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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Dark Matter and Track Triggering with the CMS Experiment (Final Report)

This report summarizes the progress from DOE Early Career Award entitled “Dark Matter and Track Triggering with the CMS Experiment”. The first major goal of the project was to establish a sensitive Dark Matter (DM) search program for the CMS experiment in Run-2 of the LHC. Two related strategies were developed to accomplish this goal. First, we designed and executed searches for DM produced in association with heavy flavor quark pairs, top/anti-top (ttbar) and bottom/anti-bottom (bbbar). In addition, we sought to maximize the power of Run-2 DM searches through the development of a statistical combination of all major search channels within a consistent theoretical framework. The results of these aspects of the project are detailed in Section 1. The second major goal of the project was to develop a real-time “Level-1” tracking trigger system for the high-luminosity LHC (HL-LHC) CMS upgrade. Charged particle tracking in the first stage of the CMS trigger will be crucial for surviving the high-pileup environment expected at the HL-LHC. The L1 tracking trigger must process all front-end hit data sent from the inner Tracker and will have just 4us to output track primitives to the downstream L1 trigger without data loss. Our development of the CMS tracking trigger is described in Section 2. The team supported by the award is given in Section 3. The project resulted in 10 peer reviewed publications, a graduate student thesis, and contributions to the CMS Phase-2 Tracker Technical Design Report, as is detailed in Section 4. Our development work for the CMS tracking trigger has been integrated in the backend system architecture for the Tracker upgrade.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Vision and Development of a Design, Implementation, and Verification Automation (DIVA) Software Platform for DNA Construction

Abstract DNA construction, while a prerequisite to many biological endeavors, is often a time-consuming distraction from an individual’s primary research objectives. We envisioned that with the right software infrastructure and cultural mindset, a single person could execute in parallel the batched DNA construction tasks of an entire research institute, at scales realizing efficiency gains through process and laboratory automation. In pursuit of this vision, we developed the Design, Implementation, and Verification Automation (DIVA) software platform. DIVA’s web interface enables researchers to design DNA constructs (using visual biological computer-aided design tools and biological parts repositories), submit designs for construction to dedicated staff, and track DNA construction as it progresses. DIVA supports the dedicated staff through the DNA construction process and records both successful and unsuccessful attempts toward improving the overall process. The platform is publicly available at public-diva.jbei.org and its open-source code through github.com/JBEI/DIVA.

Plahar, Hector [DOE Agile BioFoundry , , ,; DOE Jo↗
DOE OSTI2017

Influence of Particle Morphology on 3D Kinematic Behavior and Strain Localization of Sheared Sand

The constitutive behavior of sheared sand is highly influenced by particle morphology, gradation, mineralogy, specimen density, loading condition, stress path, and boundary conditions. The current literature lacks a three-dimensional (3D) systematic experimental study that investigates the influence of particle morphology, confining pressure, and specimen density on the failure mode of sheared sand. In this paper, surface texture, roundness, and sphericity of three uniform sands and glass beads with similar grain size were quantified by using 3D images of particles. In situ nondestructive 3D synchrotron microcomputed tomography (SMT) was used to monitor the deformation of medium-dense and very dense dry sand specimens that were tested under axisymmetric triaxial loading condition at 15 and 400 kPa confining pressures. The particles were identified and tracked in 3D as shearing progressed within the specimens, and maps of incremental particle translation and rotation were developed and used to uncover the relationship between particle morphology, specimen density, and confining pressure on the deformation and failure mode of sheared sand. This paper discusses the relationship between the failure mode and particle morphology, specimen density, and confining pressure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

