A graphene/AlGaN deep-ultraviolet(UV)photodetector is presented with ultrahigh responsivity of 3.4×105 A/W at 261 nm incident wavelength and 149 pW light power.A gain mechanism based on electron trapping at the p...A graphene/AlGaN deep-ultraviolet(UV)photodetector is presented with ultrahigh responsivity of 3.4×105 A/W at 261 nm incident wavelength and 149 pW light power.A gain mechanism based on electron trapping at the potential well is proposed to be responsible for the high responsivity.To optimize the trade-off between responsivity and response speed,a back-gate electrode is designed at the AlGaN/GaN two-dimensional electron gas(2DEG)area which eliminates the persistent photocurrent effect and shortens the recovery time from several hours to milliseconds.The 2DEG gate is proposed as an alternative way to apply the back gate electrode on AlGaN based devices on insulating substrates.This work sheds light on a possible way for weak deep-UV light detection.展开更多
Introducing polarization field of piezoelectric materials is an effective strategy to improve photocatalytic performance.In this study,a new type of BaTiO_(3)/CuO heterostructure catalyst was designed and synthesized ...Introducing polarization field of piezoelectric materials is an effective strategy to improve photocatalytic performance.In this study,a new type of BaTiO_(3)/CuO heterostructure catalyst was designed and synthesized to achieve high piezo-photocatalytic activity through the synergy of heterojunction and piezoelectric effect.The BaTiO_(3)/CuO heterostructure shows a significantly enhanced piezo-photocatalytic degradation efficiency of organic pollutants compared with the individual BaTiO_(3) nanowires(NWs)and CuO nanoparticles(NPs).Under the co-excitation of ultrasonic vibration and ultraviolet radiation,the optimal degradation reaction rate constant k of polarized BaTiO_(3)/CuO heterostructure on methyl orange(MO)dye can reach 0.05 min^(−1),which is 6.1 times of photocatalytic rate and 7 times of piezocatalytic rate.The BaTiO_(3)/CuO heterostructure with remarkable piezo-photocatalytic behavior provides a promising strategy for the development of high-efficiency catalysts for wastewater purification,and it also helps understand the coupling mechanism between piezoelectric effect and photocatalysis.展开更多
Ratiometric fluorescent probes hold great promise for in vivo imaging;however,stimuli-activatable ratiometric probes with fluorescence emissions in near-infrared(NIR)region are still very few.Herein,we report a hydrog...Ratiometric fluorescent probes hold great promise for in vivo imaging;however,stimuli-activatable ratiometric probes with fluorescence emissions in near-infrared(NIR)region are still very few.Herein,we report a hydrogen sulfide(H_2S)-activatable ratiometric NIR fluorescent probe(1-SPN)by integrating a H_2S-responsive NIR fluorescent probe 1 into a H_2S-inert poly[2,6-(4,4-bis-(2-ethylhexyl)-4 H-cyclopenta[2,1-b;3,4-b′]dithiophene)-alt-4,7(2,1,3-benzothiadiazole)](PCPDTBT)-based NIR semiconducting polymer nanoparticle(SPN).1-SPN shows"always on"PCPDTBT fluorescence at 830 nm and weak probe 1 fluorescence at 725 nm under excitation at 680 nm.The ratio of NIR fluorescence intensities between 725 and 830 nm(I_(725)/I_(830))is small.Upon interaction with H_2S,the fluorescence at 725 nm is rapidly switched on,resulting in a large enhancement of I_(725)/I_(830),which is allowed for sensitive visualization and quantification of H_2S concentrations in living cells.Taking advantage of enhanced tissue penetration depth of NIR fluorescence,1-SPN is also applied for real-time ratiometric fluorescence imaging of hepatic and tumor H_2S in living mice.This study demonstrates that activatable ratiometric NIR fluorescent probes hold great potential for in vivo imaging.展开更多
The process of discovering and developing new materials currently requires considerable effort,time,and expense.Machine learning(ML)algorithms can potentially provide quick and accurate methods for screening new mater...The process of discovering and developing new materials currently requires considerable effort,time,and expense.Machine learning(ML)algorithms can potentially provide quick and accurate methods for screening new materials.In the present work,the features of the metal organic frameworks(MOFs)as a catalyst for fixing carbon dioxide into cyclic carbonate were extracted to build a data set,which were collected from the experimental results of approximately 100 published papers.Classifiers were trained with the data set with various ML algorithms,including support vector machine(SVM),K-nearest neighbor classification(KNN),decision trees(DT),stochastic gradient descent(SGD),and neural networks(NN),to predict the catalytic performance.The ML models were trained on 80% of the data set and then tested on the remaining 20%to predict the carbon dioxide fixation ability.The trained ML model was extended to explore 1311 hypothetical MOFs,and some structures displayed a strong catalytic ability.Finally,the six best metal ions(Mn,V,Cu,Ni,Zr and Y)and four best ligands(tactmb,tdcbpp,TCPP,H_(3)L)were determined.These six metals and four ligands could be combined into 24 MOFs,which are strongly potential catalysts for carbon dioxide fixation.Using machine learning methods can speed up the screening of materials,and this methodology is promising for application not only to MOFs as catalysts but also in many other materials science projects.展开更多
