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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Optimization-based modeling and economic comparison of membrane distillation configurations for application in shale gas produced water treatment

Membrane distillation (MD) is an emerging membrane technology with great potential for treatment of hypersaline wastewater generated by unconventional (shale) oil and gas reservoirs. However, the low energy efficiency of this technology makes the operating cost of MD systems relatively high, especially in the absence of waste heat. There are several MD configurations with inherent advantages and disadvantages and varying performance. As such, there is a need for thermo-economic optimization of MD systems in a systematic manner to assess their economic performance. Here we present an optimization framework to model and compare the performance of six MD configurations (DCMD, AGMD, PGMD, CGMD, SGMD, and VMD) in continuous recirculation mode for treatment of hypersaline wastewater. The optimization results show that AGMD with small gap size operated at low stream Reynolds number outperforms all other configurations with treatment cost of 4.57 US $/m 3 of feed. However, restricting the system design to more practically relevant operating conditions, such as higher Reynolds number and larger gap size, diminishes the cost superiority of AGMD over other configurations. We also observed that treatment cost using PGMD configuration approaches those of CGMD and DCMD, particularly when modules with small gaps are used.

42 ENGINEERING↗
DOE OSTI2023

Multiscale graph neural network autoencoders for interpretable scientific machine learning

The goal of this work is to address two limitations in autoencoder-based models: latent space interpretability and compatibility with unstructured meshes. This is accomplished here with the development of a novel graph neural network (GNN) autoencoding architecture with demonstrations on complex fluid flow applications. To address the first goal of interpretability, the GNN autoencoder achieves reduction in the number nodes in the encoding stage through an adaptive graph reduction procedure. Further, this reduction procedure essentially amounts to flowfieldconditioned node sampling and sensor identification, and produces interpretable latent graph representations tailored to the flowfield reconstruction task in the form of so-called masked fields. These masked fields allow the user to (a) visualize where in physical space a given latent graph is active, and (b) interpret the time-evolution of the latent graph connectivity in accordance with the time-evolution of unsteady flow features (e.g. recirculation zones, shear layers) in the domain. To address the goal of unstructured mesh compatibility, the autoencoding architecture utilizes a series of multi-scale message passing (MMP) layers, each of which models information exchange among node neighborhoods at various lengthscales. The MMP layer, which augments standard single-scale message passing with learnable coarsening operations, allows the decoder to more efficiently reconstruct the flowfield from the identified regions in the masked fields. Analysis of latent graphs produced by the autoencoder for various model settings are conducted using unstructured snapshot data sourced from large-eddy simulations in a backward-facing step (BFS) flow configuration with an OpenFOAM-based flow solver at high Reynolds numbers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Reliability of tandem solar cells and modules: what's next?

Hybrid tandem photovoltaic (PV) technology development has gained momentum in the last few years. This has been motivated by a need to push module efficiencies beyond what is theoretically capable with single-junction technologies to further accelerate total global PV deployment. Significant advances have been made with multiple material systems achieving tandem efficiencies over 30% in the last decade. All of the highest record efficiencies have been from laboratory-scale devices, with areas of 1 cm2 or less. Interestingly, there are multiple material combinations and terminal configurations that have demonstrated promising results. Despite these high laboratory efficiencies, reasonable service lifetimes (a useful operating lifetime of at least 25 years) are needed for tandems to compete with the levelized cost of energy (LCOE) of traditional single junction PV technologies. Existing commercial Si PV products have demonstrated performance in the field with an average of less than 1% relative annual degradation in module and system performance, and many manufacturers now provide 30 year warranties on their products.

14 SOLAR ENERGY↗
DOE OSTI2025

Non-destructive evaluation and machine learning methods for inspection of spent nuclear fuel canisters: A state-of-the-art review

