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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 685 records · Page 38

CMPLE: Correlation Modeling to Decode Photosynthesis Using the Minorize–Maximize Algorithm

In plant genomic experiments, correlations among various biological traits (phenotypes) give new insights into how genetic diversity may have tuned biological processes to enhance fitness under diverse conditions. Consequently, knowing how the correlations are affected by genetic (G) and environmental (E) factors helps develop climate-resilient plants. However, the current literature lacks any method for assessing the effect of predictors on pairwise correlations among multiple phenotypes together with easily interpretable model parameters. To address this need, we propose to model pairwise correlations directly in terms of G and E and develop a computationally efficient inference procedure. Two major novelties in our methodology are (1) the use of a composite pairwise likelihood method to avoid the positive definiteness restriction on the correlation matrix and (2) the use of a novel Minorize–Maximize (MM) algorithm for the efficient estimation of a large number of parameters. The proposed method shows excellent numerical performance on synthetic datasets. Here, the analysis of the motivating data on cowpea reveals that the rates of solar energy storage by photosynthesis (the aggregate trait) are differentially affected by different genetic loci through two distinct processes: “photoinhibition” which results from photodamage caused by excess light, and “photoprotection” which protects plants from photodamage but also results in energy loss.

Correlation modeling↗

Combinatorial appraisal of transition states for in situ pair distribution function analysis

In situ total scattering measurements are increasingly utilized to follow atomic and nanoscale structural details of phase transitions and other transient processes in materials. This contribution presents an automated method and associated tool set to analyze series of diffraction and pair distribution function data with a linear combination of end-member states. It is demonstrated that the combinatorial appraisal of transition states (CATS) software tracks phase changes, relative phase fractions and length scales of interest in experimental data series. Here it is further demonstrated, using a series of local structure data simulations, that the misfit of such a model can reveal details of phase aggregation and growth related to the pair distribution function's sensitivity to interphase correlations. CATS may be applied to quantitative evaluation of many transient processes, including amorphous-to-crystalline phase transitions, the evolution of solid-solution behaviors, the precipitation and growth of aggregates, and other atomic to nanoscale details of crystallization and phase transformation phenomena.

36 MATERIALS SCIENCE↗

Localization of polyhydroxybutyrate in sugarcane using Fourier-transform infrared microspectroscopy and multivariate imaging

Background: Slow-degrading, fossil fuel-derived plastics can have deleterious effects on the environment, especially marine ecosystems. The production of bio-based, biodegradable plastics from or in plants can assist in supplanting those manufactured using fossil fuels. Polyhydroxybutyrate (PHB) is one such biodegradable polyester that has been evaluated as a possible candidate for relinquishing the use of environmentally harmful plastics. Results: PHB, possessing similar properties to polyesters produced from non-renewable sources, has been previously engineered in sugarcane, thereby creating a high-value co-product in addition to the high biomass yield. This manuscript illustrates the coupling of a Fourier-transform infrared microspectrometer, equipped with a focal plane array (FPA) detector, with multivariate imaging to successfully identify and localize PHB aggregates. Principal component analysis imaging facilitated the mining of the abundant quantity of spectral data acquired using the FPA for distinct PHB vibrational modes. PHB was measured in the chloroplasts of mesophyll and bundle sheath cells, acquiescent with previously evaluated plant samples. Conclusion: This study demonstrates the power of IR microspectroscopy to rapidly image plant sections to provide a snapshot of the chemical composition of the cell. While PHB was localized in sugarcane, this method is readily transferable to other value-added co-products in different plants.

36 MATERIALS SCIENCE↗

Status and Trends in the U.S. Voluntary Green Power Market (2013 Data)

Voluntary green power markets are those in which consumers and institutions voluntarily purchase renewable energy to match their electricity needs. This report surveys utilities, competitive suppliers, renewable energy certificate (REC) marketers, and, for the first time, the community choice aggregation market. This report finds that the voluntary market totaled 62 million megawatt-hours in 2013. Approximately 5.4 million customers are purchasing green power. This report presents data and analysis on voluntary market sales and customer participation, products and premiums, green pricing marketing, and administrative expenses. The report also details trends in REC tracking systems, REC pricing in voluntary and compliance markets, community and crowd-funded solar, and interest in renewable energy by the information and communication technologies sector.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A Retrospective Analysis of the Benefits and Impacts of U.S. Renewable Portfolio Standards

This is the second in a series of reports exploring the costs, benefits, and other impacts of state renewable portfolio standards (RPS), both retrospectively and prospectively. This report focuses on the benefits and impacts of all state RPS programs, in aggregate, for the year 2013 (the most-recent year for which the requisite data were available). Relying on a well-vetted set of methods, the study evaluates a number of important benefits and impacts in both physical and monetary terms, where possible, and characterizes key uncertainties. The prior study in this series focused on historical RPS compliance costs, and future work will evaluate costs, benefits, and other impacts of RPS policies prospectively.

