Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “superior rate performance”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Synthesis of Core@Shell Cu-Ni@Pt-Cu Nano-Octahedra and Their Improved MOR Activity

Fabrication of 3d metal-based core@shell nanocatalysts with engineered Pt-surfaces provides an effective approach for improving the catalytic performance. The challenges in such preparation include shape control of the 3d metallic cores and thickness control of the Pt-based shells. Herein, we report a colloidal seed-mediated method to prepare octahedral CuNi@Pt-Cu core@shell nanocrystals using CuNi octahedral cores as the template. By precisely controlling the synthesis conditions including the deposition rate and diffusion rate of the shell-formation through tuning the capping ligand, reaction temperature, and heating rate, uniform Pt-based shells can be achieved with a thickness of < 1 nm. Furthermore, the resultant carbon-supported CuNi@Pt-Cu core@shell nano-octahedra showed superior activity in electrochemical methanol oxidation reaction (MOR) compared with the commercial Pt/C catalysts and carbon-supported CuNi@Pt-Cu nano-polyhedron counterparts, demonstrating that both the lattice strain and shape effects arising from the as-prepared CuNi@Pt-Cu octahedral nanocatalysts play a crucial role in MOR performance.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A Propane Hydronic Heat Pump with Energy Storage

Propane is an environment-friendly refrigerant, having a 20-year GWP (global warming potential) of 0.072 and a 100-year GWP of 0.02, as compared to R-410A having a GWP > 2000. It has superior thermodynamic cycle performance and heat transfer characteristics. However, propane is classified as a A3 refrigerant, which is highly flammable, and not allowed to be used indoor if the system charge is higher than 150 grams. It is a challenge to use propane in residential applications requiring a rated capacity larger than 10 k Watts. A hydronic heat pump, i.e., containing propane in an outdoor unit and distributing the cooling and heating capacity through a hydronic coil to the indoor space addresses the flammability issue, while maintaining a high efficiency. We developed a hydronic heat pump with propane, it uses a two-stage compressor, a brazed plate indoor heat exchanger, and a microchannel outdoor heat exchanger. It achieves a rated cooling capacity larger than 10 k Watts, and a cooling SEER (cooling seasonal energy efficiency rating) > 16.0 (cooling seasonal COP > 4.7) and a heating HSPF (heating seasonal performance factor) > 9.5 (heating seasonal COP > 2.78), while requiring a system charge < 1200 grams. Additionally, the hydronic heat pump was evaluated in a laboratory water heating loop to heat a 50-gallon water tank in a full condensing mode. Experiments of heating the tank water from 58F(14.4°C) to 150F(65.6°C) were conducted under ambient temperatures from 17F(-8.3°C) to 75F(23.9°C), at the compressor high and low stages.

Shen, Bo↗
DOE OSTI2021

Stable bismuth-antimony alloy cathode with a conversion-dissolution/deposition mechanism for high-performance zinc batteries

Although a large number of intercalation cathode materials for aqueous Zn batteries have been reported, limited intercalation capacity precludes achieving a higher energy density. Here, for this work, we develop a high-performance aqueous Zn battery based on BiSb alloy (Bi 0.5 Sb 0.5 ) using a high-concentrated strong-basic polyelectrolyte. We demonstrate that a conversion-dissolution/deposition electrochemical mechanism (BiSb ↔ Bi + SbO 2 – ↔ Bi + SbO 3 – ↔ Bi 2 O 3 ) through in situ X-ray diffraction (XRD), Raman, and ex-situ X-ray photoelectron spectrometry (XPS) characterizations with the help of density functional theory calculations. The BiSb cathode delivers large capacity of 512 mAh g –1 at 0.3 Ag –1 and superior rate capability of 90 mAh g –1 even at 20 Ag –1 , and long-term cyclability with capacity retentions of 184 mAh g –1 after 600 cycles at 0.5 Ag –1 and 130 mAh g –1 after 1300 cycles at 1 Ag –1 . Remarkably, even at temperatures as low as –10 and –20 °C, capacities of 210 and 197 mAh g –1 are reserved at 1 Ag –1 , respectively. Moreover, the prepared pouch Zn//BiSb battery delivers a high energy density of 303 Wh kg –1 BiSb at 0.3 Ag –1 . When coupled with a high concentration polyelectrolyte, the Zn/BiSb battery exhibits an excellent performance over a wide temperature range (–40 to 40 °C). Our research reveals the metal cathode is promising for Zn batteries to achieve a high performance with the unique mechanism and alloys can be an effective approach to stabilize metal electrodes for cycling.

