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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Study of Ferrocene Diffusion in Toluene/Tween 20/1-Butanol/Water Microemulsions for Redox Flow Battery Applications

Redox flow batteries (RFBs) possess multiple advantages as a flexible energy storage solution. However, RFB researchers are still facing many challenges in finding an appropriate electrolyte. Microemulsions have recently been proposed as a promising alternative RFB electrolyte because of their ability to accommodate organic redox species with fast electron transfer rates that are not soluble in aqueous phase, while still offering the high conductivity of an aqueous salt electrolyte. In this work, we focused on understanding the transport of ferrocene (Fc) in a toluene/Tween 20/1-butanol/water model microemulsion and studied the compositional influence on Fc diffusion. The results show that Fc redistributes among the oil, surfactant, and water microenvironments, and the corresponding diffusion and partition coefficients are quantified. Thus, a tortuous path diffusion model is proposed to describe the mass transport of Fc to an electrode surface. Diffusion coefficients are also obtained by pulsed-field gradient nuclear magnetic resonance (PFG NMR), while the values for Fc diffusion are substantially higher than those from electrochemical measurements, suggesting that they measure samples in different ways. The current contributions from each microenvironment indicate that the Fc permeability is much higher in the oil, even though the electron transfer reaction is likely occurring in the surfactant.

25 ENERGY STORAGE↗
DOE OSTI2022

Curated Collection of More than 20,000 Experimentally Reported One-Dimensional Metal–Organic Frameworks

Herein, a collection of more than 20,000 experimentally derived crystal structures for metal–organic frameworks (MOFs) that do not have two- or three-dimensional covalently bonded networks has been developed from the materials available at the Cambridge Crystallographic Data Centre. Of these 20,000 1D MOFs, more than 12,000 structures have been verified to be solvent-free and in exact agreement with the stoichiometry of the synthesized materials. More than 10% of the complete data set comprise materials including two or more distinct metals. The band gaps of more than 12,000 1D MOFs have been computed at the density functional theory-generalized gradient approximation level, finding more than 2000 materials that have a zero band gap. Molecular simulations of CH4 adsorption in a small number of 1D MOFs indicated that adsorbate-induced deformation plays a significant role in determining adsorption isotherms in these materials. As a result, methods that have been used previously for high-throughput predictions of molecular adsorption in 3D MOFs are not suitable for 1D MOFs.

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

Highly Rectifying Fluidic Diodes Based on Asymmetric Layer-by-Layer Nanofilms on Nanochannel Membranes

Nanochannel-based fluidic diodes display ion selectivity and ion-current rectification (ICR), which may prove important in energy harvesting and biosensors. This paper reports asymmetric functionalization of the outer surface of a flexible nanochannel polymer membrane to create fluidic diodes that give ICR. Layer-by-layer (LbL) adsorption with cross-linking of only the underlying part of the polyelectrolyte nanofilm leads to a porosity step across the film. The combination of a high effective surface-charge density and the porosity step in the film leads to a remarkable maximum ICR factor of ~200 with a pH gradient across the film. Incorporation of pH-sensitive polyelectrolyte components enables the ICR factor to increase an order of magnitude on going from pH 8 to pH 3. Furthermore, the coated membrane shows excellent anion-selectivity. Thus, LbL adsorption with partial cross-linking provides a simple method for creating coated nanochannel membranes that serve as pH-responsive ionic diodes for potential chemical/biosensors.

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

Pharmacoepidemiology, Machine Learning and COVID-19: An intent-to-treat analysis of hydroxychloroquine, with or without azithromycin, and COVID-19 outcomes amongst hospitalized US Veterans

