Effects of spectrophotometric wavelength-scale error on color coordinate determination

1983 ◽  
Vol 26 (9) ◽  
pp. 745-749 ◽  
Author(s):  
V. I. Lagutin
Keyword(s):  
Coordinate Determination ◽  
Color Coordinate ◽  
Scale Error ◽  
Wavelength Scale

scholarly journals Observing and controlling a Tamm plasmon at the interface with a metasurface

Nanophotonics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 897-903 ◽  
Author(s):  
Oleksandr Buchnev ◽  
Alexandr Belosludtsev ◽  
Victor Reshetnyak ◽  
Dean R. Evans ◽  
Vassili A. Fedotov
Keyword(s):  
Liquid Crystal ◽  
Metal Film ◽  
Near Infrared ◽  
Thin Metal Film ◽  
Outer Side ◽  
Spectral Position ◽  
External Perturbations ◽  
Dielectric Mirror ◽  
Wavelength Scale ◽  
Sub Wavelength

AbstractWe demonstrate experimentally that Tamm plasmons in the near infrared can be supported by a dielectric mirror interfaced with a metasurface, a discontinuous thin metal film periodically patterned on the sub-wavelength scale. More crucially, not only do Tamm plasmons survive the nanopatterning of the metal film but they also become sensitive to external perturbations as a result. In particular, by depositing a nematic liquid crystal on the outer side of the metasurface, we were able to red shift the spectral position of Tamm plasmon by 35 nm, while electrical switching of the liquid crystal enabled us to tune the wavelength of this notoriously inert excitation within a 10-nm range.

scholarly journals Ultra-high-Q resonances in plasmonic metasurfaces

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
M. Saad Bin-Alam ◽  
Orad Reshef ◽  
Yaryna Mamchur ◽  
M. Zahirul Alam ◽  
Graham Carlow ◽  
...  
Keyword(s):  
Incident Light ◽  
Reducing Power ◽  
Field Enhancement ◽  
Plasmonic Nanostructures ◽  
High Q ◽  
Alternative Material ◽  
Order Of Magnitude ◽  
Wavelength Scale ◽  
Strong Confinement ◽  
Sub Wavelength

AbstractPlasmonic nanostructures hold promise for the realization of ultra-thin sub-wavelength devices, reducing power operating thresholds and enabling nonlinear optical functionality in metasurfaces. However, this promise is substantially undercut by absorption introduced by resistive losses, causing the metasurface community to turn away from plasmonics in favour of alternative material platforms (e.g., dielectrics) that provide weaker field enhancement, but more tolerable losses. Here, we report a plasmonic metasurface with a quality-factor (Q-factor) of 2340 in the telecommunication C band by exploiting surface lattice resonances (SLRs), exceeding the record by an order of magnitude. Additionally, we show that SLRs retain many of the same benefits as localized plasmonic resonances, such as field enhancement and strong confinement of light along the metal surface. Our results demonstrate that SLRs provide an exciting and unexplored method to tailor incident light fields, and could pave the way to flexible wavelength-scale devices for any optical resonating application.

Compact spectrometer modeling based on wavelength-scale stationary wave Fourier transform in integrated optic

2008 ◽  
Author(s):  
Alain Morand ◽  
Guillaume Custillon ◽  
Pierre Benech ◽  
Etienne Le Coarer ◽  
Gregory Leblond ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Stationary Wave ◽  
Wavelength Scale

scholarly journals Deep machine learning of the spectral power distribution of the LED system with multiple degradation mechanisms

2020 ◽  
Vol 37 ◽  
pp. 172-183
Author(s):  
Cadmus C A Yuan ◽  
JiaJie Fan ◽  
XueJun Fan
Keyword(s):  
Machine Learning ◽  
Thermal Aging ◽  
Empirical Relationship ◽  
Machine Learning Techniques ◽  
Color Temperature ◽  
Design Parameters ◽  
Degradation Mechanisms ◽  
Theoretical Understanding ◽  
Color Coordinate ◽  
Led Luminaire

Abstract The performance and reliability of the light-emitting diode (LED) system significantly depend on the thermal–mechanical loading-enhanced multiple degradation mechanisms and their interactions. The complexity of the LED system restricts the theoretical understanding of the root causes of the luminous fluctuation or the establishment of the direct correlation between the thermal aging loading and the luminous outputs. This paper applies the deep machine learning techniques and develops a gated network with the two-step learning algorithm to build the empirical relationship between the design parameters and the thermal aging loading and the luminous output of LED products. The flexibility of the proposed method will be demonstrated by integrating it with different neural network architectures. The proposed gated network concept has been validated in both multiple LED chip packaging and LED luminaire under thermal aging loading. The validation of the luminous data of multiple LED chip packaging shows that the maximum differences of the correlated color temperature (CCT) and color coordinate are 2.6% and 1.0%, respectively. Moreover, the machine learning results of the LED luminaire exhibit that the differences of lumen depreciation, CCT and color coordinate are 1.6%, 1.9% and 1.1%, after 2160 h of thermal aging.

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