Machine learning-enabled feature classification of evaporation-driven multi-scale 3D printing.

The freeform generation of active electronics can impart advanced optical, computational, or sensing capabilities to an otherwise passive construct by overcoming the geometrical and mechanical dichotomies between conventional electronics manufacturing technologies and a broad range of three-dimensional (3D) systems. Previous work has demonstrated the capability to entirely 3D print active electronics such as photodetectors and light-emitting diodes by leveraging an evaporation-driven multi-scale 3D printing approach. However, the evaporative patterning process is highly sensitive to print parameters such as concentration and ink composition.

Nanomaterial Patterning in 3D Printing.

The synergistic integration of nanomaterials with 3D printing technologies can enable the creation of architecture and devices with an unprecedented level of functional integration. In particular, a multiscale 3D printing approach can seamlessly interweave nanomaterials with diverse classes of materials to impart, program, or modulate a wide range of functional properties in an otherwise passive 3D printed object. However, achieving such multiscale integration is challenging as it requires the ability to pattern, organize, or assemble nanomaterials in a 3D printing process.

3D printed nanomaterial-based electronic, biomedical, and bioelectronic devices.

The ability to seamlessly integrate functional materials into three-dimensional (3D) constructs has been of significant interest, as it can enable the creation of multifunctional devices. Such integration can be achieved with a multiscale, multi-material 3D printing strategy. This technology has enabled the creation of unique devices such as personalized tissue regenerative scaffolds, biomedical implants, 3D electronic devices, and bionic constructs which are challenging to realize with conventional manufacturing processes.