fig10

Accelerating perovskite materials discovery and correlated energy applications through artificial intelligence

Figure 10. (A) Workflow for high-throughput synthesis of single-crystal perovskites and the image-recognition classification model. Copyright from Elsevier[47]. (B) Prediction accuracy vs. the number of training experiments for PUFK-SVM models of different crystallization systems. Solid lines show mean accuracy, and shaded bands indicate the standard deviation from five-fold CV results for each system. Copyright from ACS Publications[73]. (C) Workflow of ML-guide robot-based MHPs synthesis system. Copyright from ACS Publications[77]. (D) Schematic of the developed intelligent modular fluidic microprocessor for autonomous synthetic path discovery and optimization of colloidal QDs and the process flow diagram detailing its operation. Copyright from Wiley[78].

Energy Materials
ISSN 2770-5900 (Online)
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