the warm dense matter and plasma regimes. The calculated thermodynamic factors indicate different mixing behavior across phase space, which can significantly affect the corresponding mutual diffusion coefficients. As MD simulations are still computationally expensive, we apply modern data science tools to predict the thermodynamic factor over a large phase space. Further, we propose a more accurate approximation to the mutual diffusion coefficient than the commonly applied Darken relation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Direct Monte Carlo Simulations of Chemical Equilibrium Composition of Molecular Fluid Mixtures Under Shock Conditions

A new Monte Carlo simulation method is implemented which holds the number and kind of atoms constant rather than the number and kind of molecules for a molecular fluid mixture. Chemical reactions are allowed as a correlated move of atoms such as an interchange of atoms between molecules. Equilibrium chemical composition is determined as an average over the simulation along with equation of state quantities. Results are presented for N 2 + O 2 → 2NO at 30GPa and 3000K. The equilibrium composition is shown to be sensitive to the potentials between unlike species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Generative Electrolyte Solvent and Formulation Discovery

Molecular mixtures and/or formulations are of great importance in fields ranging from materials science to pharmaceuticals to chemistry. In batteries, electrolytes are complex molecular mixtures consisting of multiple salts and solvents and additives at different concentrations that dictate battery capacity, safety, and cycle life, among others. Unfortunately, due to the complex composition and infinite design space as well as the conflicting property requirements, electrolyte design is the rate-determining step in the design of next generation battery chemistries. In this work, we develop a transformer-based generative AI model − ElectrolyteGPT − capable of generating solvents and electrolyte formulations to satisfy a wide range of desired property requirements. First, we curate an electrolyte-relevant database and develop a new line notation for formulations. Then, we show that ElectrolyteGPT can generate solvents and formulations conditioned on a wide range of important electrolyte properties such as ionic conductivity, oxidative stability, Coulombic efficiency, viscosity, and more. Finally, we experimentally synthesize the generated solvents and fabricate the electrolyte formulations and show that they can meet the desired property requirements and enable longterm cycling in energy-dense anode-free lithium metal batteries. Our work showcases the ability of generative models to address challenges in molecular mixture design for next generation batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evidence for Methane Segregation at the Surface of Pluto

In May 1995, a set of spectrophotometric curves of the system Pluto-Charon was recorded with the UKIRT telescope equipped with the spectrometer CGS4. As for the previous observations, the spectra cover a part of the near infrared range, between 1.4 and 2.55 micrometers, but with a higher resolution of approximately 700. In both the 1992 and 1995 data, the existence of solid methane is confirmed by numerous absorption bands, and the carbon monoxide and the nitrogen ices are identified by their respective signatures at 2.35 and 2.15 um. The solid nitrogen seems to be the principal icy component and forms a matrix in which the CH4 and CO molecules are diluted. However a spectroscopic analysis of the 1995 observations indicates that pure methane may coexist with its diluted phase in N2. In order to derive the horizontal and vertical distribution of these different species and to obtain some quantitative information about their characteristics, we have modeled the spectrum of May 15 that corresponds to the maximum of Pluto's visible light curve. This was achieved by means of a radiative transfer algorithm dealing with compact and stratified media. Among the various representations we have tested to describe the surface of Pluto, only a geographical mixture of three distinct units explains all the significant structures of the analyzed spectrum. The first unit is a thin granular layer of pure CH4 covering a compact polycrystalline substratum of N2-CH4-CO, which are in a molecular mixture (concentrations of and CO of the order of 0.45%, 0.1-0.2% respectively). It covers about 70% of the observed area and corresponds to volatile deposits that are sublimating under solar illumination. The second unit is either (a) a single thick layer of pure granular methane or (b) a unit similar to the first unit but with the two components inverted (i.e. with CH4 forming a substratum and the N2-CH4-CO mixture a superficial layer of fine grains). Covering 20% of the surface, it represents some old surfaces that have been sublimated for a long time, and eventually recovered later by very small amounts of fresh deposits of the molecular mixture N2-CH4-CO. Finally, the third unit may result from the condensation of very fine grains of nearly pure N2. It covers the remainder of the surface (about 10%). All these results allow a better understanding of the processes of deposition, metamorphism, sublimation and transport affecting the different ices detected on Pluto during its climatic cycles.

