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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Design principles for energy transfer in the photosystem II supercomplex from kinetic transition networks

Photosystem II (PSII) has the unique ability to perform water-splitting. With light-harvesting complexes, it forms the PSII supercomplex (PSII-SC) which is a functional unit that can perform efficient energy conversion, as well as photoprotection, allowing photosynthetic organisms to adapt to the naturally fluctuating sunlight intensity. Achieving these functions requires a collaborative energy transfer network between all subunits of the PSII-SC. In this work, we perform kinetic analyses and characterise the energy landscape of the PSII-SC with a structure-based energy transfer model. With first passage time analyses and kinetic Monte Carlo simulations, we are able to map out the overall energy transfer network. We also investigate how energy transfer pathways are affected when individual protein complexes are removed from the network, revealing the functional roles of the subunits of the PSII-SC. In addition, we provide a quantitative description of the flat energy landscape of the PSII-SC. We show that it is a unique landscape that produces multiple kinetically relevant pathways, corresponding to a high pathway entropy. These design principles are crucial for balancing efficient energy conversion and photoprotection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Dual-Phase Malicious User Detection Scheme for IM-OFDMA Systems Using IQ Imbalance

Physical-layer security techniques have contributed to the achievement of various security objectives in an efficient and lightweight manner. Thus, these techniques have been widely considered for limited-resource networks such as Internet of Things networks. Among the different security objectives, malicious user detection by exploiting physical-layer parameters has demonstrated efficient performance. In this work, malicious user detection in the recently proposed index modulation-based orthogonal frequency division multiple access (IM-OFDMA) is addressed. The proposed malicious user detection scheme exploits the hardware impairments, especially the in-phase and quadrature imbalance parameters, for both legitimate and malicious users to design a dual-phase efficient detection scheme. The proposed scheme accounts for the special characteristics of IM-OFDMA transmission that are different from other multiple-access techniques. The performance of the proposed scheme was evaluated considering detection probability and false alarm probability performance metrics. Moreover, closed-form expressions of these metrics were derived for both phases and were validated by Monte Carlo simulation results under different configurations of IM-OFDMA systems.

Alaca, Ozgur [ORNL] (ORCID:0000000153713758)↗
DOE OSTI2024

Tunnel junction-enabled monolithically integrated GaN micro-light emitting transistor

GaN/InGaN microLEDs are a very promising technology for next-generation displays. Switching control transistors and their integration are key components in achieving high-performance, efficient displays. Monolithic integration of microLEDs with GaN switching devices provides an opportunity to control microLED output power with capacitive (voltage)-controlled rather than current-controlled schemes. This approach can greatly reduce system complexity for the driver circuit arrays while maintaining device opto-electronic performance. In this work, we demonstrate a 3-terminal GaN micro-light emitting transistor that combines a GaN/InGaN blue tunneling-based microLED with a GaN n-channel FET. Further, the integrated device exhibits excellent gate control, drain current control, and optical emission control. This work provides a promising pathway for future monolithic integration of GaN FETs with microLED to enable fast switching, high-efficiency microLED display and communication systems.

42 ENGINEERING↗
DOE OSTI2024

Tailoring the Coordination Micro‐Environment in Nanotraps for Efficient Platinum/Palladium Separation

Abstract Recovering platinum group metals from secondary resources is crucial to meet the growing demand for high‐tech applications. Various techniques are explored, and adsorption using porous materials has emerged as a promising technology due to its efficient performance and environmental beingness. However, the challenge lies in effectively recovering and separating individual platinum group metals (PGMs) given their similar chemical properties. Herein, a breakthrough approach is presented by sophisticatedly tailoring the coordination micro‐environment in a series of aminopyridine‐based porous organic polymers, which enables the creation of platinum‐specific nanotraps for efficient separation of binary PGMs (platinum/palladium). The newly synthesized POP‐o2NH 2 ‐Py demonstrates record uptakes and selectivity toward platinum over palladium, with the amino groups adjacent to the pyridine moieties being vital in improving platinum binding performance. Further breakthrough experiments underline its remarkable ability to separate platinum and palladium. Spectroscopic analysis reveals that POP‐o2NH 2 ‐Py offers a more favorable coordination fashion to platinum ions compared to palladium ions owing to the greater interaction between N and Pt 4+ and stronger intramolecular hydrogen bonding between the amino groups and four coordinating chlorines at platinum. These findings underscore the importance of fine‐tuning the coordination micro‐environment of nanotraps through subtle modifications that can greatly enhance the selectivity toward the desired metal ions.

