Efficient Carrier Multiplication in Self-Powered Near-Ultraviolet γ-InSe/Graphene Heterostructure Photodetector with External Quantum Efficiency Exceeding 161.

Carrier multiplication (CM) in semiconductors, the process of absorbing a single high-energy photon to form two or more electron-hole pairs, offers great potential for the high-response detection of high-energy photons in the ultraviolet spectrum. However, compared to two-dimensional semiconductors, conventional bulk semiconductors not only face integration and flexibility bottlenecks but also exhibit inferior CM performance. To attain efficient CM for ultraviolet detection, we designed a two-terminal photodetector featuring a unilateral Schottky junction based on a two-dimensional γ-InSe/graphene heterostructure. Benefiting from a strong built-in electric field, the photogenerated high-energy electrons in γ-InSe, an ideal ultraviolet light-absorbing layer, can efficiently transfer to graphene without cooling. It results in efficient CM within the graphene, yielding an ultrahigh responsivity of 468 mA/W and a record-high external quantum efficiency of 161.2% when it is exposed to 360 nm light at zero bias. This work provides valuable insights into developing next-generation ultraviolet photodetectors with high performance and low-power consumption.

Engineering Relaxation-Paths of C-Exciton for Constructing Band Nesting Bypass in WS2 Monolayer.

Transition-metal dichalcogenides exhibit strong photon absorption characteristics in the band nesting region (denoted as C-exciton) due to intrinsic van Hove singularities despite being atomically thin. However, because of unique parallel band structure and ineluctably unfavorable recombination process, only a small fraction of the hot carriers from C-excitons are converted into optically active band-edge excitons via inherent relaxation-paths. The resultant photoluminescence quantum yield (PLQY) is severely suppressed for the resonant excitation of C-exciton. To overcome this limitation, we have designed double type-I band alignments to construct a band nesting bypass in a monolayer WS2/CdS quantum dot heterostructure for cooling the C-excitons. Transient optical measurements confirmed that the hot carriers from the C-excitons were effectively transferred from WS2 to CdS with an efficiency of 50% and subsequently back to the WS2 band-edge to form A-excitons over an ultrafast subpicosecond time scale, accompanied by a record high PLQY of ∼11.1% for near-resonance C-exciton excitation.

Towards Semi-Autonomous Colon Screening Using an Electromagnetically Actuated Soft-Tethered Colonoscope Based on Visual Servo Control.

OBJECTIVE: Conventional colonoscopy using a flexible colonoscope remains two major limitations, including patient discomfort and difficult manipulations for surgeons. Robotic colonoscopes have been developed to conduct colonoscopy in a patient-friendly manner. However, most robotic colonoscopes still maintain nonintuitive and difficult manipulations, which limits their clinical applications. In this paper, we demonstrated visual servo-based semi-autonomous manipulations of an electromagnetic actuated soft-tethered (EAST) colonoscope, which aims to lower difficulties of robotic colonoscope manipulations. METHODS: Kinematic modeling of EAST colonoscope is conducted, with an adaptive visual servo controller established. Template matching method and a lumen and polyp detection model are developed to enable semi-autonomous manipulations, including region-of-interest automatic tracking and autonomous navigation with automatic polyp detection. RESULTS: The EAST colonoscope demonstrates visual servoing with an average convergence time of around 2.5 s and performs disturbance rejection within 3.0 s. Semi-autonomous manipulations were conducted in both a commercialized colonoscopy simulator and an ex-vivo porcine colon to show the efficacy of reducing the user workload compared to manual control. CONCLUSION: The EAST colonoscope can perform visual servoing and semi-autonomous manipulations with the developed methods in both laboratory and ex-vivo environments. SIGNIFICANCE: The proposed solutions and techniques improve the autonomy level of robotic colonoscopes and reduce user workloads, which promotes the development and clinical translation of robotic colonoscopy.

Self-powered and broadband opto-sensor with bionic visual adaptation function based on multilayer γ-InSe flakes.

