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At least 1,549 records · Page 86
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Structural basis of the promiscuity of the unusual Fe(II) and 2-oxoglutarate dependent human aspartate/asparagine-β-hydroxylase

Protein-hydroxylation catalysed by Fe(II) and 2-oxoglutarate (2OG) dependent oxygenases is an important regulatory mechanism in human biology. Such oxygenases typically coordinate their Fe(II) cofactor via a conserved triad of an aspartate- or glutamate- and two histidine-residues. By contrast, aspartate/asparagine β-hydroxylase (AspH), which catalyses asparagine/aspartate-residue oxidation in epidermal growth factor-like domains (EGFDs), has only two histidine-residues (H679, H725), with a water occupying the site normally occupied by an aspartate- or glutamate-residue. We describe mechanistic studies with catalytically active AspH crystals. Turnover studies with single crystals under cryogenic conditions give (3 R)-hydroxylated EGFDs with the product alcohol coordinating Fe(II) trans to H725. Time-resolved serial crystallography of microcrystals using an acoustic droplet ejection system, coupled to X-ray emission analyses, demonstrate turnover within 1.5 s, giving a product complex in which Fe(II) is regenerated. Solution and crystallographic studies with the O 2 surrogate nitric oxide imply O 2 binds to Fe(II) trans to H725. The additional Fe-chelating water is maintained throughout AspH catalysis and is not directly involved in substrate hydroxylation, because O 2 is the sole oxygen source in alcohol products, as shown by 18 O labelling studies. The results reveal how AspH accommodates both aspartate- and asparagine-substrates and will assist in efforts targeting AspH for cancer treatment.

de Munnik, Mariska↗
DOE OSTI2025

Metabolic flux analysis in leaf metabolism quantifies the link between photorespiration and one carbon metabolism

Photorespiration is the second largest carbon flux in most leaves and is integrated into metabolism broadly including one-carbon (C 1 ) metabolism. Photorespiratory intermediates such as serine and others may serve as sources of C 1 units, but it is unclear to what degree this happens in vivo, whether altered photorespiration changes flux to C 1 metabolism, and if so through which intermediates. To clarify these questions, we quantified carbon flux from photorespiration to C 1 metabolism using 13 CO 2 labelling and isotopically non-stationary metabolic flux analysis in Arabidopsis thaliana under different O 2 concentrations which modulate photorespiration. The results revealed that ~5.8% of assimilated carbon passes to C 1 metabolism under ambient photorespiratory conditions, but this flux greatly decreases under limited photorespiration. Furthermore, the primary carbon flux from photorespiration to C 1 metabolism is through serine. Our results provide fundamental insight into how photorespiration is integrated into C 1 metabolism, with possible implications for C 1 metabolic response to climate change.

Photosynthesis↗
DOE OSTI2021

Defect detection in atomic-resolution images via unsupervised learning with translational invariance

Abstract Crystallographic defects can now be routinely imaged at atomic resolution with aberration-corrected scanning transmission electron microscopy (STEM) at high speed, with the potential for vast volumes of data to be acquired in relatively short times or through autonomous experiments that can continue over very long periods. Automatic detection and classification of defects in the STEM images are needed in order to handle the data in an efficient way. However, like many other tasks related to object detection and identification in artificial intelligence, it is challenging to detect and identify defects from STEM images. Furthermore, it is difficult to deal with crystal structures that have many atoms and low symmetries. Previous methods used for defect detection and classification were based on supervised learning, which requires human-labeled data. In this work, we develop an approach for defect detection with unsupervised machine learning based on a one-class support vector machine (OCSVM). We introduce two schemes of image segmentation and data preprocessing, both of which involve taking the Patterson function of each segment as inputs. We demonstrate that this method can be applied to various defects, such as point and line defects in 2D materials and twin boundaries in 3D nanocrystals.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Predicting solid state material platforms for quantum technologies

