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Multifunctional structural design of graphene thermoelectrics by Bayesian optimization.

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Optimizing graphene nanoribbons (GNRs) for thermoelectrics breaks property correlations. This study achieved over five times higher efficiency than random search, enhancing the figure of merit by 11 times.

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Area of Science:

  • Materials Science
  • Condensed Matter Physics
  • Nanotechnology

Background:

  • Materials development faces challenges in meeting conflicting multifunctional demands, such as optimizing thermoelectric properties.
  • Thermoelectric conversion requires high electrical conductivity, high Seebeck coefficient, and low thermal conductivity, properties typically inversely correlated.
  • Nanostructuring offers a route to decouple these properties, but optimal design is complex due to vast structural possibilities.

Purpose of the Study:

  • To perform multifunctional structural optimization of graphene nanoribbons (GNRs) as a representative thermoelectric material.
  • To resolve the trade-off between conflicting thermoelectric properties through advanced computational methods.
  • To develop a generalizable optimization framework for multifunctional material design.

Main Methods:

  • Utilized graphene nanoribbons (GNRs) as a model system for thermoelectric material optimization.
  • Employed alternating multifunctional (phonon and electron) transport calculations.
  • Integrated Bayesian optimization to efficiently explore the large design space and identify optimal structures.

Main Results:

  • Achieved multifunctional structural optimization yielding efficiencies over five times greater than random search.
  • Optimized GNRs with antidots demonstrated an enhancement of the thermoelectric figure of merit by up to 11 times compared to pristine GNRs.
  • Identified optimal structures providing physical insights into independent tuning of electron and phonon transport via zigzag edge states and aperiodic nanostructuring.

Conclusions:

  • The developed optimization framework successfully addresses the multifunctional design challenge in thermoelectric materials.
  • Optimized GNR structures significantly boost thermoelectric performance, offering a pathway to highly efficient thermoelectric devices.
  • The demonstrated approach is applicable to a broader range of multifunctional material design problems across various scientific and engineering fields.