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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Unveiling Highly Sensitive Active Site in Atomically Dispersed Gold Catalysts for Enhanced Ethanol Dehydrogenation

Developing a desirable ethanol dehydrogenation process necessitates a highly efficient and selective catalyst with low cost. Herein, we show that the “complex active site” consisting of atomically dispersed Au atoms with the neighboring oxygen vacancies (Vo) and undercoordinated cation on oxide supports can be prepared and display unique catalytic properties for ethanol dehydrogenation. The “complex active site” Au-Vo-Zr 3+ on Au 1 /ZrO 2 exhibits the highest H 2 production rate, with above 37,964 mol H 2 per mol Au per hour (385 g H 2 $g^{-1}_{Au}$ h -1 ) at 350 °C, which is 3.32, 2.94 and 15.0 times higher than Au 1 /CeO 2 , Au 1 /TiO 2 , and Au 1 /Al 2 O 3 , respectively. Combining experimental and theoretical studies, we demonstrate the structural sensitivity of these complex sites by assessing their selectivity and activity in ethanol dehydrogenation. Our study sheds new light on the design and development of cost-effective and highly efficient catalysts for ethanol dehydrogenation. Fundamentally, atomic-level catalyst design by colocalizing catalytically active metal atoms forming a structure-sensitive “complex site”, is a crucial way to advance from heterogeneous catalysis to molecular catalysis. In conclusion, our study advanced the understanding of the structure sensitivity of the active site in atomically dispersed catalysts.

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

Unveiling Highly Sensitive Active Site in Atomically Dispersed Gold Catalysts for Enhanced Ethanol Dehydrogenation

Developing a desirable ethanol dehydrogenation process necessitates a highly efficient and selective catalyst with low cost. Herein, we show that the “complex active site” consisting of atomically dispersed Au atoms with the neighboring oxygen vacancies (Vo) and undercoordinated cation on oxide supports can be prepared and display unique catalytic properties for ethanol dehydrogenation. The “complex active site” Au–Vo–Zr 3+ on Au 1 /ZrO 2 exhibits the highest H 2 production rate, with above 37,964 mol H 2 per mol Au per hour (385 g H 2 $\text{g}^{-1}_{\text{Au}} \text{h}^{–1}$) at 350 °C, which is 3.32, 2.94 and 15.0 times higher than Au 1 /CeO 2 , Au 1 /TiO 2 , and Au 1 /Al 2 O 3 , respectively. Combining experimental and theoretical studies, we demonstrate the structural sensitivity of these complex sites by assessing their selectivity and activity in ethanol dehydrogenation. Our study sheds new light on the design and development of cost-effective and highly efficient catalysts for ethanol dehydrogenation. Fundamentally, atomic-level catalyst design by colocalizing catalytically active metal atoms forming a structure-sensitive “complex site”, is a crucial way to advance from heterogeneous catalysis to molecular catalysis. Finally, our study advanced the understanding of the structure sensitivity of the active site in atomically dispersed catalysts.

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

Electric Field Control of Magnetic Skyrmion Helicity in a Centrosymmetric 2D van der Waals Magnet

Two-dimensional van der Waals magnets hosting topological magnetic textures, such as skyrmions, show promise for spintronics and quantum computing. Electrical control of these topological spin textures is crucial for enhancing operational performance and functionality. Here, using electron microscopy combined with in situ electric and magnetic biasing, we show that the skyrmion helicity in insulating Cr 2 Ge 2 Te 6 can be controlled by the direction of the external electric field applied during the field cooling process. The electric field-tuned helicity remains stable at low temperature, even amid variations in magnetic and electric fields. Our theoretical investigation reveals that nonzero Dzyaloshinskii-Moriya interactions between nearest neighbors, induced by the electric field, change their sign upon reversing the electric field direction, thereby facilitating helicity selection. The electrical control of magnetic helicity demonstrated in this study can be extended to other centrosymmetric skyrmion-hosting magnets, paving the way for future device designs in topological spintronics and quantum computing.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Insights into the Mechanism of Methanol Steam Reforming Tandem Reaction over CeO 2 Supported Single-Site Catalysts

