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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 955 records · Page 53

Novel Low-Density Ablators Containing Hyperbranched Poly(azomethine)s

An ablative composite is low-density (0.25 to 0.40 g/cu cm), easy to fabricate, and superior to the current state-of-the-art ablator (phenolic impregnated carbon ablator, PICA) in terms of decomposition temperature, char yield, and mechanical strength. Initial ablative testing with a CO2 laser under high-heat-flux (1,100 W/sq cm) conditions showed these new ablators are over twice as effective as PICA in terms of weight loss, as well as transfer of heat through the specimen. The carbon fiber/poly(azomethine) composites have the same density as PICA, but are 8 to 11 times stronger to irreversible breaking by tensile compression. In addition, polyazomethine char yields by thermogravimetric analysis are 70 to 80 percent at 1,000 C. This char yield is 10 to 20 percent higher than phenolic resins, as well as one of the highest char yields known for any polymer. A high char yield holds the composite together better toward shearing forces on reentry, as well as reradiates high heat fluxes. This innovative composite is stronger than PICA, so multiple pieces can be sealed together without fracture. Researchers have also studied polyazomethines before as linear polymers. Due to poor solubility, these polymers precipitate from the polymerization solvent as a low-molecular-weight (2 to 4 repeat units) powder. The only way found to date to keep linear polyazomethines in solution is by adding solubilizing side groups. However, these groups sacrifice certain polymer properties. These hyperbranched polyazomethines are high molecular weight and fully aromatic.

Tigelaar, Dean↗

Predicting Energetics Materials’ Crystalline Density from Chemical Structure by Machine Learning

To expedite new molecular compound development, a long-sought goal within the chemistry community has been to predict molecules’ bulk properties of interest a priori to synthesis from a chemical structure alone. In this work, we demonstrate that machine learning methods can indeed be used to directly learn the relationship between chemical structures and bulk crystalline properties of molecules, even in the absence of any crystal structure information or quantum mechanical calculations. We focus specifically on a class of organic compounds categorized as energetic materials called high explosives (HE) and predicting their crystalline density. An ongoing challenge within the chemistry machine learning community is deciding how best to featurize molecules as inputs into machine learning models—whether expert handcrafted features or learned molecular representations via graph-based neural network models—yield better results and why. We evaluate both types of representations in combination with a number of machine learning models to predict the crystalline densities of HE-like molecules curated from the Cambridge Structural Database, and we report the performance and pros and cons of our methods. Our message passing neural network (MPNN) based models with learned molecular representations generally perform best, outperforming current state-of-the-art methods at predicting crystalline density and performing well even when testing on a data set not representative of the training data. However, these models are traditionally considered black boxes and less easily interpretable. Here, to address this common challenge, we also provide a comparison analysis between our MPNN-based model and models with fixed feature representations that provides insights as to what features are learned by the MPNN to accurately predict density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ligand Tuning in Cu(pyalk)2 Water Oxidation Electrocatalysis

Molecular copper water oxidation electrocatalysts have been extensively studied in recent years for their potential use in artificial photosynthetic systems for solar energy conversion. Although ligand modification and its ability to influence catalytic properties is a key advantage of molecular systems, there are, as yet, few examples of systematic studies of these effects. Our oxidatively resistant pyalk (2-pyridyl-2-propanoate) ligand forms a complex with copper(II) that catalyzes water oxidation and provides an attractive scaffold for systematic ligand tuning. Here, we report a series of analogous copper complexes with electron-donating (methoxy-) and -withdrawing (methoxycarbonyl-) groups at the para-position of the pyalk ligand. Trends in the pKa and redox potential align with first-principles predictions for the electron-withdrawing and electron-donating groups. While the modified complexes show good activity for water oxidation, lowered faradaic efficiency in comparison to the parent complex highlights the importance of stability considerations for catalyst tuning.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Melt flow properties of LARC-TPI 1500 series mixtures

This study examines the melt-flow properties of 50/50 mixtures of high flow grade/medium flow grade LARC-TPI 1500 series pellets and a new form (94/6), of medium flow grade material which contains 6 percent of a low molecular weight imide additive. The flow properties are compared with previously reported flow properties of mixtures of earlier batches of high and medium flow grade TPI 1500 materials. Unlike the earlier batches of materials, the later materials were synthesized and mixed at Mitsui Toatsu Chemicals, Inc., Japan, and made into pellets before NASA received them for characterization. They exhibited a lower melt viscosity as well as improved melt stability.

