Direct methanol fuel cells(DMFCs) have attracted extensive attention as promising next-generation energy conversion devices. However, commercialized proton exchange membranes(PEMs) hardly fulfill the demand of methano...Direct methanol fuel cells(DMFCs) have attracted extensive attention as promising next-generation energy conversion devices. However, commercialized proton exchange membranes(PEMs) hardly fulfill the demand of methanol tolerance for DMFCs employing high-concentration methanol solutions.Herein, we report a series of semi-crystalline poly(arylene ether ketone) PEMs with ultra-densely sulfonic-acid-functionalized pendants linked by flexible alkyl chains, namely, SL-SPEK-x(where x represents the molar ratio of the novel monomer containing multiple phenyl side chain to the bisfluoride monomers). The delicate structural design rendered SL-SPEK-x membranes with high crystallinity and well-defined nanoscale phase separation between hydrophilic and hydrophobic phases. The reinforcement from poly(ether ketone) crystals enabled membranes with inhibited dimensional variation and methanol penetration. Furthermore, microphase separation significantly enhanced proton conductivity. The SL-SPEK-12.5 membrane achieved the optimum trade-off between proton conductivity(0.182 S cm^(-1), 80 ℃), water swelling(13.6%, 80 ℃), and methanol permeability(1.6 × 10^(-7)cm~2 s^(-1)). The DMFC assembled by the SL-SPEK-12.5 membrane operated smoothly with a 10 M methanol solution, outputting a maximum power density of 158.3 mW cm^(-2), nearly twice that of Nafion 117(94.2 mW cm^(-2)). Overall, the novel structural optimization strategy provides the possibility of PEMs surviving in high-concentration methanol solutions, thus facilitating the miniaturization and portability of DMFC devices.展开更多
Peroxidase plays an important role in living systems;however,its storage difficulty and easy inactivation have limited its applications in complex environments.To address these problems,herein,we proposed a method to ...Peroxidase plays an important role in living systems;however,its storage difficulty and easy inactivation have limited its applications in complex environments.To address these problems,herein,we proposed a method to synthesize peroxidase mimics by amination,carbonization,and Fe^(3+)-doping of industrial alkali lignin.The Fe^(3+)-doped lignin-based peroxidase mimic(Fe-LPM),with active centers of coordination between Fe^(3+)and N atoms,showed higher tolerance to pH value and temperature than natural peroxidase.Using Fe-LPM,10-100 mmol/L of H_(2)O_(2) and glucose could be colorimetrically detected with the lowest detection limits of 80μmol/L and 1.5 mmol/L and visual detection limits of 1.0 mmol/L and 10 mmol/L,respectively.The Fe-LPM maintained peroxidase-like activity after 10 cycles and could even be used for H_(2)O_(2) detection in practical samples.This work not only provides a new approach to synthesize peroxidase mimics using biomass materials but also promotes the high-value utilization of lignin.展开更多
In this paper,a highly parallel batch processing engine is designed for SPARQL queries.Machine learning algorithms were applied to make time predictions of queries and reasonably group them,and further make reasonable...In this paper,a highly parallel batch processing engine is designed for SPARQL queries.Machine learning algorithms were applied to make time predictions of queries and reasonably group them,and further make reasonable estimates of the memory footprint of the queries to arrange the order of each group of queries.Finally,the query is processed in parallel by introducing pthreads.Based on the above three points,a spall time prediction algorithm was proposed,including data processing,to better deal with batch SPARQL queries,and the introduction of pthread can make our query processing faster.Since data processing was added to query time prediction,the method can be implemented in any set of data-queries.Experiments show that the engine can optimize time and maximize the use of memory when processing batch SPARQL queries.展开更多
基金supported by the program of Jilin Provincial Department of Science and Technology (YDZJ202301ZYTS320)。
文摘Direct methanol fuel cells(DMFCs) have attracted extensive attention as promising next-generation energy conversion devices. However, commercialized proton exchange membranes(PEMs) hardly fulfill the demand of methanol tolerance for DMFCs employing high-concentration methanol solutions.Herein, we report a series of semi-crystalline poly(arylene ether ketone) PEMs with ultra-densely sulfonic-acid-functionalized pendants linked by flexible alkyl chains, namely, SL-SPEK-x(where x represents the molar ratio of the novel monomer containing multiple phenyl side chain to the bisfluoride monomers). The delicate structural design rendered SL-SPEK-x membranes with high crystallinity and well-defined nanoscale phase separation between hydrophilic and hydrophobic phases. The reinforcement from poly(ether ketone) crystals enabled membranes with inhibited dimensional variation and methanol penetration. Furthermore, microphase separation significantly enhanced proton conductivity. The SL-SPEK-12.5 membrane achieved the optimum trade-off between proton conductivity(0.182 S cm^(-1), 80 ℃), water swelling(13.6%, 80 ℃), and methanol permeability(1.6 × 10^(-7)cm~2 s^(-1)). The DMFC assembled by the SL-SPEK-12.5 membrane operated smoothly with a 10 M methanol solution, outputting a maximum power density of 158.3 mW cm^(-2), nearly twice that of Nafion 117(94.2 mW cm^(-2)). Overall, the novel structural optimization strategy provides the possibility of PEMs surviving in high-concentration methanol solutions, thus facilitating the miniaturization and portability of DMFC devices.
基金The authors are grateful for the financial support by the
文摘Peroxidase plays an important role in living systems;however,its storage difficulty and easy inactivation have limited its applications in complex environments.To address these problems,herein,we proposed a method to synthesize peroxidase mimics by amination,carbonization,and Fe^(3+)-doping of industrial alkali lignin.The Fe^(3+)-doped lignin-based peroxidase mimic(Fe-LPM),with active centers of coordination between Fe^(3+)and N atoms,showed higher tolerance to pH value and temperature than natural peroxidase.Using Fe-LPM,10-100 mmol/L of H_(2)O_(2) and glucose could be colorimetrically detected with the lowest detection limits of 80μmol/L and 1.5 mmol/L and visual detection limits of 1.0 mmol/L and 10 mmol/L,respectively.The Fe-LPM maintained peroxidase-like activity after 10 cycles and could even be used for H_(2)O_(2) detection in practical samples.This work not only provides a new approach to synthesize peroxidase mimics using biomass materials but also promotes the high-value utilization of lignin.
文摘In this paper,a highly parallel batch processing engine is designed for SPARQL queries.Machine learning algorithms were applied to make time predictions of queries and reasonably group them,and further make reasonable estimates of the memory footprint of the queries to arrange the order of each group of queries.Finally,the query is processed in parallel by introducing pthreads.Based on the above three points,a spall time prediction algorithm was proposed,including data processing,to better deal with batch SPARQL queries,and the introduction of pthread can make our query processing faster.Since data processing was added to query time prediction,the method can be implemented in any set of data-queries.Experiments show that the engine can optimize time and maximize the use of memory when processing batch SPARQL queries.
