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DOE OSTI2023

Accelerating Informed Local Climate Action by Improving Access to DOE Predictive Modeling and Science-Based Tools

The threat of climate change is becoming increasingly urgent, and local governments across the United States are working to develop and implement climate action plans to reduce greenhouse gas emissions and mitigate the impacts of climate change. At the same time, the U.S. Department of Energy's Office of Science, Earth and Environmental Systems Sciences Division (EESSD) has been developing a range of tools and technologies to help predict the potential multi-faceted impacts from climate change given varying environmental and socioeconomic scenarios. However, local governments have been slow to engage with these scientific assets due to a lack of understanding and awareness. The DOE researchers interviewed highlighted three primary types of resources that could benefit local governments and climate practitioners: climate models, modeled datasets, and scientific journal articles. Although many of these resources are open source and available to the public, there were several challenges identified in translating these resources and their research insights directly to decision-makers.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Systematic comparison of local approaches for isotopically nonstationary metabolic flux analysis

Quantification of reaction fluxes of metabolic networks can help us understand how the integration of different metabolic pathways determine cellular functions. Yet, intracellular fluxes cannot be measured directly but are estimated with metabolic flux analysis (MFA) that relies on the patterns of isotope labeling of metabolites in the network. For metabolic systems, typical for plants, where all potentially labeled atoms effectively have only one source atom pool, only isotopically nonstationary MFA can provide information about intracellular fluxes. There are several global approaches that implement MFA for an entire metabolic network and estimate, at once, a steady-state flux distribution for all reactions with identifiable fluxes in the network. In contrast, local approaches deal with estimation of fluxes for a subset of reactions, with smaller data demand for flux estimation. Here we present a systematic comparative review and benchmarking of the existing local approaches for isotopically nonstationary MFA. The comparison is conducted with respect to the required data and underlying computational problems solved on a synthetic network example. Furthermore, we benchmark the performance of these approaches in estimating fluxes for a subset of reactions using data obtained from the simulation of nitrogen fluxes in the Arabidopsis thaliana core metabolism. The findings pinpoint practical aspects that need to be considered when applying local approaches for flux estimation in large-scale plant metabolic networks.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Calibration and Localization of Optically Pumped Magnetometers Using Electromagnetic Coils

In this paper, we propose a method to estimate the position, orientation, and gain of a magnetic field sensor using a set of (large) electromagnetic coils. We apply the method for calibrating an array of optically pumped magnetometers (OPMs) for magnetoencephalography (MEG). We first measure the magnetic fields of the coils at multiple known positions using a well-calibrated triaxial magnetometer, and model these discreetly sampled fields using vector spherical harmonics (VSH) functions. We then localize and calibrate an OPM by minimizing the sum of squared errors between the model signals and the OPM responses to the coil fields. We show that by using homogeneous and first-order gradient fields, the OPM sensor parameters (gain, position, and orientation) can be obtained from a set of linear equations with pseudo-inverses of two matrices. The currents that should be applied to the coils for approximating these low-order field components can be determined based on the VSH models. Computationally simple initial estimates of the OPM sensor parameters follow. As a first test of the method, we placed a fluxgate magnetometer at multiple positions and estimated the RMS position, orientation, and gain errors of the method to be 1.0 mm, 0.2°, and 0.8%, respectively. Lastly, we calibrated a 48-channel OPM array. The accuracy of the OPM calibration was tested by using the OPM array to localize magnetic dipoles in a phantom, which resulted in an average dipole position error of 3.3 mm. The results demonstrate the feasibility of using electromagnetic coils to calibrate and localize OPMs for MEG.