Noninvasive in vivo imaging of hepatic glutathione(GSH)levels is essential to early diagnosis and prognosis of acute hepatitis.Although GSH-responsive fluorescence imaging probes have been reported for evaluation of h...Noninvasive in vivo imaging of hepatic glutathione(GSH)levels is essential to early diagnosis and prognosis of acute hepatitis.Although GSH-responsive fluorescence imaging probes have been reported for evaluation of hepatitis conditions,the low penetration depth of light in liver tissue has impeded reliable GSH visualization in the human liver.We present a liver-targeted and GSH-responsive trimodal probe(GdNPs-Gal)for rapid evaluation of lipopolysaccharide-(LPS-)induced acute liver inflammation via noninvasive,real-time in vivo imaging of hepatic GSH depletion.GdNPs-Gal are formed by molecular coassembly of a GSH-responsive Gd(III)-based MRI probe(1-Gd)and a liver-targeted probe(1-Gal)at a mole ratio of 5/1(1-Gd/1-Gal),which shows high r_(1) relaxivity with low fluorescence and fluorine magnetic resonance spectroscopic(^(19)F-MRS)signals.Upon interaction with GSH,1-Gd and 1-Gal are cleaved and GdNPs-Gal rapidly disassemble into small molecules 2-Gd,2-Gal,and 3,producing a substantial decline in r_(1) relaxivity with compensatory enhancements in fluorescence and ^(19)F-MRS.By combining in vivo magnetic resonance imaging(^(1)H-MRI)with ex vivo fluorescence imaging and ^(19)F-MRS analysis,GdNPs-Gal efficiently detect hepatic GSH using three independent modalities.We noninvasively visualized LPS-induced liver inflammation and longitudinally monitored its remediation in mice after treatment with an anti-inflammatory drug,dexamethasone(DEX).Findings highlight the potential of GdNPs-Gal for in vivo imaging of liver inflammation by integrating molecular coassembly with GSH-driven disassembly,which can be applied to other responsive molecular probes for improved in vivo imaging.展开更多
基金Project supported by the Research Innovation Fund for College Students of Beijing University of Posts and Telecommunications(Grant No.202002046)the National Natural Science Foundation of China(Grant No.61804012).
文摘A graphene/AlGaN deep-ultraviolet(UV)photodetector is presented with ultrahigh responsivity of 3.4×105 A/W at 261 nm incident wavelength and 149 pW light power.A gain mechanism based on electron trapping at the potential well is proposed to be responsible for the high responsivity.To optimize the trade-off between responsivity and response speed,a back-gate electrode is designed at the AlGaN/GaN two-dimensional electron gas(2DEG)area which eliminates the persistent photocurrent effect and shortens the recovery time from several hours to milliseconds.The 2DEG gate is proposed as an alternative way to apply the back gate electrode on AlGaN based devices on insulating substrates.This work sheds light on a possible way for weak deep-UV light detection.
基金This work was supported by the Major Science and Technology Programs of Yunnan(No.202002AB080001-1)National Natural Science Foundation of China(No.91963114)+1 种基金Fundamental Research Funds for the Central Universities(No.FRF-TP-20-12B)National Key R&D Program of China(No.2018YFB0704301).
文摘Introducing polarization field of piezoelectric materials is an effective strategy to improve photocatalytic performance.In this study,a new type of BaTiO_(3)/CuO heterostructure catalyst was designed and synthesized to achieve high piezo-photocatalytic activity through the synergy of heterojunction and piezoelectric effect.The BaTiO_(3)/CuO heterostructure shows a significantly enhanced piezo-photocatalytic degradation efficiency of organic pollutants compared with the individual BaTiO_(3) nanowires(NWs)and CuO nanoparticles(NPs).Under the co-excitation of ultrasonic vibration and ultraviolet radiation,the optimal degradation reaction rate constant k of polarized BaTiO_(3)/CuO heterostructure on methyl orange(MO)dye can reach 0.05 min^(−1),which is 6.1 times of photocatalytic rate and 7 times of piezocatalytic rate.The BaTiO_(3)/CuO heterostructure with remarkable piezo-photocatalytic behavior provides a promising strategy for the development of high-efficiency catalysts for wastewater purification,and it also helps understand the coupling mechanism between piezoelectric effect and photocatalysis.
