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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Plume backscatter measurements using quartz crystal microbalances in JPL Molsink (molecular sink)

Quantitative evidence of gas flows in the far upstream region of small nozzles with large boundary layer flow are discussed. Gas mass fluxes were measured using quartz crystal microbalances. Both nitrogen and carbon dioxide gases were used as test gases. Gas deposition rates on the order of 100 monolayers per minute were detected 13 inches upstream of the nozzle exit plane. It is significant to note that the crystals detected gases considerably beyond the Prandtl-Meyer turning angle. The data from these tests will be essential in the formulation of scaling laws and analytical prediction methods for viscous plume behavior.

Simon, W.↗
NASA NTRS1973

A molecular-field approximation for quantum crystals

Ground-state properties of quantum crystals have received considerable attention from both theorists and experimentalists. The theoretical results have varied widely with the Monte Carlo calculations being the most successful. The molecular field approximation yields ground-state properties which agree closely with the Monte Carlo results. This approach evaluates the dynamical behavior of each pair of molecules in the molecular field of the other N-2 molecules. In addition to predicting ground-state properties that agree well with experiment, this approach yields data on the relative importance of interactions of different nearest neighbor pairs.

Danilowicz, R.↗
DOE OSTI2024

Evolution of structure and spectroscopic properties of a new 1,3-diacetylpyrene polymorph with temperature and pressure

A new polymorph of 1,3-diacetylpyrene has been obtained from its melt and thoroughly characterized using single-crystal X-ray diffraction, steady-state UV–Vis spectroscopy and periodic density functional theory calculations. Experimental studies covered the temperature range from 90 to 390 K and the pressure range from atmospheric to 4.08 GPa. Optimal sample placement in a diamond anvil cell according to our previously presented methodology ensured over 80% data coverage up to 0.8 Å for a monoclinic sample. Unrestrained Hirshfeld atom refinement of the high-pressure crystal structures was successful and anharmonic behavior of carbonyl oxygen atoms was observed. Unlike the previously characterized polymorph, the structure of 2°AP-β is based on infinite π-stacks of antiparallel 2°AP molecules. 2°AP-β displays piezochromism and piezofluorochromism which are directly related to the variation in interplanar distances within the π-stacking. The importance of weak intermolecular interactions is reflected in the substantial negative thermal expansion coefficient of -55.8 (57) MK -1 in the direction of C—H∙∙∙O interactions.

36 MATERIALS SCIENCE↗
NASA NTRS2003

Which Strategy for a Protein Crystallization Project?

The three-dimensional, atomic-resolution protein structures produced by X-ray crystallography over the past 50+ years have led to tremendous chemical understanding of fundamental biochemical processes. The pace of discovery in protein crystallography has increased greatly with advances in molecular biology, crystallization techniques, cryo-crystallography, area detectors, synchrotrons and computing. While the methods used to produce single, well-ordered crystals have also evolved over the years in response to increased understanding and advancing technology, crystallization strategies continue to be rooted in trial-and-error approaches. This review summarizes the current approaches in protein crystallization and surveys the first results to emerge from the structural genomics efforts.

Kundrot, Craig E.↗
NASA NTRS2004

Which strategy for a protein crystallization project?

The three-dimensional, atomic-resolution protein structures produced by X-ray crystallography over the past 50+ years have led to tremendous chemical understanding of fundamental biochemical processes. The pace of discovery in protein crystallography has increased greatly with advances in molecular biology, crystallization techniques, cryocrystallography, area detectors, synchrotrons and computing. While the methods used to produce single, well-ordered crystals have also evolved over the years in response to increased understanding and advancing technology, crystallization strategies continue to be rooted in trial-and-error approaches. This review summarizes the current approaches in protein crystallization and surveys the first results to emerge from the structural genomics efforts.

