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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Quantum Circuits for the Preparation of Spin Eigenfunctions on Quantum Computers

The application of quantum algorithms to the study of many-particle quantum systems requires the ability to prepare wave functions that are relevant in the behavior of the system under study. Hamiltonian symmetries are important instruments used to classify relevant many-particle wave functions and to improve the efficiency of numerical simulations. In this work, quantum circuits for the exact and approximate preparation of total spin eigenfunctions on quantum computers are presented. Two different strategies are discussed and compared: exact recursive construction of total spin eigenfunctions based on the addition theorem of angular momentum, and heuristic approximation of total spin eigenfunctions based on the variational optimization of a suitable cost function. The construction of these quantum circuits is illustrated in detail, and the preparation of total spin eigenfunctions is demonstrated on IBM quantum devices, focusing on three- and five-spin systems on graphs with triangle connectivity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Chiral topologically ordered insulating phases in arrays of interacting integer quantum Hall islands

Here, we study networks of Coulomb-blockaded integer quantum Hall islands with even fillings ν = 2 k ( k being an integer), including cases with 2 k layers each of ν = 1 fillings. Allowing only spin-current interactions between the islands (i.e., without any charge transfer), we obtain solvable models leading to a rich set of insulating S U ( 2 ) k topologically ordered phases. The case with k = 1 is dual to the Kalmeyer-Laughlin phase, k = 2 to Kitaev's chiral spin liquid and the Moore-Read state, and k = 3 contains a Fibonacci anyon that may be utilized for universal topological quantum computation. Additionally, we show how the S U ( 2 ) k topological phases may be obtained also in an array of islands with ν = 2 k integer quantum Hall states and critical spin chains in a checkerboard pattern. The array and checkerboard constructions gap out the charge mode and additional “flavor” modes by virtue of their geometry. Furthermore, we find that a fine tuning of the system parameter is not needed in the checkerboard configuration and the ν = 2 case. We also discuss their bulk excitations, and show that their thermal Hall conductance is universal, reflecting the central charge c = 3 k / ( k + 2 ) of the chiral edge modes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Machine-learning based model reduction for partial differential equations

We develop a novel synergistic approach between model reduction and machine learning. The specific goal of this project is to aid in the construction of reduced order models for basis functions that are custom-made to represent the solution of partial differential equations. Partial differential equations (PDEs) are one of the main mathematical tools for describing physical phenomena. However, due to either efficiency or necessity, for many real-world problems, we are interested in constructing reduced order models (ROMs) which focus only on the explicit computation of subsets of the active spatio-temporal scales in the problem, while treating the interaction with the rest of the scales approximately. The task of accurate representation of such interactions (usually called memory terms) constitutes a vast area of research known as model reduction. PI Stinis has significant expertise in the construction of ROMs for complex systems. In addition, in recent work with the project key participant Qadeer, they have utilized machine learning to acquire custom-made basis functions (CBFs) to expand the solutions of PDEs. In the proposed work, we will merge the two concepts by constructing ROMs for subsets of the CBFs needed to represent the solution of a PDE. Specifically, we will use the Mori-Zwanzig model reduction formalism to construct ROMs for subsets of CBFs for nonlinear PDEs of various complexity, as well as investigate the usage of CBFs in the spectral vanishing viscosity method for problems that can form shocks in finite time. The outcome of the research is aimed to be proof-of-concept about a novel synergistic approach between model reduction and machine learning, thus advancing the field of scientific machine learning. Such a capability will benefit the efficient modeling of physical systems appearing in various areas of interest to the DOE.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Enabling Structure/Interface Regulation for High Performance Ni-Rich Cathodes

Here, further commercialization of Ni-rich layered cathodes is hindered by severe structure/interface degradation and kinetic hindrance that occur during electrochemical operation, which leads to safety risks and reduced range in electric vehicles (EVs). Herein, by selecting elements with different solubility properties, a multifunctional strategy that synchronously fabricates perovskite-type SrZrO 3 coating and Sr/Zr co-doping is employed to strengthen the structure/interface stability and the Li + transport mobility of LiNi 0.85 Co 0.10 Mn 0.05 O 2 (NCM). Perovskite-type SrZrO 3 protective layers formed on the particle surface can substantially mitigate the unexpected interfacial side reactions and surface phase transitions. In addition, a robust crystal framework is constructed by optimizing local O coordination through the introduction of strong Zr-O bonds. Notably, Li + diffusion kinetics is effectively improved due to expanded cell parameters and O-Li-O slab spacing with the incorporation of large-diameter Sr pillar ions, as revealed by X-ray diffraction. As a result, the Sr/Zr-modified NCM achieves a remarkable capacity retention of 99.4% after 200 cycles at 1 C, and a high rate capacity of 168.9 mAh g -1 at 10 C. This work opens new avenues to develop high-performance NCM cathodes with high energy and high power for EVs with long calendar life.

