The toxicity of heavy metals can cause water pollution and has harmful effects on human health and the environment. Various methods are used to overcome this pressing issue and each method has its own advantages and disadvantages. Membrane filtration technology such as nanofiltration (NF) produces high quality water and has a very small footprint, which results in lower energy usage. Nanofiltration is a membrane-based separation technique based on the reverse osmosis separation process developed in the 1980s. NF membranes have a pore size of 1 nm and molecular weight cut off (MWCO) of 300 to 500 Da. The properties of NF membranes are unique since the surface charge of the membranes is dependent on the functional groups of the membrane. The rejection mechanism of NF membrane is unique as it is a combination of various rejection mechanisms such as steric hindrance, electric exclusion, dielectric effect, and hydration mechanism. However, these mechanisms have not been studied in-depth due to their complexity. There are also many factors contributing to the rejection of NF membrane. Many junior researchers would face difficulty in studying NF membrane. Therefore, this paper is designed for researchers new to the field, and will briefly review the rejection mechanisms of NF membrane by both sieving and non-sieving separation processes. This mini-review aims to provide new researchers with a general understanding of the concept of the separation process of charged membranes.
Traumatic brain injury (TBI) is a leading cause of death and disability in individuals worldwide. Producing a clinically relevant TBI model in small-sized animals remains fairly challenging. For good screening of potential therapeutics, which are effective in the treatment of TBI, animal models of TBI should be established and standardized. In this study, we established mouse models of closed head injury using the Shohami weight-drop method with some modifications concerning cognitive deficiency assessment and provided a detailed description of the severe TBI animal model. We found that 250 g falling weight from 2 cm height produced severe closed head injury in C57BL/6 male mice. Cognitive disorders in mice with severe closed head injury could be detected using passive avoidance test on day 7 after injury. Findings from this study indicate that weight-drop injury animal models are suitable for further screening of brain neuroprotectants and potentially are similar to those seen in human TBI.
Green diesel as a second-generation biofuel has received enormous attention owing to the huge demand for renewable fuel for addressing the net zero target in 2050. This study examines the development of green diesel research through a bibliometric analysis. The state-of-the-art green diesel research is studied based upon 1285 documents (1153 articles and 132 reviews) retrieved from the Scopus database related to the used keywords. The analysis focused on three categories: publication outcomes, most cited papers, and research area identification. The VOSviewer and RStudio (bibliometrix) were applied to analyse the data, rationalized within the framework of author, affiliation, country, citation analysis, cross-dimensional keyword analysis, research streams, and research gaps. The general result of the study highlighted a continuous incline in article numbers classified into three stages: initiation, exploration, and elevation. Those articles were mainly published in bioenergy-themed journals, including Fuel, Energy & Fuels, and Renewable and Sustainable Energy Reviews. Taufiq-Yap Yun Hin is the highest contributor with 41 articles, and Fuel published 110 articles. The rapid growth of green diesel was also inferred by the extensive spread of research maps worldwide. Amid those swift developments, the state of the art on green diesel through bibliometric analysis is not available to the best of our knowledge as far. Subsequently, this review aims to display the state of the art, research gap, and future forecast of green diesel research.