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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Cloning and characterization of a panel of mitochondrial targeting sequences for compartmentalization engineering in Saccharomyces cerevisiae

Mitochondrion is generally considered as the most promising subcellular organelle for compartmentalization engineering. Much progress has been made in reconstituting whole metabolic pathways in the mitochondria of yeast to harness the precursor pools (i.e., pyruvate and acetyl-CoA), bypass competing pathways, and minimize transportation limitations. However, only a few mitochondrial targeting sequences (MTSs) have been characterized (i.e., MTS of COX4), limiting the application of compartmentalization engineering for multigene biosynthetic pathways in the mitochondria of yeast. In the present study, based on the mitochondrial proteome, a total of 20 MTSs were cloned and the efficiency of these MTSs in targeting heterologous proteins, including the Escherichia coli FabI and enhanced green fluorescence protein (EGFP) into the mitochondria was evaluated by growth complementation and confocal microscopy. After systematic characterization, six of the well!performed MTSs were chosen for the colocalization of complete biosynthetic pathways into the mitochondria. As proof of concept, the full alpha-santalene biosynthetic pathway consisting of 10 expression cassettes capable of converting acety coA to alpha-santalene was compartmentalized into the mitochondria, leading to a 3.7 fold improvement in the production of alpha-santalene. Furthermore, the newly characterized MTSs should contribute to the expanded metabolic engineering and synthetic biology toolbox for yeast mitochondrial compartmentalization engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Target–decoy false discovery rate estimation using Crema

Assigning statistical confidence estimates to discoveries produced by a tandem mass spectrometry proteomics experiment is critical to enabling principled interpretation of the results and assessing the cost/benefit ratio of experimental follow-up. The most common technique for computing such estimates is to use target-decoy competition (TDC), in which observed spectra are searched against a database of real (target) peptides and a database of shuffled or reversed (decoy) peptides. TDC procedures for estimating the false discovery rate (FDR) at a given score threshold have been developed for application at the level of spectra, peptides, or proteins. Although these techniques are relatively straightforward to implement, it is common in the literature to skip over the implementation details or even to make mistakes in how the TDC procedures are applied in practice. Here we present Crema, an open-source Python tool that implements several TDC methods of spectrum-, peptide- and protein-level FDR estimation. Crema is compatible with a variety of existing database search tools and provides a straightforward way to obtain robust FDR estimates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Knocking Out the Wall: Revised Protocols for Gene Targeting in Physcomitrella patens

The moss Physcomitrella patens has become established as a model for investigating plant gene function due to the feasibility of gene targeting. The chemical composition of the P. patens cell wall is similar to that of vascular plants and phylogenetic analyses of glycosyltransferase sequences from the P. patens genome have identified genes that putatively encode cell wall biosynthetic enzymes, providing a basis for investigating the evolution of cell wall polysaccharides and the enzymes that synthesize them. Here, the protocols described in this chapter provide methods for targeted gene knockout in P. patens, from constructing vectors and maintaining cultures to transforming protoplasts and analysing the genotypes and phenotypes of the resulting transformed lines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Sensitivity of an early dark matter search using the electromagnetic calorimeter as a target for the Light Dark Matter eXperiment

The Light Dark Matter eXperiment (LDMX) is proposed to employ a thin tungsten target and a multi-GeV electron beam to carry out a missing momentum search for the production of dark matter candidate particles. We study the sensitivity for a complementary missing-energy-based search using the LDMX Electromagnetic Calorimeter as an active target with a focus on early running. In this context, we construct an event selection from a limited set of variables that projects sensitivity into previously-unexplored regions of light dark matter phase space — down to an effective dark photon interaction strength y of approximately 2 × 10 −13 (5 × 10 −12 ) for a 1 MeV (10 MeV) dark matter candidate mass.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Design and synthesis of astatinated benzothiazole compounds for their potential use in Targeted Alpha Therapy (TAT) strategies to treat Alzheimer's disease-associated amyloid plaques

