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T Trittel1, K Harth1,2, C Klopp1

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Summary
This summary is machine-generated.

Controlled material transport in thin smectic films is achieved using temperature differences. This phenomenon, observed in microgravity, demonstrates Marangoni effects driving flow towards colder or hotter edges based on surface tension properties.

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Area of Science:

  • Physics
  • Materials Science
  • Fluid Dynamics

Background:

  • Thin freely suspended smectic films exhibit complex behaviors under thermal gradients.
  • Marangoni effects, driven by surface tension gradients, are known to influence fluid flow.
  • Understanding material transport in microgravity is crucial for advanced material processing.

Purpose of the Study:

  • To demonstrate and quantify controlled material transport in thin smectic films driven by temperature differences.
  • To investigate the role of Marangoni effects in directing material flow within these films.
  • To develop and validate a model predicting material transport behavior.

Main Methods:

  • Experiments were conducted on submicrometer thick smectic films with millimeter lateral extensions.
  • Studies were performed in microgravity conditions during suborbital rocket flights.
  • In-plane temperature differences were applied to induce Marangoni effects, and material accumulation was observed.

Main Results:

  • Directed material transport was observed, with flow direction dependent on the surface tension's temperature coefficient (dσ/dT).
  • Materials with dσ/dT<0 showed transport from hot to cold edges, accumulating at the cold edge.
  • Materials with dσ/dT>0 exhibited reverse transport from cold to hot edges.
  • A quantitative model was developed, highlighting the relevance of the temperature difference between thermopads over the in-plane gradient.

Conclusions:

  • Temperature differences effectively control material transport in thin smectic films via Marangoni effects.
  • The direction of transport is predictable based on the material's surface tension temperature coefficient.
  • The developed model accurately describes the observed phenomena and identifies key driving parameters.