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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Degradation of Coflon in Methanol at Temperatures Around 140 C

An unexpected and significant physico-chemical degradation of Coflon PVDF specimens was observed at the end of 1994 during routine scheduled exposure exercises on strained material. The intent was to age various samples, including some strained in a 4-point bend configuration, in methanol at 140 C and subsequently submit the aged samples to various tests including dynamic fatigue and fracture toughness. However, the samples deteriorated to such an extent that such testing was not possible: only when conditions were made less severe was it found possible to perform such testing. The purpose of the current report is to describe the nature of the PVDF deterioration observed during a number of tests performed to examine this phenomenon. This report also records, as Appendix 1, some SEM/X-ray microanalysis data on Coflon samples exposed to a methanol/amine mixture, and to other amine or H2S-aged samples.

Campion, R. P.↗
DOE OSTI2019

Proteomic Sample Preparation Techniques: Towards Forensic Proteomic Applications

Proteomic sample preparation techniques rely on dynamic multi-step processes that are sample type dependent. Forensic proteomic applications comprise diverse sample types and therefore require numerous sample preparation workflows. A sample may need pre-treatment steps to solubilize proteins from a solid surface, for example - from clothing, from a swab, or off of a filter. A sample may need to be disrupted or homogenized to liberate proteins trapped in cells. Or a sample may need additional processing steps, such as organic extraction, to isolate proteins from small molecule contaminants which interfere with mass spectrometry (MS) measurements. Following these pre-treatment steps, proteins are reduced, denatured, alkylated, and enzymatically digested. The resulting peptide mixture can be desalted by solid phase extraction or fractionated prior to liquid chromatography MS-based proteomic characterization. Here we detail each step of this multi-stage sample type dependent processing.

Nicora, Carrie D.↗
DOE OSTI2025

Free-Energy Landscapes and Surface Dynamics in Methane Activation on Ni(511) via Machine Learning and Enhanced Sampling

Methane activation on stepped Ni(511) surfaces involves the rearrangement of surface atoms as the chemical reaction proceeds. This process is particularly sensitive to temperature. Using machine-learned interatomic potentials (MLIPs) coupled with enhanced sampling techniques, we investigate the activation of methane under realistic operando conditions. Our analysis reveals that methane dissociation occurs predominantly at step-edge nickel atoms. As CH x (where x = 3 or 4) species bind to additional surface nickel atoms, their reduced mobility leads to entropic penalties that suppress certain configurations and transition states. This is reflected in the underlying free energy surfaces, where configurations such as methyl binding to hollow sites and activation routes involving two nickel atoms become unfavorable as temperature increases. At elevated temperatures, methane activation extends from step-edge sites to terrace regions because of reduced free-energy barriers and enhanced surface dynamics. By decomposing the free-energy into enthalpic and entropic contributions, we uncover temperature-dependent shifts in the preferences of methane for the relevant active sites and arrive at a detailed molecular picture of methane activation.

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

Weak Electron–Phonon Coupling and Enhanced Thermoelectric Performance in n-type PbTe–Cu 2 Se via Dynamic Phase Conversion

This study investigates Ga-doped n-type PbTe thermoelectric materials and the dynamic phase conversion process of the second phases via Cu 2 Se alloying. Introducing Cu 2 Se enhances its electrical transport properties while reducing its lattice thermal conductivity (κlat) via weak electron–phonon coupling. Additionally, Cu 2 Te and CuGa(Te/Se) 2 (tetragonal phase) nanocrystals precipitate during the alloying process, resulting in Te vacancies and interstitial Cu in the PbTe matrix. At room temperature, Te vacancies and interstitial Cu atoms serve as n-type dopants, increasing the carrier concentration and electrical conductivity from ≈1.18 × 10 19 cm –3 and ≈1870 S cm –1 to ≈2.26 × 10 19 cm –3 and ≈3029 S cm –1 , respectively. With increasing temperature, the sample exhibits a dynamic change in Cu 2 Te content and the generation of a new phase of CuGa(Te/Se) 2 (cubic phase), strengthening the phonon scattering and obtaining an ultralow k lat . Pb 0.975 Ga 0.025 Te-3%CuSe exhibits a maximum figure of merit of ≈1.63 at 823 K, making it promising for intermediate-temperature device applications.

