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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

ExINP-ENA Ice-Nucleating Particle Concentrations - PINE

This data set comprises cumulative ambient ice-nucleating particle (INP) concentrations measured at the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) Eastern North Atlantic (ENA) observatory on Graciosa Island, Azores (39.0916° N, 28.0257° W). Our INP data were generated using a combination of online instruments, the Portable Ice Nucleation Experiment chamber (PINE), and an offline assay instrument, the West Texas Cryogenic Refrigerator Applied to Freezing Test system (WT-CRAFT), for aerosol particle samples collected on polycarbonate filters (with 0.2-micron diameter pores).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

From PeleC to PeleACC, to PeleC++

PeleC is an Exascale Computing Project application for simulating compressible combustion in complex geometries. It has been built on top of the popular AMReX library. In the beginning of the Exascale Computing Project, PeleC was focused on KNL. It uses a mixture of C++, C, and kernels written in Fortran to obtain performance by focusing on vectorization. Recently we have taken two approaches in deciding PeleC's future for obtaining performance on exascale GPU machines. In the first programming model, we decorated the Fortran kernels with OpenACC directives. This expedited our ability to run at large scales on Summit's GPUs, where we achieved a significant speedup over the CPUs on Summit. The second programming model involved rewriting the Fortran kernels in C++ and using AMReX's Kokkos-like lambda abstractions for running on the GPU. This resulted in similar speedups on Summit's GPUs over merely utilizing the CPUs. Both approaches involved AMReX's management of memory transfers between the device and host. In this work, we compare and contrast the benefits and pitfalls to both programming approaches regarding performance, performance portability, and productivity. We also discuss advantages we have found in taking the time to modernize our code and why have chosen a specific pathway to prepare our code for the future DOE exascale machines.

exascale computing↗
DOE OSTI2025

Lightweight, Flexible Electromagnetic Shielding Composite Films Reinforced with Recycled Carbon Fibers and Carbon Nanofillers

Lightweight, flexible polymer composites are widely adopted in modern electronic devices and systems for high-efficiency electromagnetic interference (EMI) shielding. Reinforcing polymer composites with conductive fillers offers a promising alternative to conventional metal-based shielding material thanks to their low density, tunable properties, and flexibility. Herein, lightweight, flexible ultra-high molecular weight polyethylene composite films reinforced with recycled carbon fibers (rCFs) and carbon-based nanofillers, including graphene nanoplatelets (GNPs) and carbon nanotubes, are reported for EMI shielding applications. The incorporation of these nanofillers significantly reduces the required content of rCFs and improves processability while maintaining comparable shielding effectiveness. The addition of these nanofillers with rCFs enhances the EMI shielding effectiveness by up to 15 dB. Incorporating 1 wt% GNPs can replace 5 wt% rCFs and achieve comparable EMI shielding performance, while 5 wt% of either nanofillers can substitute for 10 wt% rCFs. Numerical modeling of electromagnetic wave transmission reveals that increasing nanofiller concentrations enhances both reflection and absorption losses, with absorption consistently dominating across all levels. Furthermore, this study not only provides insight into the synergistic contributions of rCFs and carbon nanofillers to shielding effectiveness but also paves the way for the design of sustainable, lightweight EMI shielding composite films for applications in electric vehicles, medical equipment, and portable electronics.

carbon nanofiller↗
DOE OSTI2023

Incombustible Polymer Electrolyte Boosting Safety of Solid–State Lithium Batteries: A Review

