| Title | Informatics Driven Materials Innovation for a Regenerative Economy: Harnessing NLP for Safer Chemistry in Manufacturing of Solar Cells |
|---|---|
| ID_Doc | 8 |
| Authors | Giri, D; Mukherjee, A; Rajan, K |
| Title | Informatics Driven Materials Innovation for a Regenerative Economy: Harnessing NLP for Safer Chemistry in Manufacturing of Solar Cells |
| Year | 2022 |
| Published | Rewas 2022: Developing Tomorrow'S Technical Cycles, Vol I, , |
| Abstract | The objective of this paper is to demonstrate the use of natural language processing tools to map the propensity of usage of specific solvents used for the fabrication of different perovskite photovoltaic (PV) systems. This article focuses on implementing contextual natural language processing (NLP) tool to identify different chemicals that appear in the synthesis of perovskite solar cells. This information is linked to the known level of hazard of those solvents. This work serves to demonstrate how by harnessing the tools of informatics, in this case NLP, offers a powerful framework to guide environmentally conscious selection of chemicals used in the manufacturing of perovskite solar cells. |
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