With an ultrahigh theoretical specific capacity of 3860 mAh g-1 and the least negative electrochemical potential of -3.04 V (vs the standard hydrogen electrode), Lithium Metal Batteries (LMBs) are seen as a promising energy storage candidate for next-generation electric vehicles. Unfortunately, their enormous interfacial resistance and uncontrollably growing dendrites have made their future applications extremely difficult. In this review article, firstly we have summarized systematic and in-depth issues associated with dendrites in polymer and inorganic Solid-State Electrolytes (SSEs), and the various ways of LMB's failure due to dendrites. Second, different tactics have been explored depending on dendritic nucleation and growth, either to block the dendrites or to increase the LMB's operational lifetime before it short circuits. In the end, the extensive conclusion and outlook on the ongoing limitations and recommended research on LMBs have been discussed.

Nanocrystalline yttria-stabilized zirconia (YSZ) was synthesized by a modified co-precipitation method. The process involves the use of molecular water associated with metal precursors to facilitate the hydroxylation. In this method, triethylamine was used to generate hydroxide ions from the molecular water of precursors, which helps to produce the metal hydroxides. Since no external water is utilized during the precipitation process, it is expected that the as-prepared and calcined materials should have minimum aggregation caused by the hydrogen bonding. The as-prepared and calcined YSZ powders are characterized by X-ray powder diffraction (XRD), energy dispersive X-ray analysis (EDX), Brunauer Emmett-Teller (BET), transmission and scanning electron microscopy (TEM and SEM) and electrochemical impedance spectroscopy (EIS). Cubic phase YSZ, having yttria content of 8 mol

A hydrothermal approach is reported for producing Ce-doped MnO2 (0.5 to 2 mol

Unlike conventional liquid electrolytes, solid-state electrolytes (SSEs) have gained increased attention in the domain of all-solid-state lithium-ion batteries (ASSBs) due to their safety features, higher energy/power density, better electrochemical stability, and a broader electrochemical window. SSEs, however, face several difficulties, such as poorer ionic conductivity, complicated interfaces, and unstable physical characteristics. Vast research is still needed to find compatible and appropriate SSEs with improved properties for ASSBs. Traditional trial-and-error procedures to find novel and sophisticated SSEs require vast resources and time. Machine learning (ML), which has emerged as an effective and trustworthy tool for screening new functional materials, was recently used to forecast new SSEs for ASSBs. In this study, we developed an ML-based architecture to predict ionic conductivity by utilizing the characteristics of activation energy, operating temperature, lattice parameters, and unit cell volume of various SSEs. Additionally, the feature set can identify distinct patterns in the data set that can be verified using a correlation map. Because they are more reliable, the ensemble-based predictor models can more precisely forecast ionic conductivity. The prediction can be strengthened even further, and the overfitting issue can be resolved by stacking numerous ensemble models. The data set was split into 70:30 ratios to train and test with eight predictor models. The maximum mean-squared error and mean absolute error in training and testing for the random forest regressor (RFR) model were obtained as 0.001 and 0.003, respectively.

CuO films on transparent, conductive substrates (fluorine doped tin oxide, FTO), obtained by spray pyrolysis, were analyzed photoelectrochemically in neutral and alkaline solutions. The photoresponse was typical for a p -type semiconductor in a junction with an electrolyte. In absence of an electron scavenger in solution, cathodic photocurrents decayed rapidly (within minutes). This is ascribed to photogenerated conduction band electron initiated reduction of the electrode material to Cu2O. Such films could be reactivated by annealing in air, which resulted in the reconstruction of the CuO phase and complete recovery of photocurrents. Reducible species (methylviologen, ferricyanide, oxygen) were added to the electrolyte in order to compete with the photoelec-trochemical auto-reduction of the semiconducting layer. In the case of O-2 as scavenger, formation of a product in solution, H2O2, was observed, although with a Faradaic efficiency of only 2 percent. In all cases, only minor long-term stabilization was achieved. This was because sufficiently high concentrations of electron scavengers could not be used when high cathodic dark currents were developed (case of ferricyanide), or when the solubility was limited (case of oxygen). In addition, reduction of the semiconductor by the reduced photoactive species (case of methylviologen) can occur.

Lithium-ion-based all solid-state batteries (ASSBs) with inorganic solid-state electrolytes have attracted much attention due to their high energy density, excellent mechanical-electrochemical stability, and lower manufacturing cost. Also, from an environmental perspective ASSBs guarantee a cleaner alternative to fossil-fuel-based applications. Relatively lower Li-ion conductivity of most inorganic solid-state electrolytes and higher electrode-electrolyte interfacial resistance are the most challenging aspects of inorganic solid-state electrolytes. Here, to support researcher's understanding of the inorganic solid-state electrolytes, we have summarized the background and recent advancements in the fundamental understanding of the heart of ASSBs i.e. the inorganic solid electrolytes, by addressing the domains of their structure, Li-ion transport mechanism and the current processing routes. Also, strategies to enhance the performance and stability of ASSBs, the optimization of electrode-electrolyte interfacial resistance are discussed.