25 ENERGY STORAGE↗
DOE OSTI2017

Strengths, challenges, and opportunities for hydrothermal pretreatment in lignocellulosic biorefineries

Pretreatment prior to or during biological conversion is required to achieve high sugar yields essential to economic production of fuels and chemicals from low cost, abundant lignocellulosic biomass. Aqueous thermochemical pretreatments achieve this performance objective from pretreatment coupled with subsequent enzymatic hydrolysis, but chemical pretreatment can also suffer from additional costs for exotic materials of construction, the need to recover or neutralize the chemicals, introduction of compounds that inhibit downstream operations, and waste disposal, as well as for the chemicals themselves. The simplicity of hydrothermal pretreatment with just hot water offers the potential to greatly improve the cost of the entire conversion process if sugar degradation during pretreatment, production of un-fermentable oligomers, and the amount of expensive enzymes needed to obtain satisfactory yields from hydrothermally pretreated solids can be reduced. Biorefinery economics would also benefit if value could be generated from lignin and other components that are currently fated to be burned for power. However, achieving these goals will no doubt require development of advanced hydrothermal pretreatment configurations. For example, passing water through a stationary bed of lignocellulosic biomass in a flowthrough configuration achieves very high yields of hemicellulose sugars, removes more than 75% of the lignin for potential valorization, and improves sugar release from the pretreated solids with lower enzyme loadings. Unfortunately, the large quantities of water needed to achieve this performance result in very dilute sugars, high energy costs for pretreatment and product recover, and large amounts of oligomers. Furthermore, improving our understanding of hydrothermal pretreatment fundamentals is needed to gain insights into R&D opportunities to improve performance, and help identify novel configurations that lower capital and operating costs and achieve higher yields.

09 BIOMASS FUELS↗
DOE OSTI2018

On ’t Hooft defects, monopole bubbling and supersymmetric quantum mechanics

We revisit the localization computation of the expectation values of ’t Hooft operators in N = 2* SU(N) theory on R 3 × S 1 . We show that the part of the answer arising from “monopole bubbling” on R 3 can be understood as an equivariant integral over a Kronheimer-Nakajima moduli space of instantons on an orbifold of C 2 . It can also be described as a Witten index of a certain supersymmetric quiver quantum mechanics with N = (4, 4) supersymmetry. The map between the defect data and the quiver quantum mechanics is worked out for all values of N. For the SU(2) theory, we compute several examples of these line defect expectation values using the Witten index formula and confirm that the expressions agree with the formula derived by Okuda, Ito and Taki. In addition, we present a Type IIB construction — involving D1-D3-NS5-branes — for monopole bubbling in N = 2* SU(N) SYM and demonstrate how the quiver quantum mechanics arises in this brane picture.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Matrix polysaccharides affect preferred orientation of cellulose crystals in primary cell walls

The spatial organization and interactions of constituent components influence cell growth and determine physical and chemical properties of the cell wall, including its rigidity, flexibility, and degradability. Elucidating the interactions between cell wall polysaccharides is crucial for advancing our knowledge of how cell walls are assembled and for designing approaches to efficiently break down cell walls to produce renewable energy and biomaterials. Here, we investigated the effect of defects in the biosynthesis of cell wall components on the nanoscale organization of cellulose in primary cell walls through grazing incidence wide angle X-ray scattering (GIWAXS) measurements of hypocotyls of wild type Arabidopsis thaliana and of cellulose, pectin, and xyloglucan (hemicellulose) deficient mutants. GIWAXS reveals changes in lattice spacings, coherence lengths, and relative crystalline content for cellulose between wild type and mutant plants. In addition, X-ray pole figures constructed using GIWAXS and X-ray diffraction (XRD) rocking scans quantify an emerging measure of cellulose organization, the degree of preferred orientation (texture) of cellulose crystals with respect to the cell wall plane. Comparing X-ray pole figures from pectin-deficient and xyloglucan-deficient mutants to that of wild type plants reveals that cellulose texture is disrupted in pectin-deficient mutants, but not in xyloglucan mutants. Furthermore, our results indicate that a deficiency of pectin during cell wall biosynthesis alters cellulose organization in plant cell walls.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A bootstrapping approach to social media quantification

