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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Dynamic Building Load Control to Facilitate High Penetration of Solar Photovoltaic Generation (Final Technical Report)

Solar photovoltaic (PV) resources are the most common form of distributed generation in residential and commercial customer premises within electric distribution networks. A higher penetration of PV generation in distribution circuits will impose challenges on maintaining service voltages within the range of industry standards, power quality, and power flow. Buildings consume 74% of the electricity produced in the United States, and a significant portion of the building load is dispatchable, making them responsive to electrical grid needs. Oak Ridge National Laboratory—in collaboration with Southern Company; the University of Tennessee, Knoxville; and the Georgia Institute of Technology—is examining the PV integration issues in distribution-level electrical grids and developing integrated demand-side control and communication systems to enable responsive loads. The proposed responsive loads mechanism performs renewable generation following to increase the penetration of solar PV within each feeder. The specific objectives of this project are to (1) examine distribution-level PV integration scenarios to understand requirements, (2) undertake an end-to-end simulation-based design of a distributed control strategy of loads geographically near the PV generation asset to minimize the effect on the distribution feeder, (3) deploy and demonstrate the control technology developed in partnership with utilities, and (4) perform a scalability analysis at the utility scale. This 3-year integrated project aims to develop, demonstrate, and validate demand-side control technology to enable increased the penetration of renewables while mitigating challenges that arise due to their intermittency. Activities in Budget Period (BP) 1 focused on a literature review and the formal design of a control system for integrating local distribution with generation and loads. The team used modeling and simulation to evaluate the impact of varying buildings loads, variable PV generation, and power flow dynamics on the distribution circuit. The dynamic models developed in BP 1 were used in BP 2 to develop a model-based control design and a test bed. The test bed has enabled the simulation-based testing and comparison of different control designs and formulations applied to different configurations of the distribution grid, PVs, and building loads. The control approaches developed in BP 2 were implemented in BP 3 in the form of hardware deployed at the Central Baptist Church (CBC) in Knoxville, Tennessee, for testing and evaluation. The outcome of this project was the development and demonstration of open-source, low-cost, low-touch sensing and control retrofits to distributed PV generation and building loads that, in a coordinated fashion, provide the load-shaping response needed to integrate high levels of renewable penetration. This research addresses the target metrics by dynamically controlling a load with solar generation variability to minimize the extent of two-way power flow, enhance reliability, facilitate high PV penetration (>100% of peak load in a line segment), and generate scalable software and hardware solutions adaptable to any penetration levels. The research and development activities are focused and designed to be impactful within the relevant 2020 targets time frame.An accurate open-source integration simulation framework for end-to-end control design was developed and deployed at the CBC facility for testing and evaluation. This final report provides a detailed review of the technical results achieved during this 3-year integrated project. A novel spectral analysis of PV data is demonstrated to derive the requirements of the control design. A detailed simulation-based analysis of PV integration at increasing penetration levels is presented using 1 year of PV data to demonstrate the impact on the distribution circuits. Two different control strategies were developed and demonstrated via simulation to track variable PV generation with adaptive load dispatch. The report concludes with a summary of accomplishments and recommendations for a path forward.

14 SOLAR ENERGY↗
DOE OSTI2021

Assess and Benchmark Magneto-Inertial Fusion (MIF) Scaling. Final Technical Report for the SNL/Rochester ALPHA Follow-on Project

