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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

CasDinG is a 5′-3′ dsDNA and RNA/DNA helicase with three accessory domains essential for type IV CRISPR immunity

Abstract CRISPR-associated DinG protein (CasDinG) is essential to type IV-A CRISPR function. Here, we demonstrate that CasDinG from Pseudomonas aeruginosa strain 83 is an ATP-dependent 5′-3′ DNA translocase that unwinds double-stranded (ds)DNA and RNA/DNA hybrids. The crystal structure of CasDinG reveals a superfamily 2 helicase core of two RecA-like domains with three accessory domains (N-terminal, arch, and vestigial FeS). To examine the in vivo function of these domains, we identified the preferred PAM sequence for the type IV-A system (5′-GNAWN-3′ on the 5′-side of the target) with a plasmid library and performed plasmid clearance assays with domain deletion mutants. Plasmid clearance assays demonstrated that all three domains are essential for type IV-A immunity. Protein expression and biochemical assays suggested the vFeS domain is needed for protein stability and the arch for helicase activity. However, deletion of the N-terminal domain did not impair ATPase, ssDNA binding, or helicase activities, indicating a role distinct from canonical helicase activities that structure prediction tools suggest involves interaction with dsDNA. This work demonstrates CasDinG helicase activity is essential for type IV-A CRISPR immunity as well as the yet undetermined activity of the CasDinG N-terminal domain.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Meta-virus resource (MetaVR): expanding the frontiers of viral diversity with 24 million uncultivated virus genomes

Viruses are ubiquitous in all environments and impact host metabolism, evolution, and ecology, although our knowledge of their biodiversity is still extremely limited. Viral diversity from genomic and metagenomic datasets has led to an explosion of uncultivated virus genomes (UViGs) and the development of specialized databases to catalog this viral diversity, though many lack comprehensive integration. Here, we introduce meta-virus resource (MetaVR), the successor of the IMG/VR database, designed to overcome previous limitations such as large-scale querying and programmatic access. Drawing on the increase of publicly available genomes and metagenomes, MetaVR significantly expands viral diversity, now comprising 24,435,662 UViGs, a 57.6% increase from its predecessor, organized into over 12 million viral operational taxonomic units. Key enhancements include the integration of curated eukaryotic host information, the integration of protein clusters and predicted structures for comparative studies, and an API for programmatic data access. Furthermore, MetaVR features an updated taxonomic framework based on ICTV release 39, assignment to Baltimore classes, and enhanced host assignment through novel computational tools like iPHoP. These advancements position MetaVR as a unique resource for exploring viral diversity, evolution, and host interactions across diverse environments. MetaVR can be freely accessed at https://www.meta-virome.org/.

Fiamenghi, Mateus B↗
DOE OSTI2021

Deep learning of accurate force field of ferroelectric HfO 2

The discovery of ferroelectricity in HfO 2 -based thin films opens up new opportunities for using this silicon-compatible ferroelectric to realize low-power logic circuits and high-density nonvolatile memories. The functional performances of ferroelectrics are intimately related to their dynamic responses to external stimuli such as electric fields at finite temperatures. Molecular dynamics is an ideal technique for investigating dynamical processes on large length and time scales, though its applications to new materials are often hindered by the limited availability and accuracy of classical force fields. Here we present a deep neural network–based interatomic force field of HfO 2 learned from ab initio data using a concurrent learning procedure. The model potential is able to predict structural properties such as elastic constants, equation of states, phonon dispersion relationships, and phase transition barriers of various hafnia polymorphs with accuracy comparable with density functional theory calculations. Here, the validity of this model potential is further confirmed by the reproduction of experimental sequences of temperature-driven ferroelectric-paraelectric phase transitions of HfO 2 with isobaric-isothermal ensemble molecular dynamics simulations. We suggest a general approach to extend the model potential of HfO 2 to related material systems including dopants and defects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

