Radiation Power Research Articles

Light-Field Optimization of Deep-Ultraviolet LED Modules for Efficient Microbial Inactivation

Public awareness of preventing pathogenic microorganisms has significantly increased. Among numerous microbial prevention methods, the deep-ultraviolet (DUV) disinfection technology has received wide attention by using the nitride-based light-emitting diode (LED). However, the light extraction efficiency of DUV LEDs and the utilization rate of emitted DUV light are relatively low at the current stage. In this study, a light distribution design (referred to as the reflective system) was explored to enhance the utilization of emitted DUV from LEDs, leading to successful and efficient surface and air disinfection. Optical power measurements and microbial inactivation tests demonstrated an approximately 79% improvement in average radiation power density achieved by the reflective system when measured at a 5 cm distance from the irradiation surface. Moreover, a statistically significant enhancement in local surface disinfection was observed with low electric power consumption. The reflective system was integrated into an air purifier and underwent air disinfection testing, effectively disinfecting a 3 m3 space within ten minutes. Additionally, a fluorine resin film at the nanolevel was developed to protect the light module from oxidation, validated through a 1200 h accelerated aging test under humid conditions. This research offers valuable guidance for efficient and energy-saving DUV disinfection applications.

Field emission from point diamond cathodes under continuous laser irradiation

The presented study investigates the impact of continuous laser irradiation in the visible range on the field emission properties of diamond needle-like micro-sized crystallites with a nanometer tip radius. The measurements were carried out in a vacuum diode configuration with a flat metal anode using DC voltage source. It was found that the field emission current increased under illumination, showing a direct correlation with the radiation power. At a maximum power density of about 400 W/cm2 the relative increase in current under the action of laser irradiation was 13%. The relative increase in current is determined by the parameters of the dark current-voltage characteristic and reaches its maximum value in the region corresponding to the minimum increase in dark current with voltage. It is shown that the most likely mechanism for the increase in current is a change in the electrical resistance of the diamond microneedle as a result of absorption of laser radiation in the presence of electron levels located in the band gap of the diamond associated with impurities or structural defects in the near surface layer of the diamond microneedle.

Increase in Power of Radiation and Specific Concentration of Energy of Plasma of the High-Current Z-Pinches due to Compression of the Cascade Wire Arrays Interacting via Magnetic Field

Increase in Power of Radiation and Specific Concentration of Energy of Plasma of the High-Current Z-Pinches due to Compression of the Cascade Wire Arrays Interacting via Magnetic Field

Giant enhancement of vacuum friction in spinning YIG nanospheres

Experimental observations of vacuum radiation and vacuum frictional torque are challenging due to their vanishingly small effects in practical systems. For example, a nanosphere rotating at 1GHz in free space slows down due to friction from vacuum fluctuations with a stopping time around the age of the Universe. Here, we show that a spinning yttrium iron garnet (YIG) nanosphere near aluminum or YIG slabs generates vacuum radiation with radiation power eight orders of magnitude larger than other metallic or dielectric spinning nanospheres. We achieve this giant enhancement by exploiting the large near-field magnetic local density of states in YIG systems, which occurs in the low-frequency GHz regime comparable to the rotation frequency. Furthermore, we propose a realistic experimental setup for observing the effects of this large vacuum radiation and frictional torque under experimentally accessible conditions.

