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At least 343 records · Page 19

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DOE OSTI2024

In-flight performance of S PIDER'S 280-GHz receivers

S PIDER is a balloon-borne instrument designed to map the cosmic microwave background at degree-angular scales in the presence of Galactic foregrounds. S PIDER has mapped a large sky area in the Southern Hemisphere using more than 2000 transition-edge sensors (TESs) during two NASA Long Duration Balloon flights above the Antarctic continent. During its first flight in January 2015, S PIDER observed in the 95 GHz and 150 GHz frequency bands, setting constraints on the B-mode signature of primordial gravitational waves. Its second flight in the 2022-23 season added new receivers at 280 GHz, each using an array of TESs coupled to the sky through feedhorns formed from stacks of silicon wafers. Here, these receivers are optimized to produce deep maps of polarized Galactic dust emission over a large sky area, providing a unique data set with lasting value to the field. In this work, we describe the instrument’s performance during S PIDER'S second flight.

280 GHz cosmology↗

DOE OSTI2020

Origin and mitigation of wind noise on balloon-borne infrasound microbarometers

High-altitude monitoring of low-frequency acoustic waves (infrasound) on Earth has regained prominence in recent years, primarily driven by improvements in light-weight sensor technology and advances in scientific ballooning techniques. Balloon-borne infrasound monitoring is also being proposed as a remote sensing technique for planetary exploration. Contrary to ground-based infrasound monitoring, the infrasound noise background in the stratosphere as measured by a balloon remains uncharacterized and the efficacy of wind noise mitigation filters has not been investigated. In this study, an analysis of pressure data collected using infrasound microbarometers during the flight of a long-duration zero pressure balloon is presented. Here, a dramatic reduction of background noise in the stratosphere is demonstrated and it is shown that wind noise mitigation filters are not effective at reducing wind noise under these conditions. Results from this study demonstrate stratospheric balloons as a low-noise platform for infrasound monitoring and motivate the development of improved noise mitigation tools.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Ambient Temperature Sodium Polysulfide Catholyte for Nonaqueous Redox Flow Batteries

This study reports a sodium polysulfide catholyte for nonaqueous redox flow batteries (RFBs). We demonstrate reversible capacities up to 200 mAh/gS with negligible fade over 250 cycles at room temperature for sodium polysulfide|biphenyl full cells containing Na + ß '' -Al 2 O 3 solid electrolyte (BASE) membranes. Interestingly, formation of insoluble S and Na 2 S 4 phases did not inhibit the catholyte's cycle life which is likely due to the low concentrations used in the lab-scale prototypes. 3-electrode galvanostatic AC impedance measurements demonstrate that voltage losses were dominated by charge transfer at the cathode, and relevant kinetic parameters (i.e., transfer coefficients and exchange current density) were calculated through a Tafel analysis. To the best of our knowledge, this is the first report applying such an impedance approach to nonaqueous RFBs. Overall, the use of low-cost active materials makes sodium polysulfide|biphenyl RFBs promising for long duration energy storage applications. Furthermore, if strategies are developed to increase the solubility of S and/or low order polysulfides (Na 2 S x , x ≤ 4), specific energies up to 100 Wh kg -1 (including combined mass of the anolyte and catholyte) can be achieved.

25 ENERGY STORAGE↗

DOE OSTI2021

Electrolyte Takeover Strategy for Performance Recovery in Polysulfide-Permanganate Flow Batteries

The abundance of active material precursors for a polysulfide-permanganate flow battery makes it a compelling chemistry for large-scale, and potentially long-duration (>10 h), grid electricity storage. Precipitation, arising from either reactant crossover or electrolyte side reactions, decrease cell efficiencies during charge/discharge cycling. Regardless of the abundance and low cost of active materials, a system without high cyclability cannot meet grid electricity storage economic targets for applications that cycle regularly. Precipitated species can be removed, and reactor efficiency performance restored, by using an electrolyte takeover process, or ETP. Two ETP methods are investigated. One ETP uses the negative electrolyte, an alkaline polysulfide (pS) solution, as takeover solution, and another uses dilute acidic peroxide (DAP) as the takeover solution. Both ETPs maintain functional cell operation within an acceptable performance range over >1000 h and >200 cycles, a duration over which cells that do not undergo ETPs clog and fail. The DAP ETP proves especially effective and limits irrecoverable voltage efficiency fade below 0.02%/cycle. These ETPs, either individually, or in combination, can enable the requisite cyclability for practical polysulfide-permanganate flow battery systems.