Burks, H. D.↗

Computational and experimental analysis of structural and Thermophysical properties of LiX-KX (X = chloride, iodide, or bromide) molten salts

Molten salts containing lithium (Li) and potassium (K) halides, including chlorides (Cl), bromides (Br), and iodides (I), are pivotal in advanced technological applications including nuclear reactor technologies, thermal batteries, and industrial pyrochemical processes. Despite their significance, the availability of the temperature-dependent structural and thermophysical properties of these molten salts remain scarce. Here, this study addresses this knowledge gap by predicting and measuring the key properties such as coordination number, radial distribution function, density, heat capacity, and volumetric thermal expansion of molten LiI-KI, LiBr-KBr and LiCl-KCl eutectic mixtures. Utilizing ab initio molecular dynamics (AIMD) simulations, we predict these properties of LiX-KX (X=Br,I, Cl) across various temperatures, with chlorides as a benchmark. Experimental measurements using Archimedes methods and Differential Scanning Calorimetry validate the densities and heat capacities of these molten salts. Our comprehensive analysis of the structural and thermophysical properties provides critical insights into the behavior of these molten salts at various temperatures, enhancing the understanding necessary for their application in advanced technologies.

36 - MATERIALS SCIENCE↗

Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules

Abstract Graph Convolutional Neural Network (GCNN) is a popular class of deep learning (DL) models in material science to predict material properties from the graph representation of molecular structures. Training an accurate and comprehensive GCNN surrogate for molecular design requires large-scale graph datasets and is usually a time-consuming process. Recent advances in GPUs and distributed computing open a path to reduce the computational cost for GCNN training effectively. However, efficient utilization of high performance computing (HPC) resources for training requires simultaneously optimizing large-scale data management and scalable stochastic batched optimization techniques. In this work, we focus on building GCNN models on HPC systems to predict material properties of millions of molecules. We use HydraGNN, our in-house library for large-scale GCNN training, leveraging distributed data parallelism in PyTorch. We use ADIOS, a high-performance data management framework for efficient storage and reading of large molecular graph data. We perform parallel training on two open-source large-scale graph datasets to build a GCNN predictor for an important quantum property known as the HOMO-LUMO gap. We measure the scalability, accuracy, and convergence of our approach on two DOE supercomputers: the Summit supercomputer at the Oak Ridge Leadership Computing Facility (OLCF) and the Perlmutter system at the National Energy Research Scientific Computing Center (NERSC). We present our experimental results with HydraGNN showing (i) reduction of data loading time up to 4.2 times compared with a conventional method and (ii) linear scaling performance for training up to 1024 GPUs on both Summit and Perlmutter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Performances of ionic liquid matrices with butyl ammonium counterion for matrix-assisted laser desorption/ionization mass spectrometric detection and analysis of sucralfate

In this work, the performances of two ionic liquid matrices (ILMs) with the same ammonium counterpart for mass spectrometric analysis of the insoluble and soluble sucralfate were compared. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) was performed assisted by the butylammonium salts of α-cyano-hydroxycinnamic acid (CHCAB) and 2,5-dihydroxybenzoic acid (DHBB). CHCAB has a higher IE than DHBB, but better optical properties. CHCAB is more suitable for the analysis of sucralfate, although molecular ions of both compounds were detectable only with low intensities. Thus, optical properties of ILMs are crucial to enhance the sensitivity of MALDI MS detection of polysulfated oligosaccharides. © 2019, © 2019 Taylor & Francis Group, LLC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exploring internal structures and properties of terpolymer fibers via real-space characterizations

While significant research has investigated the processing and properties of high-performance terpolymer fibers, much remains to be understood about the internal nano- and microstructures of these fibers, and how these morphologies relate to fiber properties. Here we use a focused ion beam notch technique and multifrequency atomic force microscope mapping to characterize the internal structure and local mechanical properties within Technora ® fibers. We find a highly fibrillated structure that appears to connect with both the fiber’s molecular chemistry and full-fiber mechanical properties. In addition, through detailed comparisons with Kevlar ® K29 fibers, we find remarkable differences between the internal structures of the two fibers, and posit connections between our measurements and multifunctional performance studies from the literature.

36 MATERIALS SCIENCE↗

Thermodynamic Approach to Enhanced Dispersion and Physical Properties in a Carbon Nanotube/Polypeptide Nanocomposite

A high molecular weight synthetic polypeptide has been designed which exhibits favorable interactions with single wall carbon nanotubes (SWCNTs). The enthalpic and entropic penalties of mixing between these two molecules are reduced due to the polypeptide's aromatic sidechains and helical secondary structure, respectively. These enhanced interactions result in a well dispersed SWCNT/Poly (L-Leucine-ran-L-Phenylalanine) nanocomposite with enhanced mechanical and electrical properties using only shear mixing and sonication. At 0.5 wt% loading of SWCNT filler, the nanocomposite exhibits simultaneous increases in the Young's modulus, failure strain, and toughness of 8%, 120%, and 144%, respectively. At one kHz, the same nanotube loading level also enhances the dielectric constant from 2.95 to 22.81, while increasing the conductivity by four orders of magnitude.

