As a potential adsorption material,it is still a challenge for activated carbon fiber(ACF)in efficient adsorption of ethanol due to its nonpolar surface,which is mainly emitted from the grain drying industry.This stud...As a potential adsorption material,it is still a challenge for activated carbon fiber(ACF)in efficient adsorption of ethanol due to its nonpolar surface,which is mainly emitted from the grain drying industry.This study prepared surface polarity-modified ACF using the heteroatom doping method.The modified ACF possessed a richer array of strongly polar oxygen/nitrogen-containing functional groups(primarily phenolic hydroxyl and lactone groups),a larger specific surface are1,and a more developed micropore structure.The adsorption capacities of ethanol for O-ACF and N-ACF were 4.110 mmol/g and 1.698 mmol/g,respectively,which were 11.3 times and 4.7 times those of unmodified ACF.This was a significant improvement over our previous work(0.363 mmol/g).The improvement of adsorption capacity for the N-ACF was mainly due to the higher specific surface are1,greater number of micropores(more adsorption sites)and abundant existence of defects,whereas,for O-ACF,the improvement mainly relied on the abundant presence of oxygen-containing functional groups on the surface.However,water had a negative effect on the adsorption of ethanol for the modified ACF due to competitive adsorption and the disappearance of capillary condensation.It was further revealed that the adsorption process of ethanol and water was quite different.It obeyed the linear driving force(LDF)model for ethanol adsorption,however,the intraparticle diffusion(IPD)model for water adsorption.展开更多
In the rapidly evolving technological landscape,state-owned enterprises(SOEs)encounter significant challenges in sustaining their competitiveness through efficient R&D management.Integrated Product Development(IPD...In the rapidly evolving technological landscape,state-owned enterprises(SOEs)encounter significant challenges in sustaining their competitiveness through efficient R&D management.Integrated Product Development(IPD),with its emphasis on cross-functional teamwork,concurrent engineering,and data-driven decision-making,has been widely recognized for enhancing R&D efficiency and product quality.However,the unique characteristics of SOEs pose challenges to the effective implementation of IPD.The advancement of big data and artificial intelligence technologies offers new opportunities for optimizing IPD R&D management through data-driven decision-making models.This paper constructs and validates a data-driven decision-making model tailored to the IPD R&D management of SOEs.By integrating data mining,machine learning,and other advanced analytical techniques,the model serves as a scientific and efficient decision-making tool.It aids SOEs in optimizing R&D resource allocation,shortening product development cycles,reducing R&D costs,and improving product quality and innovation.Moreover,this study contributes to a deeper theoretical understanding of the value of data-driven decision-making in the context of IPD.展开更多
基金supported by the National Key R&D Program of China(Nos.2022YFB4101500 and 2022YFE0209500)the National Natural Science Foundation of China(Nos.22276191 and 21976177)the Qinghai Province Air Pollution Assessment and Fine Management Support Project,and the University of Chinese Academy of Science.
文摘As a potential adsorption material,it is still a challenge for activated carbon fiber(ACF)in efficient adsorption of ethanol due to its nonpolar surface,which is mainly emitted from the grain drying industry.This study prepared surface polarity-modified ACF using the heteroatom doping method.The modified ACF possessed a richer array of strongly polar oxygen/nitrogen-containing functional groups(primarily phenolic hydroxyl and lactone groups),a larger specific surface are1,and a more developed micropore structure.The adsorption capacities of ethanol for O-ACF and N-ACF were 4.110 mmol/g and 1.698 mmol/g,respectively,which were 11.3 times and 4.7 times those of unmodified ACF.This was a significant improvement over our previous work(0.363 mmol/g).The improvement of adsorption capacity for the N-ACF was mainly due to the higher specific surface are1,greater number of micropores(more adsorption sites)and abundant existence of defects,whereas,for O-ACF,the improvement mainly relied on the abundant presence of oxygen-containing functional groups on the surface.However,water had a negative effect on the adsorption of ethanol for the modified ACF due to competitive adsorption and the disappearance of capillary condensation.It was further revealed that the adsorption process of ethanol and water was quite different.It obeyed the linear driving force(LDF)model for ethanol adsorption,however,the intraparticle diffusion(IPD)model for water adsorption.
文摘In the rapidly evolving technological landscape,state-owned enterprises(SOEs)encounter significant challenges in sustaining their competitiveness through efficient R&D management.Integrated Product Development(IPD),with its emphasis on cross-functional teamwork,concurrent engineering,and data-driven decision-making,has been widely recognized for enhancing R&D efficiency and product quality.However,the unique characteristics of SOEs pose challenges to the effective implementation of IPD.The advancement of big data and artificial intelligence technologies offers new opportunities for optimizing IPD R&D management through data-driven decision-making models.This paper constructs and validates a data-driven decision-making model tailored to the IPD R&D management of SOEs.By integrating data mining,machine learning,and other advanced analytical techniques,the model serves as a scientific and efficient decision-making tool.It aids SOEs in optimizing R&D resource allocation,shortening product development cycles,reducing R&D costs,and improving product quality and innovation.Moreover,this study contributes to a deeper theoretical understanding of the value of data-driven decision-making in the context of IPD.