Lithium-ion batteries with their portability, high energy density, and reusability are frequently used in today's world. Under extreme conditions, lithium-ion batteries leak, burn, and even explode. Therefore, improving the safety of lithium-ion batteries has become a focus of attention. Researchers believe using a solid electrolyte instead of a liquid one can solve the lithium battery safety issue. Due to the low price, good processability and high safety of the solid polymer electrolytes, increasing attention have been paid to them. However, polymer electrolytes can also decompose and burn under extreme conditions. Moreover, lithium dendrites are formed continuously due to the uneven charge distribution on the surface of the lithium metal anode. A short circuit caused by a lithium dendrite can cause the battery to thermal runaway. As a result, the safety of polymer solid-state batteries remains a challenge. In this review, the thermal runaway mechanism of the batteries is summarized, and the batteries abuse test standard is introduced. In addition, the recent works on the high-safety polymer electrolytes and the solution strategies of lithium anode problems in polymer batteries are reviewed. Finally, the development direction of safe polymer solid lithium batteries is prospected.

25 ENERGY STORAGE↗
DOE OSTI2020

Trace-Level, Multi-Gas Detection for Food Quality Assessment Based on Decorated Silicon Transistor Arrays

Multiplexed gas detection at room temperature is critical for practical applications, such as for tracking the complex chemical environments associated with food decomposition and spoilage. Here, an integrated array of multiple silicon-based, chemical-sensitive field effect transistors (CSFETs) is presented to realize selective, sensitive, and simultaneous measurement of gases typically associated with food spoilage. CSFETs decorated with sensing materials based on ruthenium, silver, and silicon oxide are used to obtain stable room-temperature responses to ammonia (NH 3 ), hydrogen sulfide (H 2 S), and humidity, respectively. For example, one multi-CSFET sensor signal changes from its baseline by 13.34 in response to 1 ppm of NH 3 , 724.45 under 1 ppm H 2 S, and 23.46 under 80% relative humidity, with sensitive detection down to 10 ppb of NH 3 and H 2 S. To demonstrate this sensor for practical applications, the CSFET sensor array is combined with a custom-printed circuit board into a compact, fully integrated, and portable system to conduct real-time monitoring of gases generated by decomposing food. By using existing silicon-based manufacturing methodologies, this room-temperature gas sensing array can be fabricated reproducibly and at low cost, making it an attractive platform for ambient gas measurement needed in food safety applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Broadband and Tunable Microwave Absorption Properties from Large Magnetic Loss in Ni–Zn Ferrite

Highly effective electromagnetic (EM) wave absorber materials with strong reflection loss (RL) and a wide absorption bandwidth (EBW) in gigahertz (GHz) frequencies are crucial for advanced wireless applications and portable electronics. Traditional microwave absorbers lack magnetic loss and struggle with impedance matching, while ferrites are stable, exhibit excellent magnetic and dielectric losses, and offer better impedance matching. However, achieving the desired EBW in ferrites remains a challenge, necessitating further composition design. In this study, impedance matching is successfully enhanced and EBW in Ni–Zn ferrite is broadened by successive doping with Mn and Co , without incorporation of any polymer filler. It is found that Ni 0.4 Co 0.1 Zn 0.5 Fe 1.9 Mn 0.1 O 4 material exhibits exceptional EM wave absorption, with a maximum RL of −48.7 dB. It also featured a significant EBW of 10.8 GHz, maintaining a 90% absorption rate (RL < −10 dB) for a thickness of 4.5 mm. These outstanding properties result from substantial magnetic losses and favorable impedance matching. These findings represent a significant step forward in the development of microwave absorber materials, addressing EM wave pollution concerns within GHz frequencies, including the frequency band used in popular 5G technology.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Airborne Acoustic Vortex End Effector‐Based Contactless, Multi‐Mode, Programmable Control of Object Surfing

