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Results for “K(CoP)2”

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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Materials Data on K(CoP)2 by Materials Project

K(CoP)2 is alpha bismuth trifluoride-derived structured and crystallizes in the tetragonal I4/mmm space group. The structure is three-dimensional. K1+ is bonded in a body-centered cubic geometry to eight equivalent P3- atoms. All K–P bond lengths are 3.36 Å. Co+2.50+ is bonded to four equivalent P3- atoms to form a mixture of edge and corner-sharing CoP4 tetrahedra. All Co–P bond lengths are 2.20 Å. P3- is bonded in a 8-coordinate geometry to four equivalent K1+ and four equivalent Co+2.50+ atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Modeling of hydrogen liquefaction using magnetocaloric cycles with permanent magnets

Hydrogen (H 2 ) is promising alternative to replace fossil fuels, but its transport and storage has been challenging. As H 2 fuel cell vehicles are gaining traction, the infrastructure for storing large amounts of liquid H 2 is needed. However, liquid H 2 would suffer from boil-off loss, and traditional vapor compression refrigeration systems would not be able to economically recover the lost H 2 due to the low efficiencies at cryogenic temperature. Magnetocaloric (MC) refrigeration systems could possess much higher coefficient of performance (COP) at cryogenic temperature compared to the vapor compression ones. Previous work on cryogenic MC systems, however, have only focused on large scale applications which use superconducting magnets to provide a large magnetic field but are prohibitively expensive to operate for small scale applications, such as that of a H 2 refilling station. In this work, we model the performance of a MC refrigeration cycle using 1-Tesla permanent magnets for H 2 liquefaction, with the objective of cooling H 2 from 80 K (using liquid nitrogen as the heat sink) to 20 K (boiling point of hydrogen). We evaluate main performance metrics including the total work input to the refrigeration system, COP, total MCM mass in the system, and total volume of the permanent magnets, etc. Our modeling results indicate that such a permanent magnet-based MC cooling system is feasible for small-scale H 2 liquefaction, with projected COP values significantly higher than those of vapor compression systems. In conclusion, this work provides design guidelines for future experimental efforts on permanent magnet MC cooling systems for cryogenic cooling.

08 HYDROGEN↗
DOE OSTI2024

Machine learning-accelerated discovery of iron cobalt phosphides as rare-earth-free magnets

Here, the discovery of rare-earth-free permanent magnets has been a goal of scientists for decades. The absence of rare-earth elements will alleviate a pressing concern about the availability of rare-earth elements used in permanent magnets. These magnets are crucial for applications such as wind turbines, electric cars, and memory devices. Rare-earth magnets are special owing to a large magnetic anisotropy energy (K 1 ). In contrast, iron cobalt phosphides hold promise since doping P into cubic FeCo can induce anisotropy, leading to a large coercivity, without introducing rare-earth elements. We present a comprehensive search over the Fe-Co-P ternary space for magnets, utilizing recently developed adaptive machine learning feedback to efficiently screen over 850 000 structures. We focus on machine learning acceleration as a paradigm for materials design. Further adaptive genetic algorithm searches and first-principles calculations aid in the identification of 16 new structures below the known convex hull. Five of them possess high magnetic polarization (J s > 1 T). The structures with desirable magnetic properties center on (Fe,Co) 2⁢ P. This supports conventional wisdom, which focuses on the mixture of the two known end compounds: Fe 2 ⁢P and Co 2 ⁢P. Our work provides guidance for synthesis. We find Fe 7 ⁢CoP 4 shows the most promise (J s = 1.03T and K 1 = 0.83MJ/m 3 ).

36 MATERIALS SCIENCE↗
DOE OSTI2021

Decarbonization of Residential Building Energy Supply: Impact of Cogeneration System Performance on Energy, Environment, and Economics

Electrical and thermal loads of residential buildings present a unique opportunity for onsite power generation, and concomitant thermal energy generation, storage, and utilization, to decrease primary energy consumption and carbon dioxide intensity. This approach also improves resiliency and ability to address peak load burden effectively. Demand response programs and grid-interactive buildings are also essential to meet the energy needs of the 21st century while addressing climate impact. Given the significance of the scale of building energy consumption, this study investigates how cogeneration systems influence the primary energy consumption and carbon footprint in residential buildings. The impact of onsite power generation capacity, its electrical and thermal efficiency, and its cost, on total primary energy consumption, equivalent carbon dioxide emissions, operating expenditure, and, most importantly, thermal and electrical energy balance, is presented. The conditions at which a cogeneration approach loses its advantage as an energy efficient residential resource are identified as a function of electrical grid’s carbon footprint and primary energy efficiency. Compared to a heat pump heating system with a coefficient of performance (COP) of three, a 0.5 kW cogeneration system with 40% electrical efficiency is shown to lose its environmental benefit if the electrical grid’s carbon dioxide intensity falls below 0.4 kg CO 2 per kWh electricity.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Emulation of radiation transport in 3D stochastic media using 1D planar Monte Carlo stochastic media radiation transport algorithms

A subset of stochastic media radiation transport problems involves those in which radiation is incident on a thin slab of stochastic material. Particle tracking in 3D for such problems is expensive, and 1D planar models lack accuracy because they only allow the material to change in one dimension. Therefore, we propose dimensional emulation, which through a slight modification allows existing 1D planar geometry stochastic media radiation transport models to reproduce results from the equivalent 3D models by allowing the material to change in all three dimensions, reproducing the fidelity of the 3D model for the low computational cost of the 1D planar model. In this work, we apply dimensional emulation to three Monte Carlo stochastic media radiation transport models: Chord Length Sampling (CLS), the Local Realization Preserving method (LRP), and a variant of Conditional Point Sampling (CoPS). For a common Markovian benchmark set, the 3D emulation variants of these algorithms are numerically verified to reproduce the results of the 3D variants within statistics while running 1.3 to 2 times faster in the implementation within Sandia National Laboratories open-source research code PlaybookMC. The 3D emulation variants are also shown to yield a 72%–92% reduction in error for the thin slab problems in comparison to the 1D benchmark. As a result, the 3D emulation variant of CLS and CoPS-1 are shown to reproduce 3D CLS results that were used to approximate results for a 3D spherical inclusion geometry benchmark set.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