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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Transit Time Estimation in Catchments: Recent Developments and Future Directions

Abstract Water transit time is now a standard measure in catchment hydrological and ecohydrological research. The last comprehensive review of transit time modeling approaches was published 15+ years ago. But since then the field has largely expanded with new data, theory and applications. Here, we review these new developments with focus on water‐age‐balance approaches and data‐based approaches. We discuss and compare methods including StorAge‐Selection functions, well/partially mixed compartments, water age tracking through spatially distributed models, direct transit time estimates from controlled experiments, young water fractions, and ensemble hydrograph separation. We unify some of the heterogeneity in the literature that has crept in with these many new approaches, in an attempt to clarify the key differences and similarities among them. Finally, we point to open questions in transit time research, including what we still need from theory, models, field work, and community practice.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Modeling the Contribution of Precipitation Loss to a Radiation Belt Electron Dropout Observed by Van Allen Probes

A drift-diffusion model is used to simulate the low-altitude electron distribution, accounting for azimuthal drift, pitch angle diffusion, and atmospheric backscattering effects during a rapid electron dropout event on 21st August 2013, at L = 4.5. Additional external loss effects are introduced during times when the low-altitude electron distribution cannot be reproduced by diffusion alone. Here, the model utilizes low-altitude electron count rate data from five POES/MetOp satellites to quantify pitch angle diffusion rates. Low-altitude data provides critical constraint on the model because it includes the drift loss cone region where the electron distribution in longitude is highly dependent on the balance between azimuthal drift and pitch angle diffusion. Furthermore, a newly derived angular response function for the detectors onboard POES/MetOp is employed to accurately incorporate the bounce loss cone measurements, which have been previously contaminated by electrons from outside the nominal field-of-view. While constrained by low-altitude data, the model also shows reasonable agreement with high-altitude data. Pitch angle diffusion rates during the event are quantified and are faster at lower energies. Precipitation is determined to account for all of the total loss observed for 450 keV electrons, 88% for 600 keV and 38% for 900 keV. Predictions made in the MeV range are deemed unreliable as the integral energy channels E3 and P6 fail to provide the necessary constraint at relativistic energies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

DESC: A stellarator equilibrium solver

In this paper, the new code DESC is presented to solve for fixed-boundary ideal magnetohydrodynamic equilibria in stellarators. The approach directly solves the equilibrium force balance as a system of nonlinear equations in the form f(x) = 0. The independent variables x represent nested magnetic flux surfaces expressed in the inverse representation with toroidal flux coordinates, and the equations f(x) quantify equilibrium force balance errors at discrete points in real space. Discretizing with global Fourier–Zernike basis functions properly treats the magnetic axis and minimizes the number of coefficients needed to describe the flux surfaces. The pseudospectral method provides great flexibility in where the errors are evaluated, and the system of equations is efficiently solved with a Newton–Raphson iteration. Equilibria are computed and compared against VMEC for both axisymmetric and non-axisymmetric examples. The results show fast convergence rates and solutions with low errors throughout the plasma volume.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Effect of Solvent Motion on Ion Transport in Electrolytes

We use concentrated solution theory to derive an equation governing solvent velocity in a binary electrolyte when a current passes through it. This equation, in combination with the material balance equation, enables the prediction of electrolyte concentration profiles and species velocities as a function of space and time. This framework is used to predict ion velocities in Li-Li symmetric cells containing a mixture of lithium bis(trifluoromethanesulfonyl)imide and poly(ethylene oxide) (LiTFSI/PEO), for which the cation transference number relative to the solvent velocity, ${t}_{+}^{0},$ can be either positive or negative, depending on salt concentration. Accounting for the solvent motion is increasingly important at higher concentrations. Especially for negative ${t}_{+}^{0},$ if solvent velocity is set to zero, the cation velocity, based on the electrode-electrolyte interface reference frame, is pointed opposite to the current flow. However, when solvent motion is taken into account, the cation velocity, based on the same reference frame, is in the same direction as the current. This analysis demonstrates the importance of accounting for solvent velocity rigorously in seemingly simple systems such as symmetric cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Mapping Spatiotemporal Solvent Velocity from Measured Concentration Gradients in a Polarized Electrolyte

The electric-field induced motion of neutral species impedes the efficacy of electrochemical devices. By combining operando X-ray transmission measurements with continuum mechanics, we have developed a methodology for determining the velocity of neutral solvent molecules under an applied field. The X-ray transmission experiments were used to determine ion concentration profiles as a function of space and time in a polymer electrolyte. The unsteady state solvent mass balance equation was solved numerically with experimental concentration profiles to map spatiotemporal solvent velocities. We compare our experimentally derived results with predictions made with concentrated solution theory. We use the cation transference number as the only adjustable parameter to match experimental measurements of both concentration and solvent velocity. Our approach may be used to determine solvent velocity with any operando technique used to measure time-dependent ion concentration profiles.

