Investigation on the bright and stable upconversion(UC)phosphors with multicolor emissions is fundamental and significant for the frontier applications of display and tempe rature probe.He re,dive rse emitting colors ...Investigation on the bright and stable upconversion(UC)phosphors with multicolor emissions is fundamental and significant for the frontier applications of display and tempe rature probe.He re,dive rse emitting colors with blue,cyan and yellowish green,which are caused by the energy transfer and crossrelaxation processes,are obtained by altering Er^3+,Tm^3+and Yb^3+concentrations in Er3+singly,Er^3+-Tm^3+-Yb^3+co-and tri-doped double perovskite La2ZnTiO6(LZT)phosphors synthesized by a simple solid-state reaction.In addition,excellent infrared emission at 801 nm located at"first biological windo w"is collected in Tm^3+-Yb^3+co-doped phosphors.Meanwhile,the temperature sensing properties based on the thermally coupled levels((^2H11/2)/(^4S3/2))of Er3+ions were analyzed from 298 to 573 K of LZT:0.15 Er^3+/0.10 Yb^3+phosphor,demonstrating that the maximal sensitivity value is about56×10^-4 K^-1 at 448 K.All these results imply that this kind of UC material has potential applications in display,bioimaging and optical device.展开更多
Recently,electric vehicles(EVs)have been widely used under the call of green travel and environmental protection,and diverse requirements for charging are also increasing gradually.In order to ensure the authenticity ...Recently,electric vehicles(EVs)have been widely used under the call of green travel and environmental protection,and diverse requirements for charging are also increasing gradually.In order to ensure the authenticity and privacy of charging information interaction,blockchain technology is proposed and applied in charging station billing systems.However,there are some issues in blockchain itself,including lower computing efficiency of the nodes and higher energy consumption in the consensus process.To handle the above issues,in this paper,combining blockchain and mobile edge computing(MEC),we develop a reliable billing data transmission scheme to improve the computing capacity of nodes and reduce the energy consumption of the consensus process.By jointly optimizing the primary and replica nodes offloading decisions,block size and block interval,the transaction throughput of the blockchain system is maximized,as well as the latency and energy consumption of the system are minimized.Moreover,we formulate the joint optimization problem as a Markov decision process(MDP).To tackle the dynamic and continuity of the system state,the reinforcement learning(RL)is introduced to solve the MDP problem.Finally,simulation results demonstrate that the performance improvement of the proposed scheme through comparison with other existing schemes.展开更多
A series of Sm^(3+)-doped La_(3)Si_(6)N_(11)phosphor materials we re synthesized by a high temperature solid-state reaction method.The crystal structure,micro structure,photoluminescence properties,decay curves as wel...A series of Sm^(3+)-doped La_(3)Si_(6)N_(11)phosphor materials we re synthesized by a high temperature solid-state reaction method.The crystal structure,micro structure,photoluminescence properties,decay curves as well as thermal quenching properties of the as-prepared phosphors were investigated systematically.The excitation spectra contain a wide asymmetric band below 350 nm originating from the host absorption,several sharp excitation peaks in the range of 300-550 nm corresponding to f-f transition of Sm^(3+).Under the excitation of 369 and 414 nm light,the phosphors exhibit strong narrow-band orangered emission peaked at 605 nm.The average decay time of La_(2.99)Si_(6)N_(11):0.01 Sm^(3+)sample is fitted to be0.38 ms and the CIE coordinates were calculated to be(0.6105,0.3833).For water resistance,La_(3)Si_(6)N_(11):Sm^(3+)is better than K_(2)SiF_(6):Mn^(4+)phosphor.After soaking in deionized water for 300 min,the La_(3)Si_(6)N_(11):Sm^(3+)sample retains approximately 80%of its initial relative emission intensity.When the temperature rises to 423 K(150℃),the emission intensity of La_(2.99)Si_(6)N_(11):0.01 Sm^(3+)sample remains 85%in co mparison to that of room tempe rature.The activation energy was calculated to be 0.63253 eV,which is higher than those of Sm^(3+)-activated oxide phosphors,indicating that the phosphor has relatively good thermal stability.展开更多