Abstract This work considers the use of classifiers in a downstream aggregation task estimating class proportions, such as estimating the percentage of reviews for a movie with positive sentiment. We derive the bias and variance of the class proportion estimator when taking classification error into account to determine how to best trade off different error types when tuning a classifier for these tasks. Additionally, we propose a method for constructing confidence intervals that correctly adjusts for classification error when estimating these statistics. We conduct experiments on four document classification tasks comparing our methods to prior approaches across classifier thresholds, sample sizes, and label distributions. Prior approaches have focused on providing the most accurate point estimate while this work focuses on the creation of correct confidence intervals that appropriately account for classifier error. Compared to the prior approaches, our methods provide lower error and more accurate confidence intervals.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

Techno-economic analysis of advanced small modular nuclear reactors

Here, small modular nuclear reactors (SMRs) represent a robust opportunity to develop low-carbon and reliable power with the potential to meet cost parity with conventional power systems. This study presents a detailed, bottom-up economic evaluation of a 12 × 77 MW e (924 MW e total) light-water SMR (LW-SMR) plant, a 4 × 262 MW e (1,048 MW e ) gas-cooled SMR (GC-SMR) plant, and a 5 × 200 MW e (1,000 MW e total) molten salt SMR (MS-SMR) plant. Cost estimates are derived from equipment costs, labor hours, material inputs, and process-engineering models. The advanced SMRs are compared to natural gas combined cycle plants with and without post-combustion carbon capture and a conventional large nuclear reactor. Overnight capital cost (OCC) and levelized cost of energy (LCOE) estimates are developed. The OCC of the LW-SMR, GC-SMR, and MS-SMR are found to be $\$4,844$/kW, $\$4,355$/kW, and $\$3,985$/kW respectively. The LCOE of the LW-SMR, GC-SMR, and MS-SMR are found to be $\$89.6$/MWh, $\$81.5$/MWh, and $\$80.6$/MWh respectively. A Monte Carlo analysis is performed, for which the OCC and construction time of the LW-SMR is found to have a lower mean and standard deviation than a conventional large reactor. The LW-SMR OCC is found to have a mean of $\$5,233$/kW with a standard deviation of $\$658$/kW and a 90 % probability of remaining between $\$4,254$/kW and $\$6,399$/kW, while the construction duration is found to have a mean of 4.5 years with a standard deviation of 0.8 years and a 90 % probability of remaining between 3.4 and 6.0 years. The economic impact of economies of scale, simplification, modularization, and construction time for SMRs are discussed. Additionally, policy implications for direct SMR capital subsidies and the impact of a carbon tax on natural gas emissions are explored.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Machine learning assisted rediscovery of methane storage and separation in porous carbon from material literature

Porous carbon (PC) has been widely regarded as one of the most promising absorbents for methane storage. Studies show that its uptake capacity and selectivity highly depend on textural structures. Although much effort has been made, unveiling their detailed structure-performance relationship remains a challenge. Here, we propose an innovative study where, with the assistance of machine learning, the hidden relationship of the textural structures of PC with the methane uptake and separation can be derived from existing data in material literature. Machine learning models were trained by the data, including specific surface area, micropore volume, mesopore volume, temperature, and pressure as the input variables and methane uptake as the output variable for prediction. Among the tested models, the multilayer perceptron (MLP) shows the highest accuracy in predicting the methane uptake. In addition, the model enables to automatically construct a uptake performance map in terms of micropore volume and mesopore volume. The obtained MLP model was also extended to explore the CO 2 /CH 4 selectivity by retraining it with the data collected from literature of PC for the CO 2 uptake. Finally, the constructed 2D selectivity map shows that the high selectivity can be achieved in the low CH 4 uptake region.