Nuclear energy is among the cleanest and most efficient energy sources currently available. The operation of nuclear power plants (NPPs) produces large amounts of high-level radioactive waste known as spent nuclear fuel (SNF). Currently, large amounts of SNF is stored in dry cask storage systems (DCSSs) for extended interim storage until a permanent disposal solution becomes available. During the extended interim storage, the DCSS, particularly the SNF canisters, may degrade and abnormal conditions may occur. Therefore, non-destructive evaluation (NDE) and machine learning (ML) approaches are necessary for inspection of SNF canisters. This paper presents a state-of-the-art review of literature by summarizing recent progress made on the applications of NDE and ML for inspection of SNF canisters. Sixteen NDE methods are examined and compared: visual inspection, ultrasonic guided waves (UGWs), laser-based approaches, acoustic emission (AE), eddy current testing (ECT), non-invasive acoustic sensing, dynamic modal testing, cosmic ray muons tomography, neutron imaging, gamma rays detection, fiber optical sensors, through-wall communications, X-ray computed tomography (CT), vibrothermography, monoenergetic photon sources, and surface acoustic wave (SAW) sensors. The technology readiness level (TRL) for each method is assessed and compared. Recent publications on ML-enhanced visual inspection, AE, non-invasive acoustic sensing, dynamic modal testing, and neutron imaging for SNF canisters are summarized and future research needs are identified. In conclusion, this review article provides a convenient reference on the state-of-the-art applications of NDE and ML methods for inspection of SNF canisters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

GX: a GPU-native gyrokinetic turbulence code for tokamak and stellarator design

GX is a code designed to solve the nonlinear gyrokinetic system for low-frequency turbulence in magnetized plasmas, particularly tokamaks and stellarators. In GX, our primary motivation and target is a fast gyrokinetic solver that can be used for fusion reactor design and optimization along with wide-ranging physics exploration. Here, this has led to several code and algorithm design decisions, specifically chosen to prioritize time to solution. First, we have used a discretization algorithm that is pseudospectral in the entire phase space, including a Laguerre–Hermite pseudospectral formulation of velocity space, which allows for smooth interpolation between coarse gyrofluid-like resolutions and finer conventional gyrokinetic resolutions and efficient evaluation of a model collision operator. Additionally, we have built GX to natively target graphics processors (GPUs), which are among the fastest computational platforms available today. Finally, we have taken advantage of the reactor-relevant limit of small $\rho _*$ by using the radially local flux-tube approach. In this paper we present details about the gyrokinetic system and the numerical algorithms used in GX to solve the system. We then present several numerical benchmarks against established gyrokinetic codes in both tokamak and stellarator magnetic geometries to verify that GX correctly simulates gyrokinetic turbulence in the small $\rho _*$. Moreover, we show that the convergence properties of the Laguerre–Hermite spectral velocity formulation are quite favourable for nonlinear problems of interest. Coupled with GPU acceleration, which we also investigate with scaling studies, this enables GX to be able to produce useful turbulence simulations in minutes on one (or a few) GPUs and higher fidelity results in a few hours using several GPUs. GX is open-source software that is ready for fusion reactor design studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Understanding and Mitigating Stickiness in Biochar Produced through Acid Hydrolysis and Dehydration

Levulinic acid is a platform chemical with significant potential for conversion into a wide range of biobased chemicals and fuels. A common process for producing levulinic acid from lignocellulosic feedstocks involves acid hydrolysis and dehydration (AHDH), where hexose polymers are hydrolyzed into monomeric sugars and subsequently dehydrated to levulinic acid and formic acid in the presence of dilute sulfuric acid. However, scaling the AHDH process is challenging because of the formation of byproducts such as sticky biochar, which accumulates in continuous-flow reactors, reducing effective reaction volume and increasing process downtime. This study investigates the effect of a chemical preconditioning step on mitigating sticky biochar formation. Woody biomass was preconditioned at 170 °C with 0.26 wt % sulfuric acid for 30 min, resulting in substantial removal of hemicellulose and acid-soluble lignin. AHDH of these preconditioned solids produced biochar that did not adhere to reactor surfaces. TGA analysis confirmed that the chemical preconditioning step minimized interactions between hemicellulose-derived degradation products and lignin side chains, reducing sticky char formation. Additionally, the study observed a 6% higher yield of organic acids from softwood species compared to hardwoods, with bark content shown to negatively impact yield. These findings suggest that targeted preconditioning of lignocellulosic biomass can enhance reactor operability and improve organic acid production efficiency in AHDH processes.

biopolymers↗
DOE OSTI2025

Joint Theoretical and Experimental Study of the Electronic, Magnetic, and Lattice Phonon Dynamics Properties of Ca x Fe y O z Compounds Applied to CO 2 Capture