The Muon g-2 Experiment overview and status as of June 2016

The Muon g-2 Experiment at Fermilab will measure the anomalous magnetic moment of the muon to a precision of 140 parts per billion, which is a factor of four improvement over the previous E821 measurement at Brookhaven. The experiment will also extend the search for the electric dipole moment (EDM) of the muon by approximately two orders of magnitude, with a sensitivity down to 10 -21 e.cm. Both of these measurements are made by combining a precise measurement of the 1.45T storage ring magnetic field with an analysis of the modulation of the decay rate of higher-energy positrons (from anti-muons), recorded by 24 calorimeters and 3 straw tracking detectors. Furthermore, the recent progress in the alignment of the electrostatic quadrapole plates and the trolley rails inside the vacuum chambers, and in establishing the uniform storage ring magnetic field will be described.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Gene Regulation Shifts Shed Light on Fungal Adaption in Plant Biomass Decomposers

ABSTRACT Fungi dominate the recycling of carbon sequestered in woody biomass. This process of organic turnover was first evolved among “white rot” fungi that degrade lignin to access carbohydrates and later evolved multiple times toward more efficient strategies to selectively target carbohydrates—“brown rot.” The brown rot adaption was often explained by mechanisms to deploy reactive oxygen species (ROS) to oxidatively attack wood structures. However, its genetic basis remains unclear, especially in the context of gene contractions of conventional carbohydrate-active enzymes (CAZYs) relative to white rot ancestors. Here, we hypothesized that these apparent gains in brown rot efficiency despite gene losses were due, in part, to upregulation of the retained genes. We applied comparative transcriptomics to multiple species of both rot types grown across a wood wafer to create a gradient of progressive decay and to enable tracking temporal gene expression. Dozens of “decay-stage-dependent” ortho-genes were isolated, narrowing a pool of candidate genes with time-dependent regulation unique to brown rot fungi. A broad comparison of the expression timing of CAZY families indicated a temporal regulatory shift of lignocellulose-oxidizing genes toward early stages in brown rot compared to white rot, enabling the segregation of oxidative treatment ahead of hydrolysis. These key brown rot ROS-generating genes with iron ion binding functions were isolated. Moreover, transcription energy was shifted to be invested on the retained GHs in brown rot fungi to strengthen carbohydrate conversion. Collectively, these results support the hypothesis that gene regulation shifts played a pivotal role in brown rot adaptation. IMPORTANCE Fungi dominate the turnover of wood, Earth’s largest pool of aboveground terrestrial carbon. Fungi first evolved this capacity by degrading lignin to access and hydrolyze embedded carbohydrates (white rot). Multiple lineages, however, adapted faster reactive oxygen species (ROS) pretreatments to loosen lignocellulose and selectively extract sugars (brown rot). This brown rot “shortcut” often coincided with losses (>60%) of conventional lignocellulolytic genes, implying that ROS adaptations supplanted conventional pathways. We used comparative transcriptomics to further pursue brown rot adaptations, which illuminated the clear temporal expression shift of ROS genes, as well as the shift toward synthesizing more GHs in brown rot relative to white rot. These imply that gene regulatory shifts, not simply ROS innovations, were key to brown rot fungal evolution. These results not only reveal an important biological shift among these unique fungi, but they may also illuminate a trait that restricts brown rot fungi to certain ecological niches.

plant biomas↗
DOE OSTI2022

Intelligent Process Visualization through Nuclear Operation Process Modeling, Reasoning, and Object Detection from Field Videos (Final Report)

