Table of Content

25 January 2025, Volume 53 Issue 1

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2025, 53(1):  0. 

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Energy，Power & Electrical Engineering

Distributed Energy Cluster Scheduling Method Based on EA-RL Algorithm



CHENG Xiaohua, WANG Zefu, ZENG Jun, et al

2025, 53(1):  1-9.  doi:10.12141/j.issn.1000-565X.240218

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At present, the research on distributed energy cluster scheduling is mostly limited to a single scenario and lacks efficient and accurate algorithms. Aiming at these problems, this paper proposed a multi-scenario scheduling method for distributed energy clusters based on evolutionary algorithm experience-guided deep reinforcement learning (EA-RL). The individual models of power supply, energy storage and load in distributed energy cluster were established, respectively. Based on the individual scheduling model, a multi-scenario distributed energy cluster optimal scheduling model including auxiliary peak regulation and frequency modulation was established. Based on the framework of evolutionary reinforcement learning algorithm, an EA-RL algorithm was proposed. The algorithm combines genetic algorithm (GA) and deep deterministic policy gradient (DDPG) algorithm. The empirical sequence was used as the individual of genetic algorithm for crossover, mutation and selection. The high-quality experience was selected to join the DDPG algorithm experience pool to guide the training of the agent to improve the search efficiency and convergence of the algorithm. According to the multi-scenario scheduling model, the state space and action space of the multi-scenario scheduling problem of distributed energy cluster were constructed. Then, the reward function was constructed by minimizing the scheduling cost, the deviation of the auxiliary service scheduling instruction, the over-limit power of the tie line and the power difference between the source and the load, and the reinforcement learning model was established. To validate the effectiveness of the proposed algorithm and model, offline training of scheduling agents was conducted based on multi-scenario simulation cases, resulting in agents capable of adapting to various grid scenarios. Verification was carried out through online decision-making, and their scheduling decision-making capabilities were assessed based on decision outcomes. The validity of the algorithm was further verified through comparison with the DDPG algorithm. Finally, the trained agents undergo 60 consecutive days of online decision-making tests incorporating varying degrees of disturbances to validate their posterior effectiveness and robustness.

Digital Twin Modeling Method of Temperature Field in Distribution Cables Based on Reduced Order Model



NIU Haiqing, HUANG Shijie, WANG Dong, et al

2025, 53(1):  10-20.  doi:10.12141/j.issn.1000-565X.240050

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State perception of power equipment is one of the key issues in the construction of smart grid. Digital twin (DT) technology can map and quickly predict the physical state of equipment in real-time, but existing modeling methods are difficult to meet the real-time computing requirements. This paper proposes a DT modeling method for distribution cables temperature field based on reduced-order model. The method first establishes a multi-physics full-order model of cables, builds a reduced-order model of the steady-state temperature field based on singular value decomposition and response surface interpolation methods. Combining the steady-state reduced-order model and temperature measurement data, the multi-circuit cables heat transfer inverse problem is solved to reconstruct the transient temperature field inside the cables in real-time, and the correctness is verified based on the temperature rise test results. Furthermore, the proposed method is employed to reconstruct the internal transient temperature field of 10 kV cables in actual operation. Taking the reconstructed result as the known initial state, the cable conductor temperature during emergency operation is quickly predicted based on the reduced-order model and the improved superposition method. As compared with the simulation results of the full-order model, the maximum relative error of the conductor temperature DT reconstruction value is 1.76%, the conductor temperature prediction error during emergency operation is 1.01%. The calculation time of single reconstruction and prediction is 8.1 s and 3.6 s, and the calculation efficiency is about 35 555 times and 6 000 times that of the full-order model, respectively. The new method takes calculation speed, calculation accuracy and modeling cost into consideration, and has reference significance for the temperature field DT modeling of other types of power equipment.