We demonstrated how the special synergy between a noble metal single site and neighboring oxygen vacancies provides an "ensemble reaction pool" for high hydrogen generation efficiency and carbon dioxide (CO 2 ) selectivity of a tandem reaction: methanol steam reforming. Specifically, the hydrogen generation rate over single site Ru 1 /CeO 2 catalyst is up to 9360 mol H 2 per mol Ru per hour (579 mL H2 g Ru -1 s -1 ) with 99.5% CO 2 selectivity. Reaction mechanism study showed that the integration of metal single site and O vacancies facilitated the tandem reaction, which consisted of methanol dehydrogenation, water dissociation, and the subsequent water gas shift (WGS) reaction. In addition, the strength of CO adsorption and the reaction activation energy difference between methanol dehydrogenation and WGS reaction play an important role in determining the activity and CO 2 selectivity. Our study paves the way for the further rational design of single site catalysts at the atomic scale. Furthermore, the development of such highly efficient and selective hydrogen evolution systems promises to deliver highly desirable economic and ecological benefits.

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

Machine Learning-Based Classification of Lignocellulosic Biomass from Pyrolysis-Molecular Beam Mass Spectrometry Data

High-throughput analysis of biomass is necessary to ensure consistent and uniform feedstocks for agricultural and bioenergy applications and is needed to inform genomics and systems biology models. Pyrolysis followed by mass spectrometry such as molecular beam mass spectrometry (py-MBMS) analyses are becoming increasingly popular for the rapid analysis of biomass cell wall composition and typically require the use of different data analysis tools depending on the need and application. Here, the authors report the py-MBMS analysis of several types of lignocellulosic biomass to gain an understanding of spectral patterns and variation with associated biomass composition and use machine learning approaches to classify, differentiate, and predict biomass types on the basis of py-MBMS spectra. Py-MBMS spectra were also corrected for instrumental variance using generalized linear modeling (GLM) based on the use of select ions relative abundances as spike-in controls. Machine learning classification algorithms e.g., random forest, k-nearest neighbor, decision tree, Gaussian Naïve Bayes, gradient boosting, and multilayer perceptron classifiers were used. The k-nearest neighbors (k-NN) classifier generally performed the best for classifications using raw spectral data, and the decision tree classifier performed the worst. After normalization of spectra to account for instrumental variance, all the classifiers had comparable and generally acceptable performance for predicting the biomass types, although the k-NN and decision tree classifiers were not as accurate for prediction of specific sample types. Gaussian Naïve Bayes (GNB) and extreme gradient boosting (XGB) classifiers performed better than the k-NN and the decision tree classifiers for the prediction of biomass mixtures. The data analysis workflow reported here could be applied and extended for comparison of biomass samples of varying types, species, phenotypes, and/or genotypes or subjected to different treatments, environments, etc. to further elucidate the sources of spectral variance, patterns, and to infer compositional information based on spectral analysis, particularly for analysis of data without a priori knowledge of the feedstock composition or identity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Deciphering the Distribution and Crystal-Chemical Environment of Arsenic, Lead, Silica, Phosphorus, Tin, and Zinc in a Porous Ferrihydrite Grain Using Transmission Electron Microscopy and Atom Probe Tomography

Here the interaction of contaminants and nutrients with soil constituents is controlled by processes in intergranular and intragranular pore spaces of organic matter or/and common secondary minerals such as ferrihydrite, ~Fe 3+ 10 O 14 (OH) 2 . This contribution shows that distribution and clustering of the contaminants As, P, Pb, Si, Sn, and Zn in a porous ferrihydrite grain is greatly affected by the heterogeneous size distribution and chemical composition of the pores as well as the ability of their polyhedra to polymerize with the same type of polyhedron. Transmission electron microscopy (TEM) and atom probe tomography (APT) studies are conducted on focused ion beam (FIB) sections extracted from a porous ferrihydrite grain from the smelter-impacted topsoil in Sudbury, Ontario, Canada. The ferrihydrite grain has pore spaces ranging in diameter from tens to hundreds of nanometers. TEM and scanning-TEM studies indicate that the surfaces of the pore walls are enriched in Si. APT data in conjunction with First Near Neighbor (1NN) analyses indicate different degrees of clustering of Pb, As, Sn, Zn, Si, and P within the sample and selected domains. Careful evaluations of 3D atomic plots and 1NN distances indicates the occurrence of polymerized arsenite-, silica-, Sn-, and Zn-polyhedra within pore spaces of the ferrihydrite. Deciphering adsorption, polymerization, and nucleation processes in porous Fe-(hydr)oxides and other soil constituents requires multianalytical approaches and, in this regard, we discuss the advantages and disadvantages of the combination of TEM and APT for characterizing complex environmental samples at the atomic to nanometer scale.

