Collision Probability Research Articles

Risk of pedestrian collision for persons with peripheral field loss: A computational analysis.

People with peripheral field loss report colliding with other pedestrians on their blind side(s). We show that, in dyadic collision scenarios between persons, one with field loss, such as homonymous hemianopia, and the other normally sighted pedestrian, collisions occur only if the persons with homonymous hemianopia are overtaking the pedestrians, and the collision risk is concentrated at farther bearing angles than previously suggested. Prior work computed the risk of collision while simulating both pedestrians as points and did not consider the ability of the other pedestrian's normal vision to avoid the collision. We extended the model to better characterize the open space collision risk posed for persons with homonymous hemianopia by normally sighted pedestrians where both have volume. We computed the risk of collision with approaching pedestrians using a model that simulates approaching pedestrians as volumetric entities without vision, volumetric entities with vision, and as points for comparison with the prior work. Collision risk of approaching pedestrians is characterized for all three conditions through spatial collision risk maps and collision risk densities as a function of bearing and radial distances. The collision risk for volumetric pedestrians is slightly different from that of point pedestrians. For volumetric pedestrians simulated with normal vision, the risk of collision was reduced substantially, as the other pedestrians could detect and avoid most impending collisions. The remaining collision risk is from pedestrians approaching at higher bearing angles (>50°) and from shorter radial distances (<2 m). Thus, collisions occurred when the pedestrians started in front of the person with homonymous hemianopia that was overtaking the pedestrian. The probability of collisions between pedestrians and the person with peripheral field loss is low and occurs only when the person with peripheral field loss is walking from behind the pedestrian at faster speed, thereby overtaking them. Such collisions occur with pedestrians at higher bearing angles, which should be monitored by assistive aids to avoid collisions. The same collision risk applies not only in homonymous hemianopia but also in other peripheral field loss such as monocular vision loss or concentric field loss, as common in retinitis pigmentosa and glaucoma.

Safety considerations for large constellations of satellites

The deployment of constellations of satellites within low Earth orbit (LEO) has implications for space operations and for the broader space environment. A large active satellite population will experience high numbers of conjunctions with other resident space objects (RSOs). Even if only a small proportion are high-probability events, the substantial number of conjunctions will still lead to many potentially high-risk encounters with other RSOs and a correspondingly high burden for their operators to mitigate them via maneuvers. This burden is exacerbated if the operator adopts an approach whereby risk mitigation maneuvers are conducted at collision probability levels below the widely accepted 1E-4 (1-in-10,000). Despite these significant efforts the remaining aggregate risk may still be relatively high because of the large number of conjunctions experienced by some constellations, leading to ongoing concern over the safety of these space systems. Through an analysis of conjunction assessment data, simulations using the DAMAGE computational model, and a new mapping approach, the risks from conjunctions between large constellations and other RSOs have been investigated. The results show that some existing constellations currently face more than a 10 % annual collision probability even after accounting for their robust risk mitigation approaches, with implications for the safety and long-term sustainability of large constellations and the broader LEO environment. Overall, the work emphasizes the need for new research and guidance on this aspect of space operations.

Path planning and collision avoidance approach for a multi-agent system in grid environments

Abstract In multi-robot systems, ensuring efficient, safe, and conflict-free navigation for each robot is crucial, especially in scenarios requiring the coordination of complex tasks and interactions with the environment. Currently, most related research focuses on simplified grid environments, making it difficult to apply these findings to real-world scenarios. This paper introduces actual physical constraints into traditional grid environment path planning and designs a set of motion rules suitable for grid environments and a collision avoidance algorithm. We also propose a novel multi-agent path planning approach that integrates deep reinforcement learning with collision avoidance algorithms. Through a series of experiments, we have demonstrated that this method effectively guides agents in navigating from their starting points to their targets within grid environments that possess physical constraints, and significantly reduces the probability of collisions when used in conjunction with our collision avoidance algorithm. These findings not only showcase the efficacy of our approach but also open new avenues for deploying multi-agent systems in more complex real-world scenarios.