42 ENGINEERING↗
DOE OSTI2021

A Physics-Constrained Deep Learning Model for Simulating Multiphase Flow in 3D Heterogeneous Porous Media

Physics-based simulators for multiphase flow in porous media emulate nonlinear processes with coupled physics, and usually require extensive computational resources for software development, maintenance and simulation execution. As a result, a huge demand exists for fast modeling of coupled processes in a wide range of subsurface applications including geological sequestration, hydrocarbon recovery and geothermal energy extraction. In this work, an efficient physics-constrained deep learning model is developed for solving multiphase flow in 3-Dimensional (3D) heterogeneous porous media. The model fully leverages the spatial topology predictive capability of convolutional neural networks, specifically U-Net with successive contracting and expansive steps, and is coupled with an efficient continuity-based smoother to predict flow responses that need spatial continuity. Furthermore, the transient regions are penalized to steer the training process such that the model can accurately capture flow in these regions. The model takes inputs including properties of porous media, fluid properties and well controls, and predicts the temporal-spatial evolution of the state variables (pressure and saturation). While maintaining the continuity of fluid flow, the 3D spatial domain is decomposed into 2D images for reducing training cost, and the decomposition results in an increased number of training data samples and better training efficiency. Additionally, a surrogate model is separately constructed as a postprocessor to calculate well flow rate based on the predictions of state variables from the deep learning model. We use the example of CO 2 injection into saline aquifers, and apply the physics-constrained deep learning model that is trained from physics-based simulation data and emulates the physics process. The model performs prediction with a speedup of ~ 1400 times compared to physics-based simulations, and the average temporal errors of predicted pressure and saturation plumes are 0.27% and 0.099% respectively. Furthermore, water production rate is efficiently predicted by a surrogate model for well flow rate, with a mean error less than 5%. Therefore, with its unique scheme to cope with the fidelity in fluid flow in porous media, the physics-constrained deep learning model can become an efficient predictive model for computationally demanding inverse problems or other coupled processes.

58 GEOSCIENCES↗
DOE OSTI2014

The Muon System of the Daya Bay Reactor Antineutrino Experiment

The Daya Bay experiment consists of functionally identical antineutrino detectors immersed in pools of ultrapure water in three well-separated underground experimental halls near two nuclear reactor complexes. These pools serve both as shields against natural, low-energy radiation, and as water Cherenkov detectors that efficiently detect cosmic muons using arrays of photomultiplier tubes. Each pool is covered by a plane of resistive plate chambers as an additional means of detecting muons. Design, construction, operation, and performance of these muon detectors are described. (auth)

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Incorporating Rich Mesoporosity into a Ceria-Based Catalyst via Mechanochemistry

Ceria-based materials possessing mesoporous structures afford higher activity than the corresponding bulk materials in CO oxidation and other catalytic applications, because of the wide pore channel and high surface area. The development of a direct, template-free, and scalable technology for directing porosity inside ceriabased materials is highly welcome. Here in this paper, a family of mesoporous transition-metaldoped ceria catalysts with specific surface areas up to 122 m 2 g -1 is constructed by mechanochemical grinding. No templates, additives, or solvents are needed in this process, while the mechanochemistry-mediated restructuring and the decomposing of the organic group led to plentiful mesopores. Interestingly, the copper species are evenly dispersed in the ceria matrix at the atomic scale, as observed in high resolution scanning transmission electron microscopy in high angle annular dark field. The copper-doped ceria materials show good activity in the CO oxidation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Effect of the hydroaffinity and topology of pore walls on the structure and dynamics of confined water

We perform molecular dynamics simulations to observe the structure and dynamics of SPC/E water in amorphous silica pores and amorphous ice pores with radii slightly larger than 10 Å. In addition to atomically rough pores, we construct completely smooth pores such that the potential felt at a given distance from the pore wall is an averaged atomic potential. As compared to rough walls, smooth walls induce stronger distortions of water structure for both silica and ice confinements. On the other hand, unlike the smooth pores, the rough pores strongly slow down water dynamics at the pore wall. The slowdown vanishes when reducing the atomic charges in the wall, i.e., when varying the hydroaffinity, while keeping the surface topology, indicating that it is not a geometric effect. Rather, it is due to the fact that the wall atoms provide a static energy landscape along the surface, e.g., fixed anchor-points for hydrogen bonds, to which the water molecules need to adapt, blocking channels for structural rearrangement. In the smooth pores, water dynamics can be faster than in the bulk liquid not only at the pore wall but also in the pore center. Changes in the tetrahedral order rather than in the local density are identified as the main cause for this change of the dynamical behavior in the center of smooth pores.

