Impact of Dopant Compensation on Graded <i>p</i>–<i>n</i> Junctions in Si Nanowires

The modulation between different doping species required to produce a diode in VLS-grown nanowires (NWs) yields a complex doping profile, both axially and radially, and a gradual junction at the interface. We present a detailed analysis of the dopant distribution around the junction. By combining surface potential measurements, performed by KPFM, with finite element simulations, we show that the highly doped (5 × 10¹⁹ cm^–3) shell surrounding the NW can screen the junction’s built in voltage at shell thickness as low as 3 nm. By comparing NWs with high and low doping contrast at the junction, we show that dopant compensation dramatically decreases the electrostatic width of the junction and results in relatively low leakage currents

Evidence for Deep Acceptor Centers in Plant Photosystem I Crystals

Dry micrometer-thick crystalline photosystem I (PSI) has been shown to generate unprecedented large photovoltage under illumination. We use variable-temperature Kelvin probe force microscopy to show that deep acceptor centers are responsible for this anomalous photovoltage. We assumed that these centers are located close to the positively charged F_B²⁺ clusters, forming a coupled center that effectively captures the photoexcited electron into a deep state. We extract the main inherent parameters of the deep centers, which are extremely important in the potential use of photosynthetic proteins in various optoelectronic devices

Density and Energy Distribution of Interface States in the Grain Boundaries of Polysilicon Nanowire

Wafer-scale fabrication of semiconductor nanowire devices is readily facilitated by lithography-based top-down fabrication of polysilicon nanowire (P-SiNW) arrays. However, free carrier trapping at the grain boundaries of polycrystalline materials drastically changes their properties. We present here transport measurements of P-SiNW array devices coupled with Kelvin probe force microscopy at different applied biases. By fitting the measured P-SiNW surface potential using electrostatic simulations, we extract the longitudinal dopant distribution along the nanowires as well as the density of grain boundaries interface states and their energy distribution within the band gap

Room Temperature Observation of Quantum Confinement in Single InAs Nanowires

Quantized conductance in nanowires can be observed at low temperature in transport measurements; however, the observation of sub-bands at room temperature is challenging due to temperature broadening. So far, conduction band splitting at room temperature has not been observed in III–V nanowires mainly due to the small energetic separations between the sub-bands. We report on the measurement of conduction sub-bands at room temperature, in single InAs nanowires, using Kelvin probe force microscopy. This method does not rely on charge transport but rather on measurement of the nanowire Fermi level position as carriers are injected into a single nanowire transistor. As there is no charge transport, electron scattering is no longer an issue, allowing the observation of the sub-bands at room temperature. We measure the energy of the sub-bands in nanowires with two different diameters, and obtain excellent agreement with theoretical calculations based on an empirical tight-binding model

Control of the Intrinsic Sensor Response to Volatile Organic Compounds with Fringing Electric Fields

The ability to control surface–analyte interaction allows tailoring chemical sensor sensitivity to specific target molecules. By adjusting the bias of the shallow p–n junctions in the electrostatically formed nanowire (EFN) chemical sensor, a multiple gate transistor with an exposed top dielectric layer allows tuning of the fringing electric field strength (from 0.5 × 10⁷ to 2.5 × 10⁷ V/m) above the EFN surface. Herein, we report that the magnitude and distribution of this fringing electric field correlate with the intrinsic sensor response to volatile organic compounds. The local variations of the surface electric field influence the analyte–surface interaction affecting the work function of the sensor surface, assessed by Kelvin probe force microscopy on the nanometer scale. We show that the sensitivity to fixed vapor analyte concentrations can be nullified and even reversed by varying the fringing field strength, and demonstrate selectivity between ethanol and <i>n</i>-butylamine at room temperature using a single transistor without any extrinsic chemical modification of the exposed SiO₂ surface. The results imply an electric-field-controlled analyte reaction with a dielectric surface extremely compelling for sensitivity and selectivity enhancement in chemical sensors

