Mid-infrared wavelengths are called the molecular fingerprint region because it contains the fundamental vibrational modes inherent to the substances of interest. Since the mid-infrared spectrum can ...provide non-destructive identification and quantitative analysis of unknown substances, miniaturized mid-infrared spectrometers for on-site diagnosis have attained great concern. Filter-array based on-chip spectrometer has been regarded as a promising alternative. In this study, we explore a way of applying a pillar-type plasmonic nanodiscs array, which is advantageous not only for excellent tunability of resonance wavelength but also for 2-dimensional integration through a single layer process, to the multispectral filter array for the on-chip spectrometer. We theoretically and experimentally investigated the optical properties of multi-periodic triangular lattices of metal nanodiscs array that act as stopband filters in the mid-infrared region. Soft-mold reverse nanoimprint lithography with a subsequent lift-off process was employed to fabricate the multispectral filter array and its filter function was successfully extracted using a Fourier transform infrared microscope. With the measured filter function, we tested the feasibility of target spectrum reconstruction using a Tikhonov regularization method for an ill-posed linear problem and evaluated its applicability to the infrared spectroscopic sensor that monitors an oil condition. These results not only verify that the multispectral filter array composed of stopband filters based on the metal nanodiscs array when combined with the spectrum reconstruction technique, has great potential for use to a miniaturized mid-infrared on-chip spectrometer, but also provide effective guidance for the filter design.
A novel nano-plasmonic sensing platform based on vertical conductive bridge was suggested as an alternative geometry for taking full advantages of unique properties of conductive junction while ...substantially alleviating burdens in lithographic process. The effects of various geometrical parameters on the plasmonic properties were systematically investigated. Theoretical simulation on this structure demonstrates that the presence of vertical conductive bridge with smaller diameter sandwiched between two adjacent thin nanodiscs excites a bridged mode very similar to the charge transfer plasmon and exhibits a remarkable enhancement in the extinction efficiency and the sensitivity when the electric field of incident light is parallel to the conductive bridge. Furthermore, for the electric field perpendicular to the bridge, another interesting feature is observed that two magnetic resonance modes are excited symmetrically through open-gaps on both sides of the bridge together with strongly enhanced electric field intensity, which provides a very favorable environment as a surface enhanced Raman scattering substrate for fluid analysis. These results verify a great potential and versatility of our approach for use as a nanoplasmonic sensing platform. In addition, we demonstrated the feasibility of fabrication process of vertical conductive bridge and high tunability in controlling the bridge width.
Core–shell PbS–CdS quantum dots enhance the peak external quantum efficiency of shortwave‐infrared light‐emitting devices by up to 50–100‐fold (compared with core‐only PbS devices). This is more than ...double the efficiency of previous quantum‐dot light‐emitting devices operating at wavelengths beyond 1 μm, and results from the passivation of the PbS cores by the CdS shells against in situ photoluminescence quenching.
Human behavior (e.g., the response to any incoming information) has very complex forms and is based on the response to consecutive external stimuli entering varied sensory receptors. Sensory ...adaptation is an elementary form of the sensory nervous system known to filter out irrelevant information for efficient information transfer from consecutive stimuli. As bioinspired neuromorphic electronic system is developed, the functionality of organs shall be emulated at a higher level than the cell. Because it is important for electronic devices to possess sensory adaptation in spiking neural networks, the authors demonstrate a dynamic, real‐time, photoadaptation process to optical irradiation when repeated light stimuli are presented to the artificial photoreceptor. The filtered electrical signal generated by the light and the adapting signal produces a specific range of postsynaptic states through the neurotransistor, demonstrating changes in the response according to the environment, as normally perceived by the human brain. This successfully demonstrates plausible biological sensory adaptation. Further, the ability of this circuit design to accommodate changes in the intensity of bright or dark light by adjusting the sensitivity of the artificial photoreceptor is demonstrated. Thus, the proposed artificial photoreceptor circuits have the potential to advance neuromorphic device technology by providing sensory adaptation capabilities.
Sol–gel‐derived neurotransistors integrated with perovskite‐based photodetectors are designed to serve as an artificial optoelectronic device array, which experimentally demonstrates the emulation of the dynamic adaptation process of the biological visual nervous system. The fundamental properties of biological adaptation, such as accuracy and desensitization behaviors, are characterized. These results enable post‐synaptic responses to be manipulated to obtain external‐environment‐dependent encoded images.
Abstract
The optical and electronic performance of quantum dots (QDs) are affected by their size distribution and structural quality. Although the synthetic strategies for size control are well ...established and widely applicable to various QD systems, the structural characteristics of QDs, such as morphology and crystallinity, are tuned mostly by trial and error in a material-specific manner. Here, we show that reaction temperature and precursor reactivity, the two parameters governing the surface-reaction kinetics during growth, govern the structural quality of QDs. For conventional precursors, their reactivity is determined by their chemical structure. Therefore, a variation of precursor reactivity requires the synthesis of different precursor molecules. As a result, existing precursor selections often have significant gaps in reactivity or require synthesis of precursor libraries comprising a large number of variants. We designed a sulfur precursor employing a boron-sulfur bond, which enables controllable modulation of their reactivity using commercially available Lewis bases. This precursor chemistry allows systematic optimization of the reaction temperature and precursor reactivity using a single precursor and grows high-quality QDs from cores of various sizes and materials. This work provides critical insights into the nanoparticle growth process and precursor designs, enabling the systematic preparation of high-quality QD of any sizes and materials.