47 OTHER INSTRUMENTATION↗

DOE OSTI2016

Mutation of the rice XA21 predicted nuclear localization sequence does not affect resistance to Xanthomonas oryzae pv. oryzae

Background: The rice receptor kinase XA21 confers robust resistance to the bacterial pathogen Xanthomonas oryzae pv. oryzae ( Xoo ). We previously reported that XA21 is cleaved in transgenic plants overexpressing XA21 with a GFP tag ( Ubi -XA21-GFP) and that the released C-terminal domain is localized to the nucleus. XA21 carries a predicted nuclear localization sequence (NLS) that directs the C-terminal domain to the nucleus in transient assays, whereas alanine substitutions in the NLS disrupt the nuclear localization. Methods: To determine if the predicted NLS is required for XA21-mediated immunity in planta , we generated transgenic plants overexpressing an XA21 variant carrying the NLS with the same alanine substitutions ( Ubi -XA21nls-GFP). Results: Ubi- XA21nls-GFP plants displayed slightly longer lesion lengths, higher Xoo bacterial populations after inoculation and lower levels of reactive oxygen species production compared with the Ubi- XA21-GFP control plants. However, the Ubi- XA21nls-GFP plants express lower levels of protein than that observed in Ubi- XA21-GFP. Discussion: These results demonstrate that the predicted NLS is not required for XA21-mediated immunity.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2004

Local oscillator distribution using a geostationary satellite

A satellite communication system suitable for distribution of local oscillator reference signals for a widely spaced microwave array has been developed and tested experimentally. The system uses a round-trip correction method of the satellite This experiment was carried out using Telstar-5, a commercial Ku-band geostationary satellite. For this initial experiment, both earth stations were located at the same site to facilitate direct comparison of the received signals. The local oscillator reference frequency was chosen to be 300MHz and was sent as the difference between two Ku-band tones. The residual error after applying the round trip correction has been measured to be better than 3psec for integration times ranging from 1 to 2000 seconds. For integration times greater then 500 seconds, the system outperforms a pair of hydrogen masers with the limitation believed to be ground-based equipment phase stability. The idea of distributing local oscillators using a geostationary satellite is not new; several researchers experimented with this technique in the eighties, but the achieved accuracy was 3 to 100 times worse than the present results. Since substantially and the performance of various components has improved. An important factor is the leasing of small amounts of satellite communication bandwidth. We lease three 100kHz bands at approximately one hundredth the cost of a full 36 MHz transponder. Further tests of the system using terminal separated by large distances and comparison tests with two hydrogen masers and radio interferometry is needed.

hydrogen maser↗

NASA NTRS2005

Vision Based Localization in Urban Environments

As part of DARPA's MARS2020 program, the Jet Propulsion Laboratory developed a vision-based system for localization in urban environments that requires neither GPS nor active sensors. System hardware consists of a pair of small FireWire cameras and a standard Pentium-based computer. The inputs to the software system consist of: 1) a crude grid-based map describing the positions of buildings, 2) an initial estimate of robot location and 3) the video streams produced by each camera. At each step during the traverse the system: captures new image data, finds image features hypothesized to lie on the outside of a building, computes the range to those features, determines an estimate of the robot's motion since the previous step and combines that data with the map to update a probabilistic representation of the robot's location. This probabilistic representation allows the system to simultaneously represent multiple possible locations, For our testing, we have derived the a priori map manually using non-orthorectified overhead imagery, although this process could be automated. The software system consists of two primary components. The first is the vision system which uses binocular stereo ranging together with a set of heuristics to identify features likely to be part of building exteriors and to compute an estimate of the robot's motion since the previous step. The resulting visual features and the associated range measurements are software component, a particle-filter based localization system. This system uses the map and the then fed to the second primary most recent results from the vision system to update the estimate of the robot's location. This report summarizes the design of both the hardware and software and will include the results of applying the system to the global localization of a robot over an approximately half-kilometer traverse across JPL'S Pasadena campus.

unmanned-ground vehicles↗

NASA NTRS2014

The Origin of the Local 1/4-KeV X-Ray Flux in Both Charge Exhange and a Hot Bubble

