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NASA NTRS1986

Effects of high-energy neutrino production and interactions on stars in close X-ray binaries

Limits are discussed that may be placed on binary systems in which a compact partner is a strong source of high-energy particles that produce photons, neutrinos, and other secondary particles in the companion star. The highest energy neutrinos are absorbed deep in the companion and the associated energy deposition may be large enough to affect its structure or lead to its ultimate disruption. This neutrino heating is evaluated, starting with a detailed numerical calculation of the hadronic cascade induced in the atmosphere of the companion star. For some theoretical models, the resulting energy deposition from neutrino absorption may be so great as to disrupt the companion star over a time scale of 10,000-100,000 yr. Even if the energy deposition is smaller, it may still be high enough to alter the system substantially.

Gaisser, T. K.↗

DOE OSTI2023

Understand the Costs of an Energy or Water Outage with the Customer Damage Function Calculator

The Customer Damage Function (CDF) Calculator is a free, publicly available web tool that helps users estimate the costs incurred at their site due to an electric grid or water service outage. Developed by the National Renewable Energy Laboratory (NREL) with support from the Federal Energy Management Program (FEMP), the tool is designed to help federal facility owners, building energy managers, and resilience planners understand and quantify the value of resilience to justify investments that would prevent or lessen the impact of a disruption.

CDF Calculator↗

DOE OSTI2024

Disruptive Silicon Anode Technology for Next-Generation Lithium-Ion Batteries

The National Renewable Energy Laboratory (NREL) has pioneered novel processing technology for silicon nanoparticles (Si NPs) synthesized from plasma-enhanced chemical vapor deposition (PECVD) that will disrupt current lithium-ion battery technology. This revolutionary Si NP-based anode leverages a molecular coating applied to PECVD Si NPs that transforms them into homogeneous colloids suitable for conventional slurry formulation and electrode deposition resulting in delivered capacities of >2000 mAh/g (total electrode mass) at >90 wt% Si content anodes.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

GIS Visualization of Transportation Energy Consumption

Transportation is witnessing unprecedented transformation, where emerging technologies are disrupting the way we travel. Be it sharing economy, or micro-mobility, the landscape of urban transportation is undergoing a much-needed paradigm shift. In order to capture and model these shifts, researchers need to be agile in their studies of the current and future transportation landscape. The need for agility in turn calls for sophisticated, intuitive, and reliable means to visualize and share transportation data. Travel is inherently spatial, so methods of visualizing transportation information should also be rooted in spatial analysis. Geographic Information Systems (GIS) are the premier technological framework to analyze and display spatial data. GIS tools have been used in the past to depict flow of vehicles, and display of network conditions (speed, congestion, etc.). However, in an ever-changing technological landscape, spanning advancements in vehicle as well as information systems, depicting vehicle flows falls short of providing a comprehensive picture of the impact these advancements have on travel related energy consumption. To address this issue, this research effort presents a web-based mapping application to visualize how travel related energy flows across a city. The application is being developed by National Renewable Energy Laboratory researchers to integrate various transportation energy consumption models within a GIS schema. This has the goal of enabling rapid analysis of energy impacts of the dramatically evolving transportation environment. The application is being developed using a Python framework for ArcGIS Online. Using road network data from the City of Columbus, Ohio and traffic data from CATT Laboratory's Regional Integrated Transportation Information System, transportation energy consumption will be modeled at a macro level. The application aims to provide highly accurate data while still maintaining the flexibility needed to adapt the model when new technologies arise. The methodology presented through this effort is expected to provide insights into how light-duty vehicles use energy on a large scale based on the road network they use. The application will also provide data exports to enable sharing and collaboration. " need for agility in turn calls for sophisticated, intuitive, and reliable means to visualize and share transportation data. Travel is inherently spatial, so methods of visualizing transportation information should also be rooted in spatial analysis. Geographic Information Systems (GIS) are the premier technological framework to analyze and display spatial data. GIS tools have been used in the past to depict flow of vehicles, and display of network conditions (speed, congestion, etc.). However, in an ever-changing technological landscape, spanning advancements in vehicle as well as information systems, depicting vehicle flows falls short of providing a comprehensive picture of the impact these advancements have on travel related energy consumption. To address this issue, this research effort presents a web-based mapping application to visualize how travel related energy flows across a city. The application is being developed by National Renewable Energy Laboratory researchers to integrate various transportation energy consumption models within a GIS schema. This has the goal of enabling rapid analysis of energy impacts of the dramatically evolving transportation environment. The application is being developed using a Python framework for ArcGIS Online. Using road network data from the City of Columbus, Ohio and traffic data from CATT Laboratory's Regional Integrated Transportation Information System, transportation energy consumption will be modeled at a macro level. The application aims to provide highly accurate data while still maintaining the flexibility needed to adapt the model when new technologies arise. The methodology presented through this effort is expected to provide insights into how light-duty vehicles use energy on a large scale based on the road network they use. The application will also provide data exports to enable sharing and collaboration.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1986