Improving the systems for controlling ground-based sun orientation devices

The control system for terrestrial two-axis devices for orientation to the Sun has been improved with a high-speed microcontroller operation algorithm. A geomagnetic sensor was introduced into the system to increase the reliability of monitoring the positioning of solar cells. The basis of the algorithm is a simplified astronomical and geographical model of the movement of the Sun in the celestial sphere. The control system automatically tracks the trajectory of the Sun and calculates its angular coordinates for the current moment of time on any day of the year and for any point on the globe. The derived equations of the simplified mathematical model are suitable for calculations of orientation angles to the Sun in real time on 8-bit microcontrollers with low computing power. The control system by AVR-328 microcontrollers was studied. It was established that the use of the algorithm when programming microcontrollers for two-axis orientation systems ensures high stability and reliability of the tracker`s functioning process. The technical parameters of the AVR-328 microcontrollers in the case of using the developed algorithm ensure that the control system performs one reorientation step in a time interval of less than 2 seconds, which ensures the minimum technical period of the reorientation process by the tracker drive mechanisms which is about 5 seconds. Deviations of the calculated orientation angle from the exact value do not exceed 3°, which corresponds to the relative accuracy of recording the solar radiation intensity, which is less than 0.3 %. The microcontroller program written according to the developed simplified algorithm occupies about 35 % of its memory. Therefore, the use of the developed algorithm frees up the resources of AVR-328 microcontrollers for performing additional data processing operations and automatic control over various additional devices related to the process of orientation to the Sun. In the case of solar energy, the algorithm ensures the use of about 98 % of the power of solar radiation

Spatial Identification and Distribution Pattern of the Complexity of Rural Poverty in China Using Multisource Spatial Data

Regional poverty is one of the most serious challenges facing the world today. Poverty, antipoverty, and poverty alleviation are the focus of the attention of scholars and the public. This paper takes China’s counties as the research unit, selects the influencing factors of poverty from natural and socio-economic factors, establishes an evaluation index system, simulates the natural poverty index and socio-economic poverty eradication index of each county, and clarifies the distribution characteristics of spatial poverty using GIS spatial analysis and BP artificial neural network. The results indicate that natural factors are the main cause of poverty in Chinese counties, with 710 counties having a high natural poverty index, accounting for nearly 30% of the total number of counties in the country. The national county-level natural poverty index shows a clear strip distribution pattern along latitude and longitude, with a strip distribution from north to south and from west to east; socio-economic factors have played a certain role in poverty alleviation, with as many as 1521 counties with low socio-economic poverty alleviation indices, accounting for approximately 64% of the total number of counties in the country. The spatial distribution of the county-level socio-economic poverty alleviation index is relatively fragmented. Through spatial scanning statistics, a total of 44 county poverty pressure index risk clusters reached a statistical significance level, involving 243 counties and districts. In poverty reduction practice, the internal counties and districts of contiguous poverty-stricken areas should strengthen cooperation and exchange. In the process of poverty alleviation and development, targeted poverty alleviation and economic development should be carried out based on the poverty-dominant type and self-development ability of the county, in order to improve efficiency. Regions that are relatively prosperous and have taken the lead in poverty reduction should play a leading and exemplary role in strengthening the radiation power of regional central cities. The prominent feature of this study is the comprehensive utilization of multisource data and the use of new spatial analysis methods (flexible spatial scanning method is widely used in the field of infectious disease prevention and control research). By constructing a multidimensional poverty measurement system that includes natural and social factors, it distinguishes the differences between the factors that cause poverty and the factors that eliminate poverty in regional poverty. At the same time, the flexible spatial scanning detection method was used to detect the differentiation mechanism of poverty spatial patterns.

Automatic identification and quantification of volcanic hotspots in Alaska using HotLINK: the hotspot learning and identification network