This report is a deliverable for the “Final Report” task of DOE NEET Project 19-16790, "Context-Aware Safety Information Display for Nuclear Field Workers." This project's overall goal is to test the hypothesis that integrating computer vision and process reasoning methods will enable proactive visualization of the safe operation and maintenance processes of Nuclear Power Plants (NPP) for field workers. Augmented Reality (AR) glasses adopting such proactive safety information visualization techniques can significantly increase personnel safety and reduce the NPP’s operating costs. The current practice of monitoring NPPs requires workers to switch between digital models, data, and physical workspaces in identifying relevant but potentially occluded objects and in assessing the risks of operation and maintenance processes. On the other hand, frequently changed field conditions require field workers to report to supervisors for real-time guidance. Such guidance is essential to ensure that changing conditions will not invalidate or endanger the work order and other ongoing processes that may jeopardize NPP operations. Additionally, incorrect recognition of equipment objects can result in communication errors and safety problems. AR techniques can assist engineers in viewing the physical workspaces with objects labeled with detailed operation procedures and safety reminders during field operations. The project team developed an “Intelligent Context-Aware Safety Information Display” (ICAD) for supporting Nuclear Power Plant (NPP) field workers in achieving safe and efficient execution of a series of operational tasks in uncertain and changing workspaces of an NPP. Before designing the ICAD-AR prototype, the project team synthesized NPP operational knowledge models through literature review studies, surveys, interviews with domain experts, and knowledge modeling. The project team conducted an extensive study of the operational procedures of various NPPs, and digital technologies that can support the safe and efficient execution of those procedures in different NPP operational contexts. This literature review helped the project team conduct surveys and interviews with nuclear engineers and field workers to identify three categories of information. The NPP knowledge modeling efforts reveal that the three categories of information identified have different levels of importance in a typical procedure of carrying out a series of tasks to achieve a specific NPP operation goal (e.g., shutdown, mode changes). These three categories of information include 1) Workspace dynamics – the changing spatial arrangements of workspaces, tools, protection equipment, and supporting materials, 2) Workflow prognostics – the dynamic dependencies between different parts of an NPP that functionally support and influence each other in terms of safety and efficiency, and 3) Hazards – objects and spaces that contain hazardous materials or physical conditions that can pose risks to workers or mechanical systems. The project team has profiled the importance levels of these categories of information into a knowledge model. This knowledge model specifies what types of information are more critical for a given task in a given workspace so that computers can automatically identify critical objects and sensors in a scene for delivering context-ware safety information to field workers through AR devices. Significant research development of this project results in technical research outcomes and a prototyping system that illustrates the technical feasibility of establishing an ICAD-AR system supporting the proactive safety information display for nuclear field workers. This final report summarizes the project team’s technological achievements in the past three years. Overall, the project team completed the development and integration of five techniques into a prototype ICAD Augmented Reality (ICAD-AR) system and demonstrated the developed system’s real-time execution in a mechanical room. The project team completed the analysis of using this prototype in other types of workspaces based on 3D image data and digital design models collected from two additional workspaces (a water treatment plant and a flow loop training facility). The integrated techniques include 1) Natural Language Processing (NLP) algorithms supporting the generation and updates of nuclear fieldwork process models based on text analysis of work packages and operation manuals; 2) sensor log analysis for predicting control actions in given sensor reading contexts; 3) computer vision algorithms for automatic localization and navigation of workers; 4) object detection algorithms for identifying task-related objects and correlated sensors for safety checking; 5) AR technique as a platform for supporting the integration. The testing results of these five techniques have shown that 1) the sensor log analysis model can predict the next control action with an accuracy of 0.883; 2) the trained natural language processing model can extract more than 80% of the critical information from paper-based procedures (PBPs); 3) the navigation algorithm with the integration of Visual Inertial Odometry (VIO) and Non-Recursive Bayesian Filter methods make operator’s trajectory estimation resilient to drift error; 4) the computer vision algorithm can detect task-specific and safety-critical objects with an average accuracy of 95.3%. The project team used work procedures collected from a flow loop training facility and two datasets collected from two mechanical rooms simulating the workspaces of NPPs to demonstrate the technical capabilities of the developed ICAD-AR prototype. The demonstration validated the technical feasibility of establishing the ICAD-AR system for nuclear field workers and identified the challenges in 1) automatic text analysis of work packages; 2) use of limited samples of sensor logs for predicting the proper timings of control actions; 3) reliably tracking workers and their task progress in mechanical rooms with many similar objects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

