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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 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A reverse-selective ion exchange membrane for the selective transport of phosphates via an outer-sphere complexation–diffusion pathway

Specific-ion selectivity is a highly desirable feature for the next generation of membranes. However, existing membranes rely on differences in charge, size and hydration energy, which limits their ability to target individual ion species. Here we demonstrate a nanocomposite ion-exchange membrane material that enables a reverse-selective transport mechanism that can selectively pass a single ion species. Here we demonstrate this transport mechanism with phosphate ions selectively transporting across negatively charged cation exchange membranes. Selective transport is enabled by the in situ growth of hydrous manganese oxide nanoparticles throughout a cation exchange membrane that provide a diffusion pathway via phosphate-specific, reversible outer-sphere interactions. On incorporating the hydrous manganese oxide nanoparticles, the membrane’s phosphate flux increased by a factor of 27 over an unmodified cation exchange membrane, and the selectivity of phosphorous over sulfate, nitrate and chloride reaches 47,100 and 20, respectively. By pairing ion-specific outer-sphere interactions between the target ions and appropriate nanoparticles, these nanocomposite ion-exchange materials can, in principle, achieve selective transport for a range of ions.

42 ENGINEERING↗
DOE OSTI2022

Unconventional spectral signature of $T_c$ in a pure d -wave superconductor

We report in conventional superconductors, the phase transition into a zero-resistance and perfectly diamagnetic state is accompanied by a jump in the specific heat and the opening of a spectral gap. In the high-transition-temperature (high-T c ) cuprates, although the transport, magnetic and thermodynamic signatures of T c have been known since the 1980s, the spectroscopic singularity associated with the transition remains unknown. Here we resolve this long-standing puzzle with a high-precision angle-resolved photoemission spectroscopy (ARPES) study on overdoped (Bi,Pb) 2 Sr 2 CaCu 2 O 8+δ (Bi2212). We first probe the momentum-resolved electronic specific heat via spectroscopy and reproduce the specific heat peak at T c , completing the missing link for a holistic description of superconductivity. Then, by studying the full momentum, energy and temperature evolution of the spectra, we reveal that this thermodynamic anomaly arises from the singular growth of in-gap spectral intensity across T c . Furthermore, we observe that the temperature evolution of in-gap intensity is highly anisotropic in the momentum space, and the gap itself obeys both the d-wave functional form and particle–hole symmetry. These findings support the scenario that the superconducting transition is driven by phase fluctuations. They also serve as an anchor point for understanding the Fermi arc and pseudogap phenomena in underdoped cuprates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Single-cell quantification of ribosome occupancy in early mouse development

Translation regulation is critical for early mammalian embryonic development. However, previous studies had been restricted to bulk measurements, precluding precise determination of translation regulation including allele-specific analyses. Here, to address this challenge, we developed a novel microfluidic isotachophoresis (ITP) approach, named RIBOsome profiling via ITP (Ribo-ITP), and characterized translation in single oocytes and embryos during early mouse development. We identified differential translation efficiency as a key mechanism regulating genes involved in centrosome organization and N 6 -methyladenosine modification of RNAs. Our high-coverage measurements enabled, to our knowledge, the first analysis of allele-specific ribosome engagement in early development. These led to the discovery of stage-specific differential engagement of zygotic RNAs with ribosomes and reduced translation efficiency of transcripts exhibiting allele-biased expression. By integrating our measurements with proteomics data, we discovered that ribosome occupancy in germinal vesicle-stage oocytes is the predominant determinant of protein abundance in the zygote. The Ribo-ITP approach will enable numerous applications by providing high-coverage and high-resolution ribosome occupancy measurements from ultra-low input samples including single cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Multiomics and deep learning dissect regulatory syntax in human development

