Agentic Workflow for High-Throughput Synthesis Campaigns: Mapping the Persistent Phosphor Ca2ZnSi2O7:Eu2+,Nd3+
- 1Department of Materials Science and Engineering
- 2University of Utah
- 383 Sciences
Abstract
The structural and spectroscopic record of a high-throughput synthesis campaign exceeds what experimenters can closely and accurately analyze with conventional tools alone. We report a workflow built for this problem: a language model agent operates an automated Rietveld phasesearch pipeline, Crystalyze Match, built on the open-source DARA engine, and then interprets the phases, optical spectra, and synthesis metadata. We demonstrate this workflow on a 48 sample campaign for the persistent phosphor Ca 2 ZnSi 2 O 7 :Eu 2+ ,Nd 3+ (doped hardystonite), a water-stable candidate alternative to SrAl 2 O 4 :Eu 2+ ,Dy 3+ for luminescent road markings. Within the campaign’s lifetime, the workflow mapped two decomposition pathways, incomplete reaction and zinc volatilization, that validate the two-step synthetic approach. The workflow also identified the fate of the rare-earth dopants: a silicate oxyapatite, Ca 2 (Eu,Nd) 8 (SiO 4 ) 6 O 2 , missed by prior manual analysis, is present in every doped sample. Human adjudication proved necessary as the search first scored the oxyapatite through a lanthanide-free proxy structure that scatters too weakly to register at low fractions, and a corrected-model re-screen of all 48 patterns recovered it. Though the rare-earth dopants appear to end up in the oxyapatite phase, emission rises monotonically with Eu content, and the material shows the target persistent luminescence, so where the emitting Eu 2+ resides remains unresolved. Our work highlights that human review and re-screening after every structure-model revision dramatically improve the trustworthiness of campaign-scale claims.
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BibTeX
@misc{jiang2026agentic,
title = {{Agentic Workflow for High-Throughput Synthesis Campaigns: Mapping the Persistent Phosphor Ca2ZnSi2O7:Eu2+,Nd3+}},
author = {Ziyang Jiang and Eric Riesel and Ian Naccarella and Taylor D. Sparks},
howpublished = {ChemRxiv},
year = {2026},
month = sep,
doi = {10.26434/chemrxiv.15009032/v1},
url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15009032/v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Agentic Workflow for High-Throughput Synthesis Campaigns: Mapping the Persistent Phosphor Ca2ZnSi2O7:Eu2+,Nd3+
AU - Ziyang Jiang
AU - Eric Riesel
AU - Ian Naccarella
AU - Taylor D. Sparks
PY - 2026
DA - 2026/09/18
PB - ChemRxiv
DO - 10.26434/chemrxiv.15009032/v1
UR - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15009032/v1
AB - The structural and spectroscopic record of a high-throughput synthesis campaign exceeds what experimenters can closely and accurately analyze with conventional tools alone. We report a workflow built for this problem: a language model agent operates an automated Rietveld phasesearch pipeline, Crystalyze Match, built on the open-source DARA engine, and then interprets the phases, optical spectra, and synthesis metadata. We demonstrate this workflow on a 48 sample campaign for the persistent phosphor Ca 2 ZnSi 2 O 7 :Eu 2+ ,Nd 3+ (doped hardystonite), a water-stable candidate alternative to SrAl 2 O 4 :Eu 2+ ,Dy 3+ for luminescent road markings. Within the campaign’s lifetime, the workflow mapped two decomposition pathways, incomplete reaction and zinc volatilization, that validate the two-step synthetic approach. The workflow also identified the fate of the rare-earth dopants: a silicate oxyapatite, Ca 2 (Eu,Nd) 8 (SiO 4 ) 6 O 2 , missed by prior manual analysis, is present in every doped sample. Human adjudication proved necessary as the search first scored the oxyapatite through a lanthanide-free proxy structure that scatters too weakly to register at low fractions, and a corrected-model re-screen of all 48 patterns recovered it. Though the rare-earth dopants appear to end up in the oxyapatite phase, emission rises monotonically with Eu content, and the material shows the target persistent luminescence, so where the emitting Eu 2+ resides remains unresolved. Our work highlights that human review and re-screening after every structure-model revision dramatically improve the trustworthiness of campaign-scale claims.
ER -