Differentialiy expressed polypeptides in the brain of a BALB/c mouse model infected with scrapie strain 22L were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The results sh...Differentialiy expressed polypeptides in the brain of a BALB/c mouse model infected with scrapie strain 22L were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The results showed that 21 peptides were down-regulated, with peptides of mass-to-charge ratio 758.772 5 and mass-to-charge ratio 5 432.206 9, demonstrating the most significant decreases. These finding suggest that these peptides are candidate biomarkers and may play an important role in the pathogenesis of prion disease.展开更多
Recycling spent lithium-ion batteries is integral to today's low-carbon environmental protection efforts.The concept of direct regeneration,acknowledged for its environmental sustainability,economic viability,and ...Recycling spent lithium-ion batteries is integral to today's low-carbon environmental protection efforts.The concept of direct regeneration,acknowledged for its environmental sustainability,economic viability,and consistent performance of recycled materials,is gaining prominence.This study presents an efficient and nondestructive approach by utilizing an ultrafast microwave technology to directly regenerate spent lithium cobaltate(LCO)cathode materials.In contrast to conventional furnacebased processes,this method significantly reduces the regeneration timeframe.By subjecting the spent LCO mixed with lithium sources to three microwave heating cycles(at approximately 1,350 K),LCO regeneration is achieved,yielding a specific capacity of 140.8 mAh g^(-1)(0.2 C)with a robust cycle stability.With further environmental and economic benefits,the ultrafast microwave technology holds scientific promise for directly regenerating cathode materials,while establishing competitiveness for industrial applications.展开更多
Accurate detection of uric acid(UA)is crucial for diagnosing gout,yet traditional sweat-based UA sensors continue to face challenges posed by complex and costly electrode fabrication methods,as well as weakly hydrophi...Accurate detection of uric acid(UA)is crucial for diagnosing gout,yet traditional sweat-based UA sensors continue to face challenges posed by complex and costly electrode fabrication methods,as well as weakly hydrophilic substrates.Here,we designed and developed simple,low-cost,and hydrophilic sweat UA detection sensors constructed by carbon electrodes and cellulose paper substrates.The carbon electrodes were made by carbonized polyimide films through a simple,one-step laser engraving method.Our electrodes are porous,possess a large specific surface area,and are flexible and conductive.The substrates were composed of highly hydrophilic cellulose paper that can effectively collect,store,and transport sweat.The constructed electrodes demonstrate high sensitivity of 0.4μA Lμmol^(-1)cm^(-2),wide linear range of 2–100μmol/L.In addition,our electrodes demonstrate high selectivity,excellent reproducibility,high flexibility,and outstanding stability against mechanical bending,temperature variations,and extended storage periods.Furthermore,our sensors have been proven to provide reliable results when detecting UA levels in real sweat and on real human skin.We envision that these sensors hold enormous potential for use in the prognosis,diagnosis,and treatment of gout.展开更多
Battery lifetime prediction at early cycles is crucial for researchers and manufacturers to examine product quality and promote technology development.Machine learning has been widely utilized to construct data-driven...Battery lifetime prediction at early cycles is crucial for researchers and manufacturers to examine product quality and promote technology development.Machine learning has been widely utilized to construct data-driven solutions for high-accuracy predictions.However,the internal mechanisms of batteries are sensitive to many factors,such as charging/discharging protocols,manufacturing/storage conditions,and usage patterns.These factors will induce state transitions,thereby decreasing the prediction accuracy of data-driven approaches.Transfer learning is a promising technique that overcomes this difficulty and achieves accurate predictions by jointly utilizing information from various sources.Hence,we develop two transfer learning methods,Bayesian Model Fusion and Weighted Orthogonal Matching Pursuit,to strategically combine prior knowledge with limited information from the target dataset to achieve superior prediction performance.From our results,our transfer learning methods reduce root-mean-squared error by 41%through adapting to the target domain.Furthermore,the transfer learning strategies identify the variations of impactful features across different sets of batteries and therefore disentangle the battery degradation mechanisms and the root cause of state transitions from the perspective of data mining.These findings suggest that the transfer learning strategies proposed in our work are capable of acquiring knowledge across multiple data sources for solving specialized issues.展开更多
Carbonaceous materials,such as graphite,carbon nanotubes(CNTs),and graphene,are in high demand for a broad range of applications,including batteries,capacitors,and composite materials.Studies on the transformation bet...Carbonaceous materials,such as graphite,carbon nanotubes(CNTs),and graphene,are in high demand for a broad range of applications,including batteries,capacitors,and composite materials.Studies on the transformation between diferent types of carbon,especially from abundant and low-cost carbon to high-end carbon allotropes,have received surging interest.Here,we report that,without a catalyst or an external carbon source,biomass-derived amorphous carbon and defective reduced graphene oxide(RGO)can be quickly transformed into CNTs in highly confned spaces by high temperature Joule heating.Combined with experimental measurements and molecular dynamics simulations,we propose that Joule heating induces a high local temperature at defect sites due to the corresponding high local resistance.Te resultant temperature gradient in amorphous carbon or RGO drives the migration of carbon atoms and promotes the growth of CNTs without using a catalyst or external carbon source.Our fndings on the growth of CNTs in confned spaces by fast high temperature Joule heating shed light on the controlled transition between diferent carbon allotropes,which can be extended to the growth of other high aspect ratio nanomaterials.展开更多
基金the National Natural Science Foundation of China,No. 30972197 and 31072148Science and Technology Plan Program of Jilin Province,No. 201105038
文摘Differentialiy expressed polypeptides in the brain of a BALB/c mouse model infected with scrapie strain 22L were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The results showed that 21 peptides were down-regulated, with peptides of mass-to-charge ratio 758.772 5 and mass-to-charge ratio 5 432.206 9, demonstrating the most significant decreases. These finding suggest that these peptides are candidate biomarkers and may play an important role in the pathogenesis of prion disease.
