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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Cilia-enriched oxysterol 7β,27-DHC is required for polycystin ion channel activation

Polycystin-1 (PC-1) and PC-2 form a heteromeric ion channel complex that is abundantly expressed in primary cilia of renal epithelial cells. This complex functions as a non-selective cation channel, and mutations within the polycystin complex cause autosomal dominant polycystic kidney disease (ADPKD). The spatial and temporal regulation of the polycystin complex within the ciliary membrane remains poorly understood. Using both whole-cell and ciliary patch-clamp recordings, we identify a cilia-enriched oxysterol, 7β,27-dihydroxycholesterol (DHC), that serves as a necessary activator of the polycystin complex. We further identify an oxysterol-binding pocket within PC-2 and showed that mutations within this binding pocket disrupt 7β,27-DHC–dependent polycystin activation. Pharmacologic and genetic inhibition of oxysterol synthesis reduces channel activity in primary cilia. In summary, our findings reveal a regulator of the polycystin complex. This oxysterol-binding pocket in PC-2 may provide a specific target for potential ADPKD therapeutics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Models and Algorithms for Equilibrium Analysis of Mixed-Material Nucleic Acid Systems

Dynamic programming algorithms within the NUPACK software suite enable analysis of equilibrium base-pairing properties for complex and test tube ensembles containing arbitrary numbers of interacting nucleic acid strands. Currently, calculations are limited to single-material systems that are either all-RNA or all-DNA. Here, to enable analysis of mixed-material systems that are critical for modern applications in vitro, in situ, and in vivo, we develop physical models and dynamic programming algorithms that allow the material of the system to be specified at nucleotide resolution. Free energy parameter sets are constructed for both RNA/DNA and RNA/2'OMe-RNA mixed-material systems by combining available empirical mixed-material parameters with single-material parameter sets to enable treatment of the full complex and test tube ensembles. New dynamic programming recursions account for the material of each nucleotide throughout the recursive process. For a complex with N nucleotides, the mixed-material dynamic programming algorithms maintain the O(N 3 ) time complexity of the single-material algorithms, enabling efficient calculation of diverse physical quantities over complex and test tube ensembles (e.g., complex partition function, equilibrium complex concentrations, equilibrium base-pairing probabilities, minimum free energy secondary structure(s), and Boltzmann-sampled secondary structures) at a cost increase of roughly 2.0-3.5×. The results of existing single-material algorithms are exactly reproduced when applying the new mixed-material algorithms to single-material systems. Accuracy is significantly enhanced using mixed-material models and algorithms to predict RNA/DNA and RNA/2'OMe-RNA duplex melting temperatures from the experimental literature as well as RNA/DNA melt profiles from new experiments. In conclusion, mixed-material analyses can be performed online using the NUPACK web app (www.nupack.org) or locally using the NUPACK Python module.

2′OMe-RNA↗
DOE OSTI2025

Full complex amplitude control of second-harmonic generation via electrically tunable intersubband polaritonic metasurfaces

Nonlinear intersubband polaritonic metasurfaces based on coupling of the intersubband nonlinear optical response of quantum-engineered semiconductor heterostructures and electromagnetic modes of nanoresonators provide efficient frequency mixing with moderate pump intensities. The resonant nonlinear optical response, represented as a complex function, can be modulated via Stark tuning of intersubband transition energies under applied voltages. However, achieving full complex amplitude control (both phase and magnitude) remains challenging. In this work, we present and experimentally validate electrically tunable nonlinear intersubband polaritonic metasurfaces that achieve complete complex amplitude control for second-harmonic generation (SHG). Through a design featuring two in-plane flipped meta-atoms per unit cell, we achieve complete electrical control of both the amplitude and phase of the metasurface second-order nonlinear susceptibility, with a tuning range of 0 to 30 nm V −1 for the magnitude and 0-2π for the phase of the nonlinear optical response. Using these properties, we achieve complete on-off SHG modulation and beam diffraction tuning through electrically controlled amplitude and phase gratings.

