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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Metabolic Interactions between Brachypodium and Pseudomonas fluorescens under Controlled Iron-Limited Conditions

Plant iron (Fe) nutritional status has a significant impact on rhizosphere microbial communities. While this effect has been attributed to alterations in the composition of root exudates, the underlying mechanisms are not known. Here, we investigated the effect of Fe deficiency on the interactions between the grass Brachypodium distachyon and the common soil bacteria Pseudomonas fluorescens SBW25. Increased phytosiderophore production was the most significant response of Brachypodium root exudation to Fe deficiency. We observed upregulated expression of phytosiderophore biosynthesis genes but lower accumulated exudate concentrations in the presence of Pseudomonas, indicating that the bacteria degrade these phytosiderophores. Pseudomonas did not produce endogenous siderophores under the low Fe conditions. Rather, the bacterial transcriptome revealed upregulation of four genes in response to Fe deficiency that contain motifs associated with cellular uptake of small molecules. Collectively, these results suggest that rhizosphere Pseudomonas fluorescens may take up phytosiderophores produced by grasses in response to Fe deficiency, and we propose target genes that may be involved. Our findings provide insight into the molecular basis for the exchange of C, N, and Fe between plants and bacteria under Fe deficient conditions. These interactions may contribute to differences in the rhizosphere microbial community structure across soil pH regimes.

Boiteau, Rene M.↗
DOE OSTI2022

Capabilities of an Acoustic Camera to Inform Fish Collision Risk with Current Energy Converter Turbines

A diversified energy portfolio may include marine energy in the form of current energy converters (CECs) such as tidal or in-river turbines. New technology development in the research stage typically requires monitoring for environmental effects. A significant environmental effect of concern for CECs is the risk of moving parts (e.g., turbine blades) colliding with animals such as fishes. CECs are installed in energetic locations in which it is difficult to operate sensors to fulfill monitoring requirements for informing collision risk. Collecting data (i.e., about blade strikes or near-misses) that inform interactions of fishes with CECs is usually attempted using active acoustic sensors or video cameras (VCs). Limitations of low-light conditions or water turbidity that preclude effective use of VCs are overcome by using high-resolution multibeam echosounders (or acoustic cameras (ACs)). We used an AC at two sites to test its ability to detect artificial and real fish targets and determine if strike, near-miss, and near-field behavior could be observed. Interactions with fish and artificial targets with turbines have been documented but strike confirmation with an AC is novel. The first site was in a tidal estuary with a 25 kW turbine and water clarity sufficient to allow VC data to be collected concurrently with AC data showing turbine blade strike on tethered artificial fish targets. The second site was a turbid, debris-laden river with a 5 kW turbine where only AC data were collected due to high water turbidity. Data collection at the second site coincided with downstream Pacific salmon (Oncorhynchus spp.) smolt migration. Physical fish capture downstream of the turbine was performed with an incline plane trap (IPT) to provide context for the AC observations, by comparing fish catches. Discrimination between debris and fishes in the AC data was not possible, because active movement of fishes was not discernable. Nineteen fishes were released upstream of the turbine to provide known times of possible fish/turbine interactions, but detection was difficult to confirm in the AC data. ACs have been used extensively in past studies to count large migratory fish such as Pacific salmon, but their application for small fish targets has been limited. The results from these two field campaigns demonstrate the ability of ACs to detect targets in turbid water and observe blade strikes, as well as their limitations such as the difficulty of distinguishing small fishes from debris in a high-energy turbid river. Recommendations are presented for future applications associated with CEC device testing.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Closed-loop control of active nematic flows

Stabilizing and shaping autonomous flows of active fluids is a fundamental challenge and a prerequisite for applications. We embed a light-responsive microtubule-based nematic in a proportional-integral control loop that adjusts the applied light intensity in response to real-time measurements of the spatially averaged flow speed. The self-regulating hardware/software/wetware system maintains a target flow speed against external or internal perturbations, including protein aging and aggregation, sample-to-sample variability, and temperature variation. Varying the controller’s gains reveals antagonistic roles between feedback and intrinsic processes, leading to nontrivial dynamics observed in fluctuation spectra. In particular, oscillations emerge from the interplay between the controller, motor binding kinetics, and active hydrodynamic relaxation. Accounting for the underlying binding timescale, our coarse-grained model and nematohydrodynamics simulations corroborate these observations. This work provides insight into the coupled dynamics of controlled active matter, laying the foundation for spatiotemporal patterning of active stress to generate and stabilize new dynamical configurations.