Unleashing energy innovation ensures a resilient and reliable energy supply. There is a critical need for the development of new carbon dioxide (CO 2 ) captors that have improved energy efficiency accompanied by lower capital and operational costs to ensure abundant, affordable, and secure energy. Among solid materials, CaO is a good CO 2 sorbent for capture technology due to its wide availability and low cost. However, CaO also suffers from some disadvantages, such as high calcination temperature, decreasing capability due to sintering, attrition, and reaction with SO x and NO x . In this study, we employed an ab initio thermodynamic approach and experimental measurements to improve its CO 2 capture performance during the cycles. To do so, we explored the electronic, magnetic, and lattice dynamic properties of a series of calcium ferrites (Ca x Fe y O z ) and applied them for CO 2 capture. Our results showed that all of them can thermodynamically react with CO 2 to form CaCO 3 and iron oxides. Compared to pure CaO capturing CO 2 , CaFe 3 O 4 , CaFe 2 O 4 , and Ca 2 Fe 2 O 5 could shift the CO 2 regeneration temperature to a lower range. The experimental measurements showed that CaFeO 2 is a good CO 2 captor with or without the presence of an O 2 presence. The calculated thermodynamic properties of Ca x Fe y O z capturing the CO 2 reactions can be used to find their operational temperature ranges for different CO 2 capture technologies.

CO2 capture↗
DOE OSTI2025

Kinetics and Thermodynamics of Sr Permeation in CeO 2 -Based Barrier Layers for Solid-Oxide Electrolyzer Cells

Solid-oxide electrolyzer cells (SOECs) convert steam to hydrogen efficiently at high temperatures. However, during operation, the diffusion of cations or impurities through the cells due to electrode degradation can cause unwanted secondary phases to form, which may degrade device performance. Here, in this study, we use atomistic and mesoscale simulations coupled with experimental analysis to study the diffusion of Sr through the Gd-doped CeO 2 (GDC) barrier layer used to protect the yttria-stabilized zirconia (YSZ) electrolyte in SOECs. From our atomistic calculations, we find Sr diffusion to be negligibly slow in bulk GDC; however, surface diffusion is much more favorable. Subsequent mesoscale simulations show that Sr diffusion is activated when the porosity of GDC exceeds ∼10% and significantly exceeds diffusion in bulk and grain boundary regions. We also find that SrO-based species can accumulate at GDC surfaces; however, SrO aggregation and coarsening will be limited by the large lattice mismatch between GDC and SrO. Energy-dispersive X-ray spectroscopy (EDS) and electron diffraction confirm that Sr can accumulate within GDC pores and form disperse Sr-containing secondary phases. Altogether, Sr diffusion in dense GDC is unlikely to give rise to thick SrO layers, which would severely limit device performance. The formation of Sr-containing secondary phases can largely be avoided by restricting the porosity of the GDC layer as much as possible.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Toward Fullerene-Free PIN Perovskite Solar Cells

We highlight opportunities for a transformative shift in perovskite solar cell design by expanding electron transport layers (ETLs) beyond fullerenes. Fullerenes have known limitations, including constraints on open-circuit voltage, stability, and mechanical integrity. Recently, fullerene-free p-i-n cells with power conversion efficiencies exceeding 25% have been demonstrated via both naphthalene diimide-SnO x bilayers and nonfullerene acceptor-based ETLs. Despite successes, fullerenes remain the de facto ETLs for perovskites. Drawing lessons from organic photovoltaics, where it took decades to transition from fullerenes to more broadly available and efficient materials, we explore pathways to accelerate the development and adoption of fullerene-free ETLs. This requires understanding the similarities and differences between organic and perovskite solar cells, which will necessitate carefully designing fullerene replacements with both, high efficiency and also, critically, durability under operation. Here, we incorporate literature data to facilitate comparisons, and independently conduct fracture energy measurements for alternative ETL configurations to motivate their adoption.

14 SOLAR ENERGY↗
DOE OSTI2021

Lead-Free Organic–Perovskite Hybrid Quantum Wells for Highly Stable Light-Emitting Diodes

