Recently,azobenzene-4,4'-dicarboxylic acid(ADCA)has been produced gradually for use as an organic synthesis or pharmaceutical intermediate due to its eminent performance.With large quantities put into application ...Recently,azobenzene-4,4'-dicarboxylic acid(ADCA)has been produced gradually for use as an organic synthesis or pharmaceutical intermediate due to its eminent performance.With large quantities put into application in the future,the thermal stability of this substance during storage,transportation,and use will become quite important.Thus,in this work,the thermal decomposition behavior,thermal decomposition kinetics,and thermal hazard of ADCA were investigated.Experiments were conducted by using a SENSYS evo DSC device.A combination of differential iso-conversion method,compensation parameter method,and nonlinear fitting evaluation were also used to analyze thermal kinetics and mechanism of ADCA decomposition.The results show that when conversion rate α increases,the activation energies of ADCA's first and main decomposition peaks fall.The amount of heat released during decomposition varies between 182.46 and 231.16 J·g^(-1).The proposed kinetic equation is based on the Avrami-Erofeev model,which is consistent with the decomposition progress.Applying the Frank-Kamenetskii model,a calculated self-accelerating decomposition temperature of 287.0℃is obtained.展开更多
The quantification of the relationship between morphological and color indicators in various organs of horticultural crops is of great significance for crop digital visualization research using computer vision technol...The quantification of the relationship between morphological and color indicators in various organs of horticultural crops is of great significance for crop digital visualization research using computer vision technology.To study this relationship,observational data from a six-year experiment were collected,focusing on seven kinds of color component values of different organs including root,stem,and leaf.Using the collected color data as input,a simulation model was established based on the Elman neural network for six horticultural crops including zizania,cucumber,celery,spinach,parsley,and tea.Results indicated that the horticultural crop morphology model based on the Elman neural network exhibited high simulation accuracy with root mean square error(RMSE)ranging from 0.14 to 1.05 cm and normalized root mean square error(NRMSE)ranging from 2.02% to 11.34% for the maximum root length simulation model.The simulation model for stem length and diameter had an RMSE ranging from 1.42 to 4.96 cm and 0.25 to 1.17 mm,respectively,with NRMSE ranging from 18.19%to 25.65%and 15.13%to 27.25%,respectively.Similarly,chlorophyll content,leaf length,leaf width,and leaf area simulation models exhibited RMSE ranging from 2.80 to 8.22 SPAD,0.44 to 18.04 cm,0.22 to 3.49 cm,and 0.25 to 36.39 cm2,respectively,with NRMSE ranging from 8.63% to 21.04%,15.00%to 22.87%,15.12%to 33.58%,and 6.88%to 24.90%,respectively.These findings provide essential theoretical support for precision agriculture in areas of water and fertilizer management,plant growth diagnosis,and yield prediction.展开更多
基金supported by National Natural Science Foundation of China(51974166).
文摘Recently,azobenzene-4,4'-dicarboxylic acid(ADCA)has been produced gradually for use as an organic synthesis or pharmaceutical intermediate due to its eminent performance.With large quantities put into application in the future,the thermal stability of this substance during storage,transportation,and use will become quite important.Thus,in this work,the thermal decomposition behavior,thermal decomposition kinetics,and thermal hazard of ADCA were investigated.Experiments were conducted by using a SENSYS evo DSC device.A combination of differential iso-conversion method,compensation parameter method,and nonlinear fitting evaluation were also used to analyze thermal kinetics and mechanism of ADCA decomposition.The results show that when conversion rate α increases,the activation energies of ADCA's first and main decomposition peaks fall.The amount of heat released during decomposition varies between 182.46 and 231.16 J·g^(-1).The proposed kinetic equation is based on the Avrami-Erofeev model,which is consistent with the decomposition progress.Applying the Frank-Kamenetskii model,a calculated self-accelerating decomposition temperature of 287.0℃is obtained.
基金supported by Soft Science Research Program Project in Zhejiang Province(Grant No.2022C35063)Lishui Public Welfare Technology Application Research Plan Project(Grant No.2024GYX14)+2 种基金Scientific Research Project of Tianjin Vegetable Industry Technology System Innovation Team(Grant No.201716)the Science and Technology Innovation Activity Plan for College Students in Zhejiang Province(New Talent Plan)(Grant No.2023R480014,2023R480021)the National College Student Innovation and Entrepreneurship Training Programme(Grant No.S202210352001X,S202210352009,S202210352010).
文摘The quantification of the relationship between morphological and color indicators in various organs of horticultural crops is of great significance for crop digital visualization research using computer vision technology.To study this relationship,observational data from a six-year experiment were collected,focusing on seven kinds of color component values of different organs including root,stem,and leaf.Using the collected color data as input,a simulation model was established based on the Elman neural network for six horticultural crops including zizania,cucumber,celery,spinach,parsley,and tea.Results indicated that the horticultural crop morphology model based on the Elman neural network exhibited high simulation accuracy with root mean square error(RMSE)ranging from 0.14 to 1.05 cm and normalized root mean square error(NRMSE)ranging from 2.02% to 11.34% for the maximum root length simulation model.The simulation model for stem length and diameter had an RMSE ranging from 1.42 to 4.96 cm and 0.25 to 1.17 mm,respectively,with NRMSE ranging from 18.19%to 25.65%and 15.13%to 27.25%,respectively.Similarly,chlorophyll content,leaf length,leaf width,and leaf area simulation models exhibited RMSE ranging from 2.80 to 8.22 SPAD,0.44 to 18.04 cm,0.22 to 3.49 cm,and 0.25 to 36.39 cm2,respectively,with NRMSE ranging from 8.63% to 21.04%,15.00%to 22.87%,15.12%to 33.58%,and 6.88%to 24.90%,respectively.These findings provide essential theoretical support for precision agriculture in areas of water and fertilizer management,plant growth diagnosis,and yield prediction.