High energy neutrino absorption and its effects on stars in close X-ray binaries

The physics and astrophysics of high energy neutrino production and interactions in close X-ray binary systems are studied. These studies were stimulated by recent observations of ultrahigh energy gamma-rays and possibly other ultrahigh energy particles coming from the directions of Cygnus X-3 and other binary systems and possessing the periodicity characteristics of these systems. Systems in which a compact object, such as a neutron star, is a strong source of high energy particles which, in turn, produce photons, neutronos and other secondary particles by interactions in the atmosphere of the companion star were considered. The highest energy neutrinos are absorbed deep in the companion and the associated energy deposition may be large enough to effect its structure or lead to its ultimate disruption. This neutrino heating was evaluated, starting with a detailed numerical calculation of the hadronic cascade induced in the atmosphere of the companion star. For some theoretical models, the resulting energy deposition from neutrino absorption may be so great as to disrupt the companion star over an astronomically small timescale of the order of 10,000 years. Even if the energy deposition is smaller, it may still be high enough to alter the system substantially, perhaps leading to quenching of high energy signals from the source. Given the cosmic ray luminosities required to produce the observed gamma rays from cygnus X-3 and LMX X-4, such a situation may occur in these sources.

Gaisser, T. K.↗

DOE OSTI2020

Physics-guided machine learning approaches to predict the ideal stability properties of fusion plasmas

One of the biggest challenges to achieve the goal of producing fusion energy in tokamak devices is the necessity of avoiding disruptions of the plasma current due to instabilities. The disruption event characterization and forecasting (DECAF) framework has been developed in this purpose, integrating physics models of many causal events that can lead to a disruption. Two different machine learning approaches are proposed to improve the ideal magnetohydrodynamic (MHD) no-wall limit component of the kinetic stability model included in DECAF. First, a random forest regressor (RFR), was adopted to reproduce the DCON computed change in plasma potential energy without wall effects for a large database of equilibria from the national spherical torus experiment (NSTX). This tree-based method provides an analysis of the importance of each input feature, giving an insight into the underlying physics phenomena. Secondly, a fully-connected neural network has been trained on sets of calculations with the DCON code, to get an improved closed form equation of the no-wall β limit as a function of the relevant plasma parameters indicated by the RFR. The neural network has been guided by physics theory of ideal MHD in its extension outside the domain of the NSTX experimental data. The estimated value has been incorporated into the DECAF kinetic stability model and tested against a set of experimentally stable and unstable discharges. Moreover, the neural network results were used to simulate a real-time stability assessment using only quantities available in real-time. Finally, the portability of the model was investigated, showing encouraging results by testing the NSTX-trained algorithm on the mega ampere spherical tokamak (MAST).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Cloud-based Testbed for Adaptive Under-Frequency Load Shedding with High DER Penetration

Increasing penetration of distributed energy resources and behind-the-meter renewables may soon disrupt the efficacy of critical protection schemes, such as under-frequency load shedding (UFLS). Improved data exchange and coordination across the transmission-distribution boundary will be required to maintain reliability of bulk electric system. Standards-based data integration platforms using agreed-upon semantic vocabularies, such as the Common Information Model, will be key to enabling adaptive protection schemes requiring synthesized data from both the bulk power system and behind-the-meter resources. This paper introduces a cloud-based open-source data integration environment and UFLS clustering algorithm being developed to enable adaptive relay coordination between transmission and distribution utilities in the state of Vermont.