基金supported by the startup funding of Shanghai Jiao Tong Universitythe National Natural Science Foundation of Chinathe Ministry of Higher Education of Malaysia for the Fundamental Research Grant(FRGS/1/2022/STG05/UM/02/3)to Woo Haw Jiunn。
文摘Recycling spent lithium-ion batteries is integral to today's low-carbon environmental protection efforts.The concept of direct regeneration,acknowledged for its environmental sustainability,economic viability,and consistent performance of recycled materials,is gaining prominence.This study presents an efficient and nondestructive approach by utilizing an ultrafast microwave technology to directly regenerate spent lithium cobaltate(LCO)cathode materials.In contrast to conventional furnacebased processes,this method significantly reduces the regeneration timeframe.By subjecting the spent LCO mixed with lithium sources to three microwave heating cycles(at approximately 1,350 K),LCO regeneration is achieved,yielding a specific capacity of 140.8 mAh g^(-1)(0.2 C)with a robust cycle stability.With further environmental and economic benefits,the ultrafast microwave technology holds scientific promise for directly regenerating cathode materials,while establishing competitiveness for industrial applications.
基金funded by Guangdong Basic and Applied Basic Research Foundation(No.2023A1515011388)Guangzhou City Industrial Science&Technology Projects(No.202201010059)+2 种基金the fund from Guangxi China Tobacco Industry Co.,Ltd.(No.2022450000340057)the fund for the construction of Bengbu-SCUT Research Center for Advanced Manufacturing of Biomaterials(No.20210190)The National Key Research and Development Program of China(No.2018YFC1902102)。
文摘Accurate detection of uric acid(UA)is crucial for diagnosing gout,yet traditional sweat-based UA sensors continue to face challenges posed by complex and costly electrode fabrication methods,as well as weakly hydrophilic substrates.Here,we designed and developed simple,low-cost,and hydrophilic sweat UA detection sensors constructed by carbon electrodes and cellulose paper substrates.The carbon electrodes were made by carbonized polyimide films through a simple,one-step laser engraving method.Our electrodes are porous,possess a large specific surface area,and are flexible and conductive.The substrates were composed of highly hydrophilic cellulose paper that can effectively collect,store,and transport sweat.The constructed electrodes demonstrate high sensitivity of 0.4μA Lμmol^(-1)cm^(-2),wide linear range of 2–100μmol/L.In addition,our electrodes demonstrate high selectivity,excellent reproducibility,high flexibility,and outstanding stability against mechanical bending,temperature variations,and extended storage periods.Furthermore,our sensors have been proven to provide reliable results when detecting UA levels in real sweat and on real human skin.We envision that these sensors hold enormous potential for use in the prognosis,diagnosis,and treatment of gout.
基金This work is supported by the startup fund of Shanghai Jiao Tong UniversitySouthern University of Science and TechnologyS.J.H is supported by the Laboratory Directed Research and Development Program of Lawrence Berkeley National Laboratory under U.S.Department of Energy contract no.DE-AC02-05CH11231.
文摘Battery lifetime prediction at early cycles is crucial for researchers and manufacturers to examine product quality and promote technology development.Machine learning has been widely utilized to construct data-driven solutions for high-accuracy predictions.However,the internal mechanisms of batteries are sensitive to many factors,such as charging/discharging protocols,manufacturing/storage conditions,and usage patterns.These factors will induce state transitions,thereby decreasing the prediction accuracy of data-driven approaches.Transfer learning is a promising technique that overcomes this difficulty and achieves accurate predictions by jointly utilizing information from various sources.Hence,we develop two transfer learning methods,Bayesian Model Fusion and Weighted Orthogonal Matching Pursuit,to strategically combine prior knowledge with limited information from the target dataset to achieve superior prediction performance.From our results,our transfer learning methods reduce root-mean-squared error by 41%through adapting to the target domain.Furthermore,the transfer learning strategies identify the variations of impactful features across different sets of batteries and therefore disentangle the battery degradation mechanisms and the root cause of state transitions from the perspective of data mining.These findings suggest that the transfer learning strategies proposed in our work are capable of acquiring knowledge across multiple data sources for solving specialized issues.
基金The authors acknowledge the support of the Maryland NanoCenter and its AIMLab.
文摘Carbonaceous materials,such as graphite,carbon nanotubes(CNTs),and graphene,are in high demand for a broad range of applications,including batteries,capacitors,and composite materials.Studies on the transformation between diferent types of carbon,especially from abundant and low-cost carbon to high-end carbon allotropes,have received surging interest.Here,we report that,without a catalyst or an external carbon source,biomass-derived amorphous carbon and defective reduced graphene oxide(RGO)can be quickly transformed into CNTs in highly confned spaces by high temperature Joule heating.Combined with experimental measurements and molecular dynamics simulations,we propose that Joule heating induces a high local temperature at defect sites due to the corresponding high local resistance.Te resultant temperature gradient in amorphous carbon or RGO drives the migration of carbon atoms and promotes the growth of CNTs without using a catalyst or external carbon source.Our fndings on the growth of CNTs in confned spaces by fast high temperature Joule heating shed light on the controlled transition between diferent carbon allotropes,which can be extended to the growth of other high aspect ratio nanomaterials.