Visual adaptation that can autonomously adjust the response to light stimuli is a basic function of artificial visual systems for intelligent bionic robots. To improve efficiency and reduce complexity, artificial visual systems with integrated visual adaptation functions based on a single device should be developed to replace traditional approaches that require complex circuitry and algorithms. Here, we have developed a single two-terminal opto-sensor based on multilayer γ-InSe flakes, which successfully emulated the visual adaptation behaviors with a new working mechanism combining the photo-pyroelectric and photo-thermoelectric effect. The device can operate in self-powered mode and exhibit good human-eye-like adaptation behaviors, which include broadband light-sensing image adaptation (from ultraviolet to near-infrared), near-complete photosensitivity recovery (99.6%), and synergetic visual adaptation, encouraging the advancement of intelligent opto-sensors and machine vision systems.

A Semi-Autonomous Stereotactic Brain Biopsy Robotic System With Enhanced Surgical Safety and Surgeon-Robot Collaboration.

OBJECTIVE: Despite benefits brought by recent neurosurgical robots, surgical safety and surgeon-robot collaboration remain significant challenges. In this article, we analyze and address these problems in the context of brain biopsy, by proposing a semi-autonomous system. METHODS: A robotic module is designed for the automation of all the brain biopsy procedures, and a biopsy cannula with tissue blocker is developed to avoid tissue excess and haemorrhage. In addition, two methods are proposed for surgical safety and surgeon-robot collaboration enhancement. First, a priority-based control framework is proposed for neuronavigation with simultaneous optical tracking line-of-sight maintenance and surgeon avoidance. Second, after neuronavigation, an adaptive reconfiguration method is developed to optimize the arm angle of KUKA robot based on the surgeon's pose, for workspace interference minimization, high robot dexterity, and joint-limit avoidance. RESULT: Effectiveness of the proposed solution demonstrated by simulations and experiments. CONCLUSION: The system can perform automatic navigation with simultaneous optical tracking maintenance and surgeon avoidance, autonomous brain biopsy, and adaptive reconfiguration for workspace interference minimization. SIGNIFICANCE: This work improves existing neurosurgical systems, in terms of autonomy level from mechanical guidance to task autonomy, surgical safety, and surgeon-robot collaboration.

Fast Convergent Antinoise Dual Neural Network Controller With Adaptive Gain for Flexible Endoscope Robots.

Manual rigid endoscopes have defects such as a low efficiency, difficult operation, and safety risks, and the antinoise interference ability, convergence speed, and control accuracy of the neural network control technology for the existing autonomous endoscopes are often ignored. Solving these problems is important for the stable operation of endoscopes. Therefore, a new adaptive fast convergent antinoise dual neural network (AFA-DNN) controller for the visual servo control of ten-degree of freedom flexible endoscope robots (FERs) with physical constraints is proposed in this work. First, the control scheme of the FERs is formulated as a quadratic programming problem, and then, an AFA-DNN visual servo controller is designed for the FERs. The adaptive gains of the controller can accelerate the convergence, improve the antinoise ability, and increase the convergence accuracy of the controller. Then, according to the Lyapunov theory, the fast convergence of the AFA-DNN in finite time is proven for both noise-free and noisy conditions. The experimental results indicate that the FER controlled by the proposed AFA-DNN can accurately track various trajectories and that the AFA-DNN has a better antinoise interference ability, higher convergence accuracy, and faster convergence speed than conventional methods. The convergence speed of the AFA-DNN is increased by a factor of 4.22 by using the adaptive gains. Experiments also indicate that the AFA-DNN remains well functioning under various noise disturbances (such as constant, periodic, linear, and Gaussian noise).

Estimating dewatering in an underground mine by using a 3D finite element model.

Groundwater inflow to an underground mine will seriously affect its mining plan and engineering geology safety. Groundwater models are powerful tools commonly used in the mines to develop dewatering strategies. Many mines in the Kolwezi area have been present since the 1950s, and groundwater flow patterns have been significantly influenced by mining activities. A mining plan is developed for an underground mine with overturned syncline strata in Kolwezi, Congo. Previous groundwater models using layered homogeneous media lowered model accuracies. A new three-dimensional groundwater model using FEFLOW, consisting of a combined regionally and locally geology models integrating 16 hydrogeological cross-sections and borehole logging data, are formulated to predict the underground dewatering in the study area. A 31-days pumping tests with 3 pumping wells and 28 observation wells are carried out to estimate the hydrogeological properties. The simulated water level data match the observed data rather well. Under 8 scenarios of possible well designs, the model predicts a possible dewatering capacity greater 23,900 m3/d at the initial stage of mining. The concept of the model and its application can be a reference for other mines with complex geology for mining safety in the region of interest.