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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Water-enhanced bifunctional metal-acid catalyst for C=C bond hydrogenation

Water-assisted proton shuttling can promote hydrogenation of polar functional groups, and it is generally believed that such an effect can be hardly applied to hydrogenation of C═C bonds due to the latter's weak interaction with water. Here, we report density functional theory calculations and metadynamics simulations, through which we show a dynamic bifunctional metal–acid site that can be transformed, when interacting with water, into an active configuration for unexpected water-enhanced proton shuttling to C═C bonds. In particular, we investigated B(OH)3 anchored to a Ni catalyst for hydrogenation of cyclohexene in an organic solvent, which showed in experiments an increased rate by 100 times when adding a small amount of water. Metadynamics simulations suggest that a B(OH)3–H2O cluster can form on Ni(111), which promotes the proton transfer in the first hydrogenation step, while the second hydrogenation is still driven by metal-mediated direct H-transfer. The recovery process of B(OH)3–H2O also involves a proton shuttling step. We find that the boric species on the surface serves as an electron reservoir and carries the negative charge to balance the positive charge in the proton transfer steps. This work thus provides fundamental insights into this dynamic transformation process of the metal–acid interface, which can in principle be applied to many other bifunctional systems for hydrogenating non-polar unsaturated groups by engineering the interfacial charge separation.

Sun, Shoutian↗
DOE OSTI2020

Insights into the unique carboxylation reactions in the metabolism of propylene and acetone

Alkenes and ketones are two classes of ubiquitous, toxic organic compounds in natural environments produced in several biological and anthropogenic processes. In spite of their toxicity, these compounds are utilized as primary carbon and energy sources or are generated as intermediate metabolites in the metabolism of other compounds by many diverse bacteria. The aerobic metabolism of some of the smallest and most volatile of these compounds (propylene, acetone, isopropanol) involves novel carboxylation reactions resulting in a common product acetoacetate. Propylene is metabolized in a four-step pathway involving five enzymes where the penultimate step is a carboxylation reaction catalyzed by a unique disulfide oxidoreductase that couples reductive cleavage of a thioether linkage with carboxylation to produce acetoacetate. The carboxylation of isopropanol begins with conversion to acetone via an alcohol dehydrogenase. Acetone is converted to acetoacetate in a single step by an acetone carboxylase which couples the hydrolysis of MgATP to the activation of both acetone and bicarbonate, generating highly reactive intermediates that are condensed into acetoacetate at a Mn2+ containing the active site. Acetoacetate is then utilized in central metabolism where it is readily converted to acetyl-coenzyme A and subsequently converted into biomass or utilized in energy metabolism via the tricarboxylic acid cycle. This review summarizes recent structural and biochemical findings that have contributed significant insights into the mechanism of these two unique carboxylating enzymes.

Biochemistry & Molecular Biology↗
DOE OSTI2020

A brief note on the properties of linear pathways

Linear metabolic pathways are the simplest network architecture we find in metabolism and are a good starting point to gain insight into the operating principles of metabolic control. Linear pathways possess some well-known properties, such as a bias of flux control towards the first few steps of the pathway as well as the lack of flux control at reactions close to equilibrium. In both cases, a rationale for these behaviors is given in terms of how elasticities transmit changes through a pathway. A discussion is given on the fundamental role that two reaction step sections play in a linear pathway when transmitting changes. For a pathway with irreversible steps, the deconstruction is straight forward and includes a product of local response coefficients that cascade along the pathway. When reversibility is included, the picture became more complex but a relationship in terms of the local response coefficients if derived that includes the reverse response coefficients and highlights the interplay between the forward and backward transmission of changes during a perturbation.

Biochemistry & Molecular Biology↗
DOE OSTI2020

Strong dependence of Type Ia supernova standardization on the local specific star formation rate