Abstract Tweezers based on optical, electric, magnetic, and acoustic fields have shown great potential for contactless object manipulation. However, current tweezers designed for manipulating millimeter‐sized objects such as droplets, particles, and small animals exhibit limitations in translation resolution, range, and path complexity. Here, a novel acoustic vortex tweezers system is introduced, which leverages a unique airborne acoustic vortex end effector integrated with a three‐degree‐of‐freedom (DoF) linear motion stage, for enabling contactless, multi‐mode, programmable manipulation of millimeter‐sized objects. The acoustic vortex end effector utilizes a cascaded circular acoustic array, which is portable and battery‐powered, to generate an acoustic vortex with a ring‐shaped energy pattern. The vortex applies acoustic radiation forces to trap and spin an object at its center, simultaneously protecting this object by repelling other materials away with its high‐energy ring. Moreover, The vortex tweezers system facilitates contactless, multi‐mode, programmable object surfing, as demonstrated in experiments involving trapping, repelling, and spinning particles, translating particles along complex paths, guiding particles around barriers, translating and rotating droplets containing zebrafish larvae, and merging droplets. With these capabilities, It is anticipated that the tweezers system will become a valuable tool for the automated, contactless handling of droplets, particles, and bio‐samples in biomedical and biochemical research.

Li, Teng↗
DOE OSTI2020

Tracking the Influence of Thermal Expansion and Oxygen Vacancies on the Thermal Stability of Ni-Rich Layered Cathode Materials

The ever-growing demand for high-energy lithium-ion batteries in portable electronics and electric vehicles has triggered intensive research efforts over the past decade. An efficient strategy to boost the energy and power density of lithium-ion batteries is to increase the Ni content in the cathode materials. However, a higher Ni content in the cathode materials gives rise to safety issues. Herein, thermal expansion and oxygen vacancies are proposed as new critical factors that affect the thermal stability of charged Ni-rich cathode materials based on a systematic synchrotron-based X-ray study of Li 0.33 Ni 0.5+x Co 0.2 Mn 0.3-x O 2 (x = 0, 0.1, 0.2) cathode materials during a heating process. Charged cathode materials with higher Ni contents show larger thermal expansion, which accelerates transition metal migration to the Li layers. Oxygen vacancies are formed and accumulate mainly around Ni ions until the layered-to-spinel phase transition begins. The oxygen vacancies also facilitate transition metal migration to the Li layers. Thermal expansion and the presence of oxygen vacancies decrease the energy barrier for cation migration and facilitate the phase transitions in charged cathode materials during the heating process. These results provide valuable guidance for developing new cathode materials with improved safety characteristics.

25 ENERGY STORAGE↗
DOE OSTI2020

Efficient, Thermally Stable, and Mechanically Robust All-Polymer Solar Cells Consisting of the Same Benzodithiophene Unit-Based Polymer Acceptor and Donor with High Molecular Compatibility

All-polymer solar cells (all-PSCs) are a highly attractive class of photovoltaics for wearable and portable electronics due to their excellent morphological and mechanical stabilities. Recently, new types of polymer acceptors (P A s) consisting of non-fullerene small molecule acceptors (NFSMAs) with strong light absorption have been proposed to enhance the power conversion efficiency (PCE) of all-PSCs. However, polymerization of NFSMAs often reduces entropy of mixing in PSC blends and prevents the formation of intermixed blend domains required for efficient charge generation and morphological stability. One approach to increase compatibility in these systems is to design P A s that contain the same building blocks as their polymer donor (P D ) counterparts. Here, a series of NFSMA-based P A s [P(BDT2BOY5-X), (X = H, F, Cl)] are reported, by copolymerizing NFSMA (Y5-2BO) with benzodithiophene (BDT), a common donating unit in high-performance P D s such as PBDB-T. All-PSC blends composed of PBDB-T PD and P(BDT2BOY5-X) P A show enhanced molecular compatibility, resulting in excellent morphological and electronic properties. Specifically, PBDB-T:P(BDT2BOY5-Cl) all-PSC has a PCE of 11.12%, which is significantly higher than previous PBDB-T:Y5-2BO (7.02%) and PBDB-T:P(NDI2OD-T2) (6.00%) PSCs. Additionally, the increased compatibility of these all-PSCs greatly improves their thermal stability and mechanical robustness. For example, the crack onset strain (COS) and toughness of the PBDB-T:P(BDT2BOY5-Cl) blend are 15.9% and 3.24 MJ m -3 , respectively, in comparison to the PBDB-T:Y5-2BO blends at 2.21% and 0.32 MJ m -3 .