Semiconductor materials provide a compelling platform for quantum technologies (QT). However, identifying promising material hosts among the plethora of candidates is a major challenge. Therefore, we have developed a framework for the automated discovery of semiconductor platforms for QT using material informatics and machine learning methods. Different approaches were implemented to label data for training the supervised machine learning (ML) algorithms logistic regression, decision trees, random forests and gradient boosting. We find that an empirical approach relying exclusively on findings from the literature yields a clear separation between predicted suitable and unsuitable candidates. In contrast to expectations from the literature focusing on band gap and ionic character as important properties for QT compatibility, the ML methods highlight features related to symmetry and crystal structure, including bond length, orientation and radial distribution, as influential when predicting a material as suitable for QT.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Leveraging generative adversarial networks to create realistic scanning transmission electron microscopy images

Abstract The rise of automation and machine learning (ML) in electron microscopy has the potential to revolutionize materials research through autonomous data collection and processing. A significant challenge lies in developing ML models that rapidly generalize to large data sets under varying experimental conditions. We address this by employing a cycle generative adversarial network (CycleGAN) with a reciprocal space discriminator, which augments simulated data with realistic spatial frequency information. This allows the CycleGAN to generate images nearly indistinguishable from real data and provide labels for ML applications. We showcase our approach by training a fully convolutional network (FCN) to identify single atom defects in a 4.5 million atom data set, collected using automated acquisition in an aberration-corrected scanning transmission electron microscope (STEM). Our method produces adaptable FCNs that can adjust to dynamically changing experimental variables with minimal intervention, marking a crucial step towards fully autonomous harnessing of microscopy big data.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

DONUT: physics-aware machine learning for real-time X-ray nanodiffraction analysis

Coherent X-ray scattering techniques are critical for investigating the fundamental structural properties of materials at the nanoscale. While advancements have made these experiments more accessible, real-time analysis remains a significant bottleneck, often hindered by artifacts and computational demands. In scanning X-ray nanodiffraction microscopy, which is widely used to spatially resolve structural heterogeneities, this challenge is compounded by the convolution of the divergent beam with the sample’s local structure. To address this, we introduce DONUT (Diffraction with Optics for Nanobeam by Unsupervised Training), a physics-aware neural network designed for the rapid and automated analysis of nanobeam diffraction data. By incorporating a differentiable geometric diffraction model directly into its architecture, DONUT learns to predict crystal lattice strain and orientation in real-time. Crucially, this is achieved without reliance on labeled datasets or pre-training, overcoming a fundamental limitation for supervised machine learning in X-ray science. We demonstrate experimentally that DONUT accurately extracts all features within the data over 200 times more efficiently than conventional fitting methods.

Materials science↗
DOE OSTI2025

Real-space chirality from crystalline topological defects in the Kitaev spin liquid

We show that certain crystalline topological defects in the gapless Kitaev honeycomb spin liquid model generate a chirality and Majorana fermion orbital magnetization that depends in a universal manner on their emergent flux. Focusing on 5–7 dislocations as building blocks, consisting of pentagon and heptagon disclinations, we identify the Kitaev bond label configurations that preserve solvability. By computing two formulations of local markers M(r) we find that the 5 and 7 lattice defects generate a real-space contribution to Chern number and an associated Majorana fermion orbital magnetization proportional to M(r). The sign of the M(r) contribution from each 5/7 defect, i.e. its q M = ± 1 chirality, is determined by the defect Frank angle sign F and emergent gauge field flux W = ± i through the expression q M = − iFW. Remarkably, though lattice curvature and torsion can interplay with the surrounding gapless background to modify the profile of M(r), its sign q M is determined locally, implying that crystalline defects in the Kitaev spin liquid can generate a robust and observable chirality.