Chemistry↗
DOE OSTI2021

Toward efficient single-atom catalysts for renewable fuels and chemicals production from biomass and CO 2

Transformation of biomass and CO 2 into renewable value-added chemicals and fuels has been identified as a promising strategy to fulfill high energy demands, lower greenhouse gas emissions, and exploit under-utilized resources. Cost-effective and performance-efficient catalysts are of great importance to lowering the conversion cost of biomass and CO 2 . Significant progress has been made to advance the catalyst design for these processes, with metal catalysts playing a critical role in many involved catalytic reactions. Traditional nanoparticle-based metal catalysts still require improvement in metal utilization rates, stability, and selectivity tunability. Single-atom catalysts, which have maximum atomic efficiency and a uniform and tunable metal center, as well as an adjustable metal-support interaction, provide potential opportunities to boost catalyst efficiency and thermal stability. Their well-defined and uniform structure also provides advantages to fundamental studies for understanding of the intrinsic reaction mechanism and site requirement in biomass and CO 2 conversion. In this article, we summarize and highlight the recent advances in converting biomass and CO 2 to renewable fuels and chemicals using single-atom catalysts. We discuss the design principles of single-atom catalysts and their potential applications to biomass and CO 2 upgrading as well as the origins of catalytic activity. Moreover, we compare the catalytic efficiency of various catalysts reported thus to provide a fair assessment of these catalysts. Finally, perspectives are given on the interesting fields that may guide future studies.

09 BIOMASS FUELS↗
DOE OSTI2021

UPC++ as_eager Working Group Draft, Revision 2020.6.2

This draft proposes an extension for a new future-based completion variant that can be more effectively streamlined for RMA and atomic access operations that happen to be satisfied at runtime using purely node-local resources. Many such operations are most efficiently performed synchronously using load/store instructions on shared-memory mappings, where the actual access may only require a few CPU instructions. In such cases we believe it’s critical to minimize the overheads imposed by the UPC++ runtime and completion queues, in order to enable efficient operation on hierarchical node hardware using shared-memory bypass. The new upcxx::{source,operation}_cx::as_eager_future() completion variant accomplishes this goal by relaxing the current restriction that future-returning access operations must return a non-ready future whose completion is deferred until a subsequent explicit invocation of user-level progress. This relaxation allows access operations that are completed synchronously to instead return a ready future, thereby avoiding most or all of the runtime costs associated with deferment of future completion and subsequent mandatory entry into the progress engine. We additionally propose to make this new as_eager_future() completion variant the new default completion for communication operations that currently default to returning a future. This should encourage use of the streamlined variant, and may provide performance improvements to some codes without source changes. A mechanism is proposed to restore the legacy behavior on-demand for codes that might happen to rely on deferred completion for correctness. Finally, we propose a new as_eager_promise() completion variant that extends analogous improvements to promise-based completion, and corresponding changes to the default behavior of as_promise().

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Biochemical and spectroscopic characterizations of the oligomeric antenna of the coral symbiotic Symbiodiniaceae Fugacium kawagutii