Abdo, Emily E↗
DOE OSTI2022

Granal thylakoid structure and function: explaining an enduring mystery of higher plants

Summary In higher plants, photosystems II and I are found in grana stacks and unstacked stroma lamellae, respectively. To connect them, electron carriers negotiate tortuous multi‐media paths and are subject to macromolecular blocking. Why does evolution select an apparently unnecessary, inefficient bipartition? Here we systematically explain this perplexing phenomenon. We propose that grana stacks, acting like bellows in accordions, increase the degree of ultrastructural control on photosynthesis through thylakoid swelling/shrinking induced by osmotic water fluxes. This control coordinates with variations in stomatal conductance and the turgor of guard cells, which act like an accordion's air button. Thylakoid ultrastructural dynamics regulate macromolecular blocking/collision probability, direct diffusional pathlengths, division of function of Cytochrome b 6 f complex between linear and cyclic electron transport, luminal pH via osmotic water fluxes, and the separation of pH dynamics between granal and lamellar lumens in response to environmental variations. With the two functionally asymmetrical photosystems located distantly from each other, the ultrastructural control, nonphotochemical quenching, and carbon‐reaction feedbacks maximally cooperate to balance electron transport with gas exchange, provide homeostasis in fluctuating light environments, and protect photosystems in drought. Grana stacks represent a dry/high irradiance adaptation of photosynthetic machinery to improve fitness in challenging land environments. Our theory unifies many well‐known but seemingly unconnected phenomena of thylakoid structure and function in higher plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Structural and dynamic mechanisms for coupled folding and tRNA recognition of a translational T-box riboswitch

T-box riboswitches are unique riboregulators where gene regulation is mediated through interactions between two highly structured RNAs. Despite extensive structural insights, how RNA-RNA interactions drive the folding and structural transitions of T-box to achieve functional conformations remains unclear. Here, by combining SAXS, single-molecule FRET and computational modeling, we elaborate the folding energy landscape of a translational T-box aptamer consisting of stems I, II and IIA/B, which Mg 2+ -induced global folding and tRNA binding are cooperatively coupled. smFRET measurements reveal that high Mg 2+ stabilizes IIA/B and its stacking on II, which drives the pre-docking of I and II into a competent conformation, subsequent tRNA binding promotes docking of I and II to form a high-affinity tRNA binding groove, of which the essentiality of IIA/B and S-turn in II is substantiated with mutational analysis. We highlight a delicate balance among Mg 2+ , the intra- and intermolecular RNA-RNA interactions in modulating RNA folding and function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Task 12 Sustainability - Methodological Guidelines on Net Energy Analysis of Photovoltaic Electricity (2nd Edition)

Net Energy Analysis (NEA) is a structured, comprehensive method of quantifying the extent to which a given energy source is able to provide a net energy gain (i.e., an energy surplus) to the end user, after accounting for all the energy losses occurring along the chain of processes that are required to exploit it (i.e., for its extraction, processing and transformation into a usable energy carrier, and delivery to the end user), as well as for all the additional energy 'investments' that are required in order to carry out the same chain of processes. However, this general framework leaves the individual practitioner with a range of choices that can affect the results and thus, the conclusions of a NEA study. The current IEA PVPS guidelines were developed to provide guidance on assuring consistency, balance, and quality to enhance the credibility and reliability of the results from photovoltaic (PV) NEAs. The guidelines represent a consensus among the authors - PV NEA experts in North America and Europe - for assumptions made on PV performance, process inputs and outputs, methods of analysis, and reporting of the results. Guidance is given on photovoltaic-specific parameters used as inputs in NEA and on choices and assumptions in inventory data analysis and on implementation of modelling approaches. A consistent approach towards system modelling, the functional unit, the system boundaries and allocation aspects enhance the credibility of PV electricity NEA studies and enables balanced NEA-based comparisons. Specifically, "apples-to-oranges" comparisons of different energy carriers (e.g., fuels vs. electricity) are not methodologically sound and are to be avoided in all cases; also, any comparison across renewable and non-renewable electricity generation technologies must clearly point out the intrinsically short-term nature of the NEA viewpoint, which does not capture the long-term sustainability implications of renewable vs. non-renewable primary energy harvesting and use: non-renewable primary energy resources are depleted and finally exhausted (irrespective of the size of the EROI), while renewable primary energy resources are not. This document provides an in-depth discussion of a common metric of NEA, namely the energy return on investment (EROI), and how this is to be interpreted vis-a-vis the deceptively similar-sounding metrics in the field of Life Cycle Assessment (LCA): cumulative energy demand (CED) and non-renewable cumulative energy demand (nr-CED) per unit output. Specifically, a number of key differences are highlighted between these metrics as applied to electricity production systems, which are listed in Table S-1.

