Model Detail
phonon-40m-en
—phonon-40m-en is an audio model with 25M parameters released by gradium. The model is registered under the text-to-speech pipeline tag on Hugging Face, distributed under the permissive cc-by-nc-4.0 license.
phonon-40m-en ships with 25M parameters. The cc-by-nc-4.0 license is permissive, allowing commercial deployment and derivative work without per-seat fees, though attribution requirements still apply.
phonon-40m-en is best fit for speech recognition, transcription, or speech synthesis depending on the task head. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.
PhononBench-MP40: a spectrum-resolved benchmark dataset for phonon stability
arXiv:2607.22573v1 Announce Type: new Abstract: Imaginary phonon modes remain a practical bottleneck in computational materials screening because otherwise plausible structures can be locally dynamically unstable under a chosen workflow. Here we present PhononBench-MP40, a spectrum-resolved benchmar
PhononBench:A Large-Scale Phonon-Based Benchmark for Dynamical Stability in Crystal Generation
arXiv:2512.21227v3 Announce Type: replace-cross Abstract: In recent years, generative artificial intelligence has made significant advances in the design of crystalline materials, giving rise to approaches based on graph neural networks, diffusion models, and large language models. Existing evaluati
PFT: Phonon Fine-tuning for Machine Learned Interatomic Potentials
arXiv:2601.07742v4 Announce Type: replace-cross Abstract: Many materials properties depend on higher-order derivatives of the potential energy surface, yet machine learned interatomic potentials (MLIPs) trained with a standard loss on energy, force, and stress errors can exhibit error in curvature,
Physics Enhanced Deep Surrogates for the Phonon Boltzmann Transport Equation
arXiv:2512.05976v3 Announce Type: replace-cross Abstract: Designing materials with controlled heat flow at the nano-scale is central to advances in microelectronics, thermoelectrics, and energy-conversion technologies. At these scales, phonon transport follows the Boltzmann Transport Equation (BTE),
Lattice-to-Total Thermal Conductivity Ratio: A Phonon-Glass Electron-Crystal Descriptor for Data-Driven Thermoelectric Design
arXiv:2511.21213v2 Announce Type: replace-cross Abstract: Thermoelectrics (TEs) are promising candidates for energy harvesting with performance quantified by figure of merit, $ZT$. To accelerate the discovery of high-$ZT$ materials, efforts have focused on identifying compounds with low thermal cond
