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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Improving convergence of the Matrix Power Control Algorithm for random vibration testing

Herein, this paper describes modifications to the Matrix Power Control Algorithm (MPCA) to improve convergence for Random Vibration Control (RVC) testing. In particular, this paper presents Multiple-Input Multiple-Output (MIMO) implementations of MPCA in simulation and experiment. An Euler–Bernoulli beam model was simulated with applied base excitations and the Box Assembly with Removable Component (BARC) was used in experiment to validate results. The Bayesian optimization package Dragonfly was used to optimize control parameters. Additionally, a moving-average was employed and optimized to improve the measured response feedback for MPCA, reduce the number of averages needed to be taken between control updates, and further improve convergence. The key results of this paper show that the performance of MPCA can be improved by tuning the control parameters and by applying an optimized moving-average. Furthermore, it is demonstrated that convergence can be achieved within 12 drive-frames, which greatly enhances vibration control capability.

42 ENGINEERING↗
DOE OSTI2022

The Pantheon+ analysis: Improving the redshifts and peculiar velocities of Type Ia supernovae used in cosmological analyses

We examine the redshifts of a comprehensive set of published Type Ia supernovae, and provide a combined, improved catalogue with updated redshifts. We improve on the original catalogues by using the most up-to-date heliocentric redshift data available; ensuring all red shifts have uncertainty estimates; using the exact formulae to convert heliocentric redshifts into the Cosmic Microwave Background (CMB) frame; and utilising an improved peculiar velocity model that calculates local motions in redshift-space and more realistically accounts for the external bulk flow at high-redshifts. We review 2607 supernova redshifts; 2285 are from unique supernovae and 322 are from repeat observations of the same supernova. In total, we updated 990 unique heliocentric redshifts, and found 5 cases of missing or incorrect heliocentric corrections, 44 incorrect or missing supernova coordinates, 230 missing heliocentric or CMB frame redshifts, and 1200 missing redshift uncertainties. The absolute corrections range between 10 -8 ≤ Δz ≤ 0.038, and RMS(Δz) ~ 3 × 10 -3 . The sign of the correction was essentially random, so the mean and median corrections are small: 4 × 10 -4 and 4 × 10 -6 respectively. We examine the impact of these improvements for H 0 and the dark energy equation of state w and find that the cosmological results change by ΔH 0 = -0.12 km s -1 Mpc -1 and Δw = 0.003, both significantly smaller than previously reported uncertainties for H 0 of 1.0 km s -1 Mpc -1 and w of 0.04 respectively.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Biodiesel Ethers: Fatty Acid-Derived Alkyl Ether Fuels as Improved Bioblendstocks for Mixing-Controlled Compression Ignition Engines

In the last 20 years, biodiesel consumption in the United States has swiftly increased to ~2 billion gallons per year as a renewable supplement to fossil fuel. However, further expansion of biodiesel use is currently limited in part by poor cold weather performance, which prevents year-round blending and necessitates blend walls ≤5% v/v. In order to provide a diesel fuel blendstock with improved cold weather performance (cloud point, pour point, and cold filter plug point), while at the same time maintaining other required fuel performance specifications, several biodiesel redox analogues were synthesized and tested. The best performing candidate fuels from this class showed improvement in the derived cetane number (29.3% shorter ignition delay), lower heating value (+4.7 MJ/kg), relative sooting tendency (–7.4 YSI/MJ), and cloud point (15 °C lower) when compared to a B100 biodiesel composed of an identical fatty acid profile. It was observed as a general trend that the reduced form of biodiesel, fatty alkyl ethers (FAEs), shows performance improvements in all fuel property metrics. The suite of improved properties provided by FAEs gives biodiesel producers the opportunity to diversify their portfolio of products derived from lipid and alcohol feedstocks to include long-chain alkyl ethers, a biodiesel alternative with particular applicability for winter weather conditions across the US.

