Singing Materials: Initial experiments in applying sonification to phonon spectra

Abstract

Solid materials may appear static, but at the atomic scale they are in constant vibrational motion. These vibrations, described by phonons, govern many key material properties, including structural stability, mechanical strength, optical behaviour, and thermal transport. Understanding phonon physics is therefore central to the rational design of materials with targeted functionalities. Singing Materials is a research project that explores how sonification can be applied to this domain. In this work, we introduce \texttt{SingingMaterials}, a modular Python package for sonifying materials simulation data. The software interfaces with the Materials Project database and is designed to be extensible, enabling the incorporation of additional sonification strategies and data sources. Built using the Sonification Toolkit \texttt{Strauss}, the current implementation supports three core approaches: spectral, synthesised, and sample-based. We demonstrate these approaches using phonon density-of-states data and evaluate their effectiveness through a user study, investigating whether listeners can distinguish differences in material properties from their auditory representations. The results show that sonification can provide an interpretable and complementary approach for exploring vibrational materials data.

Figures (4)

• Figure 1: Schematic illustration of atomic vibrations in a crystalline lattice. (a) Equilibrium (lowest energy) atomic positions in a 2D hexagonal (honeycomb) structure. (b) Example of a collective displacement pattern (phonon mode), where the green arrows indicate the displacement vectors of each atom. Each phonon mode is associated with a single vibrational frequency. The full vibrational behaviour of a material arises from the superposition of many such modes. Phonon visualisation is generated using https://henriquemiranda.github.io/phononwebsite
• Figure 2: Phonon projected density-of-states (PDOS) for boron arsenide (BAs). The x-axis shows the phonon frequency, and the y-axis shows the PDOS. The large mass difference between B and As leads to two distinct regions: a lower-frequency region dominated by As vibrations and a higher-frequency region dominated by B vibrations. The species-resolved phonon band centres (dashed lines) reflect this separation, while the interquartile ranges (dotted lines) show that As exhibits a broader spread of phonon frequencies. A phonon band gap separates the low- and high-frequency vibrations.
• Figure 3: Architecture of the SingingMaterials package. Phonon data is retrieved from the Materials Project Database via its API and processed within a modular Python workflow. The central object is the PhononDOSSonifier class which implements sonification methods using the Strauss toolkit. Sonifications are output as .wav files.
• Figure 4: Example usage of the three user interfaces for SingingMaterials. a) YAML file with sonification and mixing parameters specified; b) Python API for integration into existing workflows and the Jupyter ecosystem; c) command line interface for integration into remote and/or high-throughput workflows