Hydroxychloroquine (HCQ) was proposed as an early therapy for coronavirus disease 2019 (COVID-19) after in vitro studies indicated possible benefit. Previous in vivo observational studies have presented conflicting results, though recent randomized clinical trials have reported no benefit from HCQ amongst hospitalized COVID-19 patients. In this work, we examined the effects of HCQ alone, and in combination with azithromycin, in a hospitalized COVID-19 positive, United States (US) Veteran population using a propensity score adjusted survival analysis with imputation of missing data. From March 1, 2020 through April 30, 2020, 64,055 US Veterans were tested for COVID-19 based on Veteran Affairs Healthcare Administration electronic health record data. Of the 7,193 positive cases, 2,809 were hospitalized, and 657 individuals were prescribed HCQ within the first 48-hours of hospitalization for the treatment of COVID-19. There was no apparent benefit associated with HCQ receipt, alone or in combination with azithromycin, and an increased risk of intubation when used in combination with azithromycin [Hazard Ratio (95% Confidence Interval): 1.55 (1.07, 2.24)]. In conclusion, we assessed the effectiveness of HCQ with or without azithromycin in treating patients hospitalized with COVID-19 using a national sample of the US Veteran population. Using rigorous study design and analytic methods to reduce confounding and bias, we found no evidence of a survival benefit from the administration of HCQ.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Predictive analytics of selections of russet potatoes

We explore the application of machine learning algorithms specifically to enhance the selection process of Russet potato (Solanum tuberosum L.) clones in breeding trials by predicting their suitability for advancement. This study addresses the challenge of efficiently identifying high-yield, disease-resistant, and climate-resilient potato varieties that meet processing industry standards. Leveraging manually collected data from trials in the state of Oregon, we investigate the potential of a wide variety of state-of-the-art binary classification models. The dataset includes 1086 clones, with data on 38 attributes recorded for each clone, focusing on yield, size, appearance, and frying characteristics, with several control varieties planted consistently across four Oregon regions from 2013 to 2021. We conduct a comprehensive analysis of the dataset that includes preprocessing, feature engineering, and imputation to address missing values. We focus on several key metrics such as accuracy, F1-score, and Matthews correlation coefficient (MCC) for model evaluation. The top-performing models, namely a feedforward neural network classifier (Neural Net), a histogram-based gradient boosting classifier (HGBC), and a support vector machine classifier (SVM), demonstrate consistent and significant results. To further validate our findings, we conducted a simulation study using the aims, data-generating mechanisms, estimands, methods, and performance measures (ADEMP) framework, simulating different data-generating scenarios to assess model robustness and performance through true positive, true negative, false positive, and false negative distributions, area under the receiver operating characteristic curve (AUC-ROC) and MCC. The simulation results highlight that non-linear models like SVM and HGBC consistently show higher AUC-ROC and MCC than logistic regression, thus outperforming the traditional linear model across various distributions, and emphasizing the importance of model selection and tuning in agricultural trials. Variable selection further enhances model performance and identifies influential features in predicting trial outcomes. The findings emphasize the potential of machine learning in streamlining the selection process for potato varieties, offering benefits such as increased efficiency, substantial cost savings, and judicious resource utilization. Our study contributes insights into precision agriculture and showcases the relevance of advanced technologies for informed decision-making in breeding programs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Numerical Investigation of Susceptor-Catalyst Design for Ethylene Generation in Radio Frequency Based Reactors

Ethylene is the most widely produced petrochemical component in the world. Whether reactors are heated directly or indirectly via steam, manufacturers use economies of scale to overcome inherent thermodynamic inefficiencies when burning fossil fuels. While allowing large-scale operations to use alternative sources of energy and raw materials, new methods of supplying energy to chemical reactor systems can reduce the energy waste produced by conventional processes. One viable method for effectively supplying energy to reactor systems is electromagnetic (EM) induction heating. Using the properties of radio frequency (RF) waves, heterogeneous catalysts can be precisely targeted for heating inside reactors. Site-selective heating can greatly lower the energy requirements of the process by supplying heat to reaction sites while reducing needless heat transfer elsewhere. In this study, a microscale model was used to help create guidelines for susceptors and catalysts to improve ethylene production. The oxidative dehydrogenation of ethane is investigated by utilizing several catalysts and potential catalyst/susceptor combinations, with heat provided by an EM susceptor. Having the susceptors and catalyst function separately results in higher gradients in both heat and mass transfer, which drives transport through the catalyst region, while still providing adequate heating for endothermic reactions. However, using a susceptive core with a catalyst covering produces the maximum ethylene concentration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Constraints on light QCD and CP-violating axions from the death line of rotation-powered pulsars