A summary comparison of design evaluation techniques - 270

Many nuclear power plants in the United States have recently been granted a 20 year extension to their operation license and are considering modernization. The Idaho National Laboratory is committed to successful modernizations and has been identifying and developing candidate technologies for power plants using methods that match the requirements of an integrated system validation. To do so this paper discusses current and potential workload, situation awareness and other performance methods used in evaluating control room design against the criteria defined by the Nuclear Regulatory Commission. The analysis provided is narrowed to the scope of methods surrounding the Light Water Reactor Sustainability research at the Idaho National Laboratory and therefore evaluates only a handful of the numerous methods used in control room modernizing efforts. As such, it was determined the most popular methods for measuring situation awareness, workload, and performance are measurements that rarely measure their intended construct directly and must be inferred. Physiological measures of workload have matured and become more accessible, sensitive, unobtrusive, valid, and objective but are reliant on variable technology. Situation Awareness measures possess little construct validity but eye-tracking technology is a measure progressing in sensitivity, objectivity, and continues to improve in unobtrusiveness. All things considered, this paper has identified a significant need for a more extensive review of the various performance measures used in modernizing control rooms and integrated system validation. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Status of the Measurement of Proton Scattering on Carbon Nuclei in EMPHATIC for Neutrino Flux Uncertainty Reduction

In long-baseline neutrino oscillation experiments, Monte Carlo (MC) simulations based on hadron interactions and decays are used to predict the neutrino flux. The 10%-level systematic uncertainty of the predicted neutrino fluxes from these simulations is dominated by uncertainties in hadron interaction cross sections due to limited hadron scattering data. EMPHATIC aims to reduce the neutrino flux uncertainty by providing additional data. Using a table-top-sized spectrometer located at the Fermilab Test Beam Facility (FTBF), its physics program includes precise measurements of hadron scattering and production cross sections at various beam momenta and target species that are relevant for GeV-scale neutrino production. Using simulation, we have developed a simple single-track reconstruction algorithm that has a momentum resolution of 3-4\%. We will demonstrate the progress in developing one of EMPHATIC’s first track reconstruction algorithms – an important step in making a new single-track forward scattering measurement (p + C $\rightarrow$ p + C at several beam momenta) using Phase 1 data collected between 2022 and 2023.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Advanced silicon tracking detector developments for the future Electron-Ion Collider

The proposed Electron-Ion Collider (EIC) will operate high-luminosity high-energy electron+proton and electron+nucleus collisions at the collision energies from 20 GeV to 141 GeV to solve several fundamental questions in the high energy and nuclear physics fields. Its instantaneous luminosity can reach 10 33-34 cm -2 s -1 and the bunching crossing rate is around 10 ns. The EIC project has received CD1 approval from the US DOE in 2021 and moves toward the machine design and preparation for construction. To realize various particle measurements with high precision at the future EIC, a low material-budget and high-granularity silicon vertex and tracking detector with fine spatial and momentum resolutions and nearly 4π solid angle coverage is desired. The Monolithic Active Pixel Sensor (MAPS) and AC Coupled Low Gain Avalanche Diode (AC-LGAD) technologies stand out of several advanced technology options for the EIC silicon vertex and tracking detector subsystems. The MAPS technology has advanced features of low material budget, low power consumption, good radiation resistance and fine spatial resolution. The AC-LGAD technology can achieve fast timing resolution. Latest studies and progress of the EIC silicon vertex and tracking detector conceptual design, performance validations in simulation and ongoing MAPS and AC-LGAD R&D will be shown. Furthermore, schedule and plan of the EIC project detector development will be discussed as well.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

A population data-driven workflow for COVID-19 modeling and learning

CityCOVID is a detailed agent-based model that represents the behaviors and social interactions of 2.7 million residents of Chicago as they move between and colocate in 1.2 million distinct places, including households, schools, workplaces, and hospitals, as determined by individual hourly activity schedules and dynamic behaviors such as isolating because of symptom onset. Disease progression dynamics incorporated within each agent track transitions between possible COVID-19 disease states, based on heterogeneous agent attributes, exposure through colocation, and effects of protective behaviors of individuals on viral transmissibility. Throughout the COVID-19 epidemic, CityCOVID model outputs have been provided to city, county, and state stakeholders in response to evolving decision-making priorities, while incorporating emerging information on SARS-CoV-2 epidemiology. Here we demonstrate our efforts in integrating our high-performance epidemiological simulation model with large-scale machine learning to develop a generalizable, flexible, and performant analytical platform for planning and crisis response.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Offshore Wind Market Report: 2023 Edition

