Neuron-Inspired Steiner Tree Networks for 3D Low-Density Metastructures

Three-dimensional (3D) micro-and nanostructures have played an important role in topological photonics, microfluidics, acoustic, and mechanical engineering. Incorporating biomimetic geometries into the design of metastructures has created low-density metamaterials with extraordinary physical and photonic properties. However, the use of surface-based biomimetic geometries restricts the freedom to tune the relative density, mechanical strength, and topological phase. The Steiner tree method inspired by the feature of the shortest connection distance in biological neural networks is applied, to create 3D metastructures and, through two-photon nanolithography, neuron-inspired 3D structures with nanoscale features are successfully achieved. Two solutions are presented to the 3D Steiner tree problem: the Steiner tree networks (STNs) and the twisted Steiner tree networks (T-STNs). STNs and T-STNs possess a lower density than surface-based metamaterials and that T-STNs have Young's modulus enhanced by 20% than the STNs. Through the analysis of the space groups and symmetries, a topological nontrivial Dirac-like conical dispersion in the T-STNs is predicted, and the results are based on calculations with true predictive power and readily realizable from microwave to optical frequencies. The neuron-inspired 3D metastructures opens a new space for designing low-density metamaterials and topological photonics with extraordinary properties triggered by a twisting degree-of-freedom.

Nanoscale optical writing through upconversion resonance energy transfer

Nanoscale optical writing using far-field super-resolution methods provides an unprecedented approach for high-capacity data storage. However, current nanoscale optical writing methods typically rely on photoinitiation and photoinhibition with high beam intensity, high energy consumption, and short device life span. We demonstrate a simple and broadly applicable method based on resonance energy transfer from lanthanide-doped upconversion nanoparticles to graphene oxide for nanoscale optical writing. The transfer of high-energy quanta from upconversion nanoparticles induces a localized chemical reduction in graphene oxide flakes for optical writing, with a lateral feature size of ~50 nm (1/20th of the wavelength) under an inhibition intensity of 11.25 MW cm-2 Upconversion resonance energy transfer may enable next-generation optical data storage with high capacity and low energy consumption, while offering a powerful tool for energy-efficient nanofabrication of flexible electronic devices.