Nishiyama, Katsu [Brandeis Univ., Waltham, MA (Uni↗
DOE OSTI2026

An Activity-Based Sensing Approach to Monitor Nanomaterial-Promoted Changes in Labile Metal Pools in Living Systems

Metal-based nanoparticles are a promising class of materials for diagnosis and treatment of cancer and other diseases. However, mechanisms of action of these nanomedicines remain insufficiently understood due in large part to our limited understanding of the dynamic equilibria between solid metal nanoparticles and labile metal ions generated from these nanoparticles within complex biological milieus. Here, we apply activitybased sensing to directly identify and investigate the fate of labile copper pools with metal and oxidation state-specificity generated by anticancer copper nanomedicines. We found that treatment of cells with copper-releasing nanoparticles alter labile Cu(I)/Cu(II) ratios through an increase in labile Cu(II), while overall labile copper levels decrease. Labile copper release triggers compensatory responses in two major antioxidant pathways, glutathione (GSH) and nuclear factor erythroid 2-related factor 2 (NRF2), as well as in metal homeostasis to limit copper availability via regulation of copper export (ATP7B) and copper import (CTR1) proteins. These findings establish the value of activity-based sensing as a generalizable approach for labile metal imaging to help decipher molecular mechanisms of bioactive metal nanoparticles and guide the development of more effective nanomedicine diagnostics and therapies to target metal-dependent disease vulnerabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Wireless Bioelectronic Modulation of Membrane Potential in Glioblastoma Using Carbon Nanotube Porins

Disruption of membrane potential (V mem ) can activate pathways associated with cancer proliferation. Manipulating ion channels may therefore present an effective strategy for treating cancers that fail to respond to conventional therapies. One approach to target these channels is to manipulate the membrane charge, which involves the use of wireless bipolar electrodes such as carbon nanotube porins (CNTPs) inserted into cell membranes to modulate membrane charge and ionic flux. By utilizing membrane dyes, we observed alterations in V mem induced by CNTPs and externally applied voltages. Analyses of cellular behaviors and processes indicated that V mem is more receptive to stimuli in invasive cancers, while it leads to increased metabolism in less invasive cancers, with notable changes in the cell cycle occurring at approximately 48 h post-treatment in Glioblastoma (GB) cell lines. This work shows that CNTPs, in combination and with externally applied voltages, can modulate V mem and alter cancer cell processes, supporting their potential as a therapeutic.

bioelectricity↗
DOE OSTI2023

Optimizing the Composite Cathode Microstructure in All‐Solid‐State Batteries by Structure‐Resolved Simulations

Abstract All‐solid‐state batteries are considered as an enabler for applications requiring high energy and power density. However, they still fall short of their theoretical potential due to various limitations. One issue is poor charge transport kinetics resulting from both material inherit limitations and non‐optimized design. Therefore, a better understanding of the relevant properties of the cathode microstructure is necessary to improve cell performance. In this article, we identify optimization potentials of the composite cathode by structure‐resolved electrochemical 3D‐simulations. In our simulation study, we investigate the influence of cathode active material fraction, density, particle size, and active material properties on cell performance. Special focus is set on the impact of grain boundaries on the cathode design. Based on our simulation results, we can predict target values for cell manufacturing and reveal promising optimization strategies for an improved cathode design.

