4.8 Article

Spin Transition in Arrays of Gold Nanoparticles and Spin Crossover Molecules

Journal

ACS NANO
Volume 9, Issue 4, Pages 4496-4507

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acsnano.5b01103

Keywords

gold nanoparticles; spin crossover molecules; molecular charge transport devices; self-assembly; two-dimensional arrays

Funding

  1. NanoSci-E+ ERA scheme, a European initiative
  2. Agence Nationale de la Recherche [Labex NIE 11-LABX-0058_NIE, ANR-10-IDEX-0002-02]
  3. Science Foundation Ireland [10/IN.1/B3025]
  4. NBIPI
  5. Marie Curie Actions
  6. Slovak grant agency:VEGA [1/0522/14]
  7. Netherlands Organisation for Scientific Research, NWO

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We investigate if the functionality of spin crossover molecules is preserved when they are assembled into an interfacial device structure. Specifically, we prepare and investigate gold nanoparticle arrays, into which room-temperature spin crossover molecules are introduced, more precisely, [Fe(AcS-BPP)(2)](ClO4)(2), where AcS-BPP = (S)-(4-{[2,6-(dipyrazol-1-yl)pyrid-4-yl]ethynyl}phenyl)ethanethioate (in short, Fe(S-BPP)(2)). We combine three complementary experiments to characterize the molecule-nanoparticle structure in detail. Temperature-dependent Raman measurements provide direct evidence for a (partial) spin transition in the Fe(S-BPP)(2)-based arrays. This transition is qualitatively confirmed by magnetization measurements. Finally, charge transport measurements on the Fe(S-BPP)(2)-gold nanoparticle devices reveal a minimum in device resistance versus temperature, R(T), curves around 260-290 K. This is in contrast to similar networks containing passive molecules only that show monotonically decreasing R(T) characteristics. Backed by density functional theory calculations on single molecular conductance values for both spin states, we propose to relate the resistance minimum in R(T) to a spin transition under the hypothesis that (1) the molecular resistance of the high spin state is larger than that of the low spin state and (2) transport in the array is governed by a percolation model.

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