36 MATERIALS SCIENCE↗
NASA NTRS1995

A new technique for ground simulation of hypervelocity debris

A series of hypervelocity damage experiments were preformed on spacecraft materials. These experiments employed a technique which accelerates micro flyer plates simulating space debris traveling at 3 to 8 km/sec. The apparatus used to propel the micro flyer plates was compact and fit well into a space environmental chamber equipped with instrumentation capable of analyzing the vapor ejected from the sample. Mechanical damage to the sample was also characterized using optical and scanning electron microscpopy. Data for this work was obtained from hypervelocity impacts on a polysulfone resin and a graphite polysulfone composite. Polysulfone was selected because it was flown on the Long Duration Exposure Facility (LDEF) which spent several years in low earth orbit (LEO). Chemistry of the vapor produced by the impact was analyzed with a time of flight mass spectrometer, (TOFMS). This represents the first time that ejected vapors from hypervelocity collisions were trapped and analyzed with a mass spectrometer. With this approach we are able to study changes in the vapor chemistry as a function of time after impact, obtain a velocity measurement of the vapor, and estimate a temperature of the surface at time of impact using dynamic gas equations. Samples of the vapor plume may be captured and examined by transmission electron microscopy. Studies were also conducted to determine mechanical damage to a graphite polysulfone composite and a polysulfone resin. Impact craters were examined under optical and scanning electron microscopes. The collision craters in the matrix were typical of those shown in conventional shock experiments. However, the hypervelocity collisions with the graphite polysulfone composite were remarkably different than those with the resin.

Roybal, R.↗
DOE OSTI2023

Long-term CRISPR locus dynamics and stable host-virus co-existence in subsurface fractured shales

Viruses are the most ubiquitous biological entities on Earth. Even so, elucidating the impact of viruses on microbial communities and associated ecosystem processes often requires identification of unambiguous host-virus linkages-an undeniable challenge in many ecosystems. Subsurface fractured shales present a unique opportunity to first make these strong linkages via spacers in CRISPR-Cas arrays and subsequently reveal complex long-term host-virus dynamics. Here, we sampled two replicated sets of fractured shale wells for nearly 800 days, resulting in 78 metagenomes from temporal sampling of six wells in the Denver-Julesburg Basin (Colorado, USA). At the community level, there was strong evidence for CRISPR-Cas defense systems being used through time and likely in response to viral interactions. Within our host genomes, represented by 202 unique MAGs, we also saw that CRISPR-Cas systems were widely encoded. Together, spacers from host CRISPR loci facilitated 2,110 CRISPR-based viral linkages across 90 host MAGs spanning 25 phyla. We observed less redundancy in host-viral linkages and fewer spacers associated with hosts from the older, more established wells, possibly reflecting enrichment of more beneficial spacers through time. Leveraging temporal patterns of host-virus linkages across differing well ages, we report how host-virus co-existence dynamics develop and converge through time, possibly reflecting selection for viruses that can evade host CRISPR-Cas systems. Together, our findings shed light on the complexities of host-virus interactions as well as long-term dynamics of CRISPR-Cas defense among diverse microbial populations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Noise reduction in X-ray photon correlation spectroscopy with convolutional neural networks encoder–decoder models

Abstract Like other experimental techniques, X-ray photon correlation spectroscopy is subject to various kinds of noise. Random and correlated fluctuations and heterogeneities can be present in a two-time correlation function and obscure the information about the intrinsic dynamics of a sample. Simultaneously addressing the disparate origins of noise in the experimental data is challenging. We propose a computational approach for improving the signal-to-noise ratio in two-time correlation functions that is based on convolutional neural network encoder–decoder (CNN-ED) models. Such models extract features from an image via convolutional layers, project them to a low dimensional space and then reconstruct a clean image from this reduced representation via transposed convolutional layers. Not only are ED models a general tool for random noise removal, but their application to low signal-to-noise data can enhance the data’s quantitative usage since they are able to learn the functional form of the signal. We demonstrate that the CNN-ED models trained on real-world experimental data help to effectively extract equilibrium dynamics’ parameters from two-time correlation functions, containing statistical noise and dynamic heterogeneities. Strategies for optimizing the models’ performance and their applicability limits are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Machine learning for collective variable discovery and enhanced sampling in biomolecular simulation

