Advanced dielectric spectroscopy, electrochemical impedance spectroscopy and machine learning investigation of DMF–n-Octanol binary mixtures

Dielectric studies provide valuable insight into molecular interactions in hydrogen-bonded liquid mixtures. In this study, the dielectric properties of binary mixtures of n-octanol and N,N-dimethylformamide (DMF) were investigated over the entire composition range (0.0→1.0) at 293.15, 303.15, and 313.15 K in the frequency range of 20 Hz→2 MHz using a precision LCR metre. The dielectric response was analysed through complex permittivity, electric modulus, conductivity, and impedance formalisms to explore relaxation dynamics and charge transport mechanisms. Cole-Cole and Nyquist analyses indicated significant electrode polarisation and non-Debye relaxation behaviour arising from hydrogen bonding and dipolar interactions. Relaxation parameters and excess dielectric properties revealed the formation of antiparallel dipolar aggregates within the mixtures. Theoretical mixing rules showed good agreement with experimental dielectric constants. Machine learning models were used for dielectric prediction, with CatBoost exhibiting excellent performance (R2 ≈1.0), demonstrating the potential of predictive modelling for complex liquid systems.