25 ENERGY STORAGE↗

DOE OSTI2022

Electrochemical Stability and Reversibility of Aqueous Polysulfide Electrodes Cycled Beyond the Solubility Limit

Batteries which use dissolved redox-active species, such as redox flow batteries (RFBs), are often considered to be constrained in their operation and energy density by the solubility limit of the redox species. Here, we show that soluble redox active electrolytes can be reversibly cycled deeply into the precipitation regime, permitting higher effective concentrations, energy densities, and lower costs. Using aqueous sodium polysulfide negative electrolytes cycled in the nominal Na 2 S 2 to Na 2 S 4 capacity range as an example, we show that the effective solubility can be increased from 5 M in the fully-dissolved state to as much as 10 M using the precipitation strategy. Stable cycling was observed at 8 M concentration over more than 1600h at room temperature. We also analyze the range of polysulfide electrochemical stability, and characterize the precipitate composition. This enhanced effective concentration approach may be generalized to other redox chemistries that utilize solubilized reactants, and may be especially useful for long-duration storage applications where slow charge-discharge rates allow equilibration of precipitated species with the redox-active solution.

25 ENERGY STORAGE↗

DOE OSTI2026

Quantifying Energy Storage Density Utilization Trends in Redox Flow Battery Chemistries

The transition to new energy resources is driving the need for efficient energy storage. Redox flow batteries (RFBs) are a promising solution due to their flexible design and safer materials, particularly for long-duration storage applications. Despite these advantages, RFB technologies still have considerable room for growth in terms of utilizing all of their available energy storage density. Herein, we assess RFB energy storage density utilization trends for multiple chemistries by accounting for their unique thermodynamic limits, energy efficiencies, and charge capacity constraints. Of the RFBs chemistries analyzed, most still use less than 60% of their theoretical energy storage capacity. The conventional all-vanadium RFB was the closest to its thermodynamic limit available. Moreover, the volumetric footprint and electrolyte cost analyses demonstrate the real-world implications of these inefficiencies. This analysis further indicates that future studies would benefit from clearer reporting of two key quantities: discharge efficiency, which is more directly tied to practically recoverable energy density than round-trip energy efficiency, and state-of-charge or capacity-utilization limits, which govern access to theoretical storage capacity. More consistent reporting of these factors would improve the accuracy and comparability of energy storage utilization analyses across RFB chemistries.

battery energy storage↗

DOE OSTI2026

Binder-Stabilized Carbon Fiber Hosts for High-Utilization Sodium–Polysulfide Flow Catholytes

Sodium-sulfur (Na-S) batteries hold promise as high-energy-density batteries for long-duration energy storage due to their high open circuit voltage and Earth-abundant active materials. However, low utilization of the sulfur active material limits the achievable specific capacity, especially when a liquid polysulfide catholyte is utilized. High-surface-area carbon materials demonstrate promise to increase sulfur utilization in a Na-S battery. To make the carbon host material applicable for a flow battery application, a binder is required to bind the carbon materials together and to a porous substrate. Here, we utilize a composite carbon paper electrode coated by polymer,carbon nanofibers (CNFs) and carbon black (CB). By varying the mass ratios of CNF to CB, we found that a 70/20/10 mass ratio of CNF/CB/binder provided the highest capacity (260 mAh g −1 compared to the baseline of 156 mAh g −1 ) and stable battery performance over 100 cycles. Analysis of the composite electrode and full cells reveals that the amount of CB in the composite electrode influences binder distribution, cell resistance, and full cell performance.

