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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Cybersecurity for the Operational Technology Environment (CyOTE) (Final Technical Report)

Electric grids have historically been susceptible to both physical attacks and environmental hazards but the implementation of smart grids, remote management, and self-healing networks, has now made the grid vulnerable to cyber attacks. To address risks introduced by routable connectivity, utilities must establish dynamic solutions to identify, protect, detect, respond to, and recover from cyber security threats and vulnerabilities. In response to the evolving threat landscape U.S. Department of Energy-Office of Cybersecurity, Energy Security, and Emergency Response (DOE CESER) initiated the Cybersecurity for the OT Environment (CyOTE) pilot program, a U.S. Department of Energy (DOE) effort designed to leverage U.S. intelligence capabilities to prevent, detect, or mitigate a cyber attack on utility operational technology (OT) networks. As part of the CyOTE pilot, The Southern Company (Southern Company or Southern) researched, evaluated and deployed emerging Commercial off the Shelf (COTS) technologies and cyber security monitoring architectures to provide previously unrealized network visibility and situational awareness through deep packet inspection and data analytics. This Final Scientific/Technical Report documents the objectives, methodology, lessons learned, and results of Southern Company’s participation in the CyOTE pilot from December 2018 to September 2023.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Gen3 Gas Phase System Development and Demonstration (Final Technical Report)

Work undertaken in this project seeks to transform the current baseline technology – which is a collection of related but separately developed components and concepts – into a unified and operating test facility and an accompanying preliminary commercial design. This project is motivated by the primary goal of developing a system to absorb concentrated solar energy and deliver it into thermal energy storage at temperatures above 700°C, thereby enabling integration with a high-efficiency supercritical carbon dioxide (sCO 2 ) power cycle to achieve or exceed a levelized cost of electricity (LCOE) target of 6 ¢ per kilowatt-hour electric (kW e -hr). The proposed baseline solution utilizes a high-temperature gas phase (GP) system interfacing with a two-tank particle thermal energy storage (TES) and intermediate heat exchangers to supply sCO 2 at 20-25 megapascals (MPa) and 700°C at the turbine inlet.

14 SOLAR ENERGY↗
DOE OSTI2023

Equitable Energy Transition Planning in Holyoke, Massachusetts: A Technical Analysis for Strategic Gas Decommissioning and Grid Resiliency

Buildings account for 30% of the emissions in Massachusetts and are the largest source of emissions in the United States, along with transportation. Pipeline-delivered methane gas is the dominant heating source in Massachusetts, representing 51% of heating in the state. The current gas network in Massachusetts and across many other US states is aging, a relic of the coal gas era, with thousands of miles of cast iron and unprotected steel pipes that are considered leak prone. Even newer plastic pipes are subject to degradation and in need of replacement, an upgrade that averages $2.8 million per mile of pipeline replacement across investor-owned utilities in Massachusetts.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Investigation of Defect Physics for Efficient, Durable and Ubiquitous Perovskite Solar Modules (Final Technical Report)

Organometal halide perovskite solar cells have experienced eye-catching improvements in its recent few years. It serves as one of the most promising candidates to replace the currently widely used silicon-based solar modules. To implement its final step to the real application, functional longevity becomes the dernier continent to conquer. As a polycrystalline material, defect plays critical role in the efficiency and stability of the perovskite solar cells. Thus, the investigation of the defect physics of the perovskite layer is indispensable in this research field. However, hard evidence and a consensus are still lacking in terms of the specific nature of the defects and their effects on performance and hysteresis, and perhaps even more importantly, there is absence of fundamental understanding of the correlations between the defects and long-term operational stability of the device. A more fundamental understanding of the nature of defects in perovskite materials is of paramount importance to progress their efficiency and durability. In this work we propose in-depth studies of correlations of defects with performance and stability of perovskite solar cells. Our project aimed 1) to investigate the defects physics in perovskite solar cells, and 2) to develop a comprehensive understanding and physical model of defects and its influence on performance and stability of perovskite solar cells. With the support from program manager, Peter Lobaccaro, and the Solar Energy Technologies Office of U.S. Department of Energy, the project ends with impact achievements. Our research results have systematically provided strategies to analyze the influences of constructive molecular configurations to the charged defects in the perovskite lattices and developed in-depth understanding of chemical additive approach to improve the perovskite solar cell performance and stability. As history has shown us, control over defect properties of semiconductor materials is the key to achieving high performance and low cost devices. Therefore, the potential impact of unlocking the understanding and manipulation of defects in perovskites is great, enabling this technology to realize SETO goals. The research project is highly productive with 18 published papers in three years in top-level journals such as Science, Nature, Nature Materials, Nature Communications, Journal of American Chemistry Society, Joule, Advanced Materials, and Nano Letters. These works have drawn great attention nationwide with notable total citations over 700 times from 2020 to 2022.