Light-harvesting antennas in photosynthesis capture light energy and transfer it to the reaction centers (RCs) where photochemistry takes place. The sustainable growth of the reef-building corals relies on a constant supply of the photosynthates produced by the endosymbiotic dinoflagellate, belonging to the family of Symbiodiniaceae. The antenna system in this group consists of the water-soluble peridinin-chlorophyll $\textit{a}$-protein (PCP) and the intrinsic membrane chlorophyll $\textit{a}$-chlorophyll $c_2$-peridinin protein complex (acpPC). In this report, a nonameric acpPC is reported in a dinoflagellate, Fugasium kawagutii (formerly Symbiodinium kawagutii sp. CS-156). We found that extensive biochemical purification altered the oligomerization states of the initially isolated nonameric acpPC. The excitation energy transfer pathways in the acpPC nonamer and its variants were studied using time-resolved fluorescence and time-resolved absorption spectroscopic techniques at 77 K. Compared to the well-characterized trimeric acpPC, the nonameric acpPC contains an 11 nm red-shifted terminal energy emitter and substantially altered excited state lifetimes of Chl $\textit{a}$. The observed energetic overlap of the fluorescence terminal energy emitters with the absorption of RCs is hypothesized to enable efficient downhill excitation energy transfer. Additionally, the shortened Chl $\textit{a}$ fluorescence decay lifetime in the oligomeric acpPC indicate a protective self-relaxation strategy. We propose that the highly-oligomerized acpPC nonamer represents an intact functional unit in the Symbiodiniaceae thylakoid membrane. They perform efficient excitation energy transfer (to RCs), and are under manageable regulations in favor of photoprotection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Gamma-Ray and Cosmic Ray Muon Modalities for Cargo Inspection

Screening and inspection of cargo containers are two essential methods to nondestructively examine the contents of shipment. These methods enable the detection of illicit transportation of unauthorized materials such as nuclear and radioactive materials, explosives, drugs, and so on, typically at borders or secure facilities. Although high-energy X-ray transmission is a standard system and is widely used for cargo inspection, the inherent challenges of high false-positive rates and high attenuation factors necessitate the development of complementary techniques that can increase the detection efficiency and accuracy in large and dense materials. Gamma-rays, which possess higher penetration characteristics because of their high energy, offer an alternative nonintrusive modality for cargo scanning. They represent a promising inspection method when compared to X-rays for three reasons: (1) improved ability to detect nuclear and radioactive materials, (2) higher inspection throughput rates, and (3) lower false-positive rates. Currently, there are two main gamma-ray inspection techniques, active and passive interrogation. Active interrogation can be further grouped into (1) gamma-ray transmission imaging and (2) neutron-induced gamma-ray emission detection. Gamma-ray transmission imaging utilizes differences in material densities for mapping the shipment contents and detecting anomalies. It is analogous to the X-ray transmission method; however, the high-energy photons make it more difficult to shield against, which enables more efficient performance in large and dense material inspection. Neutron-induced gamma-ray emission inspection is designed for the detection of nuclear and radioactive material because those materials emit characteristic gamma-rays when they are activated by neutron absorption. On the other hand, passive interrogation techniques rely on high-efficiency detectors to detect radiation emitted from hidden special nuclear or other radioactive materials. Similar to passive interrogation, cosmic ray muon monitoring and imaging are relatively new techniques that do not require external radioactive sources. These techniques have received attention as a potential next-generation radiographic probe to identify illicit transportation of nuclear and radioactive materials in cargo containers. Cosmic ray muons have unique features, (1) much higher energies than X-rays or gamma-rays (on the order of 10−1—104 GeV), (2) enhanced penetration capability, and (3) natural occurrence, thereby eliminating the need for induced radiation sources. These features enable cosmic ray muons to be utilized for detection of special nuclear materials in high-background-noise environments. By analyzing incoming and outgoing muon trajectories, scattering angles, and energies, it has been shown that it would be possible to locate hidden and well-shielded materials in cargo containers via three-dimensional muon tomography images or signal analysis. Gamma-rays, cosmic ray muons, and other nonintrusive cargo inspection modalities are complementary to each other, allowing them to address various cargo inspection conditions (i.e., scanning time, cost, radiation exposure level, and types of target materials). This chapter presents a detailed review of the theoretical fundamentals and technical principles behind the current gamma-ray and cosmic ray muon modalities for cargo inspection. Additionally, critical assessments and suggestions for the future directions to advance the use of gamma and muon modalities are discussed.