Investigating an Enhanced H-AC Algorithm-Based Strategy for Energy-Saving Optimization Control in Cold Source System



ZHOU Xuan, MO Haohua, YAN Junwei

2025, 53(1):  21-31.  doi:10.12141/j.issn.1000-565X.240105

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The optimization of the number of central air-conditioning cooling source units and their operating parameters is a collaborative optimization problem involving both discrete and continuous variables, which poses challenges for classical reinforcement learning algorithms. To address this problem, this paper proposed an energy-saving optimization control strategy for central air-conditioning cooling source systems based on a combination of the options-critic and actor-critic frameworks. Firstly, a hierarchical actor-critic (H-AC) algorithm was utilized to hierarchically optimize the number of units and operating parameters, with both the high-level and low-level models sharing a Q-network to evaluate state values, thereby addressing optimization challenges across multiple time scales. Secondly, the H-AC algorithm was improved in terms of agent architecture, policy, and network update mechanisms to accelerate the convergence of the agent. Finally, the proposed method was validated on the cooling source system of a research building located in a hot summer and warm winter region, using a TRNSYS simulation platform for experiments. The results demonstrate that, under conditions where the average indoor comfort time proportion is increased by 14.08, 11.23, 29.70 and 9.07 percentage points, respectively, the system energy consumption based on the improved H-AC algorithm is reduced by 32.28%, 28.55%, 28.64%, and 11.53% compared to four classical DRL algorithms. Although the system energy consumption of the improved H-AC algorithm is 0.27% higher than that of the options-critic framework, it achieves a more stable learning process and increases the average indoor comfort time proportion by 4.8%. This approach offers effective technical solutions for energy-saving optimization of central air-conditioning cold source systems in various building types, contributing to the achievement of buildings’ dual-carbon goals.

Review of Decision-Making Analysis for Transportation Energy Transition



CHEN Cuifeng, LIN Zhenhong, HUANG Chikun, et al

2025, 53(1):  32-48.  doi:10.12141/j.issn.1000-565X.240238

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To achieve the goal of building a country with strong transportation network, it is necessary to highly develop infrastructure, establish an efficient operational system, promote technological innovation, and achieve sustainable development. Under the dual carbon goals, the sector of transportation must achieve deep carbon reduction through energy transition. This aligns with the sustainable development element in the process of building a country with strong transportation network. However, it is also essential to avoid negative impacts on resource allocation for transportation infrastructure and operational systems due to errors or overly hasty decisions in energy transition. Such impacts could hinder the smooth advancement of the strategy to build a country with strong transportation network. Because energy transition involves many key decision factors such as vehicle power technology, infrastructure building, user conduct, and policy-making, its complexity and importance can’t be ignored. This paper aims to delve into the significance, methods, tools, and experiences of decision-making analysis for transportation energy transition at the intersection of building a country with strong transportation network and achieving the dual carbon goals. By combining literature reviews and case studies, it seeks to provide theoretical and practical reference for national policies and corporate decision-making, while also fostering greater attention and research on related decision-making analyses. Firstly, this paper describes the meaning and motivation of transportation energy decision-making analysis and abstractly summarizes it relying on an optimization model framework. Secondly, based on the vehicle power technology, infrastructure, user conduct, and policy-making, a detailed demonstration is carried out by using the optimization model framework mentioned above and citing analytical cases in existing cases which include mileage optimization of an electric vehicle, charging network planning, user conduct of making choice, emission reduction and fairness of policy, and so on. Thirdly, the impact that improper assumptions in the decision-making and analysis of transportation energy transition on industry and society is pointed out according to the published cases or policy implementations. Finally, this paper summarizes the significance and feasibility of decision-making analysis in the transformation of transportation energy and proposes several research topics to encourage further exploration in this field. By integrating the strategy of building a country with strong transportation network with the dual carbon goals, this paper aims to provide comprehensive theoretical support and practical gui-dance for decision-making in transportation energy transformation, thereby promoting sustainable development in China’s transportation sector.

Electronics, Communication & Automation Technology

Design of a Cascade Controller of Trajectory Tracking for Omnidirectional AGV Driven by Mecanum Wheels