Magnetic properties and materials↗
DOE OSTI2021

Site-selective tyrosine bioconjugation via photoredox catalysis for native-to-bioorthogonal protein transformation

The growing prevalence of synthetically modified proteins in pharmaceuticals and materials has exposed the need for efficient strategies to enable chemical modifications with high site-selectivity. While genetic engineering can incorporate non-natural amino acids into recombinant proteins, regioselective chemical modification of wild-type proteins remains a challenge. In this work, we use photoredox catalysis to develop a site-selective tyrosine bioconjugation pathway that incorporates bioorthogonal formyl groups, which subsequently allows for the synthesis of structurally defined fluorescent conjugates from native proteins. A water-soluble photocatalyst, lumiflavin, has been shown to induce oxidative coupling between a previously unreported phenoxazine dialdehyde tag and a single tyrosine site, even in the presence of multiple tyrosyl side chains, through the formation of a covalent C–N bond. A variety of native proteins, including those with multiple tyrosines, can successfully undergo both tyrosine-specific and single-site-selective labelling. This technology directly introduces aldehyde moieties onto native proteins, enabling rapid product diversification using an array of well-established bioorthogonal functionalization protocols including the alkyne–azide click reaction.

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

Upcycling of polyethylene to gasoline through a self-supplied hydrogen strategy in a layered self-pillared zeolite

Conversion of plastic wastes to valuable carbon resources without using noble metal catalysts or external hydrogen remains a challenging task. Here we report a layered self-pillared zeolite that enables the conversion of polyethylene to gasoline with a remarkable selectivity of 99% and yields of >80% in 4 h at 240 °C. The liquid product is primarily composed of branched alkanes (selectivity of 72%), affording a high research octane number of 88.0 that is comparable to commercial gasoline (86.6). In situ inelastic neutron scattering, small-angle neutron scattering, solid-state nuclear magnetic resonance, X-ray absorption spectroscopy and isotope-labelling experiments reveal that the activation of polyethylene is promoted by the open framework tri-coordinated Al sites of the zeolite, followed by β-scission and isomerization on Brönsted acids sites, accompanied by hydride transfer over open framework tri-coordinated Al sites through a self-supplied hydrogen pathway to yield selectivity to branched alkanes. This study shows the potential of layered zeolite materials in enabling the upcycling of plastic wastes.

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

The enduring role of contracts for difference in risk management and market creation for renewables

Governments procure renewables through a variety of mechanisms. Contracts for difference (CfDs) have been used for more than 50% of the global offshore wind supply. The payments awarded through CfDs are sometimes labelled subsidies, suggesting that they support uneconomic activity. Here, in this study, we argue that the primary role of CfDs is rather risk management by creating a market for electricity supply at stable long-term prices. Similar to its use in other sectors of the economy, this contract type transforms a variable to a fixed price to reallocate volatility risks. Such long-term contracts are often necessary for renewables financing due to limited hedging options in existing markets. Our perspective could imply a shift in perception towards CfDs as a fundamental and lasting market feature. We hope to stimulate a timely discussion about the impact of greater CfD diffusion on electricity market mechanisms, risk allocation and the potential for combining fragmented streams of energy finance, market and policy research.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Bioorthogonal catalytic patch

The toxicity and complicated administration procedures of transition metal catalysts have hampered the applications of bioorthogonal catalysis in vivo. Here the authors fill the needles of a microneedle array patch with palladium nanoparticles deposited on titanium nanosheets and show that the device, applied locally on the skin of mouse models bearing melanoma, promotes intratumoural conversion of systemically injected caged doxorubicin into the active drug, reducing its toxicity and side effects. Bioorthogonal catalysis mediated by transition metals has inspired a new subfield of artificial chemistry complementary to enzymatic reactions, enabling the selective labelling of biomolecules or in situ synthesis of bioactive agents via non-natural processes. However, the effective deployment of bioorthogonal catalysis in vivo remains challenging, mired by the safety concerns of metal toxicity or complicated procedures to administer catalysts. Here, we describe a bioorthogonal catalytic device comprising a microneedle array patch integrated with Pd nanoparticles deposited on TiO 2 nanosheets. This device is robust and removable, and can mediate the local conversion of caged substrates into their active states in high-level living systems. In particular, we show that such a patch can promote the activation of a prodrug at subcutaneous tumour sites, restoring its parent drug's therapeutic anticancer properties. Finally, this in situ applied device potentiates local treatment efficacy and eliminates off-target prodrug activation and dose-dependent side effects in healthy organs or distant tissues.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Li + (ionophore) nanoclusters engineered aqueous/non-aqueous biphasic electrolyte solutions for high-potential lithium-based batteries

