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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A high-resolution large-eddy simulation framework for wildland fire predictions using TensorFlow

Background: Wildfires are becoming more severe, so we need improved tools to predict them over a wide range of conditions and scales. One approach towards this goal entails the use of coupled fire/atmosphere modelling tools. Although significant progress has been made in advancing their physical fidelity, existing tools have not taken full advantage of emerging programming paradigms and computing architectures to enable high-resolution wildfire simulations. Aims: The aim of this study was to present a new framework that enables landscape-scale wildfire simulations with physical representation of combustion at an affordable cost. Methods: We developed a coupled fire/atmosphere simulation framework using TensorFlow, which enables efficient and scalable computations on Tensor Processing Units. Key Results: Simulation results for a prescribed fire were compared with experimental data. Predicted fire behavior and statistical analysis for fire spread rate, scar area, and intermittency showed overall reasonable agreement. Scalability analysis was performed, showing close to linear scaling. Conclusions: While mesh refinement was shown to have less impact on global quantities, such as fire scar area and spread rate, it benefits predictions of intermittent fire behavior, buoyancy-driven dynamics, and small-scale turbulent motion. Implications: This new simulation framework is efficient in capturing both global quantities and unsteady dynamics of wildfires at high spatial resolutions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Development of a colloidal gold immunochromatographic assay strip using monoclonal antibody for rapid detection of porcine deltacoronavirus

Porcine deltacoronavirus (PDCoV) cause diarrhea and dehydration in newborn piglets and has the potential for cross-species transmission. Rapid and early diagnosis is important for preventing and controlling infectious disease. In this study, two monoclonal antibodies (mAbs) were generated, which could specifically recognize recombinant PDCoV nucleocapsid (rPDCoV-N) protein. A colloidal gold immunochromatographic assay (GICA) strip using these mAbs was developed to detect PDCoV antigens within 15 min. Results showed that the detection limit of the GICA strip developed in this study was 10 3 TCID 50 /ml for the suspension of virus-infected cell culture and 0.125 μg/ml for rPDCoV-N protein, respectively. Besides, the GICA strip showed high specificity with no cross-reactivity with other porcine pathogenic viruses. Three hundred and twenty-five fecal samples were detected for PDCoV using the GICA strip and reverse transcription-quantitative real-time PCR (RT-qPCR). The coincidence rate of the GICA strip and RT-qPCR was 96.9%. The GICA strip had a diagnostic sensitivity of 88.9% and diagnostic specificity of 98.5%. The specific and efficient detection by the strip provides a convenient, rapid, easy to use and valuable diagnostic tool for PDCoV under laboratory and field conditions.

Wang, Wei↗
DOE OSTI2022

Assessing the performance of global thermostat adjustment in commercial buildings for load shifting demand response

Abstract Efficiently leveraging new sources of flexibility is critical to mitigating load balancing challenges posed by variable renewable resources. The thermal inertia of commercial buildings allows us to shift their power consumption on minute to hourly timescales to provide demand response to the grid while maintaining occupant comfort. Global thermostat adjustment (GTA) provides a readily available and scalable approach for implementing load shifting demand response using commercial heating, ventilation, and air conditioning (HVAC) systems, since it leverages the inherent sophistication of modern building automation systems. However, there is an incomplete understanding of GTA’s performance for this purpose and its impact on building systems and occupant comfort. In this paper, we explore the performance of GTA by analyzing results from nearly nine hundred experiments on eight university campus buildings in Michigan and North Carolina. Using GTA, we manipulate each building’s thermostat setpoints causing the building to shift its power consumption with respect to its baseline. We quantify the magnitude of HVAC power response, energy use of HVAC subsystems, and impact on occupant comfort. Finally, we connect our experimental results with power system operation using an optimization model that coordinates GTA actions across a large collection of grid-interactive efficient buildings (GEBs) to reduce high ramp rates on the grid and mitigate renewable energy curtailment. Overall, our work finds that the impacts on HVAC subsystems are often complex, and may result in additional energy being consumed by fans and terminal reheat. These effects must be considered when using GTA for load shifting. Additionally, we demonstrate that occupant comfort, as assessed by indoor temperature and humidity, can be maintained during GTA events. From a societal perspective, our modeling work finds that the additional renewable energy that can be integrated through the use of GTA strategies eclipses any additional energy consumed by buildings.

