Erratum to: Charge transfer in graphene/polymer interfaces for CO2 detection

Nano Research - The order of the authors in the original version of this article was unfortunately incorrect on the first page and the first page of the ESM. Instead of Myungwoo Son1, Yusin Pak1,...     

Robust speech recognition based on independent vector analysis using harmonic frequency dependency

This paper describes an algorithm that enhances speech by independent vector analysis (IVA) using harmonic frequency dependency for robust speech recognition. While the conventional IVA exploits the full-band uniform dependencies of each source signal, a harmonic clique model is introduced to improve the enhancement performance by modeling strong dependencies among multiples of fundamental frequencies. An IVA-based learning algorithm is derived to consider the non-holonomic constraint and the minimal distortion principle to reduce the unavoidable distortion of IVA, and the minimum power distortionless response beamformer is used as a pre-processing step. In addition, the algorithm compares the log-spectral features of the enhanced speech and observed noisy speech to identify time–frequency segments corrupted by noise and restores those with the cluster-based missing feature reconstruction technique. Experimental results demonstrate that the proposed method enhances recognition performance significantly in noisy environments, especially with competing interference.     

Charge transfer in graphene/polymer interfaces for CO<Subscript>2</Subscript> detection

Understanding charge transfer processes between graphene and functional materials is crucial from the perspectives of fundamental sciences and potential applications, including electronic devices, photonic devices, and sensors. In this study, we present the charge transfer behavior of graphene and amine-rich polyethyleneimine (PEI) upon CO₂ exposure, which was significantly improved after introduction of hygroscopic polyethylene glycol (PEG) in humid air. By blending PEI and PEG, the number of protonated amine groups in PEI was remarkably increased in the presence of water molecules, leading to a strong electron doping effect on graphene. The presence of CO₂ gas resulted in a large change in the resistance of PEI/PEG-co-functionalized graphene because of the dramatic reduction of said doping effect, reaching a maximum sensitivity of 32% at 5,000 ppm CO₂ and an applied bias of 0.1 V in air with 60% relative humidity at room temperature. This charge transfer correlation will facilitate the development of portable graphene-based sensors for real-time gas detection and the extension of the applications of graphene-based electronic and photonic devices.

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Diode-less bilayer oxide (WO(x)-NbO(x)) device for cross-point resistive memory applications

The combination of a threshold switching device and a resistive switching (RS) device was proposed to suppress the undesired sneak current for the integration of bipolar RS cells in a cross-point array type memory. A simulation for this hybrid-type device shows that the matching of key parameters between switch element and memory element is an important issue. Based on the threshold switching oxides, a conceptual structure with a simple metal-oxide?1-oxide?2-metal stack was provided to accommodate the evolution trend. We show that electroformed W-NbO(x)-Pt devices can simultaneously exhibit both threshold switching and memory switching. A qualitative model was suggested to elucidate the unique properties in a W-NbO(x)-Pt stack, where threshold switching is associated with a localized metal-insulator transition in the NbO(x) bulk, and the bipolar RS derives from a redox at the tip of the localized filament at the WO(x)-NbO(x) interface. Such a simple metal-oxide-metal structure, with functionally separated bulk and interface effects, provides a fabrication advantage for future high-density cross-point memory devices.