Abstract
The main objective of this work is to explore the field dependence of the electrocaloric effect (ECE) in KTa
0.57
Nb
0.43
O
3
in terms of the entropy change (Δ
S
) and the temperature change (Δ
T
) for applied electric fields ranging from 5 to 15 kV cm
−1
. The artificial neural network (ANN) may be used as a reliable modeling method for simulating and predicting electrocaloric behavior under different thermoelectrical conditions. The experimental data collection was employed for this purpose to forecast the coefficient of performance and temperature span for KTa
0.57
Nb
0.43
O
3
operating near room temperature. The large ECE, comparatively high relative cooling power (RCP), temperature-averaged entropy change (TEC), normalized refrigerant capacity (NRC), and low cost jointly make the present compound a promising candidate for cooling devices near room temperature. The electrical field dependence of ECE can help to predict the ECE characteristics of cooling devices and facilitate the design of highly efficient cooling devices.