For axions that couple to nucleons, the presence of dense nuclear matter can displace the axion from its vacuum minimum, sourcing large field gradients around neutron stars (and, more generally, compact objects). These gradients, which we refer to as axion hair, couple to the local background magnetic field, inducing a large voltage drop near the surface of the star; here, we demonstrate that the presence of axion hair decouples local near-field particle acceleration in the open magnetic field line bundle from the rotational frequency of the pulsar itself. This is significant as the non-observation of old slowly-rotating pulsars is attributed to the fact the rotationally-induced electric fields are not strong enough to sustain $e^\pm$ pair production. In this work, we review the evidence for the existence for `pulsar death', i.e. the threshold at which $e^\pm$ pair production (and thus, by association, coherent radio emission) ceases, and demonstrate using both semi-analytics and particle-in-cell simulations that the existence of axion hair can dramatically extend pulsar lifetimes. We show that the non-observation of extremely old, slowly rotating, pulsars allows for a new probe of light QCD and CP-violating axions. We also demonstrate how the observation of emission from both poles of pulsars with nearly orthogonal rotational and magnetic axes, as seen e.g. in PSR J1906+0746, can be used to set competitive limits on CP-violating axion-nucleon interactions.

Witte, Samuel J. [Oxford U., Theor. Phys.; DESY; H↗
DOE OSTI2021

A machine learning approach for efficient multi-dimensional integration

Many physics problems involve integration in multi-dimensional space whose analytic solution is not available. The integrals can be evaluated using numerical integration methods, but it requires a large computational cost in some cases, so an efficient algorithm plays an important role in solving the physics problems. We propose a novel numerical multi-dimensional integration algorithm using machine learning (ML). After training a ML regression model to mimic a target integrand, the regression model is used to evaluate an approximation of the integral. Then, the difference between the approximation and the true answer is calculated to correct the bias in the approximation of the integral induced by ML prediction errors. Because of the bias correction, the final estimate of the integral is unbiased and has a statistically correct error estimation. Three ML models of multi-layer perceptron, gradient boosting decision tree, and Gaussian process regression algorithms are investigated. The performance of the proposed algorithm is demonstrated on six different families of integrands that typically appear in physics problems at various dimensions and integrand difficulties. The results show that, for the same total number of integrand evaluations, the new algorithm provides integral estimates with more than an order of magnitude smaller uncertainties than those of the VEGAS algorithm in most of the test cases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Role of Intra-Domain Heterogeneity on Ion and Polymer Dynamics in Block Polymer Electrolytes: An Approach for Spatially Resolving Dynamics and Ion Transport

The design of safe and high-performance, nanostructured, block polymer (BP) electrolytes for lithium-ion batteries requires a thorough understanding of the key parameters that govern local structure and dynamics. Yet, the interfaces between microphase separated domains can introduce complexities in this local behavior that can be challenging to quantify. Herein, the local polymer, cation (Li + ), and anion dynamics were described in salt-doped polystyrene block poly(oligo-oxyethylene methyl ether methacrylate) (PS-b-POEM) through a quantitative framework that considered the effects of polymer architecture, segmental mixing, chain stretching, and confinement on polymer mobility and ion transport. This framework was validated through nuclear magnetic resonance (NMR) spectroscopy measurements on solid (dry) polymer electrolyte samples. Notably, a mobility transition temperature (T mobility ) was identified through NMR spectroscopy that captured the local dynamics more accurately than the thermal glass transition temperature. Additionally, the approach quantitatively described the mobility gradient across a domain when segmental mixing effects were combined with chain stretching and confinement information, especially at higher segregation strengths – facilitating the assessment of local ion diffusion and conductivity. As a result, spatially averaged local ion diffusion predictions quantitatively matched NMR-measured ion diffusivities in the BP samples, while spatially summed ionic conductivity predictions across a domain qualitatively captured trends in the measured ionic conductivities.