14 SOLAR ENERGY↗
DOE OSTI2023

Physiological Functions of Phospholipid:Diacylglycerol Acyltransferases

Abstract Triacylglycerol (TAG) is among the most energy dense storage forms of reduced carbon in living systems. TAG metabolism plays critical roles in cellular energy balance, lipid homeostasis, cell growth and stress responses. In higher plants, microalgae and fungi, TAG is assembled by acyl-CoA-dependent and acyl-CoA-independent pathways catalyzed by diacylglycerol (DAG) acyltransferase and phospholipid:DAG acyltransferase (PDAT), respectively. This review contains a summary of the current understanding of the physiological functions of PDATs. Emphasis is placed on their role in lipid remodeling and lipid homeostasis in response to abiotic stress or perturbations in lipid metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Operation and Control of a Back to Back Modular Multilevel Converter System for Grid Forming Application with Advanced Grid Support Functionalities

The main focus of this paper is to investigate the possibility of using modular multilevel converter based back-to-back system for grid forming applications. A decentralized hierarchical control architecture with a modified local controller based on nonlinear techniques for grid forming application have been investigated. Grid functionalities based on IEEE 1547-2018 for grid forming converters have been utilized. The local controllers ensure distortion free balanced sinusoidal output voltage on the grid forming side with unbalanced or nonlinear loading condition. The grid following side ensures unity power factor currents under unbalanced grid voltage condition. The dc bus voltage control ensures oscillation free voltage under balanced conditions and control of the average voltage under unbalanced condition. Efficacy of the overall system is verified by modeling the system in MATLAB/Simulink and PLECS domain and the most important case studies are presented.

advanced grid support functionalities↗
DOE OSTI2022

Charging of radioactive and environmental airborne particles

The charging of various airborne particles was investigated using single-particle levitation and charge-balance equations. Though radioactive decay and triboelectrification can induce charging, it is typically assumed that the aerosols in a radioactive plume will not carry significant charge at steady state since atmospheric particles can have their charge neutralized through the capture of adjacent counter-ions (i.e., diffusion charging). Here to assess this assumption, we directly measured the surface charge and charge density of various triboelectrically charged aerosols including radioactive uranium oxide (<1 μm), urban dust, Arizona desert dust, hydrophilic and hydrophobic silica nanoparticles, and graphene oxide powders using an electric field-assisted particle levitator in air. Of these particles, uranium oxide aerosols exhibited the highest surface charge density. Charge balance equations were employed to predict the average charge gained from radioactive decay as a function of time and to evaluate the effects of diffusion charging on triboelectrically charged radioactive and non-radioactive particles in the atmosphere. Simulation results show that particles, initially charged through triboelectrification, can be quickly discharged by diffusion charging in the absence of radioactive decay. Nevertheless, simulation results also indicate that particles can be strongly charged when they carry radionuclides. These experimental and simulation results suggest that radioactive decay can induce strong particle charging that may potentially affect atmospheric transport of airborne radionuclides.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Assembling Vertical Block Copolymer Nanopores via Solvent Vapor Annealing on Homopolymer-Functionalized Substrates