As a cyan-emitting oxonitridosilicate phosphor,BaSi_(2)O_(2)N_(2):Eu^(2+)can be used as a competent cyan compensator to improve the color rendering index of white light-emitting diodes(WLEDs).However,low luminescence ...As a cyan-emitting oxonitridosilicate phosphor,BaSi_(2)O_(2)N_(2):Eu^(2+)can be used as a competent cyan compensator to improve the color rendering index of white light-emitting diodes(WLEDs).However,low luminescence efficiency and poor thermal stability of this type of phosphor seriously suppress its actual application in full-spectrum lighting.The replacements of Ba^(2+)by Lu^(3+)and Ba^(2+)-Si^(4+)by Lu^(3+)-Al^(3+)can greatly increase the luminescence intensity and improve the thermal stability at the same time.With Lu^(3+)doping,the internal quantum efficiencyηIQE Ba_(0.925)Si_(2)O_(2)N_(2):0.03 Eu^(2+),0.045 Lu^(3+)is 24.08%higher than that of Ba_(0.97)Si_(2)O_(2)N_(2):0.03 Eu^(2+).After Al^(3+)co-doping,theηIQE is further increased by 10.31%compared to Ba_(0.925)Si_(2)O_(2)N_(2):0.03 Eu^(2+),0.045 Lu^(3+).When the temperature rises to 473 K,the luminescence intensity of Ba_(0.925)Si_(2)O_(2)N_(2):0.03 Eu^(2+),0.045 Lu^(3+)maintains 62.32%of that at room temperature,which increases by 17.35%in relative to the Ba_(0.97)Si_(2)O_(2)N_(2):0.03 Eu^(2+),while the luminescence intensity of Ba_(0.925)Si_(1.97)O_(2)N_(2):0.03 Eu^(2+),0.045 Lu^(3+),0.03 Al^(3+)keeps 73.87%of the initial value,which increases by18.52%compared to Ba_(0.925)Si_(2)O_(2)N_(2):0.03 Eu^(2+),0.045 Lu^(3+).The mechanisms for luminescence and thermal stability improvement are proposed.The Ba_(0.925)Si_(1.97)O_(2)N_(2):0.03 Eu^(2+),0.045 Lu^(3+),0.03 Al^(3+)cyan phosphor,Y3 Al5 O12:Ce3+yellow phosphor and CaAlSiN3:Eu^(2+)red phosphor are mixed thoroughly and coated on a blue LED(450 nm)to assemble a WLED.The WLED demonstrates a color rendering index(Ra)of 97.1 at150 mA,and the R1-R15 values are all above 90.The results indicate that as an effective cyan compensator in WLED,the BaSi_(2)O_(2)N_(2):Eu^(2+),Lu^(3+),Al^(3+)phosphor has great application prospect in the field of full-spectrum lighting.展开更多
It is well known that cyan-emitting phosphors play a very important role in full-spectrum white LEDs.A large number of cyan-emitting phosphors have been reported in the past few years,however,most of them can only be ...It is well known that cyan-emitting phosphors play a very important role in full-spectrum white LEDs.A large number of cyan-emitting phosphors have been reported in the past few years,however,most of them can only be effectively excited by near-ultraviolet light.There are very few cyan-emitting phosphors that can be intensively excited by blue light(440 and 470 nm).Here,a novel blue-light excitable cyan-emitting phosphor BaLu_(1.95)Ce_(0.05)Al_(2)Ga_(2)SiO_(12)with excellent performance is reported.The cyan phosphor has a cubic structure in space group Ia3^(-)d with a=1.205379(3)nm,which can be easily obtained through a solid-state reaction pathway.The emission peak of the cyan phosphor is located at 500 nm and its internal quantum efficiency is as high as 90.01%when excited at 455 nm at 25℃.The cyan phosphor exhibits superior resistance against thermal quenching of luminescence,and its intensity at 125℃is as strong as 92.14%of the intensity at room temperature.Meanwhile,it also shows an outstanding resistance against water,where its luminescence intensity is hardly changed after being immersed in pure water for 528 h.The white LED lamp prepared by employing the obtained BaLu_(1.95)-Ce_(0.05)Al_(2)Ga_(2)SiO_(12)as cyan phosphor displays remarkable optical properties with CCT=4441 K,Ra=93.7,CRI=90.4 and CIE 1931(x,y)as(x=0.3648,y=0.3752).The experimental results demonstrate that BaLu_(1.95)Ce_(0.05)Al_(2)Ga_(2)SiO_(12)is a promising cyan-emitting phosphor with great application potential in full-spectrum white LEDs.展开更多
National Auditing is established to sustain the Superstructure and supervise the economic order. In this article, the relative content and basic characters of Legislative Model National Auditing will be analyzed and e...National Auditing is established to sustain the Superstructure and supervise the economic order. In this article, the relative content and basic characters of Legislative Model National Auditing will be analyzed and evaluated. Some apocalypses which are useful to the auditing reformation of our country hope to find.展开更多
