Self Assembly of Semiconductor Helices with Specific Twist Counts

Helical geometry is utilized for a broad range of biological structures that span from the double helix data storage structure of DNA to the mechanical propulsion mechanism of a bacterium or a biomimetic nanobot. The combination of a continuous helical geometry with charge transport and storage properties of semiconductor materials however has recently served as a focus in the development of optoelectronics, photocatalysts, and biomimetics. Notably the self-assembly behavior of chiral cadmium telluride (CdTe) nanoparticles into continuous semiconductor helices has shown the strong tuneable chiroptical activity in the near infrared (NIR) segment of the electromagnetic spectrum that is necessary for these emerging applications. Though recent investigations have demonstrated the potential of post-synthesis mechanisms to tune both the chiroptical properties and morphologies of semiconductor helices, this work focuses on the optimization of the self-assembly process to achieve helices of desired twist count with chiroptical activity that can be predicted by computational models.