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

Crystallizing Kagome Artificial Spin Ice

Artificial spin ices are engineered arrays of dipolarly coupled nanobar magnets. They enable direct investigations of fascinating collective phenomena from their diverse microstates. However, experimental access to ground states in the geometrically frustrated systems has proven difficult, limiting studies and applications of novel properties and functionalities from the low energy states. In this work, we introduce a convenient approach to control the competing diploar interactions between the neighboring nanomagnets, allowing us to tailor the vertex degeneracy of the ground states. We achieve this by tuning the length of selected nanobar magnets in the spin ice lattice. We demonstrate the effectiveness of our method by realizing multiple low energy microstates in a kagome artificial spin ice, particularly the hardly accessible long range ordered ground state—the spin crystal state. Our strategy can be directly applied to other artificial spin systems to achieve exotic phases and explore new emergent collective behaviors.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Achieving Ultra-High Selectivity to Hydrogen Production from Formic Acid on Pd–Ag Alloys

Palladium-silver based alloy catalysts have a great potential for CO-free hydrogen production from formic acid for fuel cell applications. However, the structural factors affecting the selectivity of formic acid decomposition is still debated. Herein, the decomposition pathways of formic acid on Pd-Ag alloys with different atomic configurations have been investigated to identify the alloy structures yielding high H 2 selectively. Several Pd x Ag 1-x surface alloys with various compositions were generated on a Pd(111) single crystal; their atomic distribution and electronic structure were determined by a combination of infrared reflection absorption spectroscopy (IRAS), X-ray photoelectron spectroscopy (XPS), and density functional theory (DFT). It was established that the Ag atoms with Pd neighbors are electronically altered, and the degree of alteration correlates with the number of nearest Pd. Temperature programmed reaction spectroscopy (TPRS) and DFT demonstrated that the electronically altered Ag domains create a new reaction pathway that selectively dehydrogenates formic acid. In contrast, Pd monomers surrounded by Ag are demonstrated to have a similar reactivity compared to pristine Pd(111), yielding CO and H 2 O in addition to the dehydrogenation products. Furthermore, they bind to the produced CO weaker than pristine Pd, demonstrating an enhancement in resistance to CO poisoning. This work therefore shows that surface Ag domains modified by interaction with subsurface Pd are the key active sites for selective decomposition of formic acid, while surface Pd atoms are detrimental for selectivity. Hence the decomposition pathways can be tailored for CO-free H 2 production on Pd-Ag alloy systems.

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

Mechanistic Insights into Nonoxidative Ethanol Dehydrogenation on NiCu Single-Atom Alloys

