Superconductivity in correlated carbon nanotubes under pressure: A Bogoliubov-de Gennes study

In contrast to most microscopic theories of superconductivity based on the reciprocal space, the Bogoliubov-de Gennes (BdG) formalism provides a real-space alternative for addressing inhomogeneous systems. In this article, we study the superconducting states in correlated single-walled carbon nanotubes (SWNTs) with curvature and spin-orbit corrections, as well as the inter-tube interaction through a connecting molecule using an attractive Hubbard model. The results reveal a close relationship between the on-site superconducting gap and the single-electron local density of states. For the limiting case of independent large-diameter nanotubes, the BdG equations can be reduced to the standard Bardeen-Cooper-Schrieffer one with analytical solutions. Moreover, an optimal separation between nanotubes is found, which leads to a maximal superconducting critical temperature. This finding has a remarkable accordance with the experimental data obtained from Buckypapers built of boron doped SWNTs under external pressure.Comment: Accepted in Physica B: Condensed Matte

Fingerprints of a position-dependent Fermi velocity on scanning tunnelling spectra of strained graphene

Nonuniform strain in graphene induces a position dependence of the Fermi velocity, as recently demonstrated by scanning tunnelling spectroscopy experiments. In this work, we study the effects of a position-dependent Fermi velocity on the local density of states (LDOS) of strained graphene, without and with the presence of a uniform magnetic field. The variation of LDOS obtained from tight-binding calculations is successfully explained by analytical expressions derived within the Dirac approach. These expressions also rectify a rough Fermi velocity substitution used in the literature that neglects the strain-induced anisotropy. The reported analytical results could be useful for understanding the nonuniform strain effects on scanning tunnelling spectra of graphene, as well as when it is exposed to an external magnetic field.Comment: Revised version as published in JPC

Theory of Raman Scattering by Phonons in Germanium Nanostructures

Within the linear response theory, a local bond-polarization model based on the displacement–displacement Green’s function and the Born potential including central and non-central interatomic forces is used to investigate the Raman response and the phonon band structure of Ge nanostructures. In particular, a supercell model is employed, in which along the [001] direction empty-column pores and nanowires are constructed preserving the crystalline Ge atomic structure. An advantage of this model is the interconnection between Ge nanocrystals in porous Ge and then, all the phonon states are delocalized. The results of both porous Ge and nanowires show a shift of the highest-energy Raman peak toward lower frequencies with respect to the Raman response of bulk crystalline Ge. This fact could be related to the confinement of phonons and is in good agreement with the experimental data. Finally, a detailed discussion of the dynamical matrix is given in the appendix section

Oxygen Absorption in Free-Standing Porous Silicon: A Structural, Optical and Kinetic Analysis

Porous silicon (PSi) is a nanostructured material possessing a huge surface area per unit volume. In consequence, the adsorption and diffusion of oxygen in PSi are particularly important phenomena and frequently cause significant changes in its properties. In this paper, we study the thermal oxidation of p+-type free-standing PSi fabricated by anodic electrochemical etching. These free-standing samples were characterized by nitrogen adsorption, thermogravimetry, atomic force microscopy and powder X-ray diffraction. The results show a structural phase transition from crystalline silicon to a combination of cristobalite and quartz, passing through amorphous silicon and amorphous silicon-oxide structures, when the thermal oxidation temperature increases from 400 to 900 °C. Moreover, we observe some evidence of a sinterization at 400 °C and an optimal oxygen-absorption temperature about 700 °C. Finally, the UV/Visible spectrophotometry reveals a red and a blue shift of the optical transmittance spectra for samples with oxidation temperatures lower and higher than 700 °C, respectively

Seed-TTS: A Family of High-Quality Versatile Speech Generation Models

We introduce Seed-TTS, a family of large-scale autoregressive text-to-speech (TTS) models capable of generating speech that is virtually indistinguishable from human speech. Seed-TTS serves as a foundation model for speech generation and excels in speech in-context learning, achieving performance in speaker similarity and naturalness that matches ground truth human speech in both objective and subjective evaluations. With fine-tuning, we achieve even higher subjective scores across these metrics. Seed-TTS offers superior controllability over various speech attributes such as emotion and is capable of generating highly expressive and diverse speech for speakers in the wild. Furthermore, we propose a self-distillation method for speech factorization, as well as a reinforcement learning approach to enhance model robustness, speaker similarity, and controllability. We additionally present a non-autoregressive (NAR) variant of the Seed-TTS model, named $\text{Seed-TTS}_\text{DiT}$, which utilizes a fully diffusion-based architecture. Unlike previous NAR-based TTS systems, $\text{Seed-TTS}_\text{DiT}$ does not depend on pre-estimated phoneme durations and performs speech generation through end-to-end processing. We demonstrate that this variant achieves comparable performance to the language model-based variant and showcase its effectiveness in speech editing. We encourage readers to listen to demos at \url{https://bytedancespeech.github.io/seedtts_tech_report}