Projectability disentanglement for accurate and automated electronic-structure Hamiltonians

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<oai_dc:dc xmlns:dc="" xmlns:oai_dc="" xmlns:xsi="" xsi:schemaLocation="">
  <dc:creator>Qiao, Junfeng</dc:creator>
  <dc:creator>Pizzi, Giovanni</dc:creator>
  <dc:creator>Marzari, Nicola</dc:creator>
  <dc:description>Maximally-localized Wannier functions (MLWFs) are a powerful and broadly used tool to characterize the electronic structure of materials, from chemical bonding to dielectric response to topological properties. Most generally, one can construct MLWFs that describe isolated band manifolds, e.g. for the valence bands of insulators, or entangled band manifolds, e.g. in metals or describing both the valence and the conduction manifolds in insulators. Obtaining MLWFs that describe a target manifold accurately and with the most compact representation often requires chemical intuition and trial and error, a challenging step even for experienced researchers and a roadblock for automated high-throughput calculations. Here, we present a very natural and powerful approach that provides automatically MLWFs spanning the occupied bands and their natural complement for the empty states, resulting in WĂŽannier Hamiltonian models that provide a tight-binding picture of optimized atomic orbitals in crystals. Key to the success of the algorithm is the introduction of a projectability measure for each Bloch state onto atomic orbitals (here, chosen from the pseudopotential projectors) that determines if that state should be kept identically, discarded, or mixed into a disentangling algorithm. We showcase the accuracy of our method by comparing a reference test set of 200 materials against the selected-columns-of-the-density-matrix (SCDM) algorithm, and its reliability by Wannierizing 21 737 materials from the Materials Cloud.</dc:description>
  <dc:publisher>Materials Cloud</dc:publisher>
  <dc:rights>Creative Commons Attribution 4.0 International</dc:rights>
  <dc:subject>Wannier functions</dc:subject>
  <dc:title>Projectability disentanglement for accurate and automated electronic-structure Hamiltonians</dc:title>