Transverse mode instability(TMI),induced by nonlinear thermal-optical coupling,poses a primary challenge for the power scaling of fiber lasers.In the fiber oscillator,a sealed resonant cavity,TMI could become particul...Transverse mode instability(TMI),induced by nonlinear thermal-optical coupling,poses a primary challenge for the power scaling of fiber lasers.In the fiber oscillator,a sealed resonant cavity,TMI could become particularly complex due to the mode competition during the laser oscillation.While traditional theories of TMI predominantly address two-mode coupling,this paper explores the TMI phenomena in few-mode fiber oscillators utilizing a holistic approach that includes solving steady-state thermal-optic coupling equations.The simulation shows that there is a non-monotonic correlation between bending loss and the TMI threshold,which is contrary to the monotonic associations suggested by two-mode interaction theory.When one high-order mode experiences net gain,fluctuations of the TMI threshold would occur,leading to the amplification of a new mode within the uncoupled frequency region,thus affecting the gain saturation.By designing the linewidth of a low-reflection grating(LR),the modal power management in the uncoupled frequency domain can be achieved.An excessively broad LR linewidth exacerbates mode coupling within the shared frequency region,thus exacerbating TMI.To validate the theoretical simulation,we carefully fabricated LRs and optimized the fiber coiling to elevate the TMI threshold.Through careful optimization of LR linewidth and bending radii,we achieved a record-breaking laser output of 10.07kW using a monolithic fiber oscillator,with no observable evidence of TMI.Our work demonstrates that modal power redistribution in independent frequency domains offers a novel approach to mitigating TMI in high-power fiber lasers.Additionally,it provides new insights into mode decoupling strategies pertinent to fiber communications.展开更多
The development of high-efficiency perovskite solar cells(PSCs)demands a comprehensive control of multi-scale factors that influence device performance.In recent years,artificial intelligence(AI),represented by machin...The development of high-efficiency perovskite solar cells(PSCs)demands a comprehensive control of multi-scale factors that influence device performance.In recent years,artificial intelligence(AI),represented by machine learning(ML),has rapidly become a key tool for the design and optimization of PSCs.However,current ML models often oversimplify the design of PSCs at the device level,making it difficult to capture the complexity of their multi-scale features.Moreover,they are constrained by relatively small and specialized datasets,which limits their generalizability across diverse device architectures and fabrication methods.In this work,we developed a full-process AI framework based on over 20,000 experimentally measured PSC samples and approximately 260 multi-scale features.This framework offers significant advantages in both sample diversity and feature richness.It combines material selection,fabrication processes,and environmental factors to provide a more accurate and comprehensive optimization solution for PSCs.We addressed challenges from data diversity and heterogeneity through feature engineering and model training,which results in a highly generalizable PSC performance prediction model with comparable prediction error to small-scale models.The framework enables precise optimization of specific features for any PSCs,and provides valuable insights for designing high-performance photovoltaic devices.展开更多
