Rank Prize Internship – Edoardo Altamura

Over Summer 2018, Edoardo Altamura has worked as a Rank Prize Optoelectronics Intern on developing techniques for photovoltaic characterisation. He describes his research:

Photovoltaic energy proved to play a decisive role in a variety of areas, from everyday life power consumption to space satellites. Assessing the efficiency of devices capable of producing such energy is crucial for exploiting their properties at maximum performance, and even seeking new technologies for pushing them beyond the current standards. 

The focus of my internship was on a particular technique for measuring the energy-production efficiency across solar cells, in order to study how manufacturing defects or other forms of impurities affect the overall performance of the device. Using the results obtained by previous MPhys students, I started developing a system capable of projecting random light patterns and reconstructing the efficiency map using Compressed Sensing algorithms. 

Such research has been a great opportunity to learn about defects in semicondutor devices, as well as methods for probing them. Moreover, the effort dedicated into optimising custom software and ensuring its scalability gives me reasons to hope for further development of this project, which may result in some useful applications in semiconductor and solar energy industry.

Thanks again to Edoardo for all of his work over the summer!

Photon 2018

Both Stefan and Arturo will present at Photon 2018 in Aston, UK (September 3rd-6th, 2018).

20180904_175257.jpgStefan presented a poster on “Time and Spectrally-Resolved Microscopy of GaAsP-GaAs core-shell Quantum Well Lasers“, describing some recent work with collaborators in the group of Prof. Huiyun Liu at University College London.





Arturo presented a talk on “Nanolaser optimization through statistical optoelectronic analysis“. This work, done in collaboration with the EME group at the Australian National University, describes his recent work on all optical high throughput techniques for nanolaser optimization.