  The microstructure of material strongly influences its mechanical properties
and the microstructure itself is influenced by the processing conditions. Thus,
establishing a Process-Structure-Property relationship is a crucial task in
material design and is of interest in many engineering applications. We develop
a GAN (Generative Adversarial Network) to synthesize microstructures based on
given processing conditions. This approach is devoid of feature engineering,
needs little domain awareness, and can be applied to a wide variety of material
systems. Results show that our GAN model can produce high-fidelity multi-phase
microstructures which have a good correlation with the given processing
conditions.