Two-dimensional perovskites that could be regarded as natural organic-inorganic hybrid quantum wells (HQWs) are promising for light-emitting diode (LED) applications. High photoluminescence quantum efficiencies (approaching 80%) and extremely narrow emission bandwidth (less than 20 nm) have been demonstrated in their single crystals; however, a reliable electrically driven LED device has not been realized owing to inefficient charge injection and extremely poor stability. Furthermore, the use of toxic lead raises concerns. Here, we report Sn(II)-based organic-perovskite HQWs employing molecularly tailored organic semiconducting barrier layers for efficient and stable LEDs. Utilizing femtosecond transient absorption spectroscopy, we demonstrate the energy transfer from organic barrier to inorganic perovskite emitter occurs faster than the intramolecular charge transfer in the organic layer. Consequently, this process allows efficient conversion of lower-energy emission associated with the organic layer into higher-energy emission from the perovskite layer. Thus, this greatly broadened the candidate pool for the organic layer. Incorporating a bulky small bandgap organic barrier in the HQW, charge transport is enhanced and ion migration is greatly suppressed. We demonstrate a HQW-LED device with pure red emission, a maximum luminance of 3466 cd m -2 , a peak external quantum efficiency up to 3.33%, and an operational stability of over 150 h, which are significantly better than previously reported lead-free perovskite LEDs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Snapshot multispectral imaging using a diffractive optical network

Abstract Multispectral imaging has been used for numerous applications in e.g., environmental monitoring, aerospace, defense, and biomedicine. Here, we present a diffractive optical network-based multispectral imaging system trained using deep learning to create a virtual spectral filter array at the output image field-of-view. This diffractive multispectral imager performs spatially-coherent imaging over a large spectrum, and at the same time, routes a pre-determined set of spectral channels onto an array of pixels at the output plane, converting a monochrome focal-plane array or image sensor into a multispectral imaging device without any spectral filters or image recovery algorithms. Furthermore, the spectral responsivity of this diffractive multispectral imager is not sensitive to input polarization states. Through numerical simulations, we present different diffractive network designs that achieve snapshot multispectral imaging with 4, 9 and 16 unique spectral bands within the visible spectrum, based on passive spatially-structured diffractive surfaces, with a compact design that axially spans ~72 λ m , where λ m is the mean wavelength of the spectral band of interest. Moreover, we experimentally demonstrate a diffractive multispectral imager based on a 3D-printed diffractive network that creates at its output image plane a spatially repeating virtual spectral filter array with 2 × 2 = 4 unique bands at terahertz spectrum. Due to their compact form factor and computation-free, power-efficient and polarization-insensitive forward operation, diffractive multispectral imagers can be transformative for various imaging and sensing applications and be used at different parts of the electromagnetic spectrum where high-density and wide-area multispectral pixel arrays are not widely available.

36 MATERIALS SCIENCE↗
DOE OSTI2020

High permeability sub-nanometre sieve composite MoS 2 membranes

Two-dimensional membranes have gained enormous interest due to their potential to deliver precision filtration of species with performance that can challenge current desalination membrane platforms. Molybdenum disulfide (MoS 2 ) laminar membranes have recently demonstrated superior stability in aqueous environment to their extensively-studied analogs graphene-based membranes; however, challenges such as low ion rejection for high salinity water, low water flux, and low stability over time delay their potential adoption as a viable technology. Here, we report composite laminate multilayer MoS 2 membranes with stacked heterodimensional one- to two-layer-thick porous nanosheets and nanodisks. These membranes have a multimodal porous network structure with tunable surface charge, pore size, and interlayer spacing. In forward osmosis, our membranes reject more than 99% of salts at high salinities and, in reverse osmosis, small-molecule organic dyes and salts are efficiently filtered. Finally, our membranes stably operate for over a month, implying their potential for use in commercial water purification applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Quantum barriers engineering toward radiative and stable perovskite photovoltaic devices

Efficient photovoltaic devices must be efficient light emitters to reach the thermodynamic efficiency limit. Here, we present a promising prospect of perovskite photovoltaics as bright emitters by harnessing the significant benefits of photon recycling, which can be practically achieved by suppressing interfacial quenching. We have achieved radiative and stable perovskite photovoltaic devices by the design of a multiple quantum well structure with long (~3 nm) organic spacers with oleylammonium molecules at perovskite top interfaces. Our L-site exchange process (L: barrier molecule cation) enables the formation of stable interfacial structures with moderate conductivity despite the thick barriers. Compared to popular short (~1 nm) Ls, our approach results in enhanced radiation efficiency through the recursive process of photon recycling. This leads to the realization of radiative perovskite photovoltaics with both high photovoltaic efficiency (in-lab 26.0%, certified to 25.2%) and electroluminescence quantum efficiency (19.7 % at peak, 17.8% at 1-sun equivalent condition). Furthermore, the stable crystallinity of oleylammonium-based quantum wells enables our devices to maintain high efficiencies for over 1000 h of operation and >2 years of storage.