WEN Shengping, SU Yilong, QU Hongyi

2025, 53(1):  49-61.  doi:10.12141/j.issn.1000-565X.240207

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Aiming at the trajectory tracking control problem of four-Mecanum-wheel AGV (Automatic Guided Vehicle), this study designs a controller named MPC+ELM-SMC, which connects model prediction control and adaptive sliding mode control to improve the control accuracy and stability, and to enhance the control process hierarchy, specificity and effectiveness. At the kinematic level, the trajectory tracking error model is established, which is transformed into a quadratic programming problem, and constraints are added to solve the optimal solution of the quadratic programming online with the rolling optimization of the model predictive control, and the AGV pose error is converted into the expected output of the wheel speed. At the dynamic level, sliding mode control is used to obtain the wheel torque output and to realize the wheel’s tracking of the expected speed. The ELM (Extreme Learning Machine) neural network with fast and accurate approximation ability is introduced to carry out online observation of the model uncertainty and unknown interference, and the adaptive interference is offset in combination with sliding mode control to further improve the robustness of the controller. Under the conditions of cosine disturbance and pulse interference, the controller is simulated and verified. Compared with PID control, the MPC+SMC cascade controller has obvious advantages in tracking effect. Moreover, compared with the cascade controller observed by RBF (Radial Basis Function) neural network, the ELM observer is more robust to interference, for instance, the observation effect remains above 95% under various rotational speed conditions, the tracking error of the proposed control method is one order of magnitude smaller than other methods in multiple indicators, with a maximum deviation of only millimeters. Finally, an experimental platform is set up to perform actual trajectory tracking experiment, and the results verify the practicability and feasibility of the proposed controller.

Meta-DAE Fault Diagnosis Based on Prototype Domain Enhancement in Few-Shot



MA Ping, LIANG Cheng, WANG Cong, et al

2025, 53(1):  62-73.  doi:10.12141/j.issn.1000-565X.230715

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Rolling bearings, as a type of precision mechanical component, are widely used in modern industrial machinery and equipment. It is of great significance to diagnose bearing faults using reasonable methods during bea-ring operation. However, in the actual complex and ever-changing environment, the collection of vibration signals often faces challenges such as limited sample sizes, noise interference, and operating condition variations, resulting in low fault diagnosis accuracy. To address the problem of small-sample rolling bearing fault diagnosis under noise interference and variable operating conditions, this paper proposed a meta-learning denoising model based on prototype domain enhancement (Meta-DAE). Firstly, a small-sample fault dataset based on time-frequency diagrams was constructed, and a deep convolutional generative adversarial network was introduced for data preprocessing to gene-rate a pseudo-sample set with a similar distribution. Then, the fault sample set was input into Meta-DAE for adaptive feature extraction. Meta-DAE adopts a prototype domain enhancement strategy to make prototype points of the same category more closely clustered in the embedding space. At the same time, an encoder with noise reduction performance was constructed, and a target function based on prototype domain enhancement and denoising was designed. By fine-tuning the model under small-sample conditions, the noise robustness and classification accuracy of the model were improved. Experimental results of small-sample fault diagnosis under noise interference and variable operating conditions show that, compared to other models, the proposed model demonstrates strong noise robustness. Under -8 dB strong noise interference, the model achieves a classification accuracy improvement of 35.78% to 57.25% using only 10 samples for fine-tuning.

An Autonomous Extrinsic Calibration Method for 4D Millimeter-Wave Radar Point Clouds and Visual Images



BI Xin, WENG Caien, WANG Yu, et al

2025, 53(1):  74-83.  doi:10.12141/j.issn.1000-565X.240172

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With the rapid development of autonomous driving technology, the demand for multi-sensor fusion in environmental perception systems is increasing. Four-dimensional (4D) millimeter-wave radar has become one of the critical sensors in autonomous driving due to its stable performance under complex weather and lighting conditions. Although 4D millimeter-wave radar improves object detection accuracy by adding elevation angle information and increasing point cloud density, its sparse point clouds and noise issues limit its independent application. Therefore, the fusion of 4D millimeter-wave radar with vision sensors has become key to enhancing perception accuracy in autonomous driving. However, traditional extrinsic calibration methods rely on cumbersome manual operations, making it challenging to meet the requirements for efficient automated calibration. To address this issue, this study proposed an automated extrinsic calibration method for 4D millimeter-wave radar and visual images based on a calibration board. The method first designs a calibration board with ChArUco markers, red circular rings, and corner reflectors, and then automatically extracts image coordinates and radar point cloud coordinates of the calibration points using a circle detection algorithm and a corner reflector detection algorithm. Furthermore, a method for calibration data acquisition and validation was proposed using simulations in 3D Max and Unity. Finally, the performance of direct linear transformation (DLT) and extrinsic calibration (EC) methods is compared through experiments to evaluate calibration accuracy. Experimental results indicate that the designed calibration board and automated calibration algorithm effectively reduce manual operations, and the EC method demonstrates higher calibration stability and accuracy when more calibration points are involved.