Review↗
DOE OSTI2021

Mechanistic Pathways for the Molecular Step Growth of Calcium Oxalate Monohydrate Crystal Revealed by In Situ Liquid-Phase Atomic Force Microscopy

Calcium oxalate monohydrate (COM) crystal is the most common crystalline component of human kidney stones. The molecular-scale inhibitory mechanisms of COM crystal growth by urinary biomolecules such as citrate and osteopontin adsorbed onto the crystal surface are now well understood. However, the pathways by which dissolved calcium and oxalate ions are incorporated into the molecular step of the COM crystal surface, leading to COM crystal growth—a prerequisite to be elucidated for developing effective therapeutics to inhibit COM stones—remain unknown. Here, using in situ liquid-phase atomic microscopy along with a step kinetic model, we reveal the pathways of the calcium and oxalate ions into the COM molecular step via the growth speed analysis of the molecular steps with respect to their step width at the nanoscale. Our results show that, primarily, the ions are adsorbed onto the terrace of the crystal surface from the solution—the rate-controlling stage for the molecular step growth, i.e., COM crystal growth—and then diffuse over it and are eventually incorporated into the steps. This primary pathway of the ions is unaffected by the model peptide D-Asp6 adsorbed on the COM crystal surface, suggesting that urinary biomolecules will not alter the pathway. These new findings rendering an essential understanding of the fundamental growth mechanism of COM crystal at the nanoscale provide crucial insights beneficial to the development of effective therapeutics for COM kidney stones.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Dependence of the Elastic Stiffness Tensors of PETN, α‐RDX, γ‐RDX, ϵ‐RDX, ϵ‐CL‐20, DAAF, FOX‐7, and β‐HMX on Hydrostatic Compression

Abstract The dependence of the components of the elastic stiffness tensors (or elastic constants) of the organic explosives PETN, RDX, CL‐20, DAAF, FOX‐7, and HMX on hydrostatic pressure up to 10 GPa have been computed using dispersion‐corrected density functional theory. We report the evolution of lattice parameters and the non‐zero stiffnesses for the tetragonal, orthorhombic, and monoclinic crystal symmetries. Linear and quadratic dependencies of the components of the elastic stiffness tensors on volumetric compression and hydrostatic pressure are tabulated for use in single crystal plasticity models.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Low-power anisotropic molecular electronic memristors

A molecular electronic memristor, programmable resistive memory device, promises to revolutionize next-generation flexible data storage units, offering fast, dense and ultralow power solutions. Here we report anisotropic resistive switching in molecular κ-(BEDT-TTF) 2 Cu[N(CN) 2 ]Cl memristors, consisting of alternatively segregated bis(ethylenedithio)tetrathiafulvalene (BEDT-TTF) and Cu[N(CN) 2 ]Cl layers. Electron resistance switching behavior controlled by charge tunneling in molecular memristors show a low set voltage of 0.5 V (10 V/cm) with the ON/OFF ratio of 2.3×10 3 along a-axis and a high-level endurance of 1.25×10 4 cycles along all axes. Finally, the findings of such molecular electronic crystals promise for low-power data storage memristors.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Significant charge transport effects due to subtle molecular changes in nitroxide radical single crystals

Radical-containing materials have received renewed interest due to their charge-conducting properties. However, most work focuses on macromolecules, while less attention has been paid to radical-containing small molecules. Here, we quantify the electrical conductivity in two organic radical single crystals and demonstrate that a subtle change in atomic connectivity drastically alters the macroscopic electronic properties of the materials. One radical crystal has an electrical conductivity of 3S m –1 , which is the among the highest values for nonconjugated radical conductors over a 1 μm scale. However, the other radical crystal has a 1,000-fold lower conductivity, despite their extremely similar molecular structures. The temperature-dependent conductivity follows the variable range hopping mechanism for both radical crystals, and the difference in effective charge mobility is the reason for the conductivity difference. These results present a clear picture of the design rules and charge transport mechanism for radical-based small-molecule materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A new perspective on lone pair dynamics in halide perovskites

Halide perovskites form the foundation of an emerging class of materials for broad application in renewable and sustainable applications, including photocatalysis and solar energy harvesting. These materials exhibit beneficial photophysical properties, including bandgaps suitable for solar energy harvesting and efficient charge screening that underlies efficient charge carrier separation and resistance to defects. For organic–inorganic hybrid perovskites, these benefits are thought to arise, in part, from dipolar molecular cations that can reorient in response to charged particles and defects. In this work, we provide a similar perspective for inorganic metal halide perovskites, which do not contain molecular species with permanent dipoles. We discuss how lone pair electrons lead to dipolar ions that exhibit dynamics in analogy with traditional molecular plastic crystals and hybrid perovskites. We argue that further understanding these electronic plastic crystal motions with first principles simulations and synchrotron scattering can help create a basic understanding of photophysical properties of metal halide perovskites and inform the design of advanced functional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2006