25 ENERGY STORAGE↗
DOE OSTI2023

Structure-based mechanism and inhibition of cholesteryl ester transfer protein

Purpose of Review: Cholesteryl ester transfer proteins (CETP) regulate plasma cholesterol levels by transferring cholesteryl esters (CEs) among lipoproteins. Lipoprotein cholesterol levels correlate with the risk factors for atherosclerotic cardiovascular disease (ASCVD). This article reviews recent research on CETP structure, lipid transfer mechanism, and its inhibition. Recent Findings: Genetic deficiency in CETP is associated with a low plasma level of low-density lipoprotein cholesterol (LDL-C) and a profoundly elevated plasma level of high-density lipoprotein cholesterol (HDL-C), which correlates with a lower risk of atherosclerotic cardiovascular disease (ASCVD). However, a very high concentration of HDL-C also correlates with increased ASCVD mortality. Considering that the elevated CETP activity is a major determinant of the atherogenic dyslipidemia, i.e., pro-atherogenic reductions in HDL and LDL particle size, inhibition of CETP emerged as a promising pharmacological target during the past two decades. CETP inhibitors, including torcetrapib, dalcetrapib, evacetrapib, anacetrapib and obicetrapib, were designed and evaluated in phase III clinical trials for the treatment of ASCVD or dyslipidemia. Although these inhibitors increase in plasma HDL-C levels and/or reduce LDL-C levels, the poor efficacy against ASCVD ended interest in CETP as an anti-ASCVD target. Nevertheless, interest in CETP and the molecular mechanism by which it inhibits CE transfer among lipoproteins persisted. Insights into the structural-based CETP-lipoprotein interactions can unravel CETP inhibition machinery, which can hopefully guide the design of more effective CETP inhibitors that combat ASCVD. Summary: Individual-molecule 3D structures of CETP bound to lipoproteins provide a model for understanding the mechanism by which CETP mediates lipid transfer and which in turn, guide the rational design of new anti-ASCVD therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

High Flux Isotope Reactor (HFIR)

Oak Ridge National Laboratory’s High Flux Isotope Reactor (HFIR) is the highest-flux reactor-based neutron source in the United States. HFIR’s intense neutron flux and state-of-the-art facilities result in world-class capabilities, including neutron scattering, radioisotope production, materials irradiation, and neutron activation analysis. HFIR’s multimission capabilities are attributed to its versatile high-power-density core design consisting of a series of concentric regions, including a flux trap target region, an inner fuel element, an outer fuel element, a control element region, and a beryllium reflector. The pressurized, light-water-cooled research reactor operates at 85 MW and is fueled by 9.4 kg 235U.

Chandler, David↗
DOE OSTI2021

De-ubiquitination of p300 by USP12 Critically Enhances METTL3 Expression and Ang II-induced cardiac hypertrophy

Highlights: • The expression of USP12 is increased in Ang II-induced cardiac hypertrophy in vitro and in vivo. • USP12 aggravates Ang II-induced cardiomyocyte hypertrophy via upregulating METTL3. • USP12 promoted METTL3 expression via modulating p300. • USP12 suppresses the ubiquitination of p300 to block its degradation. Stresses, such as neurohumoral activation, induced pathological cardiac hypertrophy is the main risk factor for heart failure. The ubiquitin-proteasome system (UPS) plays a key role in maintaining protein homeostasis and cardiac function. However, research on the role and mechanism of deubiquitinating enzymes (DUBs) in cardiac hypertrophy is limited. Here, we observe that the deubiquitinating enzyme ubiquitin-specific protease 12(USP12) is upregulated in Ang II-induced hypertrophic hearts and primary neonatal rat cardiomyocytes (NRCMs). Inhibition of USP12 ameliorate Ang II-induced myocardial hypertrophy, while overexpression of USP12 have the opposite effect. USP12 deficiency also significantly attenuate the phenotype of Ang II-induced cardiac hypertrophy in vivo. Moreover, we demonstrate that USP12 aggravate Ang II-induced cardiac hypertrophy by enhancing METTL3, a methyltransferase which catalyze N{sup 6}-methyladenosine (m{sup 6}A) modification on messenger RNA and acts as a harmful factor in pathological cardiac hypertrophy. Upregulation of METTL3 reverse the reduction of myocardial hypertrophy induced by USP12 silencing in NRCMs. In contrast, knockdown of METTL3 attenuate the aggravation of myocardial hypertrophy in USP12-overexpressing NRCMs. Furthermore, we discover that USP12 promote the expression of METTL3 via upregulating p300. Mechanistically, USP12 binds and stabilizes p300, thereby activating the transcription of its downstream gene METTL3. Finally, our data show that USP12 is partially dependent on the stabilization of p300 to activate METTL3 expression and promote myocardial hypertrophy. Taken together, our results demonstrate that USP12 acts as a pro-hypertrophic deubiquitinating enzyme via enhancing p300/METTL3 axis, indicating that targeting USP12 could be a potential treatment strategy for pathological cardiac hypertrophy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Controlling Pt Crystal Defects on the Surface of Ni–Pt Core–Shell Nanoparticles for Active and Stable Electrocatalysts for Oxygen Reduction

