利用野外实时快速获取的土壤光谱进行土壤有机质(SOM)预测与制图是精确农业与土壤遥感制图的必然需要,利用ASD FieldSpec Pro FR野外型光谱仪实时快速获取的光谱数据,去除噪声较大的边缘波段后,进行倒数的对数转换(Log(1/R))为吸收光谱...利用野外实时快速获取的土壤光谱进行土壤有机质(SOM)预测与制图是精确农业与土壤遥感制图的必然需要,利用ASD FieldSpec Pro FR野外型光谱仪实时快速获取的光谱数据,去除噪声较大的边缘波段后,进行倒数的对数转换(Log(1/R))为吸收光谱。在分析吸收光谱和光谱指数与SOM关系的基础上,采用偏最小二乘回归法进行SOM的建模预测并借助地统计学方法进行SOM空间变异制图研究。结果表明,建模效果好的指标分别为特征波段(R2=0.91,RPD=3.28),归一化光谱指数(R2=0.90,RPD=3.08),特征波段与3个光谱指数组合(R2=0.87,RPD=2.67),全波段(R2=0.95,RPD=4.36)。光谱指标的克里格制图与实测SOM制图表现出相同的空间变异趋势,不同的指标均达到了较好的预测效果。展开更多
【目的】快速、准确地监测土壤有机质对于精准农业的发展具有重要意义。可见光-近红外(visible and near-infrared,Vis-NIR)光谱技术在土壤属性估算、数字化土壤制图等方面应用较为广泛,然而,在田间进行光谱测量,易受土壤含水量(soil mo...【目的】快速、准确地监测土壤有机质对于精准农业的发展具有重要意义。可见光-近红外(visible and near-infrared,Vis-NIR)光谱技术在土壤属性估算、数字化土壤制图等方面应用较为广泛,然而,在田间进行光谱测量,易受土壤含水量(soil moisture,SM)、温度、土壤表面状况等因素的影响,导致光谱信息中包含大量干扰信息,其中,SM变化是影响光谱观测结果最为显著的因素之一。此研究的目的是探讨OSC算法消除其影响,提升Vis-NIR光谱定量估算土壤有机质(soil organic matter,SOM)的精度。【方法】以江汉平原公安县和潜江市为研究区域,采集217份耕层(0—20 cm)土壤样本,进行风干、研磨、过筛等处理,采用重铬酸钾-外加热法测定SOM;将总体样本划分为3个互不重叠的样本集:建模集S^0(122个样本)、训练集S^1(60个样本)、验证集S^2(35个样本);设计SM梯度试验(梯度间隔为4%),在实验室内获取S^1和S^2样本集的9个梯度SM(0%—32%)的土壤光谱数据;分析SM对土壤Vis-NIR光谱反射率的影响,采用外部参数正交化算法(external parameter orthogonalization,EPO)、正交信号校正算法(orthogonal signal correction,OSC)消除SM对土壤光谱的干扰;利用主成分分析(principal component analysis,PCA)的前两个主成分得分和光谱相关系数两种方法检验消除SM干扰前、后的效果;基于偏最小二乘回归(partial least squares regression,PLSR)方法建立EPO和OSC处理前、后的SOM估算模型,利用决定系数(coefficient of determination,R^2)、均方根误差(root mean square error,RMSE)和RPD(the ratio of prediction to deviation)3个指标比较PLSR、EPO-PLSR、OSC-PLSR模型的性能。【结果】土壤Vis-NIR光谱受SM的影响十分明显,随着SM的增加,土壤光谱反射率呈非线性降低趋势。OSC处理前的湿土光谱数据主成分得分散点相对分散,与干土光谱数据主成分得分空间的位置不重叠,不同SM梯度之间的光谱相关系数变化较大;OSC处理后的湿土光谱数据主成分得分空间的位置基本与干土光谱数据相重合,各样本光谱数据之间相似性很高,不同SM梯度之间的光谱相关系数变化较小。9个SM梯度的EPO-PLSR模型的验证平均R^2_(pre)、RPD分别为0.69、1.7。9个SM梯度的OSC-PLSR模型的验证平均R^2_(pre)、RPD分别为0.72、1.89,校正后的OSC-PLSR模型受SM的较小,有效提升SOM估算模型的精度和鲁棒性。【结论】OSC能够消除SM变化对土壤Vis-NIR光谱的影响,可为将来田间原位实时监测SOM信息提供一定的理论支撑。展开更多
Soil moisture is essential for plant growth in terrestrial ecosystems.This study investigated the visible-near infrared(Vis-NIR)spectra of three subgroups of purple soils(calcareous,neutral,and acidic)from western Cho...Soil moisture is essential for plant growth in terrestrial ecosystems.This study investigated the visible-near infrared(Vis-NIR)spectra of three subgroups of purple soils(calcareous,neutral,and acidic)from western Chongqing,China,containing different water contents.The relationship between soil moisture and spectral reflectivity(R)was analyzed using four spectral transformations,and estimation models were established for estimating the soil moisture content(SMC)of purple soil based on stepwise multiple linear regression(SMLR)and partial least squares regression(PLSR).We found that soil spectra were similar for different moisture contents,with reflectivity decreasing with increasing moisture content and following the order neutral>calcareous>acidic purple soil(at constant moisture content).Three of the four spectral transformations can highlight spectral sensitivity to SMC and significantly improve the correlation between the reflectance spectra and SMC.SMLR and PLSRmethods provide similar prediction accuracy.The PLSR-based model using a first-order reflectivity differential(R?)is more effective for estimating the SMC,and gave coefficient