Ethanol dehydrogenation presents a promising pathway towards the production of acetaldehyde, a valuable building block in chemicals production. Under non-oxidative conditions, the reaction is facilitated by supported Cu nanoparticles which afford reasonable activity and high selectivity. The stability issues associated with Cu nanoparticle sintering can be addressed by the addition of small amounts of Ni, which further boost reactivity while retaining selectivity. Despite the promise of NiCu single-atom alloys for non-oxidative ethanol dehydrogenation, little is known about the role of each component and the pathway of this mechanistically complex process. Herein, kinetic investigations from reactor tests identify C-H bond scission as the rate limiting step, while 1-hydroxyethyl is detected as the intermediate via IR spectroscopy. Temperature program desorption studies are employed to examine the effect of Ni coverage and to demonstrate that Ni atoms activate ethanol selectively at lower temperatures, resulting in higher acetaldehyde yield than pure Cu. Temperature program desorption experiments also reveal the spillover of intermediates from the Ni atom to neighboring Cu sites as a relevant step in the reaction pathway. Density functional theory calculations are used to investigate the 2 reaction energetics and to confirm that C-H bond scission is the initial reaction step, while a clear effect of H 2 partial pressure on the reaction pathway is realized. Further, counter to the expected behavior that all reaction steps take place on the Ni atoms, our degree of rate control analysis reveals that a mechanism involving spillover of the 1-hydroxyethyl intermediate from the Ni atom to the Cu surface, where it will dehydrogenate further, is more likely. Furthermore, our combined kinetic, spectroscopic, and theoretical approach sheds light on this complex reaction mechanism and represents a promising method for the understanding and designing of highly active, selective, and stable single-atom alloys for other multistep catalytic processes.

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

Dehydrogenation of Propane and n -Butane Catalyzed by Isolated PtZn 4 Sites Supported on Self-Pillared Zeolite Pentasil Nanosheets

Propene and 1,3-butadiene are important building-block chemicals that can be produced by dehydrogenation of propane and butane over Pt catalysts. The challenge is to develop highly active and selective catalysts that are resistant to deactivation by Pt sintering and coke formation. We have recently shown that these objectives can be met for propane dehydrogenation using atomically dispersed Pt atoms anchored to neighboring ≡SiOZn-OH groups bonded to the framework dealuminated zeolite BEA. In the present study, we demonstrate that significantly superior performance can be achieved by using self-pillared pentasil (SPP) zeolite nanosheets. Following catalyst reduction in H 2 , atomic-resolution, scanning transmission electron microscopy (STEM) and X-ray absorption spectroscopy (XAS) indicate that Pt is stabilized in structures well approximated as (≡Si-O-Zn) 4-5 Pt. These species are highly active, selective, and stable for propane dehydrogenation (PDH) to give propene and for n-butane dehydrogenation (BDH) to give 1,3-butadiene. No catalyst deactivation was observed after 12 days of time on stream, and the selectivity remained at nearly 100% for PDH conducted at 823 K and a weight hourly space velocity (WHSV) of 1,350 h -1 . The apparent rate coefficient for PDH over this catalyst is significantly higher than that reported previously for Pt-containing catalysts. For BDH at 823 K and a WHSV of 3560 h -1 , the selectivity to butene isomers and 1,3-butadiene is 98.9%, and the selectivity to 1,3-butadiene is 45%. Here, we propose that the high catalyst stability observed during PDH and BDH is a consequence of a large fraction of the Pt-containing centers being located on the external surface of the zeolite nanosheets, where nascent coke precursors can desorb before condensing to form coke.

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

Automated System-wide Event Detection and Classification Using Machine Learning on Synchrophasor Data

As the number of phasor measurement units (PMUs) deployed in a power system increases, and their data volume streamed to the control canter intensifies, operators are facing challenges related to the analysis of such data, which need to be observed and responded to as the measurements are displayed in the Control Room. Humans are generally unable to process such large amount of data efficiently and rapidly. There is an apparent need for automated ways to analyze the data, extract actionable information about occurrence of specific events, and characterize the events quickly and cost effectively. This paper discusses the use of machine learning (ML) to facilitate such tasks by providing automated, highly computationally efficient, and cost-effective ways of extracting actionable information from synchrophasor big data in real-time. We developed Big Data Smart (BDSmart) ML-based prototype tool for the Control Room use that automatically analyses data properties from synchrophasor system measurements taken across the three grid Interconnections in the USA (Western, Eastern and ERCOT). The data collected from several hundreds of PMUs located across the Interconnections over a period of two years have been made available for our extensive study. As a result, we were able to identify a number of big data properties that influence how ML methodology is applied to select, develop, train and test the data models that can eventually be used for the tool implementation. The resulting set of candidate algorithms spans unsupervised, supervised, semi-supervised and transfer-learning approaches. Many ML techniques, such as decision trees, multinomial logistic regression, feed-forward neural networks, K-nearest neighbor, multiclass support vector machine, and single and multi-channel convolutional neural networks, are implemented, and their performance is examined. We offer the results from testing the data models. The novelty of our study is in the approaches for bad data detection and mitigation, selection of a simplified feature for event detection, and data label improvements. As a result, we came up with a list of recommendations for the utilities on how to improve the PMU recording practices to cater to the future ML applications aimed at automating the analysis of synchrophasor data.

