Gas identification and concentration measurements are important for both understanding and monitoring a variety of phenomena from industrial processes to environmental change. Here a novel mid-IR ...plasmonic gas sensor with on-chip direct readout is proposed based on unity integration of narrowband spectral response, localized field en-hancement and thermal detection. A systematic investigation consisting of both optical and thermal simulations for gas sensing is presented for the first time in three sensing modes including refractive index sensing, absorption sensing and spectroscopy, respectively. It is found that a detection limit less than 100 ppm for CO2 could be realized by a combination of surface plasmon resonance enhancement and metal-organic framework gas enrichment with an enhancement factor over 8000 in an ultracompact optical interaction length of only several microns. Moreover, on-chip spectroscopy is demonstrated with the compressive sensing algorithm via a narrowband plasmonic sensor array. An array of 80 such sensors with an average resonance linewidth of 10 nm reconstructs the CO2 molecular absorption spectrum with the estimated resolution of approximately 0.01 nm far beyond the state-of-the-art spectrometer. The novel device design and analytical method are expected to provide a promising technique for extensive applications of distributed or portable mid-IR gas sensor.
Fast, accurate and nondestructive spectral analysis technique is important and widely used in the fields of scientific research, information, biomedical, pharmaceutical detection, agriculture, ...environment, and security. However, the existing spectroscopic analysis equipments are usually bulky and complex, which are difficult to adapt to portable application scenarios such as on-site rapid detection, light-load platform, etc. In recent years, miniature spectroscopic detection technology and equipment have received extensive attention, and have been rapidly developed, with significant advantages in size, weight, and power consumption. In particular, the computational spectral analysis technology based on the speckle detection can obtain high-precision spectral information by recording and analyzing the speckle pattern formed by the scattering element on the measured light. This paper will first introduce the related technical principles and technological developments, then analyze the existing techniques includ
Harvesting energetic carriers from plasmonic resonance has been a hot topic in the field of photodetection in the last decade. By interfacing a plasmonic metal with a semiconductor, the photoelectric ...conversion mechanism, based on hot carrier emission, is capable of overcoming the band gap limitation imposed by the band-to-band transition of the semiconductor. To date, most of the existing studies focus on plasmonic structural engineering in a single metal-semiconductor (MS) junction system and their responsivities are still quite low in comparison to conventional semiconductor, material-based photodetection platforms. Herein, we propose a new architecture of metal-semiconductor-metal (MSM) junctions on a silicon platform to achieve efficient hot hole collection at infrared wavelengths with a photoconductance gain mechanism. The coplanar interdigitated MSM electrode’s configuration forms a back-to-back Schottky diode and acts simultaneously as the plasmonic absorber/emitter, relying on the hot-spots enriched on the random Au/Si nanoholes structure. The hot hole-mediated photoelectric response was extended far beyond the cut-off wavelength of the silicon. The proposed MSM device with an interdigitated electrode design yields a very high photoconductive gain, leading to a photocurrent responsivity up to several A/W, which is found to be at least 1000 times higher than that of the existing hot carrier based photodetection strategies.
Hydrogen energy is a zero-carbon replacement for fossil fuels. However, hydrogen is highly flammable and explosive hence timely sensitive leak detection is crucial. Existing optical sensing ...techniques rely on complex instruments, while electrical sensing techniques usually operate at high temperatures and biasing condition. In this paper an on-chip plasmonic-catalytic hydrogen sensing concept with a concentration detection limit down to 1 ppm is presented that is based on a metal-insulator-semiconductor (MIS) nanojunction operating at room temperature and zero bias. The sensing signal of the device was enhanced by three orders of magnitude at a one-order of magnitude higher response speed compared to alternative non-plasmonic devices. The excellent performance is attributed to the hydrogen induced interfacial dipole charge layer and the associated plasmonic hot electron modulated photoelectric response. Excellent agreements were achieved between experiment and theoretical calculations based on a quantum tunneling model. Such an on-chip combination of plasmonic optics, photoelectric detection and photocatalysis offers promising strategies for next-generation optical gas sensors that require high sensitivity, low time delay, low cost, high portability and flexibility.
The China Hospital Information Network Conference (CHINC) is one of the most influential academic and technical exchange activities in medical informatics and medical informatization in China. It ...collects frontier ideas in medical information and has an important reference value for the analysis of China's medical information industry development.
This study summarizes the current situation and future development of China's medical information industry and provides a future reference for China and abroad in the future by analyzing the characteristics of CHINC exhibitors in 2021.
The list of enterprises and participating keywords were obtained from the official website of CHINC. Basic characteristics of the enterprises, industrial fields, applied technologies, company concepts, and other information were collected from the TianYanCha website and the VBDATA company library. Descriptive analysis was used to analyze the collected data, and we summarized the future development directions.