Utilizing the self-assembly of block copolymers with large Flory–Huggins interaction parameters (χ) for nanofabrication is a formidable challenge due to the attendant large surface energy differences between the blocks. This work reports a robust protocol for the fabrication of thin films with highly ordered cylindrical nanopore arrays via the self-assembly of an asymmetric poly(styrene-block-4-vinylpyridine) (PS-b-P4VP) diblock copolymer blended with a P4VP homopolymer. The desired vertical domain orientation is achieved at the air–polymer interface by controlled solvent vapor annealing (SVA) using acetone, a solvent with weak selectivity for PS over P4VP, and at the substrate interface by functionalization using a hydroxy-terminated poly(2-vinylpyridine) (P2VP-OH) homopolymer brush. In contrast, the vertical cylinder orientation is unstable during acetone SVA on substrates functionalized using hydroxy-terminated poly(methyl methacrylate) (PMMA-OH). Although PMMA exhibits more balanced interfacial energies between PS and P4VP than P2VP in the dry state, it is also swollen more selectively by acetone. We hypothesize that the nearly balanced solvent swelling of the three polymers (P2VP, P4VP, and PS) stabilizes the vertical cylinder orientation, while unbalanced swelling (PMMA > P4VP and PS) does not. Here we further characterize pore formation by addition of a P4VP homopolymer and its postassembly extraction using ethanol, revealing a narrow window of pore size tunability. Notably, minimal differences in nanopore morphologies are observed for P4VP volume fractions as high as 0.1, regardless of the P4VP molar mass. However, further increasing the P4VP volume fraction results in domain reorientation or macrophase separation when its molar mass is less than or greater than the P4VP block molar mass, respectively. Using a P4VP homopolymer that is nearly equal in length to the P4VP block enables the fabrication of well-ordered arrays of vertical, through-film nanopores with high aspect ratios (>10), small periods (<23 nm), and diameters less than 10 nm.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

An analytic theory for the degree of Arctic Amplification

Arctic Amplification (AA), the amplified surface warming in the Arctic relative to the global mean, is a robust and impactful feature of climate change. While the basic physical picture of AA has been depicted, a clear understanding of how the degree of AA is determined has not been established. Here, by deciphering the intricate role of atmospheric heat transport (AHT), we build a two-box energy-balance model of AA and derive that the degree of AA is a simple nonlinear function of the Arctic and global feedbacks, the meridional heterogeneity in radiative forcing, and the partial sensitivities of AHT to global mean warming and meridional warming gradient. The formula captures the varying degree of AA in individual climate models and attributes the variation to specific physical factors. It further conveys a concise picture of how essential physics mutually determine the degree of AA and limit the range within 1.5~3.5. Our results articulate AHT as both forcing and feedback to AA, highlighting its partial sensitivities instead of total change as the key parameters for understanding AA. We also find that the effect of lapse rate feedback, a widely-recognized major contributor to AA, is fully offset by the effect of water vapor feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

FL‐ADS: Federated learning anomaly detection system for distributed energy resource networks

Abstract With the ongoing development of Distributed Energy Resources (DER) communication networks, the imperative for strong cybersecurity and data privacy safeguards is increasingly evident. DER networks, which rely on protocols such as Distributed Network Protocol 3 and Modbus, are susceptible to cyberattacks such as data integrity breaches and denial of service due to their inherent security vulnerabilities. This paper introduces an innovative Federated Learning (FL)‐based anomaly detection system designed to enhance the security of DER networks while preserving data privacy. Our models leverage Vertical and Horizontal Federated Learning to enable collaborative learning while preserving data privacy, exchanging only non‐sensitive information, such as model parameters, and maintaining the privacy of DER clients' raw data. The effectiveness of the models is demonstrated through its evaluation on datasets representative of real‐world DER scenarios, showcasing significant improvements in accuracy and F1‐score across all clients compared to the traditional baseline model. Additionally, this work demonstrates a consistent reduction in loss function over multiple FL rounds, further validating its efficacy and offering a robust solution that balances effective anomaly detection with stringent data privacy needs.