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

Near total reflection x-ray photoelectron spectroscopy: quantifying chemistry at solid/liquid and solid/solid interfaces

Near total reflection regime has been widely used in x-ray science, specifically in grazing incidence small angle x-ray scattering and in hard x-ray photoelectron spectroscopy (XPS). In this work, we introduce some practical aspects of using near total reflection (NTR) in ambient pressure XPS and apply this technique to study chemical concentration gradients in a substrate/photoresist system. Experimental data are accompanied by x-ray optical and photoemission simulations to quantitatively probe the photoresist and the interface with the depth accuracy of ~1 nm. Together, our calculations and experiments confirm that NTR XPS is a suitable method to extract information from buried interfaces with highest depth-resolution, which can help address open research questions regarding our understanding of concentration profiles, electrical gradients, and charge transfer phenomena at such interfaces. Furthermore, the presented methodology is especially attractive for solid/liquid interface studies, since it provides all the strengths of a Bragg-reflection standing-wave spectroscopy without the need of an artificial multilayer mirror serving as a standing wave generator, thus dramatically simplifying the sample synthesis.

solid/solid interface↗
DOE OSTI2021

Performance of the A-01 Constructed Wetland over 20 Years

The A-01 wetland treatment system (WTS) was designed to remove metals from the effluent at the A-01 National Pollution Discharge Elimination System (NPDES) outfall at the Savannah River Site, Aiken, SC. The A-01 effluent flows from a retention basin to a splitter box, where it is distributed to four pairs of cells in series before discharge to a stream. Each treatment cell is a one-acre wetland that contains Schoenoplectus californicus (giant bulrush) and has a nominal 24-hour retention time. The purpose of this research was to investigate metal removal, distribution and retention in the A-01 WTS over a period of 20 years. During 20 years of operation, systematic water and sediment sampling validated the wetlands' performance. After passage through the treatment cells, Cu concentrations were well below permit limits (22 pg L -1 ) during all years of operation, often falling below 10 pg L -1 . Cu removal has been consistent over time, averaging about 80% despite large changes in influent Cu concentrations. Most divalent metals were rapidly removed from the water and held in the sediments shortly after the water entered the treatment wetlands. Average removal of Pb from water by the wetland system was 67 and 74%, respectively, in 2004, and 2020. Comparable values for Zn were 52 and 65%, respectively. Generally, the highest concentrations of Cu, Pb, and Zn were found in the sediment from the first cell in each pair of cells suggesting that most of the Cu, Pb, and Zn in the A-01 effluent was bound to the sediment quickly. Diffusive gradients in thin films (DGT) measurements of Cu and Zn in the sediments were much lower than bulk sediment concentrations. These results suggest that most of the Cu and Zn in the A-01 WTS sediments was not bioavailable, hence not toxic to aquatic organisms, as a likely consequence of adsorption to sediment particles and complexation with organic and inorganic substances.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Active Plasmonics and Active Chiral Plasmonics through Orientation-Dependent Multipolar Interactions

While most active plasmonic efforts focus on responsive metamaterials to modulate optical response, we present a simple alternative based on applied orientation control that can likely be implemented for many passive plasmonic materials. Passive plasmonic motifs are simpler to prepare but cannot be altered postfabrication. Here, we show that such systems can be easily manipulated through substrate orientation control to generate both active plasmonic and active chiral plasmonic responses. Using gold nanocrescents as our model platform, we demonstrate tuning of optical extinction from -21% to +36% at oblique incidence relative to normal incidence. Variation of substrate orientation in relation to incident polarization is also demonstrated to controllably switch chiroptical handedness (e.g., Δg = ± 0.55). These active plasmonic responses arise from the multipolar character of resonant modes. In particular, we correlate magnetoelectric and dipole–quadrupole polarizabilities with different light-matter orientation-dependence in both near- and far-field localized surface plasmon activity. Additionally, the attribution of far-field optical response to higher-order multipoles highlights the sensitivity offered by these orientation-dependent characterization techniques to probe the influence of localized electromagnetic field gradients on a plasmonic response. The sensitivity afforded by orientation-dependent optical characterization is further observed by the manifestation in both plasmon and chiral plasmon responses of unpredicted structural nanocrescent variance (e.g., left- and right-tip asymmetry) not physically resolved through topographical imaging.

