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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 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Giant phonon anomalies in the proximate Kitaev quantum spin liquid α-RuCl 3

The Kitaev quantum spin liquid epitomizes an entangled topological state, for which two flavors of fractionalized low-energy excitations are predicted: the itinerant Majorana fermion and the Z 2 gauge flux. Here, it was proposed recently that fingerprints of fractional excitations are encoded in the phonon spectra of Kitaev quantum spin liquids through a novel fractional-excitation-phonon coupling. Here, we detect anomalous phonon effects in α-RuCl 3 using inelastic X-ray scattering with meV resolution. At high temperature, we discover interlaced optical phonons intercepting a transverse acoustic phonon between 3 and 7 meV. Upon decreasing temperature, the optical phonons display a large intensity enhancement near the Kitaev energy, J K ~8 meV, that coincides with a giant acoustic phonon softening near the Z 2 gauge flux energy scale. These phonon anomalies signify the coupling of phonon and Kitaev magnetic excitations in α-RuCl 3 and demonstrates a proof-of-principle method to detect anomalous excitations in topological quantum materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Designed and biologically active protein lattices

Versatile methods to organize proteins in space are required to enable complex biomaterials, engineered biomolecular scaffolds, cell-free biology, and hybrid nanoscale systems. Here, we demonstrate how the tailored encapsulation of proteins in DNA-based voxels can be combined with programmable assembly that directs these voxels into biologically functional protein arrays with prescribed and ordered two-dimensional (2D) and three-dimensional (3D) organizations. We apply the presented concept to ferritin, an iron storage protein, and its iron-free analog, apoferritin, in order to form single-layers, double-layers, as well as several types of 3D protein lattices. Our study demonstrates that internal voxel design and inter-voxel encoding can be effectively employed to create protein lattices with designed organization, as confirmed by in situ X-ray scattering and cryo-electron microscopy 3D imaging. The assembled protein arrays maintain structural stability and biological activity in environments relevant for protein functionality. The framework design of the arrays then allows small molecules to access the ferritins and their iron cores and convert them into apoferritin arrays through the release of iron ions. The presented study introduces a platform approach for creating bio-active protein-containing ordered nanomaterials with desired 2D and 3D organizations.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

A catalog of the diversity and ubiquity of bacterial microcompartments

Abstract Bacterial microcompartments (BMCs) are organelles that segregate segments of metabolic pathways which are incompatible with surrounding metabolism. BMCs consist of a selectively permeable shell, composed of three types of structurally conserved proteins, together with sequestered enzymes that vary among functionally distinct BMCs. Genes encoding shell proteins are typically clustered with those for the encapsulated enzymes. Here, we report that the number of identifiable BMC loci has increased twenty-fold since the last comprehensive census of 2014, and the number of distinct BMC types has doubled. The new BMC types expand the range of compartmentalized catalysis and suggest that there is more BMC biochemistry yet to be discovered. Our comprehensive catalog of BMCs provides a framework for their identification, correlation with bacterial niche adaptation, experimental characterization, and development of BMC-based nanoarchitectures for biomedical and bioengineering applications.

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

Pangenomics reveals alternative environmental lifestyles among chlamydiae

Chlamydiae are highly successful strictly intracellular bacteria associated with diverse eukaryotic hosts. Here we analyzed metagenome-assembled genomes of the “Genomes from Earth’s Microbiomes” initiative from diverse environmental samples, which almost double the known phylogenetic diversity of the phylum and facilitate a highly resolved view at the chlamydial pangenome. Chlamydiae are defined by a relatively large core genome indicative of an intracellular lifestyle, and a highly dynamic accessory genome of environmental lineages. We observe chlamydial lineages that encode enzymes of the reductive tricarboxylic acid cycle and for light-driven ATP synthesis. We show a widespread potential for anaerobic energy generation through pyruvate fermentation or the arginine deiminase pathway, and we add lineages capable of molecular hydrogen production. Genome-informed analysis of environmental distribution revealed lineage-specific niches and a high abundance of chlamydiae in some habitats. Together, our data provide an extended perspective of the variability of chlamydial biology and the ecology of this phylum of intracellular microbes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A multi-step nucleation process determines the kinetics of prion-like domain phase separation

