Invited7 Videos

SC02–Machine Learning for Optimization of Mass-Produced Industrial Silicon Solar Cells

Wagner-Mohnsen H., Altermatt P. P.

We present a methodology where we combine numerical TCAD device modeling, machine learning and advanced statistics for getting a deeper understanding of how process variations influence device performance in mass produced crystalline silicon solar cells. For this, we use seven model input parameters that affect the mainstream solar cell design (PERC) and its performance the […]

D01–Probability Theory of Single-Carrier Avalanche in HgCdTe APDs as a Stochastic Process

Xie R., Hu W.

Recent researches have proven that HgCdTe is a good material to acquire both high multiplication and low excess noise factor at the same time in avalanche photodiodes (APDs). As a pseudo-binary narrow bandgap semiconductor material, HgCdTe exhibits high conduction band nonparabolicity as well as strong alloy scattering, especially for hot electrons, which changes the dynamics […]

N01–Nanowire antennas embedding single quantum dots: towards the emission of indistinguishable photons

Claudon J., Kotal S., Artioli A., Finazzer M., Fons R., Genuist Y., Bleuse J., Gérard J.-M., Wang Y., Osterkryger A. D., Gregersen N., Munsch M., Kuhlmann A. V., Cadeddu D., Poggio M., Warburton R. W., Verlot P.

Nanowire antennas embedding a single semiconductor quantum dot (QD) represent an appealing solid-state platform for photonic quantum technologies. We present recent work aiming at generating indistinguishable photons with this system. We first investigate decoherence channels that spectrally broaden the QD emission, and discuss in particular the impact of nanowire thermal vibrations. We also develop nanowire […]

NM01–Machine Learning & multiscale simulations: toward fast screening of organic semiconductor materials

Rinderle M., Gagliardi A.

Organic semiconductor devices promise cost-efficient processability at low temperatures, but the usually amorphous materials suffer from low charge carrier mobility. The search for high mobility organic semiconductor materials has thrived data science and Machine Learning approaches to screen the vast amount of possible organic materials. We present a multiscale simulation model based on machine learned […]

MM01–Connecting atomistic and continuum models for (In,Ga)N quantum wells: From tight-binding energy landscapes to electronic structure and carrier transport

Schulz S., O’Donovan M., Chaudhuri D., Patra S. K., Farrell P., Marquardt O., Streckenbach T., Koprucki T.

We present a multi-scale framework for calculating electronic and transport properties of nitride-based devices. Here, an atomistic tight-binding model is connected with continuum based electronic structure and transport models. In a first step, the electronic structure of (In,Ga)N quantum wells is analyzed and compared between atomistic and continuum-based approaches, showing that even though the two […]

LD01–Multimode Dynamics and Frequency Comb Generation in Quantum Cascade Lasers

Belyanin A., Wang Y.

In this talk I will discuss how resonant light-matter interaction in the gain medium of quantum cascade lasers gives rise to a rich nonlinear multimode dynamics and a variety of phase-locked multimode regimes, most notably optical frequency combs with separation between the comb lines changing from one to many dozen round-trip frequencies. I will review […]