This project was a follow-on to the Sandia National Laboratories (SNL) and the Laboratory for Laser Energetics (LLE) ARPA-E ALPHA project entitled “Demonstrating Fuel Magnetization and Laser Heating Tools for Low-Cost Fusion Energy”. The primary purpose of this follow-on project was to obtain additional data at the OMEGA facility to help better understand how MagLIF, a platform that has already demonstrated the scientific viability of magneto-inertial fusion, scales across a factor of 1000 in driver energy. A secondary aspect of this project was to extend simulations and analysis at SNL to cover a wider magneto-inertial fusion (MIF) parameter space and test scaling of those models across this wide range of input energies and conditions of the target. This work was successful in improving understanding of how key physics elements of MIF scales and improves confidence in setting requirements for fusion gain with larger drivers. The OMEGA experiments at the smaller scale verified the hypothesis that preheating the fuel plays a significant role in introducing wall contaminants that mix into the fuel and significantly degrade fusion performance. This contamination not only impacts target performance but the optimal input conditions for the target. However, analysis at the Z-scale showed that target performance at high preheat levels is limited by the Nernst effect, which advects magnetic flux from the hot spot, reducing magnetic insulation and consequently reduces the temperature of the fuel. The combination of MagLIF experiments at the disparate scales of OMEGA and Z along with a multiscale 3D simulation analysis has led to new insight into the physical mechanisms responsible for limiting target performance and provides important benchmarks to assess target scaling more generally for MIF schemes. Finally, in addition to the MagLIF related work, a semi-analytic model of liner driven Field Reversed Configuration (FRC) was developed that predicts the fusion gain for such systems. This model was also validated with 2D radiation magneto-hydrodynamic simulations and predicts that fusion gains of near unity could be driven by the Z machine.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Low Cost HIP Fabrication of Advanced Power Cycle Components and PM/Wrought Inconel 740H Weld Development (Final Technical Report)

The objective of this Phase 1 project is to demonstrate the feasibility of structures and components for advanced fossil energy power cycle by fusion welding powder metallurgy (PM) based near net shape (NNS) hot isostatic pressing (HIP) Nickel superalloy Inconel 740H (IN740H) components to wrought IN740H components. The outcome of the project includes a prototype pipe elbow demonstration of the NNS HIP process using IN740H powder, an initial assessment of IN740H PM/wrought weldability, and a manufacturing and capital cost analysis of IN740H NNS HIP components for advanced ultra-super critical steam (AUSC) power plants. The anticipated value proposition of NNS HIP manufacturing is ~50% cost reduction of large complex components in AUSC or super-critical carbon dioxide (sCO2) power cycles. This document is a final technical report for the project, covering efforts conducted from October 2019 to June 2021.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Developing and Testing a Novel Stochastic Ice Microphysics Parameterization for Cloud and Climate Models Using ARM Field Campaign Data (Final Progress Report)

The major goals of this project were: 1) to use field campaign measurements from DOE’s Atmospheric Radiation Measurement (ARM) program to characterize variability of important parameters describing properties of ice particles in the atmosphere; 2) based on this observational analysis, to develop a parameterization scheme for weather and climate models that stochastically varies these parameters, and implement the new scheme into a weather model called the Weather Research and Forecasting model (WRF); 3) to use WRF coupled with the new stochastic scheme to simulate ARM field campaign thunderstorm cases and analyze how accounting for this parameter variability affects the model simulations. This work was performed jointly between the National Center for Atmospheric Research, University of Oklahoma, and University of Utah. To accomplish these goals, we extended an approach previously developed to characterize the variability in the size distribution of ice particles to parameters that are explicitly represented in models (i.e., relationships between ice particle mass and size, and between particle fall velocity and size). Our project was, to our knowledge, the first to apply observationally-constrained estimates of this parameter variability describing mass-size and fall velocity-size in a modeling framework. Our results showed efficacy of the approach, evaluated using ARM observations. Similarly, to our knowledge, work in this project was the first to propose and evaluate in detail a stochastic approach for unresolved turbulent mixing in high-resolution model simulations against detailed, benchmark large eddy simulations and ARM observations. Results showed some promising behavior, particularly with increased mixing and dilution of air in thunderstorm cores with surrounding environmental air, bringing the stochastic simulations closer to the benchmark large eddy simulations; however, results were somewhat degraded using stochastic mixing compared to observations from the AMIE/DYNAMO field campaign. This project also further refined and applied a modeling methodology called “piggybacking” that can robustly separate dynamical and thermodynamic impacts of model changes, and comparison studies of different models based on cases developed from ARM observations. Finally, this project directly supported three graduate students who completed their PhDs as well as a postdoctoral research fellow.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Memo regarding the Final Review of FY21 ASC L2 Milestone 7840: Neural Mini-Apps for Future Heterogeneous HPC Systems

The final review for the FY21 Advanced Simulation and Computing (ASC) Computational Systems and Software Environments (CSSE) L2 Milestone #7840 was conducted on August 25th, 2021 at Sandia National Laboratories in Albuquerque, New Mexico. The review committee/panel unanimously agreed that the milestone has been successfully completed, exceeding expectations on several of the key deliverables.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Development and implementation of an in situ high-resolution isotopic microscope for measuring metabolic interactions in soil mesocosms (Final Report)