of determination(v2),root mean square errors of validation(RMSEV),and ratio of performance to inter-quartile distance(RPIQ)values of 0.946,1.347,and 6.328,respectively,for the calcareous purple soil,and 0.944,1.818,and 6.569,respectively,for the acidic purple soil.For neutral purple soil,the best prediction was obtained using the SMLR method with R?transformation,yieldingv2,RMSEV and RPIQ values of 0.973,0.888 and 8.791,respectively.In general,PLSR is more suitable than SMLR for estimating the SMC of purple soil.展开更多
Soil texture is an indicator of soil physical structure which delivers many ecological functions of soils such as thermal regime, plant growth, and soil quality. However, traditional methods for soil texture measureme...Soil texture is an indicator of soil physical structure which delivers many ecological functions of soils such as thermal regime, plant growth, and soil quality. However, traditional methods for soil texture measurement are time-consuming and labor-intensive. This study attempts to explore an indirect method for rapid estimating the texture of three subgroups of purple soils (i.e. calcareous, neutral, and acidic). 190 topsoil (0 - 10 cm) samples were collected from sloping croplands in Tongnan and Beibei Districts of Chongqing Municipality in China. Vis-NIR spectrum was measured and processed, and stepwise multiple linear regression (SMLR), partial least squares regression (PLSR), and back propagation neural network (BPNN) models were constructed to inform the soil texture. The clay fractions ranged from 4.40% to 27.12% while sand fractions ranged from 0.34% to 36.57%, hereby soil samples encompass three textural classes (i.e. silt, silt loam, and silty clay loam). For the original spectrum, the texture of calcareous and neutral purple soils was not significantly correlated with spectral reflectance and linear models (SMLR and PLSR) exhibited low prediction accuracy. The correlation coefficients and the goodness-of-fits between soil texture and the transformed spectra of all soil groups increased by continuum-removal (CR), first-order differential (R'), and second-order differential (R") transformations. Among them, the R" had the best performance in terms of improving the correlation coefficients and the goodness-of-fits. For the calcareous purple soil, the SMLR exceeds PLSR and BPNN with a higher coefficient of determination (R<sup>2</sup>) and the ratio of performance to inter-quartile distance (RPIQ) values and lower root mean square error of validation (RMSEV), but for the neutral and acidic purple soils, the PLSR model has a better prediction accuracy. In summary, the linear methods (SMLR and PLSR) are more reliable in estimating the texture of the three purple soil groups when using Vis-NIR spectroscopy inversion.展开更多
