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At least 721 records · Page 40

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DOE OSTI2020

In Silico Insights into Protein–Protein Interaction Disruptive Mutations in the PCSK9-LDLR Complex

Gain-of-function mutations in PCSK9 (proprotein convertase subtilisin/kexin type 9) lead to reduced uptake of LDL (low density lipoprotein) cholesterol and, therefore, increased plasma LDL levels. However, the mechanism by which these mutants reduce LDL reuptake is not fully understood. Here, we have used molecular dynamics simulations, MM/PBSA (Molecular Mechanics/Poisson–Boltzmann Surface Area) binding affinity calculations, and residue interaction networks, to investigate the protein–protein interaction (PPI) disruptive effects of two of PCSK9's gain-of-function mutations, Ser127Arg and Asp374Tyr on the PCSK9 and LDL receptor complex. In addition to these PPI disruptive mutants, a third, non-interface mutation (Arg496Trp) is included as a positive control. Our results indicate that Ser127Arg and Asp374Tyr confer significantly improved binding affinity, as well as different binding modes, when compared to the wild-type. These PPI disruptive mutations lie between the EGF(A) (epidermal growth factor precursor homology domain A) of the LDL receptor and the catalytic domain of PCSK9 (Asp374Tyr) and between the prodomain of PCSK9 and the β-propeller of the LDL receptor (Ser127Arg). The interactions involved in these two interfaces result in an LDL receptor that is sterically inhibited from entering its closed conformation. This could potentially implicate the prodomain as a target for small molecule inhibitors.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

FInd Gas Source

FIGS is a neural network software that ingests real time synchronized field data on environmental flow fields and turbulence and gas concentration variations at high frequency and uses an error minimization algorithm to locate the gas source and quantify its strength. The software can be interfaced with atmospheric, oceanic and subsurface instruments in a variety of platforms stationary or mobile (e.g. cars, UAVs, submersible vehicles or boreholes) and used to find gas sources by smart use of data and phenomenology. FIGS can be trained by phenomenological model of the flow fields in the environment of interest and/or be calibrated by controlled release. After initial deployment the FIGS learning will grow with time as it accumulates data on source quantification. FIGS can be installed on any computer from small beagle-bones for field deployment/end-use to PC/MACs/main-frame for training/analysis. FIGS has been trained (using LANL's high resolution atmospheric simulations) and calibrated, tested and evaluated in the field and shown to perform well in finding and quantifying methane leaks at 10-100m scales at well pads by ingesting atmospheric measurements. The code is applicable to gas and particle source location at large scales.

Travis, Bryan↗

DOE OSTI2025

Ir(hkl) Surface Electrochemistry in a Nonadsorbing Acidic Medium

The fundamental properties of electrochemical materials depend on the multiple and often complex interactions between electrode surface sites and electrolyte species at the electrochemical interface. Despite Iridium use in electrolyzer systems, much of its surface electrochemistry remains underexplored. This study investigates the surface electrochemistry of Ir(111), Ir(100), and Ir(110) surfaces in acidic media. Using cyclic voltammetry and CO charge displacement experiments, we establish the charge states and adsorbate coverages as a function of the electrode potential, revealing the presence of hydrogen and hydroxyl co-adsorption at low potentials on (111), and almost no coverage of H ad on (110) facet. In situ Shell Isolated Nanoparticle Enhanced Raman Spectroscopy experiments provide direct evidence of the formation of key adsorbate species, such as hydrogen, hydroxyl, and oxygen, but most importantly, their interactions with interfacial water, confirmed by Density Functional Theory calculations. Our findings highlight the role of co-adsorption and interspecies interactions, with microkinetic adsorption voltammetry simulations corroborating the influence of lateral interactions on adsorption dynamics, particularly for Ir(100) where the OHad formation occurs as a sharp adsorption/desorption current. Our results underscores the importance of interfacial water and hydrogen bonding networks in shaping the electrochemical behavior on Ir surfaces, refining our baseline understanding of the Ir surface electrochemistry necessary for the development of advanced Ir-based electrochemical materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

A high-dimensional neural network potential for molecular dynamics simulations of condensed phase nickel and phase transitions

