Machine Learning-Assisted Exploration of Lead-Free Ferroelectric Materials for Flexible Sensing

by Dr Srujan S. Sapkal (Defence Institute of Advanced Technology,)

Tuesday 11 Aug 2026, 16:00 → 18:00 Asia/Kolkata

AG 80

The present talk explores ferroelectric ceramics and their properties using machine
learning (ML) models, followed by the utilisation of the modified ceramics as functional
fillers in the fabrication of flexible sensors. The growing demand for environmentally
sustainable and high-performance electronic materials has intensified research into lead-free
ferroelectrics for next-generation sensor technologies. In particular, nanocomposites
integrating ferroelectric ceramics with poly (vinylidene fluoride) (PVDF) polymers have
emerged as promising candidates for next-generation flexible sensors, combining mechanical
flexibility with enhanced electroactive properties. The presentation integrates supervised ML
models and materials science to develop a simple framework for accelerating the design of
lead-free ferroelectric materials. The work presented herein effectively utilises data-driven
methodologies to understand structure–property relationships, predict functional behaviour,
and provide physical insights into the ferroelectric properties of ceramic materials.