An increase in volcanic thermal emissions can indicate subsurface and surface processes that precede, or coincide with, volcanic eruptions. Space-borne infrared sensors can detect hotspots—defined here as localized volcanic thermal emissions—in near-real-time. However, automatic hotspot detection systems are needed to efficiently analyze the large quantities of data produced. While hotspots have been automatically detected for over 20 years with simple thresholding algorithms, new computer vision technologies, such as convolutional neural networks (CNNs), can enable improved detection capabilities. Here we introduce HotLINK: the Hotspot Learning and Identification Network, a CNN trained to detect hotspots with a dataset of −3,800 satellite-based, Visible Infrared Imaging Radiometer Suite (VIIRS) images from Mount Veniaminof and Mount Cleveland volcanoes, Alaska. We find that our model achieves an accuracy of 96% (F1-score 0.92) when evaluated on −1,700 unseen images from the same volcanoes, and 95% (F1-score 0.67) when evaluated on −3,000 images from six additional Alaska volcanoes (Augustine Volcano, Bogoslof Island, Okmok Caldera, Pavlof Volcano, Redoubt Volcano, Shishaldin Volcano). In comparison with an existing threshold-based hotspot detection algorithm, MIROVA (Coppola et al., Geological Society, London, Special Publications, 2016, 426, 181–205), our model detects 22% more hotspots and produces 12% fewer false positives. Additional testing on −700 labeled Moderate Resolution Imaging Spectroradiometer (MODIS) images from Mount Veniaminof demonstrates that our model is applicable to this sensor’s data as well, achieving an accuracy of 98% (F1-score 0.95). We apply HotLINK to 10 years of VIIRS data and 22 years of MODIS data for the eight aforementioned Alaska volcanoes and calculate the radiative power of detected hotspots. From these time series we find that HotLINK accurately characterizes background and eruptive periods, similar to MIROVA, but also detects more subtle warming signals, potentially related to volcanic unrest. We identify three advantages to our model over its predecessors: 1) the ability to detect more subtle volcanic hotspots and produce fewer false positives, especially in daytime images; 2) probabilistic predictions provide a measure of detection confidence; and 3) its transferability, i.e., the successful application to multiple sensors and multiple volcanoes without the need for threshold tuning, suggesting the potential for global application.

Experimental Study on a Photovoltaic Direct-Drive and Municipal Electricity-Coupled Electric Heating System for a Low-Energy Building in Changchun, China

This paper takes a low-energy building in Changchun, China, as an object to test and study the characteristics of two heating modes, AC/DC (Alternative current/Direct current) switching and AC/DC synthesis, from the perspectives of temperature change, irradiation intensity, power generation, electricity consumption, etc. Firstly, the experimental research was conducted under two heating cable modes by establishing mathematical models and a test rig, and it was found that the photoelectric conversion efficiency on sunny, cloudy, and overcast days was 18%, 14.5%, and 12%, respectively. A simulation model was established by TRNSYS to run an ultra-low-energy building throughout the year. It was found that the highest and lowest monthly power generation occurred in February and July, respectively. The annual power generation of the system was 6614 kWh, and the heating season power generation was 3293.42 kWh. In the current research, the DC electricity consumption was slightly higher than the AC electricity consumption. Under conditions of similar radiation intensity and power generation, the indoor temperature of the AC/DC synthesis cable heating mode were 1.38% higher than the AC/DC switching heating able mode, and the electricity consumption were 10.9% and 4.76% higher, respectively, than those of the AC switching heating cable mode. This is of great significance for clean-energy heating, energy savings, and emissions reduction in northern China.

Calculation and prediction of divertor detachment via impurity seeding by using one-dimensional model

Abstract Achieving the divertor detachment helps to alleviate excessive heat load and sputtering problems on the target plates, thereby prolonging the lifetime of divertor components for fusion devices. In order to provide a rapid but relatively reliable prediction of plasma parameters along the flux tube for future devices design, a one-dimensional (1D) modeling code for the impurity seeded detached divertor operational point has been developed based on the Python language, which is a fluid model based on the previous work.[1] The experimental observation of the onset of divertor detachment by neon (Ne) and argon (Ar) seeding in EAST is well reproduced by using the 1D modeling code. The comparison of the 1D modeling and 2D simulation by SOLPS-ITER code for CFETR detachment operation with Ne and Ar seeding also shows good consistency. The predictions of the radiative power loss and requirement of the corresponding impurity concentration for achieving divertor detachment via different impurity seeding for the high heating power scenarios on EAST and CFETR Phase II by the 1D model are also presented. Based on the predictions, the optimized parameter space for divertor detachment operation on EAST and CFETR has also been determined. Such a simple but reliable 1D model can provide a reasonable parameter inputs for a detailed and accurate analysis by 2D or 3D modeling tools through rapid parameter scanning.