Compartmentalization by liquid-liquid phase separation (LLPS) has emerged as a ubiquitous mechanism underlying the organization of biomolecules in space and time. Here, we combine rapid-mixing time-resolved small-angle X-ray scattering (SAXS) approaches to characterize the assembly kinetics of a prototypical prion-like domain with equilibrium techniques that characterize its phase boundaries and the size distribution of clusters prior to phase separation. We find two kinetic regimes on the micro- to millisecond timescale that are distinguished by the size distribution of clusters. At the nanoscale, small complexes are formed with low affinity. After initial unfavorable complex assembly, additional monomers are added with higher affinity. At the mesoscale, assembly resembles classical homogeneous nucleation. Careful multi-pronged characterization is required for the understanding of condensate assembly mechanisms and will promote understanding of how the kinetics of biological phase separation is encoded in biomolecules.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

ECNet is an evolutionary context-integrated deep learning framework for protein engineering

Abstract Machine learning has been increasingly used for protein engineering. However, because the general sequence contexts they capture are not specific to the protein being engineered, the accuracy of existing machine learning algorithms is rather limited. Here, we report ECNet (evolutionary context-integrated neural network), a deep-learning algorithm that exploits evolutionary contexts to predict functional fitness for protein engineering. This algorithm integrates local evolutionary context from homologous sequences that explicitly model residue-residue epistasis for the protein of interest with the global evolutionary context that encodes rich semantic and structural features from the enormous protein sequence universe. As such, it enables accurate mapping from sequence to function and provides generalization from low-order mutants to higher-order mutants. We show that ECNet predicts the sequence-function relationship more accurately as compared to existing machine learning algorithms by using ~50 deep mutational scanning and random mutagenesis datasets. Moreover, we used ECNet to guide the engineering of TEM-1 β-lactamase and identified variants with improved ampicillin resistance with high success rates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Autonomous extraction of millimeter-scale deformation in InSAR time series using deep learning

Systematically characterizing slip behaviours on active faults is key to unraveling the physics of tectonic faulting and the interplay between slow and fast earthquakes. Interferometric Synthetic Aperture Radar (InSAR), by enabling measurement of ground deformation at a global scale every few days, may hold the key to those interactions. However, atmospheric propagation delays often exceed ground deformation of interest despite state-of-the art processing, and thus InSAR analysis requires expert interpretation and a priori knowledge of fault systems, precluding global investigations of deformation dynamics. Here, we show that a deep auto-encoder architecture tailored to untangle ground deformation from noise in InSAR time series autonomously extracts deformation signals, without prior knowledge of a fault’s location or slip behaviour. Applied to InSAR data over the North Anatolian Fault, our method reaches 2 mm detection, revealing a slow earthquake twice as extensive as previously recognized. We further explore the generalization of our approach to inflation/deflation-induced deformation, applying the same methodology to the geothermal field of Coso, California.

58 GEOSCIENCES↗
DOE OSTI2021

Predicting fault slip via transfer learning

Abstract Data-driven machine-learning for predicting instantaneous and future fault-slip in laboratory experiments has recently progressed markedly, primarily due to large training data sets. In Earth however, earthquake interevent times range from 10’s-100’s of years and geophysical data typically exist for only a portion of an earthquake cycle. Sparse data presents a serious challenge to training machine learning models for predicting fault slip in Earth. Here we describe a transfer learning approach using numerical simulations to train a convolutional encoder-decoder that predicts fault-slip behavior in laboratory experiments. The model learns a mapping between acoustic emission and fault friction histories from numerical simulations, and generalizes to produce accurate predictions of laboratory fault friction. Notably, the predictions improve by further training the model latent space using only a portion of data from a single laboratory earthquake-cycle. The transfer learning results elucidate the potential of using models trained on numerical simulations and fine-tuned with small geophysical data sets for potential applications to faults in Earth.