The demand for in-situ detection of latent fingerprints(LFPs)in ways of high sensitivity,high selectivity,high contrast,low cost and user-friendly is still urgent.To overcome this challenge,a moisture-stable,red-emitt...The demand for in-situ detection of latent fingerprints(LFPs)in ways of high sensitivity,high selectivity,high contrast,low cost and user-friendly is still urgent.To overcome this challenge,a moisture-stable,red-emitting fluoride phosphor K_(3)AlF_(6):Mn^(4+)(KAF:Mn^(4+))with an organic hydrophobic skin was prepared.The phosphor has a uniform and superfine morphology with excellent luminescence properties.More importantly,this non-ultraviolet(UV)or non-near infrared(NIR)induced phosphor was proved to be an ideal fluorescent label for LFP imaging,which is both friendly for touch DNA analysis and compatible to forensic light sources.The well-defined ridge details with little background interference on various surfaces were presented by the oleic acid(OA)modified KAF:Mn^(4+)(KAF:Mn^(4+)-OA)phosphor in few seconds using the powder dusting method.To confirm the high selectivity of KAF:Mn^(4+)-OA for LFP imaging,an efficient quantitative evaluation method is proposed with the aid of ImageJ&Origin software.Due to the superiority of the Mn^(4+)-doped fluoride for the rapid imaging of LFPs in terms of lowcost,high compatibility and good availability,it is expected to be a promising candidate for forensic science as well as fluorescence imaging in other fields instead of rare earth luminescent materials.展开更多
Convolutional neural networks(CNNs)have been widely used for gas-insulated switchgear(GIS)partial discharge(PD)pattern recognition due to their powerful feature extraction ability.However,there is commonly a scarcity ...Convolutional neural networks(CNNs)have been widely used for gas-insulated switchgear(GIS)partial discharge(PD)pattern recognition due to their powerful feature extraction ability.However,there is commonly a scarcity of fault samples due to low insulation failure rate of GIS equipment,which degrades the diagnostic performance of these CNN networks when directly applied to small and unbalanced datasets.Therefore,we propose a novel auxiliary classifier generative adversarial network for GIS PD pattern recognition for small and unbalanced samples.First,we propose using synchrosqueezed wavelet transform to extract time-frequency characteristics of PD pulses and obtain a time-frequency image with high energy aggregation and timefrequency distribution rate.Then,we propose an improved generative adversarial network with an auxiliary classier and self-attention mechanism,which can generate highquality PD samples for situations with few classes.Experiments show that our proposed method can reach 95.75%recognition accuracy for small datasets,which is the highest among several comparable methods.Furthermore,the proposed method has excellent and stable recognition performance for various unbalanced datasets.展开更多
Understanding gene regulatory networks(GRNs)is essential for improving maize yield and quality through molecular breeding approaches.The lack of comprehensive transcription factor(TF)-DNA interaction data has hindered...Understanding gene regulatory networks(GRNs)is essential for improving maize yield and quality through molecular breeding approaches.The lack of comprehensive transcription factor(TF)-DNA interaction data has hindered accurate GRN predictions,limiting our insight into the regulatory mechanisms.In this study,we performed large-scale profiling of maize TF binding sites.We obtained and collected reliable binding profiles for 513 TFs,identified 394,136 binding sites,and constructed an accuracy-enhanced maize GRN(mGRN+)by integrating chromatin accessibility and gene expression data.The mGRN+comprises 397,699 regulatory relationships.We further divided the mGRN+into multiple modules across six major tis-sues.Using machine-learning algorithms,we optimized the mGRN+to improve the prediction accuracy of gene functions and key regulators.Through independent genetic validation experiments,we further confirmed the reliability of these predictions.This work provides the largest collection of experimental TF binding sites in maize and highly optimized regulatory networks,which serve as valuable resources forstudyingmaize genefunctionand crop improvement.展开更多
基金supported by the National Natural Science Foundation of China(11464017,11864015)the Scientific Research Foundation for Universities from the Education Bureau of Jiangxi Province(GJJ170490)+1 种基金Foundation of Natural Science Funds for Distinguished Young Scholar of Jiangxi Province(20171BCB23064)the Science and Technology Major Project of Jiangxi Province(20165ABC28010).