14 SOLAR ENERGY↗
DOE OSTI2023

High-Entropy Surface Complex Stabilized LiCoO 2 Cathode

In this study, elevating the charge voltage of LiCoO 2 increases the energy density of batteries, which is highly enticing in energy storage implementation ranging from portable electronics to e-vehicles. However, hybrid redox reactions at high voltages facilitate oxygen evolution, electrolyte decomposition and irreversible phase change, and accordingly lead to rapid battery capacity decay. Here significantly improved high-voltage cycling stability of Mg-Al-Eu co-doped LiCoO 2 is demonstrated. It is found that element co-doping induces a near-surface high-entropy zone, including an innately thin disordered rock-salt shell and a dopant segregation surface. The high-entropy complex can effectively suppress oxygen evolution and near-surface structure deconstruction. The phase change reversibility between O3 and H1-3 and thermal stability of the cathode are greatly enhanced as well. As a result, the co-doped LiCoO 2 exhibits a remarkable cycling performance, retaining 86.3% and 72.0% of initial capacity over 800 and 2000 cycles, respectively, with a high cut-off voltage of 4.6 V. The feasible co-doping approach broadens the perspective for the development of stable lithium-ion batteries with high operating voltages.

25 ENERGY STORAGE↗
DOE OSTI2025

Distinct Dynamics of Lithium Intercalation and Plating on Graphite Anode for Li‐Ion Batteries in eVTOL Applications

In the absence of viable high-energy-density battery alternatives, lithium-ion (Li-ion) batteries remain essential for enabling electric vertical take-off and landing (eVTOL) platforms in advanced air mobility. Unlike Li-ion batteries used in electric vehicles and portable electronics, eVTOL battery systems operate under distinct high-power demands, which necessitate an independent assessment of material degradation mechanisms. This study presents a case analysis of graphite anode evolution under high-power cycling conditions. The findings reveal lithium entrapment within graphite particles, potentially resulting from incomplete Li-ion de-intercalation during a high-rate discharge event that is characteristic of eVTOL take-off and landing. This phenomenon leads to a progressive reduction in graphite-specific capacity and, over time, promotes lithium metal plating on the anode. Notably, the Li-metal plating observed in this study differs from that associated with fast-charging conditions, as it is primarily governed by concentration polarization-induced overpotential in the latter case. In conclusion, these findings highlight the inherent challenges of utilizing graphite in high-power Li-ion battery applications and elucidate the unique degradation mechanisms that arise due to the sluggish reaction kinetics of Li-ion intercalation and de-intercalation within graphite.

Li plating↗
DOE OSTI2025

Estimating the State of Charge in Lithium Primary Batteries: Recent Advances and Critical Insights

Lithium primary batteries (LPBs) remain essential in critical applications such as military, aerospace, medical and emergency devices, and portable electronics. Their superior energy density over lithium-ion batteries offers a significant advantage for long-duration use. Therefore, accurate estimation of the state of charge (SoC) is essential for ensuring the reliable and safe operation of these batteries. While extensive research has been conducted on SoC estimation techniques for lithium-ion secondary batteries, LPBs present unique challenges that complicate accurate SoC estimation. Moreover, research on nondestructive testing techniques for SoC estimation in LPBs is significantly lacking. In this review article, it is aimed to provide a comprehensive overview of recent advancements in SoC estimation for LPBs and generates new insights and directions for future research. Herein, existing methods are discussed and their effectiveness and mechanisms are identified, and areas for further optimization are outlined. More theoretical/experimental efforts to advance SoC detection in LPBs is recommended due to challenges identified with existing techniques.