A Design Method of Sparse FIR Filter Based on Weighted Least Squares



ZHUANG Ling, SONG Shiwei, LIU Ying

2025, 53(1):  84-91.  doi:10.12141/j.issn.1000-565X.230574

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The development of large-scale communication systems puts higher requirements on traditional filter design. Sparse finite impulse response (FIR) filters have the characteristics of low computational complexity and low implementation cost, but conventional convex relaxation approximation design methods produce additional approximation errors, exhibit suboptimal sparsity, and involve complex solving processes. To address the issue of high implementation costs caused by the large number of multipliers in FIR filter design, this paper proposed a sparse FIR filter design method based on a weighted least squares criterion. Firstly, the norm of the initial sparse representation is replaced based on the properties of different norms, thereby improving the objective function. This modification maintains sparsity while addressing the challenge of directly solving non-convex functions. Next, the target problem was reformulated as the difference between two convex sub-problems. Simplified sub-problems were constructed according to iterative rules, and an alternating solution method was adopted to further enhance solving efficiency and reduce complexity. Finally, after determining the positions of zero coefficients, a weighted least squares problem was solved to further reduce approximation errors. The simulation results show that compared with the existing sparse filter solving methods, the proposed method can improve the coefficient sparsity performance of FIR filters, reduce the number of multipliers and obtain a compromise between root-mean-square error and maximum error in the case of sparsity enhancement. Meanwhile, the computational solving time is significantly reduced, and solving efficiency is notably improved.

Materials Science & Technology

Preparation and Performance Study of Tri-Component Copolymerized High Dielectric Performance Polyimide



CAO Xianwu, YAO Zhiqiang, HUANG Qilong, et al

2025, 53(1):  92-100.  doi:10.12141/j.issn.1000-565X.240053

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At present, with the development of the energy field, the requirements for capacitors continue to increase. Capacitors with high temperature performance and high energy storage have become a research hotspot. High energy storage density requires high dielectric constant and low dielectric loss. The special engineering material polyimide (PI) is favored by people because of its high temperature resistance, but its low energy storage density restricts its application. In order to make better use of the high temperature resistance of polyimide and find an excellent synthesis route from the diversity of its synthetic raw materials, this paper aimed to prepare polyimide (PI) with high dielectric constant and low dielectric loss, and study the effect of isomer 2,3,3',4'-biphenyltetracarboxylic dianhydride (a-BPDA) and 3,3',4,4'-biphenyltetracarboxylic dianhydride (s-BPDA) on the dielectric properties of polyimide. Using a-BPDA, s-BPDA, 3,3',4,4'-benzophenonetetracarboxylic dianhydride (BTDA), 4'-bis (3-aminophenoxy) diphenyl sulfone (m-BAPS) as raw material, PI film was prepared by ternary copolymerization, so as to verify the feasibility of the scheme. On this basis, the proportion of raw materials was allocated to explore the best performance of various raw material ratios. The films were characterized by FTIR analysis, XRD analysis, thermal performance analysis and dielectric performance analysis. The experimental results show that a-BPDA, s-BPDA, BTDA and m-BAPS can successfully synthesize polyimide films. The synthesized films still have high thermal properties. a-BPDA and s-BPDA increase the glass transition temperature of polyimide to 245.8 ℃ and 239.1 ℃, respectively. s-BPDA and a-BPDA have different effects on the dielectric properties of polyimide. When the ratio of s-BPDA to BTDA is 3∶2, the dielectric constant of sPI was 4.25 and the dielectric loss is 0.002 9 at 1 000 Hz. When the ratio of a-BPDA to BTDA is 3∶2, the dielectric constant of aPI is 3.49 and the dielectric loss is 0.002 3. Under comprehensive comparison, s-BPDA is more effective in improving the thermal and dielectric properties of polyimide.