Long-Term Fuel-Optimal Collision Avoidance Maneuvers with Station-Keeping Constraints

This work presents a sequential convex program method to compute fuel-optimal collision avoidance maneuvers for long-term encounters. The low-thrust acceleration model is used to account for the control, but the method can compute high-thrust maneuvers by increasing the maximum available acceleration. Dealing with the long-term conjunction poses additional challenges compared to the short-term problem because the encounter is not instantaneous. Thus, under the assumption of Gaussian statistics, the probability of collision is replaced by a simpler metric, the instantaneous probability of collision (IPoC), and a keep-out zone constraint is formulated as a continuous condition to be respected throughout the time frame of interest. The robustness of the solution is improved by introducing a constraint on the sensitivity of IPoC. Furthermore, the collision avoidance problem is coupled with the classical station-keeping requirement for geostationary Earth orbit satellites and with a return to the nominal orbit condition for low Earth orbit satellites. Even though no guarantee is given for the recovery of the global optimum solution, numerical simulations in different orbital regimes show that the proposed approach can yield a local fuel-optimal solution with a run time suitable for autonomous applications.

Two-Parameter Probabilistic Model and Experimental Research on Micron Particle Deposition

The deposition of micron particles in gas pipelines has always been an important problem in ultra-clean ventilation technology in the modern laser fusion, precision electronics, aerospace, and biomedical fields. Combining the mathematical expression of the migration, collision, and deposition of micron particles in a gas pipeline with a simulation of flow fields, a two-parameter particle probability deposition model based on vinl, θcr and collision probability coefficient PP is established, and the distribution law of particle deposition, considering two deposition targets of the pipe wall and deposition layer, is given. Combined with an experiment on particle migration and deposition in a gas pipeline, an interpretation and verification of the particle deposition distribution law are given, and the difference between the model and experiment is discussed through particle deposition efficiency mass distribution. Studies have shown the following: Under the premise of two kinds of deposition targets, different particle sizes in the gas pipeline present different deposition laws; the deposit morphology is a spot deposit of 10 µm particles and a flake deposit of 40 µm particles; the deposit position shows a uniform distribution and a lower wall dominance; and the deposit concentration area of 40 µm shows a more significant distribution. The results are very important for the selection and optimization of gas pipelines for clean spaces.

Smart e-waste management: a revolutionary incentive-driven IoT solution with LPWAN and edge-AI integration for environmental sustainability.

Managing e-waste involves collecting it, extracting valuable metals at low costs, and ensuring environmentally safe disposal. However, monitoring this process has become challenging due to e-waste expansion. With IoT technology like LoRa-LPWAN, pre-collection monitoring becomes more cost-effective. Our paper presents an e-waste collection and recovery system utilizing the LoRa-LPWAN standard, integrating intelligence at the edge and fog layers. The system incentivizes WEEE holders, encouraging participation in the innovative collection process. The city administration oversees this process using innovative trucks, GPS, LoRaWAN, RFID, and BLE technologies. Analysis of IoT performance factors and quantitative assessments (latency and collision probability on LoRa, Sigfox, and NB-IoT) demonstrate the effectiveness of our incentive-driven IoT solution, particularly with LoRa standard and Edge AI integration. Additionally, cost estimates show the advantage of LoRaWAN. Moreover, the proposed IoT-based e-waste management solution promises cost savings, stakeholder trust, and long-term effectiveness through streamlined processes and human resource training. Integration with government databases involves data standardization, API development, security measures, and functionality testing for efficient management.

Adaptive Speed Control Scheme Based on Congestion Level and Inter-Vehicle Distance

Cellular vehicle-to-everything (C-V2X) enables short-distance communication between vehicles and other users to improve road safety through data sharing. Conventional research on C-V2X typically assumes that vehicles travel at the same speed with a fixed inter-vehicle distance (Disinter). However, this assumption does not reflect the real driving environment or promote road traffic efficiency. Conversely, assigning different speeds to vehicles without a structured approach inevitably increases the collision risk. Therefore, determining appropriate speeds for each vehicle in the C-V2X framework is crucial. To this end, considering the road environment and mobility, this study introduces an adaptive speed mechanism based on the congestion level of a zone and Disinter. First, the given scenario is divided into several zones. Subsequently, based on the congestion level of a zone and the Disinter level, an adaptive speed is defined for each vehicle. This approach ensured that vehicles adopt lower speeds in congested situations to reduce the collision probability and higher speeds in sparse traffic cases to improve traffic efficiency. The performance of the proposed adaptive speed scheme is compared with that of conventional fixed-speed settings. The results show that the adaptive speed control scheme outperforms conventional fixed-speed schemes in terms of the packet reception ratio (PRR) and collision ratio (CR). Specifically, the proposed mechanism can reduce the CR to 0 and ensure that the PRR is higher than 0.98 in low-density scenarios.

