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PreprintCC BYChemRxiv

Transfer learning guides discovery of NIR-emissive DNA-stabilized silver nanoclusters

  • Anthea Segger1,2
  • Peter Mastracco1,2
  • I-Hsin Lin1,2
  • Kylie Lytle1,2
  • Anna Gonzàlez-Rosell1,2
  • Vanessa Rück3
  • Stacy M. Copp1,2,4,5,6
6 affiliations
  1. 1Department of Materials Science and Engineering
  2. 2University of California
  3. 3Nanoscience Center and Department of Chemistry, University of Copenhagen, Universitetsparken 5, Copenhagen, Denmark, 2100
  4. 4Department of Chemical & Biomolecular Engineering
  5. 5Department of Chemistry
  6. 6Department of Physics & Astronomy
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Abstract

Water-soluble near-infrared (NIR) emitters are of interest for imaging in the tissue transparency window. DNA-stabilized silver nanoclusters (DNA-AgN) hold promise for this spectral window, but it remains challenging to select oligonucleotides that stabilize NIR-emitting DNA-AgN. We address this challenge using transfer learning (TL), constructing a model that learns from experimental data for DNA-AgN stabilized by short 10-base oligonucleotides to then design longer oligonucleotides for larger, NIR-emitting nanoclusters. Using this model, we experimentally uncover 321 new DNA-AgN with peak emission beyond 800 nm, increasing design success by 710%. DNA-AgN designed using TL exhibit favorable properties including substantial emission above 1,000 nm, high fluorescence quantum yield, upconversion fluorescence, and a 14-electron count - the highest reported for DNA-AgN. These results demonstrate the power of TL for extracting physiochemical information from a limited parameter space and extrapolating these principles for broader design challenges, which is especially important when training data is scarce.

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Cite

BibTeXRIS
BibTeX
@misc{segger2026transfer,
  title = {{Transfer learning guides discovery of NIR-emissive DNA-stabilized silver nanoclusters}},
  author = {Anthea Segger and Peter Mastracco and I-Hsin Lin and Kylie Lytle and Anna Gonzàlez-Rosell and Vanessa Rück and Stacy M. Copp},
  howpublished = {ChemRxiv},
  year = {2026},
  month = sep,
  doi = {10.26434/chemrxiv.15008643/v1},
  url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008643/v1},
  note = {CC BY},
}
RIS
TY  - UNPB
TI  - Transfer learning guides discovery of NIR-emissive DNA-stabilized silver nanoclusters
AU  - Anthea Segger
AU  - Peter Mastracco
AU  - I-Hsin Lin
AU  - Kylie Lytle
AU  - Anna Gonzàlez-Rosell
AU  - Vanessa Rück
AU  - Stacy M. Copp
PY  - 2026
DA  - 2026/09/10
PB  - ChemRxiv
DO  - 10.26434/chemrxiv.15008643/v1
UR  - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008643/v1
AB  - Water-soluble near-infrared (NIR) emitters are of interest for imaging in the tissue transparency window. DNA-stabilized silver nanoclusters (DNA-AgN) hold promise for this spectral window, but it remains challenging to select oligonucleotides that stabilize NIR-emitting DNA-AgN. We address this challenge using transfer learning (TL), constructing a model that learns from experimental data for DNA-AgN stabilized by short 10-base oligonucleotides to then design longer oligonucleotides for larger, NIR-emitting nanoclusters. Using this model, we experimentally uncover 321 new DNA-AgN with peak emission beyond 800 nm, increasing design success by 710%. DNA-AgN designed using TL exhibit favorable properties including substantial emission above 1,000 nm, high fluorescence quantum yield, upconversion fluorescence, and a 14-electron count - the highest reported for DNA-AgN. These results demonstrate the power of TL for extracting physiochemical information from a limited parameter space and extrapolating these principles for broader design challenges, which is especially important when training data is scarce.
ER  -