Keskar, Aditya (ORCID:0000000244617980)↗
DOE OSTI2023

Unidirectional Sidechain Engineering to Construct Dual‐Asymmetric Acceptors for 19.23 % Efficiency Organic Solar Cells with Low Energy Loss and Efficient Charge Transfer

Abstract Achieving both high open‐circuit voltage ( V oc ) and short‐circuit current density ( J sc ) to boost power‐conversion efficiency (PCE) is a major challenge for organic solar cells (OSCs), wherein high energy loss ( E loss ) and inefficient charge transfer usually take place. Here, three new Y‐series acceptors of mono‐asymmetric asy‐YC11 and dual‐asymmetric bi‐asy‐YC9 and bi‐asy‐YC12 are developed. They share the same asymmetric D 1 AD 2 (D 1 =thieno[3,2‐ b ]thiophene and D 2 =selenopheno[3,2‐ b ]thiophene) fused‐core but have different unidirectional sidechain on D 1 side, allowing fine‐tuned molecular properties, such as intermolecular interaction, packing pattern, and crystallinity. Among the binary blends, the PM6 : bi‐asy‐YC12 one has better morphology with appropriate phase separation and higher order packing than the PM6 : asy‐YC9 and PM6 : bi‐asy‐YC11 ones. Therefore, the PM6 : bi‐asy‐YC12‐based OSCs offer a higher PCE of 17.16 % with both high V oc and J sc , due to the reduced E loss and efficient charge transfer properties. Inspired by the high V oc and strong NIR‐absorption, bi‐asy‐YC12 is introduced into efficient binary PM6 : L8‐BO to construct ternary OSCs. Thanks to the broadened absorption, optimized morphology, and furtherly minimized E loss , the PM6 : L8‐BO : bi‐asy‐YC12‐based OSCs achieve a champion PCE of 19.23 %, which is one of the highest efficiencies among these annealing‐free devices. Our developed unidirectional sidechain engineering for constructing bi‐asymmetric Y‐series acceptors provides an approach to boost PCE of OSCs.

Chemistry↗
DOE OSTI2022

Hybrid Entanglement Distribution between Remote Microwave Quantum Computers Empowered by Machine Learning

Superconducting microwave circuits with Josephson junctions, the major platform for quantum computing, can only reach the full capability when connected. This requires an efficient protocol to distribute microwave entanglement. While quantum computers typically use discrete-variable (DV) methods for information encoding, the entire continuous-variable (CV) degree of freedom in electromagnetic fields must be utilized to achieve the highest entanglement distribution rate. Here, we propose a hybrid protocol to resolve the incompatibility between DV microwave quantum computers and CV quantum communications. CV microwave entanglement is distributed using optical swapping of optical-microwave entanglement pairs. To interface with DV microwave quantum computers, we further design a hybrid circuit to simultaneously convert and distill high-quality DV entanglement from noisy CV entanglement. The hybrid circuit is trained with machine-learning algorithms, ensuring high entanglement fidelity and generation rate. In conclusion, our work not only provides a practical method to realize efficient quantum links for superconducting microwave quantum computers, but also opens avenues to bridge the gap between DV and CV quantum systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

A hybrid robust-stochastic optimization approach for day-ahead scheduling of cascaded hydroelectric system in restructured electricity market

Uncertainties arising from complicated natural and market environments pose great challenges for the efficient operation of cascaded hydroelectric systems. To overcome these challenges, this paper studies the day-ahead scheduling of cascaded hydroelectric systems in a restructured electricity market with the presence of uncertainties in electricity price and natural water inflow. To properly model the uncertainty, we consider the unique characteristics of these two types of uncertainties and capture them via the uncertainty set and stochastic scenarios, respectively. Further, a hybrid robust-stochastic optimization model is developed to simultaneously hedge against these two types of uncertainties, which is formulated as a large-scale non-convex optimization problem with mixed integer recourse. After introducing linearization of nonlinear terms, a tailored hybrid decomposition scheme combining Lagrangian relaxation and Dantzig-Wolfe decomposition is adopted to achieve efficient computation of the proposed model. Two real-world cases are conducted to demonstrate the capability and characteristics of the proposed model and algorithms.

