The present work describes the effects of dimethyl sulfoxide (DMSO) in KOH aqueous electrolyte on the performance of a zinc-air flow battery. Aqueous electrolytes containing 7 M KOH and (0 to 20)% v/v DMSO were studied revealing a critical role of DMSO on the dissolution and deposition of zinc. The anodic zinc dissolution process was studied via cyclic voltammetry, Tafel polarization and electrochemical impedance spectroscopy (EIS). The presence of DMSO showed improved zinc dissolution performance with the highest peak of zinc dissolution being the electrolyte containing 5% v/v DMSO. Tafel analysis demonstrated a significant decrease in polarization resistance and an increase in corrosion rate due to the introduction of DMSO to the electrolyte. This suggests that DMSO has the ability to suspend zinc oxide in the electrolyte, thus preventing passivation of the zinc surface. EIS results revealed that by adding DMSO to the electrolyte, charge transfer resistance increased. This is attributed to the formation of passive layers having arisen from DMSO adsorption, the formation of zincate ions in the vicinity of the zinc surface, and the deposition of discharged products. A difference in Nyquist plots was observed for 20% v/v DMSO/KOH and 0% v/v DMSO/KOH electrolytes implying non-Debye relaxation behavior taking place due to the surface effects. The electrolytes were implemented in a zinc-air flow battery. Maximum power densities of 130 mW/cm² (5% v/v DMSO) and 125 mW/cm² (20% v/v DMSO) were obtained and were observed to be about 43% and 28% higher than that of the DMSO-free electrolyte. Results indicated that when 20% v/v DMSO was added to KOH solution, there was 67% zinc utilization efficiency (550 mAh/g) which provided 20% improvement in discharge capacity. Further, the battery with 20% v/v DMSO demonstrated excellent cyclability. Overall, DMSO shows great promise for enhancement of zinc dissolution/deposition in zinc-air batteries.

The strategy of defect engineering is increasingly recognized for its pivotal role in modulating the electronic structure, thereby significantly improving the electrocatalytic performance of materials. In this study, we present defect-enriched nickel and iron oxides as highly active and cost-effective electrocatalysts, denoted as Ni_0.6Fe_2.4O₄@NC, derived from NiFe-based metal-organic frameworks (MOFs) for oxygen reduction reactions (ORR) and oxygen evolution reactions (OER). XANES and EXAFS confirm that the crystals have a distorted structure and metal vacancies. The cation defect-rich Ni_0.6Fe_2.4O₄@NC electrocatalyst exhibits exceptional ORR and OER activities (ΔE = 0.68 V). Mechanistic pathways of electrochemical reactions are studied by DFT calculations. Furthermore, a rechargeable zinc-air battery (RZAB) using the Ni_0.6Fe_2.4O₄@NC catalyst demonstrates a peak power density of 187 mW cm^-2 and remarkable long-term cycling stability. The flexible solid-state ZAB using the Ni_0.6Fe_2.4O₄@NC catalyst exhibits a power density of 66 mW cm^-2. The proposed structural design strategy allows for the rational design of electronic delocalization of cation defect-rich NiFe spinel ferrite attached to ultrathin N-doped graphitic carbon sheets in order to enhance active site availability and facilitate mass and electron transport.

This work introduced the high-throughput phase prediction of PtPd-based high-entropy alloys via the algorithm based on a combined Korringa-Kohn-Rostoker coherent potential approximation (KKR-CPA) and artificial neural network (ANN) technique. As the first step, the KKR-CPA was employed to generate 2,720 data of formation energy and lattice parameters in the framework of the first-principles density functional theory. Following the data generation, 15 features were selected and verified for all HEA systems in each phase (FCC and BCC) via ANN. The algorithm exhibited high accuracy for all four prediction models on 36,556 data from 9139 HEA systems with 137,085 features, verified by R² closed to unity and the mean relative error (MRE) within 5%. From this dataset comprising 5002 and 4137 systems of FCC and BCC phases, it can be realized based on the highest tendency of HEA phase formation that (1) Sc, Co, Cu, Zn, Y, Ru, Cd, Os, Ir, Hg, Al, Si, P, As, and Tl favor FCC phase, (2) Hf, Ga, In, Sn, Pb, and Bi favor BCC phase, and (3) Ti, V, Cr, Mn, Fe, Ni, Zr, Nb, Mo, Tc, Rh, Ag, Ta, W, Re, Au, Ge, and Sb can be found in both FCC and BCC phases with comparable tendency, where all predictions are in good agreement with the data from the literature. Thus, the combination of KKR-CPA and ANN can reduce the computational cost for the screening of PtPd-based HEA and accurately predict the structure, i.e., FCC, BCC, etc.