Abstract
To realize economically feasible electrochemical CO
2
conversion, achieving a high partial current density for value-added products is particularly vital. However, acceleration of the ...hydrogen evolution reaction due to cathode flooding in a high-current-density region makes this challenging. Herein, we find that partially ligand-derived Ag nanoparticles (Ag-NPs) could prevent electrolyte flooding while maintaining catalytic activity for CO
2
electroreduction. This results in a high Faradaic efficiency for CO (>90%) and high partial current density (298.39 mA cm
‒2
), even under harsh stability test conditions (3.4 V). The suppressed splitting/detachment of Ag particles, due to the lipid ligand, enhance the uniform hydrophobicity retention of the Ag-NP electrode at high cathodic overpotentials and prevent flooding and current fluctuations. The mass transfer of gaseous CO
2
is maintained in the catalytic region of several hundred nanometers, with the smooth formation of a triple phase boundary, which facilitate the occurrence of CO
2
RR instead of HER. We analyze catalyst degradation and cathode flooding during CO
2
electrolysis through identical-location transmission electron microscopy and
operando
synchrotron-based X-ray computed tomography. This study develops an efficient strategy for designing active and durable electrocatalysts for CO
2
electrolysis.
•Enhanced resolution of Bi-WCSPR sensors for the detection of CRP is systematically demonstrated.•SPR sensorgrams were measured at different CRP concentrations in both the intensity and angular ...interrogation modes.•The sensing performance of Bi-WCSPR configurations was evaluated in terms of FOM and LOD.•Bi-WCSPR2 chip exhibits a LOD three times lower than conventional Au chips, order of magnitude lower than the cut-off level for CRP.•This Bi-WCSPR approach provides a very promising sensing platform for the label-free detection of biomolecules at low concentrations.
Extensive efforts have been devoted to improving the resolution of surface plasmon resonance (SPR) sensors in the detection of trace levels of biomolecules considered essential for the early diagnosis of disease. As part of these efforts, we previously developed a bimetallic waveguide-coupled surface plasmon resonance (Bi-WCSPR) sensor configuration designed to dramatically reduce the linewidth of the SPR curve while preserving a moderate local field decay length, thereby addressing the resolution issue. In this study, we systematically quantified the enhanced resolution in Bi-WCSPR sensors used to detect C-reactive protein (CRP), a widely accepted biomarker of inflammation in cardiovascular disease. Individual SPR sensorgrams were measured at several CRP concentrations in both the intensity and angular interrogation modes, confirming that the Bi-WCSPR configuration with a high Ag-to-Au ratio provided a figure-of-merit (FOM) that was 2.53 times higher than that of conventional Au sensors and a limit-of-detection (LOD) that was an order of magnitude lower than the cut-off level for CRP. It was found that when using the Bi-WCSPR configurations, the resolution enhancement in the intensity interrogation mode becomes more evident as the CRP concentrations is lowered to the cut-off level.
To fabricate a tunable optical filter with a fast response in the near infrared region, a tunable guided-mode resonance (GMR) filter using graphene was proposed and its performance was optimized. In ...this study, a rigorous coupled wave analysis method was employed to systematically investigate the effects of geometrical configuration of graphene-integrated GMR filters and the optical properties of constituent materials including graphene on their spectral response in terms of tunability and extinction ratio. It was found that as the graphene is located close to the waveguide and the evanescent-field strength at the interface increases, the GMR filter exhibits better tunability. The bandwidth of the filter could be drastically reduced by adopting a low-index contrast grating layer, so that the extinction ratio of an optical signal could be greatly improved from 0.91 dB to 27.99 dB as the index contrast decreased from 0.99 to 0.47, respectively. Furthermore, new practical device designs, that is easy to fabricate and effectively implement the electric-field doping of graphene at low gate voltage, were also suggested and theoretically validated. These results demonstrate not only the excellent potential of a graphene-based tunable GMR filter but also provide practical design guidelines for optimizing the device performance.
Neuromorphic computing research is being actively pursued to address the challenges posed by the need for energy-efficient processing of big data. One of the promising approaches to tackle the ...challenges is the hardware implementation of spiking neural networks (SNNs) with bio-plausible learning rules. Numerous research works have been done to implement the SNN hardware with different synaptic plasticity rules to emulate human brain operations. While a standard spike-timing-dependent-plasticity (STDP) rule is emulated in many SNN hardware, the various STDP rules found in the biological brain have rarely been implemented in hardware. This study proposes a CMOS-memristor hybrid synapse circuit for the hardware implementation of a Ca ion-based plasticity model to emulate the various STDP curves. The memristor was adopted as a memory device in the CMOS synapse circuit because memristors have been identified as promising candidates for analog non-volatile memory devices in terms of energy efficiency and scalability. The circuit design was divided into four sub-blocks based on biological behavior, exploiting the non-volatile and analog state properties of memristors. The circuit was designed to vary weights using an H-bridge circuit structure and PWM modulation. The various STDP curves have been emulated in one CMOS-memristor hybrid circuit, and furthermore a simple neural network operation was demonstrated for associative learning such as Pavlovian conditioning. The proposed circuit is expected to facilitate large-scale operations for neuromorphic computing through its scale-up.
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