The aim of this study was in-line,rapid,and non-destructive detection for soluble solid content(SSC)in pomelos using visible and near-infrared spectroscopy(Vis-NIRS).However,the large size and thick rind of pomelo aff...The aim of this study was in-line,rapid,and non-destructive detection for soluble solid content(SSC)in pomelos using visible and near-infrared spectroscopy(Vis-NIRS).However,the large size and thick rind of pomelo affect the stability of spectral acquisition and the biological variabilities affect the robustness of models.Given these issues,in this study,an efficient prototype in-line detection system in transmittance mode was designed and evaluated in comparison with an off-line detection system.Data from the years 2019 and 2020 were used for modeling and the external validation data were obtained by the inline detection system in 2021.The wavelength selection methods of changeable size moving window(CSMW),random frog(RF),and competitive adaptive reweighted sampling(CARS)were used to improve the prediction accuracy of partial least squares regression(PLSR)models.The best performance of internal prediction was obtained by CARS-PLSR and the determination coefficient of prediction(),root mean square error of prediction(RMSEP),and residual predictive deviation(RPD)were 0.958,0.204%,and 4.821,respectively.However,all models obtained large prediction biases in external validation.The latent variable updating(LVU)method was proposed to update models and improve the performance in external validation.Ten samples from the external validation set were randomly selected to update the models.Compared with the recalibration method,LVU could effectively modify the original models which matched the SSC range of the external validation set.The CSMW-PLSR models were more robust in external validations.The off-line model with LVU performed best with a root mean square error of validation(RMSEV)of 0.599%and the in-line model with recalibration obtained RMSEV of 0.864%.These results demonstrated the application potential of the transmittance Vis-NIRS for in-line rapid prediction of SSC in pomelos and the modeling and updating methods could be applied to samples with biological variabilities.展开更多
The development of effective and reusable photocatalysts with broad-spectra activity has attracted attention.Herein,we have constructed n-TiO_(2)/p-Ag_(2)O junction on carbon fiber(CF)cloth as an efficient and recycla...The development of effective and reusable photocatalysts with broad-spectra activity has attracted attention.Herein,we have constructed n-TiO_(2)/p-Ag_(2)O junction on carbon fiber(CF)cloth as an efficient and recyclable photocatalyst.With CF cloth as the substrate,TiO_(2) nanorods(length:1-2μm)are prepared by a hydrothermal process,and the in-situ growth of Ag_(2)O nanoparticles(10-20 nm)is then realized by chemical bath deposition route.The flexible CF/TiO_(2)/Ag_(2)O cloth(area:4×4 cm^(2))shows a broad and strong photo-absorption(200-1000 nm).Under the illumination of visible-light(λ>400 nm),CF/TiO_(2)/Ag_(2)O cloth can efficiently eliminate 99.2%rhodamine B(RhB),99.4%acid orange 7(AO7),87.6%bisphenol A(BPA),and 89.5%hexavalent chromium(Cr^(6+))in 100 min,superior to CF/Ag_(2)O cloth(83.5%RhB,60.0%AO7,31.2%BPA and 41.8%Cr^(6+)).In particular,under the NIR-light illumination(980 nm laser),CF/TiO_(2)/Ag_(2)O cloth can remove 70.9%AO7 and 60.0%Cr^(6+) in 100 min,which are significantly higher than those by CF/Ag_(2)O cloth(19.8%AO7 and 18.9%Cr^(6+)).In addition,CF/TiO_(2)/Ag_(2)O cloth(diameter:10 cm),as a filter-membrane,can effectively wipe off 94.4%flowing RhB solution(rate:~1 L h^(−1))at 6th filtering/degrading grade.Thus,CF/TiO_(2)/Ag_(2)O cloth can be used as a Vis-NIR-responded filter-membrane-shaped photocatalyst with high-efficiency for purifying wastewater.展开更多