Lehmann, Michelle L. [Oak Ridge National Laborator↗

DOE OSTI2020

Parameter Optimization Toolbox for NS-3 network optimization, NS-3 Parameter Optimization Framework [SWR-18-60]

This simulation-based parameter optimization framework is proposed to tune parameters of different types of communication networks using ns-3 to achieve the optimal network performance. It consists of three main components: an ns-3 packet reporting module; a sampler running simulations with all possible parameter sets for the input parameter variables by using a parallel executor at each generation; and a hybrid optimization algorithm for tuning configurable parameters of hybrid designs and application parameter variables. The proposed hybrid metaheuristic optimization algorithm combines an evolutionary algorithm with a gradient descent function to quickly achieve an approximate globally optimum solution. This software is designed to be used in a multi-core processing Linux environment and run over a long duration of time. The execution time varies depending mainly upon the nature of the ns-3 configuration being simulated. This software includes a custom ns-3 QoS measurement application which must be included with the ns-3 source code during installation of the software.

Hasandka, Adarsh↗

DOE OSTI2020

RODeO (Revenue Operation and Device Optimization Model) [SWR 20-67]

The Revenue, Operation, and Device Optimization (RODeO) model explores optimal system design and operation considering different levels of grid integration, equipment cost, operating limitations, financing, and credits and incentives. RODeO is a price-taker model formulated as a mixed-integer linear programming (MILP) model in the GAMS modeling platform. The objective is to maximizes the net revenue for a collection of equipment at a given site. The equipment includes generators (e.g., gas turbine, steam turbine, solar, wind, hydro, fuel cells, etc.), storage systems (batteries, pumped hydro, gas-fired compressed air energy storage, long-duration systems, hydrogen), and flexible loads (e.g., electric vehicles, electrolyzers, flexible building loads). The input data required by RODeO can be classified into three bins: 1) utility service data, which refers to retail utility rate information (meter cost, energy and demand charges), 2) electricity market data, which include energy and reserve prices, 3) other inputs, which refer to additional electrical demand, product output demand, technological assumptions, financial properties, and operational parameters.

Guerra Fernandez, Omar Jose↗

DOE OSTI2023

SDOM (Storage Deployment Optimization Model) [SWR-21-73]

SDOM is designed to accurately represent the operation of energy storage across different timescales, including long-duration and seasonal applications, and the spatiotemporal diversity and complementarity among VRE sources. SDOM uses an hourly temporal resolution, a fine spatial resolution for VRE sources, and a 1-year optimization window. SDOM assumes that all builds of VRE are accompanied by sufficient additional transmission capacity to allow full utilization of these additional resources. Nuclear, hydropower, and other renewable generation (e.g., biomass and geothermal energy sources) are fixed based on operational data (time series) for a given year; thus, SDOM minimizes total system cost using conventional generators as balancing units and using VRE and storage technologies to achieve a user-defined carbon-free or renewable energy target. The total system cost includes capital costs, fixed operation-and-maintenance (FO&M) costs, variable operation-and-maintenance (VO&M) costs, and fuel cost for power generation and storage technologies.

Guerra Fernandez, Omar Jose↗

DOE OSTI2025

MolSieve

Visual analytics system for analyzing long-duration molecular dynamics trajectories.

