The selective aqueous-phase glycerol hydrogenolysis is a promising reaction to produce commercially useful 1,3-propanediol(1,3-PDO).The Pt-WOx bifunctional catalyst can catalyse the glycerol hydrogenol-ysis but the ca...The selective aqueous-phase glycerol hydrogenolysis is a promising reaction to produce commercially useful 1,3-propanediol(1,3-PDO).The Pt-WOx bifunctional catalyst can catalyse the glycerol hydrogenol-ysis but the catalyst deactivation via sintering,metal leaching,and coking can predominantly occur in the aqueous phase reaction.In this work,the effect of reaction temperature,pressure and second promoter(Cu,Fe,Rh,Mn,Re,Ru,Ir,Sn,B,and P)on catalytic performance and deactivation behaviour of Pt/WOx/-Al2O3 was investigated.When doped with Rh,Mn,Re,Ru,Ir,B,and P,the second promoter boosts catalytic activity by promoting great dispersion of Pt on support and increasing Pt surface area.The increased Bronsted acid sites lead to selective synthesis of 1,3-PDO than 1,2-propanediol(1,2-PDO).The characterization studies of fresh and spent catalysts reveal that the main cause of catalyst deactivation is the Pt sintering,as interpreted based on XRD,CO chemisorption,and TEM analyses.The Pt sintering is affected depending on the second promoter that can either or reduce the interaction between Pt,WO_(χ)/γ and Al_(2)O_(3).As an electron acceptor of Pt in Pt/WO_(χ)/γ-Al_(2)O_(3),Re and Mn as second promoters resulted in increased Pt^(2+) on the catalytic surface,which strengthens the contact between Pt andγ-Al_(2)O_(3) and WO_(χ),resulting in a decrease in Pt sintering.The metal leaching and coking are not affected by the presence of second promoter.The catalyst modified with a second promoter possesses improved catalytic activity and 1,3-PDO production,however the stability continues to remain a challenge.The present work unrav-elled the determining parameters of catalytic activity and deactivation,thus providing a promising pro-tocol toward effective catalysts for glycerol hydrogenolysis.展开更多
In the coal-to-ethylene glycol(CTEG)process,precisely estimating quality variables is crucial for process monitoring,optimization,and control.A significant challenge in this regard is relying on offline laboratory ana...In the coal-to-ethylene glycol(CTEG)process,precisely estimating quality variables is crucial for process monitoring,optimization,and control.A significant challenge in this regard is relying on offline laboratory analysis to obtain these variables,which often incurs substantial monetary costs and significant time delays.The resulting few-shot learning scenarios present a hurdle to the efficient development of predictive models.To address this issue,our study introduces the transferable adversarial slow feature extraction network(TASF-Net),an innovative approach designed specifically for few-shot quality prediction in the CTEG process.TASF-Net uniquely integrates the slowness principle with a deep Bayesian framework,effectively capturing the nonlinear and inertial characteristics of the CTEG process.Additionally,the model employs a variable attention mechanism to identify quality-related input variables adaptively at each time step.A key strength of TASF-Net lies in its ability to navigate the complex measurement noise,outliers,and system interference typical in CTEG data.Adversarial learning strategy using a min-max game is adopted to improve its robustness and ability to model irregular industrial data accurately and significantly.Furthermore,an incremental refining transfer learning framework is designed to further improve few-shot prediction performance achieved by transferring knowledge from the pretrained model on the source domain to the target domain.The effectiveness and superiority of TASF-Net have been empirically validated using a real-world CTEG dataset.Compared with some state-of-the-art methods,TASF-Net demonstrates exceptional capability in addressing the intricate challenges for few-shot quality prediction in the CTEG process.展开更多
Selective conversion of fructose to 1,2-propanediol(1,2-PDO)is considered as a sustainable and cost-effective alternative to petroleum-based processes,however,this approach still faces challenges associated with low e...Selective conversion of fructose to 1,2-propanediol(1,2-PDO)is considered as a sustainable and cost-effective alternative to petroleum-based processes,however,this approach still faces challenges associated with low efficiency and harsh reaction conditions.Here,we have successfully synthesized a novel bifunctional Ru-WO_(x)-MgO_(y) catalyst through a facile'one-pot'solvothermal method.Remarkably,this catalyst exhibits exceptional catalytic performances in the conversion of fructose to 1,2-PDO under mild reaction conditions.The yield of 1,2-PDO is up to 56.2%at 140°C for 4 h under an ultra-low hydrogen pressure of only 0.2 MPa,surpassing the reported results in recent literature(below 51%).Comprehensive characterizations and density functional theory(DFT)calculations reveal that the presence of oxygen vacancies in the Ru-WO_(x)-MgO_(y) catalyst,serving as active acidic sites,facilitates the chemoselective cleavage of C-C bonds in fructose,which leads to the generation of active intermediates and ultimately resulted in the high yield of 1,2-PDO.展开更多
基金funded by the National Research Council of Thailand (NRCT)the Second Century Foundation (C2F),Chulalongkorn University,ThailandResearcher Supporting Project RSP2024RR400,King Saud University,Saudi Arabia