Transcription factors establish cell identity during development by binding regulatory DNA in a sequence-specific manner, often promoting local chromatin accessibility and regulating gene expression1. Mapping accessible chromatin offers critical insights into transcriptional control, but available datasets for human development are restricted to bulk tissue, single organs or single modalities2. Here we present the Human Development Multiomic Atlas, a single-cell atlas of chromatin accessibility and gene expression from 817,740 fetal cells across 12 organs, spanning 203 cell types and more than 1 million candidate cis-regulatory elements, many of which exhibit organ-specific in vivo enhancer activity. Deep learning models trained to predict accessibility from local DNA sequence unravel a comprehensive lexicon of motifs that influence accessibility, including composite motifs exhibiting distinct syntactic constraints that are predicted to mediate transcription factor cooperativity. We identify ‘hard’ syntactic rules requiring precise motif spacing and orientation, ‘soft’ rules allowing flexible motif arrangements, and ubiquitous motifs inhibiting accessibility. Model-based interpretation of genetic variants reveals that disruption of motifs with positive and negative effects is associated with concordant effects on gene expression. Our work delineates how motif syntax governs cell-type-specific chromatin accessibility and provides a foundational resource for decoding cis-regulatory logic and interpreting genetic variation during human development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Tunable High Spatio-Spectral Purity Undulator Radiation from a Transported Laser Plasma Accelerated Electron Beam

Undulator based synchrotron light sources and Free Electron Lasers (FELs) are valuable modern probes of matter with high temporal and spatial resolution. Laser Plasma Accelerators (LPAs), delivering GeV electron beams in few centimeters, are good candidates for future compact light sources. However the barriers set by the large energy spread, divergence and shot-to-shot fluctuations require a specific transport line, to shape the electron beam phase space for achieving ultrashort undulator synchrotron radiation suitable for users and even for achieving FEL amplification. Proof-of-principle LPA based undulator emission, with strong electron focusing or transport, does not yet exhibit the full specific radiation properties. We report on the generation of undulator radiation with an LPA beam based manipulation in a dedicated transport line with versatile properties. After evidencing the specific spatio-spectral signature, we tune the resonant wavelength within 200–300 nm by modification of the electron beam energy and the undulator field. We achieve a wavelength stability of 2.6%. We demonstrate that we can control the spatio-spectral purity and spectral brightness by reducing the energy range inside the chicane. We have also observed the second harmonic emission of the undulator.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Enhanced purification coupled with biophysical analyses shows cross-β structure as a core building block for Streptococcus mutans functional amyloids

Streptococcus mutans is an etiologic agent of human dental caries that forms dental plaque biofilms containing functional amyloids. Three amyloidogenic proteins, P1, WapA, and Smu_63c were previously identified. C123 and AgA are naturally occurring amyloid-forming fragments of P1 and WapA, respectively. We determined that four amyloidophilic dyes, ThT, CDy11, BD-oligo, and MK-H4, differentiate C123, AgA, and Smu_63c amyloid from monomers, but non-specific binding to bacterial cells in the absence of amyloid precludes their utility for identifying amyloid in biofilms. Congo redinduced birefringence is a more specific indicator of amyloid formation and differentiates biofilms formed by wild-type S. mutans from a triple ΔP1/WapA/Smu_63c mutant with reduced bioiflm forming capabilities. Amyloid accumulation is a late event, appearing in older S. mutans biofilms after 60hours of growth. Amyloid derived from pure preparations of all three proteins is visualized by electron microscopy as mat-like structures. Typical amyloid fibers become evident following protease digestion to eliminate non-specific aggregates and monomers. Amyloid mats, similar in appearance to those reported in S. mutans biofilm extracellular matrices, are reconstituted by co-incubation of monomers and amyloid fibers. X-ray fiber diffraction of amyloid mats and fibers from all three proteins demonstrate patterns reflective of a cross-β amyloid structure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A data-driven approach to modeling cancer cell mechanics during microcirculatory transport

