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Al-Majali, Yahya

Publications and source records attributed to Al-Majali, Yahya.

8 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Application of the Multi-Species, Multi-Reaction Model to Coal-Derived Graphite for Lithium-Ion Batteries

Graphite is a critical material used as the negative electrode in lithium-ion batteries. Both natural and synthetic graphites are utilized, with the latter obtained from a range of carbon raw materials. In this paper, efforts to synthesize graphite from coal as a domestic feedstock for synthetic graphite are reported. Domestic coal-derived graphite could address national security and energy issues by standing up domestic supply chains for battery critical materials. The performance in lithium-ion coin cells of this coal derived graphite is compared to a commercial battery-grade graphite. For the first time, a multi-species, multi-reaction (MSMR) modeling technique is applied to synthetic graphite derived from coal. Key thermodynamic, transport, and kinetic parameters are obtained for the coal derived graphite and compared to the same parameters for commercial battery-grade graphite. Modeling of synthetic graphites will allow for virtual evaluation of these materials toward production of domestically sourced graphite.

Paul, Abigail (ORCID:0000000172892069)↗
DOE OSTI2023

Coal Plastic Composite Piping Infrastructure Components

This report examines the development and use of coal plastic composite materials for piping applications. Foam materials were developed at bench scale and evaluated according to ASTM specifications. Techno-economic analyses are also reported.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Formation of Amorphous Carbon Multi‐Walled Nanotubes from Random Initial Configurations

Amorphous carbon nanotubes (a‐CNT) with up to four walls and sizes ranging from 200 to 3200 atoms have been simulated, starting from initial random configurations and using the Gaussian Approximation Potential. The important variables (like density, height, and diameter) required to successfully simulate a‐CNTs were predicted with the machine learning random forest technique. The width of the a‐CNT models ranged between 0.55–2 nm with an average inter‐wall spacing of 0.31 nm. The topological defects in a‐CNTs were analyzed and new defect configurations were observed. The electronic density of states and localization in these phases were discussed and delocalized electrons in the π subspace were identified as an important factor for inter‐layer cohesion. Spatial projection of the electronic conductivity favors axial transport along connecting hexagons, while non‐hexagonal parts of the network either hinder or bifurcate the electronic transport. A vibrational density of states was calculated and is potentially an experimentally comparable fingerprint of the material. The appearance of a low‐frequency radial breathing mode was discussed and the thermal conductivity at 300 K was estimated using the Green‐Kubo formula.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