Science & Technology - Other Topics↗
DOE OSTI2022

Physically Informed Machine Learning Prediction of Electronic Density of States

The electronic structure of a material, such as its density of states (DOS), provides key insights into its physical and functional properties and serves as a valuable source of high-quality features for many materials screening and discovery workflows. Still, the computational cost of calculating the DOS, most commonly with density functional theory (DFT), becomes prohibitive for meeting high-fidelity or high-throughput requirements, necessitating a cheaper but sufficiently accurate surrogate. To fulfill this demand, we develop a general machine learning method based on graph neural networks for predicting the DOS purely from atomic positions, six orders of magnitude faster than DFT. This approach can effectively use large materials databases and be applied generally across the entire periodic table to materials classes of arbitrary compositional and structural diversity. We furthermore devise a highly adaptable scheme for physically informed learning which encourages the DOS prediction to favor physically reasonable solutions defined by any set of desired constraints. This functionality provides a means for ensuring that the predicted DOS is reliable enough to be used as an input to downstream materials screening workflows to predict more complex functional properties, which rely on accurate physical features.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Iodate Reduction by Shewanella oneidensis Requires Genes Encoding an Extracellular Dimethylsulfoxide Reductase

Microbial iodate (IO 3 – ) reduction is a major component of the iodine biogeochemical reaction network in anaerobic marine basins and radioactive iodine-contaminated subsurface environments. Alternative iodine remediation technologies include microbial reduction of IO 3 – to iodide (I – ) and microbial methylation of I – to volatile gases. The metal reduction pathway is required for anaerobic IO 3 – respiration by the gammaproteobacterium Shewanella oneidensis . However, the terminal IO 3 – reductase and additional enzymes involved in the S. oneidensis IO 3 – electron transport chain have not yet been identified. In this study, gene deletion mutants deficient in four extracellular electron conduits (EECs; Δ mtrA , Δ mtrA -Δ mtrDEF , Δ mtrA -Δ dmsEF , Δ mtr A-ΔSO4360) and DMSO reductase (Δ dmsB ) of S. oneidensis were constructed and examined for anaerobic IO 3 – reduction activity with either 20 mM lactate or formate as an electron donor. IO 3 – reduction rate experiments were conducted under anaerobic conditions in defined minimal medium amended with 250 μM IO 3 – as anaerobic electron acceptor. Only the Δ mtrA mutant displayed a severe deficiency in IO 3 – reduction activity with lactate as the electron donor, which suggested that the EEC-associated decaheme cytochrome was required for lactate-dependent IO 3 – reduction. The Δ mtrA -Δ dmsEF triple mutant displayed a severe deficiency in IO 3 – reduction activity with formate as the electron donor, whereas Δ mtrA -Δ mtrDEF and Δ mtr A-ΔSO4360 retained moderate IO 3 – reduction activity, which suggested that the EEC-associated dimethylsulfoxide (DMSO) reductase membrane-spanning protein DmsE, but not MtrA, was required for formate-dependent IO 3 – reduction. Furthermore, gene deletion mutant Δ dmsB (deficient in the extracellular terminal DMSO reductase protein DmsB) and wild-type cells grown with tungsten replacing molybdenum (a required co-factor for DmsA catalytic activity) in defined growth medium were unable to reduce IO 3 – with either lactate or formate as the electron donor, which indicated that the DmsAB complex functions as an extracellular IO 3 – terminal reductase for both electron donors. Results of this study provide complementary genetic and phenotypic evidence that the extracellular DMSO reductase complex DmsAB of S. oneidensis displays broad substrate specificity and reduces IO 3 – as an alternate terminal electron acceptor.

, Shewanella oneidensis↗
DOE OSTI2023

Machine-learning-based spectral methods for partial differential equations

Spectral methods are an important part of scientific computing’s arsenal for solving partial differential equations (PDEs). However, their applicability and effectiveness depend crucially on the choice of basis functions used to expand the solution of a PDE. The last decade has seen the emergence of deep learning as a strong contender in providing efficient representations of complex functions. In the current work, we present an approach for combining deep neural networks with spectral methods to solve PDEs. In particular, we use a deep learning technique known as the Deep Operator Network (DeepONet) to identify candidate functions on which to expand the solution of PDEs. We have devised an approach that uses the candidate functions provided by the DeepONet as a starting point to construct a set of functions that have the following properties: (1) they constitute a basis, (2) they are orthonormal, and (3) they are hierarchical, i.e., akin to Fourier series or orthogonal polynomials. We have exploited the favorable properties of our custom-made basis functions to both study their approximation capability and use them to expand the solution of linear and nonlinear time-dependent PDEs. The proposed approach advances the state of the art and versatility of spectral methods and, more generally, promotes the synergy between traditional scientific computing and machine learning.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Effect of Methyl Groups on Formation of Ordered or Layered Graphitic Materials from Aromatic Molecules