In order to understand the effect of cellular level features on the transport of circulating cancer cells in the microcirculation, there has been an increasing reliance on high-resolution in silico models. Accurate simulation of cancer cells flowing with blood cells requires resolving cellular-scale interactions in 3D, which is a significant computational undertaking warranting a cancer cell model that is both computationally efficient yet sufficiently complex to capture relevant behavior. Given that the characteristics of metastatic spread are known to depend on cancer type, it is crucial to account for mechanistic behavior representative of a specific cancer’s cells. To address this gap, in the present work we develop and validate a means by which an efficient and popular membrane model-based approach can be used to simulate deformable cancer cells and reproduce experimental data from specific cell lines. Here, cells are modeled using the immersed boundary method (IBM) within a lattice Boltzmann method (LBM) fluid solver, and the finite element method (FEM) is used to model cell membrane resistance to deformation. Through detailed comparisons with experiments, we (i) validate this model to represent cancer cells undergoing large deformation, (ii) outline a systematic approach to parameterize different cell lines to optimally fit experimental data over a range of deformations, and (iii) provide new insight into nucleated vs. non-nucleated cell models and their ability to match experiments. While many works have used the membrane-model based method employed here to model generic cancer cells, no quantitative comparisons with experiments exist in the literature for specific cell lines undergoing large deformation. Here, we describe a phenomenological, data-driven approach that can not only yield good agreement for large deformations, but explicitly detail how it can be used to represent different cancer cell lines. This model is readily incorporated into cell-resolved hemodynamic transport simulations, and thus offers significant potential to complement experiments towards providing new insights into various aspects of cancer progression.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The cardiac molecular setting of metabolic syndrome in pigs reveals disease susceptibility and suggests mechanisms that exacerbate COVID-19 outcomes in patients

Abstract Although metabolic syndrome (MetS) is linked to an elevated risk of cardiovascular disease (CVD), the cardiac-specific risk mechanism is unknown. Obesity, hypertension, and diabetes (all MetS components) are the most common form of CVD and represent risk factors for worse COVID-19 outcomes compared to their non MetS peers. Here, we use obese Yorkshire pigs as a highly relevant animal model of human MetS, where pigs develop the hallmarks of human MetS and reproducibly mimics the myocardial pathophysiology in patients. Myocardium-specific mass spectroscopy-derived metabolomics, proteomics, and transcriptomics enabled the identity and quality of proteins and metabolites to be investigated in the myocardium to greater depth. Myocardium-specific deregulation of pro-inflammatory markers, propensity for arterial thrombosis, and platelet aggregation was revealed by computational analysis of differentially enriched pathways between MetS and control animals. While key components of the complement pathway and the immune response to viruses are under expressed, key N6-methyladenosin RNA methylation enzymes are largely overexpressed in MetS. Blood tests do not capture the entirety of metabolic changes that the myocardium undergoes, making this analysis of greater value than blood component analysis alone. Our findings create data associations to further characterize the MetS myocardium and disease vulnerability, emphasize the need for a multimodal therapeutic approach, and suggests a mechanism for observed worse outcomes in MetS patients with COVID-19 comorbidity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Comparative and pangenomic analysis of the genus Streptomyces

Abstract Streptomycetes are highly metabolically gifted bacteria with the abilities to produce bioproducts that have profound economic and societal importance. These bioproducts are produced by metabolic pathways including those for the biosynthesis of secondary metabolites and catabolism of plant biomass constituents. Advancements in genome sequencing technologies have revealed a wealth of untapped metabolic potential from Streptomyces genomes. Here, we report the largest Streptomyces pangenome generated by using 205 complete genomes. Metabolic potentials of the pangenome and individual genomes were analyzed, revealing degrees of conservation of individual metabolic pathways and strains potentially suitable for metabolic engineering. Of them, Streptomyces bingchenggensis was identified as a potent degrader of plant biomass. Polyketide, non-ribosomal peptide, and gamma-butyrolactone biosynthetic enzymes are primarily strain specific while ectoine and some terpene biosynthetic pathways are highly conserved. A large number of transcription factors associated with secondary metabolism are strain-specific while those controlling basic biological processes are highly conserved. Although the majority of genes involved in morphological development are highly conserved, there are strain-specific varieties which may contribute to fine tuning the timing of cellular differentiation. Overall, these results provide insights into the metabolic potential, regulation and physiology of streptomycetes, which will facilitate further exploitation of these important bacteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Evidence for unconventional superconductivity and nontrivial topology in PdTe