The narrow bandgap of the low-energy near-infrared(NIR)polymer would lead to overlap between adjacent energy levels,which is a major barrier to the preparation of Vis-NIR polymer bulk hetero-junction(BHJ)photodetector...The narrow bandgap of the low-energy near-infrared(NIR)polymer would lead to overlap between adjacent energy levels,which is a major barrier to the preparation of Vis-NIR polymer bulk hetero-junction(BHJ)photodetectors with small responsivity and photocurrent.In this study,a high-performance lateral inorganic-organic hybrid photodetector was constructed to eliminate this barrier by combining GaN nanowires(GaN-NWs)with PDPP3T:PC61BM-based BHJ.In stage one,high-quality GaN-NWs were synthesized by the catalyst-free CVD method.The mechanism for controlling GaN-NWs morphology by adjusting the NH3 flow rate was revealed.In stage two,the GaN-NWs with large electron mobility were used to accelerate the transfer of photogenerated carriers in the BHJ layer.Finally,compared with the BHJ device,the BHJ/GaN device demonstrated obvious improvements in responsivity and photocurrent at the wavelength between 400 and 1000 nm.The responsivity and photocurrent increased over 20-fold at the NIR band of 800e900 nm.Besides,owing to the energy level gradient effect,the BHJ/GaN device has a response speed of 7.8/<5.0 ms,which increases over three orders of magnitude than that of the GaN-NWs-based device(tr/tf:7.1/10.9 s).Therefore,the novel device structure proposed in this work holds great potential for preparing high-performance Vis-NIR photodetectors.展开更多
Visible and even infrared(IR)light-initiated hot electrons of graphene(Gr)catalysts are a promising driven power for green,safe,and sustainable H2O2 synthesis and organic synthesis without the limitation of bandgap-do...Visible and even infrared(IR)light-initiated hot electrons of graphene(Gr)catalysts are a promising driven power for green,safe,and sustainable H2O2 synthesis and organic synthesis without the limitation of bandgap-dominated narrow light absorption to visible light confronted by conventional photocatalyst.However,the life time of photogenerated hot electrons is too short to be efficiently used for various photocatalytic reactions.Here,we proposed a straightforward method to prolong the lifetime of photogenerated hot electrons from graphene by tuning the Schottky barrier at Gr/rutile interface to facilitate the hot electron injection.The rational design of Gr-coated TiO2 heterojunctions with interface synergy-induced decrease in the formation energy of the rutile phase makes the phase transfer of TiO2 support proceed smoothly and rapidly via ball milling.The optimized Gr/rutile dyad could provide a H2O2 yield of 1.05 mM·g-1·h-1 under visible light irradiation(λ≥400 nm),which is 30 times of the state-of-the-art noble-metal-free titanium oxide-based photocatalyst,and even achieves a H2O2 yield of 0.39 mM·g-1·h-1 on photoexcitation by near-infrared-region light(~800 nm).展开更多
文摘利用野外实时快速获取的土壤光谱进行土壤有机质(SOM)预测与制图是精确农业与土壤遥感制图的必然需要,利用ASD FieldSpec Pro FR野外型光谱仪实时快速获取的光谱数据,去除噪声较大的边缘波段后,进行倒数的对数转换(Log(1/R))为吸收光谱。在分析吸收光谱和光谱指数与SOM关系的基础上,采用偏最小二乘回归法进行SOM的建模预测并借助地统计学方法进行SOM空间变异制图研究。结果表明,建模效果好的指标分别为特征波段(R2=0.91,RPD=3.28),归一化光谱指数(R2=0.90,RPD=3.08),特征波段与3个光谱指数组合(R2=0.87,RPD=2.67),全波段(R2=0.95,RPD=4.36)。光谱指标的克里格制图与实测SOM制图表现出相同的空间变异趋势,不同的指标均达到了较好的预测效果。
