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Single-crystal X-ray data reveal the structure of a 28-silver-atom cluster wrapped within two DNA oligomers. In the crystalline state, two chlorido ligands are detected, which are absent in the mass ....

Recent studies have reported long-range charge transport in peptide- and protein-based fibers and wires, rendering this class of materials as promising charge-conducting interfaces between biological systems and electronic devices. In the complex molecular environment of biomolecular building blocks, however, it is unclear which chemical and structural dynamic features support electronic conductivity. Here, we investigate the role of finite temperature fluctuations on the electronic structure and its implications for conductivity in a peptide-based fiber material composed of an antiparallel coiled coil hexamer, ACC-Hex, building block. All-atom classical molecular dynamics (MD) and first-principles density functional theory (DFT) are combined with interpretable machine learning (ML) to understand the relationship between physical and electronic structure of the peptide dimer subunit of ACC-Hex. For 1101 unique MD “snapshots” of the ACC peptide dimer, hybrid DFT calculations predict a significant variation of near-gap orbital energies among snapshots, with an increase in the predicted number of nearly degenerate states near the highest occupied molecular orbital (HOMO), which suggests improved conductivity. Interpretable ML is then used to investigate which nuclear conformations increase the number of nearly degenerate states. We find that molecular conformation descriptors of interphenylalanine distance and orientation are, as expected, highly correlated with increased state density near the HOMO. Unexpectedly, we also find that descriptors of tightly coiled peptide backbones, as well as those describing the change in the electrostatic environment around the peptide dimer, are important for predicting the number of hole-accessible states near the HOMO. Our study illustrates the utility of interpretable ML as a tool for understanding complex trends in large-scale ab initio simulations.

This study presents a dual-emissive DNA-stabilized silver nanocluster with a nanosecond-lived NIR-I emission band and a microsecond-lived NIR-II emission band. Mass spectrometry establishes that the ...

Near-infrared (NIR) emitters with high two-photon absorption (2PA) cross-sections are of interest to enable in vivo imaging in the tissue transparency windows. This study explores the potential of DNA...

Step into the forefront of scientific discovery at the world’s leading international scientific gathering for materials research. Our annual fall event returns to the culturally-rich city of Boston, M...

‪PhD Candidate, University of California, Irvine‬ - ‪‪Cited by 229‬‬ - ‪soft materials‬ - ‪metal nanoclusters‬