Alzheimer's disease (AD) is a terminal neurodegenerative disease characterized by the buildup of amyloid fibrils, amorphous aggregates and tauopathies. Several treatment modalities, which rely on various biological processes to reduce disease burden, have been largely ineffective at treating Alzheimer's disease. Targeted alpha therapy (TAT) has demonstrated positive results in the treatment of cancer. Benzothiazole derivatives have been successfully shown to target these plaques and are used in several imaging applications. One such derivative, Flutemetamol (Vizamyl TM ) is an FDA approved diagnostic tool for PET imaging of AD-associated plaques. We report the radiolabeling of benzothiazole derivatives with 211 At, a 7.2 h alpha emitting radionuclide, using a copper catalyzed reaction with a boronic acid precursor molecule. In conclusion, our final compound [ 211 At]3'-At-PIB-OMe had a radiochemical yield of 55% and was found to be stable for at least 3 h in phosphate buffered saline.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Horizontal 1 K refrigerator with novel loading mechanism for polarized solid targets

We describe a helium evaporation refrigerator used to cool dynamically polarized proton and deuteron targets for electron-scattering experiments using the CEBAF Large Acceptance Spectrometer CLAS12 at Jefferson Lab. The geometry of the CLAS12 detector systems places severe design and construction constraints on the refrigerator and its ancillary equipment, resulting in a horizontal cryostat with a length of 4 m. The 16 cm 3 target samples, consisting of frozen ammonia (NH 3 or ND 3 ), are loaded at the upstream end of the cryostat and moved to the beam-interaction region using a novel transport mechanism. At this location they are cooled with superfluid helium and polarized via dynamic nuclear polarization at 1 K and 5 T. In this manner samples can be replaced and cooled to 1 K in about 30 minutes without disturbing any elements of the electron beam line or particle detection system. In conclusion, we estimate that this method saved 18 days of valuable beam time over the course of a recent, 88-day long experiment.

Evaporation refrigerator↗
DOE OSTI2021

Novel theranostic agent for PET imaging and targeted radiopharmaceutical therapy of tumour-infiltrating immune cells in glioma

Background: Malignant gliomas are deadly tumours with few therapeutic options. Although immunotherapy may be a promising therapeutic strategy for treating gliomas, a significant barrier is the CD11b + tumour-associated myeloid cells (TAMCs), a heterogeneous glioma infiltrate comprising up to 40% of a glioma's cellular mass that inhibits anti-tumour T-cell function and promotes tumour progression. A theranostic approach uses a single molecule for targeted radiopharmaceutical therapy (TRT) and diagnostic imaging; however, there are few reports of theranostics targeting the tumour microenvironment. Methods: Utilizing a newly developed bifunctional chelator, Lumi804, an anti-CD11b antibody (αCD11b) was readily labelled with either Zr-89 or Lu-177, yielding functional radiolabelled conjugates for PET, SPECT, and TRT. Findings: 89 Zr/ 177 Lu-labeled Lumi804-αCD11b enabled non-invasive imaging of TAMCs in murine gliomas. Additionally, 177 Lu-Lumi804-αCD11b treatment reduced TAMC populations in the spleen and tumour and improved the efficacy of checkpoint immunotherapy. Interpretation: 89 Zr- and 177 Lu-labeled Lumi804-αCD11b may be a promising theranostic pair for monitoring and reducing TAMCs in gliomas to improve immunotherapy responses.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Quantifying policy gaps for achieving the net-zero GHG emissions target in the U.S. light-duty vehicle market through electrification

The U.S. light-duty vehicle (LDV) industry, a major greenhouse gas (GHG) emitting sector, is embracing decarbonization. Considering only electrification pathways, this study uses publicly-available tools – MA3T and VISION on vehicle market penetration, fleet accounting and life-cycle analysis to quantify the policy gaps for LDVs to achieve the net-zero GHG emissions target in nine vehicle penetration cases under two electricity mix scenarios, including the U.S. administration's decarbonization strategy – 100% clean electricity by 2035. The MA3T model is a multinomial discrete choice model for market share projection by vehicle technology, and the VISION is a vehicle stocks and GHG emissions projection model by using vehicle and travel characteristics. This study projects the impacts of technology and policy enforcement on shaping the dynamics and decarbonization of the LDV market. Additionally, achieving the expected improvement of battery technology and charging infrastructure is critical but can only reduce the 2050 GHG emissions to 48–54% of the 2020 level under the electricity renewable mix scenario. It is almost impossible to achieve a 100% battery electric vehicle stock by 2050 and the 2050 net-zero target in the LDV industry unless ban of internal combustion engine technology is implemented starting in 2035 and under the 2035 100% clean electricity scenario. These extreme conditions also sacrifice most from the consumer welfare perspective. A greater policy forcing intensity accelerates plug-in electric vehicle penetration, while with declining marginal effect and reduced consumer welfare. Among the investigated policy scenarios, the policy forcing intensity equivalent to a fuel tax of $1–2 per gasoline gallon reduces the most GHG emissions while keeping a positive consumer welfare.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

