Software for virtual design and optimization of Organic Electronics (OE) material and devices
A German SME has developed easy-to-use and customizable software for parameter-free, predictive device simulations in Organic Electronics. This enables virtual design by allowing researchers to optimize compounds and devices in the computer, reducing experimental trial and error efforts and thereby development time and costs. The SME is looking for license/commercial agreements with technical assistance with industrial partners interested in incorporating virtual design into their R&D process.
-Type of partner sought: Industry (they also offer licenses to academic research institutes for a reduced price, but this is not their focus) - Specific area of activity of the partner: Developer of OE materials and devices - Tasks to be performed by the partner sought: the partner should be willing to incorporate modeling and virtual design into their R&D process, define specific scientific questions and contribute to the development of a custom-tailored solution. After validation of software solutions, calculations are executed by the partner in-house.
Due to many advantages over conventional electronics, the high-tech field of Organic Electronics (OE) has grown extensively over the last years. These advantages facilitate the fabrication of novel, flexible, and large-area devices, which cannot be produced using conventional electronics (e.g. transparent lighting elements, bendable displays, and lightweight photovoltaics). OE devices, such as organic LEDs consist of one or multiple layers of organic electronic molecules. Both the single molecule properties and the setup of the layer structure play a crucial role in device performance (efficiency). Due to the vast number of possible combinations of materials and layer setups and the fact that the many microscopic processes involved in the conversion between electricity and light prevent ad hoc prediction of device properties from the constituents, the experimental development of new materials and optimization of devices relies on time-consuming and costly trial-and-error approaches. The SME facilitates the virtual design and computer aided optimization of organic electronic (OE) materials and devices by providing adjustable, easy-to-use software for parameter-free, predictive simulations. This enables their partners worldwide to understand what is going on in their device and thereby identify bottlenecks, fully in the computer. As experts in predictive OE-modeling, they develop custom-tailored solutions based on their software platform to address their partners’ specific needs. In close collaboration with one of the leading research institutes in Germany, the SME incorporates state-of-the-art methodology into their modules. The embedding of their tools into a smart workflow platform hides the complexity of multiscale high-performance computing and generates a ready-to-run solution for researchers from all backgrounds, in both SMEs and large corporations. The SME is looking for partners for license agreements and commercial agreements with technical assistance. The partner should be interested in incorporating modeling and virtual design into their R&D process. Based on the company’s software platform, they develop custom-tailored solutions to address the clients’ specific needs. Their services include software licenses, software adaption and scientific consultation. The software runs on high-performance computing (HPC) architectures (32 cores and more), either in-house or in the cloud. Expertise in quantum chemistry is a big plus.
Advantages and innovations
- Following a bottom-up approach, results on the device scale are based on electronic effects and processes computed exclusively on quantum mechanical level. - No external parameters, e.g. from experiment, are needed to compute device properties such as internal quantum efficiency or I-V-characteristics (current-voltage characteristics)of organic layers or multi-stack devices. This enables researchers to fully understand processes in OE and to pre-optimize compounds and device setups in the computer. - Including computational, predictive modeling in the complex R&D process minimizes experimental trial and error efforts. This boosts innovation by saving time and money and generates competitive advantage by short time to market.
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