Many of our planet’s ecosystems rely on the activities of soil microbial communities. These microbes have significant and wide-ranging effects: they metabolize carbon and other nutrients, interact with plants and fungi, and perform other processes important to soil health. However, our ability to directly observe the enzymatic and metabolic activities of microbes within soil is currently limited, not only by the complexity of soil microbial communities themselves, but also by the lack of experimental tools to study them and their molecular interactions in situ. These challenges hinder our understanding of the lifesustaining processes of biomass decomposition and the manner in which it contributes to the movement of freed carbon within soil ecosystems. Here we aim to develop a novel ultrahigh-resolution isotopic microscope that combines complementary imaging modalities to gain insights into metabolic cycling in soil. This final report covers the portion of this work that was completed at the University of North Carolina at Chapel Hill from 2018 to 2019; the research is continuing through 2022 at the University of Massachusetts Chan Medical School.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

FY21 NNSA-IAEC Science Area V, Environmental ISR, Waste Management and Subsurface Science (Final Report)

The FY21 NNSA NA-22 Final Report represents the progress achieved over the past year (FY21) by the research team for Topic Area 3, Waste Management & Subsurface Science (WM3), and Topic Area 7, Radiation and Thermal Effects on Bituminous Rocks (WM7). WM3 and WM7 are part of Science Area V (Subsurface Science and Waste Management) in the NNSA-IAEC Science and Technology Working Group. The project was initiated four years ago (2017) with an MOU agreement between the U.S. National Nuclear Security Administration (NNSA) and the Israel Atomic Energy Commission (IAEC) to evaluate the feasibility of geological subsurface disposal of radioactive waste in Israel. The core WM3 and WM7 teams are comprised of scientists and engineers from Los Alamos National Laboratory, the Geologic Survey of Israel (GSI), and the Nuclear Research Center - Negev (NRCN), with a close collaboration to the teams from Sandia National Laboratory (SNL) and Lawrence Livermore Laboratory (LLNL)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Atrial Model Development and Prototype Simulations; Final Report for CRADA No. TC02224.0

This project was a collaborative effort between Lawrence Livermore National Security, LLC as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Amgen, Inc. ("Amgen"), to develop a capability to computationally evaluate the importance and roles of different ion channels in atrial fibrillation. The first phase of this collaboration was to implement the atrial model, run prototype simulations, and analyze the results. Two No-Cost Time Extension (NCTE) requests were executed for this project. The first NCTE was executed on April 1, 2016, and extended the CRADA project for an additional two months to allow enough time to complete the tasks and deliverables, due to a delay in the start of the project. A second NCTE was executed on June 28, 2016, extending the project by three months, through November 3, 2016, to allow enough time to complete the final tasks and deliverables as well as negotiate a CRADA extension. The actual duration of this project was fourteen months. Amgen was unable to obtain budget approval to extend the CRADA past November 3, 2016. All of the deliverables for this CRADA project were successfully completed according to schedule.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Development of Resources and Tools to Improve Oil Content and Quality in Pennycress (Final Report)

This is the final report for the project entitled "Development of Resources and Tools to Improve Oil Content and Quality in Pennycress". The project focused on three main aspects: 1) Investigate pennycress natural variation to identify candidate genes and biomarkers associated with oil accumulation and fatty acid composition. 2) Identify targets to improve oil content and composition. 3) Establish metabolic engineering targets and develop community resources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

GMLC 1.5.03: Increasing Distribution System Resiliency using Flexible DER and Microgrid Assets Enabled by OpenFMB (Duke-RDS Final Report)

This is the final project report for the Grid Modernization Laboratory Consortium (GMLC) Resilient Distribution System (RDS) project titled “Increasing Distribution System Resiliency using Flexible DER and Microgrid Assets Enabled by OpenFMB”. The primary goal of this project was to increase the resiliency of distribution systems at utilities around the nation by deploying flexible operating strategies that engage end-use assets as a resource.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

High-dimensional Data-driven Energy optimization for Multi-Modal Transit Agencies (HD-EMMA) (Final Technical Report)