Label-free and ultrasensitive detection of environmental lead ions based on spatially localized DNA nanomachines driven by hyperbranched hybridization chain reaction

A label-free fluorescent sensing strategy for the rapid and highly sensitive detection of Pb2+ was developed by integrating Pb2+ DNAzyme-specific cleavage activity and a tetrahedral DNA nanostructure (TDN)-enhanced hyperbranched hybridization chain reaction (hHCR). This strategy provides accelerated reaction rates because of the highly effective collision probability and enriched local concentrations from the spatial confinement of the TDN, thus showing a higher detection sensitivity and a more rapid detection process. Moreover, a hairpin probe based on a G-triplex instead of a G-quadruplex or chemical modification makes hybridization chain reaction more controlled and flexible, greatly improving signal amplification capacities and eliminating labeled DNA probes. The enhanced reaction rates and improved signal amplification efficiency endowed the biosensors with high sensitivity and a rapid response. The label-free detection of Pb2+ based on G-triplex combined with thioflavin T can be achieved with a detection limit as low as 1.8 pM in 25 min. The proposed Pb2+-sensing platform was also demonstrated to be applicable for Pb2+ detection in tap water, river water, shrimp, rice, and soil samples, thus showing great potential for food safety and environmental monitoring.

Optimizing photocatalytic performance in an electrostatic-photocatalytic air purification system through integration of triboelectric nanogenerator and Tesla valve

Increasing the collision frequency between gas molecules and photocatalysts can enhance the removal efficiency of volatile organic compounds (VOCs) and particulate matter (PM) in air. In this study, we propose an Electrostatic-Photocatalytic air purification system, containing Tesla valve, triboelectric nanogenerator (TENG), and photocatalysis parts. The incorporation of Ag@ZnO nanorod array (Ag@ZnO-NR) photocatalysts into the internal baffles of the Tesla valve pipeline effectively enhances the collision probability between air pollutant molecules and photocatalysts, and thus facilitating the removal efficiency of pollutants. Additionally, the high-voltage electricity (∼9.0 kV) generated by the TENG facilitates the separation of electron-hole pairs in the photocatalyst, leading to increased production of superoxide radicals (O•−2), hydroxyl radicals (•OH), and holes (h+), thereby enhancing the photocatalytic efficiency. In a 1.8 L space system, we achieved an approximately 97 % removal efficiency for toluene within 130 minutes and a similar efficiency for formaldehyde (∼200 ppm) within 175 minutes. Additionally, the PM2.5 concentration rapidly decreased from 999 μg·m−3 to 42 μg·m−3 within 6 minutes, alongside with a significantly faster pollutant removal rate compared to conventional methods. By integrating Tesla valves, TENG, and photocatalysis, this combined system presents an efficient and promising approach for addressing indoor air pollution, with potential applications across various settings.

Reinforced robotic bean optimization algorithm for cooperative target search of unmanned aerial vehicle swarm

Increasing attention has been given to the utilization of swarm intelligent optimization algorithms to facilitate cooperative target search of unmanned aerial vehicle swarm (UAVs). However, there exist common issues associated with swarm intelligent optimization algorithms, which are low search efficiency and easy to trap in local optima. Simultaneously, the concentrated initial positioning of UAVs increase the probability of collisions between UAVs. To address these issues, this paper proposes a reinforced robotic bean optimization algorithm (RRBOA) aimed at enhancing the efficiency of UAVs for cooperative target search in unknown environments. Firstly, the algorithm employs a region segmentation exploration strategy to enhance the initialization of UAVs, ensuring a uniform distribution of UAVs to avoid collisions and the coverage capability of UAVs search. Subsequently, a neutral evolution strategy is incorporated based on the spatial distribution pattern of population, which aims to enhance cooperative search by enabling UAVs to freely explore the search space, thus improving the global exploration capability of UAVs. Finally, an adaptive Levy flight strategy is introduced to expand the search range of UAVs, enhancing the diversity of UAVs search and then preventing the UAVs search from converging to local optima. Experimental results demonstrate that RRBOA has significant advantages over other methods on nine benchmark simulations. Furthermore, the extension testing, which focuses on simulating pollution source search, confirms the effectiveness and applicability of RRBOA