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

Assembly of the MOLLER Toroidal Magnets at Jefferson Lab

The MOLLER experiment at the Thomas Jefferson National Accelerator Facility (JLab) aims to precisely measure the weak interaction between electrons. This experiment leverages the 12 GeV electron beam and will run for three years. A crucial component of MOLLER is a system of five uniquely shaped water-cooled toroidal magnets. These magnets, possessing seven-fold symmetry, are designed to focus particles by separating electrons scattered off hydrogen in a liquid hydrogen target. The five magnets separate electrons scattered off electrons (Møller scattering) and protons (elastic e-p scattering) within target into approximately circular rings at the detector. Here, this paper presents the assembly process for these five toroidal magnets, detailing critical steps including epoxy application, pin insertion, soldering and brazing, coil assembly, and alignment, all performed to meet stringent magnet specifications. Additionally, it discusses challenges encountered during construction and highlights lessons learned, offering insights for future magnet development projects.

Lamont, Joseph [Thomas Jefferson National Accelera↗
DOE OSTI2013

Comprehensive Evaluation of the Geothermal Resource Potential within the Pyramid Lake Paiute Reservation Phase III Report

This project integrated state-of-the-art exploration technologies with a geologic framework and reservoir modeling to ultimately determine the efficacy of future geothermal production within the PLPT reservation. The information gained during this study should help the PLPT to make informed decisions regarding construction of a geothermal power plant. Additional benefits included the transfer of new technologies and geothermal data to the geothermal industry and it created and/or preserved nearly three dozen jobs accordance with the American Recovery and Reinvestment Act of 2009. A variety of tasks were conducted to achieve the above stated objectives. The following are the tasks completed within the project: 1. Permitting 2. Shallow temperature survey 3. Seismic data collection and analysis 4. Fracture stress analysis 5. Phase I reporting Permitting 7. Shallow temperature survey 8. Seismic data collection and analysis 9. Fracture stress analysis 10. Phase I reporting 11. Drilling two new wells 12. Borehole geophysics 13. Phase II reporting 14. Well testing and geochemical analysis 15. Three-dimensional geologic model 16. Three-dimensional reservoir analysis 17. Reservation wide geothermal potential analysis 18. Phase III reporting Phase I consisted of tasks 1 – 5, Phase II tasks 6 – 8, and Phase III tasks 9 – 13. This report details the results of Phase III tasks. Reports are available for Phase I, and II as separate documents.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

Investigation of Microbunching Instabilities in Modern Recirculating Accelerators