A strategy of direct growth of Pt on Ni was used to create and control Pt crystal defects on the surface of Ni–Pt core–shell nanoparticles. The control over the types of defects was easily achieved by changing the surfactant system. Here, in this work, two types of crystal defects have been introduced into Ni–Pt core–shell nanoparticles: polycrystalline shells with multiple grain boundaries and step-edge shells with undercoordinated atoms at corners and steps. We show that the step-edge shell has a higher specific activity for the oxygen reduction reaction (ORR), while the thinner polycrystalline shell results in a higher activity per mass and stability. Our results suggest that Ni–Pt core–shell nanoparticles with a thin Pt shell that have high density of crystal defect should be targeted for high performance ORR catalysts.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Demonstration of Super-X divertor exhaust control for transient heat load management in compact fusion reactors

Nuclear fusion could offer clean, abundant energy. However, managing the power exhausted from the core fusion plasma towards the reactor wall remains a major challenge. This is compounded in emerging compact reactor designs promising more cost-effective pathways towards commercial fusion energy. Alternative Divertor Configurations (ADCs) are a potential solution. In this work, we demonstrate exhaust control in ADCs, employing a novel method to diagnose the neutral gas buffer, which shields the target. Our work on the Mega Ampere Spherical Tokamak Upgrade shows that ADCs tackle key risks and uncertainties for fusion energy. Their highly reduced sensitivity to perturbations enables active exhaust control in otherwise unfeasible situations and facilitates an increased passive absorption of transients, which would otherwise damage the divertor. We observe a strong decoupling of each divertor from other reactor regions, enabling near-independent control of the divertors and core plasma. Our work showcases the real-world benefits of ADCs for effective heat load management in fusion power reactors.

Imaging techniques↗
DOE OSTI2022

Decoding the protein–ligand interactions using parallel graph neural networks

Abstract Protein–ligand interactions (PLIs) are essential for biochemical functionality and their identification is crucial for estimating biophysical properties for rational therapeutic design. Currently, experimental characterization of these properties is the most accurate method, however, this is very time-consuming and labor-intensive. A number of computational methods have been developed in this context but most of the existing PLI prediction heavily depends on 2D protein sequence data. Here, we present a novel parallel graph neural network (GNN) to integrate knowledge representation and reasoning for PLI prediction to perform deep learning guided by expert knowledge and informed by 3D structural data. We develop two distinct GNN architectures: $$\hbox {GNN}_{\mathrm{F}}$$ GNN F is the base implementation that employs distinct featurization to enhance domain-awareness, while $$\hbox {GNN}_{\mathrm{P}}$$ GNN P is a novel implementation that can predict with no prior knowledge of the intermolecular interactions. The comprehensive evaluation demonstrated that GNN can successfully capture the binary interactions between ligand and protein’s 3D structure with 0.979 test accuracy for $$\hbox {GNN}_{\mathrm{F}}$$ GNN F and 0.958 for $$\hbox {GNN}_{\mathrm{P}}$$ GNN P for predicting activity of a protein–ligand complex. These models are further adapted for regression tasks to predict experimental binding affinities and $$\hbox {pIC}_{\mathrm{50}}$$ pIC 50 crucial for compound’s potency and efficacy. We achieve a Pearson correlation coefficient of 0.66 and 0.65 on experimental affinity and 0.50 and 0.51 on $$\hbox {pIC}_{\mathrm{50}}$$ pIC 50 with $$\hbox {GNN}_{\mathrm{F}}$$ GNN F and $$\hbox {GNN}_{\mathrm{P}}$$ GNN P , respectively, outperforming similar 2D sequence based models. Our method can serve as an interpretable and explainable artificial intelligence (AI) tool for predicted activity, potency, and biophysical properties of lead candidates. To this end, we show the utility of $$\hbox {GNN}_{\mathrm{P}}$$ GNN P on SARS-Cov-2 protein targets by screening a large compound library and comparing the prediction with the experimentally measured data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