NIRDye 812: A molecular platform tailored for multimodal bioimaging applications of targeted fluorescence- and photoacoustic-guided surgery

The primary treatment for malignant tumors remains to be surgical removal of the diseased tissue. The presence or absence of residual diseased tissue at the tumor margin is the strongest predictor of postoperative prognosis and recurrence. Accordingly, reliance on the ability of surgeons to visually distinguish diseased tissue from healthy tissue unambiguously in real time is crucial. Near infrared-I (NIRsingle bondI) fluorescence-emitting targeting biomolecular constructs such as anticancer antibody-fluorophore conjugates, namely cetuximab-IRDye® 800CW (CTB-IRDye® 800CW), are FDA-approved for clinical trial usage in the fluorescence-guided resection of diseased tissue due to affording improved direct visualization of tumor tissue when compared to the use of either the unaided eye under standard white light illumination (WLI) surgical techniques or non-targeting fluorophores. Unfortunately, though helpful, CTB-IRDye® 800CW affords limited (i) identification of diseased tissue and (ii) tumor margin delineation, because the immunoconjugate generates suboptimal tumor-to-background ratios (TBRs) as a result of its spectral/photophysical profiles poorly aligning with the fixed optical windows of pre-/clinical setups. As such, CTB-IRDye® 800CW is more prone to affording incomplete resection compared to if TBRs were higher due to otherwise. Here, to aid in accurately identifying deep-seated diseased tissue, photoacoustic (PA) tomography has been implemented alongside CTB-IRDye® 800CW to achieve PA signals that could result in higher TBRs. However, in clinical trial practice, using IRDye® 800CW for PA imaging also yields subpar TBRs due to it affording low PA signals. To overcome such limitations, we developed NIRDye 812, a structurally-modified topological equivalent of IRDye® 800CW, to confer it the capability to yield both higher TBRs and superior PA signal than that of the equivalent CTB-conjugate and fluorophore IRDye® 800CW itself, respectively. To do so, we substituted the oxygen atom at its meso-position with a sulfur atom. CTB-NIRDye 812 demonstrated a red-shifted absorption wavelength at 796 nm and a peak NIR-I fluorescence emission wavelength at 820 nm, which better dovetails with the fixed windows of preinstalled fixed emission filters within commercial pre-/clinical NIR-I fluorescence imaging instruments. Overall, CTB-NIRDye 812 provided a ~ 2-fold increase in TBRs compared to those of CTB-IRDye® 800CW in vivo. Also, NIRDye 812 displayed an ~60% higher PA signal than that of IRDye® 800CW. Collectively, we achieved our goal of improving upon the spectral/photophysical and PA properties of IRDye® 800CW via introducing a subtle modification to its electronic core such that its CTB immunoconjugate could potentially allow for fast track or breakthrough designation by the FDA due to its near-identical structure displaying considerably improved efficacy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Unsupervised learning for identifying events in active target experiments

This article presents novel applications of unsupervised machine learning methods to the problem of event separation in an active target detector, the Active-Target Time Projection Chamber (AT-TPC). The overarching goal is to group similar events in the early stages of the data analysis, thereby improving efficiency by limiting the computationally expensive processing of unnecessary events. The application of unsupervised clustering algorithms to the analysis of two-dimensional projections of particle tracks from a resonant proton scattering experiment on 46 Ar is introduced. We explore the performance of autoencoder neural networks and a pre-trained VGG16 Simonyan and Zisserman (2015) convolutional neural network. We study clustering performance on both data from a simulated 46 Ar experiment, and real events from the AT-TPC detector. We find that a -means algorithm applied to simulated data in the VGG16 latent space forms almost perfect clusters. Additionally, the VGG16+-means approach finds high purity clusters of proton events for real experimental data. Here, we also explore the application of clustering the latent space of autoencoder neural networks for event separation. While these networks show strong performance, they suffer from high variability in their results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

A new cw-NMR Q-meter for dynamically polarized targets for particle physics

Polarized solid targets produced via Dynamic Nuclear Polarization rely on Continuous-Wave Nuclear Magnetism Resonance measurements to accurately determine the degree of polarization of bulk samples polarized to nearly 100%. Since the late 1970's phase sensitive detection methods have been utilized to observe the magnetization of a sample as a small change in inductance under RF excitation near the Larmor frequency of the nuclear species of interest, using a device known as a Q-meter. Liverpool Q-meters, produced in the UK in the 80's and 90's, have been the workhorse devices for these targets for decades, however their age and scarcity has meant new systems are needed. In conclusion, we describe a Q-meter system designed and built at Jefferson Lab in the Liverpool style to have comparable electronic performance with several improvements to update and adapt the devices for modern use.