Abstract Developing functionally complex carbon materials from small aromatic molecules requires an understanding of how the chemistry and structure of its constituent molecules evolve and crosslink, to achieve a tailorable set of functional properties. Here, molecular dynamics (MD) simulations are used to isolate the effect of methyl groups on condensation reactions during the oxidative process and evaluate the impact on elastic modulus by considering three monodisperse pyrene‐based systems with increasing methyl group fraction. A parameter to quantify the reaction progression is designed by computing the number of new covalent bonds formed. Utilizing the previously developed MD framework, it is found that increasing methylation leads to an almost doubling of bond formation, a larger fraction of the new bonds oriented in the direction of tensile stress, and a higher basal plane alignment of the precursor molecules along the direction of tensile stress, resulting in enhanced tensile modulus. Additionally, via experiments, it is demonstrated that precursors with a higher fraction of methyl groups result in a higher alignment of molecules. Moreover, increased methylation results in the lower spread of single molecule alignment which may lead to smaller variations in tensile modulus and more consistent properties in carbon materials derived from methyl‐rich precursors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Synthesis and Characterization of [Ni(H 2 O)(7-P Ph 2 N ArSO3 ) 2 ](NaBF 4 ) for Light-Driven Quantum Dot-Catalyst Hydrogen Evolution

Light-driven hydrogen generation from water is a route to carbon-neutral fuels. However, the integrated light absorbers and catalysts must be compatible and functional under the same conditions. A sulfate-functionalized complex, [Ni(H 2 O)(7-P Ph 2 N ArSO3 ) 2 ](NaBF 4 ), where P Ph 2 N ArSO3 = 4-(3,6-diphenyl-1,3,6-azadiphosphepan-1-yl)benzenesulfonate), was synthesized and characterized. A solid-state structure from single-crystal X-ray crystallography is also reported. The electrocatalytic activity for hydrogen evolution of this complex in 7:3 H 2 O:CH 3 CN was characterized by cyclic voltammetry and controlled potential electrolysis, with a maximum observed rate of 83 s –1 . Density functional theory was used to characterize the favorable binding of the sulfate functionalities to cadmium sulfide quantum dots. Experimental assembly of these catalysts onto cadmium sulfide quantum dots was successful. In conclusion, both fast electron transfer and light-driven pH-dependent hydrogen evolution were observed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Mutagenesis of Human Cytomegalovirus Glycoprotein L Disproportionately Disrupts gH/gL/gO over gH/gL/pUL128-131

Herein, cell-free and cell-to-cell spread of herpesviruses involves a core fusion apparatus comprised of the fusion protein glycoprotein B (gB) and the regulatory factor gH/gL. The human cytomegalovirus (HCMV) gH/gL/gO and gH/gL/pUL128-131 facilitate spread in different cell types. The gO and pUL128-131 components bind distinct receptors, but how the gH/gL portions of the complexes functionally compare is not understood. We previously characterized a panel of gL mutants by transient expression and showed that many were impaired for gH/gL-gB-dependent cell-cell fusion but were still able to form gH/gL/pUL128-131 and induce receptor interference. Here, the gL mutants were engineered into the HCMV BAC clones TB40/e-BAC4 (TB), TR, and Merlin (ME), which differ in their utilization of the two complexes for entry and spread. Several of the gL mutations disproportionately impacted gH/gL/gO-dependent entry and spread over gH/gL/pUL128-131 processes. The effects of some mutants could be explained by impaired gH/gL/gO assembly, but other mutants impacted gH/gL/gO function. Soluble gH/gL/gO containing the L201 mutant failed to block HCMV infection despite unimpaired binding to PDGFRα, indicating the existence of other important gH/gL/gO receptors. Another mutant (L139) enhanced the gH/gL/gO-dependent cell-free spread of TR, suggesting a “hyperactive” gH/gL/gO. Recently published crystallography and cryo-electron microscopy studies suggest structural conservation of the gH/gL underlying gH/gL/gO and gH/gL/pUL128-131. However, our data suggest important differences in the gH/gL of the two complexes and support a model in which gH/gL/gO can provide an activation signal for gB.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Peptoid-directed assembly of CdSe nanoparticles