Bae, Junghyun↗
DOE OSTI2025

Generalized framework for likelihood-based field-level inference of growth rate from velocity and density fields

Measuring the growth rate of large-scale structures ( f ) as a function of redshift has the potential to break degeneracies between modified gravity and dark energy models, when combined with expansion-rate probes. Direct estimates of peculiar velocities of galaxies have attracted interest as a means of estimating fσ 8 . In particular, field-level methods can be used to fit the field nuisance parameter along with cosmological parameters simultaneously. This article aims to provide the community with a unified framework for the theoretical modeling of the likelihood-based field-level inference by performing fast field covariance calculations for velocity and density fields. Our purpose is to lay the foundations for a nonlinear extension of the likelihood-based method at the field level. We have developed a generalized framework, implemented in the dedicated software flip to perform a likelihood-based inference of fσ 8 . We derived a new field covariance model, which includes wide-angle corrections. We also included the models previously described in the literature inside our framework. We compared their performance against ours, and we validated our model by comparing it with the two-point statistics of a recent N-body simulation. The tests we performed have allowed us to validate our software and determine the appropriate wavenumber range to integrate our covariance model and its validity in terms of separation. Our framework allows for a wider wavenumber coverage to be used in our calculations than in previous works, which is particularly interesting for nonlinear model extensions. Finally, our generalized framework allows us to efficiently perform a survey geometry-dependent Fisher forecast of the fσ 8 parameter. We show that the Fisher forecast method we developed gives an error bar that is 30% closer to a full likelihood-based estimation than a standard volume Fisher forecast.

Ravoux, Corentin↗
DOE OSTI2025

S AP F LOWER : an automated tool for sap flow data preprocessing, gap-filling, and analysis using deep learning

Sap flow, a critical process in plant water use and ecosystem water cycles, is often measured using thermal dissipation probes (TDP) due to their ease of installation and continuous data collection. However, sap flow data frequently include noise, outliers, and gaps, creating challenges for analysis and requiring substantial manual processing. We developed S AP F LOWER , a tool that automates data preprocessing, model training, gap-filling, sapwood area scaling and modeling, and water use analysis. It integrates autocleaning, machine learning and deep learning models (e.g. random forest, Gaussian process regression, long short-term memory (LSTM), bidirectional LSTM (BiLSTM)), and efficient workflows to process sap flow data. S AP F LOWER can remove over 90% of noisy data while preserving legitimate variations and achieve high accuracy in gap-filling based on user-determined parameters. Random forest, LSTM, and BiLSTM models reduced root mean square error to 10% or less for long-term gaps. Model training and prediction can be performed efficiently within seconds. S AP F LOWER significantly enhances the efficiency and accessibility of TDP data analysis by automating complex tasks, enabling researchers without programming expertise to employ advanced techniques. Future improvements will focus on species-specific corrections for TDP and support for additional measurement methods. S AP F LOWER is openly available on GitHub (https://github.com/JiaxinWang123/SapFlower) and Zenodo (doi: 10.5281/zenodo.13665919).

ecosystem water balance↗
DOE OSTI2021

Fuel Property Effects of a Broad Range of Potential Biofuels on Mixing Control Compression Ignition Engine Performance and Emissions

Conventional diesel engines will continue to hold a vital role in the heavy- and medium-duty markets for the transportation of goods along with many other uses. The ability to offset traditional diesel fuels with low-net-carbon biofuels could have a significant impact on reducing the carbon footprint of these vehicles. A prior study screened several hundred candidate biofuel blendstocks based on required diesel blendstock properties and identified 12 as the most promising. Eight representative biofuel blendstocks were blended at a 30% volumetric concentration with EPA certification ultra-low-sulfur diesel (ULSD) and were investigated for emissions and fuel efficiency performance. This study used a single cylinder engine (based on the Ford 6.7L engine) using Conventional Diesel Combustion (CDC), also known as Mixing Control Compression Ignition (MCCI). The density, cetane number, distillation curve and sooting tendency (using the yield sooting index method) of the fuels were measured. Start of injection (SOI) timing and exhaust gas recirculation (EGR) sweeps were conducted at three separate speed-load operating points to examine fuel effects on the NOX/soot and NOX/efficiency trade-offs as well as to evaluate EGR tolerance. The results show that the biofuel blends all reduced NOX and soot emissions without penalty to engine efficiency, even improving efficiency for some of the blends at certain points, with one particular blend of polyoxymethylene ethers (POMEs) improving efficiency at all points while drastically reducing soot by 79%.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Heavy-Duty Low-Temperature and Diesel Combustion & Heavy-Duty Combustion Modeling (FY 2018 Annual Progress Report)