The use of aqueous/non-aqueous biphasic electrolyte solutions in Li-based battery systems circumvents the limitations of poor reductive stability of aqueous electrolyte solutions, broadening their electrochemical stability window. However, aqueous/non-aqueous electrolytes suffer from biphasic mixing and high impedance when Li ions cross the biphasic interface. Here we propose the use of 12-crown-4 (12C4) and tetraglyme (G4) as lithium ionophores to form Li + (ionophore) nanoclusters in both non-aqueous and aqueous phases to overcome the interface challenges in biphasic electrolytes. The Li + (ionophore) nanoclusters have the H 2 O-excluding inner Li + solvation structure in non-polar 1,1,2,2-tetrafluoroethyl 2,2,3,3-tetrafluoropropyl ether (TTE), allowing fast charge transport across the biphasic interface without solvent mixing or water shuttling. Further, a tailored electrolyte formulation comprising the lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) salt, 12C4, TTE and H 2 O solvents (labelled LiTFSI-12C4@TTE/H 2 O) demonstrates low impedance (2.7 Ω cm -2 ) at the TTE/H 2 O interface and enabling 2,000 cycles of prelithiated graphite||LiFePO 4 coin cells at 850 mA g -1 with an average Coulombic efficiency of 99.8%. Single-layer 22.5 mAh Li||LiMn 2 O 4 pouch cells using LiTFSI-12C4@TTE/H 2 O electrolyte with G4 delivered a stable discharge capacity of about 1.3 mAh cm -2 for 80 cycles at 0.5 mA cm -2 .

25 ENERGY STORAGE↗
DOE OSTI2025

Imaging and spatially resolved mass spectrometry applications in nephrology

The application of spatially resolved mass spectrometry (MS) and MS imaging approaches for studying biomolecular processes in the kidney is rapidly growing. These powerful methods, which enable label-free and multiplexed detection of many molecular classes across omics domains (including metabolites, drugs, proteins and protein post-translational modifications), are beginning to reveal new molecular insights related to kidney health and disease. Further, the complexity of the kidney often necessitates multiple scales of analysis for interrogating biofluids, whole organs, functional tissue units, single cells and subcellular compartments. Various MS methods can generate omics data across these spatial domains and facilitate both basic science and pathological assessment of the kidney. Optimal processes related to sample preparation and handling for different MS applications are rapidly evolving. Emerging technology and methods, improvement of spatial resolution, broader molecular characterization, multimodal and multiomics approaches and the use of machine learning and artificial intelligence approaches promise to make these applications even more valuable in the field of nephology. Overall, spatially resolved MS and MS imaging methods have the potential to fill much of the omics gap in systems biology analysis of the kidney and provide functional outputs that cannot be obtained using genomics and transcriptomic methods.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Mirror-symmetry violation in bound nuclear ground states

Conservation laws are deeply related to any symmetry present in a physical system. Analogously to electrons in atoms exhibiting spin symmetries, it is possible to consider neutrons and protons in the atomic nucleus as projections of a single fermion with an isobaric spin (isospin) of t = 1/2. Every nuclear state is thus characterized by a total isobaric spin T and a projection T z —two quantities that are largely conserved in nuclear reactions and decays. A mirror symmetry emerges from this isobaric-spin formalism: nuclei with exchanged numbers of neutrons and protons, known as mirror nuclei, should have an identical set of states, including their ground state, labelled by their total angular momentum J and parity π. In this work, we report evidence of mirror-symmetry violation in bound nuclear ground states within the mirror partners strontium-73 and bromine-73. We find that a J π = 5/2 - spin assignment is needed to explain the proton-emission pattern observed from the T = 3/2 isobaric-analogue state in rubidium-73, which is identical to the ground state of strontium-73. Therefore the ground state of strontium-73 must differ from its J π = 1/2 - mirror bromine-73. This observation offers insights into charge-symmetry-breaking forces acting in atomic nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Experimental evidence for recovery of mercury-contaminated fish populations