Vacuum Ultraviolet Radiation Desorption of Molecular Contaminants Deposited on Quartz Crystal Microbalances

Recent quartz crystal microbalance measurements made in the Marshall Space Flight Center, Photo-Deposition Facility, for several materials, recorded a significant loss of deposited contaminants when the deposition surface of the microbalance was illuminated by a deuterium lamp. These measurements differ from observations made by other investigators in which the rate of deposition increased significantly when the deposition surface was illuminated with vacuum ultraviolet radiation. These observations suggest that the accelerated deposition of molecular contaminants on optically sensitive surfaces is dependant upon the contaminant being deposited and must be addressed during the materials selection process by common material screening techniques.

Albyn, Keith↗
DOE OSTI2024

Physics-based modeling and data analytics [Slides]

This presentation contains a summary of ongoing work within the physics-based modeling and data analytics work package within the Nuclear Materials Discovery and Qualification initiative (NMDQi). Topics include work on MOOSE-based crystal plasticity, molecular dynamics modeling of recombination in metals and alloys, the MOOSE Stochastic Tools Module, and machine learning and atomistic modeling to predict thermo-kinetic properties of nuclear structural materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1995

Stable loop in the crystal structure of the intercalated four-stranded cytosine-rich metazoan telomere

In most metazoans, the telomeric cytosine-rich strand repeating sequence is d(TAACCC). The crystal structure of this sequence was solved to 1.9-A resolution. Four strands associate via the cytosine-containing parts to form a four-stranded intercalated structure held together by C.C+ hydrogen bonds. The base-paired strands are parallel to each other, and the two duplexes are intercalated into each other in opposite orientations. One TAA end forms a highly stabilized loop with the 5' thymine Hoogsteen-base-paired to the third adenine. The 5' end of this loop is in close proximity to the 3' end of one of the other intercalated cytosine strands. Instead of being entirely in a DNA duplex, this structure suggests the possibility of an alternative conformation for the cytosine-rich telomere strands.

NASA Discipline Exobiology↗
DOE OSTI2021

Machine-learning accelerated geometry optimization in molecular simulation

Geometry optimization is an important part of both computational materials and surface science because it is the path to finding ground state atomic structures and reaction pathways. These properties are used in the estimation of thermodynamic and kinetic properties of molecular and crystal structures. This process is slow at the quantum level of theory because it involves an iterative calculation of forces using quantum chemical codes such as density functional theory (DFT), which are computationally expensive and which limit the speed of the optimization algorithms. It would be highly advantageous to accelerate this process because then one could do either the same amount of work in less time or more work in the same time. Here, we provide a neural network (NN) ensemble based active learning method to accelerate the local geometry optimization for multiple configurations simultaneously. We illustrate the acceleration on several case studies including bare metal surfaces, surfaces with adsorbates, and nudged elastic band for two reactions. In all cases, the accelerated method requires fewer DFT calculations than the standard method. In addition, we provide an Atomic Simulation Environment (ASE)-optimizer Python package to make the usage of the NN ensemble active learning for geometry optimization easier.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

End-to-End Optimization for Battery Materials and Molecules by Combining Graph Neural Networks and Reinforcement Learning

The National Renewable Energy Laboratory (NREL), together with the Colorado School of Mines (CSM) and Colorado State University (CSU), has developed a machine learning-enhanced approach to the design of new battery materials. Currently, such materials are designed in part via numerous expensive high-fidelity computational simulations that predict the performance of a given composition. Even with computational screening tools, the vast landscape of possible molecular or crystal structures exceeds current and future computational capacity. Improving the efficiency by which new materials can be optimized will therefore disrupt the cost, risk, and time required to bring new energy solutions to the marketplace. Predicting the properties of an organic molecule or periodic crystalline material given its structure has grown increasingly common. These approaches leverage large-scale computational and experimental databases and ML approaches such as graph neural networks. The inverse design problem of finding a material that possesses desired properties is substantially more challenging, since enumerating all valid material structures is not feasible. In this project, we leveraged recent success in reinforcement learning to efficiently navigate this high-dimensional search space. Just as algorithms can find the optimal chess moves from nearly limitless options, we train an approach to evolve a simple starting structure into a complex structure that possess the desired properties. Our solution has been demonstrated by applying it to two related design application tasks for short- and long-term energy storage, respectively: (1) the design of solid-state ion conductors and (2) the design of organic redox-active materials. The project has resulted an open-source software library for material design, documented examples of applying the library to both organic and inorganic material optimization, and peer-reviewed publications detailing the data, computational models, and resulting candidate materials.