13 HYDRO ENERGY↗
DOE OSTI2021

Comparison of 1D and 2D particle-in-cell simulations for DC magnetron sputtering discharges

One-dimensional and two-dimensional particle-in-cell (PIC)/Monte Carlo collision simulations are performed for a balanced direct current magnetron sputtering (DCMS) discharge. The plasma parameters obtained by both simulations above the target racetrack share similar features and magnitudes under similar discharge intensities, i.e., similar local discharge current densities. The commonly observed high-energy tail of electron energy distribution in DCMS discharges is reproduced in both simulations. Additionally, the accuracy and applicability of using onedimensional simulations to qualitatively investigate the characteristics of balanced DCMS discharge are confirmed. In terms of capturing the key physical mechanisms in DCMS, one-dimensional PIC simulation is an efficient method, which could largely alleviate the computational expense and preserve the physical fidelity of modeling results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Robust Optimization for the Day-Ahead Scheduling of Cascaded Hydroelectric Systems

Uncertain electricity prices resulting from the re-structuring of electricity market have brought new opportu-nities and challenges for hydroelectric producers. This paper presents a data-driven robust optimization approach for the day-ahead scheduling of cascaded hydroelectric systems (CHS) with electricity price uncertainty. In this paper, a minimum volume enclosing ellipsoid (MVEE) is adopted to construct an ellipsoidal uncertainty set that fully identifies and exploits the historical characteristics data. Here, a second-order conic optimization formulation of the robust counterpart is derived for efficient computation. A real-world case study is conducted to demonstrate the capability of the proposed optimization approach compared with the traditional robust optimization approach.

13 HYDRO ENERGY↗
DOE OSTI2020

Terrestrial radiative cooling: Using the cold universe as a renewable and sustainable energy source

Photonic materials designed at wavelength scales have enabled a range of emerging energy technologies, from solid-state lighting to efficient photovoltaics that have transformed global energy landscapes. Daytime passive radiative cooling materials shed heat from the ground to the cold universe by taking advantage of the terrestrial thermal radiation that is as large as the renewable solar energy. Newly developed photonic materials permit subambient cooling under direct sunshine, and their applications are expanding rapidly enabled by scalable manufacturing. We review here the recent advancement of daytime subambient radiative cooling materials, which allow energy-efficient cooling and are paving the way toward technologies that harvest the coldness from the universe as a new renewable energy source.

Science & Technology - Other Topics↗
DOE OSTI2024

In Situ and Operando Observation of Zinc Moss Growth and Dissolution in Alkaline Electrolyte for Zinc–Air Batteries

As a promising battery technology, zinc–air batteries still face significant challenges, including the formation of a mossy structure on the zinc metal anode in alkaline electrolyte. Because a similar phenomenon also plagues lithium and sodium metal batteries, elucidating its mechanism has important implications for progress in energy storage. Herein, operando X-ray nanotomography was employed to visualize zinc moss growth and dissolution at the individual colony level. By tracking its microstructure evolution, zinc moss was found to display irreversible plating/stripping behavior. While zinc moss exhibits self-limiting growth and zinc deposition occurs mainly in its outer region, zinc dissolution is more uniformly distributed inside the moss colony upon stripping, leading to the formation of “dead” zinc and capacity loss. A direct correlation is established between the moss amount and zinc plating/stripping efficiency. Finally, results from this study offer new insights into mitigating the unstable zinc plating morphology and improving the cycle life of aqueous zinc–air batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Reinforcement learning for bluff body active flow control in experiments and simulations

Significance Reinforcement learning (RL) has been applied effectively in games and robotic manipulation. We demonstrate the effectiveness of RL in experimental fluid mechanics by applying it to reduce the drag of circular cylinders in turbulent flow, a canonical fluid–structure interaction problem. Although physics agnostic, RL managed to reduce the drag by 30 % or reach another specified optimum point very quickly. Following this discovery, we used high-fidelity simulations to probe the underlying physical mechanisms so that the discovered control techniques can be generalized to other similar flow problems. More broadly, RL-guided active control can lead to efficient exploration of additional flow-control strategies in experimental fluid mechanics, potentially paving the way for accelerating scientific discovery and different designs in flow-related engineering problems.