58 GEOSCIENCES↗
DOE OSTI2022

Biosensor for branched-chain amino acid metabolism in yeast and applications in isobutanol and isopentanol production

Abstract Branched-chain amino acid (BCAA) metabolism fulfills numerous physiological roles and can be harnessed to produce valuable chemicals. However, the lack of eukaryotic biosensors specific for BCAA-derived products has limited the ability to develop high-throughput screens for strain engineering and metabolic studies. Here, we harness the transcriptional regulator Leu3p from Saccharomyces cerevisiae to develop a genetically encoded biosensor for BCAA metabolism. In one configuration, we use the biosensor to monitor yeast production of isobutanol, an alcohol derived from valine degradation. Small modifications allow us to redeploy Leu3p in another biosensor configuration that monitors production of the leucine-derived alcohol, isopentanol. These biosensor configurations are effective at isolating high-producing strains and identifying enzymes with enhanced activity from screens for branched-chain higher alcohol (BCHA) biosynthesis in mitochondria as well as cytosol. Furthermore, this biosensor has the potential to assist in metabolic studies involving BCAA pathways, and offers a blueprint to develop biosensors for other products derived from BCAA metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Density of states prediction for materials discovery via contrastive learning from probabilistic embeddings

Abstract Machine learning for materials discovery has largely focused on predicting an individual scalar rather than multiple related properties, where spectral properties are an important example. Fundamental spectral properties include the phonon density of states (phDOS) and the electronic density of states (eDOS), which individually or collectively are the origins of a breadth of materials observables and functions. Building upon the success of graph attention networks for encoding crystalline materials, we introduce a probabilistic embedding generator specifically tailored to the prediction of spectral properties. Coupled with supervised contrastive learning, our materials-to-spectrum (Mat2Spec) model outperforms state-of-the-art methods for predicting ab initio phDOS and eDOS for crystalline materials. We demonstrate Mat2Spec’s ability to identify eDOS gaps below the Fermi energy, validating predictions with ab initio calculations and thereby discovering candidate thermoelectrics and transparent conductors. Mat2Spec is an exemplar framework for predicting spectral properties of materials via strategically incorporated machine learning techniques.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Structural basis for the mechanisms of human presequence protease conformational switch and substrate recognition

Presequence protease (PreP), a 117kDa mitochondrial M16C metalloprotease vital for mitochondrial proteostasis, degrades presequence peptides cleaved off from nuclear-encoded proteins and other aggregation-prone peptides, such as amyloid β (Aβ). PreP structures have only been determined in a closed conformation; thus, the mechanisms of substrate binding and selectivity remain elusive. Here, we leverage advanced vitrification techniques to overcome the preferential denaturation of one of two ~55 kDa homologous domains of PreP caused by air-water interface adsorption. Thereby, we elucidate cryoEM structures of three apo-PreP open states along with Aβ- and citrate synthase presequence-bound PreP at 3.3–4.6 Å resolution. Together with integrative biophysical and pharmacological approaches, these structures reveal the key stages of the PreP catalytic cycle and how the binding of substrates or PreP inhibitor drives a rigid body motion of the protein for substrate binding and catalysis. Together, our studies provide key mechanistic insights into M16C metalloproteases for future therapeutic innovations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Hardware functional obfuscation with ferroelectric active interconnects