25 ENERGY STORAGE↗
DOE OSTI2022

Not All Aggregates Are Made the Same: Distinct Structures of Solution Aggregates Drastically Modulate Assembly Pathways, Morphology, and Electronic Properties of Conjugated Polymers

Abstract Tuning structures of solution‐state aggregation and aggregation‐mediated assembly pathways of conjugated polymers is crucial for optimizing their solid‐state morphology and charge‐transport property. However, it remains challenging to unravel and control the exact structures of solution aggregates, let alone to modulate assembly pathways in a controlled fashion. Herein, aggregate structures of an isoindigo–bithiophene‐based polymer (PII‐2T) are modulated by tuning selectivity of the solvent toward the side chain versus the backbone, which leads to three distinct assembly pathways: direct crystallization from side‐chain‐associated amorphous aggregates, chiral liquid crystal (LC)‐mediated assembly from semicrystalline aggregates with side‐chain and backbone stacking, and random agglomeration from backbone‐stacked semicrystalline aggregates. Importantly, it is demonstrated that the amorphous solution aggregates, compared with semicrystalline ones, lead to significantly improved alignment and reduced paracrystalline disorder in the solid state due to direct crystallization during the meniscus‐guided coating process. Alignment quantified by the dichroic ratio is enhanced by up to 14‐fold, and the charge‐carrier mobility increases by a maximum of 20‐fold in films printed from amorphous aggregates compared to those from semicrystalline aggregates. This work shows that by tuning the precise structure of solution aggregates, the assembly pathways and the resulting thin‐film morphology and device properties can be drastically tuned.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Acetylcholinesterase: Structure, dynamics, and interactions with organophosphorus compounds

Acetylcholinesterase (AChE) is an enzyme that hydrolyzes the neurotransmitter acetylcholine (ACh), removing it from the synaptic cleft after the transmission of an electrical signal, making it an essential component of chemical neurotransmission. AChE is a serine hydrolase, containing a catalytic triad of Ser/His/Glu. AChE is a prime target for pharmaceuticals treating a variety of neurological disorders. It is also the target of synthetic organophosphorus (OP) compounds that have been used as pesticides and chemical warfare agents. OP compounds contain a potent leaving group, such as fluorine, and act by forming a covalent adduct with the catalytic serine of the AChE active site. A wealth of structural information is available for AChE, including over 300 structures, including a subset of structures in complex with drugs as well as OP compounds. This review will highlight the interactions between OP compounds and AChE from a structural and computational perspective, with a discussion of access to the active site, as well as side reactions that lead to dealkylation of the OP-catalytic serine adduct, a process known as aging. We conclude that while the majority of the conformational changes needed to accommodate the OP compounds are localized to the acyl loop in the crystal structures, molecular dynamics simulations highlight the potential for a far more dynamic enzyme.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

The non-relativistic effective field theory of dark matter-electron interactions

Electronic excitations in atomic, molecular, and crystal targets are at the forefront of the ongoing search for light, sub-GeV dark matter (DM). In many light DM-electron interactions the energy and momentum deposited is much smaller than the electron mass, motivating a non-relativistic (NR) description of the electron. Thus, for any target, light DM-electron phenomenology relies on understanding the interactions between the DM and electron in the NR limit. In this work we derive the NR effective field theory (EFT) of general DM-electron interactions from a top-down perspective, starting from general high-energy DM-electron interaction Lagrangians. This provides an explicit connection between high-energy theories and their low-energy phenomenology in electron excitation based experiments. Furthermore, we derive Feynman rules for the DM-electron NR EFT, allowing observables to be computed diagrammatically, which can systematically explain the presence of in-medium screening effects in general DM models. We use these Feynman rules to compute absorption, scattering, and dark Thomson scattering rates for a wide variety of high-energy DM models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