The Offshore Wind Market Report: 2023 Edition provides detailed information on the U.S. and global offshore wind energy industries to inform policymakers, researchers, and analysts about technology, economic, and market trends. The scope of the report covers the status of over 293 global operating offshore wind energy projects as well as the broader global pipeline of projects in various stages of development through December 31, 2022. To provide up-to-date information and discussion on this emerging industry in the United States, this report tracks the significant U.S. domestic industry progress and events from January 1, 2022, through May 31, 2023. The U.S. offshore wind energy project development pipeline has reached a potential generating capacity of over 52 gigawatts, and the industry has seen strong support from state and federal governments (such as from the Inflation Reduction Act of 2022 and the announced Floating Offshore Wind Shot to reduce the cost of floating wind by 70%). There are contracts for over 17 gigawatts of the electricity from these offshore wind projects and state policies are in place to procure over 42 gigawatts by 2040. Although some projects are facing economic headwinds due to rising costs and higher interest rates (corresponding to project cost increases of 11% - 30% in 2022), there has still been significant investment in a domestic supply chain (including manufacturing facilities, new vessels, and upgraded or planned ports). Technologies continue to evolve as offshore wind turbines in the 15-megawatt class advance towards commercial production. Key offshore wind energy market indicators, such as commercial leasing, state energy planning targets, procurement policies, offtake agreements, and federal support for U.S. jobs and supply chain development, point toward sustained market growth when viewed together, but the macroeconomic hurdles facing the first generation of commercial projects could significantly stunt that growth.

17 WIND ENERGY↗
DOE OSTI2017

2015 China Green Low-Carbon City scorecard

In China’s rapid urbanization and industrialization, cities are playing important roles in helping the country reach its climate change mitigation goal of peaking CO2 emissions around 2030, and improving environmental quality. During the 12th Five-Year Plan (12th FYP) period (2011–2015), Chinese cities set ambitious goals and implemented diverse policies aimed at transitioning to a greener economy. The Chinese central government also set targets on a number of indicators, such economic energy intensity and carbon intensity (e.g., CO2 per unit GDP), and air quality (e.g., PM2.5 concentration). These targets are helpful for tracking implementation of individual policies or progress at a sectoral level. However, a more comprehensive and integrated approach is needed to assess progress and capture the multi-dimensional aspects of Chinese cities’ transition to a greener economy, an approach that offers comparison with international best practices, as well as working with data availability in China’s statistical system. This paper presents the development of a China Green LowCarbon City Index2 (CGLCCI, or City Index) and its application to 115 Chinese cities – the largest assessment of Chinese cities to date. The GCLCCI includes 23 key indicators across seven categories: economy, energy, industry, buildings, transportation, environment and land use, and climate policy and outreach. This paper applied the CGLCCI to benchmark the green and low-carbon development status of 115 Chinese cities in the year 2015. Data for the analysis came from government and publicly available data sources. The CGLCCI methodology provides a standardized method to benchmark each indicator, calculate overall city scores, and rank the cities.3 The results showed that the low-carbon transition in Chinese cities is still in its early stages. Compared to the best practices benchmarks, the 2015 City Index scores ranged from a low of 28 to a high score of 70 in 2015 (maximum score is 100). This paper also presents three top-performing cities in different stages of development and discusses how their scores across the index categories. Creating a green low-carbon index that relies on publicly available data in China, and regularly evaluating city performance, can encourage Chinese cities to learn best practices from each other, and to strengthen their goals and implementation efforts toward a green low-carbon transition.