Regulatory drivers and market demands for lower pollutant emissions, lower carbon dioxide emissions, and lower fuel consumption motivate the development of clean and fuel-efficient engine operating strategies. Most current production engines use a combination of both in-cylinder and exhaust emission control strategies to achieve these goals. The emissions and efficiency performance of in-cylinder strategies depend strongly on flow and mixing processes associated with fuel injection. Both heavy- and light-duty engine/vehicle manufacturers use multiple-injection strategies to reduce noise, emissions, and fuel consumption. For both conventional and low-temperature diesel combustion, the state of knowledge and modeling tools for multiple injections are far less advanced than for single-injection strategies. Engine efficiency is limited to some degree by tradeoffs that must be accepted to meet particulate matter (including soot) emissions limits. Recent work on this project has filled some knowledge gaps on soot oxidation with multiple injections, and the current work for Fiscal Year (FY) 2018 addresses knowledge gaps on soot formation for multiple injections. While total in-cylinder soot is readily measured, discerning formation from oxidation is difficult. The FY 2018 experiments are designed to create in-cylinder conditions at the threshold of soot formation, where processes that affect soot formation can be more readily discerned. Soot formation pathways under such conditions are fraught with uncertainties, and soot models significantly overpredict polyaromatic hydrocarbon (PAH) and soot, so experimental data at these conditions will provide much needed data for improvements to PAH and soot models.

02 PETROLEUM↗
DOE OSTI2022

Benchmarking Real-Time Control Platforms Using a Matlab/Simulink Coder with Applications in the Control of DC/AC Switched Power Converters

In the control of DC/AC switched power converters (SPC), one of the most important aspects to be considered is the selection of the real-time control platform. The real-time control platform must be able to meet the high performance efficiency and regulation requirements of the DC/AC SPC, as these typically operate at switching frequencies in the order of kHz to MHz. For this reason, the hardware characteristics of the ADC and PWM, and the processing capacity of the real-time control platform are of vital importance when implementing advanced digital controllers that maintain voltage and current levels within regulatory standards. In this context, we aimed to perform a comparative study of the computation times of different real-time control platforms when implementing different control strategies for DC/AC switched power converters. We also analyzed the impact of the real-time control platforms on the THD of the voltages generated by the DC/AC switched power converters. With the help of this paper, researchers and developers will have criteria to select which real-time control platform to use in real-time control for DC/AC SPC applications.

42 ENGINEERING↗
DOE OSTI2020

Strong mutual increase in the efficiency of isotope-selective laser IR dissociation of molecules under nonequilibrium thermodynamic conditions of the compression shock under irradiation in a bimolecular mixture

We have revealed a strong (by a factor of 2 to 5) mutual increase in the yield of IR molecular dissociation (by the example of CF{sub 2}HCl and CF{sub 3}Br) and a significant (by a factor of 1.5 to 3) lowering of dissociation thresholds in the nonequilibrium thermodynamic conditions of compression shock in the irradiation of the molecules by resonance IR laser radiation in the bimolecular mixture in comparison with their individual irradiation. This opens up the possibility to perform efficient isotope-selective IR dissociation of molecules at lower excitation energy densities (Φ ⩽ 1.5 – 2.0 J cm{sup −2}) and thereby to improve the dissociation selectivity. This was demonstrated by the example of chlorine- and bromine-isotope selective dissociation of the specified molecules, which are characterised by quite small (less than 0.25 cm{sup −1}) isotope shifts in the IR vibrational absorption spectra excited by laser radiation. The enrichment coefficients K {sub enr}({sup 35}Cl / {sup 37}Cl) = 0.90 ± 0.05 in the residual CF{sub 2}HCl gas and K {sub enr}({sup 79}Br / {sup 81}Br) in the resultant Br{sub 2} product are obtained when the CF{sub 2}HCl : CF{sub 3}Br = 1 : 1 molecular mixture and CF{sub 3}Br molecules, respectively, are irradiated by the 9R(30) CO{sub 2} laser line (frequency, 1084.635 cm{sup −1}) at an energy density Φ ≈ 1.3 J cm{sup −2}. (laser isotope separation)