Anthropogenic releases of mercury (Hg) are a human health issue because the potent toxicant methylmercury (MeHg), formed primarily by microbial methylation of inorganic Hg in aquatic ecosystems, bioaccumulates to high concentrations in fish consumed by humans. Predicting the efficacy of Hg pollution controls on fish MeHg concentrations is complex because many factors influence the production and bioaccumulation of MeHg. Here we conducted a 15-year whole-ecosystem, single-factor experiment to determine the magnitude and timing of reductions in fish MeHg concentrations following reductions in Hg additions to a boreal lake and its watershed. During the seven-year addition phase, we applied enriched Hg isotopes to increase local Hg wet deposition rates fivefold. The Hg isotopes became increasingly incorporated into the food web as MeHg, predominantly from additions to the lake because most of those in the watershed remained there. Thereafter, isotopic additions were stopped, resulting in an approximately 100% reduction in Hg loading to the lake. The concentration of labelled MeHg quickly decreased by up to 91% in lower trophic level organisms, initiating rapid decreases of 38–76% of MeHg concentration in large-bodied fish populations in eight years. Although Hg loading from watersheds may not decline in step with lowering deposition rates, this experiment clearly demonstrates that any reduction in Hg loadings to lakes, whether from direct deposition or runoff, will have immediate benefits to fish consumers.

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

Modification of cell wall polysaccharide guides cell division in Streptococcus mutans

In ovoid-shaped, Gram-positive bacteria, MapZ guides FtsZ-ring positioning at cell equators. The cell wall of the ovococcus Streptococcus mutans contains peptidoglycan decorated with serotype c carbohydrates (SCCs). In the present study, we identify the major cell separation autolysin AtlA as an SCC-binding protein. AtlA binding to SCC is attenuated by the glycerol phosphate (GroP) modification. Using fluorescently labeled AtlA constructs, we mapped SCC distribution on the streptococcal surface, revealing enrichment of GroP-deficient immature SCCs at the cell poles and equators. The immature SCCs co-localize with MapZ at the equatorial rings throughout the cell cycle. In GroP-deficient mutants, AtlA is mislocalized, resulting in dysregulated cellular autolysis. These mutants display morphological abnormalities associated with MapZ mislocalization, leading to FtsZ-ring misplacement. Altogether, our data support a model in which maturation of a cell wall polysaccharide provides the molecular cues for the recruitment of cell division machinery, ensuring proper daughter cell separation and FtsZ-ring positioning.

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

Long-term super-resolution inner mitochondrial membrane imaging with a lipid probe

The inner mitochondrial membrane (IMM) generates power to drive cell function, and its dynamics control mitochondrial health and cellular homeostasis. Here, we describe the cell-permeant, lipid-like small molecule MAO-N 3 and use it to assemble high-density environmentally sensitive (HIDE) probes that selectively label and image the IMM in live cells and multiple cell states. MAO-N 3 pairs with strain-promoted azide–alkyne click chemistry-reactive fluorophores to support HIDE imaging using confocal, structured illumination, single-molecule localization and stimulated emission depletion microscopy, all with significantly improved resistance to photobleaching. These probes generate images with excellent spatial and temporal resolution, require no genetic manipulations, are non-toxic in model cell lines and primary cardiomyocytes (even under conditions that amplify the effects of mitochondrial toxins) and can visualize mitochondrial dynamics for 12.5 h. This probe will enable comprehensive studies of IMM dynamics with high temporal and spatial resolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