25 ENERGY STORAGE↗
DOE OSTI2022

Stable all-solid-state sodium-sulfur batteries for low-temperature operation enabled by sodium alloy anode and confined sulfur cathode

All-solid-state sodium-sulfur (Na-S) batteries are promising for stationary energy storage devices because of their low operating temperatures (less than 100 °C), improved safety, and low-cost fabrication. Using Na alloy instead of Na metal as an anode in Na-S batteries can prevent dendrite growth and improve interfacial stability between the anode and solid electrolytes to achieve long-cycling stability. A high-sulfur content cathode possessing high sulfur utilization is also important to enable an energy-dense Na-S battery. In this work, we studied Na-Sb and Na- Sn alloy anodes and demonstrated the superiority of Na 3 Sb alloy undergoing a stable Na alloying/dealloying process at 0.04 mA cm -2 for over 500 hours. Combining the optimized Na3Sb alloy anode with sulfur-carbon composites prepared by the vapor deposition approach, the full cell shows a high sulfur specific capacity and improved rate performance. Moreover, the all-solid-state Na alloy-S battery can deliver a high initial discharge specific capacity of 1377 mAh g -1 and maintain good capacity retention of 70 % after 180 cycles at 60 °C. Further, post-cycle characterizations show that both the anode and cathode perform a reversible discharge/charge process after the 1st cycle, and the cathode undergoes significantly rearranged distributions of carbon and solid-state electrolytes after 180 cycles due to severe volume change induced by repeated sodiation/desodiation process.

25 ENERGY STORAGE↗
DOE OSTI2022

A Fast‐Charging and High‐Temperature All‐Organic Rechargeable Potassium Battery

Abstract Developing fast‐charging, high‐temperature, and sustainable batteries is critical for the large‐scale deployment of energy storage devices in electric vehicles, grid‐scale electrical energy storage, and high temperature regions. Here, a transition metal‐free all‐organic rechargeable potassium battery (RPB) based on abundant and sustainable organic electrode materials (OEMs) and potassium resources for fast‐charging and high‐temperature applications is demonstrated. N‐doped graphene and a 2.8 m potassium hexafluorophosphate (KPF 6 ) in diethylene glycol dimethyl ether (DEGDME) electrolyte are employed to mitigate the dissolution of OEMs, enhance the electrode conductivity, accommodate large volume change, and form stable solid electrolyte interphase in the all‐organic RPB. At room temperature, the RPB delivers a high specific capacity of 188.1 mAh g −1 at 50 mA g −1 and superior cycle life of 6000 and 50000 cycles at 1 and 5 A g −1 , respectively, demonstrating an ultra‐stable and fast‐charging all‐organic battery. The impressive performance at room temperature is extended to high temperatures, where the high‐mass‐loading (6.5 mg cm −2 ) all‐organic RPB exhibits high‐rate capability up to 2 A g −1 and a long lifetime of 500 cycles at 70–100 °C, demonstrating a superb fast‐charging and high‐temperature battery. The cell configuration demonstrated in this work shows great promise for practical applications of sustainable batteries at extreme conditions.