基金supported by the National Natural Science Foundation of China(21922406,21775071,21632008)the Natural Science Foundation of Jiangsu Province(BK20190055)+1 种基金the Fundamental Research Funds for the Central Universities(020514380185)Excellent Research Program of Nanjing University(ZYJH004)。
文摘Ratiometric fluorescent probes hold great promise for in vivo imaging;however,stimuli-activatable ratiometric probes with fluorescence emissions in near-infrared(NIR)region are still very few.Herein,we report a hydrogen sulfide(H_2S)-activatable ratiometric NIR fluorescent probe(1-SPN)by integrating a H_2S-responsive NIR fluorescent probe 1 into a H_2S-inert poly[2,6-(4,4-bis-(2-ethylhexyl)-4 H-cyclopenta[2,1-b;3,4-b′]dithiophene)-alt-4,7(2,1,3-benzothiadiazole)](PCPDTBT)-based NIR semiconducting polymer nanoparticle(SPN).1-SPN shows"always on"PCPDTBT fluorescence at 830 nm and weak probe 1 fluorescence at 725 nm under excitation at 680 nm.The ratio of NIR fluorescence intensities between 725 and 830 nm(I_(725)/I_(830))is small.Upon interaction with H_2S,the fluorescence at 725 nm is rapidly switched on,resulting in a large enhancement of I_(725)/I_(830),which is allowed for sensitive visualization and quantification of H_2S concentrations in living cells.Taking advantage of enhanced tissue penetration depth of NIR fluorescence,1-SPN is also applied for real-time ratiometric fluorescence imaging of hepatic and tumor H_2S in living mice.This study demonstrates that activatable ratiometric NIR fluorescent probes hold great potential for in vivo imaging.
基金This study was supported by the National Natural Science Foundation of China(21676004).
文摘The process of discovering and developing new materials currently requires considerable effort,time,and expense.Machine learning(ML)algorithms can potentially provide quick and accurate methods for screening new materials.In the present work,the features of the metal organic frameworks(MOFs)as a catalyst for fixing carbon dioxide into cyclic carbonate were extracted to build a data set,which were collected from the experimental results of approximately 100 published papers.Classifiers were trained with the data set with various ML algorithms,including support vector machine(SVM),K-nearest neighbor classification(KNN),decision trees(DT),stochastic gradient descent(SGD),and neural networks(NN),to predict the catalytic performance.The ML models were trained on 80% of the data set and then tested on the remaining 20%to predict the carbon dioxide fixation ability.The trained ML model was extended to explore 1311 hypothetical MOFs,and some structures displayed a strong catalytic ability.Finally,the six best metal ions(Mn,V,Cu,Ni,Zr and Y)and four best ligands(tactmb,tdcbpp,TCPP,H_(3)L)were determined.These six metals and four ligands could be combined into 24 MOFs,which are strongly potential catalysts for carbon dioxide fixation.Using machine learning methods can speed up the screening of materials,and this methodology is promising for application not only to MOFs as catalysts but also in many other materials science projects.
基金Financial supports from National Key R&D Program of China(2017YFA0701301)National Natural Science Foundation of China(21922406,21775071,and 21632008)+3 种基金Natural Science Foundation of Jiangsu Province(BK20190055)CAS Key Laboratory of Receptor Research(SIMM1904YKF-03)Fundamental Research Funds for the Central Universities(020514380185)Excellent Research Program of Nanjing University(ZYJH004)are acknowledged.
文摘Noninvasive in vivo imaging of hepatic glutathione(GSH)levels is essential to early diagnosis and prognosis of acute hepatitis.Although GSH-responsive fluorescence imaging probes have been reported for evaluation of hepatitis conditions,the low penetration depth of light in liver tissue has impeded reliable GSH visualization in the human liver.We present a liver-targeted and GSH-responsive trimodal probe(GdNPs-Gal)for rapid evaluation of lipopolysaccharide-(LPS-)induced acute liver inflammation via noninvasive,real-time in vivo imaging of hepatic GSH depletion.GdNPs-Gal are formed by molecular coassembly of a GSH-responsive Gd(III)-based MRI probe(1-Gd)and a liver-targeted probe(1-Gal)at a mole ratio of 5/1(1-Gd/1-Gal),which shows high r_(1) relaxivity with low fluorescence and fluorine magnetic resonance spectroscopic(^(19)F-MRS)signals.Upon interaction with GSH,1-Gd and 1-Gal are cleaved and GdNPs-Gal rapidly disassemble into small molecules 2-Gd,2-Gal,and 3,producing a substantial decline in r_(1) relaxivity with compensatory enhancements in fluorescence and ^(19)F-MRS.By combining in vivo magnetic resonance imaging(^(1)H-MRI)with ex vivo fluorescence imaging and ^(19)F-MRS analysis,GdNPs-Gal efficiently detect hepatic GSH using three independent modalities.We noninvasively visualized LPS-induced liver inflammation and longitudinally monitored its remediation in mice after treatment with an anti-inflammatory drug,dexamethasone(DEX).Findings highlight the potential of GdNPs-Gal for in vivo imaging of liver inflammation by integrating molecular coassembly with GSH-driven disassembly,which can be applied to other responsive molecular probes for improved in vivo imaging.