42 ENGINEERING↗
DOE OSTI2022

Optimizing the Internal Cell Structure of the Radon Monitor Based on Electrostatic Collection Method

Abstract As Rn-222 decays, an alpha particle is emitted and the residual polonium nucleus recoils in the opposite direction. At the end of the recoil path, 88% of the polonium atoms have a positive charge and 12% are neutral. The electric potential distribution in the 60 ml hemispherical internal cell of the radon monitor based on electrostatic collection is studied for reducing the combined probability of the positively charged Po-218 and the OH− produced by the ionization of water vapour in the air. The COMSOL software is used to simulate the electric potential distribution in the internal cell of the radon monitor based on the electrostatic collection method at 27°C, a pressure of 0.1 Mpa. For improving the collection efficiency of Po-218 ions, the average collection time along vertical and oblique lines is calculated when the upper surface of the internal cell is plastic, uncharged metal and charged metal, respectively. Assuming that the gas in the internal cell is uniformly distributed, the results show that if the upper surface of the hemispherical internal cell is plastic or uncharged metal, the electric potential formed in the internal cell is more uniform, and it is beneficial to reduce the total collection time of the positively charged Po-218 ions, thereby improving collection efficiency. The simulation results can be used as an effective reference for optimizing the design of the internal cell structure of the radon monitor based on electrostatic collection method.

Fan, Zhongkai (ORCID:0000000181247459)↗
DOE OSTI2026

ComStock Measure Documentation: Fan Static Pressure Reset for Multizone Variable Air Volume Systems

This report assesses the potential for nationwide adoption of a duct static pressure reset in MZ VAV systems in appropriate applications. Building on the 3-year End-Use Load Profiles project to calibrate and validate the U.S. Department of Energy’s ResStock™ and ComStock™ models, this work produces national datasets that enable cities, states, utilities, and other stakeholders to answer a broad range of questions regarding their commercial building stock. ComStock is a highly granular, bottom-up model that uses various data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual sub-hourly energy consumption of the commercial building stock across the United States. The “baseline” model intends to represent the U.S. commercial building stock as it existed in 2018. The methodology of the baseline model is discussed in the ComStock Reference Documentation. The goal of this work is to develop energy efficiency and demand flexibility measures that cover market-ready technologies and study their mass-adoption impact on the baseline building stock. “Measures” refers to various “what-if” scenarios that can be applied to buildings. The results for the baseline and measure scenario simulations are published in public datasets that provide insights into building stock characteristics, operational behaviors, utility bill impacts, and annual and sub-hourly energy usage by fuel type and end use. This report describes the modeling methodology for a single ComStock measure scenario—Fan Static Pressure Reset for Multizone Variable Air Volume (VAV) Systems—and briefly introduces key results. The full public dataset can be accessed on the ComStock data lake or via the Data Viewer at comstock.nrel.gov. The public dataset enables users to create custom aggregations of results for their use case (e.g., filter to a specific county or building type).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Facile and Scalable Synthesis of Metal- and Nitrogen-Doped Carbon Nanotubes for Efficient Electrochemical CO 2 Reduction

Metal- and nitrogen-doped carbon (M–N–C) is a promising material to catalyze electrochemical CO 2 reduction reaction (CO 2 RR). However, most M–N–C catalysts in the literature require complicated synthesis procedures and produce small quantities per batch, limiting the commercialization potential. In this work, we developed a simple and scalable synthesis method to convert metal-impurity-containing commercial carbon nanotubes (CNTs) and nitrogen-containing organic precursors into M–N–C via one-step moderate-temperature (650 °C) pyrolysis without any other treatment nor the need to add metal precursors. Batches of catalysts in varied mass up to 10 g (150 mL in volume) per batch were synthesized, and repeatable catalytic performances were demonstrated. To the best of our knowledge, the 10 g batch is one of the largest batches of CO2RR catalysts synthesized in the literature while requiring minimal synthesis steps. The catalyst possessed single-atomic iron–nitrogen (Fe–N) sites, enabling a high performance of >95% CO product selectivity at a high current density of 400 mA/cm 2 and high stability for 45 h at 100 mA/cm 2 in a flow cell testing. The catalyst outperformed a benchmark noble-metal nanoparticle catalyst and achieved longer stability than many other reported M–N–C catalysts in the literature. The scalable and cost-effective synthesis developed in this work paves a pathway toward practical CO 2 RR applications. The direct utilization of metal impurities from raw CNTs for efficient catalyst synthesis with minimal treatment is a green and sustainable engineering approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Tailoring Interfaces for Enhanced Methanol Production from Photoelectrochemical CO 2 Reduction