High-pressure phase diagram of beryllium from ab initio free-energy calculations

In this report we use first-principles molecular dynamics simulations coupled with the thermodynamic integration method to study the hexagonal close-packed (hcp) to body-centered cubic (bcc) transition and melting of beryllium up to a pressure of 1600 GPa. We derive the melting line by equating solid and liquid Gibbs free energies and represent it by a Simon-Glatzel fit T m = 1564 K [1 + P/(15.6032 GPa)] 0.383 , which is in good agreement with previous two-phase simulations <6000 K. We also derive the hcp-bcc solid-solid phase boundary and show that the quasiharmonic approximation underestimates the stability of the hcp structure, predicting lower transition pressures between hcp and bcc phases. Our results are consistent with the stability regime predicted by the phonon quasiparticle method. We also predict that the hcp-bcc-liquid triple point is located at 164.7 GPa and 4314 K. In addition, we compute the shock Hugoniot curve and show that it is in good agreement with experiments, intersecting our derived melting curve at ~235 GPa and 4900 K. Finally, we make predictions for future ramp compression experiments. Starting with an isentropic compression of the liquid, we predict the path to intersect the melting line at low pressure and temperature, then to continue along the melting line over a large temperature interval of 7000 K as the sample remains in the mixed solid-liquid state before it enters the solid phase.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Ground-state degeneracy and complex magnetism of geometrically frustrated Gd 2 Ir 0.97 Si 2.97

We report a new triangular-lattice intermetallic compound Gd 2 Ir 0.97 Si 2.97 was successfully synthesized as single phase by deliberately introducing vacancies. Theoretical analysis suggests that the ground state is competing with several low-energy spin configurations due to magnetic frustration on a nearly ideal triangular lattice. Despite a number of competing magnetic states, the compound exhibits long-range antiferromagnetic order at16K, a long-range ferrimagnetic transition at 6.5 K, and a reentrant cluster-glass transition below T f ~ 3K. The complex magnetism in the compound could be correlated with competing antiferromagnetic and ferrimagnetic structures predicted theoretically.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Detection of Hole Pockets in the Candidate Type-II Weyl Semimetal MoTe 2 from Shubnikov-de Haas Quantum Oscillations

We report the bulk electronic structure of T d -MoTe 2 features large hole Fermi pockets at the Brillouin zone center (Γ) and two electron Fermi surfaces along the Γ-X direction. However, the large hole pockets, whose existence has important implications for the Weyl physics of T d -MoTe 2 , has never been conclusively detected in quantum oscillations. This raises doubt about the realizability of Majorana states in T d -MoTe 2 , because these exotic states rely on the existence of Weyl points, which originated from the same band structure predicted by density functional theory (DFT). Here, we report an unambiguous detection of these elusive hole pockets via Shubnikov–de Haas (SdH) quantum oscillations. At ambient pressure, the quantum oscillation frequencies for these pockets are 988 and 1513 T, when the magnetic field is applied along the c axis. The quasiparticle effective masses m* associated with these frequencies are 1.50 and 2.77 m e , respectively, indicating the importance of Coulomb interactions in this system. We further measure the SdH oscillations under pressure. At 13 kbar, we detected a peak at 1798 T with m* = 2.86 m e . Relative to the oscillation data at a lower pressure, the amplitude of this peak experienced an enhancement, which can be attributed to the reduced curvature of the hole pockets under pressure. Combining our experimental data with DFT +U calculations, where U is the Hubbard parameter, our results shed light on why these important hole pockets have not been detected until now.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Likelihood-based interactive local docking into cryo-EM maps in ChimeraX

The interpretation of cryo-EM maps often includes the docking of known or predicted structures of the components, which is particularly useful when the map resolution is worse than 4 Å. Although it can be effective to search the entire map to find the best placement of a component, the process can be slow when the maps are large. However, frequently there is a well-founded hypothesis about where particular components are located. In such cases, a local search using a map subvolume will be much faster because the search volume is smaller, and more sensitive because optimizing the search volume for the rotation-search step enhances the signal to noise. A Fourier-space likelihood-based local search approach, based on the previously published em_placement software, has been implemented in the new emplace_local program. Tests confirm that the local search approach enhances the speed and sensitivity of the computations. An interactive graphical interface in the ChimeraX molecular-graphics program provides a convenient way to set up and evaluate docking calculations, particularly in defining the part of the map into which the components should be placed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Performance simulation of the soft gamma-ray concentrator

The soft gamma-ray concentrator is a telescope mission concept utilizing a suitable arrangement of bent multilayer structures of alternating low- and high-density materials. This lens is able to channel gamma-ray photons via total external reflection and concentrate the incident radiation to a point. The channeling technique offers the potential for concentrating gamma rays with focal lengths <10 m and energies >100 keV, beyond the reach of current grazing-incidence hard x-ray mirrors. For the performance estimation of such an instrument, we have developed a flexible set of computer modeling tools to compute the optical properties of multilayer structures, predict the channeling efficiency for a given multilayer configuration, and aid in the optimization of potential gamma-ray concentrator-based telescope designs. This modeling includes the multilayer optical properties calculated by the IMD software, the ray tracing using an IDL code, and the focal plane detector simulation by MEGAlib. We illustrate the potential of this approach by presenting simulated astronomical observations from a balloon-borne platform. The final result, including simulated effective area, instrument sensitivity, and polarization performance, shows that the gamma-ray concentrator will provide greatly increased sensitivity for next-generation soft gamma-ray missions with modest cost and complexity.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Robust deep learning–based protein sequence design using ProteinMPNN

