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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 253 records · Page 14

Fundamental Investigations of Mechanical and Chemical Degradation Mechanisms in Lithium Ion Battery Materials (Final Technical Report)

The objective of our effort under the DOE EPSCoR Implementation grant is to establish a comprehensive and internationally recognized research program at Brown University and University of Rhode Island in understanding degradation mechanisms and to improve the cycle and calendar life of lithium ion battery (LIB) materials. A series of basic investigations are undertaken to characterize the mechanical and chemical degradation mechanisms, which can help enable new higher capacity and longer lasting electrode designs. Controlling mechanical and chemical degradation is the primary challenge in developing the next generation of higher energy density batteries. The development of failure resistant battery microstructures will require a fundamental understanding of the evolution of stress, deformation, damage, and electrochemistry in battery materials during cyclic charging and discharging. In addition, controlling the reactions at the electrode/electrolyte interface is critical for the formation of a stable SEI layer. We address these issues through a combination of controlled experiments on model battery materials and practical composite electrodes, together with multi-scale computations. Our effort is organized into three focus areas that encompass many critical challenges in Lithium Ion Battery Technologies: (i) Mechanical properties, fracture and damage in electrode materials; (ii) Chemistry and Mechanics of Solid Electrolyte Interphase (SEI); (iii) Mechanical and Chemical Integrity of Solid-Solid Interfaces in Practical Electrodes.

25 ENERGY STORAGE↗

Offshore Wind Project Study (Final Technical Report)

Within the Long Island electric service territory and throughout New York State there is increasing interest in and mandate for increasing clean energy technologies and renewable energy generation while reducing dependency on fossil fuels for electric production with goal of a carbon free system by 2040. This report discusses the implications of the reduction of forecasted load in the Long Island electric service territory and the impact of energy efficiency; increasing reliance of wind and other renewable resources on the transmission system; opportunities for interconnecting these resources; and reductions on the reliance of baseload fossil fueled power facilities over the coming years.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Collider Physics (Final Technical Report)

The UNM members of the ATLAS Collaboration published a comprehensive study of ATLAS Pixel leakage current recorded from the beginning of Run 1 through the end of Run 2. This study depended upon a hardware system that was designed and built by UNM and installed by us in the ATLAS cavern. The study compared ATLAS data to predictions by the Hamburg Model, thereby leveraging ATLAS data to improve a widely used simulation that has application to other LHC experiments as well as silicon systems in radiation environments outside HEP applications. Having validated the model in this way, we then used it to make predictions for ATLAS tracker design and operational conditions in Run 3 and beyond.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Using Behavioral Science to Target LMI and High-Value Solar Installations (Final Technical Report)

This project is a data-driven analysis of approaches to facilitate solar adoption in LMI communities and areas with high potential benefits to the electric grid. The cornerstone of the project was two waves of randomized field experiments. The first wave involved novel approaches to reaching LMI communities based on insights from literature. The second wave involved areas of high potential of solar to the electricity grid, as determined in collaboration with the local utilities in Connecticut. Both waves were followed by surveys to develop insight into the effectiveness of different approaches. A third key element of the project is the development of new agent-based models of solar energy diffusion that explicitly incorporate the real spatial and temporal constraints that influence solar diffusion, based on real-world data on solar adoption. The project also involved outreach and dissemination of key findings to relevant stakeholders, including a guidebook on strategies to accelerate solar deployment to low and moderate income communities, multiple academic publications, and numerous presentations of the research findings.

14 SOLAR ENERGY↗

In situ Diagnostics of Coupled Electrochemical-Mechanical Properties of Solid Electrolyte Interphases on Lithium Metal Rechargeable Batteries (Final Technical Report)

The fundamental understanding of the coupled mechanical/chemical degradation of the SEI layer during lithium cycling will enable the project to identify the desirable mechanical properties on SEI/lithium as a system and the specific transport properties that enable the homogenous lithium stripping/plating while avoiding the mossy structure. Furthermore, it will allow the project to develop a highly impactful strategy to protect lithium metal and achieve dendrite free high cycle efficiency, which can dramatically increase the energy density of lithium batteries for EV applications. During past three years, four coherent steps have been taken to solve the coupled mechanical and electrochemical degradation: (1) Developed a comprehensive set of in-situ diagnostic techniques to investigate the coupled mechanical/chemical properties of SEI layer and its impact on lithium striping/plating. (2) Identified failure mechanisms of SEI/Li as a whole electrode system using in-situ electrochemical tools. (3) Established a design strategy of protective coatings on Li metal to extend the cycle life Li meal electrode. (4) Developed novel surface coatings as the artificial SEI layer to protect Li metal and significantly extend cycle life. During past 3-year budget period, we have published over 16 peer-reviewed paper, filed 7 patents, and given over 30 invited talks. 5 graduated students and 2 postdocs were supported by this project.