A high-dimensional neural network interatomic potential was developed and used in molecular dynamics simulations of condensed phase Ni and Ni systems with liquid–solid phase coexistence. The reference data set was generated by sampling the potential energy surface over a broad temperature-pressure domain using ab initio MD simulations to train a unified potential. Excellent agreement was achieved between bulk face-centered cubic nickel thermal expansion simulations and relevant experimental data. The same potential also yields accurate structures and diffusivities in the liquid state. The phase transition between liquid and solid phases was simulated using the two-phase interface method. The predicted melting point temperature is within a few kelvins of the literature value. Here, the general methodology could be applied to describe crystals with much more complex phase behaviors.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2020

Asphaltene-induced spontaneous emulsification: Effects of interfacial co-adsorption and viscoelasticity

Asphaltenes are a class of high molecular weight aromatic compounds found in crude oil. They adsorb onto toluene-water interfaces and induce a spontaneous emulsification phenomenon, whereby stable water-in-oil emulsions form without the need of an external energy input. This work aims to control and understand the factors affecting spontaneous droplet formation in the presence of asphaltene adsorption. This is particularly useful for crude oil refining, where the presence of a stable emulsion hampers the efficiency of downstream processing operations. We explore the effect of the addition of copolymers designed as crude oil flow improvers as a means to control the extent of emulsion formation. We find that the polymers competitively adsorb onto the toluene-water interface and diminish spontaneous emulsification. Additionally, we conduct fluorescence microscopy experiments and measurements of the interfacial energy to determine the mechanism of spontaneous emulsification in asphaltene systems. We conclude that an emulsion forms via the diffusion of molecular water into the oil phase and subsequent binding with asphaltene aggregates, leading to the nucleation of micrometer-sized water droplets. We find that the polymer forms complexes with the dissolved asphaltenes, possibly hampering the ability of diffused water to bind to the asphaltenes and reducing the extent of spontaneous emulsification. Finally, we investigate the role of interfacial shear and dilatational viscoelasticity to better understand which fundamental interfacial properties are important in the emulsification of asphaltene-laden systems. We find that the rate of formation of an interfacial microstructural network is inversely correlated with the extent and rate of spontaneous emulsification.

42 ENGINEERING↗

DOE OSTI2016

Investigation of radiation damage tolerance in interface-containing metallic nano structures

The proposed work seeks to conduct a basic study by applying experimental and computational methods to obtain quantitative influence of helium sink strength and proximity on He bubble nucleation and growth in He-irradiated nano-scale metallic structures, and the ensuing deformation mechanisms and mechanical properties. We utilized a combination of nano-scale in-situ tension and compression experiments on low-energy He-irradiated samples combined with site-specific microstructural characterization and modeling efforts. We also investigated the mechanical deformation of nano-architected materials, i.e. nanolattices which are comprised of 3-dimensional interwoven networks of hollow tubes, with the wall thickness in the nanometer range. This systematic approach will provide us with critical information for identifying key factors that govern He bubble nucleation and growth upon irradiation as a function of both sink strength and sink proximity through an experimentally-confirmed physical understanding. As an outgrowth of these efforts, we performed irradiations with self-ions (Ni 2+ ) on Ni-Al-Zr metallic glass nanolattices to assess their resilience against radiation damage rather than He-ion implantation. We focused our attention on studying individual bcc/fcc interfaces within a single nano structure (nano-pillar or a hollow tube): a single Fe (bcc)-Cu (fcc) boundary per pillar oriented perpendicular to the pillar axes, as well as pure bcc and fcc nano structures. Additional interfaces of interest include bcc/bcc and metal/metallic glass all within a single nano-structure volume. The model material systems are: (1) pure single crystalline Fe and Cu, (2) a single Fe (bcc)-Cu (fcc) boundary per nano structure (3) a single metal–metallic glass, all oriented non-parallel to the loading direction so that their fracture strength can be tested. A nano-fabrication approach, which involves e-beam lithography and templated electroplating, as well as two-photon lithography, was utilized, which enabled precise control of the initial microstructure control. Experimentally determined stress-strain relationships were enhanced by in-situ SEM observations coupled with TEM microstructural characterization of the same samples before and after deformation (irradiated and as-fabricated) and atomistic (MD) modeling. A comprehensive suite of experiments was conducted to quantitatively assess the key parameters for He bubble nucleation and growth by independently varying the sink strength, sink proximity, and He implantation temperature and dose. The implantations were conducted at Sandia and Los Alamos National Labs (CINT). Nano structuress containing He-enriched interfaces and irradiation-damaged microstructure were tested under uniaxial tension to assess embrittlement, resulting boundary strength, and deformation mechanisms. Results of this work helped identify which types of interfaces are particularly resilient against radiation damage.