Insight into the Effect of Nanobubbles on Fine Muscovite Powder Flotation in Different Dodecylamine Concentrations and Stirring Intensities: Kinetics and Mechanism

Flotation-introduced nanobubbles were expected to be an efficient and economical method to recover fine muscovite. This study aimed to explore the mechanism of the change appearing in flotation after introducing nanobubbles through micro-flotation, particle vision and measurement, flotation kinetics, and induction time measurement. The results of micro-flotation, which respectively feed muscovite or muscovite pretreated with nanobubbles in different concentrations of dodecylamine (DDA), were fitted with four flotation kinetic models using Origin. Different methods were used to examine how the introduction of nanobubbles affected the flotation process. The results showed that nanobubbles improved both the flotation rate and recovery of muscovite. Nanobubbles played different roles in different stirring intensities. At low stirring intensity, nanobubbles did not perform well. In suitable stirring intensity, nanobubbles helped particles aggregate and improved the collision probability between bubbles and minerals. However, at high stirring intensity, shear forces caused by ultra-high fluid velocities could disrupt particle aggregation.

Influences of Space Weather Forecasting Uncertainty on Satellite Conjunction Assessment

AbstractA significant increase in the number of anthropogenic objects in Earth orbit has necessitated the development of satellite conjunction assessment and collision avoidance capabilities for new spacecraft. Neutral mass density variability in the thermosphere, driven by enhanced geomagnetic activity and solar EUV absorption, is a major source of satellite propagation error. This work investigates the impacts of space weather driver forecasting uncertainty on satellite drag and collision avoidance maneuver decision‐making. Since most operational space weather driver forecasts do not offer an uncertainty assessment, the satellite operator community is left to make dangerous assumptions about the trustworthiness of the forecast models they use to perform satellite state propagation. Climatological persistence‐based forecast models are developed for F10.7 and Kp. These models accurately capture the heteroscedastic and, at times, highly non‐Gaussian uncertainty distribution on forecasts of the drivers of interest. A set of realistic satellite conjunction scenarios is simulated to demonstrate the contributions of space weather driver forecast uncertainty on the probability of collision and maneuver decisions. Improved driver forecasts, especially forecasts of F10.7, are demonstrated to be very useful for enabling durable maneuver decisions with additional lead time (up to 24 hr for the period examined), though the improvement depends on the specific conjunction scenario of interest.

Evaluation of industrial performance of a new three phase fluidized bed flotation column-Based on product size characterization

There are still a large number of minerals processed by flotation every year, so it is extremely important to improve the flotation efficiency in industrial production. This study established an experimental test platform for new three-phase fluidized bed flotation column (TFC). The effects of different operating conditions and equipment parameters (apparent gas velocity, apparent liquid velocity, and filling height) on separation effect of coal slime were investigated. Relationship between turbulence intensity inside TFC and the flotation effect of coal slime with different particle sizes was analyzed. Results show that turbulence intensity in fluidized environment can be influenced by adjusting operating conditions to increase the probability of adhesion and collision of fine-grained particles with air bubbles. Differences of particle size distribution in the radial and axial directions of TFC are influenced by settling velocity. Increasing circulation volume can increase residence time of particles in flotation process. Micro and nano bubbles have excellent characteristics which are beneficial to particle collision and adhesion. By adjusting the parameters, it can meet needs of mineral separation and mineralization environment and realize effective recovery of slime with different particle sizes. This study was conducted by analyzing the flotation of fine particles by TFC during industrial platform testing. By evaluating the industrial performance of TFC, it provides a reference for future industrial large-scale applications.

Decision support for traffic safety: case of rear-end collision modelling

ABSTRACT This paper presents the decision problem of selecting a collision-warning activation algorithm for Rear-End Collision Alert Signal (RECAS) systems installed in motorcycles and other powered two-wheelers. Using Agent-Based Modelling, Discrete Event Simulation and System Dynamics, we have developed a hybrid simulation model of three scenarios of rear-end collisions to measure the performance of several algorithms found in the literature. The best-performing algorithm, by Hirst & Graham, has reduced the probability of collisions on average by 31.21% in comparison with the baseline scenario of using a standard brake light. Using this algorithm also resulted in up to 11.20% reduction in the estimated severity of injuries when a rear-end collision was not averted. As the Hirst & Graham algorithm was the most effective in all the tested emergency braking scenarios and across all the tested speed limits, we recommend this algorithm to be used in RECAS systems in powered two-wheelers.