Efficient and stable photoelectrochemical reduction of CO 2 into highly reduced liquid fuels remains a formidable challenge, which requires an innovative semiconductor/catalyst interface to tackle. In this study, we introduce a strategy involving the fabrication of a silicon micropillar array structure coated with a superhydrophobic fluorinated carbon layer for the photoelectrochemical conversion of CO 2 into methanol. The pillars increase the electrode surface area, improve catalyst loading and adhesion without compromising light absorption, and help confine gaseous intermediates near the catalyst surface. The superhydrophobic coating passivates parasitic side reactions and further enhances local accumulation of reaction intermediates. Upon one-electron reduction of the molecular catalyst, the semiconductor–catalyst interface changes from adaptive to buried junctions, providing a sufficient thermodynamic driving force for CO 2 reduction. These structures together create a unique microenvironment for effective reduction of CO 2 to methanol, leading to a remarkable Faradaic efficiency reaching 20% together with a partial current density of 3.4 mA cm –2 , surpassing the previous record based on planar silicon photoelectrodes by a notable factor of 17. Furthermore, this work demonstrates a new pathway for enhancing photoelectrocatalytic CO 2 reduction through meticulous interface and microenvironment tailoring and sets a benchmark for both Faradaic efficiency and current density in solar liquid fuel production.

14 SOLAR ENERGY↗
DOE OSTI2021

Bidirectional interconversion of microwave and light with thin-film lithium niobate

Abstract Superconducting cavity electro-optics presents a promising route to coherently convert microwave and optical photons and distribute quantum entanglement between superconducting circuits over long-distance. Strong Pockels nonlinearity and high-performance optical cavity are the prerequisites for high conversion efficiency. Thin-film lithium niobate (TFLN) offers these desired characteristics. Despite significant recent progresses, only unidirectional conversion with efficiencies on the order of 10 −5 has been realized. In this article, we demonstrate the bidirectional electro-optic conversion in TFLN-superconductor hybrid system, with conversion efficiency improved by more than three orders of magnitude. Our air-clad device architecture boosts the sustainable intracavity pump power at cryogenic temperatures by suppressing the prominent photorefractive effect that limits cryogenic performance of TFLN, and reaches an efficiency of 1.02% (internal efficiency of 15.2%). This work firmly establishes the TFLN-superconductor hybrid EO system as a highly competitive transduction platform for future quantum network applications.

42 ENGINEERING↗
DOE OSTI2021

Simulation-aided characterization of a versatile water-based condensation particle counter for atmospheric airborne research

Capturing the vertical profiles and horizontal variations of atmospheric aerosols often requires accurate airborne measurements. With the advantage of avoiding health and safety concerns related to the use of butanol or other chemicals, water-based condensation particle counters have emerged to provide measurements under various environments. However, airborne deployments are relatively rare due to the lack of instrument characterization under reduced pressure at flight altitudes. This study investigates the performance of a commercial “versatile” water-based condensation particle counter (vWCPC, model 3789, TSI, Shoreview, MN, USA) under various ambient pressure conditions (500–920 hPa) with a wide range of particle total number concentrations (1500–70 000 cm -3 ). The effect of conditioner temperature on vWCPC 3789 performance at low pressure is examined through numerical simulation and laboratory experiments. We show that the default instrument temperature setting of 30 °C for the conditioner is not suitable for airborne measurement and that the optimal conditioner temperature for low-pressure operation is 27°. Under the optimal conditioner temperature (27°), the 7 nm cut-off size is also maintained. Additionally, we show that insufficient droplet growth becomes more significant under the low-pressure operation. The counting efficiency of the vWCPC 3789 can vary up to 20 % for particles of different chemical compositions (e.g., ammonium sulfate and sucrose particles). However, such variation is independent of pressure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Relationship between charge transfer state electroluminescence and the degradation of organic photovoltaics

The degradation of archetype organic photovoltaics comprising both vacuum and solution-deposited bulk heterojunction active regions is investigated and quantified using a theory based on detailed balance, which relates the open-circuit voltage to the efficiency of charge transfer state emission. To describe this relationship, we account for the difference between electroluminescent external quantum efficiency and the charge transfer emission efficiency. Here, an empirical factor, m, is introduced to distinguish between nonradiative defect sites both within, m = 1, and outside, m >1, of the photoactive heterojunction. The m-factor is used to determine the primary sources of degradation for archetype solution- and vacuum-processed material systems. We conclude that degradation occurs primarily within the donor–acceptor heterojunction for the vacuum-processed devices (where m = 1.020 ± 0.002) and outside of the photoactive heterojunction for the solution-processed devices studied, both with and without an anode buffer layer (where m = 2.93 ± 0.09 and m = 1.90 ± 0.01, respectively).

14 SOLAR ENERGY↗