The high information content of proteins drives their hierarchical assembly and complex function, including the organization of inorganic nanomaterials. Peptoids offer an organic scaffold very similar to proteins, but with a wider solubility range and easily tunable side chains and functional groups to create a variety of self-assembling architectures with atomic precision. If we could harness this paradigm and understand the factors that govern how they direct nucleation and assembly of inorganic materials to design order within such materials, new dimensions of function and fundamental science would emerge. In this work, peptoid tubes and sheets were explored as platforms to assemble colloidal quantum dots (QDs) and clusters. We have successfully synthesized CdSe QDs with difunctionalized capping ligands containing both carboxylic acid and thiol groups and mixed them with maleimide containing peptoids, to create an assembly of the QDs on the peptoid surface via a covalent linkage. This conjugation was seen to be successful with peptoid tubes, sheets and CdSe QDs and clusters. The particles were seen to have a high preference for the peptoid surface but non-specific interactions with carboxylic acid groups on the peptoids limited control over QD density via maleimide conjugation. Replacing the carboxylic acid groups with methoxy ethers, however, allowed for control over QD density as a function of maleimide concentration. 1 H NMR analysis demonstrated that binding of QDs to peptoids involved a subset of surface ligands bound through the carboxylate functional group, allowing the distal thiol to engage in a covalent linkage to the maleimide. Overall, we have shown the compatibility and control of CdSe-peptoid interactions via a covalent linkage with varying peptoid structures and CdSe particles to create complex hybrid structures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Ligand Noninnocence in β-Diketiminate and β-Diketimine Copper Complexes

Metal–ligand cooperative systems have a long precedent in catalysis, with the classification depending on the site of substrate bond cleavage and formation and on redox state changes. Recently, our group reported the participation of a β-diketiminate ligand in chemical bonding to heterocumulenes such as CO 2 and CS 2 by tricopper complexes, leading to cooperative catalysis. Herein, we report the reactivity of these copper clusters, [Cu 3 EL] – (E = S, Se; L = tris(β-diketiminate) cyclophane ligand), toward other electrophiles, viz. alkyl halides and Brønsted acids. We identified a family of ligand-functionalized complexes, Cu 3 EL (R) (R = primary alkyls), and a series of disubstituted products, Cu 3 EL (R) 2 , through single-crystal X-ray diffraction, mass spectrometry, and infrared and UV–visible spectroscopy. Furthermore, as part of mechanistic studies on these alkylation reactions, we evaluated the acid–base reactivity of these complexes and the influence of the backbone substitution on the reduction potential. Implications of these findings for ligand noninnocence and the relevance of the metal core as a cofactor for the ligand’s reactivity are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Fault Network Geometry Modulates Earthquake Source Spectra Across Scales

Earthquake source spectra provide unique insights into the earthquake rupture process. Motivated by previous research suggesting that complex fault geometries enhance high‐frequency seismic radiation, we study the influence of fault network geometry on earthquake source spectra using multiple independent observations. At regional scales, we examine correlations of stress drop measurements with surface fault trace misalignment in Southern California, Japan, and Central Italy. At a global scale, we examine correlations of moment‐rate function complexity of large earthquakes with focal mechanism variability, a proxy for local fault complexity. Despite significant scatter in the observations, we find overall consistent positive correlations. The concept that elastic interactions of discrete fault structures during the earthquake rupture process generates high‐frequency ground motions offers a coherent framework for interpreting our observations. These findings suggest that variations in fault complexity explain why some earthquakes produce stronger high‐frequency ground motions than others.

Lee, Jaeseok [Brown Univ., Providence, RI (United ↗
DOE OSTI2023

Editorial: Functional microcircuits in the brain and in artificial intelligent systems

Fundamental principles underlying higher-order cognitive functions remain elusive, but recent breakthroughs in neurophysiology and deep learning offer new perspectives. First, experimental studies have uncovered neural circuit motifs consisting of various neuron types; see Brain Initiative Cell Census Network (https://www.nature.com/collections/cicghheddj). For example, inhibitory neuron types expressing exclusive genes have specific targets and distinct functions (Pfeffer et al., 2013). Furthermore, diverse neuron types in cortex and their connectomes were identified in cortical columns (Jiang et al., 2015); see also Barth et al. (2016) for a debate on neuron types. Second, artificial neural networks were originally inspired by structures of the brain (McCulloch and Pitts, 1943) and could be trained to perform complex functions similar to human perception/cognition by deep learning (DL) (Lecun et al., 2015).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