文摘Investigation on the bright and stable upconversion(UC)phosphors with multicolor emissions is fundamental and significant for the frontier applications of display and tempe rature probe.He re,dive rse emitting colors with blue,cyan and yellowish green,which are caused by the energy transfer and crossrelaxation processes,are obtained by altering Er^3+,Tm^3+and Yb^3+concentrations in Er3+singly,Er^3+-Tm^3+-Yb^3+co-and tri-doped double perovskite La2ZnTiO6(LZT)phosphors synthesized by a simple solid-state reaction.In addition,excellent infrared emission at 801 nm located at"first biological windo w"is collected in Tm^3+-Yb^3+co-doped phosphors.Meanwhile,the temperature sensing properties based on the thermally coupled levels((^2H11/2)/(^4S3/2))of Er3+ions were analyzed from 298 to 573 K of LZT:0.15 Er^3+/0.10 Yb^3+phosphor,demonstrating that the maximal sensitivity value is about56×10^-4 K^-1 at 448 K.All these results imply that this kind of UC material has potential applications in display,bioimaging and optical device.
基金in part by the National Natural Science Foundation of China under Grant 61901011in part by the Foundation of Beijing Municipal Commission of Education under Grant KM202110005021 and KM202010005017.
文摘Recently,electric vehicles(EVs)have been widely used under the call of green travel and environmental protection,and diverse requirements for charging are also increasing gradually.In order to ensure the authenticity and privacy of charging information interaction,blockchain technology is proposed and applied in charging station billing systems.However,there are some issues in blockchain itself,including lower computing efficiency of the nodes and higher energy consumption in the consensus process.To handle the above issues,in this paper,combining blockchain and mobile edge computing(MEC),we develop a reliable billing data transmission scheme to improve the computing capacity of nodes and reduce the energy consumption of the consensus process.By jointly optimizing the primary and replica nodes offloading decisions,block size and block interval,the transaction throughput of the blockchain system is maximized,as well as the latency and energy consumption of the system are minimized.Moreover,we formulate the joint optimization problem as a Markov decision process(MDP).To tackle the dynamic and continuity of the system state,the reinforcement learning(RL)is introduced to solve the MDP problem.Finally,simulation results demonstrate that the performance improvement of the proposed scheme through comparison with other existing schemes.
基金the Doctoral Scientific Research Foundation of Jiangxi University of Science and Technology(3401223311)Science and Technology Research Project of Jiangxi Provincial Education Department(GJJ160636)+1 种基金National Natural Science Foundation of China(51962005)Natural Science Foundation of Jiangxi Province of China(20192BAB206010)。
文摘A series of Sm^(3+)-doped La_(3)Si_(6)N_(11)phosphor materials we re synthesized by a high temperature solid-state reaction method.The crystal structure,micro structure,photoluminescence properties,decay curves as well as thermal quenching properties of the as-prepared phosphors were investigated systematically.The excitation spectra contain a wide asymmetric band below 350 nm originating from the host absorption,several sharp excitation peaks in the range of 300-550 nm corresponding to f-f transition of Sm^(3+).Under the excitation of 369 and 414 nm light,the phosphors exhibit strong narrow-band orangered emission peaked at 605 nm.The average decay time of La_(2.99)Si_(6)N_(11):0.01 Sm^(3+)sample is fitted to be0.38 ms and the CIE coordinates were calculated to be(0.6105,0.3833).For water resistance,La_(3)Si_(6)N_(11):Sm^(3+)is better than K_(2)SiF_(6):Mn^(4+)phosphor.After soaking in deionized water for 300 min,the La_(3)Si_(6)N_(11):Sm^(3+)sample retains approximately 80%of its initial relative emission intensity.When the temperature rises to 423 K(150℃),the emission intensity of La_(2.99)Si_(6)N_(11):0.01 Sm^(3+)sample remains 85%in co mparison to that of room tempe rature.The activation energy was calculated to be 0.63253 eV,which is higher than those of Sm^(3+)-activated oxide phosphors,indicating that the phosphor has relatively good thermal stability.