Abstract PdTe is a superconductor with T c ~ 4.25 K. Recently, evidence for bulk-nodal and surface-nodeless gap features has been reported in PdTe. Here, we investigate the physical properties of PdTe in both the normal and superconducting states via specific heat and magnetic torque measurements and first-principles calculations. Below T c , the electronic specific heat initially decreases in T 3 behavior (1.5 K < T < T c ) then exponentially decays. Using the two-band model, the superconducting specific heat can be well described with two energy gaps: one is 0.372 meV and another 1.93 meV. The calculated bulk band structure consists of two electron bands (α and β) and two hole bands (γ and η) at the Fermi level. Experimental detection of the de Haas-van Alphen (dHvA) oscillations allows us to identify four frequencies ( F α = 65 T, F β = 658 T, F γ = 1154 T, and F η = 1867 T for H // a ), consistent with theoretical predictions. Nontrivial α and β bands are further identified via both calculations and the angle dependence of the dHvA oscillations. Our results suggest that PdTe is a candidate for unconventional superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

A polyketide-based biosynthetic platform for diols, amino alcohols and hydroxy acids

Medium- and branched-chain diols and amino alcohols are important industrial solvents, polymer building blocks, cosmetics and pharmaceutical ingredients, yet biosynthetically challenging to produce. Here we present an approach that uses a modular polyketide synthase (PKS) platform for the efficient production of these compounds. This platform takes advantage of a versatile loading module from the rimocidin PKS and nicotinamide adenine dinucleotide phosphate-dependent terminal thioreductases. Reduction of the terminal aldehyde with alcohol dehydrogenases enables the production of diols, oxidation enables the production of hydroxy acids and specific transaminases allow the production of various amino alcohols. Furthermore, replacement of the malonyl-coenzyme A-specific acyltransferase in the extension module with methyl- or ethylmalonyl-coenzyme A-specific acyltransferase enables the production of branched-chain diols, amino alcohols and carboxylic acids in high titres. Use of our PKS platform in Streptomyces albus demonstrated the high tunability and efficiency of the platform.

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

A localized view on molecular dissociation via electron-ion partial covariance

Inner-shell photoelectron spectroscopy provides an element-specific probe of molecular structure, as core-electron binding energies are sensitive to the chemical environment. Short-wavelength femtosecond light sources, such as Free-Electron Lasers (FELs), even enable time-resolved site-specific investigations of molecular photochemistry. Here, we study the ultraviolet photodissociation of the prototypical chiral molecule 1-iodo-2-methylbutane, probed by extreme-ultraviolet (XUV) pulses from the Free-electron LASer in Hamburg (FLASH) through the ultrafast evolution of the iodine 4d binding energy. Methodologically, we employ electron-ion partial covariance imaging as a technique to isolate otherwise elusive features in a two-dimensional photoelectron spectrum arising from different photofragmentation pathways. The experimental and theoretical results for the time-resolved electron spectra of the 4d 3/2 and 4d 5/2 atomic and molecular levels that are disentangled by this method provide a key step towards studying structural and chemical changes from a specific spectator site.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Targeted sulfur(VI) fluoride exchange-mediated covalent modification of a tyrosine residue in the catalytic pocket of tyrosyl-DNA phosphodiesterase 1