Zhang, Jingjing↗
DOE OSTI2013

New Directions: GEIA’s 2020 Vision for Better Air Emissions Information

We are witnessing a crucial change in how we quantify and understand emissions of greenhouse gases and air pollutants, with an increasing demand for science-based transparent emissions information produced by robust community efforts. Today’s scientific capabilities, with near-real-time in-situ and remote sensing observations combined with forward and inverse models and a better understanding of the controlling processes, are contributing to this transformation and providing new approaches to derive, verify, and forecast emissions (Tong et al., 2011; Frost et al., 2012) and to quantify their impacts on the environment (e.g., Bond et al., 2013). At the same time, the needs for emissions information and the demands for their accuracy and consistency have grown. Changing economies, demographics, agricultural practices, and energy sources, along with mandates to evaluate emissions mitigation efforts, demonstrate compliance with legislation, and verify treaties, are leading to new challenges in emissions understanding. To quote NOAA Senior Technical Scientist David Fahey, "We are in the Century of Accountability. Emissions information is critical not only for environmental science and decision-making, but also as an instrument of foreign policy and international diplomacy." Emissions quantification represents a key step in explaining observed variability and trends in atmospheric composition and in attributing these observed changes to their causes. Accurate emissions data are necessary to identify feasible controls that reduce adverse impacts associated with air quality and climate and to track the success of implemented policies. To progress further, the international community must improve the understanding of drivers and contributing factors to emissions, and it must strengthen connections among and within different scientific disciplines that characterize our environment and entities that protect the environment and influence further emissions. The Global Emissions InitiAtive, GEIA (http://www.geiacenter.org/), is a center for emissions information exchange and competence building created in 1990 in response to the need for high quality global emissions data (Graedel et al., 1993). While the past two decades have seen considerable progress in developing, improving and assessing emission estimates, emissions continue to be a major contributor to overall uncertainty in atmospheric model simulations. Moving forward, GEIA aims to help build emissions knowledge in a rapidly evolving society by: 1) enhancing understanding, quantification, and analysis of emissions processes; 2) improving access to emissions information; and 3) strengthening the community of emissions groups involved in research, assessment, operations, regulation and policy.

Frost, G. J.↗
DOE OSTI2025

Mesoporous Thin Film Architectures: Addressing Material Demands through Molecular Self-Assembly

Mesoporous thin films spark interest across a wide range of disciplines due to their tunable nanostructures, large internal surface areas, and strong compatibility with planar optical, electronic, and microfluidic devices. While attention in the porous materials community has shifted toward macroporous or disordered nanoporous systems, a resurgence in mesoporous thin film research is underway, driven by new molecular self-assembly methods, advanced materials chemistry, and improved characterization techniques. The integration of high-χN block copolymer design, kinetically persistent micelle templating, and postdeposition processing protocols now allows control over structural parameters such as pore size, wall thickness, porosity, and connectivity. These advances have overcome many of the thermodynamic and processing constraints that previously limited widespread adoption. Rather than serving only as high-surface-area supports, mesoporous thin films are engineered as active interfaces where responsive chemistries and nanoscale confinement act in tandem. Embedding switchable ligands, thermoresponsive polymers, redox mediators, or ion-selective groups directly within the pore walls enables real-time control over transport, optical, and electrochemical properties. These capabilities open up new directions in adaptive coatings, gated membranes, and fast-response biosensors. To further expand their functional scope, mesoporous films are integrated into hierarchical and multicomponent architectures. Techniques such as triblock terpolymer templating, crack-directed assembly, and nanoimprint lithography allow for control over spatial organization on the micron and submicron scale and pore system orientation. This enables programmable anisotropy, enhanced molecular diffusion, and wavelength-selective photonic behavior, essential for next-generation sensing, catalysis, and energy applications. Such structural and functional complexity requires equally sophisticated characterization. Multimodal and in situ techniques can track material dynamics under operational conditions. Recent progress includes extended-range ellipsometric porosimetry (EP) for hierarchical architectures, vacuum EP for interface energetics, time-resolved EP for diffusion kinetics, and correlative AFM-SAXS mapping. The introduction of advanced neutron-based spectroscopies, particularly quasielastic neutron scattering (QENS), promises to provide real-time access to ion transport dynamics and segmental motion under nanoscale confinement, offering a path toward deeper mechanistic understanding of structure-performance correlations in mesoporous systems. This Account reflects the technical advances made and the interdisciplinary collaborations that have shaped our collective vision. The particular dimensions of mesopores enable us to subtly tune interactions at the molecular, interfacial, and mesoscopic levels that permit us to harness nanoconfinement. What emerges is a versatile, modular platform capable of chemical gating, energy transduction, and sensing with a level of tunability unmatched by other porous materials. We highlight critical challenges including the need for more robust large-area processing, a deeper understanding of dynamic behavior under cycling, and better integration with device-level architectures. Our strategies support the transition of mesoporous thin films into active high-performance components in next-generation energy, environmental, and biomedical systems.