36 MATERIALS SCIENCE↗

Platform for efficient large-scale storage and analysis of multi-omics data in plant and microbial systems (Final Technical Report)

Genomic variation at the sequence level fundamentally affects the phenotypic state of all organisms at all stages of development, while dynamic processes such as changes in the epigenome (e.g. DNA methylation state) and transcriptome regulate the specific phenotype expressed at any given state of development based upon that genomic variation. In plants, DNA methylation is a particularly important mechanism for both regulating transcriptomic expression and for management of genomic variations that could be deleterious to the organism due to the presence of active retrotransposons in plant genomes. While DNA methylation is heritable, it is also dynamic through a given plant’s development and life cycle, particularly during the development from seed to mature specimen suggesting variations in DNA methylation could be critical regulators of biologically and commercially important phenotypes such as time to flowering; in addition, plant DNA methylation is more complex than that of animals, with methylation of CHG and CHH trinucleotides evident in addition to the better-known CG methylation. The complexity of plant DNA methylation and its interplay with genomic sequence variation, transcriptomics and other epigenomic factors demand a storage and analysis framework that can cope with the complexity both within a single specimen and with analyses that span many individuals and even many species, such as attempts to extend models from model organisms to commercially relevant species. In addition to complexity, the rapid development and proliferation of sequencing technology has led to an explosion of data volume that conventional storage and analysis solutions will likely be unable to cope with in the long run. We proposed to study these with suitable distributed storage and computation and therefore for the application of cloud computing to biological analyses; integrate with existing data sources and compatible with virtually any interface use case, from fully automated shell scripts to notebooks and do all these at scale in this STTR grant.

60 APPLIED LIFE SCIENCES↗

Minnesota Solar Pathways: Illuminating Pathways to 10% Solar (Final Technical Report)

The Minnesota Solar Pathways project, funded in part by the Department of Energy’s Solar Energy Technologies Office, was a three-year project designed to explore least-risk, best-value strategies for meeting the State of Minnesota’s solar goals. As part of this aim, the Pathways Team modeled renewable generation costs, examined ways to streamline interconnection, and evaluated technologies that can increase solar hosting capacity on the distribution grid. Midway through the project period, the Pathways Team expanded the scope of study using the same modeling framework from the Minnesota Solar Potential Analysis to estimate and compare generation costs for high renewables penetration scenarios across the Midcontinent Independent System Operator (MISO) region. The analysis concludes that it can be cheaper to overbuild solar + wind and curtail surplus than to store all generation. In addition, the analysis of individual MISO subregions compared with the whole region highlights the opportunities of enabling market potential compared with impact of ongoing transmission constraints. Beyond the analysis of future scenarios, the partnerships initiated and supported through this project underscored the ongoing need for work with stakeholders to address key issues, particularly around siting, and leverage symbiotic strategies to meet state goals.

14 SOLAR ENERGY↗

Parsimonious Inference Information-Theoretic Foundations for a Complete Theory of Machine Learning (CIS-LDRD Project 218313 Final Technical Report)

This work examines how we may cast machine learning within a complete Bayesian framework to quantify and suppress explanatory complexity from first principles. Our investigation into both the philosophy and mathematics of rational belief leads us to emphasize the critical role of Bayesian inference in learning well-justified predictions within a rigorous and complete extended logic. The Bayesian framework allows us to coherently account for evidence in the learned plausibility of potential explanations. As an extended logic, the Bayesian paradigm regards probability as a notion of degrees of truth. In order to satisfy critical properties of probability as a coherent measure, as well as maintain consistency with binary propositional logic, we arrive at Bayes' Theorem as the only justifiable mechanism to update our beliefs to account for empiracle evidence. Yet, in the machine learning paradigm, where explanations are unconstrained algorithmic abstractions, we arrive at a critical challenge: Bayesian inference requires prior belief. Conventional approaches fail to yield a consistent framework in which we could compare prior plausibility among the infinities of potential choices in learning architectures. The difficulty of articulating well-justified prior belief over abstract models is the provinence of memorization in traditional machine learning training practices. This becomes exceptionally problematic in the context of limited datasets, when we wish to learn justifiable predictions from only a small amount of data.

97 MATHEMATICS AND COMPUTING↗

World Congress on High Entropy Alloys (HEA 2019) (Final Technical Report)

The World Congress on High Entropy Alloys (HEA 2019) was a new, cross-disciplinary technical forum designed to share the latest research advances in materials with high configurational entropy, including both single-phase and multiphase (compositionally complex) alloys. This inaugural World Congress on High Entropy Alloys (HEA 2019) was held in Seattle, Washington from November 17-20, 2019 with the goal of HEA 2019 to assemble the international community of HEA stakeholders – including researchers, educators, and engineers – to capture the current state-of-the-art, identify current gaps in HEA efforts, and to set the stage for the future growth and application of HEAs worldwide. HEA 2019 was the environment for leaders in this field to showcase their researc, and network with their peers to informally discuss the latest developments in high entropy alloys, while also making valuable professional connections. The goal of the organizers was to ensure a high-quality conference that held a strong international presence and aimed to highlight the important advances in HEA research on a global scale. Student participation was greatly encouraged in order to give students exposure to recent advances in this field. This meeting was open to all interested individuals and attempted to provide the most advanced technical meeting possible, with a mixture of attendees from research and development, industry, and education.

36 MATERIALS SCIENCE↗

Development of Improved Noble Liquid Purity Measurements (Final Technical Report)

The main goal of the Detector R&D project supported by this grant, “Development of Improved Noble Liquid Purity Measurements”, was to perform a scoping study of the feasibility of trapping ions in a liquid argon medium using a radiofrequency (RF) quadrupole trap, and to subsequently use the population of trapped ions to make measurements of the properties of the liquid medium. Using RF quadrupole traps immersed in a noble liquid to trap ions may yield new capabilities to detect and quantify the presence of impurities, as well as enabling other measurements of the microphysics in a noble liquid environment. The major activities undertaken during this project include: the development of a simulation of ions in a liquid argon medium; the designing of a prototype RF quadrupole trap; and the setup of hardware to be used in testing the prototype in vacuum and gas conditions. The summary of these major activities is reported here.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Spectroscopy of Resonances in the Astrophysical r p –Process Path. Final Technical report

This report describes the results of a project to study the spectrum of proton-resonances which determine the energy release and timescale for the astrophysical rp-process path. Steps to achieve successful experiments include the commissioning of a the in-flight radioactive-beam facility RESOLUT , development of instrumentation and analysis techniques for experiments performed with it. Radioactive-beam experiments performed in the context of the grant included the reactions 25 Al(d,n) 26 Si, 19 O(d,p) 20 O, 19 Ne(d,n) 20 Na and 17 F(d,n) 18 Ne. The experimental program developed experiments and methods to characterize aspects of proton-capture reactions with respect to the in the context of the astrophysical rp-process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Confronting Dark Matter with the Multiwavelength Sky (Final Technical Report)

The existence of dark matter is a key clue to new fundamental physics, yet its nature and non-gravitational interactions remain mysterious. In the course of this five-year project (spanning July 2015 - July 2020), we have developed novel analysis techniques to separate dark matter signals from astrophysical backgrounds in the inner Galaxy, and measured hitherto-unknown properties of the Fermi Bubbles and the Galactic Center excess in gamma-rays from the inner Milky Way. We have improved predictions for the spatial distribution and energy spectra of photon signals from dark matter, and set new limits from astrophysical and cosmological datasets on dark matter inhabiting complex dark sectors, multi-particle dark matter annihilation, and tiny primordial black holes. We have successfully adapted effective field theory techniques from collider physics to make high-precision predictions for signals from heavy weakly-interacting DM, allowing us to essentially exclude the possibility that DM is a thermal wino, and have discovered novel theoretical and observational implications for dark matter bound states and self-interactions. We have developed a comprehensive public code package for modeling the effects of exotic energy injections, such as from dark matter annihilation and decay, on the ionization and temperature history of the early cosmos, and have used these tools to set robust, powerful and broadly-applicable constraints on models of light dark matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A Multi-Instrument Cloud Condensation Nuclei Spectrum Product (Final Technical Report)

A wealth of observational data exists on the characteristics of atmospheric particulate matter, over multiple years, at the DOE ARM Southern Great Plains (SGP) Central Facility site. This site is located in a region of the country that frequently experiences weather extremes, and that is removed from many local sources of pollution but is affected by transported smoke, dust, and urban emissions. The relationships between particulate matter, cloud formation and evolution, and precipitation are therefore of strong interest, and are being explored via modeling on a variety of scales. These models require as input detailed information on the characteristics of particles capable of serving as the nuclei for cloud formation. Sufficient data exist to be able to put together a picture of the nature of the total aerosol and the cloud condensation nuclei (CCN) subset, and their variability, through merged data products. This study was aimed at exploiting the multiple measurement types at SGP to develop the first such multi-year estimates. Further, the resulting data were analyzed to understand temporal patterns ranging from hourly to seasonal, thereby gaining insights into the particle sources affecting the atmosphere in this region. DOE-funded datasets that were analyzed in this study include total particle number concentrations, submicron aerosol scattering coefficients, dry aerosol size distributions, and more recently, time-resolved submicron aerosol chemical composition. Data are also available for the number concentrations of particles that are activated in a cloud condensation nucleus instrument at a series of setpoint supersaturations, providing direct observations of the number concentrations of “CCN”. This variable is the quantity that is generally desired for inclusion in numerical models that seek to represent and predict the impacts of varying aerosol characteristics on the formation and microphysical properties of clouds. One limitation of the use of direct CCN observations is that they are not available for supersaturations larger than about 1%, which is insufficient for deep convection and may be insufficient even for shallow convection, depending on the nature of the available CCN and the dynamics of the cloud. We developed a data-based approach to representing the full aerosol size spectrum with size-dependent hygroscopicity, and used this to extrapolate CCN spectra beyond the limited measurements. Five years of SGP aerosol data (2009 -2013) were analyzed. As a side product of our work, we identified and communicated several previously-unflagged data quality issues. The resulting merged aerosol distributions, along with fits for seasonal averages, were published and submitted to the ARM archive as a special value-added product (VAP; submitted as a PI product). CCN spectra were computed for the same data period and will similarly be published and submitted to the archive for use by the community. We also note that our methodologies and findings have been discussed at several Joint ARM User Facility/Atmospheric System Research (ASR) Principal Investigators Meetings and that recent ARM/ASR aerosol data reporting strategies have included similar ideas for data merging, indicating that this work has had a lasting impact on ARM aerosol data acquisition and reporting. The proposed work advances the science of the interactions of aerosols, clouds and precipitation, with direct application to improve representation of such interactions for clouds in regional and global climate models. The archived data will continue to serve research studies in the future.

54 ENVIRONMENTAL SCIENCES↗

Methanotrophic-Mediated Methylmercury Transformation: Characterization of Products, Mechanism, and Environmental Significance (Final Technical Report)

Previous work in the laboratories of the PIs found that methanotrophs, through the production of a novel metal chelator called methanobactin (MB), can bind inorganic mercury (Hg[II]). By doing so, methanotrophs substantially reduce Hg[II] toxicity. We have also recently shown that MB can bind a much more toxic form of mercury, the neurotoxin methylmercury (MeHg). MeHg bioaccumulates and biomagnifies in biota such as fish, and is of significant concern. Further, certain methanotrophs expressing MB are able to demethylate significant amounts of MeHg despite lacking merB, the organomercurial lyase. Further, unlike the canonical organomercurial lyase, methanotrophs take up and degrade MeHg at environmentally relevant pH and Hg concentrations (i.e., picomolar to nanomolar), suggesting that methanotrophs likely play a critical role in controlling net MeHg production and toxicity in situ. However, although MB is necessary for methanotrophic-mediated MeHg degradation, it is not sufficient as purified MB binds, but does not degrade MeHg. That is, MB appears to serve as binding device leading to demethylation of MeHg by an as yet unknown mechanism. The major goals of this project were to extend this initial work and characterize the mechanism of methanotrophic-mediated MeHg demethylation and how methanobactin production may affect net methylmercury production in situ.

54 ENVIRONMENTAL SCIENCES↗

Charged Microdroplets in Air: Characterization and Use in Surface Functionalization and Nanomaterials Preparation (Final Technical Report)

The major theme of this project is the exploration of ions and charged droplets in the open air. The specific goals are (1) focusing ions in the open air, (2) separating and measuring the sizes of charged droplets, (3) examining chemical reactions occurring within droplets, (4) examining chemical reactions occurring between charged droplets and chemical vapors, and (5) characterizing surfaces post droplet deposition. The analysis of ions in the open air greatly simplifies instrumentation as it removes the need for large, costly vacuum pumps. Major strides in this project include the sizing of electrospray droplets using structured illumination microscopy, 3D printed drift tube ion mobility (both standalone and coupled with mass spectrometry), and accelerated Suzuki reactions in Leidenfrost droplets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nanostructures for Electrical Energy Storage (NEES) (2020 Final Technical Report)