The solar neighbourhood is the closest and most easily studied sample of the Galactic interstellar medium, an understanding of which is essential for models of star formation and galaxy evolution. Observations of an unexpectedly intense diffuse flux of easily absorbed 1/4-kiloelectronvolt X-rays coupled with the discovery that interstellar space within about a hundred parsecs of the Sun is almost completely devoid of cool absorbing gas, led to a picture of a 'local cavity' filled with X-ray-emitting hot gas, dubbed the local hot bubble. This model was recently challenged by suggestions that the emission could instead be readily produced within the Solar System by heavy solar-wind ions exchanging electrons with neutral H and He in interplanetary space, potentially removing the major piece of evidence for the local existence of million-degree gas within the Galactic disk. Here we report observations showing that the total solar wind charge-exchange contribution is approximately 40 percent of the 1/4-keV flux in the Galactic plane. The fact that the measured flux is not dominated by charge exchange supports the notion of a million-degree hot bubble extending about a hundred parsecs from the Sun.

Charge exhange and a hot bubble↗

NASA NTRS2024

Machine Learning for the Prediction of Local Asteroid Damages

Risk assessment studies of local asteroid hazards traditionally simulate the physics of meteors with engineering models tailored to analyze tens-of-millions of scenarios. However, these simplified approaches still need to solve time-dependent ODEs to model the entry process and the resulting ground damage. With a computational cost of O(0.01 CPU.s) per scenario, simulating these large numbers of potential entry conditions in risk assessment studies can take several days on local computers. To improve computational efficiency, we propose in this paper an orthogonal approach based on machine learning models to predict the size of damaged areas given a list of entry parameters. We train 5 machine learning methods and compare the predictions to the outputs of the PAIR model, first only with primitive entry condition variables, and then with more advanced features. We find that complex models like neural networks are well-suited to estimate blast hazards, while simpler linear models can accurately assess thermal damage. For both types of hazards, the radii of damaged areas can be predicted with around 10% average errors and a coefficient of determination (R2) of 0.99. The CPU time is decreased by a factor O(10 3 ) compared to the PAIR model, which enables the simulation of millions of scenarios in minutes, on a local computer. We then use the same machine learning approaches for a classification task where the models are trained to predict if an asteroid will produce a given level of damage. Results show that complex models like the gradient boosting classifier and the neural network can perform this task with 98% accuracy. Beyond surrogate models, we finally incorporate the machine learning algorithms to the state-of-the-art Shapley sensitivity analysis and present a ranking of the entry parameters based on their contributions to ground damages.

SMD↗

DOE OSTI2019

State and Local Planning for Energy (SLOPE) Platform: Overview

The State and Local Planning for Energy (SLOPE) Platform, a collaboration between eight U.S. Department of Energy (DOE) technology offices and the National Renewable Energy Laboratory (NREL), is a tool to enable more data-driven state and local energy planning by integrating dozens of distinct sources of energy efficiency, renewable energy, and sustainable transportation data and analyses into an easy-to-access online platform that more effectively supports state and local energy planning and decision making.

State and Local Planning for Energy Platform, SLOP↗

DOE OSTI2023

Waste-to-Energy Technical Assistance for Local Governments

The goal of this project is to mobilize data, information, and knowledge generated about organic waste streams to local governments and support their decision-making. It builds on previous work related to wet organic waste resources (food waste, sludge, manure, waste fats and oils). The project provides an improved understanding of local waste challenges and priorities to inform BETO's R&D strategies and decision-making. It also supports local governments' goals and plans related to sustainable waste management, enables energy and/or resource recovery projects development at municipal level, and facilitates public-private partnerships. A key challenge is associated with more activities requested by entities than program allows which is mitigated by prioritization by requesting agency. All FY21 and FY22 TA requests have been completed. Major accomplishments include: 1). 34 requests managed in the past two years, 2) Distilled key challenges faced by communities. Key outcomes include strong community participation since inception of the program, dedicated program web site, deliverables tailored to communities' needs, and distribution materials (e.g., fact sheets, brochures) for a broader audience.

