Mini-LED backlight has emerged as a promising technology for high performance LCDs,yet the massive detection of dead pixels and precise LEDs placement are constrained by the miniature scale of the Mini-LEDs.The high-r...Mini-LED backlight has emerged as a promising technology for high performance LCDs,yet the massive detection of dead pixels and precise LEDs placement are constrained by the miniature scale of the Mini-LEDs.The high-resolution network(Hrnet)with mixed dilated convolution and dense upsampling convolution(MDC-DUC)module and a residual global context attention(RGCA)module has been proposed to detect the quality of vehicular Mini-LED backlights.The proposed model outperforms the baseline networks of Unet,Pspnet,Deeplabv3+,and Hrnet,with a mean intersection over union(Miou)of 86.91%.Furthermore,compared to the four baseline detection networks,our proposed model has a lower root-mean-square error(RMSE)when analyzing the position and defective count of Mini-LEDs in the prediction map by canny algorithm.This work incorporates deep learning to support production lines improve quality of Mini-LED backlights.展开更多
Mini-LED backlights,combining color conversion materials with blue mini-LED chips,promise traditional liquid crystal displays(LCDs)with higher luminance,better contrast,and a wider color gamut.However,as color convers...Mini-LED backlights,combining color conversion materials with blue mini-LED chips,promise traditional liquid crystal displays(LCDs)with higher luminance,better contrast,and a wider color gamut.However,as color conversion materials,quantum dots(QDs)are toxic and unstable,whereas commercially available inorganic phosphors are too big in size to combine with small mini-LED chips and also have strong size-dependence of quantum efficiency(QE)and reliability.In this work,we prepare fine-grained Sr_(2)Si_(5)N_(8):Eu^(2+)-based red phosphors with high efficiency and stability by treating commercially available phosphors with ball milling,centrifuging,and acid washing.The particle size of phosphors can be easily controlled by milling speed,and the phosphors with a size varying from 3.5 to 0.7 mm are thus obtained.The samples remain the same QE as the original ones(~80%)even when their particle size is reduced to 3.2-3.5 mm,because they contain fewer surface suspension bond defects.More importantly,SrBaSi_(5)N_(8):Eu^(2+)phosphors show a size-independent thermal quenching behavior and a zero thermal degradation.We demonstrate that red-emitting mini-LEDs can be fabricated by combining the SrBaSi_(5)N_(8):Eu^(2+)red phosphor(3.5 mm in size)with blue mini-LED chips,which show a high external quantum efficiency(EQE)of above 31%and a super-high luminance of 34.3 Mnits.It indicates that fine and high efficiency phosphors can be obtained by the proposed method in this work,and they have great potentials for use in mini-LED displays.展开更多
基金National Natural Science Foundation of China(Grant Nos.62275227,62274138,and 11904302)Project of Ministry of Industry and Information Technology of China(Grant No.246)+2 种基金Science and Technology Project of Fujian Province(Grant Nos.2023H4028 and 2023H6038)Key Research and Industrialization Projects of Technological Innovation of Fujian Province(Grant No.2023G043)Shenzhen Science and Technology Program(Grant No.JCYJ20220530143407017).
文摘Mini-LED backlight has emerged as a promising technology for high performance LCDs,yet the massive detection of dead pixels and precise LEDs placement are constrained by the miniature scale of the Mini-LEDs.The high-resolution network(Hrnet)with mixed dilated convolution and dense upsampling convolution(MDC-DUC)module and a residual global context attention(RGCA)module has been proposed to detect the quality of vehicular Mini-LED backlights.The proposed model outperforms the baseline networks of Unet,Pspnet,Deeplabv3+,and Hrnet,with a mean intersection over union(Miou)of 86.91%.Furthermore,compared to the four baseline detection networks,our proposed model has a lower root-mean-square error(RMSE)when analyzing the position and defective count of Mini-LEDs in the prediction map by canny algorithm.This work incorporates deep learning to support production lines improve quality of Mini-LED backlights.
基金This work is supported by the National Natural Science Foundation of China(Nos.51832005 and 52172157)the Fundamental Research Funds for the Central Universities(No.20720200075)Fujian Provincial Science and Technology Project(Nos.2020I0002 and 2021J01042).
文摘Mini-LED backlights,combining color conversion materials with blue mini-LED chips,promise traditional liquid crystal displays(LCDs)with higher luminance,better contrast,and a wider color gamut.However,as color conversion materials,quantum dots(QDs)are toxic and unstable,whereas commercially available inorganic phosphors are too big in size to combine with small mini-LED chips and also have strong size-dependence of quantum efficiency(QE)and reliability.In this work,we prepare fine-grained Sr_(2)Si_(5)N_(8):Eu^(2+)-based red phosphors with high efficiency and stability by treating commercially available phosphors with ball milling,centrifuging,and acid washing.The particle size of phosphors can be easily controlled by milling speed,and the phosphors with a size varying from 3.5 to 0.7 mm are thus obtained.The samples remain the same QE as the original ones(~80%)even when their particle size is reduced to 3.2-3.5 mm,because they contain fewer surface suspension bond defects.More importantly,SrBaSi_(5)N_(8):Eu^(2+)phosphors show a size-independent thermal quenching behavior and a zero thermal degradation.We demonstrate that red-emitting mini-LEDs can be fabricated by combining the SrBaSi_(5)N_(8):Eu^(2+)red phosphor(3.5 mm in size)with blue mini-LED chips,which show a high external quantum efficiency(EQE)of above 31%and a super-high luminance of 34.3 Mnits.It indicates that fine and high efficiency phosphors can be obtained by the proposed method in this work,and they have great potentials for use in mini-LED displays.
