Optimization of polyaniline nanofiber loading in polymer matrix for strong microwave absorption using materials data-driven discovery

The prediction of electromagnetic properties and microwave absorption characteristics for different filler loading to polymer matrix is crucial for any composite or hybrid materials to understand the best performance. In this work, a simple and effective materials data-driven method is explored to predict the electromagnetic parameters and microwave absorption characteristics for polyaniline nanofiber (PANI NF) loading to the polyvinyl butyral (PVB), hence predicting percolation threshold with limited resources and time. With this method, the reflection loss (RL) is predicted for different PANI NF weight percentage (wt %) loading in X-band (8.2–12.4 GHz). The data-driven method shows that RL ≤ −10 dB (which is potentially important for real time applications) can be achieved from 3 wt% PANI NF loading onwards, and filler loading range 5–12 wt% is the best range for tuneable excellent RL characteristics (minimum RL value and RL ≤ −10 dB absorption bandwidth at minimum thickness). The predicted data suggests a minimum RL value −38 dB for 8 wt% PANI NF loading at 2 mm (with an excellent absorption bandwidth), which is not investigated before. The experimental data are well matched with the predicted results. • A novel data-driven method for electromagnetic application. • Prediction of electromagnetic properties for polyaniline nanofiber (PANI NF) loading to poly vinyl butyral (PVB). • Evaluation of percolation threshold of PVB-PANI NF system easy and effective way. • Validation of predicted data with experimental data.