Synchrophasors, Machine Learning, System-wide Even↗
DOE OSTI2022

Iridium pair sites anchored to Zr 6 O 8 nodes of the metal–organic framework UiO-66 catalyze ethylene hydrogenation

Isolated metal pair sites on metal oxide and zeolite supports are drawing attention as catalysts, because—in contrast to single atomically dispersed metals—they provide neighboring metal centers that can act cooperatively. We now report pairs of iridium atoms anchored to the Zr 6 O 8 nodes of the metal–organic framework (MOF) UiO-66, synthesized by chemisorption of Ir 2 (μ-OCH 3 ) 2 (COD) 2 (COD is cyclooctadienyl) followed by removal of the COD ligands. The supported species were characterized with infrared spectra of adsorbed CO combined with iridium LIII-edge extended X-ray absorption fine structure and high-energy-resolution fluorescence detection X-ray absorption near edge (HERFD XANES) spectra. The HERFD XANES spectra were recorded with the sample in a variety of atmospheres in which the iridium pair sites were stable, including CO, H 2 , and C 2 H 4 + H 2 at temperatures in the range of 35–80 °C. The data provide sensitive measures of the electronic structure of the iridium in the pair sites. The samples were evaluated as catalysts for ethylene hydrogenation, with the pair-sites being more selective for hydrogenation than analogous isolated atomically dispersed iridium, which catalyzes both hydrogenation and isomerization. Metal pair sites on MOFs offer uncharted opportunities for catalysts having reactivities associated with neighboring metal centers.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Quenching in the Right Place at the Right Time: Tracing the Shared History of Starbursts, Active Galactic Nuclei, and Poststarburst Galaxies Using Their Structures and Multiscale Environments

This work uses multiscale environments and the structures of galaxies in the Sloan Digital Sky Survey as consistency checks on the evolution from starburst to quiescence at redshift z < 0.2. The environmental indicators include fixed-aperture mass overdensities (δ xMpc , x ϵ {0.5, 1, 2, 4, 8} h –1 Mpc), k-nearest neighbor distances, the tidal parameter, halo mass (M h ), and satellite/central classification. The residuals of the specific star formation rates (Δ SSFRs) are used to select starbursts (ΔSSFR > 0.6 dex, N ≈ 8600). Quenched poststarbursts (QPSBs) are selected using Hα < 3 Å emission and Hδ A > 4 Å absorption (N ≈ 750). The environments of starbursts and QPSBs are compared with those of active galactic nuclei (AGNs) and inactive galaxies of varying ΔSSFR. The environments of starbursts, AGNs, and QPSBs are unlike the environments of most quiescent galaxies (QGs). About 70%–90% of starbursts, AGNs with Hδ A > 4 Å, and QPSBs are centrals; ~80%–90% have M h < 10 13 M ⊙ , and only ~2%–4% have M h > 10 14 M ⊙ or live in clusters. Their M h and satellite fractions are also different from those of QGs. All QPSBs are matched to some SFGs, starbursts, AGNs, and QGs of similar M $\star$ , environments, concentration indices, and velocity dispersions. A significant fraction (~20%–30%) of starbursts cannot be matched to QPSBs or QGs. The implications are that: (1) some starbursts do not quench rapidly; (2) the satellite-quenching mechanisms operating in high-density environments cannot account for most QPSBs; (3) the evolution from starbursts to QPSBs to QGs is not the dominant path at z < 0.2; and (4) starbursts are not mainly triggered by tidal interactions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Vapor–Fed Electrolyzers for Carbon Dioxide Reduction Using Tandem Electrocatalysts: Cuprous Oxide Coupled with Nickel–Coordinated Nitrogen–Doped Carbon