文摘【目的】快速、准确地监测土壤有机质对于精准农业的发展具有重要意义。可见光-近红外(visible and near-infrared,Vis-NIR)光谱技术在土壤属性估算、数字化土壤制图等方面应用较为广泛,然而,在田间进行光谱测量,易受土壤含水量(soil moisture,SM)、温度、土壤表面状况等因素的影响,导致光谱信息中包含大量干扰信息,其中,SM变化是影响光谱观测结果最为显著的因素之一。此研究的目的是探讨OSC算法消除其影响,提升Vis-NIR光谱定量估算土壤有机质(soil organic matter,SOM)的精度。【方法】以江汉平原公安县和潜江市为研究区域,采集217份耕层(0—20 cm)土壤样本,进行风干、研磨、过筛等处理,采用重铬酸钾-外加热法测定SOM;将总体样本划分为3个互不重叠的样本集:建模集S^0(122个样本)、训练集S^1(60个样本)、验证集S^2(35个样本);设计SM梯度试验(梯度间隔为4%),在实验室内获取S^1和S^2样本集的9个梯度SM(0%—32%)的土壤光谱数据;分析SM对土壤Vis-NIR光谱反射率的影响,采用外部参数正交化算法(external parameter orthogonalization,EPO)、正交信号校正算法(orthogonal signal correction,OSC)消除SM对土壤光谱的干扰;利用主成分分析(principal component analysis,PCA)的前两个主成分得分和光谱相关系数两种方法检验消除SM干扰前、后的效果;基于偏最小二乘回归(partial least squares regression,PLSR)方法建立EPO和OSC处理前、后的SOM估算模型,利用决定系数(coefficient of determination,R^2)、均方根误差(root mean square error,RMSE)和RPD(the ratio of prediction to deviation)3个指标比较PLSR、EPO-PLSR、OSC-PLSR模型的性能。【结果】土壤Vis-NIR光谱受SM的影响十分明显,随着SM的增加,土壤光谱反射率呈非线性降低趋势。OSC处理前的湿土光谱数据主成分得分散点相对分散,与干土光谱数据主成分得分空间的位置不重叠,不同SM梯度之间的光谱相关系数变化较大;OSC处理后的湿土光谱数据主成分得分空间的位置基本与干土光谱数据相重合,各样本光谱数据之间相似性很高,不同SM梯度之间的光谱相关系数变化较小。9个SM梯度的EPO-PLSR模型的验证平均R^2_(pre)、RPD分别为0.69、1.7。9个SM梯度的OSC-PLSR模型的验证平均R^2_(pre)、RPD分别为0.72、1.89,校正后的OSC-PLSR模型受SM的较小,有效提升SOM估算模型的精度和鲁棒性。【结论】OSC能够消除SM变化对土壤Vis-NIR光谱的影响,可为将来田间原位实时监测SOM信息提供一定的理论支撑。
基金funded by Chongqing Talent Program(CQYC201905009)Chongqing Education Commission(KJZD-K201800502,KJQN201800531)Science Fund for Distinguished Young Scholars of Chongqing(cstc2019jcyjjq X0025)。
文摘Soil moisture is essential for plant growth in terrestrial ecosystems.This study investigated the visible-near infrared(Vis-NIR)spectra of three subgroups of purple soils(calcareous,neutral,and acidic)from western Chongqing,China,containing different water contents.The relationship between soil moisture and spectral reflectivity(R)was analyzed using four spectral transformations,and estimation models were established for estimating the soil moisture content(SMC)of purple soil based on stepwise multiple linear regression(SMLR)and partial least squares regression(PLSR).We found that soil spectra were similar for different moisture contents,with reflectivity decreasing with increasing moisture content and following the order neutral>calcareous>acidic purple soil(at constant moisture content).Three of the four spectral transformations can highlight spectral sensitivity to SMC and significantly improve the correlation between the reflectance spectra and SMC.SMLR and PLSRmethods provide similar prediction accuracy.The PLSR-based model using a first-order reflectivity differential(R?)is more effective for estimating the SMC,and gave coefficient of determination(v2),root mean square errors of validation(RMSEV),and ratio of performance to inter-quartile distance(RPIQ)values of 0.946,1.347,and 6.328,respectively,for the calcareous purple soil,and 0.944,1.818,and 6.569,respectively,for the acidic purple soil.For neutral purple soil,the best prediction was obtained using the SMLR method with R?transformation,yieldingv2,RMSEV and RPIQ values of 0.973,0.888 and 8.791,respectively.In general,PLSR is more suitable than SMLR for estimating the SMC of purple soil.