Anderson, Alexander A.↗

DOE OSTI2024

Leverage demand-side policies for energy security

Energy security is a top priority for governments, companies, and households because energy systems and the critical functions that they support are threatened by disruptions from wars, pandemics, climate change, and other shocks (1). More often than not, governments rely on policies focused on energy supply to enhance energy security while generally ignoring demand-side possibilities. Further, the indicators traditionally used to measure energy security are also tilted toward the supply side; this fails to capture the full spectrum of vulnerability to energy crises. Energy security assessments need to reflect the wider benefits of security related interventions more accurately. To that end, we develop a systematic approach to measuring the energy security impacts of policy interventions that explicitly considers energy demand (buildings, transport, and industry). Here, we determine that demand-side actions outperform conventional supply-side approaches at making countries more resilient. Energy demand links more directly than supply to the satisfaction of critical social functions and human well-being that are at the core of energy security. Yet, demand-side perspectives tend to be neglected or underrepresented in analysis and policy debates on energy security. Factors that contribute to this supply-side bias include the traditional sectoral organization of industries and policy institutions along fuels (coal, oil, and gas) and energy forms (electric utilities) as well as the decentralized and multivaried activities characteristic of energy demand (from vehicles to household appliances to manufacturing and more), which leads to a multitude of actors and institutional fragmentation. The basic fundamentals of energy systems and markets, where demand and supply are intricately linked, have also not yet risen from vague awareness to a central organizing principle among policy-makers for structuring the energy security discourse.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Cryogenic Carbon Capture™ (CCC) Status Report

The Cryogenic Carbon Capture™ (CCC) process separates CO2 from light gases in essentially any continuous process. CCC cools the gases to the frost or desublimation point of CO2 (-100 to -135 °C), separates and pressurizes the solids, and warms all streams to produce a CO2-depleted stream at ambient pressure and a pure (99+%) pressurized liquid CO2 stream typically to about 150 bar, both at ambient temperature. The process also recovers all gas moisture and most gas impurities less volatile than CO2 (NOx, SOx, Hg, PM, UHC, CCC, etc.) in separable streams. CCC nearly eliminates refrigeration energy for sensible temperature changes through heat integration. CCC does require energy to change the CO2 phase from a mixed vapor to a pressurized fluid, which represents the minimum energy required of any process for this separation. CCC uses additional energy for turbomachinery inefficiencies, heat losses, moisture removal and overall process pressure drop. Aside from these real-world energy demands, CCC operates near the minimum energy required to perform this gas separation by minimizing stream recycling. CCC compresses CO2 as a liquid, which is one of several reasons it costs about about half as much and consumes about half as much energy as an amine process when using flue gases with about 15% CO2. The process also has several major additional advantages, including (a) it is a bolt-on retrofit technology that does not need steam or any modification of existing equipment, (b) it recovers water and nearly all pollutants in addition to CO2 from the flue gas, (c) it enables highly efficient and cost effective energy storage at grid scale and on time scales of minutes, (d) it enables NG storage if the energy storage option is used, and (d) it has a small footprint and is minimally disruptive to existing plants, requiring only electrical power and a gas source to operate. Sustainable Energy Solutions (SES) has scaled this technology through several levels, the largest of which captures nominally 1 tonne of CO2/day and is called the skid system. Skid system field tests include utility-scale power plants, cement plants, heating plants, and other utility or industrial sites that burn natural gas, biomass, coal, shredded tires, municipal waste, and combinations of these fuels. These field tests produced 95-99% CO2 capture with CO2 purities of 99+% and initial CO2 contents that range from 4 to 28%. SES currently seeks to scale the system to merchant scale (10-80 tonnes of CO2 per day). In the process of doing so, SES has demonstrated the potential for CCC to contribute to energy storage and direct air capture in innovative and cost-effective ways. This presentation discusses the overall process and highlights results from field and in-house tests. These include (a) measured CO2 capture rates and operating conditions from in-house and field tests, and (b) predicted utility-scale costs and energy demands. This discussion also includes the application of the CCC technology to energy storage and direct air capture.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2023

Collaborating with Utilities to Meet Underserved Community Needs: A Guide to Equitable Commercial Solar and Solar + Storage Deployment

Communities of color and low-income populations dedicate a disproportionate amount of their income to pay for energy. They also experience more frequent and prolonged service disruptions, impacting community health and safety. When designed correctly, commercial solar + storage installations have the potential to ameliorate these issues. However, utility programs created to support such installations are frequently underutilized because communities often lack the time and resources needed to access them. Further, historically, few utilities have had the motivation and incentives or experience to account for this barrier. RMI provided process support to Solar Energy Innovation Network teams, and described their experiences in accessing these clean energy resources to support historically underserved communities in our latest report. The report also outlines the roles of key stakeholders (e.g., utilities, building owners, and community organizations) in supporting program delivery and recommended practices to collaborate to meet community needs. The report focuses on commercial solar and solar + storage resources, including solar + storage microgrids. These technologies can offer benefits to communities who do not own their own properties. When designed to act as a "resilience hub," they can also support communities in times of electricity disruption. The report includes a step-by-step guide to collaborating with utilities to implement programs for historically underserved customers. Utilities can support these projects with financing assistance, modernized rate designs, and, in the deployment phase, technical assistance for system design and interconnection.

