Evaluation of Aerodynamic Tools for Predicting UAM Vehicle Acoustics: Best Practices to Date
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UAM↗
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Results for “Practices”
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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NASA Spacecraft Conjunction Assessment and Collision Avoidance Best Practices Handbook
This is the first revision by the Office of the Chief Engineer of the 2020 Handbook updated to reflect the release of NPR 8079.1, NASA Spacecraft Conjunction Analysis and Collision Avoidance for Space Environment Protection.
Conjunction Assessment↗
Satellite Conjunction Assessment: NASA Best Practices and Lessons Learned
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Conjunction Assessment↗
Conjunction Assessment NASA Best Practices
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Collision Avoidance↗
Conjunction Assessment NASA Best Practices
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Collision Avoidance↗
NASA Engineering and Safety Center Technical Bulletin No. 23-07: Best Practices for Fabrication of Microelectronic Devices
Material degradation during the fabrication of microelectronic devices has plagued the space industry for many years owing to the layering of many dissimilar metals to create these devices. Often, commonly used materials and systems are overlooked as potential sources of material degradation. This technical bulletin highlights extensive research to isolate probable causes of this degradation.
Best Practices↗
Department of Energy/IDEA: More best-practices research
This article continues the overview of the U.S. Department of Energy and IDEA collaboration by highlighting additional case studies that demonstrate innovative engineering approaches in district energy systems. It focuses on how campuses are improving efficiency, integrating advanced technologies, and reducing energy use and emissions through data-driven strategies. The University of Cincinnati is featured for its highly efficient chilled water system, using advanced algorithms and upgraded “smart chillers” to optimize performance, reduce energy consumption, and lower costs. Wake Forest University emphasizes a data-informed modernization process, using system optimization and targeted building improvements to significantly boost efficiency and reduce overall energy use. Arizona Western College showcases creative solutions to extreme cooling demands, including system redesign, smart controls, and thermal storage to improve reliability and cut peak energy costs. Overall, the article demonstrates that combining innovative engineering, real-time data analysis, and system optimization can significantly enhance performance, reduce emissions, and deliver cost savings in district energy systems.
96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
Practically Accessible All-Solid-State Batteries Enabled by Organosulfide Cathodes and Sulfide Electrolytes
The combination of organic electrode materials and sulfide electrolytes is expected to enable the development of all-solid-state organic batteries featuring high energy density and long-term sustainability. In this work, thiuram hexasulfide is reported as a low-cost and high-capacity organic cathode for solid-state batteries based on sulfide electrolytes, delivering a capacity of ~600 mAh g -1 and retaining 80.8 % capacity after 500 cycles. An electrochemically reversible change of the cathode interface was revealed upon cycling. Full cell displays an oscillating stress change up to 0.6 MPa during cycling, predominated by the anode side. The energy density is 1140 Wh kg -1 at the material level and 376 Wh kg -1 at the electrode level, which are among the best-reported organic cathodes to date. A high areal capacity of 10.4 mAh cm -2 is reached with a high mass loading cathode. A dry-film approach is further explored to manufacture sheet-type cells. Free-standing electrolyte film is merely ~48 μm thick and demonstrates an ultralow areal resistance of 3.9 Ω cm 2 , significantly boosts the cell-level energy density and reduces the cell internal resistance.
25 ENERGY STORAGE↗
Electrolytes with Solvating Inner Sheath Engineering for Practical Na–S Batteries
Sodium–sulfur (Na–S) batteries with durable Na-metal stability, shuttle-free cyclability, and long lifespan are promising to large-scale energy storages. However, meeting these stringent requirements poses huge challenges with the existing electrolytes. Herein, a localized saturated electrolyte (LSE) is proposed with 2-methyltetrahydrofuran (MeTHF) as an inner sheath solvent, which represents a new category of electrolyte for Na–S system. Unlike the traditional high concentration electrolytes, the LSE is realized with a low salt-to-solvent ratio and low diluent-to-solvent ratio, which pushes the limit of localized high concentration electrolyte (LHCE). The appropriate molecular structure and solvation ability of MeTHF regulate a saturated inner sheath, which features a reinforced coordination of Na + to anions, enlarged Na + -solvent distance, and weakened anion-diluent interaction. Such electrolyte configuration is found to be the key to build a sustainable interphase and a quasi-solid–solid sulfur redox process, making a dendrite-inhibited and shuttle-free Na–S battery possible. With this electrolyte, pouch cells with decent cycling performance under rather demanding conditions are demonstrated.