Dynamic Range Enhancement Using the Electrostatically Formed Nanowire Sensor

The evolution of nanotechnology based sensors has enabled detection of ultra-low-level concentrations of target species owing to their high aspect ratio. However, these sensors have a limited dynamic range at room temperature characterized by saturation in the sensor response following certain concentration exposure. In this work, we show that the dynamic range towards a target gas can be significantly enhanced using the electrostatically formed nanowire sensor. The size and shape of the nanowire conducting channel are defined and tuned by controlling the bias applied to the surrounding gates. The nanowires thus formed vary in their response, detection limit, and dynamic range for a given target gas exposure depending on its size and shape. By electrostatically tuning to the appropriate nanowire, we can not only enhance the sensor response in the low concentration regime, but also broaden the overall dynamic range capacity using a single sensor. It is demonstrated that the sensor is capable of detecting ∼26–2030 ppm ethanol and ∼40–2800 ppm of acetone efficiently with reasonably high response (≥20%) throughout the whole range. The broad dynamic range concept is also demonstrated using scanning gate microscopy measurements of the device. This represents the first nanotechnology-inspired work towards tunable dynamic range of a sensor using a single electronic device

Antenna Effect in Large Area Palladium-Coated Electrostatically Formed Silicon Nanowire for Ppb Level Hydrogen Sensing

An electrostatically formed nanowire (EFN) with an electrostatically formed channel is a highly sensitive and selective sensor for detecting various gases and volatile organic compounds. We report here on a specially designed large-area sensing antenna EFN that improves the response of the conventional EFN by several orders of magnitude, thus allowing the sensing of very low analyte concentrations. We have fabricated an EFN with a large area (∼3500 μm2) palladium sensing layer and show that its response in a dry air atmosphere to 30 ppb H2 is ∼90% at 60 °C. We show that this unprecedented sensitivity is due to the antenna effect, which causes the charged H2 species to drift to the region right above the EFN transistor channel. Electrostatic modeling shows good agreement with the measured antenna effect and predicts that this design paves the way to an ultrasensitive very-large-scale integration (VLSI) based gas sensing platform

Why Lead Methylammonium Tri-Iodide Perovskite-Based Solar Cells Require a Mesoporous Electron Transporting Scaffold (but Not Necessarily a Hole Conductor)

CH₃NH₃PbI₃-based solar cells were characterized with electron beam-induced current (EBIC) and compared to CH₃NH₃PbI_3–<i>x</i>Cl_<i>x</i> ones. A spatial map of charge separation efficiency in working cells shows p-i-n structures for both thin film cells. Effective diffusion lengths, <i>L</i>_D, (from EBIC profile) show that holes are extracted significantly more efficiently than electrons in CH₃NH₃PbI₃, explaining why CH₃NH₃PbI₃-based cells require mesoporous electron conductors, while CH₃NH₃PbI_3–<i>x</i>Cl_<i>x</i> ones, where <i>L</i>_D values are comparable for both charge types, do not

Spatially Resolved Correlation of Active and Total Doping Concentrations in VLS Grown Nanowires

Controlling axial and radial dopant profiles in nanowires is of utmost importance for NW-based devices, as the formation of tightly controlled electrical junctions is crucial for optimization of device performance. Recently, inhomogeneous dopant profiles have been observed in vapor–liquid–solid grown nanowires, but the underlying mechanisms that produce these inhomogeneities have not been completely characterized. In this work, P-doping profiles of axially modulation-doped Si nanowires were studied using nanoprobe scanning Auger microscopy and Kelvin probe force microscopy in order to distinguish between vapor–liquid–solid doping and the vapor–solid doping. We find that both mechanisms result in radially inhomogeneous doping, specifically, a lightly doped core surrounded by a heavily doped shell structure. Careful design of dopant modulation enables the contributions of the two mechanisms to be distinguished, revealing a surprisingly strong reservoir effect that significantly broadens the axial doping junctions

Selective Sensing of Volatile Organic Compounds Using an Electrostatically Formed Nanowire Sensor Based on Automatic Machine Learning

With the development of Internet of Things technology, various sensors are under intense development. Electrostatically formed nanowire (EFN) gas sensors are multigate Si sensors based on CMOS technology and have the unique advantages of ultralow power consumption and very large-scale integration (VLSI) compatibility for mass production. In order to achieve selectivity, machine learning is required to accurately identify the detected gas. In this work, we introduce automatic learning technology, by which the common algorithms are sorted and applied to the EFN gas sensor. The advantages and disadvantages of the top four tree-based model algorithms are discussed, and the unilateral training models are ensembled to further improve the accuracy of the algorithm. The analyses of two groups of experiments show that the CatBoost algorithm has the highest evaluation index. In addition, the feature importance of the classification is analyzed from the physical meaning of electrostatically formed nanowire dimensions, paving the way for model fusion and mechanism exploration