Fatigue life prediction of bending polymer films using random forest

The prediction of the fatigue life of polymer film substrates under cyclic bending plays an important role in designing durable flexible devices. Here, the fatigue life of bending polymer film was predicted using machine learning; the required data were collected via fatigue tests under different test conditions. Machine-learning models (linear regression and random forest regression) were constructed using these collected data. The random forest model predicted the fatigue life with a mean absolute percentage error of 22.3% within 1 min. Such accurate and efficient fatigue life predictions can contribute toward the development of flexible devices.

Automated summary

In this study, the fatigue life of bending polymer films was predicted using machine learning. The random forest model showed accurate and efficient predictions of fatigue life, with a mean absolute percentage error of 22.3% within 1 minute. This contributes to the development of flexible devices.