Hnatyshyn, Rostyslav [@VADERASU]↗

DOE OSTI2023

Quantification and prediction of error in MIMO tests

Dynamic testing of systems is most realistic of real-world conditions when multiple input and multiple output (MIMO) techniques are used. To replicate measured environmental conditions, a series of desired outputs (responses) on the system must be realized by inverting the frequency response functions (FRF) matrix for input estimation. System identification is dependent on the number of inputs and outputs, which affect the type of solutions. In input estimation, the auto spectra of the determined inputs are affected by both the auto spectra and cross spectra of the desired outputs. This research evaluates errors and investigates two sources in an experimental setting. The first significant error source is test-to-test variability in FRFs from system identification tests, quantified by magnitude variability from long-duration tests. The second significant error source is the realization of time histories from frequency domain inputs. The spectral content of the realized random process deviates from the desired content and is also quantified. The structure is a linear three-story frame fixed at the base; two inputs are provided uniaxially with the use of suspended electrodynamic shakers. The proposed model for error sources was found to be effective in predicting errors in a SISO (single-input single-output) and a square (2-input 2-output) MIMO test.

Yousef, Odey↗

DOE OSTI2020

The influence of spaceflight on the astronaut salivary microbiome and the search for a microbiome biomarker for viral reactivation

Background: Spaceflight impacts astronauts in many ways but little is known on how spaceflight affects the salivary microbiome and the consequences of these changes on astronaut health, such as viral reactivation. In order to understand this, the salivary microbiome was analyzed with 16S rRNA gene amplicon sequencing, and saliva viral titers were analyzed with quantitative polymerase chain reaction (qPCR) with primers specific for Epstein-Barr virus (EBV), herpes simplex virus (HSV), and varicella zoster virus (VZV) from 10 astronauts pre-flight, in-flight, and post-flight. Results: Streptococcus was the most abundant organism in the saliva, making up 8% of the total organisms detected, and their diversity decreased during spaceflight. Other organisms that had statistically significant changes were Proteobacteria and Fusobacteria which increased during flight and Actinobacteria which decreased during flight. At the genus level, Catonella , Megasphera , and Actinobacillus were absent in more than half of saliva samples collected pre-flight but were then detected during flight. In those subjects that already had these genera pre-flight, their relative abundances increased during flight. Correlation analyses between the microbiome and viral titers revealed a positive correlation with Gracilibacteria , Absconditabacteria , and Abiotrophia and a negative correlation between Oribacterium , Veillonella , and Haemophilus . There was also a significant positive correlation between microbiome richness and EBV viral titers. Conclusions: This is the first study to look at how the salivary microbiome changes as a result of spaceflight and the search for bacterial biomarkers for viral reactivation. Further studies examining the role of specific organisms that were shown to be correlative and predictive in viral reactivation, a serious problem in astronauts during spaceflight, could lead to mitigation strategies to help prevent disease during both short and long duration space missions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Evaluating proxies for the drivers of natural gas productivity using machine-learning models

We report the extensive development of unconventional reservoirs using horizontal drilling and multistage hydraulic fracturing has generated large volumes of reservoir characterization and production data. The analysis of this abundant data using statistical methods and advanced machine-learning (ML) techniques can provide data-driven insights into well performance. Most predictive modeling studies have focused on the impact that different well completion and stimulation strategies have on well production but have not fully exploited the available in situ rock property data to determine its role in reservoir productivity. We have used machine-learning techniques to rank rock mechanical properties, microseismic attributes, and stimulation parameters in the order of their significance for predicting natural gas production from an unconventional reservoir. The data for this study came from a hydraulically fractured well in the Marcellus Shale in Monongalia County, West Virginia. The data classes included measurements aggregated by well completion stage that included (1) gas production, (2) well-log-derived measurements including bulk density, elastic moduli, shear impedance, compressional impedance, brittleness, and gamma measurements, (3) microseismic attributes, (4) long-period long-duration (LPLD) event counts, (5) fracture counts, and (6) stimulation parameters that included the fluid injection volume and average pumping pressure. To identify observable proxies for the drivers of gas production, we evaluated five commonly used ML approaches including multivariate adaptive regression spline, Gaussian mixture model, random forest, gradient boosting, and neural network. We selected five variables including LPLD event count, seismogenic b-value, hydraulic diffusivity, cumulative moment, and fluid volume as the features most likely to impact gas productivity at the stage level in the study area. The data-driven selection of these parameters for their importance in determining gas production can help reservoir engineers design more effective hydraulic-fracture treatments in the Marcellus Shale and other similar unconventional reservoirs. Plain language summary: We use machine-learning methods and data-driven selection of reservoir parameters to rank and better understand their importance in determining gas production, which can help reservoir engineers design more effective hydraulic-fracture treatments in the Marcellus Shale and other similar unconventional reservoirs.