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

Carbon capture in polymer-based electrolytes

Nanoparticle organic hybrid materials (NOHMs) have been proposed as excellent electrolytes for combined CO 2 capture and electrochemical conversion due to their conductive nature and chemical tunability. However, CO 2 capture behavior and transport properties of these electrolytes after CO 2 capture have not yet been studied. Here, we use a variety of nuclear magnetic resonance (NMR) techniques to explore the carbon speciation and transport properties of branched polyethylenimine (PEI) and PEI-grafted silica nanoparticles (denoted as NOHM-I-PEI) after CO 2 capture. Quantitative 13 C NMR spectra collected at variable temperatures reveal that absorbed CO 2 exists as carbamates (RHNCOO – or RR'NCOO – ) and carbonate/bicarbonate (CO 3 2– /HCO 3 – ). The transport properties of PEI and NOHM-I-PEI studied using 1 H pulsed-field-gradient NMR, combined with molecular dynamics simulations, demonstrate that coulombic interactions between negatively and positively charged chains dominate in PEI, while the self-diffusion in NOHM-I-PEI is dominated by silica nanoparticles. These results provide strategies for selecting adsorbed forms of carbon for electrochemical reduction.

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

Mechanisms of Complete Dissociation of CO 2 on Iron Clusters

Dissociation of CO 2 on iron clusters was studied by using semilocal density functional theory and basis sets of triple-zeta quality. Fe 2 , Fe 4 , and Fe 16 clusters were selected as the representative host clusters. When searching for isomers of Fe n CO 2 , n=2, 4 and 16 corresponding to carbon dioxide attachment to the host clusters, its reduction to O and CO, and to the complete dissociation, it was found that the total spin magnetic moments of the lowest energy states of the isomers are often quenched with respect to those of initial reagents Fe n +CO 2 . Dissociation pathways of the Fe 2 +CO 2 , Fe 4 +CO 2 , and Fe 16 +CO 2 reactions contain several transition states separated by the local minima states; therefore, a natural question is where do the spin flips occur? Since lifetimes of magnetically excited states were shown to be of the order of 100 fs, the search for the CO 2 dissociation pathways was performed under the assumption that magnetic deexcitation may occur at the intermediate local minima. Two dissociation pathways were obtained for each Fe n +CO 2 reaction using the gradient-based methods. It was found that the Fe 2 +CO 2 reaction is endothermic with respect to both reduction and complete dissociation of CO 2 , whereas the Fe 4 +CO 2 and Fe 16 +CO 2 reactions are exothermic to both reduction and complete dissociation of carbon dioxide. Finally, the CO 2 reduction was found to be more favorable than its complete dissociation in the Fe 4 case.

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

Oxygen Electrocatalysis on Mixed-Metal Oxides/Oxyhydroxides: From Fundamentals to Membrane Electrolyzer Technology

Catalyzing the oxygen evolution reaction (OER) is important for key energy-storage technologies, particularly water electrolysis and photoelectrolysis for hydrogen fuel production. Under neutral-to-alkaline conditions, first-row transition-metal oxides/(oxy)hydroxides are the fastest-known OER catalysts and have been the subject of intense study for the past decade. Critical to their high performance is the intentional or accidental addition of Fe to Ni/Co oxides that convert to layered (oxy)hydroxide structures during the OER. Unraveling the role that Fe plays in the catalysis and the molecular identity of the true “active site” has proved challenging, however, due to the dynamics of the host structure and absorbed Fe sites as well as the diversity of local structures in these disordered active phases. In this Account, we highlight our work to understand the role of Fe in Ni/Co (oxy)hydroxide OER catalysts. We first discuss how we characterize the intrinsic activity of the first-row transition-metal (oxy)hydroxide catalysts as thin films by accounting for the contributions of the catalyst-layer thickness (mass loading) and electrical conductivity as well as the underlying substrate’s chemical interactions with the catalyst and the presence of Fe species in the electrolyte. We show how Fe-doped Ni/Co (oxy)hydroxides restructure during catalysis, absorb/desorb Fe, and in some cases degrade or regenerate their activity during electrochemical testing. We highlight the relevant techniques and procedures that allowed us to better understand the role of Fe in activating other first-row transition metals for OER. We find several modes of Fe incorporation in Ni/Co (oxy)hydroxides and show how those modes correlate with activity and durability. We also discuss how this understanding informs the incorporation of earth-abundant transition-metal OER catalysts in anion-exchange-membrane water electrolyzers (AEMWE) that provide a locally basic anode environment but run on pure water and have advantages over the more-developed proton-exchange-membrane water electrolyzers (PEMWE) that use platinum-group-metal (PGM) catalysts. We outline the key issues of introducing Fe-doped Ni/Co (oxy)hydroxide catalysts at the anode of the AEMWE, such as the oxidative processes triggered by Fe species traveling through the polymer membrane, pH-gradient effects on the catalyst stability, and possibly limited catalyst utilization in the compressed stack configuration. We also suggest possible mitigation strategies for these issues. Lastly, we summarize remaining challenges including the long-term stability of Fe-doped Ni/Co (oxy)hydroxides under OER conditions and the lack of accurate models of the dynamic active surface that hinder our understanding of, and thus ability to design, these catalysts.