oxides↗
DOE OSTI2022

Quantifying the regional stranded asset risks from new coal plants under 1.5 °C

Momentum to phase out unabated coal use is growing globally. This transition is critical to meeting the Paris climate goals but can potentially lead to large amounts of stranded assets, especially in regions with newer and growing coal fleets. Here we combine plant-level data with a global integrated assessment model to quantify changes in global stranded asset risks from coal-fired power plants across regions and over time. With new plant proposals, cancellations, and retirements over the past five years, global net committed emissions in 2030 from existing and planned coal plants declined by 3.3 GtCO 2 (25%). While these emissions are now roughly in line with initial Nationally Determined Contributions (NDCs) to the Paris Agreement, they remain far off track from longer-term climate goals. Progress made in 2021 towards no new coal can potentially avoid a 24% (503 GW) increase in capacity and a 55% ($520 billion) increase in stranded assets under 1.5 °C. Stranded asset risks fall disproportionately on emerging Asian economies with newer and growing coal fleets. Recent no new coal commitments from major coal financers can potentially reduce stranding of international investments by over 50%.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Probing Microplasticity in Small-Scale FCC Crystals via Dynamic Mechanical Analysis

In small-scale metallic systems, collective dislocation activity has been correlated with size effects in strength and with a steplike plastic response under uniaxial compression and tension. Yielding and plastic flow in these samples is often accompanied by the emergence of multiple dislocation avalanches. Dislocations might be active preyield, but their activity typically cannot be discerned because of the inherent instrumental noise in detecting equipment. We apply alternate current load perturbations via dynamic mechanical analysis during quasistatic uniaxial compression experiments on single crystalline Cu nanopillars with diameters of 500 nm and compute dynamic moduli at frequencies 0.1, 0.3, 1, and 10 Hz under progressively higher static loads until yielding. By tracking the collective aspects of the oscillatory stress-strain-time series in multiple samples, we observe an evolving dissipative component of the dislocation network response that signifies the transition from elastic behavior to dislocation avalanches in the globally preyield regime. We postulate that microplasticity, which is associated with the combination of dislocation avalanches and slow viscoplastic relaxations, is the cause of the dependency of dynamic modulus on the driving rate and the quasistatic stress. We construct a continuum mesoscopic dislocation dynamics model to compute the frequency response of stress over strain and obtain a consistent agreement with experimental observations. The results of our experiments and simulations present a pathway to discern and quantify correlated dislocation activity in the preyield regime of deforming crystals.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Benchmarking U.S. Small Wind Costs with the Distributed Wind Taxonomy

The objective of this report is to benchmark costs for small wind projects installed in the United States using a distributed wind taxonomy. Consequently, this report is a starting point to help expand the U.S. distributed wind market by informing potential areas for small wind cost-reduction opportunities and providing a benchmark to track future small wind cost-reduction progress.

17 WIND ENERGY↗