36 MATERIALS SCIENCE↗
DOE OSTI2021

Imposing equilibrium on experimental 3-D stress fields using Hodge decomposition and FFT-based optimization

Here, we present a methodology to impose micromechanical constraints, i.e. stress equilibrium at grain and sub-grain scale, to an arbitrary (non-equilibrated) voxelized stress field obtained, for example, by means of synchrotron X-ray diffraction techniques. The method consists in finding the equilibrated stress field closest (in L 2 -norm sense) to the measured non-equilibrated stress field, via the solution of an optimization problem. The extraction of the divergence-free (equilibrated) part of a general (non-equilibrated) field is performed using the Hodge decomposition of a symmetric matrix field, which is the generalization of the Helmholtz decomposition of a vector field into the sum of an irrotational field and a solenoidal field. The combination of: a) the Euler–Lagrange equations that solve the optimization problem, and b) the Hodge decomposition, gives a differential expression that contains the bi-harmonic operator and two times the curl operator acting on the experimental stress field. These high-order derivatives can be efficiently performed in Fourier space. The method is applied to filter the non-equilibrated parts of a synthetic piecewise constant stress fields with a known ground truth, and stress fields in Gum Metal, a beta-Ti-based alloy measured in-situ using Diffraction Contrast Tomography (DCT). In both cases, the largest corrections were obtained near grain boundaries.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Development of lean, efficient, and fast physics-framed deep-learning-based proxy models for subsurface carbon storage

In this work, we present deep-learning-based surrogate models for CCUS developed with four different algorithms and a physics-framed two-phase flow problem involving displacement of water by CO 2 . The deep-learning models were trained using 3D datasets describing the pressure plume, CO 2 saturation plume, and water extraction rate generated by numerical simulation. The hyperparameters defining the architecture of the neural networks were optimized to determine the slimmest network size and training parameters that give the most efficient performance at the least training cost. To develop a robust model that closely mimics the governing physical laws, the discretized form of the two-phase fluid transport equation was used to formulate the supervised deep-learning task. The algorithms investigated in this study predicted the data to above 95% accuracy, with the multi-layer perceptron model demonstrating the best performance by balancing training speed, prediction time, and prediction accuracy with lean network capacity. Furthermore, the surrogate models simultaneously predict reservoir pressure and CO 2 saturation in every grid block, including the surface well extraction rate and bottomhole pressure, at all simulation times for a given static model realization in just a few seconds on a standard desktop computer. A key outcome of this study is that limits can be placed on network design parameters to avoid over designing neural networks, with associated efficiencies in training and prediction times. This is very useful because large volumes of data may be generated in CCUS projects and over-design of neural network architectures imposes penalties that are antithetical to the goal of near-real time forecasting.

58 GEOSCIENCES↗
DOE OSTI2021

Resilience and fault tolerance in high-performance computing for numerical weather and climate prediction

Progress in numerical weather and climate prediction accuracy greatly depends on the growth of the available computing power. As the number of cores in top computing facilities pushes into the millions, increased average frequency of hardware and software failures forces users to review their algorithms and systems in order to protect simulations from breakdown. This report surveys hardware, application-level and algorithm-level resilience approaches of particular relevance to time-critical numerical weather and climate prediction systems. A selection of applicable existing strategies is analysed, featuring interpolation-restart and compressed checkpointing for the numerical schemes, in-memory checkpointing, user-level failure mitigation and backup-based methods for the systems. Numerical examples showcase the performance of the techniques in addressing faults, with particular emphasis on iterative solvers for linear systems, a staple of atmospheric fluid flow solvers. The potential impact of these strategies is discussed in relation to current development of numerical weather prediction algorithms and systems towards the exascale. Trade-offs between performance, efficiency and effectiveness of resiliency strategies are analysed and some recommendations outlined for future developments.

54 ENVIRONMENTAL SCIENCES↗