基金Project supported by the National Natural Science Foundation of China(51962005)the Cultivation Project of the State Key Laboratory of Green Development and High-value Utilization of Ionic Rare Earth Resources in Jiangxi Province(20194AFD44003)+3 种基金the Key Research and Development Plan Project of Jiangxi Province(20192ACB50021)Natural Science Foundation of Jiangxi Province(20192BAB206010)Key Special Project of Science and Technology to Help Economy in Jiangxi Province([2020]87)Youth Jinggang Scholars Program in Jiangxi Province([2018]82)。
文摘As a cyan-emitting oxonitridosilicate phosphor,BaSi_(2)O_(2)N_(2):Eu^(2+)can be used as a competent cyan compensator to improve the color rendering index of white light-emitting diodes(WLEDs).However,low luminescence efficiency and poor thermal stability of this type of phosphor seriously suppress its actual application in full-spectrum lighting.The replacements of Ba^(2+)by Lu^(3+)and Ba^(2+)-Si^(4+)by Lu^(3+)-Al^(3+)can greatly increase the luminescence intensity and improve the thermal stability at the same time.With Lu^(3+)doping,the internal quantum efficiencyηIQE Ba_(0.925)Si_(2)O_(2)N_(2):0.03 Eu^(2+),0.045 Lu^(3+)is 24.08%higher than that of Ba_(0.97)Si_(2)O_(2)N_(2):0.03 Eu^(2+).After Al^(3+)co-doping,theηIQE is further increased by 10.31%compared to Ba_(0.925)Si_(2)O_(2)N_(2):0.03 Eu^(2+),0.045 Lu^(3+).When the temperature rises to 473 K,the luminescence intensity of Ba_(0.925)Si_(2)O_(2)N_(2):0.03 Eu^(2+),0.045 Lu^(3+)maintains 62.32%of that at room temperature,which increases by 17.35%in relative to the Ba_(0.97)Si_(2)O_(2)N_(2):0.03 Eu^(2+),while the luminescence intensity of Ba_(0.925)Si_(1.97)O_(2)N_(2):0.03 Eu^(2+),0.045 Lu^(3+),0.03 Al^(3+)keeps 73.87%of the initial value,which increases by18.52%compared to Ba_(0.925)Si_(2)O_(2)N_(2):0.03 Eu^(2+),0.045 Lu^(3+).The mechanisms for luminescence and thermal stability improvement are proposed.The Ba_(0.925)Si_(1.97)O_(2)N_(2):0.03 Eu^(2+),0.045 Lu^(3+),0.03 Al^(3+)cyan phosphor,Y3 Al5 O12:Ce3+yellow phosphor and CaAlSiN3:Eu^(2+)red phosphor are mixed thoroughly and coated on a blue LED(450 nm)to assemble a WLED.The WLED demonstrates a color rendering index(Ra)of 97.1 at150 mA,and the R1-R15 values are all above 90.The results indicate that as an effective cyan compensator in WLED,the BaSi_(2)O_(2)N_(2):Eu^(2+),Lu^(3+),Al^(3+)phosphor has great application prospect in the field of full-spectrum lighting.
基金Project supported by the National Natural Science Foundation of China(11864015,51962005)the Scientific Research Foundation for Universities from the Education Bureau of Jiangxi Province of China(GJJ170490,GJJ180480)。
文摘It is well known that cyan-emitting phosphors play a very important role in full-spectrum white LEDs.A large number of cyan-emitting phosphors have been reported in the past few years,however,most of them can only be effectively excited by near-ultraviolet light.There are very few cyan-emitting phosphors that can be intensively excited by blue light(440 and 470 nm).Here,a novel blue-light excitable cyan-emitting phosphor BaLu_(1.95)Ce_(0.05)Al_(2)Ga_(2)SiO_(12)with excellent performance is reported.The cyan phosphor has a cubic structure in space group Ia3^(-)d with a=1.205379(3)nm,which can be easily obtained through a solid-state reaction pathway.The emission peak of the cyan phosphor is located at 500 nm and its internal quantum efficiency is as high as 90.01%when excited at 455 nm at 25℃.The cyan phosphor exhibits superior resistance against thermal quenching of luminescence,and its intensity at 125℃is as strong as 92.14%of the intensity at room temperature.Meanwhile,it also shows an outstanding resistance against water,where its luminescence intensity is hardly changed after being immersed in pure water for 528 h.The white LED lamp prepared by employing the obtained BaLu_(1.95)-Ce_(0.05)Al_(2)Ga_(2)SiO_(12)as cyan phosphor displays remarkable optical properties with CCT=4441 K,Ra=93.7,CRI=90.4 and CIE 1931(x,y)as(x=0.3648,y=0.3752).The experimental results demonstrate that BaLu_(1.95)Ce_(0.05)Al_(2)Ga_(2)SiO_(12)is a promising cyan-emitting phosphor with great application potential in full-spectrum white LEDs.