Synthesis and Emulsifying Effect of Nonionic Waterborne Epoxy Resin Emulsifiers



LI Wenbo, YI Die

2025, 53(1):  101-107.  doi:10.12141/j.issn.1000-565X.240128

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In order to improve the emulsifying agent compatibility with epoxy resin, a series of nonionic waterborne epoxy emulsifiers with A-B-A (A is epoxy chain segment, B is hydrophilic chain segment) structure were synthesized by two-step method using polyethylene glycol (PEG6000, PEG4000, PEG2000), methyl hexahydrophthalic anhydride (MHHPA) and epoxy resin (E44) as raw materials. The structure of the emulsifier was characterized by infrared spectrum analysis, and the optimal synthesis process was determined by infrared spectrum analysis and acid titration: esterification reaction was carried out with PEG and MHHPA in the molar ratio of 1∶2.1 under the temperature of 110 ℃ for 3 h; then E44 in the same number of moles of MHHPA was added in and the epoxy ring-opening reaction was carried out under the catalyst tetrabbutylammonium bromide (TBAB, 1% of the amount of epoxy resin) at 110 ℃ for 3 h. Waterborne epoxy emulsion was prepared by using the synthesized emulsifier on epoxy resin E44. Then it studied the effects of relative molecular mass of PEG, emulsifier content, emulsifying temperature and stirring speed on the stability of the emulsion. After comprehensive consideration of emulsion stability, particle size and distribution, the results show that the emulsifier synthesized by PEG6000 has better emulsifying effect, with HLB value of 16.5 and turbidity point of 90 ℃, which is superior to PEG4000 and PEG2000. When the emulsion solid content is about 45%, the emulsifier content is 20%, emulsifying at 75 ℃ and stirring speed of 2 000 r/min, the water-based epoxy emulsion with small average particle size and narrow distribution can be obtained, and shows good emulsion stability.

Microstructure and High Temperature Deformation Resistance of Nickel-Based Coating on TC4 Surface



FU Yuming, LI Changcheng, YAN Maorong, et al

2025, 53(1):  108-117.  doi:10.12141/j.issn.1000-565X.240094

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In order to study the high temperature and deformation resistance of laser cladding coating on TC4 surface, different proportions of nickel-metal-multi-ceramic composite coatings were prepared on TC4 matrix by laser cladding technology. And GH4169 nickel-based superalloy powder was taken as the base powder, HfC, ZrC, TaC and NbC transition carbides as the reinforcing phase. The microstructure, hardness and high temperature deformation resistance of coatings with different multi-component ceramic powder contents were systematically studied by microstructure characterization and performance experiments. The results show that the addition of carbide ceramic reinforcement phase refines the microstructure of the coating and improves the hardness, and the hardness is the highest when the proportion of ceramic reinforcement phase is 15%, which is 2.54 times that of the substrate. With the increase of temperature, the internal dendrites of the pure nickel-based cladding coating were dissolved and separated, and gradually isoaxed. The dendrite fragmentation appeared in the nickel-based cladding coating supplemented with 15% ceramic powder, and the ceramic strengthened phase dispersed in the cladding layer gathered and grew. Under the conditions of three temperature compression test temperatures (700, 800 and 900 ℃), the maximum equivalent stress and maximum equivalent strain of the specimen appear in the matrix, and compared with the TC4 specimen, the laser cladding specimen produces a stress abrupt change in the coating bonding zone, and the deformation resistance ability of the laser cladding specimen coating is enhanced.

Microstructure and Mechanical Properties of SiC Particle Reinforced AlMgScZr Composites by Selective Laser Melting



MA Guonan, ZHANG Le, OU Yang, et al

2025, 53(1):  118-128.  doi:10.12141/j.issn.1000-565X.240108

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Aluminum matrix composites have the characteristics of high hardness and difficult machining. In order to achieve near-net forming of aluminum matrix composites with high specific strength and high specific modulus, micron SiC particles with volume fraction of 10% reinforced AlMgScZr composites were fabricated using selective laser melting (SLM) technique. The relationship between the laser energy density and scanning rate and the forming quality of the composite was established. The microstructure and mechanical properties were characterized and tested by optical microscope (OM), scanning electron microscope (SEM), transmission electron microscope (TEM), X-ray diffraction (XRD) and universal testing machine. The effect of micron SiC particles on the solidification structure and mechanical properties of SLMed aluminum matrix composites was investigated. The results show that the best quality composite could be obtained under the conditions of layer thickness of 30 μm, scanning spacing of 0.12 mm, laser power of 260 W, scanning rate of 1 000 mm/s, and its relative density was up to 99.81%. During the laser cladding process, there was a strong interfacial reaction between SiC particles and Al matrix. Micron-sized acicular Al₄SiC₄ bands were formed in situ, and the sharp corners of SiC particles are obviously passivated. Al₄SiC₄ bands and the residual SiC particles formed a mixed reinforced structure. The optimal tensile strength, elongation and elastic modulus of aged SiC/AlMgScZr composites were 379 MPa, 12% and 84 GPa, respectively. The fracture behavior of the composites included ductile fracture of Al matrix and brittle cleavage fracture of Al₄SiC₄ phases. A large number of cross-distributed acicular Al₄SiC₄ bands were the main factors leading to premature failure and fracture of SiC/AlMgScZr composites.

