Spectral, optical and transport properties of the adiabatic anisotropic Holstein model: Application to slightly doped organic semiconductors
C.A. Perroni, A. Nocera, V. Marigliano Ramaglia, and V. Cataudella

TL;DR
This study investigates the spectral, optical, and transport properties of an anisotropic Holstein model relevant to organic semiconductors, revealing temperature-dependent spectral broadening, optical conductivity features, and a transition from metallic to insulating behavior at low densities.
Contribution
It applies multiple theoretical approaches to analyze the anisotropic Holstein model, providing new insights into temperature effects and density-dependent transport in organic semiconductors.
Findings
Spectral functions broaden with temperature, reducing quasi-particle accuracy.
Optical conductivity shows Drude behavior at weak coupling and low-frequency peaks at intermediate coupling.
Mobility exhibits a power-law temperature dependence and transitions from metallic to insulating at low densities.
Abstract
Spectral, optical and transport properties of an anisotropic three-dimensional Holstein model are studied within the adiabatic approximation. The parameter regime is appropriate for organic semiconductors used in single crystal based field effect transistors. Different approaches have been used to solve the model: self-consistent Born approximation valid for weak electron-phonon coupling, coherent potential approximation exact for infinite dimensions, and numerical diagonalization for finite lattices. With increasing temperature, the width of the spectral functions gets larger and larger making the approximation of quasi-particle less accurate. On the contrary, their peak positions are never strongly renormalized in comparison with the bare ones. As expected, the density of states is characterized by an exponential tail corresponding to localized states at low temperature. For weak…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
