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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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An important goal of New Millennium is to research new methods of performing spacecraft and mission design. We have completed the first phase of our effort on how to make design tools such as analysis programs more available.
Driven by energy efficiency advances and renewable energy cost reductions, zero energy buildings are popping up all around the country. Although zero energy represents a bold paradigm shift - from buildings that consume energy to buildings that produce enough energy to meet their energy needs on an annual basis - it isn't a sudden shift. Zero energy buildings are the result of steady, incremental progress by researchers and building professionals working together to improve building energy performance. ASHRAE is taking the lead by publishing - in partnership with the American Institute of Architects (AIA), the Illuminating Engineering Society (IES), the U.S. Green Building Council (USGBC), and the U.S. Department of Energy (DOE) - a new series of advanced energy design guides (AEDGs) focused on zero energy buildings. The recently completed Advanced Energy Design Guide for K-12 School Buildings: Achieving Zero Energy (K-12 ZE AEDG) is the first in this series.
Electrocatalytic hydrogen generation requires a multifunctional electrocatalyst with abundant active sites to drive multielectron transfer reactions. High entropy alloys (HEA) are five or more-elements with high configurational entropy are considered unique materials for next-generation electrocatalysts. Here, in this work, based on new screening guidelines for catalyst selections that combine density-functional theory calculated Gibbs formation-enthalpy with bond length and electronegativity variance, a novel HEA electrocatalyst consisting of five elements, namely, Pt, Pd, Ni, Co, and Mn has been designed. By simple room temperature electrodeposition, the designed catalyst is prepared and its hydrogen evolution reaction (HER) is explored and validated through experimental and theoretical approaches. The HEA demonstrated a superior HER activity with an overpotential of 22.6 mV at -10 mA cm -2 which outperforms Pt/C commercial catalyst. No evident degradation of the material is detected even after 100 hours of continuous operation under high current density. Moreover, the HEA has shown exceptional performance in harsh electrolyte conditions such as in simulated seawater and actual seawater. Remarkably, the density-functional theory calculated Gibbs formation-enthalpy is small (≈0 eV) compared to Pt/C placing the new HEA near the apex of Trasatti's model of Volcano plot, which is also suggestive of superior HER activity.
This work minimizes electrode passive components and moves toward bridging the gap between actual and theoretical battery gravimetric energy density. Binder-free self-supporting (BFSS) cathodes were prepared from redox-active, high aspect ratio, potassium α-MnO2 nanofibers (K-OMS-2), eliminating the binder and current collector. The electroactive and structural element, K-OMS-2, was prepared using a scalable, moderate temperature, aqueous synthesis. The BFFS electrode approach allows fabrication of thick, high energy density electrodes with low impedance, with up to 10 fold improvement in delivered specific energy relative to conventional cathodes. This could enable high capacity large form factor cell designs, as required for applications demanding high energy content. In principle, this approach suggests a widely applicable paradigm for the construction of other BFFS electrodes through the targeted synthesis of other transition metal oxides with high aspect, fibrous morphologies. Introduction
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Thin‐film solid‐state metal dealloying (thin‐film SSMD) is a promising method for fabricating nanostructures with controlled morphology and efficiency, offering advantages over conventional bulk materials processing methods for integration into practical applications. Although machine learning (ML) has facilitated the design of dealloying systems, the selection of key thermal treatment parameters for nanostructure formation remains largely unknown and dependent on experimental trial and error. To overcome this challenge, a workflow enabling high‐throughput characterization of thermal treatment parameters is demonstrated using a laser‐based thermal treatment to create temperature gradients on single thin‐film samples of Nb‐Al/Sc and Nb‐Al/Cu. This continuous thermal space enables observation of dealloying transitions and the resulting nanostructures of interest. Through synchrotron X‐ray multimodal and high‐throughput characterization, critical transitions and nanostructures can be rapidly captured and subsequently verified using electron microscopy. The key temperatures driving chemical reactions and morphological evolutions are clearly identified. While the oxidation may influence nanostructure formation during thin‐film treatment, the dealloying process at the dealloying front involves interactions solely between the dealloying elements, highlighting the availability and viability of the selected systems. Further, this approach enables efficient exploration of the dealloying process and validation of ML predictions, thereby accelerating the discovery of thin‐film SSMD systems with targeted nanostructures.
