Ultrahigh Specific Strength by Bayesian Optimization of Carbon Nanolattices.

ABSTRACT: Nanoarchitected materials are at the frontier of metamaterial design and have set the benchmark for mechanical performance in several contemporary applications. However, traditional nanoarchitected designs with conventional topologies exhibit poor stress distributions and induce premature nodal failure. Here, using multi-objective Bayesian optimization and two-photon polymerization, optimized carbon nanolattices with an exceptional specific strength of 2.03 MPa m³ kg^-1 at low densities <215 kg m^-3 are created. Generative design optimization provides experimental improvements in strength and Young's modulus by as much as 118% and 68%, respectively, at equivalent densities with entirely different lattice failure responses. Additionally, the reduction of nanol

SUBMITTER: Serles P 

PROVIDER: S-EPMC11983246 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature