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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.

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At least 109 records · Page 6

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)↗

Planar, curved and twisted molecular nanographenes: Reduction-induced alkali metal coordination

Planar and curved polycyclic aromatic hydrocarbons (PAHs) attract significant attention as molecular models of fullerenes, carbon nanotubes, and graphene, thus stimulating broad investigation of chemical reactivity and materials applications of designed nanocarbon π-systems. Non-planar molecular nanographenes (NGs) recently emerge as advanced anode materials in energy storage, showing high reduction limits and enhanced alkali metal intercalation levels. However, the lack of direct structure–property correlations in such complex hybrid systems impedes their further development and utilization. With a focus on alkali-metal-induced reduction of selected PAHs, we herein review original metal binding and intercalation trends, site specific coordination, and distinct carbon framework responses to stepwise electron uptake. Small planar graphene fragments, like triphenylene and coronene, are compared to π-expanded hexabenzocoronenes, followed by the discussion of bowl-shaped corannulene, sumanene and other carbon bowls, as well as bent, warped, and twisted molecular nanographenes. The effect of size, symmetry, and framework topology along with the structural deformation of carbon backbones upon reduction are analyzed, using recent crystallographic examples of alkali-metal intercalated products. In conclusion, the revealed insights into the structures, binding, and metal intercalation in molecular nanographenes should stimulate their future applications as new functional materials.

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Critical role of structural order in bipolar redox-active molecules for organic redox flow batteries

Bipolar redox-active molecules (BRMs) have been suggested as a means to address crossover related issues in all-organic redox flow batteries (RFBs). In such species, electron donors (anolytes) and electron acceptors (catholytes) are linked by a chain, and the same chemical composition is used in both anode and cathode compartments to reduce chemical gradients and unbalanced ion transport. The resultant RFBs resemble the aqueous vanadium RFBs, but offer greater design flexibility and potentially more favorable electrochemical and physicochemical properties. Yet the complex trade-offs in these properties have been a complication. Here we developed a fundamental rubric to uncover the likely origins in the performance metrics of these BRMs that are salient for their use in RFBs. Methylene linked phenothiazine and phthalimide moieties were employed as model BRMs and variations in their properties and molecular conformations were evaluated by systematically varying the methylene linker. Our results revealed that even minimalistic changes in the linker length resulted in dramatic oscillations in the solubility and stability. Using crystallography, quantum chemistry, and molecular dynamics, we clarify that the seemingly fluctuating behavior is due to (1) the inter- and intra-molecular charge transfer between the donor and acceptor through bond or/and through space; (2) the formation of distinctive packing/clustering motifs. Both interactions are strongly dependent on the molecular conformation. As these structural factors modify the electronic structure of both electroactive functional groups and do not change monotonically, the structure–property response in BRMs is often complex. Finally, accordingly, these behaviors need to be taken into account in developing BRMs and knowledge of these structural factors will allow the more rational design of BRMs for grid-scale energy storage.

25 ENERGY STORAGE↗

Observation of interstellar ammonia ice

An absorption band probably due to solid ammonia on interstellar grains has been detected in the infrared spectrum at 2.97 microns of the Becklin-Neugebauer object and probably in NGC 2264-IR. An ammonia-water amorphous ice mixture can explain the structure of the new band and of the 3.07 microns interstellar absorption. Laboratory data suggest that a long wavelength wind extending to 3.5 microns in interstellar dust spectra may be absorption by NH3-H2O complexes in the ices. In the molecular cloud obscuring the BN object, about 20 times as much NH3 is frozen in grains as exists in the gas phase, suggesting the gas-grain interactions may be important in the ammonia chemistry of molecular clouds. Arguments are given that interstellar features at 6.0 and 6.8 microns are also ammonia-related absorptions.

Knacke, R. F.↗

Model for photothermal ionization and molecular recombination during pulsed ablation of polyethylene

The surface erosion of polyethylene is studied under conditions characteristic of extremely high-rate heating expected in laser-driven and high energy density experiments. A coupled model for photoionization and volumetric photothermal degradation of polyethylene is developed that includes finite rate chemistry and molecular recombination of radicals. First, the model is used to explore the evolution of radicals and hydrocarbons during isochoric heating, for which it is found that polyethylene is not in chemical equilibrium for rates >108K/s. Then, the model is used to explore the cooperativity between photoionization and photothermal ionization during one-dimensional ablation from a pulsed heating source, accounting for coupled energy deposition, thermokinetics, thermochemistry, hydrodynamics, mechanics, and thermal conduction in the ALEGRA multi-physics code. The ablation depth per energy pulse is found to agree with an analytical model for instantaneous energy deposition and absent molecular recombination or photoionization. Otherwise, molecular recombination of radicals reduces the depth of ablation per pulse, owing to thermal stabilization on forming branched molecules. Radical formation through photoionization can be compensated for by recombination, but it accelerates ablation at high enough photoionization rates. Finally, the influence of molecular recombination on the ablation depth is found to decrease for long pulses, owing to decreased recombination reaction rates at lower vapor densities near the ablated surface. These and other findings highlight competition between the processes of scission, recombination, and photoionization during pulsed ablation of polyethylene.

Moore, N. W. (ORCID:0000000272259674)↗

Competing Intermolecular and Molecule–Surface Interactions: Dipole–Dipole-Driven Patterns in Mixed Carborane Self-Assembled Monolayers

Carboranedithiol isomers adsorbing with opposite orientations of their dipoles on surfaces are self-assembled together to form mixed monolayers where both lateral dipole–dipole and lateral thiol–thiolate (S–H···S) interactions provide enhanced stability over single-component monolayers. Here, we demonstrate the first instance of the ability to map individual isomers in a mixed monolayer using the model system carboranedithiols on Au{111}. The addition of methyl groups to one isomer provides both an enhanced dipole moment and extra apparent height for differentiation via scanning tunneling microscopy (STM). Associated computational investigations rationalize favorable interactions of mixed pairs and the associated stability changes that arise from these interactions. Both STM images and Monte Carlo simulations yield similarly structured mixed monolayers, where approximately 10% of the molecules have reversed dipole moment orientations but no direct chemical attachment to the surface, leading to homogeneous monolayers with no apparent phase separation. Deprotonating the thiols by depositing the molecules under basic conditions eliminates the lateral S–H···S interactions while accentuating the dipole–dipole forces. The molecular system investigated is composed of isomeric molecules with opposite orientations of dipoles and identical surface packing, which enables the mapping of individual molecules within the mixed monolayers and enables analyses of the contributions of the relatively weak lateral interactions to the overall stability of the assemblies.

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Looking Local: Milky Way Science with JWST

The James Webb Space Telescope has only been operating for a short time, but has already revolutionized multiple areas of astrophysics, including our understanding of our home Galaxy. With a 6.6 meter primary mirror and four infrared science instruments, JWST’s science mission includes measurements of exoplanet atmospheres, observations of the chemistry of molecular clouds, tracing the lifecycle of dust in the interstellar medium (ISM), investigations of galaxy mergers and probing the first galaxies and the cosmological history of the universe. By investigating the Milky Way with JWST astronomers can not only better understand the physics, chemistry and dynamics of our own backyard, but these results can be used to more accurately inform the interpretation of observations of the distant universe. This presentation will detail JWST’s capabilities for conducting observations and surveys in the Milky Way, as well as highlight some early results from the observatory.