Classical molecular dynamics simulates the time evolution of molecular systems through the phase space spanned by the positions and velocities of the constituent atoms. Molecular-level thermodynamic, kinetic, and structural data extracted from the resulting trajectories provide valuable information for the understanding, engineering, and design of biological and molecular materials. The cost of simulating many-body atomic systems makes simulations of large molecules prohibitively expensive, and the high-dimensionality of the resulting trajectories presents a challenge for analysis. Driven by advances in algorithms, hardware, and data availability, there has been a flare of interest in recent years in the applications of machine learning – especially deep learning – to molecular simulation. Furthermore, these techniques have demonstrated great power and flexibility in both extracting mechanistic understanding of the important nonlinear collective variables governing the dynamics of a molecular system, and in furnishing good low-dimensional system representations with which to perform enhanced sampling or develop long-timescale dynamical models. It is the purpose of this article to introduce the key machine learning approaches, describe how they are married with statistical mechanical theory into domain-specific tools, and detail applications of these approaches in understanding and accelerating biomolecular simulation.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2019

Application of the ESMACS Binding Free Energy Protocol to a Multi-Binding Site Lactate Dehydogenase A Ligand Dataset

Over the past two decades, the use of fragment-based lead generation has become a common, mature approach to identify tractable starting points in chemical space for the drug discovery process. This approach naturally involves the study of the binding properties of highly heterogeneous ligands. Such datasets challenge computational techniques to provide comparable binding free energy estimates from different binding modes. The performance of a range of statistically robust ensemble-based binding free energy calculation protocols, called ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent), is evaluated. Ligands designed to target two binding pockets in the lactate dehydogenase, a target protein, which vary in size, charge, and binding mode, are studied. When compared to experimental results, excellent statistical rankings are obtained across this highly diverse set of ligands. In addition, three approaches to account for entropic contributions are investigated: 1) normal mode analysis, 2) weighted solvent accessible surface area (WSAS), and 3) variational entropy. Normal mode analysis and WSAS correlate strongly with each other—although the latter is computationally far cheaper—but do not improve rankings. Variational entropy corrects exaggerated discrimination of ligands bound in different pockets but creates three outliers which reduce the quality of the overall ranking.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Comparing capacity coefficient and dual task assessment of visual multitasking workload

Capacity coefficient analysis could offer a theoretically grounded alternative approach to subjective measures and dual task assessment of cognitive workload. Workload capacity or workload efficiency is a human information processing modeling construct defined as the amount of information that can be processed by the visual cognitive system given a specified of amount of time. In this paper, I explore the relationship between capacity coefficient analysis of workload efficiency and dual task response time measures. To capture multitasking performance, I examine how the relatively simple assumptions underlying the capacity construct generalize beyond the single visual decision making tasks. The fundamental tools for measuring workload efficiency are the integrated hazard and reverse hazard functions of response times, which are defined by log transforms of the response time distribution. These functions are used in the capacity coefficient analysis to provide a functional assessment of the amount of work completed by the cognitive system over the entire range of response times. For the study of visual multitasking, capacity coefficient analysis enables a comparison of visual information throughput as the number of tasks increases from one to two to any number of simultaneous tasks. I illustrate the use of capacity coefficients for visual multitasking on sample data from dynamic multitasking in the modified Multi-attribute Task Battery.

capacity coefficient↗
DOE OSTI2022

Assessing entropy for catalytic processes at complex reactive interfaces

When chemical reactions are accelerated by a catalyst, entropy differences between reactants and their transient intermediates can be the driving force behind the promotion or inhibition of desired and parasitic chemical pathways. Understanding and controlling catalytic processes therefore requires both a fundamental and practicable understanding of entropy in addition to enthalpy. In unstructured media such as the vapor phase equilibrated with sparsely covered surfaces, entropy can be adequately accounted for by well-established approaches based on translational, rotational, and harmonic vibrational partition functions. However, these approximations become inadequate in more complex condensed phase environments, e.g., solid liquid interfaces of confined reaction spaces. In this chapter, we provide an overview of the state-of-art in the computational quantification of entropy and its known ramifications on catalysis. The fundamental roles of thermodynamics and kinetics in catalysis are covered in enough detail to appreciate and contextualize the computational methods employed to compute chemically accurate estimates of entropy. These methods are discussed in appropriate detail and range from the ubiquitous harmonic oscillator approximation where entropy unrelated to high frequency oscillations is typically underestimated, to enhanced free energy sampling with molecular dynamics where the desired accuracy must be weighed against the associated computational cost of obtaining it. The rising importance of machine learning and artificial intelligence in accelerating methodological progress in this field is touched upon, as well. Finally, applications, successes, and pitfalls of using these methods are provided to showcase past and present accomplishments while clarifying where improvements in both understanding and methodology are still needed.