58 GEOSCIENCES↗

DOE OSTI2022

Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2022-10)

36 MATERIALS SCIENCE↗

DOE OSTI2023

Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2022-10.1)

This release consists of six datasets which together include multi-modal layer-wise powder bed images from two different powder bed printing technologies. These datasets are designed primarily to facilitate the development and testing of new computer vision and machine learning based anomaly and defect detection algorithms. The authors provide both training data with corresponding ground truth pixel masks and evaluation data with corresponding baseline prediction pixel masks made by a trained neural network. The laser powder bed fusion (L-PBF) datasets are sourced from EOS M290 and AddUp FormUp 350 printers and the binder jet (BJ) dataset is sourced from an ExOne M-Flex printer. The materials represented in these datasets include 17-4 PH Stainless Steel, GammaPrint-700, Inconel 718, Maraging Steel, and H13 Steel. The sensor imaging modalities represented include visible-light (VL), temporally-integrated (i.e., long duration exposure) near-infrared (TI-NIR), and wide-band infrared (IR). To download the dataset: (1) Create a Globus account. (2) Create a Globus Endpoint on your computer. (3) Transfer the dataset from the OLCF DOI-DOWNLOADS Collection to your Collection. Common troubleshooting steps: (a) Confirm that the transfer is going from OLCF DOI-DOWNLOADS to your Collection. (b) Create an exception for Globus in your antivirus software so that it can create an Endpoint. (c) Manually create a Globus access directory (where the data will be downloaded) by going to the Preferences > Access tab.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Optimal generation and isolation of attosecond pulses in an overdriven ionized medium

We identify optimal conditions for the generation and isolation of attosecond pulses in an overdriven ionized medium. In a high-pressure and highly ionized gas, the spatiotemporal wavefront rotation of a driving laser can be optimized, leading to complete spatial separation of successive attosecond bursts in the far field. The resulting isolated attosecond pulses (IAPs) are much more divergent such that they are spatially separated from the driving laser in the far field. We show that the time delay of near-field harmonic emission along the radial distance determines the divergence of the attosecond burst in the far field. Here, the generated IAPs are phase matched upon propagation in the second half of the gas medium. Validity of the generation scheme is tested at different carrier–envelope phases for a few-cycle laser pulse and by synthesizing the fundamental and its second harmonic field for a long-duration pulse.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Design of an optical amplifier for amplified OSC in IOTA facility at Fermilab

Optical stochastic cooling (OSC) is a cutting-edge beam cooling technology to reduce, control the 3 dimensional spread and the motion of particle beams. It has recently been successfully, experimentally, demonstrated in Fermilab's IOTA storage ring, marking a major step forward in beam cooling. OSC has the potential to significantly improve both the performance and flexibility as a beam cooling system. One promising way to boost OSC performance is by adding a high-gain optical amplifier. However, this amplifier must be carefully designed to meet the specific constraints of the OSC system. A major challenge lies in the limited optical delay, which is just 6 mm for the case of IOTA, set by the beam bypass, restricts us to use a short-length gain medium. This, along with IOTA’s high repetition rate and the relatively long duration of the optical pulses, limits the peak power available for the pump laser without damaging the crystal, which is crucial for achieving strong nonlinear gain. Additionally, it's essential to preserve the phase coherence of the undulator radiation during amplification, which further complicates the amplifier design. This report details a specialized amplifier setup that addresses these challenges, includes simulations of the integrated system, and summarizes the latest experimental progress and results.

Mondal, Abhishek [Fermilab]↗