As part of an on-going effort to identify, understand and correct for astrophysics biases in the standardization of Type Ia supernovae (SN Ia) for cosmology, we have statistically classified a large sample of nearby SNe Ia into those that are located in predominantly younger or older environments. This classification is based on the specific star formation rate measured within a projected distance of 1 kpc from each SN location (LsSFR). This is an important refinement compared to using the local star formation rate directly, as it provides a normalization for relative numbers of available SN progenitors and is more robust against extinction by dust. We find that the SNe Ia in predominantly younger environments are Δ Y = 0.163 ± 0.029 mag (5.7 σ ) fainter than those in predominantly older environments after conventional light-curve standardization. This is the strongest standardized SN Ia brightness systematic connected to the host-galaxy environment measured to date. The well-established step in standardized brightnesses between SNe Ia in hosts with lower or higher total stellar masses is smaller, at Δ M = 0.119 ± 0.032 mag (4.5 σ ), for the same set of SNe Ia. When fit simultaneously, the environment-age offset remains very significant, with Δ Y = 0.129 ± 0.032 mag (4.0 σ ), while the global stellar mass step is reduced to Δ M = 0.064 ± 0.029 mag (2.2 σ ). Thus, approximately 70% of the variance from the stellar mass step is due to an underlying dependence on environment-based progenitor age. Also, we verify that using the local star formation rate alone is not as powerful as LsSFR at sorting SNe Ia into brighter and fainter subsets. Standardization that only uses the SNe Ia in younger environments reduces the total dispersion from 0.142 ± 0.008 mag to 0.120 ± 0.010 mag. Overall, we show that as environment-ages evolve with redshift, a strong bias, especially on the measurement of the derivative of the dark energy equation of state, can develop. Fortunately, data that measure and correct for this effect using our local specific star formation rate indicator, are likely to be available for many next-generation SN Ia cosmology experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Migration to WebDAV in Belle II Experiment

The usage of WebDAV protocol has become more and more popular within the physics experiments using grid middleware in the last decade, and today it represents a valid alternative to the GridFTP currently supported at best-effort level after the retirement of Globus Toolkit. Belle II experiment established the adoption of WebDAV protocol as the main protocol for data access and third-party-copy transfers, without relying on Storage Resource Manager interface (SRM). The migration process, carried on with continuous and gradual steps, has required a large effort to guarantee a smooth transition maintaining the production infrastructure fully operational. In this contribution we show the transition process, the tool of support developed to monitor step by step the status of third-party-copy support with WebDAV protocol by storages of the collaboration tested in both case pull and push, the strategy adopted to configure DIRAC and the solutions put in place for the corner cases. Finally, we will present some statistics of utilization and we will analyse the achieved results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Influence of substrate misorientation on the optical properties of Mg-doped GaN

The GaN substrate miscut angle has a significant effect on the optical properties of Mg-doped GaN grown by metal-organic chemical vapor deposition. We have studied the optical properties of epilayers grown on c-plane GaN wafers with nominal miscut angles of 0.3° and 4° toward the [11¯00] direction. Periodic surface steps are observed in thin films grown on 0.3° miscut substrates. The step separation and height, as well as the surface roughness, increase with layer thickness, leading to a decrease in Mg doping efficiency. For films grown on 4° miscut substrates, step bunching causes the formation of visually observable wavy features on the film surface with strong spatial variations in cathodoluminescence characteristics, indicating a significant effect of surface morphology on the nature of Mg incorporation and p-type characteristics.

Liu, Hanxiao (ORCID:0000000331067542)↗
DOE OSTI2020

Surface structure of linear nanopores in amorphous silica: Comparison of properties for different pore generation algorithms

In this work, we compare the surface structure of linear nanopores in amorphous silica (a-SiO 2 ) for different versions of “pore drilling” algorithms (where the pores are generated by the removal of atoms from the preformed bulk a-SiO 2 ) and for “cylindrical resist” algorithms (where a-SiO 2 is formed around a cylindrical exclusion region). After adding H to non-bridging O, the former often results in a moderate to high density of surface silanol groups, whereas the latter produces a low density. The silanol surface density for pore drilling can be lowered by a final dehydroxylation step, and that for the cylindrical resist approach can be increased by a final hydroxylation step. In this respect, the two classes of algorithms are complementary. We focus on the characterization of the chemical structure of the pore surface, decomposing the total silanol density into components corresponding to isolated and vicinal mono silanols and geminal silanols. The final dehyroxylation and hydroxylation steps can also be tuned to better align some of these populations with the target experimental values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Surface facet dependence of competing alloying mechanisms

Metal alloys are ubiquitous in many branches of heterogeneous catalysis, and it is now fairly well established that the local atomic structure of an alloy can have a profound influence on its chemical reactivity. While these effects can be difficult to probe in nanoparticle catalysts, model studies using well defined single crystal surfaces alloyed with dopants enable these structure–function correlations to be drawn. The first step in this approach involves understanding the alloying mechanism and the type of ensembles formed. In this study, we examined the atomic structure of RhCu single-atom alloys formed on Cu(111), Cu(100), and Cu(110) surfaces. Our results show a striking difference between Rh atoms alloying in Cu(111) vs the more open Cu(100) and Cu(110) surface facets. Unlike Cu(111) on which Rh atoms preferentially place-exchange with Cu atoms in the local regions above step edges leaving the majority of the Cu surface free of Rh, highly dispersed, homogeneous alloys are formed on the Cu(100) and (110) surfaces. These dramatically different alloying mechanisms are understood by quantifying the energetic barriers for atomic hopping, exchange, swapping, and vacancy filling events for Rh atoms on different Cu surfaces through theoretical calculations. Density functional theory results indicate that the observed differences in the alloying mechanism can be attributed to a faster hopping rate, relatively high atomic exchange barriers, and stronger binding of Rh atoms in the vicinity of step edges on Cu(111) compared to Cu(110) and Cu(100). Furthermore, these model systems will serve as useful platforms for examining structure sensitive chemistry on single-atom alloys.