FAIR AI models in high energy physics

Abstract The findable, accessible, interoperable, and reusable (FAIR) data principles provide a framework for examining, evaluating, and improving how data is shared to facilitate scientific discovery. Generalizing these principles to research software and other digital products is an active area of research. Machine learning models—algorithms that have been trained on data without being explicitly programmed—and more generally, artificial intelligence (AI) models, are an important target for this because of the ever-increasing pace with which AI is transforming scientific domains, such as experimental high energy physics (HEP). In this paper, we propose a practical definition of FAIR principles for AI models in HEP and describe a template for the application of these principles. We demonstrate the template’s use with an example AI model applied to HEP, in which a graph neural network is used to identify Higgs bosons decaying to two bottom quarks. We report on the robustness of this FAIR AI model, its portability across hardware architectures and software frameworks, and its interpretability.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Toward Accelerating Discovery via Physics-Driven and Interactive Multifidelity Bayesian Optimization

Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and often nondifferentiable parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, processing spaces, and molecular embedding spaces. Often these systems are expensive or time consuming to evaluate a single instance, and hence classical approaches based on exhaustive grid or random search are too data intensive. This resulted in strong interest toward active learning methods such as Bayesian optimization (BO) where the adaptive exploration occurs based on human learning (discovery) objective. However, classical BO is based on a predefined optimization target, and policies balancing exploration and exploitation are purely data driven. In practical settings, the domain expert can pose prior knowledge of the system in the form of partially known physics laws and exploration policies often vary during the experiment. Here, we propose an interactive workflow building on multifidelity BO (MFBO), starting with classical (data-driven) MFBO, then expand to a proposed structured (physics-driven) structured MFBO (sMFBO), and finally extend it to allow human-in-the-loop interactive interactive MFBO (iMFBO) workflows for adaptive and domain expert aligned exploration. These approaches are demonstrated over highly nonsmooth multifidelity simulation data generated from an Ising model, considering spin–spin interaction as parameter space, lattice sizes as fidelity spaces, and the objective as maximizing heat capacity. Detailed analysis and comparison show the impact of physics knowledge injection and real-time human decisions for improved exploration with increased alignment to ground truth. Here, the associated notebooks allow to reproduce the reported analyses and apply them to other systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Exploiting user activeness for data retention in HPC systems

HPC systems typically rely on the fixed-lifetime (FLT) data retention strategy, which only considers temporal locality of data accesses to parallel file systems. However, our extensive analysis based on the leadership-class HPC system traces suggests that the FLT approach often fails to capture the dynamics in users' behavior and leads to undesired data purge. In this study, we propose an activeness-based data retention (ActiveDR) solution, which advocates considering the data retention approach from a holistic activeness-based perspective. By evaluating the frequency and impact of users' activities, ActiveDR prioritizes the file purge process for inactive users and rewards active users with extended file lifetime on parallel storage. Our extensive evaluations based on the traces of the prior Titan supercomputer show that, when reaching the same purge target, ActiveDR achieves up to 37% file miss reduction as compared to the current FLT retention methodology.