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

Understanding Multi-Ion Transport Mechanisms in Bipolar Membranes

Bipolar membranes (BPMs) have the potential to become critical components in electrochemical devices for a variety of electrolysis and electrosynthesis applications. Because they can operate under large pH gradients, BPMs enable favorable environments for electrocatalysis at the individual electrodes. Critical to the implementation of BPMs in these devices is understanding the kinetics of water dissociation that occurs within the BPM as well as the co- and counter-ion crossover through the BPM, which both present significant obstacles to developing efficient and stable BPM-electrolyzers. In this study, a continuum model of multi-ion transport in a BPM is developed and fit to experimental data. Specifically, concentration profiles are determined for all ionic species, and the importance of a water-dissociation catalyst is demonstrated. The model describes internal concentration polarization and co- and counter-ion crossover in BPMs, determining the mode of transport for ions within the BPM and revealing the significance of salt-ion crossover when operated with pH gradients relevant to electrolysis and electrosynthesis. Lastly, a sensitivity analysis reveals that the performance and lifetime of BPMs can be improved substantially by using of thinner dissociation catalysts, managing water transport, modulating the thickness of the individual layers in the BPM to control salt-ion crossover, and increasing the ion-exchange capacity of the ion-exchange layers in order to amplify the water-dissociation kinetics at the interface.

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

Delocalization error poisons the density-functional many-body expansion

The many-body expansion is a fragment-based approach to large-scale quantum chemistry that partitions a single monolithic calculation into manageable subsystems. This technique is increasingly being used as a basis for fitting classical force fields to electronic structure data, especially for water and aqueous ions, and for machine learning. Here, we show that the many-body expansion based on semilocal density functional theory affords wild oscillations and runaway error accumulation for ion–water interactions, typified by F − (H 2 O) N with N ≳ 15. We attribute these oscillations to self-interaction error in the density-functional approximation. The effect is minor or negligible in small water clusters, explaining why it has not been noticed previously, but grows to catastrophic proportion in clusters that are only moderately larger. This behavior can be counteracted with hybrid functionals but only if the fraction of exact exchange is ≳50%, whereas modern meta-generalized gradient approximations including ωB97X-V, SCAN, and SCAN0 are insufficient to eliminate divergent behavior. Other mitigation strategies including counterpoise correction, density correction (i.e., exchange–correlation functionals evaluated atop Hartree–Fock densities), and dielectric continuum boundary conditions do little to curtail the problematic oscillations. In contrast, energy-based screening to cull unimportant subsystems can successfully forestall divergent behavior. These results suggest that extreme caution is warranted when the many-body expansion is combined with density functional theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A Two-Dimensional Non-Linear Magnetic Equivalent Circuit Model to Facilitate the Preliminary Design of a Normal Conducting Quadrupole

Normal conducting quadrupoles have been used to focus charged particle beams in synchrotrons, beam transfer lines, medical linacs, etc. for a long time. Optimization techniques based on analytical expressions combined with the use of a numerical field analysis tool exist in the literature for the design of an optimal pole tip shape. However, the initial shape and dimensions of the remaining yoke (including the pole itself and yoke base that act as the return path) are usually less well defined. This article discusses a design methodology for a normal conducting quadrupole based on a two-dimensional magnetic equivalent circuit. Here, this approach considers the geometry of the entire magnet and the non-linear behavior of the yoke material, thereby eliminating the initial iterations. The design outcome of this exercise serves as a competent starting point and can then be used to refine the pole tip, pole taper, yoke size, and add other geometrical features to achieve the required field quality, gradient, coil considerations, etc. by employing a finite element analysis tool. An example design study to demonstrate the proposed methodology is presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