54 ENVIRONMENTAL SCIENCES↗

Multi-Angle Snowflake Camera Value-Added Product

The Multi-Angle Snowflake Camera (MASC) addresses a need for high-resolution multi-angle imaging of hydrometeors in freefall with simultaneous measurement of fallspeed. As illustrated in Figure 1, the MASC consists of three cameras, separated by 36°, each pointing at an identical focal point approximately 10 cm away. Located immediately above each camera, a light aims directly at the center of depth of field for its corresponding camera. The focal point at which the cameras are aimed lies within a ring through which hydrometeors fall. The ring houses a system of near-infrared emitter-detector pairs, arranged in two arrays separated vertically by 32 mm. When hydrometeors pass through the lower array, they simultaneously trigger all cameras and lights. Fallspeed is calculated from the time it takes to traverse the distance between the upper and lower triggering arrays. The trigger electronics filter out ambient light fluctuations associated with varying sunlight and shadows. The microprocessor onboard the MASC controls the camera system and communicates with the personal computer (PC). The image data is sent via FireWire 800 line, and fallspeed (and camera control) is sent via a Universal Serial Bus (USB) line that relies on RS232-over-USB serial conversion. See Table 1 for specific details on the MASC located at the Oliktok Point Mobile Facility on the North Slope of Alaska. The value-added product (VAP) detailed in this documentation analyzes the raw data (Section 2.0) using Python: images rely on OpenCV image processing library and derived aggregated statistics rely on some clever averaging. See Sections 4.1 and 4.2 for more details on what variables are computed.

47 OTHER INSTRUMENTATION↗

Organic Speciation and Interactions in ALSEP. One Step Partitioning Process of MinorActinides, Lanthanides, and Fission Products

Research conducted in this project focused on speciation characterization of the ALSEP extraction system (similar to the TALSPEAK-like application) which addresses recovery of minor actinides and lanthanides from PUREX raffinate. The ALSEP (Actinide-Lanthanide Separation) system proposes a trivalent minor actinide/lanthanide group extraction followed by a selective actinide strip to effectively partition minor actinides, lanthanides, and other fission products. The group extraction is achieved by a mixed organic solvent, combining acidic and neutral extracting ligands. The objective of this work is investigation the interactions of the acidic and neutral ligands with each other in the extraction organic solvent and with desired metals. Four combinations of a cation-exchange ligand (either HDEHP or HEH[EHP]) and a neutral solvating ligand (either TODGA or T2EHDGA) in n-dodecane were studied. Interligand dimers in these combinations were investigated with NMR and FTIR, the strongest interaction was observed for HDEHP+TODGA and weakest for T2EHDGA+HEH[EHP]. Complexes of the trivalent Am and lanthanides Nd, Eu, Ho, Pr in these binary ligand mixtures were probed with spectroscopic (UV–vis, time-resolved fluorescence, XAFS and SAXS-spectroscopies) and extraction (Job’s plot, slope analysis) methods; co-extracted water and nitric acid were analyzed by titration methods. Comparison of the collected spectra showed significant shifting for both DGA ligands with HDEHP, while both combinations of HEH[EHP]+DGA displayed much smaller spectral changes. Data were modeled with HypSpec program, and stability constants for extracted complexes were calculated. Aggregation in these systems were studied by SAXS (small-angle X-ray scattering) spectroscopy and interfacial tension, size of aggregates were measured. Two PhD students graduated (2017, 2018) and one student continues her PhD study.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

SoDaH: the SOils DAta Harmonization database, an open-source synthesis of soil data from research networks, version 1.0