14 SOLAR ENERGY↗

DOE OSTI2025

Advanced Materials & Manufacturing Technology (AMMT): Development of Additive Manufacturing Agnostic Process Parameter Procedure, 316H Stainless Steel Readiness Level Data Sets, and Machine Maintenance Plan

The University of California, Davis is involved in a project to deploy and enhance an artificial intelligence (AI) system for predicting and preventing plasma disruptions on the DIII D tokamak, under the funding from Department of Energy DE-SC0023500 (title: AI/Deep Learning FRNN Software for Prediction & Real-Time Control of DIII-D Plasma Control System (PCS)). The overarching goal is to demonstrate that real-time, AI-guided intervention can proactively modify the plasma state to avoid or mitigate disruptions—a critical challenge for the future of fusion energy.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Microbial production of fuels, commodity chemicals, and materials from sustainable sources of carbon and energy

Anthropogenic carbon emissions are driving rapid changes to the earth's climate, disrupting whole ecosystems and endangering the stability of human society. Innovations in engineered microbial fermentation enable the fossil resource-free production of fuels, commodity chemicals, and materials, thereby reducing the carbon emissions associated with these products. Microorganisms have been engineered to catabolize sustainable sources of carbon and energy (i.e., plant biomass, plastic waste, and one-carbon feedstocks) and biosynthesize carbon-neutral or carbon-negative products. These engineering efforts exploit and optimize natural biological pathways or generate unnatural pathways which can biosynthesize chemicals that have not yet been accessed using synthetic chemistry. Further, recent advances in microbial fermentation seek not only to maximize the titer, rate, and yield of desired products, but also to tailor microbial catabolism to utilize inexpensive feedstocks. Ultimately, these advances aim to lower the cost of bioproduction so that microorganism-derived chemicals can be economically competitive with fossil-derived chemicals.

09 BIOMASS FUELS↗

DOE OSTI2020

Shatter Thresholds and Fragment Size Distributions of Deuterium–Neon Mixture Cryogenic Pellets for Tokamak Thermal Mitigation

Reliable mitigation is necessary to eliminate the detrimental effects of a disruption event in large high-current tokamaks such as ITER. To avoid serious damage to plasma-facing components during the thermal quench phase of a disruption, material is injected to radiate the plasma energy over the inner surface of the machine. The most promising method of material injection is a process known as shattered pellet injection (SPI). SPI utilizes cryogenic cooling to desublimate gas into the barrel of a pipe gun to form a solid pellet. High-pressure gas or a mechanical punch is used to dislodge the pellet and accelerate it into a bent tube to intentionally fracture it. Pellets made of a mixture of deuterium and neon are likely candidates for thermal mitigation. The survivability of these pellets throughout their flight path, before striking the shatter tube, is essential for reliable SPI operation. Experiments were conducted to determine intact speed limits for various mixtures. In this paper, we outline the details of brittle fracture theory and compare a theory-based model to experimental results from various mixtures of deuterium and neon pellets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Narrowing lab–to–market gaps: Device innovations in fuel generation, solar–cell, and photodetection

Academic translational research efforts to industry are often an underlying sought–after goal among various researchers. Through the interchanges of research endeavors between academia–industry, great innovations can/has been achieved that cater to the real–world application by bridging “industrially relevant” problem solving with pursuing fundamental studies. It is pertinent that most of the studies from university–level research works may not translate into demonstrable market products due to various reasons. Funding support, individual researcher goals, socioeconomic factors, and most importantly the technical know–how of generating revenue strategies for startups, are a few of the factors that have slowed the pace of collaborative efforts. However, we believe that the most crucial component is the identification of the critical parameters that solve long–standing problems that hinder the scale–up of the lab scale research into marketable products considering the techno–economic analysis. Here, to illustrate this, we take the three most relevant examples of devices for fuel generation, devices to utilize solar radiation, and devices for detection and other related applications. In this perspective, we provide an in–depth case study of each of these critical parameters to comment on the direction of research avenues that can serve as step–stones for the commercialization of university–level lab research studies.