Lovell, Conrad S.↗

Ballistic electron emission microscopy and spectroscopy of Au/GaAs interfaces

This paper presents the first Schottky barrier results for the Au/GaAs(100) interface prepared completely in situ on GaAs grown by molecular-beam epitaxy. The resulting interface displays unexpected properties which can be interpreted in terms of enhanced electrode interdiffusion. In addition, the capability of molecular-beam epitaxy for in situ processing enables the stabilization of this interface against diffusion and allows the formation of a Au/GaAs system with nearly ideal properties. Newly developed ballistic electron spectroscopy and imaging techniques demonstrate that the heterogeneity present at the interface of Au/GaAs(100) fabricated on chemically treated GaAs substrates is removed.

Kaiser, W. J.↗

Simplifying the Chemical Design of Nonfused-Ring Electron Acceptors─Lessons Learned from Thienothiophene and Benzodithiophene Cores

Nonfused-ring electron acceptors (NFREA)s have been proposed as alternatives to fused-ring acceptors in organic photovoltaics (OPV)s. The simpler molecular design of NFREAs results in a reduced synthetic complexity, potentially lowering manufacturing costs, and easier access to desired optoelectronic properties by structural modifications. However, they have not seen the same rise in popularity as fused nonfullerene acceptors (NFA)s due to their lower performances in devices. In this work, we explore structure–property relationships of three NFREA molecules based on thieno[3,2-b]thiophene (TT) and benzo[1,2-b:4,5-b′]dithiophene (BDT) cores and malononitrile functionalized-isatin end group acceptors. We describe their synthetic routes, computational analysis, and photophysical and electronic properties. Here, we investigated the effect of changing the core from TT to BDT on electronic properties of the molecules─a result of raising/lowering of the frontier molecular orbital (FMO) levels. We also explored the effect of branched vs nonbranched alkyl groups on the morphological and blend-capabilities in bulk heterojunction (BHJ) OPV devices. These effects were then reflected in the overall device performances, primarily due to favorable FMO energy alignment between the NFREA and polymer. To investigate the behavior of the excited states of the NFREAs within the active layer of the devices, we performed time-resolved microwave conductivity and transient absorption experiments, which confirmed that the TT molecules exhibited very low conductance while the BDT molecule showed moderate photoconductance. Our combined theoretical, synthetic, device, and charge carrier dynamics studies of these materials reveal the central role that structure–property relationships play in future molecular designs of NFREAs that can perform as well as their fused counterparts.

14 SOLAR ENERGY↗

Effect of Cr and Al on Elastic Constants of FeCrAl Alloys Investigated by Molecular Dynamics Method

The FeCrAl alloy system is recognized as one of the candidate materials for accident-tolerant fuel (ATF) cladding in the nuclear power industry due to its high oxidation resistance under irradiation and high-temperature environments. The concentrations of Cr and Al have a significant effect on elastic properties of the FeCrAl alloy. In this work, elastic constants C 11 , C 12 , C 44 , bulk modulus and shear modulus of FeCrAl alloy were calculated with molecular dynamics methods. We explored compositions with 1–15 wt.% Cr and 1–5 wt.% Al at temperatures from 0 K to 750 K. The results show that the concentrations of Al and Cr have different effects on the elastic constants. When the concentration of Al was fixed, a decrease in bulk modulus and shear modulus with increasing Cr content was observed, consistent with previous experimental results. The dependence of elastic constants on temperature was also the same as in the experiments. Investigations into elastic properties of defect-containing alloys have shown that vacancies, voids, interstitials and Cr-rich precipitations have different effects on elastic properties of FeCrAl alloys. Investigations of elastic properties of defect-containing alloys have shown that vacancies, void, interstitials and Cr-rich precipitations have different effects on elastic properties of FeCrAl alloys. Therefore, the present results indicate that both the Cr and Al concentrations and radiation defects should be considered to develop and apply the FeCrAl alloy in ATF design.

