Degradation Of Particles Research Articles

Maximum Correntropy-Based Extended Particle Filter for Nonlinear System

To solve the particle degradation and sample impoverishment, a maximum correntropy-based extended particle filter method is proposed by optimizing the important density function. In the proposed method, the importance sampling is guided by the measurement information, the entropy criterion and high-order moments information of the signal are fully utilized, and the non-Gaussian heavy-tailed distribution noise and the noise with outliers are effectively suppressed. The simulation results demonstrate the effectiveness and feasibility of the filtering method.

Application of magnetic iron oxide nanoparticles: Thrombotic activity, imaging and cytocompatibility of silica-coated and carboxymethyl dextrane-coated particles

Coated iron oxide nanoparticles (IONs) are promising candidates for various applications in nanomedicine, including imaging, magnetic hyperthermia, and drug delivery. The application of IONs in nanomedicine is influenced by factors such as biocompatibility, surface properties, agglomeration, degradation behavior, and thrombogenicity. Therefore, it is essential to investigate the effects of coating material and thickness on the behavior and performance of IONs in the human body. In this study, IONs with a carboxymethyl dextran (CMD) coating and two thicknesses of silica coating (TEOS0.98, and TEOS3.91) were screened and compared to bare iron oxide nanoparticles (BIONs). All three coated particles showed good cytocompatibility (>70%) when tested with smooth muscle cells over three days. To investigate their potential long term behavior inside the human body, the Fe2+ release and hydrodynamic diameters of silica-coated and CMD (carboxymethyl dextrane)-coated IONs were analyzed in simulated body fluids for 72 h at 37 °C. The ION@CMD showed moderate agglomeration of around 100 nm in all four simulated fluids and dissolved faster than the silica-coated particles in artificial exosomal fluid and artificial lysosomal fluid. The particles with silica coating agglomerated in all tested simulated media above 1000 nm. Increased thickness of the silica coating led to decreased degradation of particles. Additionally, CMD coating resulted in nanoparticles with the least prothrombotic activity, and the thick silica coating apparently decreased the prothrombotic properties of nanoparticles compared to BIONs and ION@TEOS0.98. For magnetic resonance applications, ION@CMD and ION@TEOS3.91 showed comparatively high relaxation rates R2 values. In magnetic particle imaging experiments ION@TEOS3.91 yielded the highest normalized signal to noise ratio values and in magnetic hyperthermia studies, ION@CMD and ION@TEOS0.98 showed similar specific loss power. These findings demonstrate the potential of coated IONs in nanomedicine and emphasize the importance of understanding the effect of coating material and thickness on their behavior and performance in the human body.

Investigation of Railway Ballast Breakage Through Large-Scale Triaxial Tests and a New Particle Breakage Approach in Discrete Element Modeling

Crushed aggregates with irregular shapes and sharp corners are preferred ballast materials to ensure proper track bearing capacity because of good contact between the particles. Meanwhile, crushed aggregates are prone to deterioration and breakage under repeated train loads. The effect of particle degradation on the mechanical behavior of ballast has been investigated before, but previous research rarely separates ballast breakage during sample compaction from breakage during shearing. This study investigates ballast particle breakage at different stages through large-scale triaxial tests and discrete element modeling. The results show that corner breakage is the primary particle breakage mode and mostly happens during compaction instead of during the shearing process. The results also indicate ballast corner breakage during sample compaction would increase the peak strength of the ballast but would not change Young’s modulus. A rubber pad is strongly recommended to reduce ballast breakage during the triaxial test sample compaction.

Doping zinc oxide (ZnO) nanoparticles with molybdenum boosts photocatalytic degradation of Rhodamine b (RhB): Particle characterization, degradation kinetics and aquatic toxicity testing