25 ENERGY STORAGE↗
DOE OSTI2025

Flux Synthesis of Lattice‐Engineered Rutile Solid Solutions for Acidic Oxygen Evolution

Developing efficient and stable electrocatalysts for the acidic oxygen evolution reaction (OER) is vital for advancing proton exchange membrane water electrolysis (PEMWE) technologies. Here, in this study, we report a flux synthesis of nitrogen-doped Ti–Ru rutile-type solid-solution oxides (M-TiRu 4 ) using molten NaNO 3 as the flux medium. The flux medium promotes the low-temperature conversion of TiN to rutile TiO 2 , while in situ-formed RuO 2 nanoparticles facilitate lattice templating and couple with interfacial ion migration, enabling the formation of homogeneous solid solutions with abundant lattice heterogeneity. Simultaneously, nitrogen atoms are stably incorporated into the lattice of solid solutions, inducing bandgap narrowing, which enhances electronic conductivity. The developed M-TiRu 4 catalyst exhibits exceptional acidic OER performance, delivering a low overpotential of 194 mV at 10 mA cm −2 , superior durability over 600 h, and a Ru mass activity 7.8 times that of commercial RuO 2 . At the device level, M-TiRu 4 enables PEMWE operation at 1.64 V @ 2 A cm −2 and maintains stable performance at 500 mA cm −2 for 200 h with a minimal degradation rate of 20 µV h −1 . This work demonstrates a robust approach for designing high-performance, durable acidic OER catalysts via synergistic lattice and electronic structure engineering, paving the way for next-generation water-splitting technologies.

Wang, Fan [Univ. of Tennessee, Knoxville, TN (Unit↗
DOE OSTI2020

Design complexity and performance analysis in additively manufactured heat exchangers

The main objective of this research is to investigate the tradeoffs between design complexity and thermal performance in additively manufactured metallic heat exchangers. Such heat exchangers have become a favorite topic for investigation in various fields ranging from air conditioning to aircraft gas turbine engines. In particular, high manufacturing cost has emerged as the major drawback in broad applications of manifold-microchannel heat exchanger (MMHXs). The possibility of cost-effective manufacturing has generated wide interest in applying additive manufacturing (AM) for fabricating MMHXs. Furthermore, AM technologies will provide an opportunity for enhanced design and superior heat transfer performance. In this study, innovative MMHXs are designed and fabricated through selective laser melting. An experimental setup was designed to measure pressure drop and heat transfer for the developed MMHXs with a wide range of Reynolds numbers. Furthermore, the coefficient of performance was calculated based on the heat flow rate, air pressure drop, and air flow rate. Measurement results demonstrated that in some scenarios adding more internal features, i.e., increasing design complexity, does not necessarily improve the MMHX performance.

10 SYNTHETIC FUELS↗
DOE OSTI2022

Bayesian Framework for Multi-Timescale State Estimation in Low-Observable Distribution Systems

To support the smart grid paradigm, there has been a significant increase in sensor deployments and metering infrastructure in distribution systems. However, the measurements provided by these sensors and metering devices are typically sampled at different rates and could suffer from losses during the aggregation process. It is crucial to effectively reconcile the time-series measurements for a reliable state estimation. While weighted least squares has been the traditional approach for state estimation, sparsity-based approaches like matrix completion have become popular due to their superior performance in low-observability conditions. This paper proposes a Bayesian framework for both multi-timescale data aggregation and matrix completion based state estimation. Specifically, the multiscale time-series data aggregated from heterogenous sources are reconciled using a multitask Gaussian process that exploits the spatio-temporal correlations. Here, the resulting consistent timeseries alongwith the confidence bound on the imputations are fed into a Bayesian matrix completion method augmented with linearized power-flow constraints to accurately estimate the states in low-observability conditions. Results on three phase unbalanced IEEE 37 and IEEE 123 bus test systems reveal the superior performance of the proposed Bayesian framework. The computational complexity for the proposed Bayesian framework is also quantified.