36 MATERIALS SCIENCE↗

DOE OSTI2017

What Causes the High Apparent Speeds in Chromospheric and Transition Region Spicules on the Sun?

Spicules are the most ubuiquitous type of jets in the solar atmosphere. The advent of high-resolution imaging and spectroscopy from the Interface Region Imaging Spectrograph ( IRIS ) and ground-based observatories has revealed the presence of very high apparent motions of order 100–300 km s{sup −1} in spicules, as measured in the plane of the sky. However, line of sight measurements of such high speeds have been difficult to obtain, with values deduced from Doppler shifts in spectral lines typically of order 30–70 km s{sup −1}. In this work, we resolve this long-standing discrepancy using recent 2.5D radiative MHD simulations. This simulation has revealed a novel driving mechanism for spicules in which ambipolar diffusion resulting from ion-neutral interactions plays a key role. In our simulation, we often see that the upward propagation of magnetic waves and electrical currents from the low chromosphere into already existing spicules can lead to rapid heating when the currents are rapidly dissipated by ambipolar diffusion. The combination of rapid heating and the propagation of these currents at Alfvénic speeds in excess of 100 km s{sup −1} leads to the very rapid apparent motions, and often wholesale appearance, of spicules at chromospheric and transition region temperatures. In our simulation, the observed fast apparent motions in such jets are actually a signature of a heating front, and much higher than the mass flows, which are of order 30–70 km s{sup −1}. Our results can explain the behavior of transition region “network jets” and the very high apparent speeds reported for some chromospheric spicules.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Enhanced rare-earth separation with a metal-sensitive lanmodulin dimer

Technologically critical rare-earth elements are notoriously difficult to separate, owing to their subtle differences in ionic radius and coordination number. The natural lanthanide-binding protein lanmodulin (LanM) is a sustainable alternative to conventional solvent-extraction-based separation. Here we characterize a new LanM, from Hansschlegelia quercus (Hans-LanM), with an oligomeric state sensitive to rare-earth ionic radius, the lanthanum(III)-induced dimer being >100-fold tighter than the dysprosium(III)-induced dimer. X-ray crystal structures illustrate how picometre-scale differences in radius between lanthanum(III) and dysprosium(III) are propagated to Hans-LanM’s quaternary structure through a carboxylate shift that rearranges a second-sphere hydrogen-bonding network. Comparison to the prototypal LanM from Methylorubrum extorquens reveals distinct metal coordination strategies, rationalizing Hans-LanM’s greater selectivity within the rare-earth elements. Finally, structure-guided mutagenesis of a key residue at the Hans-LanM dimer interface modulates dimerization in solution and enables single-stage, column-based separation of a neodymium(III)/dysprosium(III) mixture to >98% individual element purities. This work showcases the natural diversity of selective lanthanide recognition motifs, and it reveals rare-earth-sensitive dimerization as a biological principle by which to tune the performance of biomolecule-based separation processes.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Spatially-periodic microplasmas in complex microchannel networks: wall-plasma interactions and dynamic behavior