Undoped and Mo-doped ZnO photocatalysts were synthesized by hydrothermal method and characterized by field emission scanning electron microscopy coupled to energy dispersive- X ray spectroscopy (FESEM- EDAX), X-ray diffraction (XRD), fourier transform infrared spectroscopy (FTIR), Brunauer–Emmett–Teller (BET) and thermogravimetric analysis (TGA) analyses. The photocatalytic activity of the photocatalysts and the kinetic of the reaction was assessed by degrading Rhodamine B under UV and sun light irradiation under variable conditions. Eventually the acute toxicity of undoped and doped nanophotocatalysts, RhB and the consequences of photocatalytic treatment were assessed using zebrafish (Danio rerio). The analytical results showed that Mo doping increased catalysts specific surface area and thermal stability. The results of photocatalytic degradation demonstrated that Mo doping has increased the photocatalytic activity under both UV and sunlight irradiation with 95 % RhB degradation efficiency and 41 % TOC removal efficiency over 30 min. The reusability of photocatalysts showed constant degradation efficiency over multiple cycles. The 96 h LC50 of undoped ZnO, Mo doped ZnO and RhB were 482.71 and 459.05 and 20.38 mg/L, respectively. Moreover, a lower toxicity was observed for the treated compared to untreated dye solution. This study indicates a promising potential of Mo-doped ZnO nanophotocatalysts for wastewater treatment and warrants further studies in this direction.

Online parameters identification and state of charge estimation for lithium-ion batteries based on improved central difference particle filter

Accurate SOC is of great significance to alleviate the endurance anxiety of electric vehicle drivers. To improve the accuracy of SOC estimation, a method of combining FFRLS and GPR for parameter identification and an improved particle filter for lithium battery SOC estimation are proposed. The proposed collaborative parameter identification method uses the forgetting factor recursive least squares (FFRLS) to identify the parameters in the middle and high SOC region. In the low SOC region, the parameters identified by the FFRLS are used as the training data of Gaussian process regression (GPR) for model parameter prediction to improve the parameter identification accuracy in the low SOC region; in the SOC estimation stage, the central difference Kalman filter is used to generate the importance density function to overcome the particle degradation, and the step size h of the central difference is calculated suboptimal to further improve the prediction accuracy. Finally, the proposed method is compared with other methods under different working conditions and different temperatures, and the effectiveness and adaptability of the proposed method are verified.

Deployment of Superhydrophilic and Super-antifouling Cr-soc-MOF-1-Based Membrane for Ultrafast Separation of Stabilized Oil-in-Water Emulsions.

In spite of massive progress in oil-water separation, attributable to the use of advanced materials, the separation process faces challenges such as low permeance and fouling problems. Therefore, superwettable materials used in several fields are considered potential candidates for oily wastewater treatment. Metal-organic frameworks (MOFs) are receiving more and more interest in various separation applications due to their wide potential applications. Nevertheless, MOFs have been rarely explored for separating stabilized oil-in-water emulsions due to the difficulty in finding highly hydrolytic stable MOF candidates for this application. Furthermore, oil can clog water-stable materials owing to its high density, causing the degradation of MOF particles. As a result, there is a need to develop better MOF materials that can fulfill these requirements. Herein, we have explored Cr-soc-MOF-1 as a candidate for this application and deployed it as a membrane, which exhibited superhydrophilicity and underwater superoleophobicity for separating stabilized oil-in-water emulsions. The Cr-soc-MOF-1 membranes were synthesized by assembling the as-prepared MOF particles on a mixed cellulose ester substrate using a vacuum-assisted self-assembly technique. The Cr-soc-MOF-1 membrane exhibited ultrahigh water permeance (7465.9 L·m-2·h-1·bar-1), very high oil rejection (99.9%), and excellent anti-oil-fouling properties. The Cr-soc-MOF-1 membranes also exhibited excellent recyclability over 10 continuous separation cycles. Further, they exhibited an outstanding performance in separating various surfactant-stabilized oil-in-water emulsions. Thus, the Cr-soc-MOF-1 membranes exhibit a high potential in treating oily wastewater.

Antibacterial PLA/Mg composite with enhanced mechanical and biological performance for biodegradable orthopedic implants