Underestimated contribution of open biomass burning to terpenoid emissions revealed by a novel hourly dynamic inventory

Terpenoids play a crucial role in atmospheric chemistry, contributing significantly to the formation of ozone and secondary organic aerosol. However, the accurate quantification of terpenoid emissions from biomass burning is currently lacking, leading to underestimated air quality impacts. This study developed a near real-time hourly open biomass burning (OBB) emission inventory named OBEIC, which incorporated geostationary and polar-orbiting satellite fire radiative power. The OBEIC inventory provided emission estimates of 69 terpenoids, categorized into four groups, at an hourly resolution. Monoterpenes were the dominant contributors to the total emissions, accounting for 58 % of the total terpenoid emissions from OBB. Notably, only 24 % of the total monoterpenes emitted from OBB were accounted for by α-pinene and β-pinene, indicating the importance of quantifying emissions of other monoterpene species such as limonene and camphene. Additionally, oxygenated terpenoids, which were previously overlooked, contribute to 20 % of total terpenoid emissions from OBB. Diurnally, the emissions of terpenoids were primarily concentrated during the daytime (61 %); however, this study revealed the significance of nighttime emissions (39 %) as well. When compared to the biogenic and anthropogenic emissions, OBB made substantial contributions to nighttime isoprene (99.8 %), monoterpene (66.8 %), and sesquiterpene (61.7 %) emissions where OBB occurs (in 3 km range), suggesting its significant role in nighttime secondary pollutant formation. The methodology developed in this study has the potential to reduce uncertainties in OBB emissions estimation.

Propagation of NO2 originated in intense fires in the Paraná River Delta analyzed from satellite observations

Wildfires in the Paraná River Delta started to be a common situation in the year 2008 and during the first years of the 2020́s decade: 2020, 2021, 2022. These fires affected natural areas, primarily the islands within the delta, situated in front of Rosario city (32.95 °S, 60.67 °W, 25 meters above sea level (m.a.s.l.)), Argentina. They mostly occur during the period between June and September each year and are more intense when a strong La Niña event is present. The aim of this study is to examine the association between the propagation of high intensity nitrogen dioxide (NO2) plumes and the significant fire events that occurred in the Paraná River Delta from 6 to 17 September 2022. Satellite data of NO2 obtained from the TROPOspheric Monitoring Instrument (TROPOMI) on board the European Space Agency (ESA) Sentinel-5 Precursor satellite, air mass forward trajectories performed with The Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT), Fire Radiative Power (FRP) data provided by Visible Infrared Imaging Radiometer Suite (VIIRS) on board The National Oceanic and Atmospheric Administration - 20 (NOAA-20) and Suomi National Polar-orbiting Partnership (S-NPP) satellites, Aerosol Optical Depth (AOD) from VIIRS S-NPP and Smoke Injection Height from Multi-Angle Implementation of Atmospheric Correction (MAIAC) Thermal Technique were employed. The trajectories followed by the air masses coming from the major fire sources locations nearby Rosario city and its surrounding area, were analyzed at altitudes of 20, 500, 1000, 1500 and 2000 m above ground level (AGL) in order to evaluate the impact of the NO2 clouds present in the atmosphere and carried by the winds, at different sites of Rosario and its adjacent region. The NO2 plumes has the potential to pose a significant health risk for this region, inhabited by an approximate population of one and a half million individuals. This risk is contingent upon the altitude where the highest levels of NO2 in the tropospheric column are found. Tropospheric vertical column densities (VCDs) of NO2 in the range of 4.68×1014 to 1.66×1016 molecules/cm2 were determined. The results indicate a robust correlation between elevated tropospheric NO2 VCD values and intense fires, as characterized by their FRP. Additionally, high tropospheric NO2 VCDs were observed to impact cities and towns located in close proximity to the fires. In particular, the unusually high tropospheric NO2 VCDs determined for the towns of Fighiera and Pueblo Esther, situated along the coast and near the Paraná River Delta, are noteworthy. This is uncommon considering they are small towns in rural areas that typically have good air quality. The results regarding FRP, provided by VIIRS on board NOAA-20 and S-NPP satellites, indicate that the fire characterization of hotspots during the considered period had a mean value in the range of 20.17–21.47 MW. On specific days (12, 13 and 16 September 2022), the cumulative (total) daily values were very high, ranging from 2000 to 10000 MW. Furthermore, on 12 and 13 September 2022, the smoke aerosols did not reach significant altitudes in the atmosphere, remaining within the range of 0 to 1500 m AGL. During the fire period, AOD values close to 1 were observed within the fire plume. Notably, Puerto San Martín (0.27), San Lorenzo (0.22), and Ibarlucea (0.20) recorded higher average AOD values compared to other sites. The remaining sites generally exhibited lower average AOD values, with a slight distinction between rural locations (Pueblo Esther: 0.14 and Fighiera: 0.14) and the city center of Rosario (0.09).

