Active learning of polarizable nanoparticle phase diagrams for the guided design of triggerable self-assembling superlattices

Dasetty, Siva; Coropceanu, Igor; Portner, Josh; Li, Jiyuan; de Pablo, Juan J.; Talapin, Dmitri; Ferguson, Andrew L.

doi:10.1039/d1me00187f

Title: Active learning of polarizable nanoparticle phase diagrams for the guided design of triggerable self-assembling superlattices

Journal Article · 24 January 2022 · Molecular Systems Design & Engineering

DOI: https://doi.org/10.1039/d1me00187f · OSTI ID:1841556

Dasetty, Siva ^[1]; Coropceanu, Igor ^[2]; Portner, Josh ^[2]; Li, Jiyuan ^[2]; de Pablo, Juan J. ^[2]; Talapin, Dmitri ^[2];

^[2]

Univ. of Chicago, IL (United States); University of Chicago
Univ. of Chicago, IL (United States)

Polarizable nanoparticles are of interest in materials science because of their rich and complex phase behavior that can be used to engineer nanostructured materials with long-range crystalline order. To understand and rationally navigate the design space of polarizable nanoparticles for self-assembling highly ordered superlattices, we developed a coarse-grained computational model to describe the nanoparticle-nanoparticle interactions in implicit solvent and employ the computationally efficient image method to model many-body polarization interactions. We conducted high-throughput virtual screening over a five-dimensional particle design space spanned by temperature, particle size, particle charge, particle dielectric, and solvent dielectric using enhanced sampling molecular dynamics calculations within an active learning framework to efficiently map out the regions of thermodynamic stability of the self-assembled aggregates. We validate our predictions in comparisons against small angle x-ray scattering measurements of gold nanoparticles surface functionalized with metal chalcogenide ligands. Lastly, we use our validated phase maps to computationally design switchable nanostructured materials capable of triggered assembly and disassembly as a function of temperature and solvent dielectric with potential applications as sensors, smart windows, optoelectronic devices, and in medical diagnostics.

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Research Organization:: Argonne National Laboratory (ANL), Argonne, IL (United States)

Sponsoring Organization:: USDOE; USDOE Office of Science (SC), Basic Energy Sciences (BES). Materials Sciences & Engineering Division

Grant/Contract Number:: AC02-06CH11357

OSTI ID:: 1841556

Journal Information:: Molecular Systems Design & Engineering, Journal Name: Molecular Systems Design & Engineering Journal Issue: 4 Vol. 7; ISSN 2058-9689

Publisher:: Royal Society of ChemistryCopyright Statement

Country of Publication:: United States

Language:: English

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