Nanostructures for Electrical Energy Storage (NEES, www.efrc.umd.edu) was an Energy Frontier Research Center supported by the DOE Office of Science, Basic Energy Sciences, from 8/1/2009 to 7/31/2020. Led by the University of Maryland, NEES enjoyed extensive collaborations with its funded partners, including two DOE Laboratories and six universities. The NEES vision has been to reveal a set of scientific insights and design principles that can underpin a next-generation electrical energy storage approach, building on advances in nanoscale science and technology to achieve simultaneous high power and high energy over extended charge/discharge cycling. The vision is motivated by the recognition that scaling into the nano regime opens the door to new physical phenomena and that the tools enlisted in nanoscale research provide major new opportunities for the synthesis not only of materials at molecular scale but for structures at nano scale and above. NEES has translated this vision into its research program based on two observations. First, while the behavior of ions and electrons in electrolytes and in electrode materials is crucial to electrical energy storage (or more appropriately electrochemical energy storage), it is the transport of ion and electron charge between different structural components of a storage device that ultimately determine its performance. With it well recognized that the choice of electrode materials typically constrain ion transport kinetics as well as maximum ion concentration, the search for better electrode materials has been a primary driver of battery research. At the same time the synthesis of electrodes is typically based on aggregation of particles with varying size, shape, and orientation in the electrode. Together with the presence of additional materials to impart electrical conductivity and cohesion to the composite electrode, change in electrode materials is necessarily accompanied by structural changes at the nano/micro scale that are difficult to categorize and manage. From the beginning, NEES’ vision has been to create and study simpler, highly controlled spatial arrangements of known materials as battery components (electrodes, current collectors, and electrolyte) and to understand how design and structure above the molecular scale determines the energy storage performance available from known materials. Second, advances in nanoscience dramatically expanded the portfolio of synthesis methods, structural motifs, and new phenomena available for research. Some of these gave rapid access to new building blocks at the deep nanoscale (e.g., carbon nanotubes grown by self-assembly, nanoscale arrays formed by electrochemical self-alignment, monolayer films controlled by self-limiting reaction). Such advances served as the enabler for the NEES vision to be pursued experimentally through study of 3D structures created and controlled at the nano, micro, and meso scales. Here, we use meso as in the BES MESO Report, implying not only intermediate or varying length scales, but very much the way behavior is influenced by other factors including aggregation of nanocomponents at different densities and spatial configurations, statistical variations in the aggregates, hierarchical architectures in which they can be assembled, or local 3D configurations that result from the architectures. Over its life cycle, NEES has pursued two overarching goals: (1) to understand the scientific fundamentals of electrochemical storage from the nanoscale to the mesoscale; and (2) to create and learn from innovative, controlled, heterogeneous nanostructures, where such nanostructures can enable the first goal and serve as models for future paradigms in energy storage. Specific goals have included: Synthesize heterogeneous nanostructures comprised of multiple materials arranged in controlled fashion and characterize their behavior; Demonstrate and elucidate design principles for achieving simultaneous high power and high energy; Develop materials processes which enable precision control of thin layers and 3D structures; Investigate the impact of artificial interphases on electrode stability during ion insertion/deinsertion; Create dense arrays of nanostructures to understand how the architecture of these assemblies, along with nanostructure design, influences energy storage behavior at the mesoscale; Identify and understand the consequences of nanoconfinement and local inhomogeneities in 3D mesoscale arrays; Develop and apply computational models to stimulate, guide and interpret experiments.

25 ENERGY STORAGE↗

Direct Measurement of Mass-Temperature Distributions in the Core of Implosions on the National Ignition Facility (Full Technical Final Report)

Inertial confinement fusion plasmas are characterized by several kilo-electron-volt (keV) electron temperatures and ion and electron densities approaching 100 to 1000 times solid. In these implosions which simulate the dynamics of our sun, spectroscopic dopants can lead to detailed exploration of the plasma gradients that are not possible in other places. This is both in the central core pressure and temperature as well as any “mix” resultant from ablation and hydrodynamic interactions. This work will show new Bayesian atomic physics models applied to ICF plasmas to give both the temperature and density of the internal hot spot to better describe the physical nature of these implosions along with trying to spatially resolve the mix coming from the ablator region. The mission impact is to demonstrate this effect and to lead to a more quantitative description of mix in inertial confinement plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