14 SOLAR ENERGY↗
DOE OSTI2024

Low-cost, high-efficiency III-V photovoltaics enabled by remote epitaxy through graphene (Final Technical Report)

One of the most important outcomes of this project was that the team developed a method to directly grow graphene layer in wafer-scale on III-V substrates. Conventionally, graphene had to be transferred for remote epitaxy, which has imposed significant challenges in scalability, film quality, and substrate recycling, due to the transfer-related issues. The newly developed method of directly forming 2D layers by Metal-Organic Chemical Vapor Deposition (MOCVD) has realized wafer-scale, defect-free graphene formation for remote epitaxy, which has huge implications not only for solar cells but also in expanding the scalability and the possibility for heterointegration with dissimilar material platforms. Another important outcome was on better understanding of remote epitaxy mechanism. The growth of III-V on graphene is vastly different from directly growing films on III-V substrates, because the surface energy of graphene is very small, meaning that the nucleation density on graphene will be much lower than exposed III-V surfaces. Also, the graphene and the interface properties critically affect remote interaction through graphene. With this obtained knowledge regarding III-V remote epitaxy, we were able to achieve wafer-scale single-crystalline remote epitaxy, 100% exfoliation of the remote epitaxial films, as well as multiple times of GaAs wafer reusability demonstration. The general rule of thumbs found during this project will be a stepping stone for the growth and fabrication of various high-performance devices by remote epitaxy. Lastly, because remote epitaxy and 2DLT offer a pathway to isolate single-crystal membranes from the host wafers, the wafer-scale remote epitaxy processes developed in this project could open up pathways for new functionality and multi-functionality by heterointegration of remote epitaxially formed membranes.

14 SOLAR ENERGY↗
DOE OSTI2024

One-pot hydrodeoxygenation (HDO) of lignin monomers to C9 hydrocarbons co-catalyzed by Ru/C and Nb 2 O 5 (Final Technical Report)

Non-edible lignocellulosic biomass represents the most abundant source of renewable carbon on Earth. To harness its potential for producing valuable fuels and building blocks for renewable plastics, it is essential to undergo a process that involves the removal of oxygen atoms from its components. This report outlines various methodologies aimed at converting biomass components into fuels and building blocks suitable for renewable plastics. The primary emphasis of the described research lies in leveraging sustainable chemistry and catalysis to valorize biomass into fuels and chemicals.

09 BIOMASS FUELS↗
DOE OSTI2024

Tokamak Disruption Simulation (Final Technical Report)

This was a multi-institutional project concerned with simulation of tokamak disruption – rapid termination of the plasma and confining magnetic field in a tokamak fusion reactor – with the aim of quantifying the physics associated with disruption mitigation. The PI’s role is as one of a group of computational scientists concerned with development of effective solution algorithms for the underlying models of magnetohydrodynamics and transport that represent the physical processes, and to develop techniques of uncertainty quantification for treating unknown aspects of the model such as boundary conditions and effects of impurities in plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Water foraging with dynamic roots in E3SM; The role of roots in terrestrial ecosystem memory on intermediate timescales (Final Technical Report)