42 ENGINEERING↗
DOE OSTI2023

A Novel High‐Performance Electrolyte for Extreme Fast Charging in Pilot Scale Lithium‐Ion Pouch Cells

Realizing extreme fast charging (XFC) in lithium-ion batteries for electric vehicles is still challenging due to the insufficient lithium-ion transport kinetics, especially in the electrolyte. Herein, a novel high-performance electrolyte (HPE) consisting of lithium bis(fluorosulfonyl)imide (LiFSI), lithium hexafluorophosphate (LiPF 6 ) and carbonates is proposed and tested in pilot-scale, 2-Ah pouch cells. Moreover, the origin of improved electrochemical performance is comprehensively studied via various characterizations, suggesting that the proposed HPE exhibits high ionic conductivity and excellent electrochemical stability at high charging rate of 6-C. Furthermore, the HPE-based pouch cells deliver improved discharge specific capacity and excellent long-term cyclability up to 1500 cycles under XFC conditions, which is superior to the conventional state-of-the-art baseline electrolyte.

25 ENERGY STORAGE↗
DOE OSTI2021

Measurement of hybrid rocket solid fuel regression rate for a slab burner using deep learning

This study presents an imaging-based deep learning tool to measure the fuel regression rate in a 2D slab burner experiment for hybrid rocket fuels. The slab burner experiment is designed to verify mechanistic models of reacting boundary layer combustion in hybrid rockets by the measurement of fuel regression rates. A DSLR camera with a high intensity flash is used to capture images throughout the burn and the images are then used to find the fuel boundary to calculate the regression rate. A U-net convolutional neural network architecture is explored to segment the fuel from the experimental images. Here, a Monte-Carlo Dropout process is used to quantify the regression rate uncertainty produced from the network. The U-net computed regression rates are compared with values from other techniques from literature and show error less than 10%. An oxidizer flux dependency study is performed and shows the U-net predictions of regression rates are accurate and independent of the oxidizer flux, when the images in the training set are not over-saturated. Training with monochrome images is explored and is not successful at predicting the fuel regression rate from images with high noise. The network is superior at filtering out noise introduced by soot, pitting, and wax deposition on the chamber glass as well as the flame when compared to traditional image processing techniques, such as threshold binary conversion and spatial filtering. U-net consistently provides low error image segmentations to allow accurate computation of the regression rate of the fuel.

42 ENGINEERING↗
DOE OSTI2021

Accelerating Binarized Neural Networks via Bit-Tensor-Cores in Turing GPUs

Despite foreseeing tremendous speedups over conventional deep neural networks, the performance advantage of binarized neural networks (BNNs) has merely been showcased on general-purpose processors such as CPUs and GPUs. In fact, due to being unable to leverage bit-level-parallelism with a word-based architecture, GPUs have been criticized for extremely low utilization (1%) when executing BNNs. Consequently, the latest tensorcores in NVIDIA Turing GPUs start to experimentally support bit computation. In this work, we look into this brand new bit computation capability and characterize its unique features. We show that the stride of memory access can significantly affect performance delivery and a data-format co-design is highly desired to support the tensorcores for achieving superior performance than existing software solutions without tensorcores. We realize the tensorcore-accelerated BNN design, particularly the major functions for fully-connect and convolution layers — bit matrix multiplication and bit convolution. Evaluations on two NVIDIA Turing GPUs show that, with ResNet-18, our BTC-BNN design can process ImageNet at a rate of 5.6K images per second, 77% faster than state-of-the-art. Our BNN approach is released on https://github.com/pnnl/TCBNN.

Li, Ang↗
DOE OSTI2026

Unraveling the Synergistic effects of La and Al co-doping on Ni/Co-free P2-type Na 0.67 Mn 0.67 Fe 0.33 O 2 layered oxide cathodes for sodium-ion batteries

