In materials engineering, structural disorder is traditionally regarded as detrimental, whereas perfect order is associated with high performance. However, achieving perfect order demands exponentially increasing energy expenditures, raising concerns about long-term sustainability. In contrast, biological materials—though rarely perfectly ordered—often surpass synthetic analogs in performance and multifunctionality. Past studies of nacre-like biomimetic nanocomposites [1,2] suggested that living organisms strategically integrate disorder with repeatable organizational motifs to difficult-to-achieve property combinations. However, the simultaneous presence of order and disorder as well as hierarchical organization typical for biology, render biological and biomimetic materials intractable to conventional structural analysis techniques developed for crystals, quasicrystals, or glasses. What cannot be described quantitatively is difficult to design purposefully.

Biomimetic nanocomposites based on cellulose and other nanofibers offer an outstanding scientific opportunity to understand the interplay between order and disorder in materials engineering. Additionally, the self-assembling composites from nanofibers are attractive as resource- and energy-conscious alternative to current load bearing, charge transporting, ion-selective, and optically-active materials. We demonstrate that integrated account of (1) structural stochasticity; (2) repeatable structural pattens and (3) hierarchical organization in complex high-performance nanocomposites can be achieved using graph theory (GT) and topometric materials design [3,4]. Graphs—comprising nodes and edges—enable quantification of order and disorder across multiple structural scales. GT descriptors extracted from electron microscopy images reveal short-, medium-, and long-range regularities, simultaneously accounting for polydispersity and statistical variation. Examples of fibrous nanocomposites composed of cellulose nanocrystals, metal nanowires, gold nanodendrites, and aramid nanofibers will show the utility and universality of this approach. Topometric relationships—where physical properties are derived from both GT descriptors and metric parameters—have been demonstrated for nanowire coatings, nanofibrous battery cathodes [5], and chiroptical nanodendrites. GT methods can be applied to both synthetic and evolution-optimized biomaterials, enabling quantitative replication—and ultimately outperformance—of biological blueprints. Importantly, the deliberate and controllable integration of disorder in materials design also offers a pathway to scalability, addressing critical bottlenecks in the advancement of modern nanocomposites.

The universality and accessibility of GT methods open the door for the utilization of highly variable natural nanomaterials in resource-constrained environments as demonstrated by the collaborative development of advanced materials for health, energy, water and agricultural technologies in several countries in Africa [6].