Data collected from research networks present opportunities to test theories and develop models about factors responsible for the long-term persistence and vulnerability of soil organic matter (SOM). Synthesizing datasets collected by different research networks presents opportunities to expand the ecological gradients and scientific breadth of information available for inquiry. Synthesizing these data is challenging, especially considering the legacy of soil data that have already been collected and an expansion of new network science initiatives. To facilitate this effort, here we present the SOils DAta Harmonization database (SoDaH; https://lter.github.io/som-website, last access: 22 December 2020), a flexible database designed to harmonize diverse SOM datasets from multiple research networks. SoDaH is built on several network science efforts in the United States, but the tools built for SoDaH aim to provide an open-access resource to facilitate synthesis of soil carbon data. Moreover, SoDaH allows for individual locations to contribute results from experimental manipulations, repeated measurements from long-term studies, and local- to regional-scale gradients across ecosystems or landscapes. Finally, we also provide data visualization and analysis tools that can be used to query and analyze the aggregated database. The SoDaH v1.0 dataset is archived and available at https://doi.org/10.6073/pasta/9733f6b6d2ffd12bf126dc36a763e0b4 (Wieder et al., 2020).

54 ENVIRONMENTAL SCIENCES↗

Development of a Trip Energy Estimation Model Using Real-World Global Positioning System Driving Data: Preprint

A data-driven technique for estimation of energy requirements for a proposed vehicle trip has been developed. Based on over 700,000 miles of driving data, the technique has been applied to generate a model that estimates trip energy requirements. The model uses a novel binning approach to categorize driving by road type, traffic conditions, and driving profile. The trip-level energy estimations can easily be aggregated to any higher-level transportation system network desired. The model has been tested and validated on the Austin, Texas, data set used to build this model. Ground-truth energy consumption for the data set was obtained from Future Automotive Systems Technology Simulator (FASTSim) vehicle simulation results. The energy estimation model has demonstrated 12.1 percent normalized total absolute error. The energy estimation from the model can be used to inform control strategies in routing tools, such as change in departure time, alternate routing, and alternate destinations, to reduce energy consumption. The model can also be used to determine more accurate energy consumption of regional or national transportation networks if trip origin and destinations are known. Additionally, this method allows the estimation tool to be tuned to a specific driver or vehicle type.

33 ADVANCED PROPULSION SYSTEMS↗

How Driving Volatility in Time to Collision Relates to Crash Severity in a Naturalistic Driving Environment

The sequence of instantaneous driving decisions and its variations, known as driving volatility, can be a leading indicator of unsafe driving practices. The research issue is to characterize volatility in instantaneous driving decisions in longitudinal and lateral direction and to seek an understanding of how driving volatility relates to crash severity. By using a unique real-world naturalistic driving database from the SHRP 2, a test set of 671 crash events featuring around 0.2 million temporal samples of real-world driving are analyzed. Based on different driving performance measures, 16 different volatility indices are created. The volatility indices are then linked with individual crash events including information on crash severity, drivers’ pre-crash maneuvers and behaviors, secondary tasks and durations, and other factors. As driving volatility prior to crash involvement can have different components, an in-depth analysis is conducted using the aggregate as well as segmented (based on time to collision) real-world driving data. To account for the issues of observed and unobserved heterogeneity, fixed and random parameter ordered models with heterogeneity in parameter means are estimated. The findings suggest that greater driving volatility (both in longitudinal and lateral direction) prior to crash occurrence increases the likelihood of police reportable or severe crash events. Importantly, compared to the effect of volatility in longitudinal acceleration on crash outcomes, the effect of volatility in longitudinal deceleration is significantly greater in magnitude. Methodologically, the random parameter models with heterogeneity-in-means significantly outperformed both the fixed parameter and random parameter counterparts. The relevance of the findings to the development of proactive behavioral countermeasures for drivers is discussed.

Wali, Behram↗

Privacy-Preserving Knowledge Transfer with Bootstrap Aggregation of Teacher Ensembles

There is a need to transfer knowledge among institutions and organizations to save effort in annotation and labeling or in enhancing task performance. However, knowledge transfer is difficult because of restrictions that are in place to ensure data security and privacy. Institutions are not allowed to exchange data or perform any activity that may expose personal information. With the leverage of a differential privacy algorithm in a high-performance computing environment, we propose a new training protocol, Bootstrap Aggregation of Teacher Ensembles (BATE), which is applicable to various types of machine learning models. The BATE algorithm is based on and provides enhancements to the PATE algorithm, maintaining competitive task performance scores on complex datasets with underrepresented class labels.We conducted a proof-of-the-concept study of the information extraction from cancer pathology report data from four cancer registries and performed comparisons between four scenarios: no collaboration, no privacy-preserving collaboration, the PATE algorithm, and the proposed BATE algorithm. The results showed that the BATE algorithm maintained competitive macro-averaged F1 scores, demonstrating that the suggested algorithm is an effective yet privacy-preserving method for machine learning and deep learning solutions.