Particle accelerators are machines to accelerate and store charged particles, such as electrons or protons, to the energy levels for various scientific applications. A collection of charged particles usually forms a particle beam. There are three basic types of particle accelerators: linear accelerators (linac), storage-ring (or circular) accelerators, and recirculating accelerators. In a linac, particles are accelerated and pass through once along a linear or straight beamline. Storage-ring accelerators propel particles around a circular track and repetitively append the energy to the stored beam. The third type, also the most recent one in chronology, the recirculating accelerator, is designed to accelerate the particle beam in a short section of linac, circulate the beam, and then either continue to accelerate for energy boost or decelerate it for energy recovery. The beam properties of a linac machine are set at best by the initial particle sources. For storage rings, the beam equilibria are instead determined by the overall machine design. The modern recirculating machines share with linacs the advantages to both accelerate and preserve the beam with high beam quality, as well as efficiently reuse the accelerating components. The beamline design in such a machine configuration can however be much more complicated than that of linacs. As modern accelerators push toward the high-brightness or high-intensity frontier by demanding particles in a highly charged bunch (about nano-Coulomb per bunch) to concentrate in an ever-decreasing beam phase space (transverse normalized emittance about 1 μm and relative energy spread of the order of 10^-5 in GeV beam energy), the interaction amongst particles via their self-generated electromagnetic fields can potentially lead to coherent instabilities of the beam and thus pose significant challenges to the machine design and operation. In the past decade and a half, microbunching instability (MBI) has been one of the most challenging issues for such high-brightness or high-intensity beam transport, as it would degrade lasing performance in the fourth-generation light sources, reduce cooling efficiency in electron cooling facilities, and compromise the luminosity of colliding beams in lepton or lepton-hadron colliders. The dissertation work will focus on the MBI in modern recirculating electron accelerators. It has been known that the collective interactions, the coherent synchrotron radiation (CSR) and the longitudinal space charge (LSC) forces, can drive MBI. The CSR effect is a collective phenomenon in which the electrons in a curved motion, e.g. a bending dipole, emit radiation at a scale comparable to the micro-bunched structure of the bunch distribution. The LSC effect stems from non-uniformity of the charge distribution, acts as plasma oscillation, and can eventually accumulate an amount of energy modulation when the beam traverses a long section of a beamline. MBI can be seeded by non-uniformity or shot noise of the beam, which originates from granularity of the elementary charge. Through the aforementioned collective effects, the modulation of the bunch sub-structure can be amplified and, once the beam-wave interaction formed a positive feedback, can result in MBI. The problem of MBI has been intensively studied for linac-based facilities and for storage-ring accelerators. However, systematic studies for recirculation machines are still very limited and form a knowledge gap. Because of the much more complicated machine configuration of the recirculating accelerators than that of linacs, the existing MBI analysis needs to be extended to accommodate the high-brightness particle beam transport in modern recirculating accelerators. This dissertation is focused on theoretical investigation of MBI in such machine configuration in the following seven themes: (1) Development and generalization of MBI theory The theoretical formulation has been extended so as to be applicable to a general linear beamline lattice including horizontal and vertical transport bending elements, and beam acceleration or deceleration. These featured generalizations are required for MBI analysis in recirculation accelerators. (2) Construction of CSR impedance models In addition to the steady-state CSR interaction, it has been found that the exit transient effect (or CSR drift) can even result in more serious MBI in high-brightness recirculation arcs. The onedimensional free-space CSR impedances, especially the exit transients, are derived. The steady-state CSR impedance is also extended to non-ultrarelativistic beam energy for MBI analysis of low-energy merger sections in recirculating accelerators. (3) Numerical implementation of the derived semi-analytical formulation This includes the development of a semi-analytical Vlasov solver for MBI analysis, and also benchmarking of the solver against massive particle tracking simulations. (4) Exploration of multistage amplification behavior of CSR microbunching development The CSR-induced MBI acts as an amplifier, which amplifies the sub-bunch modulation of a beam. The amplification is commonly quantified by the amplification gain. A beam transport system can be considered as a cascaded amplifier. Unlike the two-stage amplification of four-dipole bunch compressor chicanes employed in linacs, the recirculation arcs, which are usually constituted by several tens of bending magnets, show a distinguishing feature of up to six-stage microbunching amplification for our example arc lattices. That is, the maximal CSR amplification gain can be proportional to the peak bunch current up to sixth power. A method to compare lattice performance has been developed in terms of gain coefficients, which nearly depend on the lattice properties only. This method has also proven to be an effective way to quantify the current dependence of the maximal (5) Control of CSR MBI in multibend transport or recirculation arcs The existing mitigation schemes of MBI mostly aim to linac-based accelerators and may not be practical to the recirculating accelerator facilities. Thus a set of conditions for suppression of CSR MBI was proposed and examined for example lattices from low (~100 MeV) to high (~1 GeV) energies. (6) Study of more aspects of microbunched structures in beam phase spaces For a cascaded amplifier in circuit electronics, the total amplification gain can be estimated as the product of individual gains. In a beam transport line of an accelerator, the (scalar) gain multiplication was examined and found to under-estimate the overall microbunching amplification. The concept of gain matrix was developed, which includes the density, energy and transverse-longitudinal modulations in a beam phase space, and used to analyze MBI for a proposed recirculating machine. Throughout the gain matrix approach, it reasonably gives the upper limit of spectral MBI gain curves. This extended analysis can be employed to study multi-pass recirculation. (7) Study of MBI for magnetized beams Driven by a recent energy-recovery-linac based cooler design for electron cooling at Jefferson Lab Electron-Ion Collider Project, the generalized theoretical formulation for MBI to a transversely coupled beam has been developed and applied to this study. A magnetized beam in general features non-zero canonical angular momentum, thus considered to be a transversely coupled beam. A novel idea of utilizing magnetized beam transport was proposed for improvement of cooling efficiency and possible mitigation of collective effects. A concern of MBI regarding this design was studied and excluded. The large transverse beam size associated with the beam magnetization is found to help suppress MBI via the transverse-longitudinal correlation.

43 PARTICLE ACCELERATORS↗