Kollias, Loukas↗
DOE OSTI2019

phq: A Fortran code to compute phonon quasiparticle properties and dispersions

We here introduce a Fortran code that computes anharmonic free energy of solids from first-principles based on our phonon quasiparticle approach. In this code, phonon quasiparticle properties, i.e., renormalized phonon frequencies and lifetimes, are extracted from mode-projected velocity auto-correlation functions (VAF) of modes sampled by molecular dynamics (MD) trajectories. Using renormalized frequencies as input, the code next constructs an effective harmonic force constant matrix to calculate anharmonic phonon dispersions over the whole Brillouin zone and thus the anharmonic free energy in the thermodynamic limit ( N → ∞ ). A detailed description of all the input parameters and the subroutines is provided as well. We illustrate the use of this code to compute ab initio temperature-dependent anharmonic phonons of Si in the diamond structure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

The exit-wave power-cepstrum transform for scanning nanobeam electron diffraction: robust strain mapping at subnanometer resolution and subpicometer precision

Scanning nanobeam electron diffraction (NBED) with fast pixelated detectors is a valuable technique for rapid, spatially resolved mapping of lattice structure over a wide range of length scales. However, intensity variations caused by dynamical diffraction and sample mistilts can hinder the measurement of diffracted disk centers as necessary for quantification. Robust data processing techniques are needed to provide accurate and precise measurements for complex samples and non-ideal conditions. Here we present an approach to address these challenges using a transform, called the exit wave power cepstrum (EWPC), inspired by cepstral analysis in audio signal processing. The EWPC transforms NBED patterns into real-space patterns with sharp peaks corresponding to inter-atomic spacings. We describe a simple analytical model for interpretation of these patterns that cleanly decouples lattice information from the intensity variations in NBED patterns caused by tilt and thickness. With tracking the inter-atomic spacing peaks in EWPC patterns, strain mapping is demonstrated for two practical applications: mapping of ferroelectric domains in epitaxially strained PbTiO 3 films and mapping of strain profiles in arbitrarily oriented core-shell Pt-Co nanoparticle fuel-cell catalysts. The EWPC transform enables lattice structure measurement at sub-pm precision and sub-nm resolution that is robust to small sample mistilts and random orientations.

42 ENGINEERING↗
DOE OSTI2021

Single-Atom Metal Oxide Sites as Traps for Charge Separation in the Zirconium-Based Metal–Organic Framework NDC–NU-1000

Solvothermal deposition in metal–organic frameworks (MOFs) can be utilized to mount single-metal-atom catalytic species at chemically reactive sites on hexa-Zr(IV)-oxy(oxo,hydroxo,aqua) nodes in nanoscale crystallites of the MOF NDC-NU-1000 in a self-limiting fashion. Upon photoexcitation of the 1,3,6,8-tetrakis( p -benzoato)pyrene chromophores of the parent framework, charge transfer may occur between the chromophores and the installed heterometal sites. Extended X-ray absorption fine structure studies revealed the single-atom nature of the installed species. A combination of steady-state and ultrafast optical spectroscopy was utilized to uncover evidence of a charge-separated (CS) state arising in the metalated samples. The relevant dynamics were characterized with transient photoluminescence and femtosecond transient absorption spectroscopy. Here, we find that a titanium-oxy single atom site gives rise to the longest-lived CS species compared to cobalt and nickel in a similar arrangement. This study provides guidance in designing MOF-based catalytic systems for photocatalysis and solar-fuel production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Data-Driven Discovery of Linear Molecular Probes with Optimal Selective Affinity for PFAS in Water