Public bus transit services in the U.S. are responsible for at least 19.7 million metric tons of CO 2 emission annually. Electric vehicles (EVs) can have a much lower environmental impact than comparable internal combustion engine vehicles (ICEVs), especially in urban areas. Unfortunately, EVs are also much more expensive than ICEVs. As a result, many public transit agencies can afford only mixed fleets of transit vehicles, consisting of EVs, hybrids (HEVs), and ICEVs. Transit agencies that operate such mixed fleets of vehicles face a challenging optimization problem: these agencies need to decide which vehicles are assigned to serving which transit trips. Since the advantage of EVs over ICEVs varies depending on the route and time of day (e.g., the benefit of EVs is higher in slower traffic with frequent stops and lower on highways), the assignment can have a significant effect on energy use and, hence, environmental impact. Through this project, we have developed reference data about energy collections and constructed a set of machine learning models that can accurately predict the energy consumption for the whole fleet at the level of each trip. We have used these models to develop a scheduling and assignment strategy that can rotate the different vehicle types across the transit agencies’ routes. The optimization algorithm ensures that the vehicles are matched to trips considering weather patterns, expected congestion, and road gradients to minimize the overall energy usage. We list the key observations from our project for other practitioners below. Details are available in the report, and the list of source code and our publications are included in the appendix. 1. We have demonstrated the feasibility of collecting, merging and analyzing large volumes of high-resolution real-world telemetry data from a mixed vehicle fleet. To mitigate the inherent noise of the recorded GPS points, the team developed an algorithm that filters data and maps the points onto a street. The algorithm considers previous and subsequent location measurements and different characteristics of nearby streets to determine how likely the vehicle travels on them. Then, the team segmented the time series into disjoint contiguous samples based on adjacent road segments and repeated the outlier detection and removal. For each data point, the team added features corresponding to elevation changes within the samples, weather features, such as temperature, and traffic data, such as speed ratio between actual speed and free-flow speed. 2. We have developed two forms of machine learning models that be used to understand and analyze the energy operations of a mixed vehicle transit fleet. The micro prediction model provides estimates of instantaneous energy prediction for all types of buses (diesel, hybrid, and electric). Such a model is important in evaluating the energy impacts of real-time bus operation strategies, but it is challenging due to diversified driving cycles of transit buses. The model can help the drivers understand the impact of their driving behaviors and short-term congestions. The macro prediction models estimate average energy consumption across the whole trip considering the features: distance traveled, various road-type features, elevation change, day of the week, time of day, various weather features (temperature, humidity, etc.), and traffic features (speed ratio and jam factor). 3. We have demonstrated that it is possible to transfer the machine learning models we have developed in this project to other teams and cities by using inductive transfer learning. We also showed that the performance of the macro energy prediction models can be improved using a multi-task learning approach where the learning parameters are shared between the models being developed for different vehicle types. The advantage of this approach is improved learning performance as the models can exploit common spatio-temporal and environmental characteristics. 4. Finally, we have developed trip and vehicle assignment and scheduling algorithms that use the energy prediction models and develop a trip to vehicle type (diesel, electric, hybrid) assignment for the whole operation to reduce overall emissions and cost. We have shown through simulations that the proposed algorithms can save $\$$ 48,910 in energy costs and 175 metric tons of CO 2 emission annually for CARTA.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Pushing the efficiency limit of low-cost, industrially relevant Si solar cells to > 22.5% by advancing cell structures and technology innovations (Final Report)