Abstract Developing effective inhibitors of the DNA repair enzyme tyrosyl-DNA phosphodiesterase 1 (TDP1) has been challenging because of the enzyme shallow catalytic pocket and non-specific substrate binding interactions. Recently, we discovered a quinolone-binding hot spot in TDP1’s active site proximal to the evolutionary conserved Y204 and F259 residues that position DNA. Sulfur (VI) fluoride exchange (SuFEx) is a biocompatible click chemistry reaction that enables acylation of protein residues, including tyrosine. Selective protein modifications can provide insights into the biological roles of proteins and inform ligand design. As we report herein, we used SuFEx chemistries to prepare covalent TDP1-bound binders showing site-specific covalent bonds with Y204. Our work presents the first application of SuFEx chemistries to TDP1 ligands. It validates the ability to covalently modify specific TDP1 residues by designed targeting and adds to the chemical biology resource toolbox for studying TDP1.

Chemistry↗
DOE OSTI2022

Deep transfer operator learning for partial differential equations under conditional shift

Transfer learning enables the transfer of knowledge gained while learning to perform one task (source) to a related but different task (target), hence addressing the expense of data acquisition and labelling, potential computational power limitations and dataset distribution mismatches. Here, we propose a new transfer learning framework for task-specific learning (functional regression in partial differential equations) under conditional shift based on the deep operator network (DeepONet). Task-specific operator learning is accomplished by fine-tuning task-specific layers of the target DeepONet using a hybrid loss function that allows for the matching of individual target samples while also preserving the global properties of the conditional distribution of the target data. Inspired by conditional embedding operator theory, we minimize the statistical distance between labelled target data and the surrogate prediction on unlabelled target data by embedding conditional distributions onto a reproducing kernel Hilbert space. We demonstrate the advantages of our approach for various transfer learning scenarios involving nonlinear partial differential equations under diverse conditions due to shifts in the geometric domain and model dynamics. Our transfer learning framework enables fast and efficient learning of heterogeneous tasks despite considerable differences between the source and target domains.

42 ENGINEERING↗
DOE OSTI2022

Genotype to ecotype in niche environments: adaptation of Arthrobacter to carbon availability and environmental conditions

Niche environmental conditions influence both the structure and function of microbial communities and the cellular function of individual strains. The terrestrial subsurface is a dynamic and diverse environment that exhibits specific biogeochemical conditions associated with depth, resulting in distinct environmental niches. Here, we present the characterization of seven distinct strains belonging to the genus Arthrobacter isolated from varying depths of a single sediment core and associated groundwater from an adjacent well. We characterized genotype and phenotype of each isolate to connect specific cellular functions and metabolisms to ecotype. Arthrobacter isolates from each ecotype demonstrated functional and genomic capacities specific to their biogeochemical conditions of origin, including laboratory-demonstrated characterization of salinity tolerance and optimal pH, and genes for utilization of carbohydrates and other carbon substrates. Analysis of the Arthrobacter pangenome revealed that it is notably open with a volatile accessory genome compared to previous pangenome studies on other genera, suggesting a high potential for adaptability to environmental niches.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Aqueous solvation of the chloride ion revisited with density functional theory: impact of correlation and exchange approximations

The specificity of aqueous halide solvation is fundamental to a wide range of bulk and interfacial phenomena spanning from biology to materials science. Halide polarizability is thought to drive the ion specificity, and if so, it is essential to have an accurate description of the electronic properties of halide ions in water. To this end, the solvation of the chloride anion, Cl - has been reinvestigated with state-of-the-art density functional theory. Specifically, the PBE-D3, PBE0-D3, and SCAN functionals have been employed to probe the impact of correlation and exchange approximations. Anticipating the findings, adding exact exchange improves the electronic structure, but simultaneously significantly reduces the Cl - polarizability, resulting in an over-structured Cl–O radial distribution function (RDF) and longer water H-bond lifetimes to Cl - . SCAN does not yield as much improvement in the energetics of Cl - relative to bulk water, but does result in a smaller reduction of the polarizability and thus a less structured Cl–O RDF, which agrees better with experiment. Special consideration is therefore warranted in assessing the impact of exchange on the energy, charge density, and the charge density response when designing and testing hybrid functionals for aqueous halide solvation.