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

Reactive burn model calibration using high-throughput initiation experiments at sub-millimeter length scales

We report a first-of-its-kind model calibration was performed using Sandia National Laboratories’ high-throughput initiation (HTI) experiment for two types of vapor-deposited explosive films consisting of hexanitrostilbene (HNS) or pentaerythritol tetranitrate (PETN). These films exhibit prompt initiation, and they reach steady detonation at sub-millimeter length scales. Following prior work on HNS, we test the hypothesis of approximating these explosive films as fine-grained homogeneous solids with simple Arrhenius kinetics burn models. The model calibration process is described herein using a single-step as well as a two-step Arrhenius rate law, and it consists of systematic parameter sampling leading to a reduction in the model degrees of freedom. Multiple local minima are observed; results are given for seven different optimized parameter sets. Each model set is further evaluated in a two-dimensional simulation of the critical failure thickness for a sustained detonation. Overall, the two-step Arrhenius kinetics model captures the observed behavior for HNS; however, neither model produces a good fit to the PETN data. We hypothesize that the HTI results for PETN correspond to a heterogeneous response, owing to the smaller reaction zone of PETN compared to HNS (i.e., it does not homogenize the fine-grained hot spots as well). Future work should consider using the ignition and growth model for PETN, as well as other reactive burn models such as xHVRB, AWSD, PiSURF, and CREST.

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

An intermediate model for fitting triplet–triplet annihilation in phosphorescent organic light emitting diode materials

Triplet–triplet annihilation (TTA) is one of the primary contributors to efficiency roll-off and permanent material degradation in phosphorescent organic light-emitting diodes. Here, the two limiting case models typically used to quantify this quenching mechanism are multi-step Dexter and single-step Förster, which, respectively, assume ideal Fickian diffusion or perfect trapping of triplet excitons. For device-relevant guest doping levels (typically 5–12 vol. %), both significant diffusion of excitons and trapping due to spatial and energetic disorder exist, so neither conventional model fits experimental data well. We develop and validate an intermediate TTA model, which is a weighted average of the limiting cases of pure radiative decay (no TTA) and multi-step Dexter based TTA that returns an effective TTA rate constant and a parameter quantifying the portion of well-isolated excitons. Kinetic Monte-Carlo simulations and time-resolved photoluminescence measurements of an archetype host–guest system demonstrate that our intermediate model provides significantly improved fits with more realistic physical values, is more robust to variations in experimental conditions, and provides an analysis framework for the effects of trapping on TTA.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Direct implicit and explicit energy-conserving particle-in-cell methods for modeling of capacitively coupled plasma devices

Achieving large-scale kinetic modeling is a crucial task for the development and optimization of modern plasma devices. With the trend of decreasing pressure in applications, such as plasma etching, kinetic simulations are necessary to self-consistently capture the particle dynamics. The standard, explicit, electrostatic, momentum-conserving particle-in-cell method suffers from restrictive stability constraints on spatial cell size and temporal time step, requiring resolution of the electron Debye length and electron plasma period, respectively. This results in a very high computational cost, making the technique prohibitive for large volume device modeling. We investigate the direct implicit algorithm and the explicit energy conserving algorithm as alternatives to the standard approach, both of which can reduce computational cost with a minimal (or controllable) impact on results. These algorithms are implemented into the well-tested EDIPIC-2D and LTP-PIC codes, and their performance is evaluated via 2D capacitively coupled plasma discharge simulations. The investigation reveals that both approaches enable the utilization of cell sizes larger than the Debye length, resulting in a reduced runtime, while incurring only minor inaccuracies in plasma parameters. The direct implicit method also allows for time steps larger than the electron plasma period; however, care must be taken to avoid numerical heating or cooling. It is demonstrated that by appropriately adjusting the ratio of cell size to time step, it is possible to mitigate this effect to an acceptable level.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Decoding diffraction and spectroscopy data with machine learning: A tutorial