25 ENERGY STORAGE↗
Unlocking Failure Mechanisms and Improvement of Practical Li–S Pouch Cells through In Operando Pressure Study
For Lithium-sulfur (Li-S) battery commercialization, the study at a pouch cell level is essential, as some problems ignored or deemed minimal at the smaller level could have a greater effect on the performance of the larger pouch cell. Herein, the failure mechanisms of Li-S pouch cells are deeply investigated via in operando pressure analysis. It is found that highly porous structures of cathodes/separators and slow electrolyte diffusion through cathodes/separators can both lead to poor initial wetting. Additionally, Li-metal anode dominates the thickness variation of the whole pouch cell, which is verified by in situ measured pressure variation. Consequently, a real-time approach that combined normalized pressure with dP/dV analysis is proposed and validated to diagnose the morphology evolution of Li-metal anode. Moreover, applied pressure and porosity/tortuosity ratio of the cathode are both identified as independent factors that influence anode performance. In addition to stabilizing anodes, high pressure is proven to improve the cathode connectivity and avoid cathode cracking over cycling, which improves the possibility of developing cathodes with high sulfur mass loading. Here, this work provides insights into Li-S pouch cell design (e.g., cathode and separator) and highlights pathways to improve cell capacity and cycling performance with applied and monitored pressure.
25 ENERGY STORAGE↗
A Solution-Processable High-Modulus Crystalline Artificial Solid Electrolyte Interphase for Practical Lithium Metal Batteries
The solid electrolyte interphase (SEI) has been identified as a key challenge for Li metal anodes. The brittle and inhomogeneous native SEI generated by parasitic reactions between Li and liquid electrolytes can devastate battery performance; therefore, artificial SEIs (ASEIs) have been proposed as an effective strategy to replace native SEIs. Herein, as a collaboration between academia and industrial R&D teams, a multifunctional (crystalline, high modulus, and robust, Li + ion conductive, electrolyte-blocking, and solution processable) ASEI material, LiAl-FBD (where “FBD” refers to 2,2,3,3-tetra-fluoro-1,4-butanediol), for improving Li metal battery performance is designed and synthesized. The LiAl-FBD crystal structure consists of Al 3+ ions bridged by FBD 2– ligands to form anion clusters while Li + ions are loosely bound at the periphery, enabling an Li + ion conductivity of 9.4 × 10 –6 S cm –1 . Further, the fluorinated, short ligands endow LiAl-FBD with electrolyte phobicity and high modulus. The ASEI is found to prevent side reactions and extend the cycle life of Li metal electrodes. Specifically, pairing LiAl-FBD coated 50 μm thick Li with industrial 3.5 mAh cm –2 NMC811 cathode and 2.8 μL mAh –1 lean elec-trolyte, the Li metal full cells show superior cycle life compared to bare ones, achieving 250 cycles at 1 mA cm –2 .
25 ENERGY STORAGE↗
Determining the Overpotential of Electrochemical Fuel Synthesis Mediated by Molecular Catalysts: Recommended Practices, Standard Reduction Potentials, and Challenges
Molecular catalysts capable of performing electrochemical transformations are frequently utilized in the synthesis of fuels. A common benchmark for evaluating catalysts for electrochemical reactions is overpotential (η) and minimizing η remains an active goal in catalysis. This Review details approaches for the determination of thermodynamic potentials for common fuel-forming reactions and for the determination of electrochemical overpotential, and underscores the need to employ methods that enable meaningful comparisons between molecular catalysts. Strategies for minimizing overpotential while maintaining high activity are highlighted.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Interpretable Machine Learning Models for Practical Antimonate Electrocatalyst Performance
Computationally predicting the performance of catalysts under reaction conditions is a challenging task due to the complexity of catalytic surfaces and their evolution in situ, different reaction paths, and the presence of solid-liquid interfaces in the case of electrochemistry. We demonstrate here how relatively simple machine learning models can be found that enable prediction of experimentally observed onset potentials. Inputs to our model are comprised of data from the oxygen reduction reaction on non-precious transition-metal antimony oxide nanoparticulate catalysts with a combination of experimental conditions and computationally affordable bulk atomic and electronic structural descriptors from density functional theory simulations. From human-interpretable genetic programming models, we identify key experimental descriptors and key supplemental bulk electronic and atomic structural descriptors that govern trends in onset potentials for these oxides and deduce how these descriptors should be tuned to increase onset potentials. Here, we finally validate these machine learning predictions by experimentally confirming that scandium as a dopant in nickel antimony oxide leads to a desired onset potential increase. Macroscopic experimental factors are found to be crucially important descriptors to be considered for models of catalytic performance, highlighting the important role machine learning can play here even in the presence of small datasets.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Morphophysiological Plant Phenotyping for the Development of Plant Breeding Under Drought and Heat Conditions: A Practical Approach
ABSTRACT Currently, the breeding programs focus their efforts on identifying and developing tolerant genotypes to adverse conditions, such as drought and high temperatures. In this context, the physiological approach, which involves phenotyping several traits, is useful for breeding programs. Leaf photosynthetic traits have become one of the main objectives to be evaluated for breeders due to their relationship with improving grain yield and biomass production. Gas exchange ( Ge ) and chlorophyll “a” fluorescence ( Chf ) are the main tools to characterize the photosynthetic activity in real time at the leaf level. Consequently, several association studies using proximal and nonproximal sensing (e.g., RGB, thermography) have been developed. However, for the correct application of this breeding approach, it is essential to have a basic knowledge of both the physiological principles involved in the readings and the limitations of phenotyping due to the characteristics of the devices available on the market. This revision also covers other traits, such as the morphological and anatomical characteristics of leaves and roots, and the use of isotopes complementing Ge and Chf measurements.
Estrada, Félix [Instituto de Investigaciones Agrop↗
Hacking Limnology Workshop and DSOS22: Creating a Community of Practice for the Nexus of Data Science, Open Science, and the Aquatic Sciences
The 2nd Aquatic Ecosystem Modeling-Junior (AEMON-J) Hacking Limnology Workshop and 3rd Virtual Summit: Incorporating Data Science and Open Science in the Aquatic Sciences (DSOS) took place on 25–29 July 2022. These virtual events were developed to bring together researchers from diverse backgrounds to share developments in data-intensive research in the aquatic sciences and train participants in cutting-edge data analysis methods related to remote sensing, data pipelines, and modeling of aquatic ecosystems.
54 ENVIRONMENTAL SCIENCES↗
Adaptive basis sets for practical quantum computing
Electronic structure calculations on small systems such as H 2 , H 2 O, LiH, and BeH 2 with chemical accuracy are still a challenge for the current generation of noisy intermediate-scale quantum (NISQ) devices. One of the reasons is that due to the device limitations, only minimal basis sets are commonly applied in quantum chemical calculations, which allows one to keep the number of qubits employed in the calculations at a minimum. However, the use of minimal basis sets leads to very large errors in the computed molecular energies as well as potential energy surface shapes. One way to increase the accuracy of electronic structure calculations is through the development of small basis sets better suited for quantum computing. In this work, we show that the use of adaptive basis sets, in which exponents and contraction coefficients depend on molecular structure, provides an easy way to dramatically improve the accuracy of quantum chemical calculations without the need to increase the basis set size and thus the number of qubits utilized in quantum circuits. As a proof of principle, we optimize an adaptive minimal basis set for quantum computing calculations on an H 2 molecule, in which exponents and contraction coefficients depend on the H—H distance, and apply it to the generation of H 2 potential energy surface on IBM-Q quantum devices. The adaptive minimal basis set reaches the accuracy of the double-zeta basis sets, thus allowing one to perform double-zeta quality calculations on quantum devices without the need to utilize twice as many qubits in simulations. This approach can be extended to other molecular systems and larger basis sets in a straightforward manner.
97 MATHEMATICS AND COMPUTING↗
A practical extension of the recursive multi-fidelity model for the emulation of hole closure experiments
We report in regimes of high strain rate, the strength of materials often cannot be measured directly in experiments. Instead, the strength is inferred based on an experimental observable, such as a change in shape, that is matched by simulations supported by a known strength model. In hole closure experiments, the rate and degree to which a central hole in a plate of material closes during a dynamic loading event are used to infer material strength parameters. Due to the complexity of the experiment, many computationally expensive, three-dimensional simulations are necessary to train an emulator for calibration or other analyses. These simulations can be run at multiple grid resolutions, where dense grids are slower but more accurate. In an effort to reduce the computational cost, a combination of simulations with different resolutions can be combined to develop an accurate emulator within a limited training time. We explore the novel design and construction of an appropriate functional recursive multi-fidelity emulator of a strength model for tantalum in hole closure experiments that can be applied to arbitrarily large training data. Hence, by formulating a multi-fidelity model to employ low-fidelity simulations, we were able to reduce the error of our emulator by approximately 81% with only an approximately 1.6% increase in computing resource utilization.
36 MATERIALS SCIENCE↗
Three practical workflow schedulers for easy maximum parallelism
Runtime scheduling and workflow systems are an increasingly popular algorithmic component in HPC because they allow full system utilization with relaxed synchronization requirements. There are so many special-purpose tools for task scheduling, one might wonder why more are needed. Use cases seen on the Summit supercomputer needed better integration with MPI and greater flexibility in job launch configurations. Preparation, execution, and analysis of computational chemistry simulations at the scale of tens of thousands of processors revealed three distinct workflow patterns. A separate job scheduler was implemented for each one using extremely simple and robust designs: file-based, task-list based, and bulk-synchronous. Comparing to existing methods shows unique benefits of this work, including simplicity of design, suitability for HPC centers, short startup time, and well-understood per-task overhead. All three new tools have been shown to scale to full utilization of Summit, and have been made publicly available with tests and documentation. This work presents a complete characterization of the minimum effective task granularity for efficient scheduler usage scenarios. Here, these schedulers have the same bottlenecks, and hence similar task granularities as those reported for existing tools following comparable paradigms.
97 MATHEMATICS AND COMPUTING↗