SPRISS: Scalable and precise resistive impact sensor for smallsats, architecture description and tests

Space debris are a tangible risk for satellites in Earth orbits. Indeed, in the last decades fragmentation events have generated a large number of uncontrolled objects that have made the debris population grow. Modelling the space debris environment is becoming a fundamental task to evaluate the vulnerability of operational satellites, the probability of accidental collisions with uncontrolled objects, and the evolution of the debris population. With this aim, remote and in-situ measurements provide valuable data to tune the space debris population models and improve their reliability. While large satellites can be observed and tracked from ground, the sub-millimeter debris population requires in-situ measurements. In this context, in-orbit impact sensors are a key technology to obtain information about the sub-mm space debris environment. In this framework, a small-scale impact sensor sized to be integrated in a 2U CubeSat is being developed at the University of Padova. The sensor consists of a multitude of thin, conductive stripes arranged on a thin film of non-conductive material. When a debris hits the sensor, one or more stripes are severed, and the impact is detected. Moreover, the sensor design ensures low power consumption, making it feasible for CubeSat space missions. This work presents the latest outcomes obtained from the development of the sensor. Specifically, structural analyses are performed to assess that the sensor can withstand the launch loads, as well as thermal analyses to confirm its endurance capability with in-orbit temperatures. The number of expected impacts during the mission is predicted through orbital propagation, using state-of-the-art debris environment modelling tools. Finally, the paper presents a functional shooting test and vibration tests, executed onto a development model of the sensor, which verify its functionality and validate a Technology Readiness Level (TRL) of 4.

Enhanced separation of oil-in-water emulsion by cyclic penetration of emulsion droplets through an oil layer

The separation of emulsion components is a typical heterogeneous phase separation process. This process can be promoted by coalescence of the dispersed phase droplets. However, the coalescence would be inhibited due to the interface between the continuous and dispersed phases. The separation efficiency can be increased by increasing the probability of collisions between the droplets, and this can be realized by increasing the area of contact among the dispersed phase droplets. In this study, a new enhanced separation method involving the circulation of emulsion droplets containing an emulsified oil phase through an oil layer is proposed. The migration of the emulsified oil phase from the millimeter-sized droplets to the oil layer was studied. This migration enabled efficient separation of the oil and water phases, and this process was assessed by using a dyeing agent in the oil phase and by monitoring the variation in the turbidity. The influence of main factors such as the circulating droplet size, thickness of the oil layer, and effect of the circulation rate on the separation was determined. The turbidity of the emulsion reduced from 394.33 NTU to 10.98 NTU, with a separation efficiency of 97.22 % under the optimum operation conditions. The linear fitting relationship for the main factors that affect separation with the duration or number of circulation cycles was obtained. The results indicate that the novel strategy of using an additional oil layer and circulating emulsion droplets through it is promising for oil–water separation, especially via gravity separation.

Hybrid CSMA/CA and HCCA uplink medium access control protocol for VLC based heterogeneous users

Light fidelity (LiFi) is an emerging wireless networking technology of visible light communication (VLC) paradigm for multiuser communication. This technology enables high data rates due to the availability of large visible light spectrum. While current studies have shown the potential for LiFi technology, they borrow the MAC-layer protocols from traditional WiFi. However, a number of prior studies have shown the challenges faced by the MAC-layer of WiFi in the presence of large number and types of devices. In this work, we show that the hybrid-coordination-function-controlled-access (HCCA) MAC protocol in LiFi provides higher throughput than the traditional CSMA/CA mechanism to user devices. We also show that HCCA has the limitation of higher message overhead in the presence of a large number of devices. We also evaluate the collision probability, busy channel probability, and delay for HCCA and CSMA/CA MAC protocol. We utilize both theoretical analysis and extensive simulations to study these performance tradeoffs and identify a threshold when a LiFi access point should switch to HCCA from CSMA/CA and vice-versa. Finally, based on our findings, we design a hybrid-MAC mechanism that switches between HCCA and CSMA/CA based on the number and type of devices present. Our evaluation shows that this hybrid mechanism can outperform both HCCA and CSMA/CA individually in the presence of different number of devices.

