Optical power scale realization using the predictable quantum efficient detector

We report realization of scales for optical power of lasers and spectral responsivity of laser power detectors based on a predictable quantum efficient detector (PQED) over the spectral range of 400 nm–800 nm. The PQED is characterized and used to measure optical power of a laser that is further used in calibration of the responsivities of a working standard trap detector at four distinct laser lines, with an expanded uncertainty of about 0.05%. We present a comparison of responsivities calibrated against the PQED at Aalto and the cryogenic radiometer at RISE, Sweden. The measurement results support the concept that the PQED can be used as a primary standard of optical power.

New facility for primary calibration of differential spectral responsivity of solar cells using LDLS-based monochromatic source

A newly established setup for primary calibration and characterization of solar cells at NMCC/SASO is presented. This differential spectral responsivity (DSR) measurement instrument uses laser-driven light source (LDLS)-based modulated (AC) source to measure the spectral responsivity of photovoltaic (PV) detectors and solar cells. The setup is intended for measuring the spectral responsivity in the wavelength range from 250 nm to 2000 nm, bias level up to 1.5 kW/m2, with which a measurement uncertainty of 1.06 % (k = 2, in the range of 300 nm to 900 nm) could be achieved. We present validation measurements as well as spectral responsivity and external quantum efficiency (EQE) measurements of reference solar cells to demonstrate the objective of the setup. We present a preliminary evaluation of the associated uncertainty components as well as an uncertainty budget for validation, optimization and standardization of our setup.

GENERAL V(λ) MISMATCH INDEX - HISTORY, CURRENT STATE, NEW IDEAS

The general V(λ) mismatch index, f_1^' quantifies the mismatch between the spectral responsivity of a photometer, s(λ), and the spectral luminous efficiency function, V(λ). A short review of its historical development is given to explain the reasons for the current definition and which adjustments may be useful for the future. The properties of the current definition are described in detail. It is very likely that in the future, calibration of photometers will be done with a white LED light source as reference. It might involve the need for a more adequate definition of the general V(λ) mismatch index, either by using a different normalization in f_1^' for the spectral responsivity of the photometer or by introducing a different type of function for assessing the mismatch. On the other hand, the measurement of coloured LEDs is also becoming increasingly important. Is a single quality index for white and coloured light sources sufficient?

UNFILTERED TRAP-BASED PHOTOMETER CALIBRATION

LED-based light sources have replaced massively traditional sources. The metrology traceability chains realised in leading European NMIs utilise the absolutely calibrated broadband radiometers (three-element silicon trap detectors) for calibrating primary photometers. Specific spectral properties of white LED allow to apply the trap detectors directly as new primary photometers. The unfiltered technique (Dӧnsberg at al., 2014) is used and the calibration of spectral irradiance responsivity is needed. We have a long experience in detector-based spectral irradiance responsivity calibrations declared by particular CMC’s published in BIPM KCDB. The aim of this work was to revise the uncertainty budget in order to reduce the measurement uncertainties for specific application of calibration of the trap-based unfiltered primary photometers UPP. The two calibration methods were used to analyse the occasional back-reflection effect of the UPP front aperture. The measurement was performed using our reference spectral responsivity facility in spectral range 350 nm – 900 nm.

IMPACT OF THE NORMALIZATION OF THE SPECTRAL RESPONSIVITY ON THE PERFORMANCE OF THE GENERAL V(λ) MISMATCH INDEX

Quality indexes are usually defined for measurement instruments in order to characterize some specific aspect of their performance. The V(λ) spectral mismatch of photometers is evaluated by the general V(λ) mismatch index, f1’, whose value must be correlated with the average measurement error introduced by this spectral mismatch. The objective of this work is to assess the correlation of several indexes of this type with this average error of photometers. The difference between the studied indexes is that the spectral responsivity of the photometer is normalized with different factors to that defined for f1’. From this study, we conclude that the most suitable normalization in the definition of a f1’-type quality index is not determined by the spectral distribution used in the calibration or by those of the light sources to be measured. The normalization factor presenting the best correlation in all studied cases was obtained by numerically minimizing the value of the index instead of by applying an explicit function, as it is done in f1’.

Measurement-based extrapolation of spectral responsivity by using a low-NEP pyroelectric detector

In case the primary realization of the spectral responsivity scale is not conducted at all target wavelengths but at only a small part of them, one needs to extrapolate values at the specific wavelengths to an extended range. In this work, we present a fully experimental procedure to extrapolate a single value of spectral responsivity at 633 nm into the whole working wavelength range (250 – 1100) nm of Si photodiodes. It is based on spectral responsivity comparison between a Si trap detector and a low-NEP pyroelectric detector of nearly flat spectral response. For this purpose, we developed a setup specialized to compare a Si-trap detector of dc-current output with a pyroelectric detector of ac-voltage output by using a modulated probing light source and a monitoring technique. To keep the probing light chopped even for the dc-photocurrent readout, we adopted a low chopping frequency of 4 Hz and a triggered readout for the Si-trap detector, which leads to a speedy comparison between the Si-trap detector and the pyroelectric detector. For the reference pyroelectric detector, we characterized the spectral absorptivity of the black-coating and the nonlinearity of the lock-in amplifier readout. Compiling all the required information, the spectral responsivity of the Si trap detector could be measured with the minimum uncertainty of 0.3 % (k = 2), which was validated by comparing with that of our previous method based on a numerical extrapolation.

Thin Film Reflectance Model for Trap Detector

The physical model of the spectral responsivity of trap detector consists of multiple parameters such as the internal quantum efficiency and the spectral reflectance. In some measurement models, the spectral reflectance of the trap detector is approximated by fitting a wavelength dependence equation which does not consider the effect of the oxide thickness of the silicon photodiode. To analyse the uncertainty due to the oxide thickness variation, a thin film reflectance model is set up in the Standards and Calibration Laboratory (SCL) for the evaluation of the spectral reflectance of the trap detectors. The model is based on the Fresnel coefficients of a 3-layer thin film structure which consists of air and a thin film oxide layer on a silicon substrate. The reflectance model was implemented as user-defined functions to calculate the spectral reflectance at different oxide thickness. It was also integrated with the SCL’s MCM program to evaluate the uncertainty of the spectral responsivity of trap detectors.

A method to measure the spectral responsivity of a photometer using optical excitations with arbitrary spectral distributions

The spectral responsivity of a photometer is usually measured using very narrow optical excitations, provided by a monochromator or a tuneable laser. This article describes a technique to measure the spectral responsivity using an arbitrary number of optical excitations having any type of spectral distribution. The problem is formulated as an inverse problem which is solved using a probabilistic approach based on Bayes’ theorem. The method requires a prior knowledge of the spectral responsivity, which can be proportional to the standard photopic function, with an uncertainty level related to the spectral match index of the photometer. Using this method, the estimation can be performed from data provided by a simple experimental set-up. The numerical application provides a stable and unique solution to the inverse problem, along with the estimation uncertainties. Using a tuneable LED source, the method was applied to an illuminance measurement head, giving an estimation of its spectral responsivity from 380 to 780 nm with a step of 1 nm. The results were in good agreement with data obtained by a monochromator-based technique. Our measurement had larger uncertainties towards the red and blue limits of the spectrum as the light source provided very little light at these wavelengths.