BIOMASS FUELS↗

DOE OSTI2026

Lessons Learned from the Energy to Communities (E2C) Peer-Learning Cohort on Engaging with Electric Utilities for Successful Local Partnerships

NLR designed and led a six-month peer-learning cohort from July through December 2025 on “Engaging With Electric Utilities for Successful Local Partnerships” as part of the U.S. Department of Energy’s Energy to Communities (E2C) program. Representatives from 15 local and regional governments from across the United States participated in monthly workshops covering best practices for engaging with their utilities to advance their own energy goals. This document shares key takeaways, lessons learned, and resources from the cohort that may be useful to local governments, regional governments, or Tribes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2017

San Jose, California: Evaluating Local Solar Energy Generation Potential (City Energy: From Data to Decisions)

This fact sheet "San Jose, California: Evaluating Local Solar Energy Generation Potential" explains how the City of San Jose used data from the U.S. Department of Energy's Cities Leading through Energy Analysis and Planning (Cities-LEAP) and the State and Local Energy Data (SLED) programs to inform its city energy planning. It is one of ten fact sheets in the "City Energy: From Data to Decisions" series.

Cities leading through energy analysis and plannin↗

DOE OSTI2022

Large Exchange Coupling Between Localized Spins and Topological Bands in MnBi 2 Te 4

Magnetism in topological materials creates phases exhibiting quantized transport phenomena with potential technological applications. The emergence of such phases relies on strong interaction between localized spins and the topological bands, and the consequent formation of an exchange gap. However, this remains experimentally unquantified in intrinsic magnetic topological materials. Here, this interaction is quantified in MnBi 2 Te 4 , a topological insulator with intrinsic antiferromagnetism. This is achieved by optically exciting Bi-Te p states comprising the bulk topological bands and interrogating the consequent Mn 3d spin dynamics, using a multimodal ultrafast approach. Ultrafast electron scattering and magneto-optic measurements show that the p states demagnetize via electron-phonon scattering at picosecond timescales. Despite being energetically decoupled from the optical excitation, the Mn 3d spins, probed by resonant X-ray scattering, are observed to disorder concurrently with the p spins. Together with atomistic simulations, this reveals that the exchange coupling between localized spins and the topological bands is at least 100 times larger than the superexchange interaction, implying an optimal exchange gap of at least 25 meV in the surface states. Here, by quantifying this exchange coupling, this study validates the materials-by-design strategy of utilizing localized magnetic order to manipulate topological phases, spanning static to ultrafast timescales.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Sub‐Diffraction Correlation of Quantum Emitters and Local Strain Fields in Strain‐Engineered WSe 2 Monolayers

Strain-engineering in atomically thin metal dichalcogenides is a useful method for realizing single-photon emitters (SPEs) for quantum technologies. Correlating SPE position with local strain topography is challenging due to localization inaccuracies from the diffraction limit. Currently, SPEs are assumed to be positioned at the highest strained location and are typically identified by randomly screening narrow-linewidth emitters, of which only a few are spectrally pure. In this work, hyperspectral quantum emitter localization microscopy is used to locate 33 SPEs in nanoparticle-strained WSe 2 monolayers with sub-diffraction-limit resolution (≈30 nm) and correlate their positions with the underlying strain field via image registration. In this system, spectrally pure emitters are not concentrated at the highest strain location due to spectral contamination; instead, isolable SPEs are distributed away from points of peak strain with an average displacement of 240 nm. These observations point toward a need for a change in the design rules for strain-engineered SPEs and constitute a key step toward realizing next-generation quantum optical architectures.

2D material↗

DOE OSTI2022

Persona of Transition Metal Ions in Solids: A Statistical Learning on Local Structures of Transition Metal Oxides

Abstract The local structure of a transition metal (TM) ion is a function of cation elements and valence states. More than that, in this work, by employing a trove of first‐principles data of TM oxides, the local structures of TM cations are statistically analyzed to extract detailed information about cation site preference, bond length, site structural distortion, and cation magnetization. It is found that cation radius alone poorly describes the local structure of a transition metal oxide, while the statistics of coordination number as well as the TMO bond length distribution, especially that of the 3d TMs, can provide comprehensive knowledge for understanding the behavior of TM elements. Based on these statistics, the interplay of site distortion due to the Jahn–Teller effect, cation site similarity, and a new set of ionic radii are all obtained to chart the “persona” of transition metal ions in solids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