42 ENGINEERING↗

DOE OSTI2026

Radiation Damage Mechanisms in Oxide-Based Solid Electrolytes

Ion implantation is a promising approach to mitigate dendrite formation in metal anode solid-state batteries by modifying the chemical and mechanical properties of oxide-based electrolyte surfaces such as Li 7 La 3 Zr 2 O 12 (LLZO). Yet, the detailed atomistic mechanisms and potentially adverse side effects of ion implantation remain poorly understood. In this study, we used molecular dynamics simulations to elucidate the evolution of radiation-induced damage in LLZO. The results reveal that radiation damage is primarily driven by recoils from heavy ions in the lattice, producing antisite defect clusters whose density decreases as recoil energy increases, a counterintuitive finding that highlights complex cascade fragmentation. Radiation-induced disruption to the crystal sublattice connectivity, especially in the La–O network critical for Li-ion transport, leads to degradation in ionic pathways at low energies, while higher energy cascades can form new conduction pathways via enhanced Zr–O network connectivity. These findings provide a mechanistic foundation for optimizing ion implantation strategies that balance disruption of the lattice for surface modification for dendrite resistance with preservation of essential ionic conductivity.

Defects↗

DOE OSTI2020

Proton affinities of pertechnetate (TcO 4 - ) and perrhenate (ReO 4 - )

The anions pertechnetate, TcO 4 - , and perrhenate, ReO 4 - , exhibit very similar chemical and physical properties. Revealing and understanding disparities between them enhances fundamental understanding of both. Electrospray ionization generated the gas-phase proton bound dimer (TcO 4 - )(H + )(ReO 4 - ). Collision induced dissociation of the dimer yielded predominantly HTcO 4 - and ReO 4 - , which according to Cooks’ kinetic method indicates that the proton affinity (PA) of TcO 4 - is greater than that of Re O 4 - . Density functional theory computations agree with the experimental observation, providing PA[TcO 4 - ] = 300.1 kcal mol -1 and PA[ReO 4 - ] = 297.2 kcal mol -1 . Attempts to rationalize these relative PAs based on elementary molecular parameters such as atomic charges indicate that the entirety of bond formation and concomitant bond disruption needs to be considered to understand the energies associated with such protonation processes. Although in both the gas and solution phases, TcO 4 - is a stronger base than ReO 4 - , it is noted that the significance of even such qualitative accordance is tempered by the very different natures of the underlying phenomena.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Magnetic reconnection and thermal equilibration

When a magnetic field is forced to evolve on a time scale sev, as by footpoint motions driving the solar corona or non-axisymmetric instabilities in tokamaks, the magnetic field lines undergo large-scale changes in topology on a time scale approximately an order of magnitude longer than $\tau$ ev . But the physics that allows such changes operates on a time scale eight or more orders of magnitude slower. An analogous phenomenon occurs in air. Temperature equilibration occurs on a time scale approximately an order of magnitude longer than it takes air to cross a room, $\tau$ ev , although the physical mechanism that allows temperature equilibration is approximately four orders of magnitude slower than $\tau$ ev . The use of Lagrangian coordinates allows the fundamental equations to be solved and both phenomena explained. The theories of thermal equilibration and magnetic reconnection are developed in parallel to help readers obtain an understanding of the importance and implications of analyses using Lagrangian coordinates.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Staged cooling of a fusion-grade plasma in a tokamak thermal quench

Abstract In tokamak disruptions where the magnetic connection length becomes comparable to or even shorter than the plasma mean-free-path, parallel transport can dominate the energy loss and the thermal quench of the core plasma goes through four phases (stages) that have distinct temperature ranges and durations. The main temperature drop occurs while the core plasma remains nearly collisionless, with the parallel electron temperature T e ∥ dropping in time t as T e ∥ ∝ t − 2 and a cooling time that scales with the ion sound wave transit time over the length of the open magnetic field line. These surprising physics scalings are the result of effective suppression of parallel electron thermal conduction in an otherwise bounded, quasineutral, and collisionless plasma, which is different from what are known to date on electron thermal conduction along the magnetic field in a nearly collisionless and quasineural plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