  Integrated sensing and communication (ISAC) has opened up numerous
game-changing opportunities for future wireless systems. In this paper, we
develop a novel scheme that utilizes orthogonal frequency division multiplexing
(OFDM) pilot signals in ISAC systems to sense the electromagnetic (EM) property
of the target and thus also identify the material of the target. Specifically,
we first establish an end-to-end EM propagation model by means of Maxwell
equations, where the EM property of the target is captured by a closed-form
expression of the ISAC channel, incorporating the Lippmann-Schwinger equation
and the method of moments (MOM) for discretization. We then model the relative
permittivity and conductivity distribution (RPCD) within a specified detection
region. Based on the sensing model, we introduce a multi-frequency-based EM
property sensing method by which the RPCD can be reconstructed from compressive
sensing techniques that exploits the joint sparsity structure of the EM
property vector. To improve the sensing accuracy, we design a beamforming
strategy from the communications transmitter based on the Born approximation
that can minimize the mutual coherence of the sensing matrix. The optimization
problem is cast in terms of the Gram matrix and is solved iteratively to obtain
the optimal beamforming matrix. Simulation results demonstrate the efficacy of
the proposed method in achieving high-quality RPCD reconstruction and accurate
material classification. Furthermore, improvements in RPCD reconstruction
quality and material classification accuracy are observed with increased
signal-to-noise ratio (SNR) or reduced target-transmitter distance.