The overall objective of this program is to achieve ~23% bifacial n-type cell efficiencies by developing and implementing optimized homogeneous or selective boron (B) emitter on front and tunnel oxide passivated contact (TOPCon) on rear side, in combination with advanced fine-line screen-printing metallization with floating busbars. During this research project, first we developed a technology roadmap to drive the 21% n-PERT cell efficiency from 21% to 23% by transforming the cell design to n-TOPCon and establishing the requirements for each layer, including B emitter, rear n-TOPCon, n-base Si and screen-printed contacts. Next, consistent with our roadmap, we developed advanced homogeneous implanted B emitter (150-180 Ω/⌫) passivated with ALD Al 2 O 3 layer capped with PECVD SiN x /SiO x double-layer antireflection coating This gave a very low recombination current density of 10-15 fA/cm 2 prior to metallization. In addition, we demonstrated metallized recombination current density of ~31 fA/cm 2 for this advanced homogeneous B emitter with industrial screen-printed, fire-through contacts with 40 μm wide grid lines, floating busbars and implementation of an advanced Ag-Al paste which resulted in local or reduced area metal-Si contact under the grid lines with virtually no emitter surface etching. This paste reduced the full area metallized J oe,metal from >1100 fA/cm 2 to ~700 fA/cm 2 . We also developed novel processes for the formation of p + /p ++ selective B emitter by a) single B diffusion with selective etch back and b) two-steps diffusion with implanted B in field region and APCVD B diffusion under the metal grid. We achieved very low un-metallized recombination current density (J 0 ) of ~18 fA/cm 2 for the selective p ++ p + emitters (30/150 Ω/⌫) and metallized J 0 of ~28 fA/cm 2 with ~3% screen-printed metal contact to p ++ regions. Next, we developed the technology for n-TOPCon by growing phosphorus-doped LPCVD and PECVD poly-Si on top of ~ 15Å chemically grown (NAO) tunnel oxide. After an optimized anneal at 875 °C for 30 min, passivated n-TOPCon have unmetallized J 0 of ~ 5 fA/cm 2 which went down further to ~ 1 fA/cm 2 after a 700 Å SiN x capping layer and simulated contact firing cycle at 770 °C. After screen-printed fire-through metallization on this n-TOPCon with ~13% metal coverage, metallized J 0 value increased to only ~5 fA/cm 2 which is among the lowest reported value to the best of our knowledge for screen-printed metallization. Finally, we integrated all the above technology innovations and enhancements and demonstrated low-cost manufacturable screen-printed n-TOPCon bifacial Si solar cell with ~23% efficiencies. Based on the experimental and theoretical understanding developed in this project, we have developed a new technology roadmap that shows that implementation of busbarless contacts, 10-20 ms bulk lifetime Si, and selective B emitter or selective TOPCon on the front can drive ~23% efficient cells achieved in this research to ~25% at low-cost.

14 SOLAR ENERGY↗
DOE OSTI2021

Big Adaptive Rotor Phase I (Final Report)

The Big Adaptive Rotor (BAR) project was initiate by DOE in 2018 with the goal of identifying novel technologies that can enable large (>100m) blades for low specific power (SP) turbines. Five distinct tasks were completed to achieve this goal: 1. Assess trends, impacts, and value of low-SP turbines, 2. Wind turbine blade cost reduction roadmap study, 3. Research and Development (R&D) opportunity screening, 4. Detailed design and analysis, and 5. Low-cost carbon fiber. These tasks were completed by the national lab team consisting of Sandia National Laboratories (SNL), the National Renewable Energy Laboratory (NREL), and Lawrence Berkeley National Laboratory (LBNL). The objective of Task 1 was to assess the historical trends of low-SP of onshore deployments, and to assess the impact and value of low-SP turbines. Analysis under this task showed that there is significant value for low-SP turbines, especially in markets where there is a higher saturation of wind energy on the grid. This has to do with the fact that low-SP turbines have increased capacity factors, and can contribute more reliable energy to the grid, even in lower wind conditions. This bodes well as higher renewable scenarios are likely in the coming years. Task 2 was a detailed analysis on the logistical challenges of deploying very large (>100m) onshore blade. This work was completed by experts at DNV-GL. The report looked at various ways to get around the current transportation constraints which are estimated to be around 75m in length. The report concluded that there are viable solutions to this issue including: segmented blades (which the industry is already pursuing), lighter than air (LTA) transportation, on-site manufacturing, and controlled bending of blades on rail. The final option was recommended for further analysis and study by DOE and the national labs because keeping a single piece blade reduces manufacturing and operations and maintenance (O&M) costs. Task 3 focused on identifying novel concepts that are capable of enabling a cost effective 5MW 206m rotor for onshore deployment. The findings from the first two tasks were considered in the analysis, in that the concepts identified must be able to overcome the transportation logistics challenges. Around 20 concepts were identified and evaluated by experts within the industry. Additionally, science and engineering challenges were identified for each concept. Based on these evaluations six concepts were deemed the most impactful and were selected for further analysis in Task 4. The concepts were: highly flexible rail transportable blades, downwind rotors, distributed aerodynamic control (DAC) devices, inflatable blade, bi-wing blade, and 4/5 bladed rotors. Task 4 conducted detailed design, optimization, and analysis on the selected BAR concepts. A modeling gaps analysis was conducted, and modeling improvements were implemented that allowed for the study and design of the novel concepts. The BAR team established a set of baseline designs by which to compare the selected designs through a technoeconomic analysis. It was found that the highly flexible rail transportable blade, the downwind rotor, and the DAC devices have the most promise to deliver the BAR targets. A Phase II for BAR has been proposed to further mature these concepts and address the open science and engineering challenges identified in Task 3. Task 5 conducted research on optimized carbon fiber materials that were used throughout the BAR Phase I project. Overall, the BAR project has identified low-SP turbines as important to continued LCOE reductions for onshore turbines. Furthermore, the project has identified viable solutions to the technical and logistical challenges to realizing these goals. The most promising technologies that were identified in Phase I of the project will be further matured and de-risked in Phase II of the BAR project.