Terrestrial ecosystems can show sustained responses to stress events that may last for years after the initial perturbation. This phenomenon is referred to as legacy or memory and it emerges from a set of ecosystem processes that are poorly captured by Earth System and Land Surface Models. Consequently, these models struggle to predict the impact that extreme climate events have on surface energy, carbon and hydrological exchange once a stressor such as drought has relaxed or in response to repeated exposure to stress. In this project, we set out to test how the addition of dynamic root profiles in land surface models impact the capacity for Earth System Models, such as the Department of Energy’s E3SM, to capture realistic legacy effects. Observations have shown that vegetation shifts their root profiles during stress events to forage for water and these altered root profiles may take years to relax back to the initial state. We hypothesized that the alteration of the belowground root structures may be a source of terrestrial ecosystem legacy that is missing from models. To test this idea we undertook three core activities. (1) We developed a global-scale analysis of the impact of dynamic roots on ecosystem legacy building from a recently developed dynamic root module. (2) We developed new root dynamics in the DOE’s Energy Land Model (ELM) that allowed not only root profiles to shift their profile but also simultaneously alter carbon allocation to fine root pools. We then tested the impact of these new dynamics with intensive sensitivity analysis at four long-term AmeriFlux sites. (3) We undertook detailed isotopic analysis of tree rings from these AmeriFlux sites to assess ecophysiological and ecohydrological legacy to stress events that can be used to benchmark the sensitivity experiments with ELM. From these core activities, we report the following key findings. Firstly, on a global scale, the addition of dynamic roots led to chronically water-stressed ecosystems recovering faster to climate stress while wetter ecosystem showed enhanced legacy. This is because across ecosystems, stress events were almost universally associated with water shortages that led to the development of deeper root profiles. These deeper root profiles proved beneficial for recovery from drought stress. While the root dynamics did not universally improve the modeled representation of legacy it showed complex transient dynamics that emerge from the addition of dynamic roots. Secondly, the sensitivity analysis illustrated long term shifts in rooting depths away from the prescribed default profile suggesting that initializing of root profiles could benefit from spin-up simulations that converge on locally optimized root profiles. In addition, by enabling dynamic allocation some of the sites predicted unrealistically low allocation to roots (and high allocation to leaves). While these changes did not dramatically alter modeled gross primary productivity, they illustrated that without more sophisticated root processes in models, there is little penalty to dramatically disinvest in roots. Thirdly, the isotopic analysis of tree rings showed highly distinct legacy responses across species and sites. For example, T. canadensis showed reduced transpiration the year after stress events illustrated by sustained elevated $\delta^{18}$O. In contrast, A saccharum displayed elevated $\delta^{13}$C associated with reduced stomatal conductance in response to the previous years’ stress event. These geochemical signatures of legacy were present despite tree growth returning to normal the year after the stress. The results show the importance of species-level dynamics in legacy that are absent in modeling that assumes common traits within plant functional types. In summary, the work here established new avenues to explore root dynamics in models while illustrating how additional root processes are needed before dynamic carbon allocation can be implemented. Lastly, this project provided mentorship to a postdoctoral fellow, training for an early career scientist and multiple undergraduate students recruited from a minority serving institution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Physics-Informed Learning Machines for Multiscale and Multiphysics Problems (PHILMS) (Technical Report)

The research work at University of California Santa Barbara (UCSB) resulted in several new developments in the areas of scientific machine learning, numerical analysis, and practical methods for data-driven modeling, prediction, reductions, and simulation. Many of the projects were carried out in collaboration with members of the national laboratories at Sandia National Laboratories (SNL), Pacific Northwestern National Laboratories (PNNL), and other institutions. Results included developing new scientific machine learning methods, related theory and mathematical frameworks for analysis and training, data-driven numerical solvers, and related tools and software for scientific computation. During the support period, over 16+ papers were submitted for publication, and 4 open-source software packages were developed and released (available at http://atzberger.org/). In addition, 7+ students and 2 post-docs were mentored in collaboration with the laboratory staff for future careers in academia, government labs, and industry.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Collaborative Research: Vlasov–Maxwell Simulations to resolve electron heating and dissipation, in quasiperpendicular shocks (Final Technical Report)

The project is to study electron heating at quasi-perpendicular shocks. We have analyzed measurements from the Magnetosphere Multiscale (MMS) spacecraft and particle-in-cell simulations to address the question. One key discovery is that waves and are excited in the shock transition region, which further develop into complicated structures and thin current layers, which contribute to accelerate and heat electrons. We further investigated the excitation and evolution of these waves and structures, and their association with ion and electron dynamics. In addition, the analysis technique of Vlasov equation terms is further applied to study electron dynamics at the dayside magnetopause, to understand the effect of density, velocity and temperature variations on electron distributions and kinetics.

