The project AI-4-QD aims at the development and optimization of light emitting and photovoltaic devices with the aid of ML and the support of an online database. The consortium unites three complementary partners that perfectly match with their mutual expertise and R&D interest: (i) The Italian Institute of Technology (IIT) is a research institute that targets innovation in material science with a view on proof-of-concept applications. (ii) Glass to Power (GTP) is a young, rapidly growing, Italian SME focused on the development of building integrated photovoltaic windows based on semiconductor colloidal nanocrystals. (iii) MaterialsZone (MZ) is a young Israeli company that pioneers the use and integration of artificial intelligence in the device and process development of semiconductor technology.
The synergistic alliance between will apply machine learning (ML) algorithms and a wide knowledge of material science to the research on colloidal nanocrystal materials and their applications. Colloidal nanocrystals are nanoscale materials prepared by chemical approaches that have found application in various fields, above all optoelectronics.
Two complementary strategies will be followed towards this aim.
One will be targeting the synthesis of novel materials via a ‘reverse tailoring’ approach, where the desired material properties are defined first, and then the artificial intelligence, drawing from a large database, suggests possible suitable protocols. In parallel, we will use ML for optimizing existing synthesis and fabrication protocols, also already employed at an industrial level, in order to obtain higher performance of the materials and devices, in particular for luminescent nanocrystals for solar concentration. Also importantly, ML concepts will be applied to the fabrication of nanocrystal-based
light-emitting diodes (LEDs) and solar harvesting, and an online platform will be explored as a marketplace for obtaining revenue from the whole set of protocols developed within the project.
AI-4-QD provides unique opportunities for each partner. Basic materials research, as performed at the IIT, typically involves an extremely large set of parameters (material choice, synthesis conditions, process type, the composition of the device) that are typically tuned based on empirical knowledge, and intuition of the scientists. Here the ML and optimization algorithms of MZ provide a completely new approach towards the development of new materials, and the design of efficient LEDs and solar harvesting. In this setting, a variety of very diverse processes and device architectures will be targeted,
which constitute new challenges for MZ and will help it to enlarge the versatility of its algorithms. The R&D company GTP develops a specific kind of nanomaterials, bright emitting colloidal semiconductor nanocrystals embedded into optical-grade polymeric nanocomposite waveguides, for a well-defined application that is the efficient spectral manipulation and the electrical conversion of sunlight. To be an effective aid to GTP activities, the ML approach needs to be applied to well-defined processes with a set of restrictions (non-toxicity of materials, compatibility of the nanocrystals with the host matrix,
material costs). Here AI-4-QD will target the optimization of the device performance as well as the yield (cost and material efficiency) of the synthesis of the colloidal materials that constitutes a major activity of GTP.
Crucially, towards the development of Artificial Intelligence for Material Science, the two Italian partners will provide complementary R&D platforms that challenge the routines and enrich the MZ database with innovative approaches tightly focused on colloidal nanocrystals and their optoelectronic properties.
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New materials with special properties are the key to new technologies and solutions. The science of materials has become the driving force behind innovation.