09 BIOMASS FUELS↗
DOE OSTI2020

Minimal Experimental Bias on the Hydrogen Bond Greatly Improves Ab Initio Molecular Dynamics Simulations of Water

Experiment Directed Simulations (EDS) is a method within a class of techniques seeking to improve molecular simulations by minimally biasing the system Hamiltonian to reproduce certain experimental observables. In a previous application of EDS to ab initio molecular dynamics (AIMD) simulation based on electronic density functional theory (DFT), the AIMD simulations of water were biased to reproduce its experimentally derived solvation structure. In particular, by solely biasing the O-O pair correlation functions, other structural and dynamical properties that were not biased were improved. In this work, the hypothesis is tested that directly biasing the OH pair correlation (and hence the H-O∙∙∙H hydrogen bonding), will provide an even better improvement of DFT-based water properties in AIMD simulations. The logic behind this hypothesis is that for most electronic DFT descriptions of water the hydrogen bonding is known to be deficient due to anomalous charge transfer and over polarization in the DFT. Using recent advances to the EDS learning algorithm, we thus train a minimal bias on AIMD water that reproduces the O-H radial distribution function derived from the highly accurate MB-pol model of water. Finally, it is then confirmed that biasing the O-H pair correlation alone can lead to improved AIMD water properties, with structural and dynamical properties in even closer to experiment than the previous EDS-AIMD model.

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

Elucidating Diiodomethane-Induced Improvement in Photonically Cured MAPbI 3 Solar Cells

Diiodomethane (CH 2 I 2 ) has been reported to improve the photonically cured perovskite solar cell (PSC) device performance by reducing pinholes. Here we show that even for pinhole-free methylammonium lead iodide (MAPbI 3 ) made by photonic curing, adding CH 2 I 2 promotes significant performance improvement. We elucidate the mechanisms behind the observed improvement. In addition to current-density versus voltage measurements, we perform a wide variety of characterization to compare the crystallinity, grain structure, optical, chemical, and electrical properties of the photonically cured samples with and without CH 2 I 2 in the MAPbI 3 layer to those of thermally annealed devices. Here, the addition of CH 2 I 2 promotes grain growth in the vertical direction, increases the I/Pb ratio in the final film, and removes the I - ionic diffusion and defect signature associated with iodine interstitials. As a result, we achieve a champion efficiency of 15.04% with MAPbI 3 conversion time of 20 ms, comparable to PSCs that have MAPbI 3 layer thermally annealed for 10 min. Understanding the mechanisms behind additive-induced improvements for non-thermal annealing processes is critical to enabling high-speed PSC manufacturing.

14 SOLAR ENERGY↗
DOE OSTI2025

Ammonolysis Under NH 3 –Limiting Conditions as a Pathway to Improved LaTiO 2 N Water Splitting Photoanodes

LaTiO 2 N is a promising intermediate band gap semiconductor for the water splitting reaction, a pathway to hydrogen fuel from solar energy. However, the photoelectrochemical (PEC) activity of the material is hindered by defects, particularly Ti(III) species, which promote photocarrier recombination. These defects are formed during the high-temperature ammonolysis reaction. Here we show that improved LaTiO 2 N materials can be synthesized under NH 3 -limiting conditions by introducing N 2 to lower the NH 3 partial pressure to0.13atm.This reduces the Ti(III) defect density in the material from 6.06 × 10 16 to ∼4.61 × 10 15 cm −3 , by a factor of 13, based on electron paramagnetic resonance (EPR) spectroscopy. Any remaining Ti(III) defects are localized at the LaTiO 2 N surface, according to X-ray photoelectron spectroscopy (XPS), due to the formation of a depletion layer in the semico. Optical absorption spectra of the improved LaTiO 2 N reveal a blue-shifted band gap absorption edge and a suppressed sub-band gap absorption. Defect removal also reduces a sub-band gap surface photovoltage feature visible in the 1.0 atm reference material. The improved LaTiO 2 N supports a 1.57 mA cm −2 water oxidation photocurrent at 1.23 V RHE under simulated sunlight conditions, and an enhanced quantum efficiency of 4.5% (400 nm) for photocatalytic oxygen evolution from aqueous silver nitrate solution. Stable PEC operation is observed for over 55 min. This confirms that ammonolysis under NH 3 -limiting conditions improves the solar energy conversion properties of LaTiO 2 N. The ability to control metal ion defects in oxynitrides by varying the ammonia partial pressure during ammonolysis might be generally useful for the preparation of metal nitrides and oxynitrides.