High Thermoelectric Performance in p-type Polycrystalline Cd-doped SnSe Achieved by a Combination of Cation Vacancies and Localized Lattice Engineering

In this paper, a high figure of merit ( ZT ) of ≈1.7 at 823 K is reported in p-type polycrystalline Cd-doped SnSe by combining cation vacancies and localized-lattice engineering. It is observed that the introduction of Cd atoms in SnSe lattice induce Sn vacancies, which act as p-type dopants. A combination of facile solvothermal synthesis and fast spark plasma sintering technique boosts the Sn vacancy to a high level of ≈2.9%, which results in an optimum hole concentration of ≈2.6 × 10 19 cm -3 and an improved power factor of ≈6.9 µW cm -1 K -2 . Simultaneously, a low thermal conductivity of ≈0.33 W m -1 K -1 is achieved by effective phonon scattering at localized crystal imperfections, as observed by detailed structural characterizations. Density functional theory calculations reveal that the role of Cd atoms in the SnSe lattice is to reduce the formation energy of Sn vacancies, which in turn lower the Fermi level down into the valence bands, generating holes. This work explores the fundamental Cd-doping mechanisms at the nanoscale in a SnSe matrix and demonstrates vacancy and localized-lattice engineering as an effective approach to boosting thermoelectric performance. The work provides an avenue in achieving high-performance thermoelectric properties of materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Probe the Localized Electrochemical Environment Effects and Electrode Reaction Dynamics for Metal Batteries using In Situ 3D Microscopy

Uncontrollable dendrite growth is closely related to non-uniform reaction environments. However, there is a lack of understanding and analysis methods to probe the localized electrochemical environment (LEE). Here the effects of the LEE are investigated, including localized ion concentrations, current density, and electric potential, on metal plating/stripping dynamics and dendrite minimization. A novel in situ 3D microscopy technique is developed to image the morphology dynamics and deposition rate of Zn plating/stripping processes on 3D Zn–Mn anodes. Using the in situ 3D microscope, the electrode morphology changes during the reactions are directly imaged and Zn deposition rate maps at different time points are obtained. It is found that reaction kinetics are highly correlated to LEE and electrode morphology. To further quantify the LEE effects, the digital twin technique is employed that allows the accurate calculation of the electrochemical environments, such as localized ion concentrations, current density, and electric potential, which cannot be directly measured from experiments. We found that the curvature of the 3D electrode surface determines the LEE and significantly influences reaction kinetics. This provides a new strategy to minimize the dendrite formation by designing and optimizing the 3D geometry of the electrode to control the LEE.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Accelerated Short Circuiting in Anode-Free Solid-State Batteries Driven by Local Lithium Depletion

“Anode-free” solid-state batteries (SSBs), which have no anode active material, can exhibit extremely high energy density (≈1500 Wh L -1 ). However, there is a lack of understanding of the lithium plating/stripping mechanisms at initially lithium-free solid-state electrolyte (SSE) interfaces because excess lithium metal is often used. Here, it is demonstrated that commercially relevant quantities of lithium (>5 mAh cm -2 ) can be reliably plated at moderate current densities (1 mA cm -2 ) using the sulfide SSE Li 6 PS 5 Cl. Investigations of lithium plating/stripping mechanisms, in conjunction with cryo-ocused ion beam (FIB) imaging, synchrotron tomography, and phase-field modeling, reveal that the cycling stability of these cells is fundamentally limited by the nonuniform presence of lithium during stripping. Local lithium depletion causes isolated lithium regions toward the end of stripping, decreasing electrochemically active area and resulting in high local current densities and void formation. This accelerates subsequent filament growth and short circuiting compared to lithium-excess cells. Despite this degradation mode, here it is shown that anode-free cells exhibit comparable Coulombic efficiency to lithium-excess cells, and improved resistance to short circuiting is achieved by avoiding local lithium depletion through retention of thicker lithium at the interface. These new insights provide a foundation for engineering future high-energy anode-free SSBs.

25 ENERGY STORAGE↗