14 SOLAR ENERGY↗
DOE OSTI2023

Co-deposition of hole-selective contact and absorber for improving the processability of perovskite solar cells

Simplifying the manufacturing processes of renewable energy technologies is crucial to lowering the barriers to commercialization. In this context, to improve the manufacturability of perovskite solar cells (PSCs), here we have developed a one-step solution-coating procedure in which the hole-selective contact and perovskite light absorber spontaneously form, resulting in efficient inverted PSCs. We observed that phosphonic or carboxylic acids, incorporated into perovskite precursor solutions, self-assemble on the indium tin oxide substrate during perovskite film processing. They form a robust self-assembled monolayer as an excellent hole-selective contact while the perovskite crystallizes. Our approach solves wettability issues and simplifies device fabrication, advancing the manufacturability of PSCs. Our PSC devices with positive-intrinsic-negative (p-i-n) geometry show a power conversion efficiency of 24.5% and retain >90% of their initial efficiency after 1,200 h of operating at the maximum power point under continuous illumination. The approach shows good generality as it is compatible with different self-assembled monolayer molecular systems, perovskites, solvents and processing methods.

14 SOLAR ENERGY↗
DOE OSTI2025

Online Electron Reconstruction at CLAS12

Online reconstruction plays a crucial role in monitoring and in real-time analysis of high energy and nuclear physics experiments. A vital aspect of reconstruction algorithms is particle identification, which combines information from various detector components to determine the type of particle. Electron identification is particularly significant in electro-production nuclear physics experiments like the CLAS12 spectrometer at Jefferson Laboratory as it is essential in data recording. A machine learning approach has been developed for CLAS12 experiments to reconstruct and identify electrons by combining raw signals from multiple detector components at the data acquisition level. This method achieves high electron identification purity while maintaining nearly 100% efficiency. Furthermore, the machine learning tools operate at rates exceeding data acquisition speed, enabling the real-time electron reconstruction. This advancement significantly improves online analyses and monitoring capabilities for CLAS12 experiments.

Tyson,, Richard [Thomas Jefferson National Acceler↗
DOE OSTI2026

Design, Manufacturing, and Installation of DIII-D Lower Hybrid Current Drive Outer Wall Waveguides and Expandable Vacuum Interface

High field side lower hybrid current drive (HFS LHCD) is promising method for efficient, off axis current drive. To operate this system, development of an expandable combination radio frequency (RF) and vacuum interface was necessary to allow the long (~2 m) waveguides to thermally expand with respect to the DIII-D 0 degree R-1 port extension without damage to the waveguide or excessive force on the vacuum seals which was previously observed when baking the waveguides during operations that were installed in 2024. Design of a custom bellows assembly with RF feedthrough that allows >20mm of waveguide thermal expansion is presented. Fabrication of this bellows assembly required simultaneously vacuum brazing multiple 304 stainless steel flanges to an oxygen free high conductivity copper waveguide section which required significant manufacturing development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Flexible hose interconnect testing for parabolic troughs with nitrate salt

The use of molten salt as a heat transfer fluid in parabolic trough concentrated solar power plants, in lieu of oil-based heat transfer fluids, presents the possibility to increase the plant's operating temperature and corresponding Rankine cycle efficiency, improve dispatchability, and decrease costs. However, several barriers still exist to commercialization of the technology. This paper discusses meaningful progress toward overcoming two specific barriers to commercialization; 1) the lack of a reliable interconnect solution for molten salt service to connect rotating collectors with stationary header pipes and 2) the limitations of publicly available system modeling tools for a plant using molten salt as both the heat transfer fluid and energy storage medium.

14 SOLAR ENERGY↗
DOE OSTI2022

Automatic derivation of many-body theories based on general Fermi vacua

This paper describes Wick&D, an implementation of the algebra of second-quantized operators normal ordered with respect to general correlated references and the corresponding Wick theorem [D. Mukherjee, Chem. Phys. Lett. 274, 561 (1997) and W. Kutzelnigg and D. Mukherjee, J. Chem. Phys. 107, 432 (1997)]. Wick&D employs a compact representation of operators and a backtracking algorithm to efficiently evaluate Wick contractions. Since Wick&D can handle both fully and partially contracted terms, it can be applied to both projective and Fock-space many-body formalisms. To demonstrate the usefulness of Wick&D, here we use it to evaluate the single-reference coupled cluster equations up to octuple excitations and report an automated derivation and implementation of the second-order driven similarity renormalization group multireference perturbation theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