For presentation at Materials Science Technology 2023, Columbus, OH, October 1-4, 2023.
Future electricity generation systems must be optimized to provide flexibility that counteracts the variability of non-dispatchable renewable energy sources and ensures the reliability and safety of critical infrastructure, including the electric grid. The current state-of-the-art is to co-optimize the design and operation of integrated energy systems (IES) treating historical or predicted time-series electricity prices as fixed parameters. Recent literature has shown the limitations of this price taker assumption, which neglects how IES optimization decisions influence market outcomes. As such, this paper proposes a new optimization formulation that uses machine learning surrogate models, trained from a library of annual market operation simulations, to embed IES market interactions into the co-optimization problem directly. Using a thermal generator example built in the open-source IDAES computational environment, we show that the price taker approach routinely over-predicts annual revenues by 8% or more compared to a validation simulation, where the proposed approach has a typical relative error of 1% or less.
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Enzymatic depolymerization of poly(ethylene terephthalate) (PET) has emerged as a promising approach for polyester recycling, and, to date, many natural and engineered PET hydrolase enzymes have been reported. For industrial use, PET hydrolases must achieve high depolymerization extent and exhibit excellent thermostability. Here, we engineered a natural PET hydrolase, Polyester Hydrolase Leipzig #7 (PHL7), through rational design and directed evolution using a high-throughput screening platform. Four new enzymes were engineered with enhanced properties compared with the parent enzyme, wild-type PHL7 (PHL7-WT), and other benchmark PET hydrolases, under the tested conditions. In bioreactors, the exemplary engineered enzyme, PHL7-Jemez, exhibited improved ability to depolymerize amorphous PET film compared with PHL7-WT at 2.9% and 20% substrate loadings, with 37% and 270% higher hydrolysis, respectively, after 48 h. This study develops several state-of-the-art PET hydrolases and demonstrates a directed evolution platform to engineer high-performance enzymes, which can accelerate enzyme discovery toward improved biocatalytic recycling.
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Deformation asymmetry of magnesium alloys is an important factor on machine design in the automobile industry. Represented by the ratio of compressive yield stress (CYS) against tensile yield stress (TYS), deformation asymmetry is strongly related to texture and grain size. A polycrystalline viscoplasticity model, modified intermediate Φ-model, is used to predict the deformation behavior of magnesium alloys with different grain sizes. Validated with experimental results, integrated computational materials engineering is applied to find out the route in achieving desired asymmetry via thermomechanical processing. For example, CYS/TYS in rolled texture is smaller than 1 under different loading directions. In other textures, such as extruded texture, CYS/TYS is large along the normal direction. Starting from rolled texture, asymmetry will increase to close to 1 along the rolling direction after being compressed to a strain of 0.2. Our modified Φ-model also shows that grain refinement increases CYS/TYS. Along with texture control, grain refinement also can optimize the yield asymmetry. After the grain size decreases to a critical value, CYS/TYS reaches to 1 because CYS increases much faster than TYS. By tailoring the microstructure using texture control and grain refinement, it is achievable to optimize yield asymmetry in wrought magnesium alloys.
There are currently no approved vaccines or small molecule therapeutics available for the prophylaxis or treatment of Middle East Respiratory Syndrome coronavirus (MERS-CoV) infections. MERS-CoV 3CL protease is essential for viral replication; consequently, it is an attractive target that provides a potentially effective means of developing small molecule therapeutics for combatting MERS-CoV. We describe herein the structure-guided design and evaluation of a novel class of inhibitors of MERS-CoV 3CL protease that embody a piperidine moiety as a design element that is well-suited to exploiting favorable subsite binding interactions to attain optimal pharmacological activity and PK properties. Additionally, the mechanism of action of the compounds and the structural determinants associated with binding were illuminated using X-ray crystallography.