defects↗
DOE OSTI2021

Improved Rate for the Oxygen Reduction Reaction in a Sulfuric Acid Electrolyte using a Pt(111) Surface Modified with Melamine

The feasible commercialization of alkaline, phosphoric acid and polymer electrolyte membrane fuel cells depends on the development of oxygen reduction reaction (ORR) electrocatalysts with improved activity, stability, and selectivity. The rational design of surfaces to ensure these improved ORR catalytic requirements relies on the so-called "descriptors" (e.g., the role of covalent and noncovalent interactions on platinum surface active sites for ORR). Here, we demonstrate that through the molecular adsorption of melamine onto the Pt(111) surface [Pt(111)-M ad ], the activity can be improved by a factor of 20 compared to bare Pt(111) for the ORR in a strongly adsorbing sulfuric acid solution. Additionally, the M ad moieties act as "surface-blocking bodies," selectively hindering the adsorption of (bi)sulfate anions (well-known poisoning spectator of the Pt(111) active sites) while the ORR is unhindered. This modified surface is further demonstrated to exhibit improved chemical stability relative to Pt(111) patterned with cyanide species (CN ad ), previously shown by our group to have a similar ORR activity increase compared to bare Pt(111) in a sulfuric acid electrolyte, with Pt(111)-M ad retaining a greater than ninefold higher ORR activity relative to bare Pt(111) after extensive potential cycling as compared to a greater than threefold higher activity retained on a CN ad -covered Pt(111) surface. We suggest that the higher stability of the Pt(111)-M ad interface stems from melamine's ability to form intermolecular hydrogen bonds, which effectively turns the melamine molecules into larger macromolecular entities with multiple anchoring sites and thus more difficult to remove.

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

Selective Isolation of Surface Grain Boundaries by Oxide Dielectrics Improves Cd(Se,Te) Device Performance

Cd(Se,Te) photovoltaics (PV) are the most widely deployed thin-film solar technology globally, yet continued efficiency improvements are stymied by challenges at the device hole contacts. The inclusion of solution-processed oxide layers such as AlGaO x in the contact stack has yielded improved device open-circuit voltages (V OC ) and fill factors (FF). However, contradictory mechanisms by which these layers improve the device properties have been proposed by the research community. We demonstrate in this work that an underappreciated property of such spin-coated layers is the preferential deposition at grain boundaries, a process that isolates the grain boundaries during contact metallization. The effects of grain-boundary isolation are probed by varying the coverage of solution-processed AlGaO x “barrier” layers on the Cd(Se,Te) surface, quantified by scanning Auger microscopy. Examining coverage-dependent V OC and FF, it was observed that isolating the grain boundaries during metallization is sufficient to prevent damage to the absorber that occurs in devices lacking a barrier layer, while additional coverage contributes to the increased series resistance. Such an effect is agnostic to the material used as a barrier layer, as long as the material does not itself damage the absorber. Spin-coated SiO x was used in place of AlGaO x for an equally beneficial effect. This grain-boundary isolation phenomenon is also observed during Mo deposition and in absorbers that have been contacted with a nitrogen-doped ZnTe layer. The mechanisms by which metallization may degrade the absorber are discussed, as are contact design strategies leveraging barrier layers, which may lead to improved device efficiencies.

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

Improving Gas Selectivity in Membranes Using Polymer-Grafted Silica Nanoparticles

Herein, we demonstrate that tuning of structural parameters and material chemistry enables control of the permeability and selectivity of gases (CO 2 , He, and CH 4 ) in membranes based on poly(butyl methacrylate)-grafted nanoparticles (PGNs). Our data show that the presence of nanoparticles and the overall dense packing of grafted chains noticeable in PGNs with low grafting density have an adverse effect on the diffusivity of gases. This effect is compensated by an improvement in the solubility of CO 2 gas promoted by the silica nanoparticle surface, yielding a substantial improvement in the permeability of CO 2 versus CH 4 . Furthermore, in membranes with high grafting density, changes in the structural arrangements and alterations in the membrane porosity, evident from small-angle X-ray scattering and positron annihilation lifetime spectroscopy, positively influence the permeability of He and CO 2 gases. In contrast, CH 4 permeability in the same membranes is significantly suppressed, suggesting the formation of a unique, highly selective environment for gas separation. As a result, an improvement of up to 50% in selectivity for gas pairs containing large CH 4 molecules is observed. Our studies provide fundamental insights into the role that structural parameters play in gas transport through polymer membranes, laying a foundation for the rational design of membranes with improved permeability and selectivity.