In situ/operando soft x-ray spectroscopy of chemical interfaces in gas and liquid environments

Many energy storage and energy conversion systems are based on the complexity of material architecture, chemistry, and interfacial interactions. To understand and thus ultimately control the energy applications calls for in situ/operando characterization tools. Over the years, in situ/operando soft x-ray spectroscopy has been developed for the studies of gas molecules, molecular liquids, catalytic, and electrochemical reactions. Soft x-ray spectroscopy offers electronic structure characterization of materials in energy conversion, energy storage, and catalysis regarding functionality, complexity of material architecture, and chemical interactions. It has been shown how to use the powerful in situ/operando soft x-ray spectroscopy characterization techniques of interfacial phenomena and how to reveal the mechanism of charge transfer and chemical transformation of solid/gas and solid/liquid interfaces of energy storage and catalytic materials in a realistic environment. It has been demonstrated how to overcome the challenge that soft x-rays cannot easily peek into the high-pressure catalytic or liquid electrochemical reactions. Finally, the unique design of in situ/operando soft x-ray spectroscopy instrumentation and fabrication principle and examples of experiments are presented.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Predictor-corrector models for lightweight massive machine-type communications in Industry 4.0

Future Industry 4.0 scenarios are characterized by seamless integration between computational and physical processes. To achieve this objective, dense platforms made of small sensing nodes and other resource constraint devices are ubiquitously deployed. All these devices have a limited number of computational resources, just enough to perform the simple operation they are in charge of. The remaining operations are delegated to powerful gateways that manage sensing nodes, but resources are never unlimited, and as more and more devices are deployed on Industry 4.0 platforms, gateways present more problems to handle massive machine-type communications. Although the problems are diverse, those related to security are especially critical. To enable sensing nodes to establish secure communications, several semiconductor companies are currently promoting a new generation of devices based on Physical Unclonable Functions, whose usage grows every year in many real industrial scenarios. Those hardware devices do not consume any computational resource but force the gateway to keep large key-value catalogues for each individual node. In this context, memory usage is not scalable and processing delays increase exponentially with each new node on the platform. In this paper, we address this challenge through predictor-corrector models, representing the key-value catalogues. Models are mathematically complex, but we argue that they consume less computational resources than current approaches. The lightweight models are based on complex functions managed as Laurent series, cubic spline interpolations, and Boolean functions also developed as series. Unknown parameters in these models are predicted, and eventually corrected to calculate the output value for each given key. The initial parameters are based on the Kane Yee formula. An experimental analysis and a performance evaluation are provided in the experimental section, showing that the proposed approach causes a significant reduction in the resource consumption.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Simple and Accurate One-Body Energy and Dipole Moment Surfaces for Water and Beyond

Water is often the testing ground for new, advanced force fields. While advanced functional forms for intermolecular interactions have been integral to the development of accurate water models, less attention has been paid to a transferable model for intramolecular valence terms. In this work, we present a one-body energy and dipole moment surface model, named 1B-UCB, that is simple yet accurate and can be feasibly adapted for both standard and advanced potentials. 1B-UCB for water is comparable in accuracy to those with much more complex functional forms, despite having drastically fewer parameters. The parametrization protocol has been implemented as part of the Q-Force automated workflow and requires only a quantum mechanical Hessian calculation as reference data, hence allowing it to be easily extended to a variety of molecular systems beyond water, which we demonstrate on a selection of small molecules with different symmetries.

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

Graphically Contracted Function Construction with the Recursive Pairwise Merge Algorithm

A new implementation of a recursive pairwise merge algorithm to construct a GCF from a list of CSF expansion coefficients is presented. The essential new feature is the preallocation of some work arrays used within the intermediate steps of the merge procedure. This results in roughly an order of magnitude improvement in overall efficiency and also approximately eliminates a factor of n, the molecular orbital dimension, from the original implementation. Initial application of this merge procedure to a series of H m molecules shows that the GCF wave functions can be represented well both with delocalized canonical Hartree-Fock orbitals and with localized molecular orbitals. Finally, for a given wave function complexity, as measured by the average facet count, $\bar{\text {f}}$, the delocalized Hartree-Fock orbitals show smaller errors for small $\bar{\text {f}}$ values, while the localized orbitals show smaller errors for larger $\bar{\text {f}}$ values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