文摘Soil texture is an indicator of soil physical structure which delivers many ecological functions of soils such as thermal regime, plant growth, and soil quality. However, traditional methods for soil texture measurement are time-consuming and labor-intensive. This study attempts to explore an indirect method for rapid estimating the texture of three subgroups of purple soils (i.e. calcareous, neutral, and acidic). 190 topsoil (0 - 10 cm) samples were collected from sloping croplands in Tongnan and Beibei Districts of Chongqing Municipality in China. Vis-NIR spectrum was measured and processed, and stepwise multiple linear regression (SMLR), partial least squares regression (PLSR), and back propagation neural network (BPNN) models were constructed to inform the soil texture. The clay fractions ranged from 4.40% to 27.12% while sand fractions ranged from 0.34% to 36.57%, hereby soil samples encompass three textural classes (i.e. silt, silt loam, and silty clay loam). For the original spectrum, the texture of calcareous and neutral purple soils was not significantly correlated with spectral reflectance and linear models (SMLR and PLSR) exhibited low prediction accuracy. The correlation coefficients and the goodness-of-fits between soil texture and the transformed spectra of all soil groups increased by continuum-removal (CR), first-order differential (R'), and second-order differential (R") transformations. Among them, the R" had the best performance in terms of improving the correlation coefficients and the goodness-of-fits. For the calcareous purple soil, the SMLR exceeds PLSR and BPNN with a higher coefficient of determination (R<sup>2</sup>) and the ratio of performance to inter-quartile distance (RPIQ) values and lower root mean square error of validation (RMSEV), but for the neutral and acidic purple soils, the PLSR model has a better prediction accuracy. In summary, the linear methods (SMLR and PLSR) are more reliable in estimating the texture of the three purple soil groups when using Vis-NIR spectroscopy inversion.
基金the key research and development projects of Zhejiang province(Grant No.2022C02021).
文摘The aim of this study was in-line,rapid,and non-destructive detection for soluble solid content(SSC)in pomelos using visible and near-infrared spectroscopy(Vis-NIRS).However,the large size and thick rind of pomelo affect the stability of spectral acquisition and the biological variabilities affect the robustness of models.Given these issues,in this study,an efficient prototype in-line detection system in transmittance mode was designed and evaluated in comparison with an off-line detection system.Data from the years 2019 and 2020 were used for modeling and the external validation data were obtained by the inline detection system in 2021.The wavelength selection methods of changeable size moving window(CSMW),random frog(RF),and competitive adaptive reweighted sampling(CARS)were used to improve the prediction accuracy of partial least squares regression(PLSR)models.The best performance of internal prediction was obtained by CARS-PLSR and the determination coefficient of prediction(),root mean square error of prediction(RMSEP),and residual predictive deviation(RPD)were 0.958,0.204%,and 4.821,respectively.However,all models obtained large prediction biases in external validation.The latent variable updating(LVU)method was proposed to update models and improve the performance in external validation.Ten samples from the external validation set were randomly selected to update the models.Compared with the recalibration method,LVU could effectively modify the original models which matched the SSC range of the external validation set.The CSMW-PLSR models were more robust in external validations.The off-line model with LVU performed best with a root mean square error of validation(RMSEV)of 0.599%and the in-line model with recalibration obtained RMSEV of 0.864%.These results demonstrated the application potential of the transmittance Vis-NIRS for in-line rapid prediction of SSC in pomelos and the modeling and updating methods could be applied to samples with biological variabilities.
基金This work was supported by the Fundamental Research Funds for the Central UniversitiesDHU Distinguished Young Professor Program,National Key Research and Development Program of China(2016YFC0400501,2016YFC0400502).