Recent developments in high-performance cathodes for sodium-ion batteries (SIBs) tend to mitigate use of critical Ni and Co active species to satisfy sustainability. P2-type layered oxide cathodes based on Mn and Fe promise high capacity, sustainability, and low cost on account of the abundance and multiple redox characteristics of Mn and Fe. However, their commercialization is still challenged due to poor cycling stability caused by phase changes emanating from inherent Jahn-Teller distortions. Herein, we propose a novel strategy of trivalent La and Al co-doping to alleviate the drawbacks, innovating a new cathode of Na 0.67 Mn 0.62 Al 0.05 Fe 0.31 La 0.02 O 2 (AlLa). The co-doped cathode delivers an impressive capacity of 128.7 mAh/g at 1C and 106.5 mAh/g at high rate of 5C with a good capacity retention of 85% after 100 cycles. These are superior to the unmodified material, whose specific capacity was 118.6 mAh/g at 1C and 61.1 mAh/g at 5C with a retention of only 65% after 100 cycles. The synergistic contribution from La and Al associated with their improved oxygen bonding, pillaring, and local electronic structural modification stemming from rigid Lasingle bondO and Alsingle bondO bonding resulted in the observed structural and electrochemical improvement. Overall, this research offers novel strategies for designing high-performance cathode materials for sodium-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2024

Characterization of build parameters and microstructure in low heat input WAAM of Ni-based superalloy Haynes 282

Conference paper for 2024 10th International Conference on Advances in Materials, Manufacturing &amp; Repair for Power Plants. Ni-based superalloy Haynes 282 is a prime candidate for advanced power generation systems due to its superior fabricability, weldability, and high-temperature performance. Additive manufacturing offers potential cost and time savings for gas turbine components. Wire-arc direct energy deposition can create large components but often requires post-processing treatments, such as hot isostatic pressing (HIP), to address porosity. This study explores a low heat-input, high deposition rate GMAW process to achieve fully dense Haynes 282 without HIP. Twenty-one blocks were deposited, varying travel and wire feed speeds. Initial analysis (visual inspection, microstructural examination, and CT) revealed the impact of build parameters on internal porosity and defects. Scanning electron microscopy provided insights into structural heterogeneity and microstructural properties. Related journal article can be found at https://doi.org/10.31399/asm.cp.am-epri-2024p0001.

Adam, Benjamin↗
DOE OSTI2024

Enable superior performance of ultra-high loading electrodes through the cost-efficient solvent-free electrode manufacturing technology

This research explores an innovative solvent-free method for fabricating ultra-high loading NMC811 and graphite electrodes (~6mAh∙cm -2 ), showcasing remarkable electrochemical performance enhancements compared to the electrodes prepared by the conventional slurry-casting method. Here, the optimized microstructure with dry-printed (DP) electrodes enhanced electrolyte penetration and minimized lithium-ion diffusion tortuosity resulting in improved rate performance at high current rates. Additionally, this innovative electrode manufacturing approach enables more uniform CEI and SEI formation and growth, which effectively doubles the cycle life of single-layer pouch cells with DP electrodes. Beyond the performance enhancements, this method also offers a notable 29.2 % overall cost advantages, potentially revolutionizing future battery manufacturing. The findings presented in this work underscore the potential of solvent-free manufacturing technology as a high-loading capable and cost-efficient path for advanced battery production.

25 ENERGY STORAGE↗
DOE OSTI2020

Roll-To-Roll Atomic Layer Deposition of Titania Nanocoating on Thermally Stabilizing Lithium Nickel Cobalt Manganese Oxide Cathodes for Lithium Ion Batteries

Conformal coating of ceramic layers (nm-thick) on Ni-rich layered cathode materials is an effective strategy for improving high-temperature longevity of Li-ion batteries (LIBs). In this work, we develop a roll-to-roll atomic layer deposition (R2R ALD) apparatus for growing uniform nanolayers of TiO 2 . We explore the effect of ALD parameters (temperature: 120–180 °C and line speed: 2–40 mm s –1 ) on the TiO 2 surface coating and subsequently investigate the electrochemical performance of the as-prepared cathodes. The capacity retention of TiO 2 -coated porous electrodes is substantially improved compared to that of the pristine cathode material for high-temperature cycling. Electrochemical impedance spectroscopy confirms that the ALD-TiO 2 coating suppresses the undesired side reactions initiated at the electrode/electrolyte interface, reduces charge transfer resistance, and ultimately facilitates the Li + transport through the composite cathode nanostructure. The robust design of the ALD-TiO 2 cathode material enables high-temperature operation (>55 °C) with enhanced specific capacity, superior rate capability, excellent cyclability, and ultra-high coulombic efficiency within a wide potential window (3.0–4.35 V). Furthermore, the R2R ALD technique developed in this work paves the way for large-scale fabrication of ceramic-coated cathode sheets with a production rate reaching 2.4 m min –1 for a continuous coating operation.

