Description:

Join the High Throughput Methods in Photovoltaics, a research department of the Helmholtz Institute in Germany for an event with presentations from speakers below.

WHEN: Thursday, March 20 | 9:15am-12:15pm CT
WHERE: Online via Zoom. Contact Jeff Mirza for more details and meeting link information. 

--------------------------------------------------------

About the Event

Jianchang Wu - A hybrid workflow to discovery tailored materials for emerging photovoltaics

Julian Haffner-Schirmer - Real time Bayesian inference of crucial material parameters

Accelerated discovery of new materials requires sampling a large experimental space, encouraging high throughput (HT) workflows. However, such workflows allow only characterization techniques which are fast, non-destructive and do not require expert interaction. This restriction impedes the access to crucial material parameters for device optimization. Here, we perform Bayesian inference on a combination of fast characterization techniques (UV-Vis, transient absorption, current-voltage) to access these parameters autonomously in a HT workflow. Real time capacity is enabled by sequential, rather than global fitting of the individual characterization techniques by a common model. We demonstrate that the sub-Langevin factor, an important figure of merit for organic photovoltaic blends, can be obtained in real time, allowing its optimization in HT.

Andreas Bornschlegl - High throughput studies for radiation hard OPV materials

To accelerate the process of finding the optimal material for a specific use-case, high-throughput studies are a very promising strategy. The high potential is exemplified in this presentation by the scenario of seeking radiation hard organic materials for emerging space solar cells. A large material library of organic hole transport, donor and acceptor materials is automatically tested for it's stability against UVC radiation in a nitrogen atmosphere, serving as the conditions for electromagnetic radiation hardness tests. A value closely related to the differential quantum yield is extracted from the UV-Vis spectra and serves as the stability target for a predictive model based on chemical structure descriptors. The established predictive model quantifies the effect of specific molecular features on UVC stability, allowing chemists to consider UVC stability in their molecular design strategy.

Zijian Peng - High throughput study towards long term stable Perovskite solar cells

Understanding perovskite degradation under operational stresses requires resolving the complex interplay of bulk and interfaces. This talk will present a high-throughput framework combining photoluminescence (PL) imaging and drift-diffusion simulations to quantitatively link potential losses (Voc/QFLS losses) with device degradation. We demonstrate that PL mapping, an indicator of trap-assist recombination, serves as a rapid, non-destructive metric for evaluating perovskite stability. By applying this approach, we achieved T80 >1,000 hours under 85°C/2-sun ageing, highlighting the role of defect thermodynamics in long-term stability.  

 
Tobias Osterrieder and Thomas Heumüller - AMANDA Line 1 – an autonomous robot based platform researching organic photovoltaics