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

Utilizing Machine Learning to Improve Neutralization Potency of an HIV-1 Antibody Targeting the gp41 N-Heptad Repeat

The N-heptad repeat (NHR) of the HIV-1 gp41 prehairpin intermediate (PHI) is an attractive potential vaccine target with high sequence conservation across diverse strains. However, despite the potency of NHR-targeting peptides and clinical efficacy of the NHR-targeting entry inhibitor enfuvirtide, no potently neutralizing NHR-directed monoclonal antibodies (mAbs) nor antisera have been identified or elicited to date. The lack of potent NHR-binding mAbs both dampens enthusiasm for vaccine development efforts at this target and presents a barrier to performing passive immunization experiments with NHR-targeting antibodies. To address this challenge, we previously developed an improved variant of the NHR-directed mAb D5, called D5_AR, which is capable of neutralizing diverse tier-2 viruses. Building on that work, here we present the 2.7Å-crystal structure of D5_AR bound to NHR mimetic peptide IQN17. We then utilize protein language models and supervised machine learning to generate small (n < 100) libraries of D5_AR variants that are subsequently screened for improved neutralization potency. We identify a variant with 5-fold improved neutralization potency, D5_FI, which is the most potent NHR-directed monoclonal antibody characterized to date and exhibits broad neutralization of tier-2 and −3 pseudoviruses as well as replicating R5 and X4 challenge strains. Additionally, our work highlights the ability of protein language models to efficiently identify improved mAb variants from relatively small libraries.

Biopolymers↗
DOE OSTI2023

Salts as Additives: A Route to Improve Performance and Stability of n-Type Organic Electrochemical Transistors

Organic electrochemical transistors (OECTs) are becoming increasingly ubiquitous in various applications at the interface with biological systems. However, their widespread use is hampered by the scarcity of electron-conducting (n-type) backbones and the poor performance and stability of the existing n-OECTs. Here, we introduce organic salts as a solution additive to improve the transduction capability, shelf life, and operational stability of n-OECTs. We demonstrate that the salt-cast devices present a 10-fold increase in transconductance and achieve at least one year-long stability, while the pristine devices degrade within four months of storage. The salt-added films show improved backbone planarity and greater charge delocalization, leading to higher electronic charge carrier mobility. These films show a distinctly porous morphology where the interconnectivity is affected by the salt type, responsible for OECT speed. The salt-based films display limited changes in morphology and show lower water uptake upon electrochemical doping, a possible reason for the improved device cycling stability. Our work provides a new and easy route to improve n-type OECT performance and stability, which can be adapted for other electrochemical devices with n-type films operating at the aqueous electrolyte interface.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Hanging drop sample preparation improves sensitivity of spatial proteomics

Spatial proteomics holds great promise for revealing tissue heterogeneity in both physiological and pathological conditions. However, one significant limitation of most spatial proteomics workflows is the requirement of large sample amounts that blurs cell-type-specific or microstructure-specific information. In this study, we developed an improved sample preparation approach for spatial proteomics and integrated it with our previously-established laser capture microdissection (LCM) and microfluidics sample processing platform. Specifically, we developed a hanging drop (HD) method to improve the sample recovery by positioning a nanowell chip upside-down during protein extraction and tryptic digestion steps. Compared with the commonly-used sitting-drop method, the HD method keeps the tissue pixel away from the container surface, and thus improves the accessibility of the extraction/digestion buffer to the tissue sample. The HD method can increase the MS signal by 7 fold, leading to a 66% increase in the number of identified proteins. An average of 721, 1489, and 2521 proteins can be quantitatively profiled from laser-dissected 10 μm-thick mouse liver tissue pixels with areas of 0.0025, 0.01, and 0.04 mm 2 , respectively. The improved system was further validated in the study of cell-type-specific proteomes of mouse uterine tissues.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Protection and enrichment: how two different carbonaceous biofilm supports improve methane yield from encapsulated anaerobic microorganisms

