This review reports progress in solid electrolytes integrated into all-solid-state 2D and 3D lithium-ion microbatteries. The latest improvements, performance and challenges of the all-solid-state 2D and 3D structured microbatteries are analyzed.

No abstract

Investigation of the physical properties of carbon nanowall (CNW) films is carried out in correlation with the growth time. The structural, electronic, optical and electrical properties of CNW films are investigated using electron microscopy, Raman spectroscopy, X-ray photoelectron spectroscopy, ultraviolet photoelectron spectroscopy, UV–Vis spectroscopy, Hall Effect measurement system, Four Point Probing system, and thermoelectric measurements. Shorter growth time results in thinner CNW films with a densely spaced labyrinth structure, while a longer growth time results in thicker CNW films with a petal structure. These changes in morphology further lead to changes in the structural, optical, and electrical properties of the CNW.

No abstract

Contemporary lithium-ion batteries (LIBs) are one of the main components of energy storage systems that need effective management to extend service life and increase reliability and safety. Their characteristics depend highly on internal and external conditions (ageing, temperature, and chemistry). Currently, the state of batteries is determined using two parameters: the state of charge (SOC) and the state of health (SOH). Applying these two parameters makes it possible to calculate the expected battery life and a battery’s performance. There are many methods for estimating the SOH of batteries, including experimental, model-based, and machine learning methods. By comparing model-based estimations with experimental techniques, it can be concluded that the use of experimental methods is not applicable for commercial cases. The electrochemical model-based SOH estimation method clearly explains processes in the battery with the help of multidifferential equations. The machine learning method is based on creating a program trained to predict the battery’s state of health with the help of past ageing data. In this review paper, we analyze the research available in the literature in this direction. It is found that all methods used to assess the SOH of an LIB play an essential role, and each method has its pros and cons.