Existing circuit camouflaging techniques to prevent reverse engineering increase circuit-complexity with significant area, energy, and delay penalty. In this paper, we propose an efficient hardware encryption technique with minimal complexity and overheads based on ferroelectric field-effect transistor (FeFET) active interconnects. By utilizing the threshold voltage programmability of the FeFETs, run-time reconfigurable inverter-buffer logic, utilizing two FeFETs and an inverter, is enabled. Judicious placement of the proposed logic makes it act as a hardware encryption key and enable encoding and decoding of the functional output without affecting the critical path timing delay. Additionally, a peripheral programming scheme for reconfigurable logic by reusing the existing scan chain logic is proposed, obviating the need for specialized programming logic and circuitry for keybit distribution. Our analysis shows an average encryption probability of 97.43% with an increase of 2.24%/ 3.67% delay for the most critical path/ sum of 100 critical paths delay for ISCAS85 benchmarks.

42 ENGINEERING↗
DOE OSTI2022

Analytical solution for nonadiabatic quantum annealing to arbitrary Ising spin Hamiltonian

Abstract Ising spin Hamiltonians are often used to encode a computational problem in their ground states. Quantum Annealing (QA) computing searches for such a state by implementing a slow time-dependent evolution from an easy-to-prepare initial state to a low energy state of a target Ising Hamiltonian of quantum spins, H I . Here, we point to the existence of an analytical solution for such a problem for an arbitrary H I beyond the adiabatic limit for QA. This solution provides insights into the accuracy of nonadiabatic computations. Our QA protocol in the pseudo-adiabatic regime leads to a monotonic power-law suppression of nonadiabatic excitations with time T of QA, without any signature of a transition to a glass phase, which is usually characterized by a logarithmic energy relaxation. This behavior suggests that the energy relaxation can differ in classical and quantum spin glasses strongly, when it is assisted by external time-dependent fields. In specific cases of H I , the solution also shows a considerable quantum speedup in computations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Quadrupolar magnetic excitations in an isotropic spin-1 antiferromagnet

The microscopic origins of emergent behaviours in condensed matter systems are encoded in their excitations. In ordinary magnetic materials, single spin-flips give rise to collective dipolar magnetic excitations called magnons. Likewise, multiple spin-flips can give rise to multipolar magnetic excitations in magnetic materials with spin S ≥ 1. Unfortunately, since most experimental probes are governed by dipolar selection rules, collective multipolar excitations have generally remained elusive. For instance, only dipolar magnetic excitations have been observed in isotropic S = 1 Haldane spin systems. Here, we unveil a hidden quadrupolar constituent of the spin dynamics in antiferromagnetic S = 1 Haldane chain material Y 2 BaNiO 5 using Ni L 3 -edge resonant inelastic x-ray scattering. Our results demonstrate that pure quadrupolar magnetic excitations can be probed without direct interactions with dipolar excitations or anisotropic perturbations. Originating from on-site double spin-flip processes, the quadrupolar magnetic excitations in Y 2 BaNiO 5 show a remarkable dual nature of collective dispersion. While one component propagates as non-interacting entities, the other behaves as a bound quadrupolar magnetic wave. This result highlights the rich and largely unexplored physics of higher-order magnetic excitations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Ligand-induced transmembrane conformational coupling in monomeric $\mathrm{EGFR}$

Single pass cell surface receptors regulate cellular processes by transmitting ligand-encoded signals across the plasma membrane via changes to their extracellular and intracellular conformations. This transmembrane signaling is generally initiated by ligand binding to the receptors in their monomeric form. While subsequent receptor-receptor interactions are established as key aspects of transmembrane signaling, the contribution of monomeric receptors has been challenging to isolate due to the complexity and ligand-dependence of these interactions. By combining membrane nanodiscs produced with cell-free expression, single-molecule Förster Resonance Energy Transfer measurements, and molecular dynamics simulations, we report that ligand binding induces intracellular conformational changes within monomeric, full-length epidermal growth factor receptor (EGFR). Our observations establish the existence of extracellular/intracellular conformational coupling within a single receptor molecule. We implicate a series of electrostatic interactions in the conformational coupling and find the coupling is inhibited by targeted therapeutics and mutations that also inhibit phosphorylation in cells. Collectively, these results introduce a facile mechanism to link the extracellular and intracellular regions through the single transmembrane helix of monomeric EGFR, and raise the possibility that intramolecular transmembrane conformational changes upon ligand binding are common to single-pass membrane proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