Biological Engineering

The Effect of Hypoxic Environment on the Enhancement of Collagen Content in Tissue-Engineered Vascular Grafts



LIN Zhanyi, XIAO Cong, XU Jianyi, et al

2025, 53(1):  129-135.  doi:10.12141/j.issn.1000-565X.240137

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In the field of vascular tissue engineering, current technological advancements are focused on the proli-feration and secretion of collagen-rich extracellular matrix (ECM) by vascular smooth muscle cells (VSMCs) in vitro, coupled with specific mechanical stimuli to reconstruct biomaterials with desired mechanical properties. The optimal oxygen concentration is crucial for three-dimensional cell culture in vitro. However, there is a lack of sufficient research regarding its application in tissue-engineered vascular graft (TEVG). To this end, this study designed varying oxygen concentration environments to determine the optimal value for VSMCs culture by assessing cell proliferation activity. Furthermore, collagen gene expression and protein secretion were measured under normoxic and hypoxic conditions, along with quantification of total collagen content deposited in the cell layer using hydroxyproline assay. Subsequently, VSMCs were seeded on polyglycolic acid (PGA) scaffolds for three-dimensional culturing to form TEVG, and the effects of hypoxic conditions on TEVG cultivation were observed through histological staining and total collagen quantification. The results indicate that VSMC cell activity increased most rapidly at 7% oxygen concentration; under hypoxic conditions, an upregulation of type I (Col I) and type Ⅲ (Col Ⅲ) collagen gene expression was observed, with an increased secretion of collagen into the culture medium between days 5 and 9, particularly Col Ⅲ. Furthermore, the total collagen content on the 11th day demonstrates a 3.1-fold increase relative to the normoxic group. The 7% oxygen concentration facilitated collagen deposition during the three-dimensional culture of VSMCs on PGA scaffolds, resulting in a 2.09-fold increase in total collagen content compared to the normoxic group. Additionally, the formation of more dense collagen fibrils was observed. These findings indicate that the utilization of a hypoxic environment can enhance the collagen content in TEVG, thereby providing a foundation for the further optimization of in vitro culture conditions for TEVG.

Advances in Amplification-Free Nucleic Acid Detection Technologies Based on CRISPR/Cas System



SHEN Xing, LI Yan, ZHANG Xu, et al

2025, 53(1):  136-146.  doi:10.12141/j.issn.1000-565X.230705

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Clustered regularly interspaced short palindromic repeats (CRISPR) are an immune system derived from archaea that recognizes and cleaves alien nucleic acids, with the assistance of specific guide RNAs. Due to the highly specific target recognition ability and target-activated nuclease activity, the system has been widely used in nucleic acid detection in recent years. To achieve highly sensitive detection, CRISPR / Cas systems usually need to be combined with pre-amplification technology, but this also brings problems with amplicon aerosol pollution, dependence on proprietary equipment, and prolonged detection time. Thus, many researchers have focused on deve-loping amplification-free CRISPR nucleic acid assays to deal with the above limitations. The high turnover non-specific cleavage activity of CRISPR / Cas targeted activation provides the possibility of developing this technology, and a number of amplification-free CRISPR nucleic acid detection technologies have been successfully developed using various strategies to improve the efficiency of trans-cleavage of the system or to enhance the signal. This article reviewed recent advancements in CRISPR-based amplification-free nucleic acid detection technologies. According to different strategies, these technologies are divided into four aspects: the combination or construction of Cas effectors, electrochemical sensing, microvolume CRISPR / Cas system, and signal reporter optimization. The article also analysed the principles of these technologies to achieve amplification-free nucleic acid detection from the perspective of strategies, that is, to achieve sensitivity enhancement through the accumulation of multiple protein complex-conducted signals, enhancement of signal sensing ability, increasing the concentration of the reaction system, and amplification of the signal. Based on the existing technical principles, the article discussed the advantages and disadvantages of several strategies. In addition, the article further outlooked the development trend of amplification-free CRISPR nucleic acid detection technology and proposes possible future research directions, which will provide a reference for the development of more rapid, sensitive, and simple molecular detection techno-logy to promote its deeper application.