Dynamic nuclear polarization↗
DOE OSTI2022

Deep-learning-based workflow for boundary and small target segmentation in digital rock images using UNet++ and IK-EBM

We report three-dimensional (3D) X-ray micro-computed tomography (μCT) has been widely used in petroleum engineering because it can provide detailed pore structural information for a reservoir rock, which can be imported into a pore-scale numerical model to simulate the transport and distribution of multiple fluids in the pore space. The partial volume blurring (PVB) problem is a major challenge in segmenting raw μCT images of rock samples, which impacts boundaries and small targets near the resolution limit. We developed a deep-learning (DL)-based workflow for accurate and fast partial volume segmentation. The DL model's performance depends primarily on the training data quality and model architecture. This study employed the entropy-based-masking indicator kriging (IK-EBM) to segment 3D Berea sandstone images as training datasets. The comparison between IK-EBM and manual segmentation using a 3D synthetic sphere pack, which had a known ground truth, showed that IK-EBM had higher accuracy on partial volume segmentation. We then trained and tested the UNet++ model, a state-of-the-art supervised encoder-decoder model, for binary (i.e., void and solid) and four-class segmentation. We compared the UNet++ with the commonly used U-Net and wide U-Net models and showed that the UNet++ had the best performance in terms of pixel-wise and physics-based evaluation metrics. Specifically, boundary-scaled accuracy demonstrated that the UNet++ architecture outperformed the regular U-Net architecture in the segmentation of pixels near boundaries and small targets, which were subjected to the PVB effect. Feature map visualization illustrated that the UNet++ bridged the semantic gaps between the feature maps extracted at different depths of the network, thereby enabling faster convergence and more accurate extraction of fine-scale features. The developed workflow significantly enhances the performance of supervised encoder-decoder models in partial volume segmentation, which has extensive applications in fundamental studies of subsurface energy, water, and environmental systems.

02 PETROLEUM↗
DOE OSTI2025

Synthesis and Evaluation of a Bifunctional Chelator for Thorium-227 Targeted Radiotherapy

Thorium-227 (227Th) is an α-emitting radionuclide currently under investigation for targeted alpha therapy. Available chelators used for this isotope suffer from challenging multistep syntheses. Here, we present the synthesis and preclinical evaluation of a novel bifunctional chelator, p-SCN-Bn-DOTHOPO, which contains an isothiocyanate group that is suitable for conjugation to biological molecules. This bifunctional chelator was prepared with a 26% overall yield in four steps and conjugated to the human epidermal growth factor receptor 2 targeting antibody, trastuzumab. The resulting immunoconjugate was labeled with [227Th]ThIV (pH 5.5, room temperature, 60 min) with ≥95% radiochemical yield and purity. The conjugate was also labeled with zirconium-89 (89Zr), which can be used for positron emission tomography imaging. The radiometal complexes were subsequently investigated for their biological stability. The results described here provide insight into ligand design strategies and optimization of chelators for the development of the next generation of 89Zr and 227Th radiopharmaceuticals.

Thorium↗
DOE OSTI2023

Production of zirconium-88 via proton irradiation of metallic yttrium and preparation of target for neutron transmission measurements at DICER

Abstract A process for the production of tens to hundreds of GBq amounts of zirconium-88 ( 88 Zr) using proton beams on yttrium was developed. For this purpose, yttrium metal targets (≈20 g) were irradiated in a ~16 to 34 MeV proton beam at a beam current of 100–200 µA at the Los Alamos Isotope Production Facility (IPF). The 88 Zr radionuclide was produced and separated from the yttrium targets using hydroxamate resin with an elution yield of 94(5)% (1σ). Liquid DCl solution in D 2 O was selected as a suitable 88 Zr sample matrix due to the high neutron transmission of deuterium compared to hydrogen and an even distribution of 88 Zr in the sample matrix. The separated 88 Zr was dissolved in DCl and 8 µL of the obtained solution was transferred to a tungsten sample can with a 1.2 mm diameter hole using a syringe and automated filling station inside a hot cell. Neutron transmission of the obtained 88 Zr sample was measured at the Device for Indirect Capture Experiments on Radionuclides (DICER).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Target Design for XFEL Experiments