36 MATERIALS SCIENCE↗

Structural Properties of [N1888][TFSI] Ionic Liquid: A Small Angle Neutron Scattering and Polarizable Molecular Dynamics Study

In this study, we investigate the quaternary ammonium-based ionic liquid (QAIL), methyltrioctylammonium bis(trifluoromethylsulfonyl)imide, [N 1888 ][TFSI], utilizing small angle neutron scattering (SANS) measurements and polarizable molecular dynamics (MD) simulations to characterize the shortand long-range liquid structure. Scattering structure factors show signatures of three length scales in reciprocal space indicative of alternating polarity (k ~ 0.44 Å –1 ), charge (k ~ 0.75 Å –1 ), and neighboring or adjacent (k ~ 1.46 Å –1 ) domains. Excellent agreement between simulation and experimental scattering structure factors validates various simulation analyses that provide detailed atomistic characterization of the different length scale correlations. The first solvation shell structure is illustrated by obtaining radial, angular, dihedral, and combined distribution functions, where two dominant spatial motifs, N + ···N – and N + ···O – , compete for optimal packing around the polar head of the [N 1888 ] + cation. Intermediate and long-range structures are governed by the balance between local electroneutrality and octyl chain networking, respectively. By computing the charge-correlation structure factor, S ZZ , and the spatial extent of the octyl chain network using graph theory, the bulk-phase structure of [N 1888 ][TFSI] is characterized in terms of electrostatic screening and apolar domain formation length scales.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigation into the transport properties of planetary interiors through inelastic X-ray scattering experiments and quantum molecular dynamics (Final Technical Report)

This was a two-year research project for the period 08/15/2018 - 08/14/2020 conducted at the University of Nevada, Reno using Pronghorn, a newly built high-performance cluster located at the University. The short-term project goal was to provide computational support for the experimental campaigns at LCLS through data analysis of previous and upcoming scheduled experiments, along with performing state-of-the-art atomistic simulations of dense plasmas. The longer-term goal was to create a new computational high energy density physics group located at the University of Nevada, Reno. Guided by results from past and future high-resolution scattering experiments, we aimed to research and develop non-equilibrium and non-adiabatic atomistic simulations of dense plasmas that went beyond the Born-Oppenheimer approximation

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Octopus, a computational framework for exploring light-driven phenomena and quantum dynamics in extended and finite systems

Over the last few years, extraordinary advances in experimental and theoretical tools have allowed us to monitor and control matter at short time and atomic scales with a high degree of precision. An appealing and challenging route toward engineering materials with tailored properties is to find ways to design or selectively manipulate materials, especially at the quantum level. To this end, having a state-of-the-art ab initio computer simulation tool that enables a reliable and accurate simulation of light-induced changes in the physical and chemical properties of complex systems is of utmost importance. The first principles real-space-based Octopus project was born with that idea in mind, i.e., to provide a unique framework that allows us to describe non-equilibrium phenomena in molecular complexes, low dimensional materials, and extended systems by accounting for electronic, ionic, and photon quantum mechanical effects within a generalized time-dependent density functional theory. This article aims to present the new features that have been implemented over the last few years, including technical developments related to performance and massive parallelism. We also describe the major theoretical developments to address ultrafast light-driven processes, such as the new theoretical framework of quantum electrodynamics density-functional formalism for the description of novel light–matter hybrid states. Those advances, and others being released soon as part of the Octopus package, will allow the scientific community to simulate and characterize spatial and time-resolved spectroscopies, ultrafast phenomena in molecules and materials, and new emergent states of matter (quantum electrodynamical-materials).

74 ATOMIC AND MOLECULAR PHYSICS↗

Molecular Functionalization of Semiconductor Surfaces

The presence of molecules on semiconductor surfaces can have a profound impact on their properties and applications in solar energy conversion. In this chapter we discuss the methods used to effect functionalization of semiconductor surfaces with molecular dipoles and catalysts. A major focus is the energetic impacts such molecules have to the fields at the semiconductor|contact interface. These field modulations are strongly dependent on the nature of the surface-bound molecule including its dipole moment and orientation as well as the distance of the dipole from the semiconductor surface. The contacting phase also has a strong impact on the energetics, since ions in the liquid electrolytes relevant to inorganic photochemistry partially screen dipolar effects at the surface. In addition to detailed description of these fundamentals, we present the history of this field as well as state-of-the-art chemistries that leverage the preceding decades of knowledge to impart the molecular interfacial layer with dynamic properties such as light absorption and catalysis. The challenges of establishing stable molecular attachment schemes at semiconductor|electrolyte interfaces are interwoven throughout the chapter. We conclude with a prognosis and future outlook that we hope will be a useful guide to those interested in developing the next generation of molecular chemistries at photoelectrode interfaces.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS,I↗