Yoon, Hong-Jun↗

Embodied carbon in the U.S. manufacturing and trade

On average, one quarter of the global carbon footprint is embodied in traded goods. These emissions are a growing issue for global efforts to decarbonize the world economy. Embodied emissions in trade are not accounted for by existing greenhouse gas accounting systems. For example, countries only report their domestic carbon emissions (also known as production-based or territorial accounting) to the Intergovernmental Panel on Climate Change (IPCC). If the embodied carbon in trade were accounted for and reported, the promising climate trends depicted by many countries would be negated or reversed. For example, many achievements of reducing emissions by developed countries under the Kyoto Protocol would actually appear as emissions outsourced to developing countries. Like many other developed countries, the United States is a net importer of embodied greenhouse gas (GHG) emissions in trade. The goal of this study was to calculate the carbon footprint of various sectors of the U.S. economy using the latest available data and based on that, estimate the embodied carbon in certain manufacturing sector products imported and exported by the U.S. First, we conducted an input-output analysis to calculate the carbon footprint of 401 aggregate level sectors of the U.S. economy. After that, for a selected number of manufacturing subsectors /products(hereafter referred to as products),we collected their trade(import/export) data and combined that with their computed carbon footprint to estimate the embodied carbon in import and export of these products for the U.S. While we conducted the carbon footprint analysis for sectors covering the entire U.S. economy (401 sectors), we only conducted the embodied carbon in trade analysis for a few products within specific aggregate level manufacturing sectors,such as computer and electronic product manufacturing (NAICS 334), transport equipment manufacturing (NAICS 336), machinery manufacturing (NAICS 333), and chemical manufacturing (NAICS 325). It is possible to do the detailed embodied carbon analysis for all other products within the various aggregate level manufacturing sectors of the U.S. economy, but given the scope of this study and space constraint of this report, we only present the results for a few products. The results of our analysis for the selected products show the embodied carbon in trade for each product by country and also show the rankings of countries in terms of top importers and exporters of embodied carbon in trade with the U.S. Our results show that in majority of cases, the U.S. is a net importer of embodied carbon in trade. Unless consumption-based accounting is used, the U.S. and other net embodied carbon importing countries may continue to outsource their emissions to meet their climate change mitigation targets under the Paris Agreement, as observed previously with the Kyoto Protocol. Some countries reported reductions that exceeded their Kyoto targets, however, the changes in emissions embodied in imports were comparable to or larger than changes in domestic emissions. Traded emissions undermined emissions reductions in the Kyoto Protocol, and threaten to continue to do so for the Paris Agreement. New climate policies such as California’s Buy Clean act, EU’s proposed border carbon tax adjustment, as well as efforts in the private sector can help address the embodied carbon in traded products.

54 ENVIRONMENTAL SCIENCES↗

An operational definition of quark and gluon jets

While “quark” and “gluon” jets are often treated as separate, well-defined objects in both theoretical and experimental contexts, no precise, practical, and hadron-level definition of jet flavor presently exists. To remedy this issue, we develop and advocate for a data-driven, operational definition of quark and gluon jets that is readily applicable at colliders. Rather than specifying a per-jet flavor label, we aggregately define quark and gluon jets at the distribution level in terms of measured hadronic cross sections. Intuitively, quark and gluon jets emerge as the two maximally separable categories within two jet samples in data. Benefiting from recent work on data-driven classifiers and topic modeling for jets, we show that the practical tools needed to implement our definition already exist for experimental applications. As an informative example, we demonstrate the power of our operational definition using Z+jet and dijet samples, illustrating that pure quark and gluon distributions and fractions can be successfully extracted in a fully well-defined manner.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A systematic analytical framework for multi-source municipal solid waste characterization for energy recovery

