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Open Access Research Article Issue
Unlocking the Potential of Li–Ag Alloys: Phase Selection and Practical Application
Energy Material Advances 2024, 5: 0108
Published: 07 August 2024
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Dendrite formation, contact loss, and continuous formation of the solid electrolyte interphase (SEI) preclude the practical use of the energy-dense lithium (Li) metal. Li–Ag alloys have the potential to address these issues due to their exceptional lithiophilicity, outstanding mechanical stability, and moderate chemical stability. This study evaluates all phases in the Li–Ag phase diagram based on lithiation capacity, Li insertion, mechanical property, and chemical stability. Our findings suggest that Li4Ag is the most promising phase, and the Gibbs free energy of nucleation (∆Gnucle) for Li–Ag alloys is 3 to 5 orders of magnitude smaller compared to pure Li, resulting in uniform nucleation and deposition behavior. We proposed practical applications within the Li4Ag phases or from the Li9Ag4 to the Li4Ag phases, which may provide a usable capacity of 409 to 696 mAh/g, respectively. Experiments indicate that Li4Ag exhibits not only the smallest impedance but also the highest capacity retention compared to Li9Ag4 and pure Li. The study provides valuable guidance for the selection and application of Li-containing alloys in future battery development.

Open Access Research paper Issue
Defect chemistry for extrinsic doping in ductile semiconductor α-Ag2S
Journal of Materiomics 2024, 10(6): 1270-1278
Published: 07 February 2024
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As a new type of inorganic ductile semiconductor, silver sulfide (α-Ag2S) has garnered a plethora of interests in recent years due to its promising applications in flexible electronics. However, the lack of detailed defect calculations and chemical intuition has largely hindered the optimization of material's performance. In this study, we systematically investigate the defect chemistry of extrinsic doping in α-Ag2S using first-principles calculations. We computationally examine a broad suite of 17 dopants and find that all aliovalent elements have extremely low doping limits (<0.002%) in α-Ag2S, rendering them ineffective in tuning the electron concentrations. In contrast, the isovalent elements Se and Te have relatively high doping limits, being consistent with the experimental observations. While the dopant Se or Te itself does not provide additional electrons, its introduction has a significant impact on the band gap, the band-edge position, and especially the formation energy of Ag interstitials, which effectively improve the electron concentrations by 2–3 orders of magnitudes. The size effects of Se and Te doping are responsible for the more favorable Ag interstitials in Ag2S0.875Se0.125 and Ag2S0.875Te0.125 with respect to pristine Ag2S. This work serves as a theoretical foundation for the rational design of Ag2S-based functional materials.

Open Access Full Length Article Issue
High-throughput calculations combining machine learning to investigate the corrosion properties of binary Mg alloys
Journal of Magnesium and Alloys 2024, 12(4): 1406-1418
Published: 04 February 2022
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Magnesium (Mg) alloys have shown great prospects as both structural and biomedical materials, while poor corrosion resistance limits their further application. In this work, to avoid the time-consuming and laborious experiment trial, a high-throughput computational strategy based on first-principles calculations is designed for screening corrosion-resistant binary Mg alloy with intermetallics, from both the thermodynamic and kinetic perspectives. The stable binary Mg intermetallics with low equilibrium potential difference with respect to the Mg matrix are firstly identified. Then, the hydrogen adsorption energies on the surfaces of these Mg intermetallics are calculated, and the corrosion exchange current density is further calculated by a hydrogen evolution reaction (HER) kinetic model. Several intermetallics, e.g. Y3Mg, Y2Mg and La5Mg, are identified to be promising intermetallics which might effectively hinder the cathodic HER. Furthermore, machine learning (ML) models are developed to predict Mg intermetallics with proper hydrogen adsorption energy employing work function (Wf) and weighted first ionization energy (WFIE). The generalization of the ML models is tested on five new binary Mg intermetallics with the average root mean square error (RMSE) of 0.11 eV. This study not only predicts some promising binary Mg intermetallics which may suppress the galvanic corrosion, but also provides a high-throughput screening strategy and ML models for the design of corrosion-resistant alloy, which can be extended to ternary Mg alloys or other alloy systems.

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