![]() The Phonon Explorer software laid out the plots in around 30 minutes. The cuts were visually examined and 35 BZs were identified. Magenta curves represent individual phonon peaks determined through the multizone fit. (c) data points represent background-subtracted data. The binning was ΔH = ΔK = ΔL = ☐.1 reciprocal lattice units (r.l.u.). Zone center phonon data obtained from measured S (Q, ω) of Ba8Ga16Ge30. Spectra plotted in blue does not depict any identifiable one-phonon scattering, while the red spectra depict broad peaks originating from one or more overlapping phonon peaks.įigure 1. The dataset covered 1500 Brillouin zones and 1454 cuts were obtained (see Figure 1). The initial step includes the identification of zones where scattering from phonons of interest has substantial intensity. The scattering intensity of every phonon is evaluated by the phonon structure factors. To enhance data usage, the analysis should cover each BZ. This article elaborates on each step of the workflow along with various examples. The current study concentrates on phonons, as their scattering intensity is higher at large wavevectors. This was applied to experiments involving the measurement of all phonons and specific phonons or phonon branches. The workflow comprises steps like 1) Identifying relevant Brillouin zones, 2) Background determination and subtraction, 3) Optimization of binning, and 4) Employing multizone fit to extract phonon dispersions, linewidths, and eigenvectors. Research in the journal Quantum Beam Sciencepresented a software tool-Phonon Explorer-that carries out a data analysis workflow that addresses the present problems. Also, there is the possibility of making errors in several overlapping resolution-limited peaks for a single broad peak. This approach also had numerous disadvantages, however, like neutron scattering intensity being dependent on the Brillouin zone (BZ), and the chance for missing interesting features found in the data when only a subset of BZs is analyzed. X-ray scattering experiments or inelastic neutrons are powerful tools for evaluating phonon dispersions, and with the recent advancements in neutron scattering instrumentation, particularly the time-of-flight (TOF) instruments, researchers can effortlessly evaluate complete scattering spectra of single-crystal samples. Hence it is vital to extract linewidths, phonon energies, and eigenvectors directly from the data without depending on DFT. However, when it comes to materials having strong electronic correlations and magnetoelastic coupling, it falls short.Īt times, some analyses require the identification of reciprocal space points, in which phonon energies deviate from DFT predictions. Phonon spectra can be obtained in numerous ways, and one among them is from DFT calculations, which are precise and advanced. For instance, the phonon spectrum evaluates the thermal conductivity of materials, and phonon anomalies might indicate the Fermi surface nesting to the superconducting gap. Scientific studies generally require extensive investigations of phonon dispersions and other lattice dynamical effects in crystalline solids. With this software, the amount of time needed to determine phonon dispersions, eigenvectors, and line widths is drastically reduced. This article introduces a software called Phonon Explorer for analyzing large datasets of the neutron scattering function. However, DFT has its disadvantages, with the time taken being a significant one. Phonon Spectra evaluation is much needed in scientific studies and is carried out with density functional theory (DFT). ![]()
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