文摘The development of effective and reusable photocatalysts with broad-spectra activity has attracted attention.Herein,we have constructed n-TiO_(2)/p-Ag_(2)O junction on carbon fiber(CF)cloth as an efficient and recyclable photocatalyst.With CF cloth as the substrate,TiO_(2) nanorods(length:1-2μm)are prepared by a hydrothermal process,and the in-situ growth of Ag_(2)O nanoparticles(10-20 nm)is then realized by chemical bath deposition route.The flexible CF/TiO_(2)/Ag_(2)O cloth(area:4×4 cm^(2))shows a broad and strong photo-absorption(200-1000 nm).Under the illumination of visible-light(λ>400 nm),CF/TiO_(2)/Ag_(2)O cloth can efficiently eliminate 99.2%rhodamine B(RhB),99.4%acid orange 7(AO7),87.6%bisphenol A(BPA),and 89.5%hexavalent chromium(Cr^(6+))in 100 min,superior to CF/Ag_(2)O cloth(83.5%RhB,60.0%AO7,31.2%BPA and 41.8%Cr^(6+)).In particular,under the NIR-light illumination(980 nm laser),CF/TiO_(2)/Ag_(2)O cloth can remove 70.9%AO7 and 60.0%Cr^(6+) in 100 min,which are significantly higher than those by CF/Ag_(2)O cloth(19.8%AO7 and 18.9%Cr^(6+)).In addition,CF/TiO_(2)/Ag_(2)O cloth(diameter:10 cm),as a filter-membrane,can effectively wipe off 94.4%flowing RhB solution(rate:~1 L h^(−1))at 6th filtering/degrading grade.Thus,CF/TiO_(2)/Ag_(2)O cloth can be used as a Vis-NIR-responded filter-membrane-shaped photocatalyst with high-efficiency for purifying wastewater.
文摘The narrow bandgap of the low-energy near-infrared(NIR)polymer would lead to overlap between adjacent energy levels,which is a major barrier to the preparation of Vis-NIR polymer bulk hetero-junction(BHJ)photodetectors with small responsivity and photocurrent.In this study,a high-performance lateral inorganic-organic hybrid photodetector was constructed to eliminate this barrier by combining GaN nanowires(GaN-NWs)with PDPP3T:PC61BM-based BHJ.In stage one,high-quality GaN-NWs were synthesized by the catalyst-free CVD method.The mechanism for controlling GaN-NWs morphology by adjusting the NH3 flow rate was revealed.In stage two,the GaN-NWs with large electron mobility were used to accelerate the transfer of photogenerated carriers in the BHJ layer.Finally,compared with the BHJ device,the BHJ/GaN device demonstrated obvious improvements in responsivity and photocurrent at the wavelength between 400 and 1000 nm.The responsivity and photocurrent increased over 20-fold at the NIR band of 800e900 nm.Besides,owing to the energy level gradient effect,the BHJ/GaN device has a response speed of 7.8/<5.0 ms,which increases over three orders of magnitude than that of the GaN-NWs-based device(tr/tf:7.1/10.9 s).Therefore,the novel device structure proposed in this work holds great potential for preparing high-performance Vis-NIR photodetectors.
基金supported by the National Natural Science Foundation of China(Nos.21737002,21931005,21720102002,and 22071146)Shanghai Science and Technology Committee(Nos.19JC1412600 and 20520711600)the SJTU-MPI partner group.
文摘Visible and even infrared(IR)light-initiated hot electrons of graphene(Gr)catalysts are a promising driven power for green,safe,and sustainable H2O2 synthesis and organic synthesis without the limitation of bandgap-dominated narrow light absorption to visible light confronted by conventional photocatalyst.However,the life time of photogenerated hot electrons is too short to be efficiently used for various photocatalytic reactions.Here,we proposed a straightforward method to prolong the lifetime of photogenerated hot electrons from graphene by tuning the Schottky barrier at Gr/rutile interface to facilitate the hot electron injection.The rational design of Gr-coated TiO2 heterojunctions with interface synergy-induced decrease in the formation energy of the rutile phase makes the phase transfer of TiO2 support proceed smoothly and rapidly via ball milling.The optimized Gr/rutile dyad could provide a H2O2 yield of 1.05 mM·g-1·h-1 under visible light irradiation(λ≥400 nm),which is 30 times of the state-of-the-art noble-metal-free titanium oxide-based photocatalyst,and even achieves a H2O2 yield of 0.39 mM·g-1·h-1 on photoexcitation by near-infrared-region light(~800 nm).