Advancing municipal solid waste (MSW) management from disposal-oriented practices toward circular, value-driven systems requires standardized methodologies capable of identifying material composition and resource recoverable potential at the point of generation. Despite extensive research, MSW characterization remains fragmented due to inconsistences in sampling methodologies, waste sorting categories, and temporal coverage across previous studies which limit cross-site comparability, reproducibility, and constrain the reliable evaluation of potential resource recovery pathways. This lack of consistency has hindered the development of a unified framework for MSW characterization and resource assessment. This study introduces a standardized, field-validated protocol for MSW sampling and composition analysis that ensures consistent, traceable data across diverse waste sources. The protocol integrates randomized spatial sampling, systematic material sorting, and controlled subsampling for multi-site and multi-season field campaigns. Validation included MSW collection from residential, grocery, restaurant, and school MSW streams across five U.S. states, including Maryland, Idaho, Virginia, Ohio, and Mississippi, to demonstrate the protocol’s ability to identify source-based composition patterns relevant to resource recovery applications. Grocery and restaurant streams were dominated by food waste and high-moisture organics, while school waste contained higher paper content and residential waste showed greater heterogeneity. Aggregation into energy-relevant fractions highlighted practical recovery pathways via anaerobic digestion or gasification, supporting data-driven planning, policy, and circular economy strategies for sustainable waste management across waste sources.

09 BIOMASS FUELS↗

Occupational Radiation Exposure Report for Calendar Year 2023

The U.S. Department of Energy Occupational Radiation Exposure Report for Calendar 2023 presents the results of analyses of occupational radiation exposures at the U.S. Department of Energy (DOE), including the National Nuclear Security Administration (NNSA) operations, during calendar year 2023. This report includes occupational radiation exposure data for over 80,000 DOE Federal employees, contractors, and subcontractors as well as members of the public who have worked in or entered controlled areas monitored for exposure to radiation. DOE publishes this annual report to provide DOE Management, Program Offices, workers, health physicists, and other stakeholders an evaluation of DOE-wide performance regarding compliance with Title 10 of the Code of Federal Regulations (CFR) Part 835, Occupational Radiation Protection (10 CFR 835) radiation exposure limits and adherence to as low as reasonably achievable principles. This report provides a discussion regarding radiation protection and exposure reporting requirements. It also includes calendar year (CY) 2023 information and analyses regarding aggregate, individual, site, DOE Program, transient individuals’ dose, as well as a historical review of DOE exposure data. DOE continues to be diligent in protecting its workers and the public from exposure to radiation from DOE operations as illustrated by the results contained in this report.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Preferential Charge Generation at Aggregate Sites in Narrow Band Gap Infrared Photoresponsive Polymer Semiconductors

Infrared organic photodetector materials are investigated using transient absorption spectroscopy, demonstrating that ultrafast charge generation assisted by polymer aggregation is essential to compensate for the energy gap law, which dictates that excited state lifetimes decrease as the band gap narrows. Short sub–picosecond singlet exciton lifetimes are measured in a structurally related series of infrared–absorbing copolymers that consist of alternating cyclopentadithiophene electron–rich “push” units and strong electron–deficient “pull” units, including benzothiadiazole, benzoselenadiazole, pyridalselenadiazole, or thiadiazoloquinoxaline. While the ultrafast lifetimes of excitons localized on individual polymer chains suggest that charge carrier generation will be inefficient, high detectivity for polymer:PC 71 BM infrared photodetectors is measured in the 0.6 < λ < 1.5 µm range. The photophysical processes leading to charge generation are investigated by performing a global analysis on transient absorption data of blended polymer:PC 71 BM films. In these blends, charge carriers form primarily at polymer aggregate sites on the ultrafast time scale (within our instrument response), leaving quickly decaying single–chain excitons unquenched. Lastly, the results have important implications for the further development of organic infrared optoelectronic devices, where targeting processes such as excited state delocalization over aggregates may be necessary to mitigate losses to ultrafast exciton decay as materials with even lower band gaps are developed.

36 MATERIALS SCIENCE↗

Intelligent Vehicle Charging Benefits Assessment Using EV Project Data

PEVs can represent a significant power resource for the grid. An IVCI with bi-direction V2G capabilities would allow PEVs to provide grid support services and thus generate a source of revenue for PEV owners. The fleet of EV Project vehicles represents a power resource between 30 MW and 90 MW, depending on the power rating of the grid connection (5-15 kW). Aggregation of vehicle capacity would allow PEVs to participate in wholesale reserve capacity markets. One of the key insights from EV Project data is the fact that vehicles are connected to an EVSE much longer than is necessary to deliver a full charge. During these hours when the vehicles are not charging, they can be participating in wholesale power markets providing the high-value services of regulation and spinning reserves. The annual gross revenue potential for providing these services using the fleet of EV Project vehicles is several hundred thousands of dollars to several million dollars annually depending on the power rating of the grid interface, the number of hours providing grid services, and the market being served. On a per vehicle basis, providing grid services can generate several thousands of dollars over the life of the vehicle.

33 ADVANCED PROPULSION SYSTEMS↗