58 GEOSCIENCES↗
DOE OSTI2024

Development of 211 At production at Crocker Nuclear Laboratory (Final Technical Report)

The focus of this effort was the development of the capability to produce and recover 211 At via the process 209 Bi(α, 2n) 211 At at the cyclotron at the Crocker Nuclear Laboratory at UC Davis. This effort required the design and fabrication of an internal production target, the development of a separation and processing area, and upgrades to the cyclotron to increase its reliability. There was a significant delay due to the pandemic lockdown, but ultimately we were able to produce and recover 211 At at the tens of µCi level using a wet chemistry method. Results of the project were presented at conference, but publication of a refereed article has been delayed by some discrepancies in understanding the calibration of total 211 At produced. We plan to repeat the production using internal funding, but first we want to revise our recovery to use a different technique, developed at the Texas A& M Cyclotron Institute.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Extension of Local Helicity Injection Startup Studies to the Urania Experiment (Final Technical Report)

Initiating high-current plasma in a spherical tokamak (ST) without a central solenoid is a critical issue for the development of the ST configuration. The goal of the research funded through this grant was focused on addressing this challenge by demonstrating scalable startup to high plasma current (I p ), while developing a physical understanding and predictive models for non-solenoidal tokamak plasma startup using Local Helicity Injection (LHI). A major objective of this research and development activity was to use scaling experiments to validate a physics understanding that will support deployment of high-current (~1 MA) startup techniques to fusion-scale facilities such as NSTX-U and beyond.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Technical Report for SMART task 3.3.4

To implement the Fourier Neural Operator (FNO) (Li et al., 2021) as well as the U-Shaped Fourier Neural Operator (U-NO) (Rahman et al., 2022) to forecast the pressure distribution in the subsurface. Furthermore, to test out approaches to work on larger-scale as well as adding physics-based constraints.

58 GEOSCIENCES↗
DOE OSTI2023

Integrating Microtransit with Public Transit for Coordinated Multi-Modal Movement of People (Final Technical Report)

This project focused on potential benefits of mobility service providers and transit agencies cooperating to offer fully integrated, seamless multi-modal mobility services for commuters. Specifically, we aimed at developing a first/last mile microtransit and micromobility services tightly integrated with fixed-route transit to achieve the “point-to-point” service capability. Our goal was to provide fixed-route transit customers with two convenient and compelling options for accessing public transit that are also operational efficient.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Final Technical Report

The Department of Energy is interested in technologies that support the sustainable production of fuels, chemicals, and other bioproducts from plant biomass, to offset the nation’s reliance on fossil resources. The plant cell wall of energy crops provides the largest reservoir of raw materials for bioproducts. However, the widespread use of plant cell walls is hampered by their complexity and resistance to breakdown. To improve the productivity and cost-effectiveness of using energy crops to generate bioproducts, the fundamental problem of deconstructing plant cell walls must be addressed. This project developed and evaluated an innovative genetic modification technology to produce strategically designed enzymes that specifically accumulate in the plant cell wall. The resulting enzyme-engineered energy crops are expected to grow normally under natural conditions but break down more quickly and easily under high temperature during the production of biobased products. As such, this plant cell wall targeting enzyme engineering effort will reduce the cost of plant cell wall deconstruction and ultimately improve the economics of bioproducts. The overall objective of this project is to develop and evaluate the in-planta enzyme engineering technology to reduce lignocellulose deconstruction cost. The concept was first validated using tobacco plant, a model plant system that is typically used in lab testing for initial concept validation. Then the enzyme optimization was validated using switchgrass, the energy crop to be used to produce bioproducts. There are three specific objectives in this Phase I project: (1) validate the enzyme optimization concept using tobacco plant, a model plant system. (2) validate the enzyme optimization concept using switchgrass. (3) techno-economic analysis (TEA) for further scale-up application. By the end of this project, in-planta enzyme engineering was validated in both tobacco and switchgrass plants, with improved enzyme activity and saccharification efficiency. The in-planta enzyme engineering in Tabacco didn’t have a significant impact on plant growth and development. Transgenic tobacco plants with in-planta cellulose degrading enzymes showed higher biomass digestibility than wild type. Gene construction and transformation in switchgrass was much longer than expected, which delayed the research progress. Besides, in-planta engineering of lignin degrading enzyme is more challenging than cellulose degrading enzyme, in terms of expression detection. Expression of lignin degrading enzyme and cellulose degrading enzyme improved biomass yield and saccharification efficiency of switchgrass, respectively. It is promising to express both genes in switchgrass for optimized overall performance. According to the results of TEA, switchgrass biomass production cost is mainly attributed to by fertility and harvesting. Biomass production profit can increase up to 10-fold depending on biomass price. The PHA production profit is also sensitive to the biomass price. The proposed technology could potentially reduce the biomass deconstruction cost from 33% to 9% of PHA revenue, making the biomass-based PHA competitive to petroleum-based polymers even in case of relatively high biomass price of biomass. Therefore, cultivation of the genetically engineered self-deconstruction switchgrass for Polyhydroxyalkanoate (PHA) production could benefit switchgrass grower and PHA producer with attractive profits for both sectors. This new enzyme optimization approach will be beneficial for bioindustries that use energy crops as feedstocks. It will improve the economic viability of converting energy crops to renewable products that support a sustainable society and helps address the Nation’s long-term strategic needs for renewable products and reduction of reliance on fossil resources.