Doute, S.↗

Solar Selective Coatings for High Temperature Applications

Solar selective coatings are envisioned for use on minisatellites, for applications where solar energy is to be used to power heat engines or to provide thermal energy for remote regions in the interior of the spacecraft. These coatings are designed to have the combined properties of high solar absorptance and low infrared emittance. The coatings must be durable at elevated temperatures. For thermal bus applications, the temperature during operation is likely to be near 100 C. For heat engine applications. the temperature is expected to be much greater. The objective of this work was to screen candidate solar selective coatings for their high temperature durability. Candidate solar selective coatings were composed of molecular mixtures of metal and dielectric, including: nickel and aluminum oxide, titanium and aluminum oxide, and platinum and aluminum oxide. To identify high temperature durability, the solar absorptance and infrared emittance of the candidate coatings were evaluated initially, and after heating to temperatures in the range of 400 C to 700 C. The titanium and aluminum oxide molecular mixture was found to be the most durable.

Jaworske, Donald A.↗

Kinetic model for the vibrational energy exchange in flowing molecular gas mixtures

The present study is concerned with the development of a computational model for the description of the vibrational energy exchange in flowing gas mixtures, taking into account a given number of energy levels for each vibrational degree of freedom. It is possible to select an arbitrary number of energy levels. The presented model uses values in the range from 10 to approximately 40. The distribution of energy with respect to these levels can differ from the equilibrium distribution. The kinetic model developed can be employed for arbitrary gaseous mixtures with an arbitrary number of vibrational degrees of freedom for each type of gas. The application of the model to CO2-H2ON2-O2-He mixtures is discussed. The obtained relations can be utilized in a study of the suitability of radiation-related transitional processes, involving the CO2 molecule, for laser applications. It is found that the computational results provided by the model agree very well with experimental data obtained for a CO2 laser. Possibilities for the activation of a 16-micron and 14-micron laser are considered.

Offenhaeuser, F.↗

A novel approach to characterize the full spectrum and radiative properties of aerosols

Organic aerosols play a significant role in the absorption and radiative budget of the atmosphere, but current modeling approaches do not adequately capture the photo-chemical and oxidative bleaching that occurs during their lifetimes. Most climate models inaccurately assume constant optical properties of these particles, therefore leading to errors in their predictions. In this study we present an approach to better parameterize the optical properties of atmospheric aerosols, including brown carbon (BrC). Using thin-film spectrometry, the full spectrum of reflectivity and emissivity was used to calculate the complex refractive index for multiple species of organic aerosols. This is in contrast to previous techniques which only probe single wavelengths. Since BrC is a complex molecular mixture, we initially focused on single species absorption using four molecular surrogates. Dye-doped polyacrylic-acid thin-films were prepared on glass slides and compared to an aerosolized collection method. Verification of the collection method will open the door to characterizing the complex refractive index of smoke and ambient aerosol.

58 GEOSCIENCES↗

Dynamics of molecular associates in methanol/water mixtures

The dynamics of molecular associates in a methanol/water mixture was investigated using quasielastic neutron scattering. By measuring the signal from four methanol/water samples differing only by their isotopic composition, the relative motion of the water to methanol molecules, i.e. their mutual dynamics, was determined at the nanoscale. The thus obtained nanoscopic mutual diffusion coefficient signals a significantly slower process than the single particle diffusion of either methanol or water in the system as well as their macroscopic mutual diffusion. The data do not provide any indication of microsegregation in this preeminent alcohol/water mixture; however, they do indicate the existence of long lived but dynamic molecular associates of water and methanol molecules. Our analysis of the structural relaxation shows that the lifetime of molecular association through hydrogen bonding determines the fact that viscosity of the mixtures at intermediate concentrations is higher than that of both pure components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ab initio Molecular Dynamics Assessment of Thermodynamic and Transport Properties in (K,Li)Cl and (K, Na)Cl Molten Salt Mixtures