17 WIND ENERGY↗
DOE OSTI2021

Exploring Novel Technologies for Particle Tracking in Gas TPCs (Final Technical Report)

This report provides the final results from R&D on a novel 2D readout for a time projection chamber (TPC), which operates with negative-ion drift. The readout consists of two gas electron multiplier (GEM) devices places at an angle with respect to each other. The 2D range of particles interacting in the TPC is reconstructed using pulse-shape timing only. Due to the low diffusion and drift speeds of the negative-ions carrying the track information to the anode, the track resolution is <200 microns. Acquiring this level of resolution for short, low energy particle tracks in a standard TPC would require a fine granularity strip or pixel readout with many 1000s of electronic channels. With this novel readout, only two channels are needed. Our results showed that the concept is fundamentally sound. We found a number of issues related to how well the timing signals are determined from the pulse waveforms. Solutions for these had to be left for future R&D.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Final Science Report of the Joint Center for Artificial Photosynthesis (JCAP)

The Joint Center for Artificial Photosynthesis (JCAP) was designated as the U.S. Department of Energy (DOE) Fuels from Sunlight Energy Innovation Hub on July 22, 2010, and began operations according to a cooperative agreement between the DOE and the California Institute of Technology on September 30, 2010. The cooperative agreement was renewed on September 30, 2015. This final science report outlines JCAP research activities from September 30, 2010 to September 30, 2021.

08 HYDROGEN↗
DOE OSTI2021

DOE Plasma Science Center - Predictive Control of Plasma Kinetics: Multi-Phase and Bounded Systems (Final Report DE-SC0001939)

Low temperature plasmas (LTPs) are the plasmas of electron-volt (eV) physics and eV technologies. LTPs have characteristic electron temperatures of a few eV and fractional ionizations that are typically small. Since LTPs have electron temperatures commensurate with the threshold energies of excited states in neutral atoms and molecules, power transfer from electrons to these atoms and molecules efficiently produces activated species (e.g., radicals, excited states, photons). Acceleration of ions in the sheaths of LTPs to energies of tens to hundreds of eV enable activation of surface modifying processes – sputtering, etching, deposition. With such properties, LTPs are often and beneficially used in technological devices, ranging from etching and deposition in microelectronics and solar cell fabrication, to hardening of surgical instruments. LTPs harbor fundamental science issues that are intellectually challenging and rewarding. At the same time, there are enormous societal benefits that are enabled by LTPs. The entire present-day and future information technology infrastructure owes its very existence to LTPs. Renewable energy sources, such as solar cell arrays, could not be economically produced in the absence of deposition and etching by LTPs. In acknowledgment of the importance of LTPs, the DOE Office of Fusion Energy Sciences supported the Plasma Science Center for Predictive Control of Plasma Kinetics: Multi-Phase and Bounded Systems from August 2009 to July 2021, consisting of an initial 5-year grant, 3 funded extensions and 2 no-cost extensions. This is the final report of the Center in which the productivity of the Center is discussed in terms of publications, impact and personnel. High-lights of the research performed in the Center are provided.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Precision Electroweak and QCD Studies with Polarized Electrons (Final Technical Report)

In this final technical report, we report on the main products from the scope of the work of the award, in particular the Ph.D. dissertations that summarize the work done by the three graduate students who completed their requirements and defenses during calendar 2021, after completing data analyses on the PREX-II and CREX experiments which made precision measurements of neutron RMS radii of 208 Pb and 48 Ca nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