Mechanically robust lattices inspired by deep-sea glass sponges

This contains the data and code for the publication in Nature Materials.

View the Project on GitHub matheuscfernandes/sponge-lattice

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About the Paper

The article featured in Nature Materials was co-authered by: Matheus C. Fernandes, Joanna Aizenberg, James C. Weaver and Katia Bertoldi.

The corresponding authors are James C. Weaver (jweaver@seas.harvard.edu) and Katia Bertoldi (bertoldi@seas.harvard.edu). This repository is maintained by Matheus C.Fernandes (fernandes@seas.harvard.edu).

The Project

A great summary of the work can be watched in my TED-style Harvard Horizons talk below.

 

Abstract

The predominantly deep-sea hexactinellid sponges are known for their ability to construct remarkably complex skeletons from amorphous hydrated silica. The skeletal system of one such species of sponge, Euplectella aspergillum, consists of a square-grid-like architecture overlaid with a double set of diagonal bracings, creating a chequerboard-like pattern of open and closed cells. Here, using a combination of finite element simulations and mechanical tests on 3D-printed specimens of different lattice geometries, we show that the sponge’s diagonal reinforcement strategy achieves the highest buckling resistance for a given amount of material. Furthermore, using an evolutionary optimization algorithm, we show that our sponge-inspired lattice geometry approaches the optimum material distribution for the design space considered. Our results demonstrate that lessons learned from the study of sponge skeletal systems can be exploited for the realization of square lattice geometries that are geometrically optimized to avoid global structural buckling, with implications for improved material use in modern infrastructural applications.

 

Structure of Repository

To download the entire repository you may use this link: Download Here

The repository is devided into two sections:

  1. Code: contains all codes necessary to reproduce the numerical simulation results presented in the paper. Please note that you will need access to the Simulia ABAQUS software to be able to reproduce the data. Details on it’s use can be found in the paper.

  2. Data: contains all data necessary to re-plot the data shown in Figs. 2-5. Plotting.ipynb serves as an example on how to plot and utilize the data.

If there are additional suggested changes or improvements to the code, please submit a GitHub pull request and email me at (fernandes@seas.harvard.edu).