文摘National Auditing is established to sustain the Superstructure and supervise the economic order. In this article, the relative content and basic characters of Legislative Model National Auditing will be analyzed and evaluated. Some apocalypses which are useful to the auditing reformation of our country hope to find.
基金support from the National Natural Science Foundation of China(NSFC)(62405373,11974427)the Science and Technology Innovation Program of Hunan Province(2021RC4027).
文摘Transverse mode instability(TMI),induced by nonlinear thermal-optical coupling,poses a primary challenge for the power scaling of fiber lasers.In the fiber oscillator,a sealed resonant cavity,TMI could become particularly complex due to the mode competition during the laser oscillation.While traditional theories of TMI predominantly address two-mode coupling,this paper explores the TMI phenomena in few-mode fiber oscillators utilizing a holistic approach that includes solving steady-state thermal-optic coupling equations.The simulation shows that there is a non-monotonic correlation between bending loss and the TMI threshold,which is contrary to the monotonic associations suggested by two-mode interaction theory.When one high-order mode experiences net gain,fluctuations of the TMI threshold would occur,leading to the amplification of a new mode within the uncoupled frequency region,thus affecting the gain saturation.By designing the linewidth of a low-reflection grating(LR),the modal power management in the uncoupled frequency domain can be achieved.An excessively broad LR linewidth exacerbates mode coupling within the shared frequency region,thus exacerbating TMI.To validate the theoretical simulation,we carefully fabricated LRs and optimized the fiber coiling to elevate the TMI threshold.Through careful optimization of LR linewidth and bending radii,we achieved a record-breaking laser output of 10.07kW using a monolithic fiber oscillator,with no observable evidence of TMI.Our work demonstrates that modal power redistribution in independent frequency domains offers a novel approach to mitigating TMI in high-power fiber lasers.Additionally,it provides new insights into mode decoupling strategies pertinent to fiber communications.
基金supported by the National Natural Science Foundation of China(52302333 to Bai Y,52373233 to Sun Y)the SIAT International Joint Lab Project(E3G113 to Sun Y)+1 种基金the Shenzhen Science and Technology Program(KQTD20221101093647058 to Bai Y and Sun Y,Shenzhen KJZD20231025152759001 to Bai Y)the Guangdong Basic and Applied Basic Research Foundation(2023A1515012788 to Bai Y,2024A1515010679 to Sun Y).
文摘The development of high-efficiency perovskite solar cells(PSCs)demands a comprehensive control of multi-scale factors that influence device performance.In recent years,artificial intelligence(AI),represented by machine learning(ML),has rapidly become a key tool for the design and optimization of PSCs.However,current ML models often oversimplify the design of PSCs at the device level,making it difficult to capture the complexity of their multi-scale features.Moreover,they are constrained by relatively small and specialized datasets,which limits their generalizability across diverse device architectures and fabrication methods.In this work,we developed a full-process AI framework based on over 20,000 experimentally measured PSC samples and approximately 260 multi-scale features.This framework offers significant advantages in both sample diversity and feature richness.It combines material selection,fabrication processes,and environmental factors to provide a more accurate and comprehensive optimization solution for PSCs.We addressed challenges from data diversity and heterogeneity through feature engineering and model training,which results in a highly generalizable PSC performance prediction model with comparable prediction error to small-scale models.The framework enables precise optimization of specific features for any PSCs,and provides valuable insights for designing high-performance photovoltaic devices.