Although deep learning has revolutionized protein structure prediction, almost all experimentally characterized de novo protein designs have been generated using physically based approaches such as Rosetta. Here, we describe a deep learning–based protein sequence design method, ProteinMPNN, that has outstanding performance in both in silico and experimental tests. On native protein backbones, ProteinMPNN has a sequence recovery of 52.4% compared with 32.9% for Rosetta. The amino acid sequence at different positions can be coupled between single or multiple chains, enabling application to a wide range of current protein design challenges. We demonstrate the broad utility and high accuracy of ProteinMPNN using x-ray crystallography, cryo–electron microscopy, and functional studies by rescuing previously failed designs, which were made using Rosetta or AlphaFold, of protein monomers, cyclic homo-oligomers, tetrahedral nanoparticles, and target-binding proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Topological grain boundary segregation transitions

Engineering the structure of grain boundaries (GBs) by solute segregation is a promising strategy to tailor the properties of polycrystalline materials. Solute segregation triggering phase transitions at GBs has been suggested theoretically to offer different pathways to design interfaces, but an understanding of their intrinsic atomistic nature is missing. Here, we combined atomic resolution electron microscopy and atomistic simulations to discover that iron segregation to GBs in titanium stabilizes icosahedral units (“cages”) that form robust building blocks of distinct GB phases. Owing to their five-fold symmetry, the iron cages cluster and assemble into hierarchical GB phases characterized by a different number and arrangement of the constituent icosahedral units. Our advanced GB structure prediction algorithms and atomistic simulations validate the stability of these observed phases and the high excess of iron at the GB that is accommodated by the phase transitions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

REC protein family expansion by the emergence of a new signaling pathway

This report presents multi-genome evidence that REC protein family expansion occurs when the emergence of new pathways gives rise to functional discordance. Specificity between residues in REC domain containing response regulators with paired histidine kinases is under negative purifying selection, constrained by the presence of other bacterial two-component systems signaling cascades that share sequence and structural identity. Presuming that the two-component systems can evolve by neutral amino acid changes (neutral drift) when purifying evolutionary constraints are relaxed, how might the REC protein family expand by amino acid changes when these constraints remain intact? Using an unsupervised machine learning approach to observe the sequence landscape of REC domains across long phylogenetic distances, we find that within-gene recombination, a subcategory of gene conversion, switched the effector domain and, consequently, the regulatory context of a duplicated response regulator from transcriptional regulation by σ54 to that by σ70. We determined that the recombined response regulator diverged from its parent by episodic diversifying selection and neutral drift. Functional experiments of the parent of recombined response regulators in a model Pseudomonas putida KT2440 model system revealed that the parent and recombined response regulators sense and respond to different carboxylic acids. Finally, a residue-switching experiment using structural predictions and functional characterization suggests that the new residues in the recombined regulator could form a new interaction interface and mediate condition-specific phosphotransfer. Overall, our study finds that genetic perturbations can create conditions of functional discordance, whereby the REC protein family can evolve by episodic diversifying selection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Auto_PDI

Protein-DNA Interaction Workflow (PDI Workflow), a pipeline that focuses on generating high-quality docking and molecular dynamics simulations for Protein-DNA complexes. This allows us to take DNA sequences with unknown tertiary structures, accurately predict their structure, dock them with the desired target protein, and then simulate their interactions using molecular dynamics simulations

Kumar, Neeraj↗
DOE OSTI2023

Hydrogen Extremely Low Probability of Rupture Version 1

SAND2024-08511O The Hydrogen Extremely Low Probability of Rupture (HELPR) software toolkit provides probabilistic fracture assessments of natural gas infrastructure for transporting hydrogen. Using probabilistic sampling and sensitivity analysis—along with engineering fatigue and fracture mechanics— the software develops models that can predict structural integrity measures for natural gas pipelines under stress. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Schroeder, Benjamin↗
DOE OSTI2025

SFold v0.1

This is a scientific software package to integrate Small Angle X-ray Scattering (SAXS) experimental data into OpenFold deep learning models to improve protein structure prediction.