A total of 205 enterprises officially participated in the exhibition. Most of the enterprises were newly founded, of which 61.9% (127/205) were founded in the past 10 years. The majority of these enterprises were from first-tier cities, and 79.02% (162/205) were from Beijing, Zhejiang, Guangdong, Shanghai, and Jiangsu Provinces. The median registered capital is 16.67 million RMB (about US $2.61 million), and there are 35 (72.2%) enterprises with a registered capital of more than 100 million RMB (about US $15.68 million), 17 (8.3%) of which are already listed. A total of 126 enterprises were found in the VBDATA company library, of which 39 (30.9%) are information technology vendors and 57 (45.2%) are application technology vendors. In addition, 16 of the 57 (28%) use artificial intelligence technology. Smart medicine and internet hospitals were the focus of the enterprises participating in this conference.
China's tertiary hospital informatization has basically completed the construction of the primary stage. The average grade of hospital electronic medical records exceeds grade 3, and 78.13% of the provinces have reached grade 3 or above. The characteristics are as follows: On the one hand, China's medical information industry is focusing on the construction of smart hospitals, including intelligent systems supporting doctors' scientific research, diagnosis-related group intelligent operation systems, and office automation systems supporting hospital management, single-disease clinical decision support systems assisting doctors' clinical care, and intelligent internet of things for logistics. On the other hand, the construction of a compact county medical community is becoming a new focus of enterprises under the guidance of practical needs and national policies to improve the quality of grassroots health services. In addition, whole-course management and digital therapy will also become a new hotspot in the future.
The relentless advancement of deep learning applications, particularly the highly potent yet computationally intensive deep unsupervised learning models, is pushing the boundaries of what modern ...general-purpose CPUs and GPUs can handle in terms of computation, communication, and storage capacities. To meet these burgeoning memory and computational demands, computing systems based on In-Memory Computing (IMC), are emerging as the next frontier in computing technology. This thesis delves into my research efforts aimed at overcoming these obstacles to develop a IMC based computing system tailored for machine learning tasks, with a focus on employing a hybrid digital/analog design approach. In the initial part of my work, I introduce a novel concept that leverages hybrid digital/analog IMC to enhance the efficiency of depth-wise convolution applications. This approach not only optimizes computational efficiency but also paves the way for more energy-efficient machine learning operations.Following this, I expand upon the initial concept by presenting a design methodology that applies hybrid digital/analog IMC to the processing of sparse attention operators. This extension significantly improves mapping efficiency, making it a vital enhancement for the processing capabilities of deep learning models that rely heavily on attention mechanisms. In my third piece of work, I detail the implementation strategies aimed at augmenting the power efficiency of IMC macros. By integrating hybrid digital/analog computing concepts, this implementation focuses on general-purpose neural network acceleration, showcasing a significant step forward in reducing the energy consumption of such computational processes.Lastly, I introduce a system-level simulation tool designed for simulating general-purpose IMC based systems. This tool facilitates versatile architecture exploration, allowing for the assessment and optimization of various configurations to meet the specific needs of machine learning workloads. Through these comprehensive research efforts, this thesis contributes to the advancement of in-memory computing technologies, offering novel solutions to the challenges posed by the next generation of machine learning applications.
Active metasurface provides an efficient way to achieve optical response in the subwavelength range, dielectric metasurface has attracted much attention due to its low-loss mode and excitable ...electric/magnetic resonance mode, resulting in a far wider range of applications. However, the resonance spectrum is relatively broad due to the strong radiative loss of the symmetric dielectric metasurface, which limits its application in large modulation extinction ratio. Hence, an active metasurface integrated with the phase change material Ge2Sb2Te5 (GST) is proposed. The active metasurface can support the symmetry-protected quasi bound states in the continuum (QBIC) and excite resonance modes with extremely high quality-factors. As an active medium, the GST layer undergoes a transition from the amorphous state to the crystalline state when the temperature increases, leading to a change in the amplitude/phase of the reflection spectrum. It is demonstrated that dual reflection modulation and the figure-of-merit (FoM) can reach up to 92.0% at the wavelength of 1.45 μm and 92.5% at the wavelength of 1.52 μm as the GST layer is in the middle of nanodisks. An extremely high FoM of 98.5% is also realized when the surface of silicon nanodisks is coated with the GST layer. In addition, the modulation mechanism of the optical response of the active metasurface has been investigated, which is of great significance to the design of the active metasurface. The proposed active all-dielectric asymmetric metasurface has a huge potential in tunable nonlinear optical devices.
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