Optoelectronics

Software to test optoelectronic devices. The NI-VISA is used to control a Keithley source measure unit (SMU). Additional information about NI-VISA can be found on the following website: https://pyvisa.readthedocs.io/en/1.8/getting_nivisa.html

Keithley2612B library was written in Python to control Keithley 2612B. Please, contact the program's writer to add other Kiethly SMU models.

KeithleyV15.py library to control Keithley SourceMeter 2600 series

Before to start:

Use the next command to install the necessary libraries::

python -m pip install -r requirements.txt

Script to check the connection of the Keithley SMU to the PC:

J-V_curve.py program was written in Python to check the correct connection of the Keithley 2612B SMU and measure voltage-dependent current on Channel A and current on Channel B. The data from the collected J-V curve will be saved in a csv-file.

First, use your own address of connection Keythley SMU to PC, here is an example of my connection in the script:

sm = SMU2612B('USB0::0x05E6::0x2612::4439973::INSTR')

Then, use the next command to start the script:

python J-V_curve.py

Before starting the J-V curve program, the IP address must be changed depending on which SMU you use. Use the following code to check your connection of the Keithley SMU to the PC (check_connection.py, script):

import pyvisa
rm = pyvisa.ResourceManager()
print(rm.list_resources())

or use the next command to start the script:

python check_connection.py

Script to measure light emitting diodes (OLEDs, PLEDs, QLEDs, QD-OLEDs and PeLEDs)

• OLEDs - organic light-emitting diodes
• PLEDs - polymer light-emitting diodes
• QLEDs - quantum dots light-emitting diodes
• QD-OLEDs - quantum dots-organic light-emitting diodes
• PeLEDs - perovskite light-emitting diodes

Use the performance_LED.py script to measure and calculate the performance of LEDs. All data will be saved in a csv-file.

Parameters in the LED scrip (performance_LED.py) must be calculated and changed. Please, contact me for additional consultation.

Script to measure photovoltaic devices (OPVs, OSCs, PSCs and QDSCs)

• OPVs - organic photovoltaics
• OSCs - organic solar cells
• PSCs - perovskite solar cells
• QDSCs - quantum dots solar cells

1. Geometrical of the setup and characteristics of the indoor light source.

In this example, the geometrical setup where the photodetector is placed on-axis in front of the indoor light source (white warm LED) to detect emitted light in the forward perpendicular direction is present in Figure 1. The distance (D) between the photodetector and white warm LED is chosen between 0.2 and 2 m (it depends on the emissivity of the white light source) to provide sufficient surface illumination.

To measure the electroluminescent spectrum of the light source the spectrometer coupled to an optical fibre has used. The calibrated lamp of known spectral emissivity has used to obtain a spectral correction for the spectrometer and optical fibre combined system.

The light intensity (Eλ), in W/m^2, is defined as:

where Ipd - the current density in the Si-photodiode (A/m^2); S(λ) - normalized spectrum of source (LED) is measured as a function of wavelength has units of “count”, R(λ) is a function of the wavelength of the calibrated Si photodiode has units of A/W.

The same result can be obtained by integrating the electroluminescent spectrum S'(λ) of the white warm LED by measuring the calibrated spectrometer, optical fibre and integrating sphere. The electroluminescent spectrum S'(λ) of the white warm LED. Integrated this spectrum we obtained the light power (Pin) on the surface.

Next, calculate the illuminance of a light source Ev in lm/m^2 = lux:

where the coefficient Km is equal to 683 lm/W, V(λ) is the spectral luminosity factor for human photopic vision. Note that this function is usually given normalized at a wavelength of ~555 nm; in which case the function must be multiplied by a factor Km of ~683 lm/W before being employed in the calculations.

2. Parameters in the PV scrip (performance_PV.py) must be calculated and changed. Please, contact me for additional consultation.

3. Use the performance_PV.py script to measure and calculate the performance of PVs and the power of the source. All data will be saved in a csv-file.

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License

MIT