Encapsulating anaerobic microorganisms allows for the separation of the solids retention time from the hydraulic retention time during anaerobic wastewater treatment. The harsh chemistries involved in the process of encapsulation can have adverse effects on microorganisms for anaerobic digestion, especially methanogens, and can lead to lower methane yields after encapsulation. Improving the survival and maintaining activity of anaerobic communities during encapsulation will likely be the key to improving methane yield. In this study, we investigated the encapsulation of biomass grown as biofilms on two carbonaceous materials, biochar and powdered activated carbon (PAC), to improve methane yield. Microorganisms grown as biofilms on biochar and PAC were encapsulated in polyethylene glycol (PEG) and incubated for 10 days. After 10 days, the unamended control capsules produced 81.6 ± 5.4 μmol of methane, while PAC-amended capsules produced 129.8 ± 1.9 μmol and biochar-amended capsules produced 432.96 ± 20.8 μmol methane, with the differences being statistically significant (p < 0.05). In biochar, a higher relative abundance of methanogens led to increased methane production capacity. The ratio of the methyl coenzyme M reductase (mcrA) genes to total 16S rRNA genes in the encapsulated biochar-supported biofilms was significantly higher than that in the encapsulated unsupported (p = 4.9 × 10 −5 ) and the PAC-supported biofilms (p = 0.012). Biochar-supported biofilms also had higher methane output per mcrA or 16S rRNA gene copy number. For the PAC, biofilms were protected from ammonium persulfate (APS), a powerful oxidant used in the encapsulation process. PAC removed 92% of dissolved APS, reducing exposure of the methanogens to this chemical. Unfortunately, this removal of APS compromised capsule stability, limiting the amount of PAC that could be added to the capsules. Furthermore, amendments that improve survival and activity of methanogens should be used in the capsules instead of those that protect methanogens by interfering with encapsulant polymerization chemistry.

Resource recovery↗
DOE OSTI2020

Improving Primary Frequency Response in Networked Microgrid Operations using Multilayer Perceptron-Driven Reinforcement Learning

Individual microgrids can improve the reliability of power grids during extreme events, and networked microgrids can further improve efficiency through resource sharing and increase the resilience of critical end-use loads. However, networked microgrid operations are subject to large switching transients, which can cause dynamic instability and lead to system collapse. These transients are especially prevalent in microgrids with high penetrations of inverter-connected renewable energy resources, which do not provide the system inertia needed to mitigate the transients. Existing generator controls can be modified to invoke a drop in terminal voltage in response to a frequency deviation, thereby reducing load and improving frequency response. This paper investigates the use of a reinforcement-learning--based controller trained over several switching transient scenarios to modify generator controls during large frequency deviations. Compared to previously used proportional integral controllers, the proposed controller can improve primary frequency response while adapting to changes in system topologies and events.

Radhakrishnan, Nikitha↗
DOE OSTI2023

Prompt core confinement improvement across the L–H transition in DIII-D: Profile stiffness, turbulence dynamics, and isotope effect

Here, we elaborate on the nature of the prompt core confinement improvement observed at the L–H transition in DIII-D, which is a long-standing issue unsolved for more than two decades and can impact future fusion reactor performance. Dynamic transport analysis suggests the essential role of the profile stiffness for understanding the mechanism of the prompt core confinement improvement. Beam emission spectroscopy shows that transport reduction at the core cannot be explained only by the ion scale turbulence density fluctuation suppression. Properties of nonlocal confinement improvement across the L–H transition are experimentally assessed in hydrogen (H) and deuterium (D) plasmas. Prompt core confinement improvement is found to be more rapid in the lighter hydrogen isotope.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Unsupervised Learning for Improved Gamma-Ray Spectrometry in Pixelated Cadmium Zinc Telluride (CZT) Detectors