Wall-plasma interactions have been observed for spatially-periodic microplasmas generated in 300–700 µm wide channels fabricated in nanoporous alumina. Examination of Ne microplasma discs produced in a standing-wave pattern in Al 2 O 3 channels illustrates the competition between electron production at the sheath-wall interface and loss by recombination in an atmospheric pressure background. Two topologies of the microplasma arrays are observed. For channel widths (d) less than 450 µm, the microplasmas are generally centered in the channel and sustained by electron generation at both plasma sheath/channel wall interfaces, presumably including the release of charge residing in the hexagonal alumina pores. As d is progressively increased from 300 to 450 µm, the microchannel plasma cross-section is gradually transformed from circular to elliptical, and its surface area declines by as much as 50% so as to minimize e - losses to the background gas. Increasing d above ~450 µm abruptly switches the topology to one in which plasmas having a triangular cross-section attach to one of the channel walls in a pattern that alternates along the channel axis. Microfabricating trapezoidal cross-section channels into complex geometries, including the Cornu spiral and intersecting linear arrays, also reveals dynamic behavior in the propagation of microplasmas. For a common spiral structure, observations of plasma expansion show the wavefront propagates over the corrugated surface or within the channel with radial and azimuthal velocities of 3 ± 1 km s -1 and 8 ± 1.5 km s -1 , respectively. Plasma formation is initiated in each ring of the spiral through electron seeding by streamers propagating radially outward at velocities approaching 200 km s -1 . In addition to electrostatic charge-mediated variations in the mean separation between adjacent microplasmas, the time-dependent interference between two 1D microplasma arrays has been observed during plasma expansion. Reproducible ignition of a microplasma ensemble along ridges micromachined into channels near the intersections of two linear arrays has also been realized. The results reported here demonstrate that microchannels with the walls overcoated with any of a variety of materials provide a promising platform for examining in detail the interaction of low temperature plasma with a surface of arbitrary composition and topography.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

The Galaxy platform for accessible, reproducible, and collaborative data analyses: 2024 update

Galaxy (https://galaxyproject.org) is deployed globally, predominantly through free-to-use services, supporting user-driven research that broadens in scope each year. Users are attracted to public Galaxy services by platform stability, tool and reference dataset diversity, training, support and integration, which enables complex, reproducible, shareable data analysis. Applying the principles of user experience design (UXD), has driven improvements in accessibility, tool discoverability through Galaxy Labs/subdomains, and a redesigned Galaxy ToolShed. Galaxy tool capabilities are progressing in two strategic directions: integrating general purpose graphical processing units (GPGPU) access for cutting-edge methods, and licensed tool support. Engagement with global research consortia is being increased by developing more workflows in Galaxy and by resourcing the public Galaxy services to run them. The Galaxy Training Network (GTN) portfolio has grown in both size, and accessibility, through learning paths and direct integration with Galaxy tools that feature in training courses. Code development continues in line with the Galaxy Project roadmap, with improvements to job scheduling and the user interface. Environmental impact assessment is also helping engage users and developers, reminding them of their role in sustainability, by displaying estimated CO 2 emissions generated by each Galaxy job.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Performance of hybrid Innegra-carbon fiber composites

Abstract In this work material synergy with high stiffness carbon fiber with ductile high strength polypropylene fiber (Innegra S), (referred to as Innegra, herein) have been evaluated in a range of laminate designs. Both woven and discontinuous carbon fiber have been considered. The discontinuous fibers are based on three-dimensional deposition (3DEP) (referred to as 3DEP, herein) carbon fiber preform process. Eleven (11) variants of Innegra-carbon fiber hybrid laminates were investigated for tensile, flexure, compression, in-plane shear and low velocity impact response. The effect of position of Innegra within the laminate was studied and found to influence strength and stiffness properties. In terms of overall trends, Innegra provides upward of 18% improvement in strain (ductility) to the composite and eliminates brittle fracture of carbon fiber. The moduli trends follow the proportionality of Innegra fiber to carbon fiber plies. However, the strength is controlled by the interface between Innegra and carbon fiber. The primary failure mode in tension and compression is via onset of debonding between Innegra and carbon fiber. The 3DEP carbon fiber constituents provided highest values of in-plane shear indicating that three-dimensional (3D) network of carbon fiber provides higher shear resistance. The Innegra intensive variants exhibited superior energy absorption under low velocity impact, at energy levels 15–60 J. This work provides insight for designers to incorporate Innegra and carbon fiber hybrids in composite structures.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Dispatch Optimization Variable Engine

The Dispatch Optimization Variable Engine (DOVE) is software tool written in python, developed at Idaho National Laboratory (INL) that provides an easily accessible application-programming-interface (API) to performing resource dispatch optimization analysis for integrated energy system (IES) configurations. DOVE is an integral part of the Framework for Optimization of Resources and Economics (FORCE) software suite and is leveraged by codes such as the Holistic Energy Resource Optimization Network (HERON) and the Optimization of Real-Time Capacity Allocation (ORCA). The philosophy behind DOVE is to provide a modular software solution to IES planning and operation by utilizing state-of-the-art algorithms and machine learning. The goal is to accurately capture the dispatching behavior of a complex energy system given varying time-dependent signals for demand and commodity pricing.

