Design & Production The of Next-Generation Advanced Materials
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Artificial Intelligence & Data Management for Colloidal Quantum Dots
The platform applies machine learning (ML) algorithms and online notebook management tools to the research on colloidal nanomaterials and their applications. MZ targets nanocrystal structures, highly luminescent quantum dots, and LED and PV devices.
MZ’s interfaces exploit large databases and suggest intelligent protocols for the synthesis of novel and improved crystals that are suitable for applications in the field of optoelectronics.
In parallel, MZ will use ML for optimizing existing synthesis and fabrication protocols, also already employed at an industrial level, to obtain higher performance of the materials and devices, in particular for luminescent nanocrystals for solar concentration.
Consolidating data from Israels leading nano technology institute
Working with Israel’s leading Nano Tech lab to make data available to its researchers, the MZ team took five years of experimental data and made it FAIR (Findable, Interopable, Accessable and Re-usable).
Consolidating data ranging from batteries to rust.
One hypothesis whereby the MZ team and researchers previously tried to fabricate rust to turn sunlight into electricity. Using the newly structured experimental data, the first attempt was to use ML (Machine Learning) to predict how to fabricate the optimal rust. The second attempt combined previous results, teaching the algorithm to find the optimal results.
Based on the new recommendation results, the outcome was x5 greater than the previous 5 years, and with a higher reproducibility – all data was stored and accessable for any future research.
AI4QD is a bilateral constortium between Italy and Israel. Glass to Power (G2P), Materials Zone (MZ) and IIT focused on the integration of luminescent nanocrystals in photovoltaic windows. The G2P team recently achieved an optical efficiency record of 6.8 percent and exceeded all their previous records.
Our platform is applying machine learning (ML) algorithms and utalising an online notebook management tool, to the research on colloidal nanomaterials and their applications. The interoperable data targets nanocrystal structures, highly luminescent quantum dots, and LED and PV devices. MZ’s interfaces exploit large databases and suggest intelligent protocols for the synthesis of novel and improved crystals that are suitable for applications in the field of optoelectronics.
Wafer maps, histograms and correlation plots for Europes leading innovation hub
The experimental data generated by the metrology tools at our undisclosed R&D institute were under-exploited, with confidentiality constraints and complex diverse measurement report formats.
To overcome these limitations, the client joint hosted the experimental data and secured them by managing the confidentiality levels and visualising the results in real-time to labaratories around the globe.
A database dedicated to the storage of data was setup, followed by a bespoke graphical user interface allowing accessibility to the data. Files could also be exported and the interoperable visualizations demonstranted as a variety of chart types, wafer maps, histograms and correlation plots.
Leveraging AI to create efficient production lines
A production line with many different steps, batches, and material properties analyzed is difficult to manage.
The products of the production line need to meet the strictest standards from the FDA, and efforts are being made towards minimizing the cost of products manufactured which don’t meet FDA standards and need to be disposed of.
Lifecycle management and advanced analytics platform can alert the management of errors early on in the production line and save the cost of production steps that result in products that don’t meet the requirements.