Combinatorial approaches for developing upconverting nanomaterials: high-throughput screening, modeling, and applications

Abstract

Colloidal nanoparticles doped with lanthanide ions can upconvert near-infrared light to visible frequencies, enabling the application of such materials to biological imaging and luminescent solar concentration. The optical properties of upconverting nanomaterials are determined by their combination of lanthanide dopants, by their morphology, by their host matrices, and by their surface ligands. Identifying ideal compositions and synthesis conditions for these materials can be tedious and time-consuming due to the large number of parameters to optimize. This review surveys the use of combinatorial strategies to rapidly screen and optimize diverse libraries of upconverting nanomaterials. I will review high-throughput techniques for synthesizing and characterizing large libraries of nanocrystals, and I will discuss theoretical methods for modeling the optical properties of lanthanide-doped materials. Case studies will illustrate the use of these approaches for optimizing the physical properties of upconverting nanoparticles, including cases in which unexpected phenomena were revealed. Finally, this review will identify promising opportunities in which combinatorial techniques could accelerate on-going research or facilitate the discovery of novel upconverting nanomaterials that overcome fundamental limitations of current material designs.