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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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Can Machine Learning Algorithms be trained to interpret and decode passively observed Automative Ethernet full-duplex signals without access to the original signals transmitted by either endpoint?
Oxygen redox chemistries at high voltage have materialized as a revolutionary paradigm for cathodes with high-energy density; however, they are plagued by the challenges of labile oxygen loss and rapid degradations upon cycling, even after concerted endeavors from the research community. Here we propose a multi-concentration stratagem propelled by entropy reinforcement to enhance the electronic structure disorder (ESD) at high desodiation states for impeding undesired oxygen mobility and ensuring controlled oxygen activity, elucidated by density functional theory calculations. The increased disorder strengthens the reversible electrochemistry of lattice oxygen redox, leading to effectively suppressed P−O structural evolution and highly stable localized TMO 6 octahedral environments, as demonstrated by soft/hard X-ray absorption spectroscopy. Furthermore, through a comparative analysis of sodium-layered cathodes with different configuration entropy, we reveal that a high-entropy state induced by cationic disordering has the capacity to perturb cationic redox boundaries, significantly restraining the formation of detrimental O′3 phases. As a consequence, the high-voltage cycling stability has been greatly upgraded, up to 4.4 V versus Na + /Na, with an impressive 90.1 % capacity retention at 1 C over 100 cycles and 76.1 % capacity retention at 2 C over 300 cycles. In conclusion, the resilient oxygen redox, enabled through the control of ESD, broadens the horizons for entropy engineering and lays the foundation for advancements in high-energy, long-cycling, and safe batteries.
LLM-105 (2,6-diamino-3,5-dinitropyrazine-1-oxide) has been prepared at several different size quantities (~10–70 Kg) and not subjected to further purification, such as recrystallization. Chemical and physical properties were compared—small-scale safety testing (impact, friction, ESD), thermal (chemical reactivity, differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), one-dimensional time-to-explosion (ODTX)), morphological (particle-size distribution (PSD), scanning electron microscopy (SEM), powder x-ray diffraction (PXRD), skeletal density). Each preparation had similar properties to the other preparations except for PSD and PXRD. For PSD, all preparations exhibited a mono-modal distribution with a variation in median values from ~ 40 μm to over 80 μm. All PXRD values indicated the same morphology with minor variations in crystal orientations. Possible polymorphism was also observed in a few cases. SEM images and PXRD indicate all preparations to be diamond-type and X-type crystals with some twinning. Impact, friction, and ESD and thermal sensitivities values are consistent with these type of crystal habits as seen in vast literature studies.
As part of our investigation into the process optimization of 2,6-diaminopyrazine-1-oxide (DAPO), small-scale sensitivity testing (impact, friction, and ESD) was conducted on the precursor, N-nitroso-bis(cyanomethyl)amine (NBCMA). NBCMA exhibited moderate sensitivity to friction, whereas no sensitivity to impact or spark was observed.
Energetic norbornenes are promising candidates toward the development of new energetic polymers due to the synthetic versatility of norbornene ring-opening metathesis polymerizations used in commercial applications. We report the synthesis of two energetic norbornene materials that can be made in two steps with modest yields, containing either trinitroethanol or fluorodinitroethanol substituents. The norbornene monomers were then polymerized, and the polymers were characterized by Fourier transform infrared spectroscopy (FT-IR), differential scanning calorimetry (DSC), contact angle measurements, and proton and carbon nuclear magnetic resonance spectroscopies ( 1 H and 13 C{ 1 H} NMR). Additionally, small-scale safety data consisting of electrostatic discharge (ESD), friction (FS), and impact (IS) sensitivities were measured for the norbornene monomers and their resulting polymers. These analyses revealed that energetic norbornene materials are relatively insensitive and have densities comparable to that of TNT (1.47–1.81 g·cm –3 ).
Since the start of LHC in 2008, the ATLAS experiment has relied on ROOT to provide storage technology for all its processed event data. Internally, ROOT files are organized around TTree structures that are capable of storing complex C++ objects. The capabilities of TTrees developed over the years and are now offering support for advanced concepts like polymorphism, schema evolution and user defined collections and ATLAS makes use of these features to handle its EDM. But some original TTrees concepts, like the POSIX file model and sequential writing, remain unchanged since the beginning and could be an obstacle to achieving the performance required for High Luminosity LHC. With the HL-LHC performance goals in mind, the ROOT project developed a new storage format - the RNTuple. RNTuple, with its accompanying user API, is now in the final development stage and is planned to be production-ready at the end of 2024. Soon after that, the TTree will become a legacy format. ATLAS intends to have its main Event processing framework Athena ready to use RNTuple in the production environment as early as possible. The work on adopting RNTuple as another ROOT storage technology in Athena started already in 2021 and is now nearly complete. Although the initial goal was to focus on derived-AOD products (PHYS and PHYSLITE), with a little added effort all ATLAS data products: RDO, HITS, ESD, AOD and DAOD can be now stored in RNTuple format and transparently read back. In this paper we will describe the current state of RNTuple adoption in the Athena framework and explain the ATLAS EDM requirements that had to be met on the ROOT side to successfully integrate both environments. We will demonstrate the ability to run standard ATLAS production workflows, based on RNTuple as the Event data storage technology, and point out key advantages of the new format.
We study the energy delivered through a small-resistance series “victim” load during electrostatic discharge events in air. For gap lengths over 1 mm, the fraction of the stored energy delivered is mostly gap-length independent, with a slight decrease at larger gaps due to electrode geometry. The energy to the victim scales linearly with circuit capacitance and victim load resistance but is not strongly dependent on circuit inductance. This scaling leads to a simple approach to predicting the maximum energy that will be delivered to a series resistance for the case where the victim load resistance is lower than the spark resistance.