We report ethylene is particularly attractive due to its major importance as a feedstock for various applications including the polymer industry. As such, catalyst and electrolyzer developments are crucial to achieve industrially relevant ethylene production and efficiency levels. In this work, a tandem electrocatalyst composed of copper nanocubes and nickel-coordinated nitrogen-doped carbon (NiNC) is presented, which is integrated into gas diffusion electrodes (GDEs) for direct conversion of vapor-fed CO 2 into ethylene. Evaluation of tandem GDEs in the vapor-fed flow electrolyzer shows significantly increased ethylene selectivity in terms of faradaic efficiency and C 2 H 4 /CO ratio compared to a non-tandem copper GDE. The enhancements are attributed to the increased local CO availability near the copper surface via effective CO 2 to CO conversion on neighboring NiNC. The experimental results are validated by 3D resolved continuum simulations, which show increased flux of higher-order prod-ucts with the added CO flux from NiNC. The practical viability of Cu/NiNC catalyst is further evaluated in a membrane electrode assembly electrolyzer, achieving 40% FE toward ethylene at 150 mA cm -2 and 3.2 V. These find-ings highlight the high selectivity and formation rate of ethylene achieved by successful device integration of the Cu/NiNC catalyst, demonstrating the potential for implementation in large-scale sustainable CO 2 electrolyzers.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Preactivated zeolite nanosheet plate-tiled membrane on porous PVDF film: Synthesis and study of proton-selective ion conduction

Preactivated MFI zeolite nanosheet plates (ZNPs) with large areas (~2.0 × 2.0 μm 2 ) and nanometer thicknesses (~60 nm) were prepared directly in liquid-dispersed state. The individual ZNP was a stack of 4-nm-thick single crystalline zeolite nanosheets (ZNs) interlinked by Si–O–Si bonds between neighboring ZN surfaces. The dispersed open-pore ZNPs allowed formulating suspensions for tiling ZNP membranes on polymer substrates without requiring post-coating activation. A pinhole-free ZNP-tiled (ZNPT) membrane has been achieved on macroporous PVDF film by a self-repairing vacuum-assisted filtration coating method. The resultant ZNPT layer was ~500 nm-thick consisting of about 7 ZNP layers with inter-ZNP width and inter-ZNP entrance porosity around 9 nm and 2%, respectively. The ZNPT-PVDF membrane exhibited high selectivity to proton transport over vanadyl ion and low resistances to proton conduction in aqueous solutions. The membrane also demonstrated to function as an efficient ion separator for the vanadium redox flow battery. The reported synthesis of preactivated ZNP suspension may overcome the major hurdle to realizing polymer-supported ZN membranes, which is the inefficiency of existing methods in obtaining readily dispersible open-pore ZNs. Finally, the ZNPT-PVDF membrane can be a more affordable and sustainable alternative to the Nafion-based ion separation membranes.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Beam test of a harmonic kicker cavity

A harmonically resonant kicker cavity designed for beam exchange in a circulator cooler was built and successfully tested at the Upgraded Injector Test Facility (UITF) at Jefferson Lab. This type of cavity is being considered for the injection scheme of the Rapid Cycling Synchrotron at the Electron-Ion Collider, where the spacing of neighboring bunches demands very short kicks. Operating with five transversely deflecting modes simultaneously that resonate at 86.6 MHz and consecutive odd harmonics thereof, the prototype cavity selectively deflects 1 of 11 electron bunches while leaving the others unperturbed. An RF driver was developed to synthesize phase- and amplitude-controlled harmonic signals and combine them to drive the cavity while also separating the modes from a field-probe antenna for RF feedback and dynamic tuning. Beam deflection was measured by sweeping the cavity phase; the deflection waveform agrees with expectations, having sub-nanosecond rise and fall times. No emittance increase is observed. Harmonically resonant cavities like the one described provide a new capability for injection and extraction at circulators and rings.

Bruker, M.W.↗