Data from: Electrical transport in tunably-disordered metamaterials

Naturally occurring materials are often disordered, with their bulk
properties being challenging to predict from the structure, due to the
lack of underlying crystalline axes. In this paper, we develop a digital
pipeline from algorithmically-created configurations with tunable disorder
to 3D printed materials, as a tool to aid in the study of such materials,
using electrical resistance as a test case. The designed material begins
with a random point cloud that is iteratively evolved using Lloyd's
algorithm to approach uniformity, with the points being connected via a
Delaunay triangulation to form a disordered network metamaterial.
Utilizing laser powder bed fusion additive manufacturing with stainless
steel 17-4 PH and titanium alloy Ti-6Al-4V, we are able to experimentally
measure the bulk electrical resistivity of the disordered network. We
found that the graph Laplacian accurately predicts the effective
resistance of the structure, but is highly sensitive to anisotropy and
global network topology, preventing a single network statistic or disorder
characterization from predicting global resistivity.