High-energy-density (HED) experiments utilizing X-ray free electron lasers (XFELs) must take a different approach to fielding these experiments than the current methodology used for the large HED facilities in the United States. The XFELs and their associated laser drivers have a much faster repetition rate than do the larger facilities. Experiments must be designed to execute hundreds rather than a few shots per experimental run. The new paradigm requires a different approach to data collection and analysis. It also requires an integrated approach to experiment and target design. Here, in this study, we developed new target designs for a future XFEL experiment that meet both experiment and cost goals.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Printed Targets with Micron-Scale Feature Patterns for the Study of Ablator Defects on OMEGA

As per present models, laser imprint and implosion symmetry are insufficient to account for observed performance degradation of direct-drive cryogenic fusion implosions. More and better data are needed on ablator defects as a source of hydrodynamic instability and mix. To investigate this, a series of OMEGA experimental campaigns is underway to study isolated target defects. Key requirements are systematic variation of the laser intensity and pulse shape at shot, with highly controlled defect type, geometry, and location. Here, given the need for sub-micron resolution and precise registration of multiple features, two-photon polymerization (TPP) printing was identified as an ideal method to fabricate these targets. TPP printing has enabled controlled formation of designed domes, divots, and vacuoles for studying the combined effect of size and proximity of these features on the hydro performance.

Two-photon polymerization printing↗
DOE OSTI2026

Ablating Pellets for Areal Density Symmetry Control in Indirectly Driven Inertial Confinement Fusion Target Designs

Asymmetry of the compressed fusion fuel configuration, as characterized by a variation in areal density, in inertial confinement fusion (ICF) implosions is a known performance limitation. While ignition has been achieved on the National Ignition Facility (NIF), implosion symmetry was not perfect, and subsequent experiments that have extended fusion performance still struggle with symmetry control and would, in principle, perform much better if the areal density uniformity of the fuel was improved by eliminating thin regions in the DT (Deuterium-Tritium) fuel that develop by the time of peak compression. In indirect drive (IDD), altering the time-dependent laser cone fraction and cross-beam energy transfer are the usual tactics for controlling implosion asymmetry in IDD target designs, but it may be that those tools have been pushed to their limits. In this Letter, we present a new tactic for controlling the implosion using satellite ablating pellets to manipulate the time-dependent x-ray field around an ICF capsule. In theory and in simulations the action of these pellets is quite effective at reducing the swing of x-ray drive from waist hot to pole hot, thus achieving a more one-dimensional fuel configuration at peak compression. Simulations show that a factor of ∼2 in yield performance can be obtained via this technique, when applied to past record implosions on the NIF. As a result, some speculative alternate uses of the proposed target concept are also mentioned in the conclusion of this Letter.

Implosion symmetry↗
DOE OSTI2020

A fixed-target platform for serial femtosecond crystallography in a hydrated environment

For serial femtosecond crystallography at X-ray free-electron lasers, which entails collection of single-pulse diffraction patterns from a constantly refreshed supply of microcrystalline sample, delivery of the sample into the X-ray beam path while maintaining low background remains a technical challenge for some experiments, especially where this methodology is applied to relatively low-ordered samples or those difficult to purify and crystallize in large quantities. This work demonstrates a scheme to encapsulate biological samples using polymer thin films and graphene to maintain sample hydration in vacuum conditions. The encapsulated sample is delivered into the X-ray beam on fixed targets for rapid scanning using the Roadrunner fixed-target system towards a long-term goal of low-background measurements on weakly diffracting samples. As a proof of principle, we used microcrystals of the 24 kDa rapid encystment protein (REP24) to provide a benchmark for polymer/graphene sandwich performance. The REP24 microcrystal unit cell obtained from our sandwiched in-vacuum sample was consistent with previously established unit-cell parameters and with those measured by us without encapsulation in humidified helium, indicating that the platform is robust against evaporative losses. While significant scattering from water was observed because of the sample-deposition method, the polymer/graphene sandwich itself was shown to contribute minimally to background scattering.

36 MATERIALS SCIENCE↗