Abstract
This article introduces software called Phonon Explorer that implements a data mining workflow for large datasets of the neutron scattering function, S(Q, ω), measured on time-of-flight neutron spectrometers. This systematic approach takes advantage of all useful data contained in the dataset. It includes finding Brillouin zones where specific phonons have the highest scattering intensity, background subtraction, combining statistics in multiple Brillouin zones, and separating closely spaced phonon peaks. Using the software reduces the time needed to determine phonon dispersions, linewidths, and eigenvectors by more than an order of magnitude.
Highlights
Many scientific studies require comprehensive investigations of phonon dispersions and other lattice dynamical effects in crystalline solids
The phonon spectrum determines in large part the thermal conductivity of materials [1]; phonons have been implicated in charge density wave formation and structural instabilities [2,3,4]; so-called phonon anomalies may indicate the Fermi surface nesting or a coupling to the superconducting gap [5,6]; comparing experimental phonon dispersions with model predictions can validate or invalidate theoretical models [7]
One way to obtain phonon spectra is from density functional theory (DFT) calculations [8]
Summary
Many scientific studies require comprehensive investigations of phonon dispersions and other lattice dynamical effects in crystalline solids. DFT results for phonon eigenvectors are often only qualitatively accurate even when dispersions closely match experiment, especially in the vicinity of branch crossings. These calculations are difficult or impossible for materials with very large unit cells. Even limiting the investigation to high-symmetry directions in momentum space still requires performing thousands of cuts if one wants to look for peaks corresponding to every phonon in every BZ. This is extremely time-consuming, even with the aid of ad-hoc scripts, and is usually not done. This article introduces a recently released software tool, Phonon Explorer, that implements a data analysis workflow that solves these problems and includes automated background subtraction
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