Machine learning has been found to be ubiquitously useful across many industries, presenting an opportunity to improve radiation detection performance using data-driven algorithms. Improved detector resolution can aid in the detection, identification, and quantification of radionuclides. Here, in this work, a novel, data-driven, unsupervised learning approach is developed to improve detector spectral characteristics by learning, and subsequently rejecting, poorly performing regions of the pixelated detector. Feature engineering is used to fit individual characteristic photo peaks to a Doniach lineshape with a linear background model. Then, principal component analysis is used to learn a lower-dimension latent space representation of each photo peak where the pixels are clustered, and subsequently ranked, based on the cluster mean distance to an optimal point. Pixels within the worst cluster(s) are rejected to improve the full-width at half-maximum (FWHM) by 10% to 15% (relative to the bulk detector) at 50% net efficiency when applied to training data obtained from measurements of a 100 μCi 154 Eu source using a H3D M400i pixelated cadmium zinc telluride detector. These results compare well with, but do not outperform, a greedy algorithm that accumulates pixels in order of FWHM from lowest to highest used as a benchmark. In the future, this approach can be extended to include the detector energy and angular response. Finally, the model is applied to newly seen natural and enriched uranium spectra relevant for nuclear safeguards applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Stability analysis of WEST L-mode discharges with improved confinement from boron powder injection

WEST L-mode plasmas with dominant electron heating and no core torque source have observed improvements in confinement during boron (B) powder injection. These results are reminiscent of previous powder injection experiments on other devices and gaseous impurity seeding experiments on WEST. During powder injection, the stored energy increased up to 25% due to enhanced ion and electron heat and particle confinement. The improvements in confinement were not indicative of an L-H transition. To identify the dominant mechanisms and the causality chain behind these improvements in confinement, we employ interpretative modeling using METIS, predictive integrated modeling using a high-fidelity plasma simulator (HFPS), and stand-alone gyrokinetic simulations using quasi-linear gyrokinetic code. Interpretative modeling with METIS allowed for the estimation of missing data while maintaining good overall consistency with experiment. These results provided the initial conditions for fully predictive flux driven simulations using the HFPS. From these simulations, quasi-linear gyrokinetic analysis was performed at ρ = 0.5 and ρ = 0.65. Collisionality was found to be a strong candidate for the turbulence suppression mechanism at ρ = 0.5, while a combination of collisionality and the T e /T i ratio was found to be the likely mechanism at ρ = 0.65. The results additionally suggested that increased Z eff (through main ion dilution) could play a role in the improved confinement, but this could not be confirmed due to a lack of experimental measurements. The modeling framework established here can now be used to evaluate and exploit a variety of future powder injection experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Design improvements to the SNS ion source and diagnostics

The U.S. Spallation Neutron Source (SNS) is a state-of-the-art neutron scattering facility delivering the world's most intense pulsed-neutron beams to a wide array of instruments which are used to conduct investigations in many fields of science and engineering. The accelerator system is fed by an RF-driven, multicusp, H - ion source which nominally provides pulsed beam currents of 50-60 mA (1ms, 60Hz). This report provides a discussion of ongoing design improvements to the SNS ion source and Low Energy Beam Transport (LEBT) as well as diagnostic upgrades undertaken since the previous ICIS conference. These improvements include (i) simple mechanical modifications to the source outlet aperture which resulted in dramatically increased extracted beam current and comparable or lower emittance at similar beam currents, (ii) design improvements to the LEBT chopper target which will enable full power beam-dumping during physics studies, (iii) refinement of the SNS Allison emittance scanner that has enabled the first reliable LEBT beam measurements at full beam power (65kV, 50-100mA, 1ms, 60Hz) on the SNS ion source test stand and (iv) the implementation of a thermal imaging camera for the monitoring the LEBT electrode temperatures. (v) The design of an advanced Cs system, capable of more efficient Cs utilization with significantly lower Cs losses from the source is also presented. Mechanical details, computational simulations and experimental results are discussed within the context of these improvements.

47 OTHER INSTRUMENTATION↗