Zhang, Wei↗
DOE OSTI2021

Antitumor T-cell Immunity Contributes to Pancreatic Cancer Immune Resistance

Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer death in the United States. Pancreatic tumors are minimally infiltrated by T cells and are largely refractory to immunotherapy. Accordingly, the role of T-cell immunity in pancreatic cancer has been somewhat overlooked. Here, we hypothesized that immune resistance in pancreatic cancer was induced in response to antitumor T-cell immune responses and that understanding how pancreatic tumors respond to immune attack may facilitate the development of more effective therapeutic strategies. We now provide evidence that T-cell–dependent host immune responses induce a PDAC-derived myeloid mimicry phenomenon and stimulate immune resistance. Three KPC mouse models of pancreatic cancer were used: the mT3-2D (Kras +/LSL-G12D ; Trp53 +/LSL-R172H ; Pdx1-Cre) subcutaneous and orthotopic models, as well as the KP1 (p48-CRE/LSL-Kras/Trp53 flox/flox ) subcutaneous model. KPC cancer cells were grown in immunocompetent and immunodeficient C57BL/6 mice and analyzed to determine the impact of adaptive immunity on malignant epithelial cells, as well as on whole tumors. We found that induced T-cell antitumor immunity, via signal transducer and activator of transcription 1 (STAT1), stimulated malignant epithelial pancreatic cells to induce the expression of genes typically expressed by myeloid cells and altered intratumoral immunosuppressive myeloid cell profiles. Targeting the Janus Kinase (JAK)/STAT signaling pathway using the FDA-approved drug ruxolitinib overcame these tumor-protective responses and improved anti–PD-1 therapeutic efficacy. Overall, these findings provide future directions for treatments that specifically disable this mechanism of resistance in PDAC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Recycling Isotopically Enriched Mo from the RadioGenix Waste Stream

NorthStar’s RadioGenix generator utilizes an aqueous biphasic extraction chromatography column to separate Tc from low-specific-activity 99 Mo. During this separation process, a fraction of the source Mo material can be found in the waste. This is not of concern when natural Mo targets are used. However, the introduction of isotopically enriched 98 Mo for neutron capture or 100 Mo for accelerator-based production requires recovery of this valuable enriched Mo material. The generator waste is absorbed and solidified in a superabsorbent hydrogel polymer. In this contribution, we report results from our small-scale experimental study on development of a separation process for recovery of molybdenum from the polymeric gel waste using common chemicals and simple chemical techniques. Our investigation confirms that the acidic deswelling of the alkaline hydrogel with concentrated hydrochloric acid converts the occluded molybdate to a neutral molybdenyl dichloride species that is freely released from the gel. Mo can then be concentrated on a commercial tri-n-butyl phosphate resin, eluted with ammonium hydroxide, and crystallized as ammonium heptamolybdate for conversion back to Mo metal. Typical Mo recoveries are 90-95%.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Purification and Concentration of 99 Mo from a UREX raffinate

The medical isotope 99m Tc ( t ½ = 6.0 h) accounts for over 80% of isotopes used in diagnostic nuclear medicine today and is normally derived from its transient equilibrium parent 99 Mo ( t ½ = 66 h). To reduce U.S. dependence on 99 Mo derived from HEU by foreign suppliers, the NNSA/M3 program—under the American Medical Isotope Production Act—has been tasked with facilitating the work of domestic 99 Mo suppliers that do not utilize HEU. Superconducting electron linear accelerators with high-Z converter targets can generate bremsstrahlung photons and neutron fluxes that can induce photonuclear reactions and LEU fission. After sufficient production intervals, targets can be rotated out and processed while another batch is irradiated. The process flow chemistry is shown in Figure 1. The irradiated U 3 O 8 targets are retrieved and dissolved in HNO 3 ; the volatile fission products are expelled and captured during this step. The HNO 3 liquor bearing the uranyl, fission and activation products is injected into the UREX suite of liquid-liquid extraction banks. The uranyl is partitioned in typical fashion using tri-$\textit{n}$-butyl phosphate (TBP) in a hydrocarbon diluent. The raffinate—comprising mainly 99 Mo and fission products—is then injected into the MoLLE (Molybdenum Liquid-Liquid Extraction) flowsheet, where the Mo is selectively extracted by an organophosphorous acid extractant such as di-(2-ethylhexyl phosphoric acid) (HDEHP). Trace amounts of Nb, Zr, Np, I, and Te are co-extracted. The Mo is stripped using acetohydroxamic acid (AHA) and fed onto an anion exchange column. Following a series of hydroxide, HCl, and oxalic acid wash steps, the Mo can be recovered in NaOH/NaCl. A manuscript describing this process chemistry in more detail was recently published.

07 ISOTOPE AND RADIATION SOURCES↗