Erin C. Smith↗

The pervasive impact of critical fluctuations in liquid–liquid extraction organic phases

Liquid-liquid extraction is an essential chemical separation technique where polar solutes are extracted from an aqueous phase into a nonpolar organic solvent by amphiphilic extractant molecules. A fundamental limitation to the efficiency of this important technology is third phase formation, wherein the organic phase splits upon sufficient loading of polar solutes. The nanoscale drivers of phase splitting are challenging to understand in the complex hierarchically structured organic phases. In this study, we demonstrate that the organic phase structure and phase behavior are fundamentally connected in a way than can be understood with critical phenomena theory. For a series of binary mixtures of trialkyl phosphate extractants with linear alkane diluents, we combine small angle x-ray scattering and molecular dynamics simulations to demonstrate how the organic phase mesostructure over a wide range of compositions is dominated by critical concentration fluctuations associated with the critical point of the third phase formation phase transition. These findings reconcile many longstanding inconsistencies in the literature where small angle scattering features, also consistent with such critical fluctuations, were interpreted as reverse micellar-like particles. Altogether, this study shows how the organic phase mesostructure and phase behavior are intrinsically linked, deepening our understanding of both and providing a new framework for using molecular structure and thermodynamic variables to control mesostructure and phase behavior in liquid-liquid extraction.

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PCR Based Microbial Monitor for Analysis of Recycled Water Aboard the ISSA: Issues and Prospects

The monitoring of spacecraft life support systems for the presence of health threatening microorganisms is paramount for crew well being and successful completion of missions. Development of technology to monitor spacecraft recycled water based on detection and identification of the genetic material of contaminating microorganisms and viruses would be a substantial improvement over current NASA plans to monitor recycled water samples that call for the use of conventional microbiology techniques which are slow, insensitive, and labor intensive. The union of the molecular biology techniques of DNA probe hybridization and polymerase chain reaction (PCR) offers a powerful method for the detection, identification, and quantification of microorganisms and viruses. This technology is theoretically capable of assaying samples in as little as two hours with specificity and sensitivity unmatched by any other method. A major advance in probe-hybridization/PCR has come about in a technology called TaqMan(TM), which was invented by Perkin Elmer. Instrumentation using TaqMan concepts is evolving towards devices that could meet NASA's needs of size, low power use, and simplicity of operation. The chemistry and molecular biology needed to utilize these probe-hybridization/PCR instruments must evolve in parallel with the hardware. The following issues of chemistry and biology must be addressed in developing a monitor: Early in the development of a PCR-based microbial monitor it will be necessary to decide how many and which organisms does the system need the capacity to detect. We propose a set of 17 different tests that would detect groups of bacteria and fungus, as well as specific eukaryotic parasites and viruses; In order to use the great sensitivity of PCR it will be necessary to concentrate water samples using filtration. If a lower limit of detection of 1 microorganism per 100 ml is required then the microbes in a 100 ml sample must be concentrated into a volume that can be added to a PCR assay; There are not likely to be contaminants in ISSA recycled water that would inhibit PCR resulting in false-negative results; The TaqMan PCR product detection system is the most promising method for developing a rapid, highly automated gene-based microbial monitoring system. The method is inherently quantitative. NASA and other government agencies have invested in other technologies that, although potentially could lead to revolutionary advances, are not likely to mature in the next 5 years into working systems; PCR-based methods cannot distinguish between DNA or RNA of a viable microorganism and that of a non-viable organism. This may or may not be an important issue with reclaimed water on the ISSA. The recycling system probably damages the capacity of the genetic material of any bacteria or viruses killed during processing to serve as a template in a PCR desinged to amplify a large segment of DNA (less than 650 base pairs). If necessary, vital dye staining could be used in addition to PCR, to enumerate the viable cells in a water sample; The quality control methods have been developed to insure that PCR's are working properly, and that reactions are not contaminated with PCR carryover products which could lead to the generation of false-positive results; and The sequences of the small rRNA subunit gene for a large number of microorganisms are known, and they consititue the best database for rational development of the oligonucleotide reagents that give PCR its great specificity. From those gene sequences, sets of oligonucleotide primers for PCR and Taqman detection that could be used in a NASA microbial monitor were constructed using computer based methods. In addition to space utilization, a microbial monitior will have tremendous terrestrial applications. Analysis of patient samples for microbial pathogens, testing industrial effluent for biofouling bacteria, and detection biological warfare agents on the battlefield are but a few of the diverse potential uses for this technology. Once fully developed, gene-based microbial monitors will become the fundamental tool in every lab that tests for microbial contaminants, and serve as a powerful weapon in mankind's war with the germ world.