25 ENERGY STORAGE↗
DOE OSTI2022

Smart connected worker edge platform for smart manufacturing: Part 1—Architecture and platform design

Abstract The challenge of sustainably producing goods and services for healthy living on a healthy planet requires simultaneous consideration of economic, societal, and environmental dimensions in manufacturing. Enabling technology for data driven manufacturing paradigms like Smart Manufacturing (a.k.a. Industry 4.0) serve as the technological backbone from which sustainable approaches to manufacturing can be implemented. Unfortunately, these technologies are typically associated with broader and deeper factory automation that is often too expensive and complex for the small and medium sized manufacturers (SMMs) that comprise the majority of manufacturing business in the USA and for whom their most valuable asset are the people whose jobs automation while replace. This paper describes an edge intelligent platform to integrate internet‐of‐things technologies with computing hardware, software, computational workflows for machine learning, and data ingestion, enabling SMMs to transition into smart manufacturing paradigms by leveraging the intelligence of their people. The platform leverages consumer grade electronics and sensors (affordable and portable), customized software with open source software packages (accessible), and existing communication network infrastructures (scalable). The software systems are implemented via Kubernetes orchestration of Docker containerization to ensure scalability and programmability. The platform is adaptive via computational workflow engines that produce information from data by processing with low‐cost edge computing devices while efficiently accessing resources of cloud servers as needed. The proposed edge platform connects workers to technological resources that provide computational intelligence (i.e., silicon‐based sensing and computation for data collection and contextualization) to enable decision making at the edge of advanced manufacturing.

Kim, Yoon G.↗
DOE OSTI2022

Smart connected worker edge platform for smart manufacturing: Part 2—Implementation and on‐site deployment case study

Abstract In this paper, we describe specific deployments of the Smart Connected Worker (SCW) Edge Platform for Smart Manufacturing through implementation of four instructive real‐world use cases that illustrate the role of people in a Smart Manufacturing paradigm through which affordable, scalable, accessible, and portable (ASAP) information technology (IT) acquires and contextualizes data into information for transmission to operation technologies (OT). For case one, the platform captures the relationships between energy consumption and human workflows for improved energy productivity while workers interact with machines during semiconductor manufacturing. The platform utilizes human cognition to identify anomalous machine behavior for root cause analysis of system faults via neural network (NN) that recognize alarm postures of workers with cameras. For case two, a smart assembly line is demonstrated for state monitoring and fault detection. Machine learning (ML) models are used to recognize system states and identify fault scenarios with human intervention. For case three, the platform monitors human–machine interactions to classify manufacturing machine states for proper operations and energy productivity. Internal energy states of individual or collections of manufacturing equipment are determined via NN based algorithms that disaggregate signals associated with smart metering typically deployed at manufacturing facilities. These methods predict the real time energy profile of each machine from the total energy profile of a manufacturing site. For case four, a software defined sensor system built with scientific workflow engines is demonstrated for contextualizing data from laser surface refraction for characterization, and diagnostics in the processing of additively manufactured titanium alloy.

Donovan, Richard P.↗
DOE OSTI2026

Rapid RASER MRI

Conventional Magnetic Resonance Imaging (MRI) relies on high-power Radio-Frequency (RF) pulses to excite nuclear spins and in turn generate NMR signals. These pulses require large high-power RF-amplifiers and cause heat deposition in the tissue, which must be minimized for safety, presenting a growing problem when moving toward ever-higher field MRI. An alternative to RF-pulse excitation is self-excitation of nuclear spins using Radiofrequency Amplification by Stimulated Emission of Radiation (RASER), where the nuclear spins undergo spontaneous transition, without RF excitation, from an over-populated state to a ground state. Here, the feasibility of recording rapid proton RASER MRI images of pyrazine at low concentration (120 mM) with large matrix (128x128 pixels) in as little as 78 ms is demonstrated at 500 MHz (11.7 T). We also recorded a time-series of images using a single bolus hyperpolarized pyrazine highlighting the feasibility of dynamic tracking. Here, the demonstrated approach allows recording MRI scans without transmit-receive electronics of the MRI scanner, which is highly desirable for portable MRI as well as the emerging field of hyperpolarized MRI using, e.g., HP protons, 129 Xe gas or HP 13 C labeled biomolecules as molecular tracers and imaging agents.