McDowell, DylanJ. [Idaho National Laboratory (INL)↗

DOE OSTI2025

Keeping LAMMPS cutting edge

Since its inception 30 years ago, LAMMPS has grown to be a world-class molecular dynamics code and a cornerstone of computational materials science research. This project aimed to keep LAMMPS at the forefront of molecular dynamics simulations by adapting LAMMPS to the latest developments in machine learning technology and hardware. Initially, the project set out to provide a unified implementation of active learning for efficient training data generation in LAMMPS, but the research trajectory pivoted to address more immediate and impactful opportunities. On the hardware side, recent record-breaking molecular dynamics simulations were developed on the Cerebras wafer-scale AI chip, and this project has developed an interface between LAMMPS and the hardware-specific molecular dynamics code to accelerate and simplify development and user adoption. On the software side, PyTorch’s Ahead-of-Time (AOT) compilation features promised increased performance for state-of-the-art equivariant neural network potentials, and this project laid the groundwork for their adoption in LAMMPS, resulting in a nearly 20x acceleration in extreme cases. Combined with a comprehensive benchmark study of LAMMPS across all current exascale systems, this project has reinforced LAMMPS’s role as a versatile, high-performance tool for current and future materials science applications.

36 MATERIALS SCIENCE↗

DOE OSTI2024

GASNet-EX Specification Collection (Rev. 2024.5.0)

GASNet-EX is a portable, open-source, high-performance communication library designed to efficiently support the networking requirements of PGAS runtime systems and other alternative models in emerging exascale systems. It provides network-independent, high-performance communication primitives including Remote Memory Access (RMA) and Active Messages (AM). GASNet-EX is an evolution of the popular GASNet communication system, building upon over 20 years of lessons learned, and the primary goals are high performance, interface portability, and expressiveness. The library has been used to implement parallel programming models and libraries such as UPC, UPC++, Fortran coarrays, Legion, Chapel, and many others. This anthology collects together the four separate volumes that currently comprise the GASNet-EX specification, as of the 2024.5.0 release of GASNet-EX.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2022

Machine learning-assisted elucidation of CD81–CD44 interactions in promoting cancer stemness and extracellular vesicle integrity

Tumor-initiating cells with reprogramming plasticity or stem-progenitor cell properties (stemness) are thought to be essential for cancer development and metastatic regeneration in many cancers; however, elucidation of the underlying molecular network and pathways remains demanding. Combining machine learning and experimental investigation, here we report CD81, a tetraspanin transmembrane protein known to be enriched in extracellular vesicles (EVs), as a newly identified driver of breast cancer stemness and metastasis. Using protein structure modeling and interface prediction-guided mutagenesis, we demonstrate that membrane CD81 interacts with CD44 through their extracellular regions in promoting tumor cell cluster formation and lung metastasis of triple negative breast cancer (TNBC) in human and mouse models. In-depth global and phosphoproteomic analyses of tumor cells deficient with CD81 or CD44 unveils endocytosis-related pathway alterations, leading to further identification of a quality-keeping role of CD44 and CD81 in EV secretion as well as in EV-associated stemness-promoting function. CD81 is coexpressed along with CD44 in human circulating tumor cells (CTCs) and enriched in clustered CTCs that promote cancer stemness and metastasis, supporting the clinical significance of CD81 in association with patient outcomes. Our study highlights machine learning as a powerful tool in facilitating the molecular understanding of new molecular targets in regulating stemness and metastasis of TNBC.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Systems and methods for rapid processing and storage of data

Systems and methods of building massively parallel computing systems using low power computing complexes in accordance with embodiments of the invention are disclosed. A massively parallel computing system in accordance with one embodiment of the invention includes at least one Solid State Blade configured to communicate via a high performance network fabric. In addition, each Solid State Blade includes a processor configured to communicate with a plurality of low power computing complexes interconnected by a router, and each low power computing complex includes at least one general processing core, an accelerator, an I/O interface, and cache memory and is configured to communicate with non-volatile solid state memory.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Systems and methods for rapid processing and storage of data

Stalzer, Mark A.↗

DOE OSTI2021

Systems and methods for rapid processing and storage of data

Stalzer, Mark A.↗