A technique for creating 3-dimensional virtual patients (3DVPs) by superimposing intraoral and facial digital scans guided with a novel aligner system is described. This aligner system supports design modifications to adapt to different facial scanning methods (FSMs) and reduce the impact of FSMs on the accuracy of 3DVPs. Two different designs of the aligner system are described: one for use with less-accurate FSMs and another for use with more-accurate FSMs. These virtual designs are available for download and use.

The disintegration time of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) in compost varies by more than an order of magnitude for the same polymer, and standardised tests quantify this variability without explaining it. Here we present a three-dimensional, spatially resolved Monte Carlo model of PHBV film disintegration, in which the polymer is discretised into a voxel lattice derived from the specimen geometry and eroded via local Monod kinetics. A single reference kinetic set is calibrated once against a benchmark dataset (RMSE = 2.27 pp) and held fixed; each compost is then described by one physically interpretable parameter, the initial density of degrading inoculum, whose fitted range quantifies the microbial-activity variability the standards leave unexplained. With the kinetics fixed, the model reproduces an independent thermophilic dataset by varying only this parameter and the geometry (RMSE = 3.05 pp), and passes two a priori tests with the parameter transferred, not fitted: a 400 µm film from the literature (RMSE = 14.1 pp) and a 50 µm film characterised here (RMSE = 7.01 pp). Together these span two ISO standards and an eightfold range of thickness (50–400 µm), bracketing the 200 µm calibration point. A further dataset, obtained in undiluted real compost rather than a diluted synthetic substrate, is reported as a documented exception requiring its own kinetic set (RMSE = 5.24 pp). Because geometry is an explicit input, the model predicts how thickness sets the disintegration window and resolves the spatial fragmentation pattern, beyond the reach of empirical fits.