Cassell, Gail H.↗

Bringing chemical structures to life with augmented reality, machine learning, and quantum chemistry

Visualizing 3D molecular structures is crucial to understanding and predicting their chemical behavior. However, static 2D hand-drawn skeletal structures remain the preferred method of chemical communication. Here, we combine cutting-edge technologies in augmented reality (AR), machine learning, and computational chemistry to develop MolAR, an open-source mobile application for visualizing molecules in AR directly from their hand-drawn chemical structures. Users can also visualize any molecule or protein directly from its name or protein data bank ID and compute chemical properties in real time via quantum chemistry cloud computing. MolAR provides an easily accessible platform for the scientific community to visualize and interact with 3D molecular structures in an immersive and engaging way.

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Accurate, Uncertainty-Aware Classification of Molecular Chemical Motifs from Multimodal X-ray Absorption Spectroscopy

Accurate classification of molecular chemical motifs from experimental measurement is an important problem in molecular physics, chemistry, and biology. In this work, we present neural network ensemble classifiers for predicting the presence (or lack thereof) of 41 different chemical motifs on small molecules from simulated C, N, and O K-edge X-ray absorption near-edge structure (XANES) spectra. Our classifiers not only achieve class-balanced accuracies of more than 0.95 but also accurately quantify uncertainty. Here, we also show that including multiple XANES modalities improves predictions notably on average, demonstrating a “multimodal advantage” over any single modality. In addition to structure refinement, our approach can be generalized to broad applications with molecular design pipelines.

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Nonvolatile Voltage Controlled Molecular Spin-State Switching for Memory Applications

Nonvolatile, molecular multiferroic devices have now been demonstrated, but it is worth giving some consideration to the issue of whether such devices could be a competitive alternative for solid-state nonvolatile memory. For the Fe (II) spin crossover complex [Fe{H2B(pz)2}2(bipy)], where pz = tris(pyrazol-1-yl)-borohydride and bipy = 2,2′-bipyridine, voltage-controlled isothermal changes in the electronic structure and spin state have been demonstrated and are accompanied by changes in conductance. Higher conductance is seen with [Fe{H2B(pz)2}2(bipy)] in the high spin state, while lower conductance occurs for the low spin state. Plausibly, there is the potential here for low-cost molecular solid-state memory because the essential molecular thin films are easily fabricated. However, successful device fabrication does not mean a device that has a practical value. Here, we discuss the progress and challenges yet facing the fabrication of molecular multiferroic devices, which could be considered competitive to silicon.

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Navigating Large Chemical Spaces Using Graph Theory and Integer Programming

Navigating and analyzing large chemical spaces are necessary to accelerate the design and discovery of new molecules and chemical processes. In this work, we introduce a computational framework that integrates graph theory and integer programming to enable the efficient navigation of large chemical spaces. Our framework represents the chemical space as a graph, wherein nodes represent molecules and edges represent the degree of similarity or connectivity based on domain-specific information. Using the graph representation, we identify representative molecules by computing the so-called minimum dominating set (MDS), which in our context is the minimum set of molecules that is connected to all other molecules. We present a suite of solution strategies for the MDS problem including heuristic and rigorous integer programming (IP) approaches. We show that these approaches allow us to capture physicochemical properties and domain-specific logic and constraints, facilitating the identification of molecules with the target properties. We demonstrate the effectiveness of the proposed approach by navigating the chemical space of per- and polyfluoroalkyl substances (PFAS); this comprises approximately 15,000 molecular structures. We compare our framework against traditional dimensionality reduction and clustering methods such as t-SNE and K-means clustering.