Molten salt mixtures are integral part of highly important technological applications such as nuclear reactors. However, due to inherent difficulties associated with experiment at high temperatures and the intrinsic complexity of liquid-phase multi-component systems, understanding their properties at a molecular level remains a challenge. Here, we report on an ab initio molecular dynamics investigation on structural, electronic, transport, and thermal properties of two common molten salt mixtures, (K, Li)Cl and (K,Na)Cl, at five different compositions and three temperatures. Most of the properties were found to depend on both composition and temperature. While properties, like atomic charges, show additive behaviors, other properties, such as electrical conductivity, show considerable deviations from additivity. We shall show that the mixing of the molten salt mixtures is mainly driven by entropy, and that the KCl and LiCl mix better than KCl and NaCl. Our computational results are in general consistent with available experimental data. Comparison with available theoretical data is also provided.

Nguyen, Manh Thuong↗

Scaling Field-Theoretic Simulation for Multicomponent Mixtures with Neural Operators

Multicomponent polymer mixtures are ubiquitous in biological self-organization but are notoriously difficult to study computationally. Plagued by both slow single molecule relaxation times and slow equilibration within dense mixtures, molecular dynamics simulations are typically infeasible at the spatial scales required to study the stability of mesophase structure. Polymer field theories offer an attractive alternative, but analytical calculations are only tractable for mean-field theories and nearby perturbations, constraints that become especially problematic for fluctuation-induced effects such as coacervation. Here, we show that a recently developed technique for obtaining numerical solutions to partial differential equations based on operator learning, neural operators, lends itself to a highly scalable training strategy by parallelizing per-species operator maps. We illustrate the efficacy of our approach on six-component mixtures with randomly selected compositions and that it significantly outperforms the state-of-the-art pseudospectral integrators for field-theoretic simulations, especially as polymer lengths become long.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ExoReL{sup R}: A Bayesian Inverse Retrieval Framework for Exoplanetary Reflected Light Spectra

The high-contrast imaging technique is meant to provide insight into those planets orbiting several astronomical units from their host star. Space missions such as Wide-Field InfraRed Survey Telescope, Habitable Exoplanet Imaging Mission, and Large Ultra-Violet/Optical/InfraRed Surveyor will measure reflected light spectra of cold gaseous and rocky planets. To interpret these observations, we introduce ExoReL{sup R} (Exoplanetary Reflected Light Retrieval), a novel Bayesian retrieval framework to retrieve cloud properties and atmospheric structures from exoplanetary reflected light spectra. As a unique feature, it assumes a vertically nonuniform volume mixing ratio (VMR) profile of water and ammonia, and uses it to construct cloud densities. In this way, clouds and molecular mixture ratios are consistent. We apply ExoReL{sup R} on three test cases: two exoplanets (υ And e and 47 Uma b) and Jupiter. We show that we are able to retrieve the concentration of methane in the atmosphere, and estimate the position of clouds when the signal-to-noise ratio of the spectrum is higher than 15, in line with previous works. Moreover, we described the ability of our model to give a chemical identity to clouds, and we discussed whether or not we can observe this difference in the planetary reflection spectrum. Finally, we demonstrate how it could be possible to retrieve molecular concentrations (water and ammonia in this work) below the clouds by linking the nonuniform VMR profile to the cloud presence. This will help to constrain the concentration of water and ammonia unseen in direct measurements.

79 ASTRONOMY AND ASTROPHYSICS↗