An essential role for tungsten in the ecology and evolution of a previously uncultivated lineage of anaerobic, thermophilic Archaea

Trace metals have been an important ingredient for life throughout Earth’s history. Here, we describe the genome-guided cultivation of a member of the elusive archaeal lineage Caldarchaeales (syn. Aigarchaeota), Wolframiiraptor gerlachensis, and its growth dependence on tungsten. A metagenome-assembled genome (MAG) of W. gerlachensis encodes putative tungsten membrane transport systems, as well as pathways for anaerobic oxidation of sugars probably mediated by tungsten-dependent ferredoxin oxidoreductases that are expressed during growth. Catalyzed reporter deposition-fluorescence in-situ hybridization (CARD-FISH) and nanoscale secondary ion mass spectrometry (nanoSIMS) show that W. gerlachensis preferentially assimilates xylose. Phylogenetic analyses of 78 high-quality Wolframiiraptoraceae MAGs from terrestrial and marine hydrothermal systems suggest that tungsten-associated enzymes were present in the last common ancestor of extant Wolframiiraptoraceae. Our observations imply a crucial role for tungsten-dependent metabolism in the origin and evolution of this lineage, and hint at a relic metabolic dependence on this trace metal in early anaerobic thermophiles.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Molecular dissection of the glutamine synthetase-GlnR nitrogen regulatory circuitry in Gram-positive bacteria

How bacteria sense and respond to nitrogen levels are central questions in microbial physiology. In Gram-positive bacteria, nitrogen homeostasis is controlled by an operon encoding glutamine synthetase (GS), a dodecameric machine that assimilates ammonium into glutamine, and the GlnR repressor. GlnR detects nitrogen excess indirectly by binding glutamine-feedback-inhibited-GS (FBI-GS), which activates its transcription-repression function. The molecular mechanisms behind this regulatory circuitry, however, are unknown. Here we describe biochemical and structural analyses of GS and FBI-GS-GlnR complexes from pathogenic and non-pathogenic Gram-positive bacteria. The structures show FBI-GS binds the GlnR C-terminal domain within its active-site cavity, juxtaposing two GlnR monomers to form a DNA-binding-competent GlnR dimer. The FBI-GS-GlnR interaction stabilizes the inactive GS conformation. Strikingly, this interaction also favors a remarkable dodecamer to tetradecamer transition in some GS, breaking the paradigm that all bacterial GS are dodecamers. These data thus unveil unique structural mechanisms of transcription and enzymatic regulation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Muconic acid production from glucose and xylose in Pseudomonas putida via evolution and metabolic engineering

Muconic acid is a bioprivileged molecule that can be converted into direct replacement chemicals for incumbent petrochemicals and performance-advantaged bioproducts. In this study, Pseudomonas putida KT2440 is engineered to convert glucose and xylose, the primary carbohydrates in lignocellulosic hydrolysates, to muconic acid using a model-guided strategy to maximize the theoretical yield. Using adaptive laboratory evolution (ALE) and metabolic engineering in a strain engineered to express the D-xylose isomerase pathway, we demonstrate that mutations in the heterologous D-xylose:H + symporter (XylE), increased expression of a major facilitator superfamily transporter (PP_2569), and overexpression of aroB encoding the native 3-dehydroquinate synthase, enable efficient muconic acid production from glucose and xylose simultaneously. Using the rationally engineered strain, we produce 33.7 g L -1 muconate at 0.18 g L -1 h -1 and a 46% molar yield (92% of the maximum theoretical yield). This engineering strategy is promising for the production of other shikimate pathway-derived compounds from lignocellulosic sugars.

09 BIOMASS FUELS↗