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

Mechanically tunable elastomer and cellulose nanocrystal composites as scaffolds for in vitro cell studies

Considering the range of properties that various materials offer for tissue engineering it has come clear that no one size fits all, as no one material can be fully effective for all types of cell and ensuing tissues. Scaffolds need to address the delicate balance between cell-scaffold interactions and the particular requirements of different cell types. To address the specific needs for the controlled growth of tissues it is imperative to match scaffold stiffness and elasticity to cells and tissues of interest to promote regeneration success. We here report an efficient method for creating scaffolds of tunable elasticity by generating a range of composites based on ε-caprolactone-D,L-lactide-based elastomer with cellulose nanocrystals (CNC). Two specific composites with different Young's modulus (E) values (~5 MPa and ~15 MPa) were selected and fully evaluated by tensile tests, Fourier Transform-Infrared (FT-IR), Scanning Electron Microscopy (SEM), contact angle measurements, and X-ray scattering. As a proof of concept this work studies how matching the scaffold's mechanical properties to neuroblastomas and fibroblasts cells affects cell behavior. Specifically, the composite with lower E, by design with less CNC content, is more suitable for neuroblastomas, whereas the one with higher E via higher CNC content is more suited for human dermal fibroblasts. The approach of matching cells with appropriate mechanical environments can provide important insights into fundamental cell behaviors.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Towards cost-competitive middle distillate fuels from ethanol within a market-flexible C2 platform-based biorefinery concept

Ethanol to middle distillates (ETMD) is a promising pathway to produce sustainable liquid fuels to decarbonize the hard-to-electrify transportation sectors due to (1) the abundant sugar/starch and lignocellulosic biomass, (2) the existing deployment scale of fuel ethanol production (similar to 29 billion gallons per year globally), and (3) emerging opportunities in C2+ alcohol synthesis from CO2. Here we report a conceptual market-responsive biorefinery centered around a new ETMD pathway based on one-step ethanol to butene-rich olefins (ETO) over a Cu-Zn-Y/Beta catalyst. Specifically, this ethanol conversion pathway comprises one-step ETO, oligomerization, and hydrotreating. This ETO is distinct from that in the conventional ethanol-to-jet process which is based on two-step ethanol to ethylene and ethylene oligomerization to butenes. Butene-rich olefins can be shifted to butadiene-rich products by simply changing the reaction atmosphere from hydrogen to inert gas over the same ETO catalyst. Leveraging the experimental results, baseline techno-economic analysis (TEA) and sensitivity analysis indicate that the ethanol conversion cost is $0.60 per gallon gasoline equivalent (GGE), with opportunities for further cost reduction via improving the liquid hydrocarbon yield and space velocities, and process optimization on balancing dewatering of ethanol feed prior to the ETO step. The minimum fuel selling price (MFSP) of liquid hydrocarbons derived from corn starch ethanol with butadiene as coproduct is $1.64 per GGE, in the range that is cost competitive with petroleum kerosene-type jet fuel. Projected MFSP for cellulosic ethanol (corn stover) derived hydrocarbons is below $3.00 per GGE and co-production of butadiene further reduces the MFSP to $1.70 per GGE. The Well-to-Wake life-cycle analysis indicates that 85% greenhouse gas emission reduction can be achieved when using corn stover compared to petroleum reference and the associated carbon credits will provide significant economic incentives to favor the cellulosic ethanol-derived hydrocarbon fuels. This study demonstrates a low-cost pathway to middle distillate fuels leveraging existing ethanol infrastructure, where catalysis innovation drives the reduction of process complexity and flexible coproduction of a value-added chemical product.

Zhang, Junyan↗