Prince, Stephanie [Lawrence Berkeley National Labo↗
DOE OSTI2022

Symmetry relation database and its application to ferroelectric materials discovery

To investigate the displacive phase transition at the atomic scale, we have implemented a numerical algorithm to automate the detection of the symmetry relations between any two candidate crystal structures. Using this algorithm, here we systematically screen all possible polar–nonpolar structure pairs from the Materials Project database and establish a library of ~4500 pairs that can be connected through a continuous phase transition with small atomic displacements. From this database, we identify several new ferroelectric materials. In addition, the database may also be used in other areas, such as material structure prediction and new materials discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Structural analyses of macromolecules by solution scattering (CRADA Final Report)

New innovative Small Angle X-ray Scattering (SAXS) methods to visualized macromolecules in solution at low resolution has led the SIBYLS group at Lawrence Berkeley Lab in being a world leader in biological SAXS. This research is particularly important now as LBNL establishes high-priority research topics including molecular to mesoscale analysis. This new expanding area of research relies on and ties in with our efforts towards developing a solution structure modeling tool for RNA structure prediction. Due to the pandemic our efforts focused on the SARS-CoV-2 proteins and RNA interactions. Specifically, we characterized SARS-CoC-2 proteins interaction with RNA (Wilanowski et al. 2021 -Hammel group) and Nucleoprotein interaction with RNA (Schneidman group).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Real-Time Krylov Theory for Quantum Computing Algorithms

Quantum computers provide new avenues to access ground and excited state properties of systems otherwise difficult to simulate on classical hardware. New approaches using subspaces generated by real-time evolution have shown efficiency in extracting eigenstate information, but the full capabilities of such approaches are still not understood. In recent work, we developed the variational quantum phase estimation (VQPE) method, a compact and efficient real-time algorithm to extract eigenvalues on quantum hardware. Here we build on that work by theoretically and numerically exploring a generalized Krylov scheme where the Krylov subspace is constructed through a parametrized real-time evolution, which applies to the VQPE algorithm as well as others. We establish an error bound that justifies the fast convergence of our spectral approximation. We also derive how the overlap with high energy eigenstates becomes suppressed from real-time subspace diagonalization and we visualize the process that shows the signature phase cancellations at specific eigenenergies. We investigate various algorithm implementations and consider performance when stochasticity is added to the target Hamiltonian in the form of spectral statistics. To demonstrate the practicality of such real-time evolution, we discuss its application to fundamental problems in quantum computation such as electronic structure predictions for strongly correlated systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Rational Design of Lanmodulin Variants for Size-Based Selectivity of Individual Rare Earth Elements

Rare earth elements (REEs) are essential to modern technologies, yet their high physical and chemical similarity makes separation of individual REEs difficult and environmentally taxing. Metalloproteins offer a promising alternative for selective REE binding, as they tend to have high metal ion affinity and specificity. Lanmodulin (LanM), in particular, has arisen as a potential candidate for REE separation as it exhibits picomolar affinity for elements in the REE family. Prior work has shown that the single point mutation D9N can shift LanM’s preference away from lanthanides toward actinides, motivating efforts to tune selectivity of LanM through targeted mutagenesis. Here, we tested the hypothesis that introducing selective aspartic acid to glutamic acid substitutions in the metal coordinating EF hands of LanM would impose steric constraints that would drive LanM affinity away from larger ions, such as La3+, to smaller ions, such as Y3+. To test this hypothesis, a combination of computational and experimental approaches were employed to evaluate the signal mutations LanM D5E and LanM D3E and the double mutants LanM D1ED5E and LanM D3ED9E. Surprisingly, increasing the number of mutations within the metal center did not enhance affinity for smaller REEs, or decrease affinity for larger ions. Only the single point mutation LanM D5E weakened La3+ binding by one order of magnitude relative to LanM wild type (WT), and pairing it with a second mutation to produce LanM D1ED5E drove La3+ affinity to be stronger than that seen for LanM WT. The D3E mutation alone prevented proper expression and folding, but paring it with D9E to produce LanM D3ED9E rescued expression and yielded La3+ affinities comparable to LanM WT. All variants that expressed (LanM D5E, LanM D1ED5E, LanM D3ED9E) displayed Y3+ affinities comparable to LanM WT. Overall, these results highlight the tunability of LanM’s metal-binding environment but also expose current limitations in predicting structural responses to point mutations within a protein sequence. This work establishes a foundation that can be used for refining computational and experimental strategies to engineer metalloproteins with tailored REE selectivity.

Close, Emily [Pacific Northwest National Laborator↗