文摘The selective aqueous-phase glycerol hydrogenolysis is a promising reaction to produce commercially useful 1,3-propanediol(1,3-PDO).The Pt-WOx bifunctional catalyst can catalyse the glycerol hydrogenol-ysis but the catalyst deactivation via sintering,metal leaching,and coking can predominantly occur in the aqueous phase reaction.In this work,the effect of reaction temperature,pressure and second promoter(Cu,Fe,Rh,Mn,Re,Ru,Ir,Sn,B,and P)on catalytic performance and deactivation behaviour of Pt/WOx/-Al2O3 was investigated.When doped with Rh,Mn,Re,Ru,Ir,B,and P,the second promoter boosts catalytic activity by promoting great dispersion of Pt on support and increasing Pt surface area.The increased Bronsted acid sites lead to selective synthesis of 1,3-PDO than 1,2-propanediol(1,2-PDO).The characterization studies of fresh and spent catalysts reveal that the main cause of catalyst deactivation is the Pt sintering,as interpreted based on XRD,CO chemisorption,and TEM analyses.The Pt sintering is affected depending on the second promoter that can either or reduce the interaction between Pt,WO_(χ)/γ and Al_(2)O_(3).As an electron acceptor of Pt in Pt/WO_(χ)/γ-Al_(2)O_(3),Re and Mn as second promoters resulted in increased Pt^(2+) on the catalytic surface,which strengthens the contact between Pt andγ-Al_(2)O_(3) and WO_(χ),resulting in a decrease in Pt sintering.The metal leaching and coking are not affected by the presence of second promoter.The catalyst modified with a second promoter possesses improved catalytic activity and 1,3-PDO production,however the stability continues to remain a challenge.The present work unrav-elled the determining parameters of catalytic activity and deactivation,thus providing a promising pro-tocol toward effective catalysts for glycerol hydrogenolysis.
基金supported by the National Natural Science Foundation of China(62333010,61673205).
文摘In the coal-to-ethylene glycol(CTEG)process,precisely estimating quality variables is crucial for process monitoring,optimization,and control.A significant challenge in this regard is relying on offline laboratory analysis to obtain these variables,which often incurs substantial monetary costs and significant time delays.The resulting few-shot learning scenarios present a hurdle to the efficient development of predictive models.To address this issue,our study introduces the transferable adversarial slow feature extraction network(TASF-Net),an innovative approach designed specifically for few-shot quality prediction in the CTEG process.TASF-Net uniquely integrates the slowness principle with a deep Bayesian framework,effectively capturing the nonlinear and inertial characteristics of the CTEG process.Additionally,the model employs a variable attention mechanism to identify quality-related input variables adaptively at each time step.A key strength of TASF-Net lies in its ability to navigate the complex measurement noise,outliers,and system interference typical in CTEG data.Adversarial learning strategy using a min-max game is adopted to improve its robustness and ability to model irregular industrial data accurately and significantly.Furthermore,an incremental refining transfer learning framework is designed to further improve few-shot prediction performance achieved by transferring knowledge from the pretrained model on the source domain to the target domain.The effectiveness and superiority of TASF-Net have been empirically validated using a real-world CTEG dataset.Compared with some state-of-the-art methods,TASF-Net demonstrates exceptional capability in addressing the intricate challenges for few-shot quality prediction in the CTEG process.
基金the financial support from the Natural Science Foundation of Chongqing(CSTB2022NSCQ-MSX0458)the State Key Laboratory of Coal Mine Disaster Dynamics and Control(2011DA105287-MS202203)+4 种基金the Joint Fund for Innovation and Development of Chongqing(CSTB2022NSCQ-LZX0030)the financial support from the National Natural Science Foundation of China(22168027 and 22308169)the financial support from the Natural Science Foundation of Chongqing(cstc2021jcyj-msxmX0741)the financial support from the National Natural Science Foundation of China(22105028)the Natural Science Foundation of Chongqing(cstc2021jcyj-msxmX0572)。
文摘Selective conversion of fructose to 1,2-propanediol(1,2-PDO)is considered as a sustainable and cost-effective alternative to petroleum-based processes,however,this approach still faces challenges associated with low efficiency and harsh reaction conditions.Here,we have successfully synthesized a novel bifunctional Ru-WO_(x)-MgO_(y) catalyst through a facile'one-pot'solvothermal method.Remarkably,this catalyst exhibits exceptional catalytic performances in the conversion of fructose to 1,2-PDO under mild reaction conditions.The yield of 1,2-PDO is up to 56.2%at 140°C for 4 h under an ultra-low hydrogen pressure of only 0.2 MPa,surpassing the reported results in recent literature(below 51%).Comprehensive characterizations and density functional theory(DFT)calculations reveal that the presence of oxygen vacancies in the Ru-WO_(x)-MgO_(y) catalyst,serving as active acidic sites,facilitates the chemoselective cleavage of C-C bonds in fructose,which leads to the generation of active intermediates and ultimately resulted in the high yield of 1,2-PDO.