Purohit, Shaurya [Iowa State University Ames Iowa ↗
DOE OSTI2022

Photometric redshift estimation with convolutional neural networks and galaxy images: Case study of resolving biases in data-driven methods

Deep-learning models have been increasingly exploited in astrophysical studies, but these data-driven algorithms are prone to producing biased outputs that are detrimental for subsequent analyses. In this work, we investigate two main forms of biases: class-dependent residuals, and mode collapse. We do this in a case study, in which we estimate photometric redshift as a classification problem using convolutional neural networks (CNNs) trained with galaxy images and associated spectroscopic redshifts. We focus on point estimates and propose a set of consecutive steps for resolving the two biases based on CNN models, involving representation learning with multichannel outputs, balancing the training data, and leveraging soft labels. The residuals can be viewed as a function of spectroscopic redshift or photometric redshift, and the biases with respect to these two definitions are incompatible and should be treated individually. We suggest that a prerequisite for resolving biases in photometric space is resolving biases in spectroscopic space. Experiments show that our methods can better control biases than benchmark methods, and they are robust in various implementing and training conditions with high-quality data. Our methods hold promises for future cosmological surveys that require a good constraint of biases, and they may be applied to regression problems and other studies that make use of data-driven models. Nonetheless, the bias-variance tradeoff and the requirement of sufficient statistics suggest that we need better methods and optimized data usage strategies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

APSO-enhanced algebraic derivative estimation approach for real-time traffic flow prediction on critical road sections during wildfire evacuation

In rapid-onset disaster scenarios such as wildfires, evacuation traffic often significantly deviates from historical patterns, rendering conventional data-driven forecasting methods less effective. To address this challenge, we propose an improved algebraic derivative estimation (ADE) incorporating particle swarm optimization (PSO) for real-time traffic flow prediction. Our approach dynamically adjusts the ADE prediction time window at each step by minimizing a cost function based on the mean and variance of accumulated forecasting errors within the window, thereby balancing bias and variability. We evaluate the method using traffic data from the January 2025 California wildfires, focusing on key road segments critical for large-scale evacuations. The results demonstrate that our approach surpasses established machine learning and deep learning models—XGBoost, LSTM, and GRU—in predictive accuracy and maintains high computational efficiency. Notably, the proposed method eliminates the need for offline model training. Moreover, rapid PSO-based tuning enables real-time deployment, which provides a crucial advantage in scenarios where evacuation timings and road closures change dynamically. In conclusion, these findings highlight the benefits of the PSO-enhanced ADE framework for emergency traffic management, where rapid, data-sparse forecasts are essential for effective evacuation planning.

Algebraic derivative estimation↗
DOE OSTI2024

Vertical GaN Superjunction Diode on Sapphire with Kilovolt Dynamic Breakdown Voltage

The development of superjunction structures for use in vertical wide bandgap power devices promise to break the 1-D material limits. Additionally, the possibility of utilizing heteroepitaxial GaN-on-Sapphire wafer for vertical devices can significantly trim the material and device cost. This work introduces a quasi-vertical GaN-on-Sapphire superjunction PN diode design utilizing sputtered p-NiO on the etched GaN fins for superjunction formation. DC breakdown voltage is shown to vary with superjunction charge imbalance and significantly exceed the expected 1-D planar limit of 350V given the epilayer design used. A maximum breakdown voltage of 840 V is extracted for near charge balance conditions limited by leakage current. Dynamic breakdown of the device is characterized as a function of reverse voltage slew rate. A maximum dynamic breakdown voltage of 1160 V under a reverse voltage slew rate of 2000 V/μs is found.

Porter, Matthew↗
DOE OSTI2020

Editors’ Choice—Flooded by Success: On the Role of Electrode Wettability in CO 2 Electrolyzers that Generate Liquid Products

Economic operation of carbon dioxide (CO 2 ) electrolyzers generating liquid products will likely require high reactant conversions and product concentrations, conditions anticipated to challenge existing gas diffusion electrodes (GDEs). Notably, electrode wettability will increase as lower surface tension products (e.g., formic acid, alcohols) are introduced into electrolyte streams, potentially leading to flooding. To understand the hydraulically stable operating envelopes in mixed aqueous-organic liquid domains, we connect intrinsic electrode wettability descriptors to operating parameters such as electrolyte flow rate and current. We first measure contact angles of water-organic product dilutions on polytetrafluoroethylene (PTFE) and graphite surfaces as planar analogues for GDE components. We then use material balances around the reactive gas-liquid-solid interface to calculate product mass fractions as functions of water sweep rate and current. Product composition maps visualize the extent to which changes in cell performance influence capillary pressure, a determinant of GDE saturation. Analyses suggest that formic acid mixtures pose little risk for GDE flooding across a wide range of conditions, but effluents containing <30% alcohol by mass may cause flooding. This study reveals opportunities to integrate microstructural features and oleophobic surface treatments into GDEs to repel aqueous-organic mixtures and expand the window of stable operating conditions.

25 ENERGY STORAGE↗