Target assignment for multiple stages of weapons systems using a deep Q-learning network and a modified artificial bee colony method

Multistage Weapon Target Assignment (MWTA) in defense systems is a critical process that focuses on minimizing deviations and inaccuracies during target assignment across stages like initialization, tracking, and counterattack. The research problem lies in efficiently assigning targets to weapon systems while accounting for distractions and tracking accuracy constraints. Existing approaches often face challenges related to computational complexity, real-time engagement limitations, and scalability issues, leading to inaccuracies in various stages within the system's perceived radius. This paper proposes a novel State-based Modified Artificial Bee Colony Method (SMABCM) that integrates Q-learning to generate adaptive target assignment decisions. SMABCM aims to maximize assignment accuracy by prioritizing low deviation rewards, enabling precise one-to-one target tracking and reducing the population of the artificial bee colony. The Q-learning network dynamically defines generation and reduction states based on deviations to minimize distracting targets and enhance tracking precision. Experimental results demonstrate SMABCM's superior performance over existing approaches in target precision comparison, hit probability, increase in distracting target detection, reduced deviation factor, and computation time. As the speed increases, the proposed SMABCM improves target accuracy by 9.54 %, hit probability by 9.17 %, distracting target detection by 12.35 %, while reducing deviation by 7.39 % and computation time by 10.11 %. This approach addresses complexities in multistage weapon systems through dynamic strategies, contributing to proactive defense against evolving security threats.

The development of an efficient precipitation-flotation-dewatering (PFD) process for acid mine drainage treatment

Acid mine drainage (AMD) stands as a prevalent environmental challenge across numerous mining sites, often addressed through the high-density sludge (HDS) process, a typical neutralization and sedimentation process. However, despite its widespread use, the HDS process requires prolonged treatment durations and presents challenges in sludge dewatering and site relocation, thus falling short of an optimal solution. In this study, an efficient precipitation-flotation-dewatering (PFD) process was developed and optimized as a viable alternative to the HDS process, offering efficient AMD treatment. The experimental results indicate that over 90 % of ions were successfully precipitated by employing CaO as a neutralizing agent to adjust AMD pH to 10.0. Flotation was then conducted with a low-profile flotation column after adding an optimal concentration of 10 mg/L of A-100 flocculant and 400 mg/L of NaOL. Compared with original AMD, the final removal of toxic and hazardous ions of Fe, Al, Cd, Sn, Co, Ni, Zn, and Mn were 97.61 %, 98.85 %, 98.21 %, 97.78 %, 97.22 %, 99.34 %, 99.89 %, and 99.14 %, respectively. Additionally, the solid content of produced sludge was 27 %. Mechanistic inquiries revealed that A-100 and NaOL both chemically adsorbed on the particle surface and respectively enhanced the collision and attachment probabilities between precipitate particles and bubbles, thereby augmenting the separation efficiency. Furthermore, shortening the flotation column reduced the particle flotation path, thereby improving the flotation efficiency. The efficient PFD process exhibits significant advantages of rapid and effective AMD treatment, high sludge solid content, small footprint, and high relocatable convenience, demonstrating satisfactory cost effectiveness and significant potential as a replacement of the HDS process for AMD treatment.

Mott-Schottky junction mediated photothermal-pyroelectric synergy for effective collection of waste heat in flexible sensing platform

Solar–energy–induced photothermal–pyroelectric synergy sensing platform provides a win-win route to harvest waste heat and convert energy. However, the increase of carrier collision probability from high temperature inevitably leads to the loss of quantum efficiency. Herein, a flexible photothermal-pyroelectric electrode platform with Schottky junction was successfully constructed for maximum utilization of carrier. Under solar-simulated irradiation, the electron-rich and electron-depletion region formed by the Bi13S18Br2-S/alloy rectifier interface in flexible polyvinylidene difluoride-hexafluoropropylene film can increase the accumulation of photogenerated electrons. Meanwhile, the surface bound charges released by dipole oscillation in photothermal-pyroelectric field are continuously supplemented by the emerged high concentration of photogenerated electrons from the Schottky junction, and this synergistic effect prolonged their lifetimes and significantly improves the photoelectric conversion efficiency. To reasonably realize the accurate quantification of the simulated target, the cleavage activity of the CRISPR–Cas system can be specifically restored with the assistance of a synergistic dual-activator, releasing silica as a padlock to produce a target concentration-dependent photoelectric signal. Besides, the temperature variation on the electrode interface was simulated, revealing the synergistic effect between Schottky junction and photothermal–pyroelectric field under photoexcitation. This work broadens a new perspective for upgrading photoelectron utilization and overall performance of flexible sensing platform.