Shedding light on the problem: Influence of the radiator power, source-sample distance, and exposure time on the performance of UV-C lamps in laboratory and real-world conditions.

Effective surface disinfection is crucial for preventing the spread of pathogens in hospitals. Standard UltraViolet-C (UV-C) lamps have been widely used for this purpose, but their disinfection efficiency under real-world conditions is not well understood. To fill this gap, the influence of the power of the ultraviolet radiator, source-sample distance, and exposure time on the performance of UV-C lamps against Escherichia coli and Staphylococcus epidermidis were experimentally determined in the laboratory and hospital. The obtained results showed that the UV irradiance and, thus, the UV-C disinfection efficiency decreased significantly at distances greater than 100 cm from the UV-C lamp. Moreover, increasing the total power of the radiators does not improve the performance of UV-C lamps under real conditions. The UV-C disinfection efficiency greater than 90% was achieved only under laboratory conditions at a close distance from the UV-C lamp, i.e., 10 cm. These findings provide novel insights into the limitations of UV-C lamps in real-world conditions and highlight the need for more effective disinfection strategies in hospitals.

Design of the Monopulse Feeding Network for a Slotted Waveguide Array on an Annular Disk

Design of a monopulse feeding network including a compact power distribution network and a monopulse comparator for a dual polarization slotted waveguide array fabricated on an annular disk is presented in this paper. As the slotted waveguide array is arranged on an annular disk, the feeding network is more complicated than that of a regular array such as a rectangular array. The design details of some key waveguide components, such as the compact assembly of H-plane T-junctions and E-plane elbows used to connect power distribution networks and radiation waveguides, are provided. Quasiplanar magic tees are designed and used to construct the compact sum and difference comparator. The antenna system contains two comparators, which are used to generate sum and difference beams for horizontal polarization and vertical polarization, respectively. Finally, the monopulse slotted waveguide array antenna is divided into two modules, a comparator module and an antenna module (including power distribution network), and fabricated with the layered processing and bonding process. The comparator module is measured using a network analyzer to verify its amplitude-frequency characteristics and phase-frequency characteristics. Screwing the comparator module and the antenna module together, a monopulse slotted waveguide array antenna is obtained, and the sum beam and difference beam characteristics of the antenna are measured in a microwave chamber and presented.

Predicting Photodetector Responsivity through Machine Learning

AbstractThis study introduces a novel methodology for predicting photodetector responsivity, specifically targeting challenging materials like borophene. The synthesis of these materials faces substantial experimental complexities, necessitating reliable performance predictions before fabrication. To address this, a comprehensive approach leveraging advanced machine learning techniques, specifically artificial neural networks (ANN), is developed. Integration of X‐ray diffraction (XRD) and Raman spectra data into AI models enables efficient prediction of photodetector efficiency prior to device fabrication. The innovation lies in strategically incorporating Generative Adversarial Networks (GANs) for dataset augmentation, significantly expanding the dataset size and enhancing the robustness of the ANN model. Sensitivity analyses highlighted influential factors such as bias voltage and spectral coefficients, validating the approach and aligning with recent experimental findings. This methodology not only advances optoelectronics, but also holds promise for materials science and device engineering. Predictions for Wavelength‐Responsivity plots, considering borophene allotropes as active layers and n‐Si as substrates, show peaks around 300–400 nm, ranging from 0.04 to 0.36 AW−1 at bias voltages between 1 and 5 volts. These estimations assume a borophene layer thickness of approximately 1.6 nm and a radiation power intensity of 5000 µ Wcm−2.

