This work features a dataset intended to aid in the development of processing parameters for particulate composite materials for additive manufacturing (AM) using digital light processing (DLP) method. Hollow glass microspheres (HGMs) are used as particulate fillers to manufacture syntactic foam composites. The standard thermosetting resins have a recommended set of 3D printing parameters. However, when the particles are mixed to 3D print composites, the mixture properties change, and the processing parameters need to be adjusted according to the particle volume fraction, size and other parameters. This dataset provides rheological measurements on the neat resin and resin–HGM composite mixtures intended for vat photopolymerization (VP) based DLP method. Three HGM density grades (0.13, 0.23, and 0.31 g/cm³ true particle densities) were examined at 10, 20, and 40 vol.% to capture the effects of particle density and volume fraction on resin flow behavior. Viscosity was measured using an Anton Paar MCR702 analyzer at a range of shear rates (1–50 s⁻¹) and temperatures (35–125 °C), generating 50 independent data files for 5 trials repeated for each of the 10 compositions. The dataset records the coupled influence of temperature and shear rate for each composition, providing a foundation for modeling viscosity–shear rate–temperature–composition relationships. Interpolations of various parameters at a benchmark viscosity of 0.40 Pa·s enable extraction of processing windows relevant to VP of the composite mixtures and significantly reduce the trial and error involved in processing parameter optimization for composite mixtures. The dataset also includes µCT image stacks for representative specimens, supporting qualitative assessment of particle dispersion and internal structure.
Beckwith et al. (Thu,) studied this question.