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Title: Energy Transfer Networks within Upconverting Nanoparticles Are Complex Systems with Collective, Robust, and History-Dependent Dynamics

Abstract

Applications of photon upconverting nanoparticles (UCNPs) in biological imaging and solar energy conversion demand that their anti-Stokes luminescence be both tunable and efficient. Rational design of more efficient UCNPs requires an understanding of energy transfer (ET) between their lanthanide dopants, dynamics that are typically characterized by measuring luminescence lifetimes. Existing knowledge, however, cannot explain basic observations in lifetime experiments, such as their dependence on excitation power, significantly limiting the generality and reliability of lifetime measurements. Here in this paper, we elucidate the origins of the ET dynamics and luminescence lifetimes of Yb 3+-, Er 3+-co-doped NaYF 4 UCNPs using time-resolved luminescence and novel applications of rate equations and stochastic simulations. Experiments and calculations consistently show that at high concentrations of Er 3+, the luminescence lifetimes of UCNPs decrease as much as six-fold when excitation power densities are increased over 6 orders of magnitude. Since power-dependent lifetimes cannot be explained by intrinsic relaxation rates of individual transitions, we analyze lifetime data by treating each UCNP as a complex ET network. We find that UCNP ET networks exhibit four distinguishing characteristics of complex systems: collectivity, nonlinear feedback, robustness, and history dependence. We conclude that power-dependent lifetimes are the consequence of thousands ofmore » minor relaxation pathways that act collectively to depopulate and repopulate Er 3+ emitting levels. These ET pathways are dependent on past excitation power because they originate from excited donors and excited acceptors; however, each transition has an unexpectedly small impact on lifetimes due to negative feedback in the network. This robustness is determined by systematically “knocking out”, or disabling, ET transitions in kinetic models. Our classification of UCNP ET networks as complex systems explains why UCNP luminescence lifetimes do not match the intrinsic lifetimes of emitting states. In the future, UCNP networks may be engineered to rival the complexity of biological networks that pattern features with unmatched precision.« less

Authors:
 [1];  [2];  [3];  [1];  [1];  [4]; ORCiD logo [1]; ORCiD logo [1]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Dalian Maritime Univ., Dalian, Liaoning (China)
  3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States)
  4. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Columbia Univ., New York, NY (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22); National Research Foundation of Korea (NRF)
OSTI Identifier:
1580361
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Physical Chemistry. C
Additional Journal Information:
Journal Volume: 123; Journal Issue: 4; Journal ID: ISSN 1932-7447
Publisher:
American Chemical Society
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY

Citation Formats

Teitelboim, Ayelet, Tian, Bining, Garfield, David J., Fernandez-Bravo, Angel, Gotlin, Adam C., Schuck, P. James, Cohen, Bruce E., and Chan, Emory M. Energy Transfer Networks within Upconverting Nanoparticles Are Complex Systems with Collective, Robust, and History-Dependent Dynamics. United States: N. p., 2019. Web. doi:10.1021/acs.jpcc.9b00161.
Teitelboim, Ayelet, Tian, Bining, Garfield, David J., Fernandez-Bravo, Angel, Gotlin, Adam C., Schuck, P. James, Cohen, Bruce E., & Chan, Emory M. Energy Transfer Networks within Upconverting Nanoparticles Are Complex Systems with Collective, Robust, and History-Dependent Dynamics. United States. doi:10.1021/acs.jpcc.9b00161.
Teitelboim, Ayelet, Tian, Bining, Garfield, David J., Fernandez-Bravo, Angel, Gotlin, Adam C., Schuck, P. James, Cohen, Bruce E., and Chan, Emory M. Tue . "Energy Transfer Networks within Upconverting Nanoparticles Are Complex Systems with Collective, Robust, and History-Dependent Dynamics". United States. doi:10.1021/acs.jpcc.9b00161. https://www.osti.gov/servlets/purl/1580361.
@article{osti_1580361,
title = {Energy Transfer Networks within Upconverting Nanoparticles Are Complex Systems with Collective, Robust, and History-Dependent Dynamics},
author = {Teitelboim, Ayelet and Tian, Bining and Garfield, David J. and Fernandez-Bravo, Angel and Gotlin, Adam C. and Schuck, P. James and Cohen, Bruce E. and Chan, Emory M.},
abstractNote = {Applications of photon upconverting nanoparticles (UCNPs) in biological imaging and solar energy conversion demand that their anti-Stokes luminescence be both tunable and efficient. Rational design of more efficient UCNPs requires an understanding of energy transfer (ET) between their lanthanide dopants, dynamics that are typically characterized by measuring luminescence lifetimes. Existing knowledge, however, cannot explain basic observations in lifetime experiments, such as their dependence on excitation power, significantly limiting the generality and reliability of lifetime measurements. Here in this paper, we elucidate the origins of the ET dynamics and luminescence lifetimes of Yb3+-, Er3+-co-doped NaYF4 UCNPs using time-resolved luminescence and novel applications of rate equations and stochastic simulations. Experiments and calculations consistently show that at high concentrations of Er3+, the luminescence lifetimes of UCNPs decrease as much as six-fold when excitation power densities are increased over 6 orders of magnitude. Since power-dependent lifetimes cannot be explained by intrinsic relaxation rates of individual transitions, we analyze lifetime data by treating each UCNP as a complex ET network. We find that UCNP ET networks exhibit four distinguishing characteristics of complex systems: collectivity, nonlinear feedback, robustness, and history dependence. We conclude that power-dependent lifetimes are the consequence of thousands of minor relaxation pathways that act collectively to depopulate and repopulate Er3+ emitting levels. These ET pathways are dependent on past excitation power because they originate from excited donors and excited acceptors; however, each transition has an unexpectedly small impact on lifetimes due to negative feedback in the network. This robustness is determined by systematically “knocking out”, or disabling, ET transitions in kinetic models. Our classification of UCNP ET networks as complex systems explains why UCNP luminescence lifetimes do not match the intrinsic lifetimes of emitting states. In the future, UCNP networks may be engineered to rival the complexity of biological networks that pattern features with unmatched precision.},
doi = {10.1021/acs.jpcc.9b00161},
journal = {Journal of Physical Chemistry. C},
number = 4,
volume = 123,
place = {United States},
year = {2019},
month = {1}
}

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Works referencing / citing this record:

Recent insights into upconverting nanoparticles: spectroscopy, modeling, and routes to improved luminescence
journal, January 2019

  • Tessitore, Gabriella; Mandl, Gabrielle A.; Brik, Mikhail G.
  • Nanoscale, Vol. 11, Issue 25
  • DOI: 10.1039/c9nr02291k