Industrial processes can lead to air and water pollution, particularly from organic contaminants such as toluene and antibiotics, posing threats to human health. Photo-assisted chemical oxidation technologies leverage...
Industrial processes can lead to air and water pollution, particularly from organic contaminants such as toluene and antibiotics, posing threats to human health. Photo-assisted chemical oxidation technologies leverage light energy to mineralize these contaminants. In this Review, we discuss the mechanisms and efficiencies of photo-assisted advanced oxidation processes for wastewater treatment and photothermal technologies for air purification. The integration of solar energy enhances degradation efficiency and reduces energy consumption, enabling more efficient remediation methods. We evaluate the technological aspects of photo-assisted technologies, such as photo-Fenton, photo-persulfate activation, photo-ozonation and photoelectrochemical oxidation, emphasizing their potential for practical applications. Finally, we discuss the challenges in scaling up photo-assisted technologies for specific environmental remediation needs. Photo-assisted technologies have demonstrated effectiveness in environmental remediation, although large-scale applications remain constrained by high costs. Future potential applications of photo-assisted technologies will require that technology selection be tailored to specific pollution scenarios and engineering processes optimized to minimize costs.
Scholars worldwide leverage science gateways/virtual research environments (VREs) for a wide variety of research and education endeavors spanning diverse scientific fields. Evaluating the value of a given science gate...
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High-performance artificial synaptic devices are key building blocks for developing efficient neuromorphic computingsystems. However, the nonlinear and asymmetric weight update of existing devices has restricted thei...
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High-performance artificial synaptic devices are key building blocks for developing efficient neuromorphic computingsystems. However, the nonlinear and asymmetric weight update of existing devices has restricted their practical applications. Herein, floating gate nonvolatile memory (FG NVM) devices based on two-dimensional (2D) HfS2/h-BN/FG-graphene heterostructures have been designed and investigated as multifunctional NVM and artificial optoelectronic synapses. Benefiting from the FG architecture, the HfS2-based NVM device exhibits competitive performances, such as a high on:off ratio (>105), large memory window (approximately 100 V), excellent charge retention ability (>104s), and robust durability (>103 cycles). Notably, the artificial optoelectronic synapses based on HfS2 FG NVM show an impressive large conductance margin and good linearity, owing to the ultrahigh photoresponsivity and photogain of HfS2. The energy consumption of per spike in our artificial synapse is as low as 0.2 pJ. Therefore, a high recognition accuracy up to 91.5% of the artificial neural network on the basis of our HfS2-based optoelectronic synapse at the system level has been achieved, which is superior to other reported 2D artificial optoelectronic synapses. This work paves the way forward for all 2D material-based memory for developing efficient optogenetics-inspired neuromorphic computing in brain-inspired intelligent systems.
Unmanned Aerial Vehicles (UAVs) play a critical role in data collection for a wide range of Internet of Things (IoT) applications across remote, urban, and marine environments. In large-scale deployments, UAVs often f...
Unmanned Aerial Vehicles (UAVs) play a critical role in data collection for a wide range of Internet of Things (IoT) applications across remote, urban, and marine environments. In large-scale deployments, UAVs often face complex decision-making challenges, for which Deep Reinforcement Learning (DRL) has emerged as a promising solution. This paper presents a comprehensive review of UAV-assisted IoT applications utilizing DRL, covering key research questions, DRL algorithm variants, deployment objectives, architectural features, integrated technologies, UAV roles, optimization constraints, energy management strategies, and performance metrics. Findings indicate that value-based and actor-critic algorithms are the most commonly employed, targeting objectives such as path planning, transmit power control, scheduling, velocity and altitude control, and charging optimization. Architectural considerations include clustering, security, obstacle avoidance, buffered sensors, and multi-UAV coordination. Beyond data collection, UAVs are also used for tasks such as device selection, data aggregation, and sensor charging, with energy management primarily achieved through charging and energy harvesting techniques. Performance is typically assessed using metrics like energy efficiency, throughput, latency, packet loss, and Age of information (AoI). The paper concludes by outlining several promising research directions and open challenges critical to the successful deployment of UAVs in IoT data collection.
We formulate and analyze a generic sequential resource access problem arising in a variety of engineering fields, where a user disposes a number of heterogeneous computing, communication, or storage resources, each ch...
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When a charged particle penetrates through an optical interface, photon emissions emerge — a phenomenon known as transition radiation. Being paramount to fundamental physics, transition radiation has enabled many app...
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We propose and experimentally demonstrate the operation of an electrically tunable, broadband coherent perfect absorption(CPA) at microwave frequencies by harnessing the CPA features of a graphene–electrolyte–graphe...
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We propose and experimentally demonstrate the operation of an electrically tunable, broadband coherent perfect absorption(CPA) at microwave frequencies by harnessing the CPA features of a graphene–electrolyte–graphene sandwich structure(GSS). Using both a simplified lumped circuit model and full-wave numerical simulation, it is found that the microwave coherent absorptivity of the GSS can be tuned dynamically from nearly 50% to 100% by changing the Fermi level of the graphene. Strikingly, our simplified lumped circuit model agrees very well with the full-wave numerical model, offering valuable insight into the CPA operation of the device. The angle dependency of coherent absorption in the GSS is further investigated, making suggestions for achieving CPA at wide angles up to 80°. To show the validity and accuracy of our theory and numerical simulations, a GSS prototype is fabricated and measured in a C-band waveguide system. The reasonably good agreement between the experimental and the simulated results confirms that the tunable coherent absorption in GSS can be electrically controlled by changing the Fermi level of the graphene.
Multi-class segmentation of the aorta in computed tomography angiography (CTA) scans is essential for diagnosing and planning complex endovascular treatments for patients with aortic dissections. However, existing met...
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A key concept underlying the specific functionalities of metasurfaces is the use of constituent components to shape the wavefront of the light on *** are versatile,novel platforms for manipulating the scattering,color...
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A key concept underlying the specific functionalities of metasurfaces is the use of constituent components to shape the wavefront of the light on *** are versatile,novel platforms for manipulating the scattering,color,phase,or intensity of ***,one of the typical approaches for designing a metasurface is to optimize one or two variables among a vast number of fixed parameters,such as various materials’properties and coupling effects,as well as the geometrical ***,this would require multidimensional space optimization through direct numerical ***,an alternative,popular approach allows for reducing the computational cost significantly based on a deep-learning-assisted *** utilize a deep-learning approach for obtaining high-quality factor(high-Q)resonances with desired characteristics,such as linewidth,amplitude,and spectral *** exploit such high-Q resonances for enhancedlight–matter interaction in nonlinearoptical metasurfaces and optomechanical vibrations,*** demonstrate that optimized metasurfaces achieve up to 400-fold enhancement of the third-harmonic generation;at the same time,they also contribute to 100-fold enhancement of the amplitude of optomechanical *** approach can be further used to realize structures with unconventional scattering responses.
Since 2020, synchrotron radiation facilities in several Asia-Pacific countries have been collaborating in a major project called “SYNAPSE” (Synchrotrons for Neuroscience: an Asia-Pacific Scientific Enterprise). They...
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