25 ENERGY STORAGE↗
DOE OSTI2023

Analysis and Compensation of Tx and Rx IQ Imbalances in Uplink IM-OFDMA Systems

Index modulation-based orthogonal division multiple access (IM-OFDMA) has recently been proposed as a potential technique for future wireless communication systems due to its superior spectral efficiency and error performance over conventional multiple access schemes. However, its performance is still under investigation by researchers in light of a variety of scenarios and assumptions. Following this direction, in this Article, the individual and joint effects of the transmitter (Tx) and receiver (Rx) in-phase and quadrature imbalances (IQI) on the bit-error-rate (BER) performance of the uplink IM-OFDMA scheme are investigated by considering whether each user's RF front-end is identical or not. Moreover, to reduce the detrimental effect of IQI, a preamble-based estimation and compensation method is proposed for IM-OFDMA. Closed-form expressions for the average BER of IM-OFDMA are obtained by considering the physical effect of the Tx and Rx IQI. Also, using Monte Carlo simulations, the derived expressions are verified under different system configurations. Furthermore, analytical and simulation results reveal that Tx and Rx IQI cause an error floor in the BER performance of IM-OFDMA schemes. However, the proposed estimation and compensation method not only reduces the impact of IQI but also leads to a better BER performance compared to the case of no IQI, which mainly refers to the frequency diversity caused by the IQI.

42 ENGINEERING↗
DOE OSTI2021

A New Class of AMG Interpolation Methods Based on Matrix-Matrix Multiplications

A new class of distance-two interpolation methods for algebraic multigrid (AMG) that can be formulated in terms of sparse matrix-matrix multiplications is presented and analyzed. Compared with similar distance-two prolongation operators, the proposed algorithms exhibit improved efficiency and portability to various computing platforms, since they allow one to easily exploit existing high-performance sparse matrix kernels. The new interpolation methods have been implemented in hypre, a widely used parallel multigrid solver library. With the proposed interpolations, the overall time of hypre's BoomerAMG setup can be considerably reduced, while sustaining equivalent, sometimes improved, convergence rates. Numerical results for a variety of test problems on parallel machines are presented that support the superiority of the proposed interpolation operators over the existing ones in hypre.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Leveraging large language models to automate the identification of healthcare access barriers for veterans

Objective: To develop and evaluate an automated system for identifying healthcare barriers focusing on transportation issues in veterans’ clinical notes using large language models (LLMs) and to assess the impact of different prompting strategies on classification performance and explanation consistency. Methods: We developed a hybrid system combining pattern matching for templated notes with LLM analysis for free-text notes. Using 2000 manually annotated clinical notes, we compared four prompting strategies (dual-role short, dual-role long, analysis-first, analysis-only) across Mistral-7B and Llama-3.1 models. We evaluated classification performance using standard metrics and assessed explanation consistency through embedding similarity analysis. Results: The analysis-first strategy achieved superior performance, with Mistral-7B reaching an F1 score of 0.914, outperforming traditional machine learning approaches (GBM: 0.786, BERT: 0.811). LLMs demonstrated higher explanation consistency within models (mean cosine similarity 0.887–0.908) compared to cross-model similarities (0.767–0.872). Pattern matching successfully handled 6.7% of templated notes deterministically. Mistral-7B showed greater internal consistency but higher abstention rates compared to Llama-3.1. Conclusion: Requiring LLMs to analyze evidence before classification improves both accuracy and explanation consistency for identifying transportation barriers in clinical notes. This approach enables automated barrier detection at scale while providing clinically relevant explanations, supporting both population-level healthcare planning and individual patient care decisions.

Healthcare access barriers↗