基金financially supported by the National Natural Science Foundation of China(51962005)China Scholarship Council(201908505044)+6 种基金the cultivation project of the State Key Laboratory of Green Development and High-value Utilization of Ionic Rare Earth Resources in Jiangxi Province(20194AFD44003)Natural Science Foundation of Jiangxi Province(20192BAB206010)Scientific and Technological Project of Chongqing Education Commission(KJZD-M202000301,KJZD-K201800301)Science and Technology Program of Ganzhou city[2017]179the Youth Jinggang Scholars Program in Jiangxi Province[2018]82Key Program of Southwest University of Political Science and Law(2018XZZD-07,2019XZXS-207)Postgraduate Innovation Special Fund Project of Jiangxi Province(YC2019-S294).
文摘The demand for in-situ detection of latent fingerprints(LFPs)in ways of high sensitivity,high selectivity,high contrast,low cost and user-friendly is still urgent.To overcome this challenge,a moisture-stable,red-emitting fluoride phosphor K_(3)AlF_(6):Mn^(4+)(KAF:Mn^(4+))with an organic hydrophobic skin was prepared.The phosphor has a uniform and superfine morphology with excellent luminescence properties.More importantly,this non-ultraviolet(UV)or non-near infrared(NIR)induced phosphor was proved to be an ideal fluorescent label for LFP imaging,which is both friendly for touch DNA analysis and compatible to forensic light sources.The well-defined ridge details with little background interference on various surfaces were presented by the oleic acid(OA)modified KAF:Mn^(4+)(KAF:Mn^(4+)-OA)phosphor in few seconds using the powder dusting method.To confirm the high selectivity of KAF:Mn^(4+)-OA for LFP imaging,an efficient quantitative evaluation method is proposed with the aid of ImageJ&Origin software.Due to the superiority of the Mn^(4+)-doped fluoride for the rapid imaging of LFPs in terms of lowcost,high compatibility and good availability,it is expected to be a promising candidate for forensic science as well as fluorescence imaging in other fields instead of rare earth luminescent materials.
文摘Convolutional neural networks(CNNs)have been widely used for gas-insulated switchgear(GIS)partial discharge(PD)pattern recognition due to their powerful feature extraction ability.However,there is commonly a scarcity of fault samples due to low insulation failure rate of GIS equipment,which degrades the diagnostic performance of these CNN networks when directly applied to small and unbalanced datasets.Therefore,we propose a novel auxiliary classifier generative adversarial network for GIS PD pattern recognition for small and unbalanced samples.First,we propose using synchrosqueezed wavelet transform to extract time-frequency characteristics of PD pulses and obtain a time-frequency image with high energy aggregation and timefrequency distribution rate.Then,we propose an improved generative adversarial network with an auxiliary classier and self-attention mechanism,which can generate highquality PD samples for situations with few classes.Experiments show that our proposed method can reach 95.75%recognition accuracy for small datasets,which is the highest among several comparable methods.Furthermore,the proposed method has excellent and stable recognition performance for various unbalanced datasets.
基金supported by the Biological Breeding-Major Projects(2023ZD0403005)the National Natural Science Foundation of China(32372123,32301846)+1 种基金the National Key Research and Development Program of China(2023YFF1000400)supported by the University of Arizona College of Agriculture,Life and Environmental Sciences,and the USDA.
文摘Understanding gene regulatory networks(GRNs)is essential for improving maize yield and quality through molecular breeding approaches.The lack of comprehensive transcription factor(TF)-DNA interaction data has hindered accurate GRN predictions,limiting our insight into the regulatory mechanisms.In this study,we performed large-scale profiling of maize TF binding sites.We obtained and collected reliable binding profiles for 513 TFs,identified 394,136 binding sites,and constructed an accuracy-enhanced maize GRN(mGRN+)by integrating chromatin accessibility and gene expression data.The mGRN+comprises 397,699 regulatory relationships.We further divided the mGRN+into multiple modules across six major tis-sues.Using machine-learning algorithms,we optimized the mGRN+to improve the prediction accuracy of gene functions and key regulators.Through independent genetic validation experiments,we further confirmed the reliability of these predictions.This work provides the largest collection of experimental TF binding sites in maize and highly optimized regulatory networks,which serve as valuable resources forstudyingmaize genefunctionand crop improvement.