Approaches to tackle the wide and growing variety of highly persistent per- and polyfluoroalkyl substances (PFAS) are of pressing global need because of their detrimental human health effects, such as cancer, birth defects, and hormone imbalance. Sensitive, selective, and easy-to-use real-time sensors to monitor and detect PFAS and sorbents to extract them are critical to meeting government-mandated environmental concentrations. In this work, we combine all-atom molecular dynamics simulations, enhanced sampling, deep representational learning, and Bayesian optimization to perform high-throughput virtual screening for highly sensitive and selective molecular probes. Our molecular design space consists of 3850 linear hydrocarbon chains with varying degrees of halogenation with and without amine- and phosphine-based headgroups. By employing a data-driven search process, we efficiently explore the molecular design space to optimize the sensitivity to perfluorooctanesulfonic acid (PFOS) as a prototypical PFAS analyte and selectivity relative to a sodium dodecyl sulfate (SDS) interferent. We calculate 504 Gibbs free energies of probe-analyte and probe-interferent interactions and identify probes with PFOS association free energies of up to (-ΔG PFOS ) = 9.8 ± 0.2 kJ/mol and selectivities relative to SDS of (-ΔΔG PFOS–SDS ) = 3.1 ± 1.5 kJ/mol. A C 11 Br 23 P(CH 3 ) 2 probe containing 11 backbone brominated carbons and a tertiary phosphine headgroup possesses the most sensitive binding constant to PFOS within the defined search space of K b PFOS = 177.4 ± 12.7, and a semibrominated probe C 5 H 11 C 7 Br 14 N(CH 3 ) 2 containing 12 backbone carbons and a tertiary amine headgroup possesses the highest selectivity relative to SDS of K b PFOS /K b SDS = 4.6 ± 1.7. A retrospective analysis of our data to extract interpretable design rules reveals that the sensitivity of linear hydrogenated probes increases by approximately 1 kJ/mol per C–C bond. The addition or removal of halogen atoms and amine or phosphine headgroups produces nonmonotonic changes in both sensitivity and selectivity with changes to the sensitivity of up to 2.5 kJ/mol. Finally, this work places empirical limitations on the performance of a wide range of linear probes for PFOS detection and offers a generic strategy for high-throughput computational screening to promote selective and sensitive binding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Ion Dissociation Dynamics in an Aqueous Premelting Layer

Using molecular dynamics simulations and methods of importance sampling, we study the thermodynamics and dynamics of sodium chloride in the aqueous premelting layer formed spontaneously at the interface between ice and its vapor. We uncover a hierarchy of time scales that characterize the relaxation dynamics of this system, spanning the picoseconds of ionic motion to the tens or hundreds of nanoseconds associated with fluctuations of the liquid-crystal interface in their presence. We find that ions distort both local interfaces, incurring restoring forces that result in the ions preferentially residing in the middle of the layer. While ion pair dissociation is thermodynamically favorable, these structural and dynamic effects cause its rate to vary by over an order of magnitude through the layer, with a maximum rate significantly depressed from the corresponding bulk value. The solvation environment of ions in the premelting layer is distinct from that in a bulk liquid, being dominated by slow reorganization of water molecules and a water structure intermediate between ice and its melt.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Molecular Simulations of the Hydration Behavior of a Zwitterion Brush Array and Its Antifouling Property in an Aqueous Environment

We carried out umbrella sampling and molecular dynamics (MD) simulations to investigate molecular interactions between sulfobetaine zwitterions or between sulfobetaine brushes in different media. Simulation results show that it is more energetically favorable for the two sulfobetaine zwitterions or brushes to be fully hydrated in aqueous solutions than in vacuum where strong ion pairs are formed. Structural properties of the hydrated sulfobetaine brush array and its antifouling behavior against a foulant gel are subsequently studied through steered MD simulations. We find that sulfobetaine brush arrays with different grafting densities have different structures and antifouling mechanisms. At a comparably higher grafting density, the sulfobetaine brush array exhibits a more organized structure which can hold a tightly bound hydration water layer at the interface. Compression of this hydration layer results in a strong repulsive force. However, at a comparably lower grafting density, the brush array exhibits a randomly oriented structure in which the antifouling of the brush array is through the deformation of the sulfobetaine branches.

36 MATERIALS SCIENCE↗