• 제목/요약/키워드: Mechanistic studies

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Explorative and Mechanistic Studies of the Photooxygenation of Sulfides

  • Albini, Angelo;Bonesi, Sergio M.
    • Journal of Photoscience
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    • 제10권1호
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    • pp.1-7
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    • 2003
  • The results of recent work on the dye-sensitized photooxygenation of sulfides is discussed. In the case of dialkyl sulfides, the weakly bonded adduct initially formed with singlet oxygen (the persulfoxide) decays unproductively unless protonation by an acid (an alcohol or a carboxylic acid) facilitates its conversion to the sulfoxide. The effect is proportional to the strength of the acid (eg., less than 0.1 % chloroacetic acid in benzene is sufficient for maximal efficiency) and corresponds to general acid catalysis, suggesting that protonation of the persulfoxide occurs. On the other hand, with sulfides possessing an activated hydrogen in ${\alpha}$ position (eg., benzyl and allyl sulfides), hydrogen transfer becomes an efficient process in aprotic media and yields a S-hydroperoxysulfoniumm ylide, possibly arising from a conformation of the persulfoxide that is different from the one protonated in the presence of acids. Calculations on some substituted sulfides support this hypothesis. This process, which leads to C-S bond fragmentation with formation of an aldehyde, may be viewed as a general method for the preparation of aryl and heteroaryl aldehydes. In this effort, mechanistic studies offered new hints on the structure of the intermediate persulfoxide.

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데이터 기반 모델에 의한 강제환기식 육계사 내 기온 변화 예측 (Data-Based Model Approach to Predict Internal Air Temperature in a Mechanically-Ventilated Broiler House)

  • 최락영;채영현;이세연;박진선;홍세운
    • 한국농공학회논문집
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    • 제64권5호
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    • pp.27-39
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    • 2022
  • The smart farm is recognized as a solution for future farmers having positive effects on the sustainability of the poultry industry. Intelligent microclimate control can be a key technology for broiler production which is extremely vulnerable to abnormal indoor air temperatures. Furthermore, better control of indoor microclimate can be achieved by accurate prediction of indoor air temperature. This study developed predictive models for internal air temperature in a mechanically-ventilated broiler house based on the data measured during three rearing periods, which were different in seasonal climate and ventilation operation. Three machine learning models and a mechanistic model based on thermal energy balance were used for the prediction. The results indicated that the all models gave good predictions for 1-minute future air temperature showing the coefficient of determination greater than 0.99 and the root-mean-square-error smaller than 0.306℃. However, for 1-hour future air temperature, only the mechanistic model showed good accuracy with the coefficient of determination of 0.934 and the root-mean-square-error of 0.841℃. Since the mechanistic model was based on the mathematical descriptions of the heat transfer processes that occurred in the broiler house, it showed better prediction performances compared to the black-box machine learning models. Therefore, it was proven to be useful for intelligent microclimate control which would be developed in future studies.