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재생가능 에너지원으로서의 해조류 유래 바이오 연료의 현황과 전망
유준,Liu, Jay 한국청정기술학회 2022 청정기술 Vol.28 No.2
Research and development of biofuels as one of the means to mitigate global warming and to avoid fossil fuel depletion has occurred for more than 30 years. However, there has only been limited distribution of a few first- and second-generation biofuels, and widespread supply and consumption of biofuels is still far from a reality. Although a relatively recently studied third-generation biofuel derived from seaweed biomass has been shown to have many advantages, it is yet to be deployed in commercial-scale seaweed biorefineries. This review paper examines the advantages and disadvantages of seaweed biorefineries for the entire value chain covering from seaweed and its cultivation to biofuel production based on an extensive literature search and the author's experience of conducting feasibility studies pertaining to seaweed biorefineries for over 10 years. For this purpose, the literature survey will cover the current status of seaweed production and its research and development worldwide, conversion technologies for biofuel production from seaweed based on bench-scale experiments, and large-scale techno-economic feasibility studies for seaweed conversion to biofuels and bioenergy. In addition, the main problems expected with the commercialization of seaweed-based biofuels will be identified. Finally, the current status of seaweed biorefinery technology and the author's views on its promising future will be summarized.
Group Contribution Method 및 Support Vector Regression 기반 모델을 이용한 방향족 화합물 물성치 예측에 관한 연구
강하영,오창보,원용선,유준,이창준,Kang, Ha Yeong,Oh, Chang Bo,Won, Yong Sun,Liu, J. Jay,Lee, Chang Jun 한국안전학회 2021 한국안전학회지 Vol.36 No.1
To simulate a process model in the field of chemical engineering, it is very important to identify the physical properties of novel materials as well as existing materials. However, it is difficult to measure the physical properties throughout a set of experiments due to the potential risk and cost. To address this, this study aims to develop a property prediction model based on the group contribution method for aromatic chemical compounds including benzene rings. The benzene rings of aromatic materials have a significant impact on their physical properties. To establish the prediction model, 42 important functional groups that determine the physical properties are considered, and the total numbers of functional groups on 147 aromatic chemical compounds are counted to prepare a dataset. Support vector regression is employed to prepare a prediction model to handle sparse and high-dimensional data. To verify the efficacy of this study, the results of this study are compared with those of previous studies. Despite the different datasets in the previous studies, the comparison indicated the enhanced performance in this study. Moreover, there are few reports on predicting the physical properties of aromatic compounds. This study can provide an effective method to estimate the physical properties of unknown chemical compounds and contribute toward reducing the experimental efforts for measuring physical properties.