42 ENGINEERING↗
DOE OSTI2024

Metal-Organic Frameworks: Structure, Function and Design via Hyperpolarized NMR Spectroscopy: Collaborative Proposal (Final Technical Report)

Nuclear magnetic resonance is a powerful tool to shed light on the properties of a vast range of materials but its use is affected by detection sensitivity. Throughout this work, we investigated new routes to dynamic nuclear spin polarization with an eye on applications to the study of metal-organic frameworks (MOFs). Work at the Meriles group focused on extending our understanding of the mechanisms governing the optical generation of spin order via photo-active electronic spin species and the subsequent transfer of spin polarization throughout the solid-state host.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Universality of Collective Density Fluctuations in Liquids at and away from Equilibrium – An Integrated Neutron Scattering, Theoretical, and Computational Study (Final Technical Report)

Liquids, ubiquitous on earth, are prototypical disordered condensed matter. As the mediate phase between non-structured gases and ordered solids, liquids p ossess intriguing complexities that are absent on either extreme counter phase, especially when they are driven away from equilibrium. Despite decades of studies, the physics of liquids still keeps surprising us and challenges our understanding of condensed matter, emergent phenomena, and complex systems. Among the many interesting properties, the nature of collective dynamics in liquids remains elusive because of both the presence of strong interactions and the absence of translational invariance. This project studied the universal features of collective density fluctuations (or collective modes), which include both phonon-like excitations and collective relaxations, in the Q-dependent generalized hydrodynamic regime in liquids and liquid-like matter both at and away from equilibrium. We performed systematic studies of the fast collective dynamics (including both phonon-like excitations and collective relaxations) of four classes of liquids characterized by different fragilities and interactions using synergistically integrated coherent neutron scattering experiments (Inelastic Neutron Scattering (INS), Quasi-Elastic Neutron Scattering (QENS), and Neutron Spin Echo (NSE)), a ViscoElastic Hydrodynamics theory we have been developing, andMolecular Dynamics (MD) simulations and our analysis package LiquidLib. The transformative knowledge of the collective dynamics in liquids is important to understand and ultimately control the transport of mass, energy, and charge in liquids, both at and away from thermal equilibrium, which may will likely impact a wide range of disciplines.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Deep Image Prior Enabled Full Waveform Inversion (Final Technical Report)

MS Student Naveen Gupta worked on the problem of full waveform inversion (FWI) using neural networks as shown in Figure 1. Our goal was to learn a neural network to represent the subsurface velocity model, which when fed into the FWI module (implemented using a numerical forward model of wave equations) produces amplitude estimates that match with ground-truth observations of amplitude. We used neural networks to solve the inverse problem of estimating velocity distributions for a given seismic amplitude data such that, once trained, our neural network model can generate a distribution of velocity profiles for different random vectors fed as inputs to the neural network model.

97 MATHEMATICS AND COMPUTING↗