DNA-stabilized silver clusters are remarkable for the selection of fluorescence color by the sequence of the stabilizing DNA oligomer. Yet despite a growing number of applications that exploit this property, no large-scale studies have probed origins of cluster color or whether certain colors occur more frequently than others. Here we employ a set of 684 randomly chosen 10-base oligomers to address these questions. Rather than a flat distribution, we find that specific color bands dominate. Cluster size data indicate that these “magic colors” originate from the existence of magic numbers for DNA-stabilized silver clusters, which differ from those of spheroidal gold clusters stabilized by small-molecule ligands. Elongated cluster structures, enforced by multiple base ligands along the DNA, can account for both magic number sizes and color variation around peak wavelength populations.

DNA nucleobase sequence controls the size of DNA-stabilized silver clusters, leading to their well-known yet little understood sequence-tuned colors. The enormous space of possible DNA sequences for templating clusters has challenged the understanding of how sequence selects cluster properties and has limited the design of applications that employ these clusters. We investigate the genomic role of DNA sequence for fluorescent silver clusters using a data-driven approach. Employing rapid parallel silver cluster synthesis and fluorimetry, we determine the fluorescence spectra of silver cluster products stabilized by 1432 distinct DNA oligomers. By applying pattern recognition algorithms to this large experimental data set, we discover certain DNA base patterns, or "motifs," that correlate to silver clusters with similar fluorescence spectra. These motifs are employed in machine learning classifiers to predictively design DNA template sequences for specific fluorescence color bands. Our method improves selectivity of templates by 330% for silver clusters with peak emission wavelengths beyond 660 nm. The discovered base motifs also provide physical insights into how DNA sequence controls silver cluster size and color. This predictive design approach for color of DNA-stabilized silver clusters exhibits the potential of machine learning and data mining to increase the precision and efficiency of nanomaterials design, even for a soft-matter-inorganic hybrid system characterized by an extremely large parameter space.

Discriminative base motifs within DNA templates for fluorescent silver clusters are identified using methods that combine large experimental data sets with machine learning tools for pattern recognition. Combining the discovery of certain multibase motifs important for determining fluorescence brightness with a generative algorithm, the probability of selecting DNA templates that stabilize fluorescent silver clusters is increased by a factor of >3.

DNA-protected silver clusters (AgN-DNA) possess unique fluorescence properties that depend on the specific DNA template that stabilizes the cluster. They exhibit peak emission wavelengths that range across the visible and near-IR spectrum. This wide color palette, combined with low toxicity, high fluorescence quantum yields of some clusters, low synthesis costs, small cluster sizes and compatibility with DNA are enabling many applications that employ AgN-DNA. Here we review what is known about the underlying composition and structure of AgN-DNA, and how these relate to the optical properties of these fascinating, hybrid biomolecule-metal cluster nanomaterials. We place AgN-DNA in the general context of ligand-stabilized metal clusters and compare their properties to those of other noble metal clusters stabilized by small molecule ligands. The methods used to isolate pure AgN-DNA for analysis of composition and for studies of solution and single-emitter optical properties are discussed. We give a brief overview of structurally sensitive chiroptical studies, both theoretical and experimental, and review experiments on bringing silver clusters of distinct size and color into nanoscale DNA assemblies. Progress towards using DNA scaffolds to assemble multi-cluster arrays is also reviewed.