This Tutorial provides a step-by-step guide on how to apply supervised machine-learning techniques to analyze diffraction and spectroscopy data. This Tutorial details four models—a reconstruction-focused model, a regression-focused model, a hybrid reconstruction/regression model, and a multimodal model—that use x-ray diffraction profiles and vibrational density of states spectra to predict various microstructural descriptors. In this Tutorial, we cover data pre-processing steps, constructions of the models via dimensionality reduction and regression, training, and analysis of these models. Comparisons of the model’s performance are provided, highlighting the strength and weakness of the various approaches utilized.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Computational prediction of the effect of amino acid changes on the binding affinity between SARS-CoV-2 spike RBD and human ACE2

The association of the receptor binding domain (RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein with human angiotensin-converting enzyme 2 (hACE2) represents the first required step for cellular entry. SARS-CoV-2 has continued to evolve with the emergence of several novel variants, and amino acid changes in the RBD have been implicated with increased fitness and potential for immune evasion. Reliably predicting the effect of amino acid changes on the ability of the RBD to interact more strongly with the hACE2 can help assess the implications for public health and the potential for spillover and adaptation into other animals. Here, we introduce a two-step framework that first relies on 48 independent 4-ns molecular dynamics (MD) trajectories of RBD-hACE2 variants to collect binding energy terms decomposed into Coulombic, covalent, van der Waals, lipophilic, generalized Born solvation, hydrogen bonding, π-π packing, and self-contact correction terms. The second step implements a neural network to classify and quantitatively predict binding affinity changes using the decomposed energy terms as descriptors. The computational base achieves a validation accuracy of 82.8% for classifying single–amino acid substitution variants of the RBD as worsening or improving binding affinity for hACE2 and a correlation coefficient of 0.73 between predicted and experimentally calculated changes in binding affinities. Both metrics are calculated using a fivefold cross-validation test. Our method thus sets up a framework for screening binding affinity changes caused by unknown single– and multiple–amino acid changes offering a valuable tool to predict host adaptation of SARS-CoV-2 variants toward tighter hACE2 binding.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Entropic control of the free-energy landscape of an archetypal biomolecular machine

Biomolecular machines are complex macromolecular assemblies that utilize thermal and chemical energy to perform essential, multistep, cellular processes. Despite possessing different architectures and functions, an essential feature of the mechanisms of action of all such machines is that they require dynamic rearrangements of structural components. Surprisingly, biomolecular machines generally possess only a limited set of such motions, suggesting that these dynamics must be repurposed to drive different mechanistic steps. Although ligands that interact with these machines are known to drive such repurposing, the physical and structural mechanisms through which ligands achieve this remain unknown. Using temperature-dependent, single-molecule measurements analyzed with a time-resolution-enhancing algorithm, here, we dissect the free-energy landscape of an archetypal biomolecular machine, the bacterial ribosome, to reveal how its dynamics are repurposed to drive distinct steps during ribosome-catalyzed protein synthesis. Specifically, we show that the free-energy landscape of the ribosome encompasses a network of allosterically coupled structural elements that coordinates the motions of these elements. Moreover, we reveal that ribosomal ligands which participate in disparate steps of the protein synthesis pathway repurpose this network by differentially modulating the structural flexibility of the ribosomal complex (i.e., the entropic component of the free-energy landscape). Here, we propose that such ligand-dependent entropic control of free-energy landscapes has evolved as a general strategy through which ligands may regulate the functions of all biomolecular machines. Such entropic control is therefore an important driver in the evolution of naturally occurring biomolecular machines and a critical consideration for the design of synthetic molecular machines.

Science & Technology - Other Topics↗
DOE OSTI2024

Homologous mutations in human β, embryonic, and perinatal muscle myosins have divergent effects on molecular power generation

Mutations at a highly conserved homologous residue in three closely related muscle myosins cause three distinct diseases involving muscle defects: R671C in β-cardiac myosin causes hypertrophic cardiomyopathy, R672C and R672H in embryonic skeletal myosin cause Freeman–Sheldon syndrome, and R674Q in perinatal skeletal myosin causes trismus-pseudocamptodactyly syndrome. It is not known whether their effects at the molecular level are similar to one another or correlate with disease phenotype and severity. To this end, we investigated the effects of the homologous mutations on key factors of molecular power production using recombinantly expressed human β, embryonic, and perinatal myosin subfragment-1. We found large effects in the developmental myosins but minimal effects in β myosin, and magnitude of changes correlated partially with clinical severity. The mutations in the developmental myosins dramatically decreased the step size and load-sensitive actin-detachment rate of single molecules measured by optical tweezers, in addition to decreasing overall enzymatic (ATPase) cycle rate. In contrast, the only measured effect of R671C in β myosin was a larger step size. Our measurements of step size and bound times predicted velocities consistent with those measured in an in vitro motility assay. Finally, molecular dynamics simulations predicted that the arginine to cysteine mutation in embryonic, but not β, myosin may reduce pre-powerstroke lever arm priming and ADP pocket opening, providing a possible structural mechanism consistent with the experimental observations. This paper presents direct comparisons of homologous mutations in several different myosin isoforms, whose divergent functional effects are a testament to myosin’s highly allosteric nature.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Hopping and crawling DNA-coated colloids

Understanding the motion of particles with multivalent ligand-receptors is important for biomedical applications and material design. Yet, even among a single design, the prototypical DNA-coated colloids, seemingly similar micrometric particles hop or roll, depending on the study. We shed light on this problem by observing DNA-coated colloids diffusing near surfaces coated with complementary strands for a wide array of coating designs. We find colloids rapidly switch between 2 modes: They hop—with long and fast steps—and crawl—with short and slow steps. Both modes occur at all temperatures around the melting point and over various designs. The particles become increasingly subdiffusive as temperature decreases, in line with subsequent velocity steps becoming increasingly anticorrelated, corresponding to switchbacks in the trajectories. Overall, crawling (or hopping) phases are more predominant at low (or high) temperatures; crawling is also more efficient at low temperatures than hopping to cover large distances. We rationalize this behavior within a simple model: At lower temperatures, the number of bound strands increases, and detachment of all bonds is unlikely, hence, hopping is prevented and crawling favored. We thus reveal the mechanism behind a common design rule relying on increased strand density for long-range self-assembly: Dense strands on surfaces are required to enable crawling, possibly facilitating particle rearrangements.

Science & Technology - Other Topics↗
DOE OSTI2020

A requirement for an active proton delivery network supports a compound I-mediated C–C bond cleavage in CYP51 catalysis

CYP51 enzymes (sterol 14α-demethylases) are cytochromes P450 that catalyze multistep reactions. The CYP51 reaction occurs in all biological kingdoms and is essential in sterol biosynthesis. It removes the 14α-methyl group from cyclized sterol precursors by first forming an alcohol, then an aldehyde, and finally eliminating formic acid with the introduction of a Δ14–15 double bond in the sterol core. The first two steps are typical hydroxylations, mediated by an electrophilic compound I mechanism. The third step, C–C bond cleavage, has been proposed to involve either compound I (i.e. FeO 3+ ) or, alternatively, a proton transfer-independent nucleophilic ferric peroxo anion (compound 0, i.e. Fe 3+ O 2 – ). In this work, using comparative crystallographic and biochemical analyses of WT human CYP51 (CYP51A1) and its D231A/H314A mutant, whose proton delivery network is destroyed (as evidenced in a 1.98-Å X-ray structure in complex with lanosterol), we demonstrate that deformylation of the 14α-carboxaldehyde intermediate requires an active proton relay network to drive the catalysis. These results indicate a unified, compound I-based mechanism for all three steps of the CYP51 reaction, as previously established for CYP11A1 and CYP19A1. We anticipate that our approach can be applied to mechanistic studies of other P450s that catalyze multistep reactions, such as C–C bond cleavage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Nonlinear Elimination Applied to Radiation Diffusion

We apply a nonlinearly preconditioned, quasi-Newton framework to accelerate the numerical solution of the thermal radiative transfer (TRT) equations. This framework was inspired by the unpublished method that has existed for years in Teton, Lawrence Livermore National Laboratory’s deterministic TRT code. In this paper, we cast this iteration scheme within a formal nonlinear preconditioning framework and compare its performance against other iteration schemes in the framework. With proper choices of iteration controls for the various levels of the solver, we can recover the standard linearized one-step method, a full nonlinear Newton scheme, as well as the method in Teton. In brief, the nonlinear preconditioning TRT scheme formally eliminates the material temperature equation from the nonlinear system in a nonlinear analog of a Schur complement. This nonlinear elimination step involves solving a decoupled nonlinear equation for each spatial degree of freedom and is therefore inexpensive. By applying a quasi-Newton iteration scheme on the new system, we obtain a three-level iteration scheme that is at least as efficient as commonly used TRT schemes. The new method allows full convergence to the nonlinear backward Euler time-discretized system, increasing accuracy and robustness, while using a similar number of linear iterations as the more common linearized one-step methods Eq. (4).

77 NANOSCIENCE AND NANOTECHNOLOGY↗