Accelerated reduction in China's cropland fires against the background of policy enhancement

Cropland fires contribute significantly to the emission of air pollutants, with implications for the atmospheric environment, public health, and climate change. However, the development of cropland fires in response to straw burning policy interventions has not been fully explored. With the Moderate Resolution Imaging Spectroradiometer Collection 6 (MODIS C6) active fire products and China land-cover data (CLCD), counts and fire radiative power (FRP) of cropland fire spots were extracted in China from 2003 to 2022, followed by analyses of their spatiotemporal patterns and evolutionary characteristics at the provincial, regional, national, and grid (0.25° × 0.25°) levels and at monthly to annual scales via trend analysis, kernel density analysis, and geographic distribution analysis. The key findings include: (1) National policies banning straw burning reversed the changes in the quantity and intensity of China's cropland fires in 2013, with the frequency and FRP in 2022 declining by 58% and 62% compared with the 2014 peak. (2) Cropland fires were highly prevalent in Northeast and North China (NEC and NC), with significant regional differences, particularly in spring, summer and autumn. (3) A notable lag effect of burning ban policies was seen in Northeast China, where the increasing trends of the frequency and intensity of cropland fires were not reversed until 2017, followed by declines in frequency and FRP of 67% and 62%, respectively during 2017–2022. (4) Cropland fires showed an increasing concentration trend but with enormous regional differences, with an increasing trend of a “high-high” concentration pattern in NEC and a decreasing trend in NC. This study contributes to understanding the effectiveness of national policies that ban straw burning and support cropland fire management and policy-making.

Double diffusive mixed convective flow over a wedge and cone in the presence of Brownian diffusion and thermophoresis parameter

The present article examines the double diffusion mixed convective nanofluid flow over a wedge and cone in which slip effects as Brownian motion and the thermophoretic parameter are considered. Mixed convective flow over wedges and cones is applied in different technical fields such as fiber technology, nuclear cooling systems, surface treatment, spray deposition techniques, and polymer production. Double diffusion is increasingly significant in scientific fields like astronomy, geosciences, oceanography, and chemical processes. Mixed convection occurs in several applications such as electric devices, solar panels, nuclear power plants, heat exchangers, radiators, and atmospheric boundary layer fluxes. The governing equations of the study are highly coupled nonlinear partial differential equations with surface constraints. The process of similarity transformation used to converts partial differential equations into nondimensional ordinary differential equations, which can be resolved using the MATLAB Bvp5c function. The graphical representation and detailed analysis of variations in velocity, temperature, and concentration distributions of nanofluids are presented. As the mixed convection parameter increases, the fluid’s velocity rises, with a more pronounced effect observed in the cone compared to the wedge. As the Brownian diffusion parameter grows, the fluid temperature increases, and velocity is more pronounced in the wedge scenario compared to the cone. Moreover, an increase in the thermophoresis parameter results in an elevation in the fluid’s temperature. Additionally, the wedge has a higher concentration of fluid and nanoparticles compared to the wedge. Fluid concentration falls with increasing Schmidt number, but fluid nanoparticle concentration decreases with increasing Lewis number.

Quantitative risk assessment of a spill fire caused by the continuously leaked fuel in a sealed ship engine room

There are a large number of high-temperature heat sources in a ship engine room. Once the oil leakage occurs, it is likely to be ignited and form a spreading and burning spill fire. In this paper, spill fire experiments are conducted in a model-scale ship engine room to investigate their characteristic parameters. The quantitative models of flame height and thermal radiant surface emission power applicable to such fires are verified by the experimental data. Based on that, the classical quantitative risk assessment method is adopted to assess the risk of spill fires using thermal radiation hazard as the main reference, and a detailed framework for quantitative risk assessment of spill fires in ship engine room is established, which includes hazard identification, probability of failure calculation, consequence assessment, and risk quantification. The possible causes of spill fire accidents are briefly analyzed based on the bow-tie model. In cases where thermal threats above the risk threshold for larger leakage rates (70 mL/min), the probability method outperforms the threshold method in terms of accuracy in risk quantification. Additionally, the variation of thermal radiation with combustion diameter is analyzed, and some recommendations for fire emergency rescue are presented.