MRI↗
DOE OSTI2024

Open‐Source Anaerobic Digestion Modeling Platform, Anaerobic Digestion Model No. 1 Fast (ADM1F)

An open‐source modeling platform, called Anaerobic Digestion Model No. 1 Fast (ADM1F), is introduced to achieve fast and numerically stable simulations of anaerobic digestion processes. ADM1F is compatible with an iPython interface to facilitate model configuration, simulation, data analysis, and visualization. Faster simulations and more stable results are accomplished by implementing an advanced open‐source library of numerical methods called Portable Extensive Toolkit for Scientific Computation (PETSc) to solve the ADM1 system of equations. Leveraging PETSc, ADM1F can consistently complete a steady‐state simulation under 0.2 s, over 99% faster than a benchmark ADM1 model implemented with MATLAB while achieving agreement of model outputs within 1% of those obtained with the benchmark model. For dynamic simulations, however, ADM1F has a computational speed advantage only when the influent characteristics update more frequently than every 4 h. The ability of ADM1F to be useful as a tool to study anaerobic digestion systems is demonstrated through two example implementations of ADM1F: (1) a two‐phase co‐digestion scenario evaluating the impact of the organic loading rate and the substrate composition on reactor performance and stability, and (2) a conventional digester scenario assessing the effectiveness of recovery strategies after disruptions that led to instability. These examples demonstrate how the high simulation speed and the convenience of the iPython interface allow ADM1F to complete complex analyses within minutes, much faster than computational strategies currently reported in the literature.

anaerobic co-digestion↗
DOE OSTI2023

Accelerating x-ray tracing for exascale systems using Kokkos

The upcoming exascale computing systems Frontier and Aurora will draw much of their computing power from GPU accelerators. The hardware for these systems will be provided by AMD and Intel, respectively, each supporting their own GPU programming model. The challenge for applications that harness one of these exascale systems will be to avoid lock-in and to preserve performance portability. We report here on our results of using Kokkos to accelerate a real-world application on NERSC's Perlmutter Phase 1 (using NVIDIA A100 accelerators) and Crusher, the testbed system for OLCF's Frontier (using AMD MI250X). By porting to Kokkos, we successfully ran the same X-ray tracing code on both systems and achieved speed-ups between 13 % and 66 % compared to the original CUDA code. Finally, these results are a highly encouraging demonstration of using Kokkos to accelerate production science code.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Evaluating integration and performance of containerized climate applications on a Hewlett Packard Enterprise Cray system

Containers have taken over large swaths of cloud computing as the most convenient way of packaging and deploying applications. The features that containers offer for packaging and deploying applications translate to high performance computing (HPC) as well. At The National Oceanic and Atmospheric Administration, containers provide an easy way to build and distribute complex HPC applications, allowing faster collaboration, portability, and experiment computer environment reproducibility amongst the scientific community. The challenge arises when applications rely on message passing interface (MPI). This necessitates investigation into how to properly run these applications with their own unique requirements and produce performance on par with native runs. We investigate the MPI performance for benchmarks and containerized climate models for various containers covering selection of compiler and MPI library combinations from the Cray provided programming environments on the Cray XC supercomputer GAEA. Performance from the benchmarks and the climate models shows that for the most part containerized applications perform on par with the natively built applications when the system optimized Cray MPICH libraries are bound into the container, and the hybrid model containers have poor performance in comparison. We also describe several challenges and our solutions in running these containers, particularly challenges with heterogeneous jobs for the containerized model runs.

Abraham, Subil↗