Chemical structure↗

Predicting chemical reaction equilibria in molten carbonate fuel cells via molecular simulations

It has been recently suggested that hydroxide ions can be formed in the electrolyte of molten carbonate fuel cells when water vapor is present. The hydroxide can replace carbonate in transporting electrons across the electrolyte, thereby reducing the CO 2 separation efficiency of the fuel cell although still producing electricity. In this work, we obtain the equilibrium concentration of hydroxide in five molten alkali carbonate salts from molecular simulations. The results reveal that there can be a substantial amount of hydroxide in the electrolyte at low partial pressures of CO 2 . In addition, we find that the equilibrium concentration of molecular water dissolved in the electrolyte is over two orders of magnitude higher than that of CO 2 . Increasing the size and polarizability (or in other words reducing the “hardness”) of the cations present in the electrolyte can reduce the hydroxide fraction, but at the cost of lowering ionic conductivity.

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Nuclear–Electronic Orbital General Rate Theory: Predicting Hydrogen Kinetic Isotope Effects in the Deep Tunneling Regime

Hydrogen transfer is a critical component of many chemical and biological processes. The ratio of rate constants for hydrogen and deuterium transfer defines the H/D kinetic isotope effect (KIE), which is a powerful tool for elucidating hydrogen transfer mechanisms. Interpretation of experimental H/D KIEs relies on accurate and affordable computational methods. However, due to their light mass, hydrogen and deuterium can undergo tunneling, which is challenging to describe in multidimensional molecular systems. Herein, we introduce the nuclear–electronic orbital general rate theory (NEO-GRT), which enables the efficient prediction of H/D KIEs based on full-dimensional molecular quantum chemistry calculations. The NEO-GRT approach describes the hydrogen transfer rate constant with a general expression that spans the vibrationally adiabatic and nonadiabatic hydrogen tunneling regimes. The input quantities are computed using NEO density functional theory, which treats the transferring hydrogen or deuterium nucleus quantum mechanically on the same level as the electrons. We investigate two intramolecular proton transfer reactions in organic molecules at temperatures down to 50 K to evaluate the performance of NEO-GRT by comparison to transition state theory and ring-polymer instanton theory. The KIEs computed with NEO-GRT agree with those calculated using ring-polymer instanton theory for the full-dimensional molecular systems at the same level of electronic structure theory. This agreement indicates that NEO-GRT captures the deep hydrogen tunneling effects, in contrast to transition state theory, which neglects such effects. Given its relatively low computational cost, NEO-GRT is a promising approach for predicting H/D KIEs in large organic and organometallic systems.

Hydrogen↗

Autonomous continuous flow reactor synthesis for scalable atom-precision

With new instrumentation design, robotics, and in-operando hyphenated analytical tool automation, the intelligent discovery of synthesis pathways is becoming feasible. It can potentially bridge the gap for the scale-up of new materials. In this article, we review current progress and describe a new system that uses an autonomous continuous flow chemistry framework to translate high-quality lead molecules and materials to quantities that can meet scalability demands. At the core is a continuous flow synthesis platform that can design its viable synthesis pathway to a particular molecule or material and then autonomously carry it out. This is realized by integrating: (1) A workflow/architecture for multimode chemical/materials characterization in-line. The in-line characterization modes are NMR, ESR, IR, Raman, UV-Vis, GC-MS, and HPLC, along with ex-situ modes for X-Ray and neutron scattering; (2) Integration for feedback/analysis/data storage of the control variables; (3) A core software stack that includes deep learning and reinforcement learning alongside quantum chemistry and molecular dynamics; (4) On-demand compute architectures that parse calculations to compute resources needed which include light-weight edge, mid-level edge (NVIDA DGX-2), and high-performance computing. We demonstrate preliminary results on how this autonomous reactor system can enhance our ability to deliver deuterated materials, copolymers, and site-substituted molecules.

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