A Numerical Case Study of Particle Flow and Solar Radiation Transfer in a Compound Parabolic Concentrator (CPC) Photocatalytic Reactor for Hydrogen Production

Compound parabolic concentrator (CPC) photocatalytic reactors are commonly used for photocatalytic water splitting in hydrogen production. This study aimed to gain a better understanding of the physical processes in CPC photocatalytic reactors and provide theoretical support for their design, optimization, and operation. The analysis involved the ray tracing approach, Euler–Euler two-fluid model, and discrete ordinates method (DOM) to study solar radiation transfer and particle flow in the reactor. The distribution of solar radiation on the receiving tube’s surface after CPC concentration was obtained by conducting the ray tracing approach. This solar radiation distribution was then coupled into the Euler–Euler two-fluid model to solve for the natural convection flow field, the temperature field, and particle phase volume fraction distribution inside the receiving tube over a period of 120 s. Lastly, the discrete ordinates method (DOM) was used to analyze the transfer of radiation inside the receiving tube at different times, obtaining the distribution of local volume radiative power absorption (LVRPA) and the total radiative power absorption (TRPA) inside the tube. The results showed that the TRPA reached its maximum at 120 s, accounting for 66.61% of the incident solar UV radiation. According to the above results, it could be suggested that adopting an intermittent operation mode in CPC photocatalytic reactors is reasonable and efficient.

Controlling of spontaneous emission of quantum dots based on hyperbolic metamaterials

The study of spontaneous emission has basic and supporting significance for enhancing the interaction between light and matter, solid-state lighting and biosensors. Hyperbolic metamaterials (HMMs) can support high k modes due to their hyperbolic dispersion characteristics, resulting in extremely high photon density, which affects spontaneous emission. Therefore, here we study the effect of HMMs on the spontaneous emission of quantum dots (QDs), and the Purcell factor reaches 20 times. At the same time, the structure of HMMs with gold nanoantennas is studied. The addition of gold nanoantennas further increases the Purcell factor to 120 times. In addition, the effects of the metal filling rate, the position and polarization direction of QDs on spontaneous emission enhancement and radiation power peak position are also studied. This provides a new perspective for enhancing and controlling spontaneous emission of QDs based on HMMs.

Acoustic and optical plasmons excitation in double-channel AlGaN/GaN HEMT under asymmetric boundaries

We have simulatively studied the electrical excitation of acoustic and optical plasmons in double-channel AlGaN/GaN high electron mobility transistors (HEMT) under asymmetric boundaries. By solving the self-consistent hydrodynamic model with Maxwell’s equations, it is found that the drift plasmons are excited in the bilayer 2DEGs under asymmetric boundaries. The oscillation intensity in a bilayer system is much stronger than that in a monolayer 2DEG system because of the simultaneous excitation of the fundamental and the second harmonic components. The fundamental component always corresponds to the acoustic plasmon, while the optical plasmon can be excited when it is resonant with the second harmonic of the acoustic plasmon. Because of the out-of-phase properties of the acoustic plasmons, their radiated power is limited by the current cancellation. On the other hand, as the optical plasmons are excited, the radiated powers are much higher than those of the single channel HEMT due to the in-phase currents generated in the double layers. The effects of different parameters such as gate lengths, 2DEG spacings, and electron concentrations on plasmon excitations and THz emissions of double-channel HEMTs are analyzed in detail. The numerical results provide a more powerful terahertz radiation mechanism in double-channel HEMT compared with the Dyakonov–Shur instability in traditional single-channel HEMT.