Biodegradability, bone-healing rate, and prevention of bacterial infection are critical factors for orthopedic implants. Polylactic acid (PLA) is a good candidate biodegradable material; however, it has insufficient mechanical strength and bioactivity for orthopedic implants. Magnesium (Mg), has good bioactivity, biodegradability, and sufficient mechanical properties, similar to that of bone. Moreover, Mg has an inherent antibacterial property via a photothermal effect, which generates localized heat, thus preventing bacterial infection. Therefore, Mg is a good candidate material for PLA composites, to improve their mechanical and biological performance and add an antibacterial property. Herein, we fabricated an antibacterial PLA/Mg composite for enhanced mechanical and biological performance with an antibacterial property for application as biodegradable orthopedic implants. The composite was fabricated with 15 and 30 vol% of Mg homogeneously dispersed in PLA without the generation of a defect using a high-shear mixer. The composites exhibited an enhanced compressive strength of 107.3 and 93.2 MPa, and stiffness of 2.3 and 2.5 GPa, respectively, compared with those of pure PLA which were 68.8 MPa and 1.6 GPa, respectively. Moreover, the PLA/Mg composite at 15 vol% Mg exhibited significant improvement of biological performance in terms of enhanced initial cell attachment and cell proliferation, whereas the composite at 30 vol% Mg showed deteriorated cell proliferation and differentiation because of the rapid degradation of the Mg particles. In turn, the PLA/Mg composites exerted an antibacterial effect based on the inherent antibacterial property of Mg as well as the photothermal effect induced by near-infrared (NIR) treatment, which can minimize infection after implantation surgery. Therefore, antibacterial PLA/Mg composites with enhanced mechanical and biological performance may be a candidate material with great potential for biodegradable orthopedic implants.

Lattice Boltzmann simulation of cathode catalyst layer degradation on transport reaction process within a proton exchange membrane fuel cell

The degradation of the catalyst layer significantly affects the gas transport and electrochemical processes in the porous electrodes, thus affecting the performance of proton exchange membrane fuel cells. To reveal the catalyst layer degradation impact, the microscopic porous structure of the cathode catalyst layer was reconstructed by a random algorithm in this work. Consequently, Lattice Boltzmann method was used to study the oxygen transport and electrochemical reaction processes at the limiting current density condition with considering the degradation of platinum, carbon particles, and ionomers under uniform and exponential degradation rates, respectively. The results reveal that the degradation of platinum reduces the reaction sites in the catalyst layer, thus deteriorating the electrochemical kinetics and lowering the total reaction rate. On the contrary, the degradation of carbon and ionomer shows two diametrically opposed effects. On the one hand, the oxygen transport is improved due to carbon and ionomer degradation, especially for ionomer degradation, thereby accelerating the total reaction rate. On the other hand, the degradation of carbon and ionomer triggers the detachment of platinum particles, leading to a decrease in reaction rate. In the early stages of the multi-component simultaneous degradation process, the total reaction rate is prohibited by oxygen transport limitation inside the catalyst layer; as the degradation degree increases, the oxygen transport through the ionomer films is enhanced and the electrochemical kinetics becomes the rate determining factor, especially for exponential degradation rate. This study provides a comprehensive assessment of the oxygen transport and electrochemical reaction within the catalyst layers with respect to different degrees of catalyst layer degradation, which can guide the design of high-performance anti-degradation catalyst layers for the next generation of fuel cells.

High-throughput experimentation for discovery of biodegradable polyesters

The consistent rise of plastic pollution has stimulated interest in the development of biodegradable plastics. However, the study of polymer biodegradation has historically been limited to a small number of polymers due to costly and slow standard methods for measuring degradation, slowing new material innovation. High-throughput polymer synthesis and a high-throughput polymer biodegradation method are developed and applied to generate a biodegradation dataset for 642 chemically distinct polyesters and polycarbonates. The biodegradation assay was based on the clear-zone technique, using automation to optically observe the degradation of suspended polymer particles under the action of a single Pseudomonas lemoignei bacterial colony. Biodegradability was found to depend strongly on aliphatic repeat unit length, with chains less than 15 carbons and short side chains improving biodegradability. Aromatic backbone groups were generally detrimental to biodegradability; however, ortho- and para-substituted benzene rings in the backbone were more likely to be degradable than metasubstituted rings. Additionally, backbone ether groups improved biodegradability. While other heteroatoms did not show a clear improvement in biodegradability, they did demonstrate increases in biodegradation rates. Machine learning (ML) models were leveraged to predict biodegradability on this large dataset with accuracies over 82% using only chemical structure descriptors.

Superparamagnetic iron oxide nanoparticles for their application in the human body: Influence of the surface

Iron oxide nanoparticles (IONs) are of great interest in nanomedicine for imaging, drug delivery, or for hyperthermia treatment. Although many research groups have focused on the synthesis and application of IONs in nanomedicine, little is known about the influence of the surface properties on the particles' behavior in the human body. This study analyzes the impact of surface coatings (dextran, polyvinyl alcohol, polylactide-co-glycolide) on the nanoparticles’ cytocompatibility, agglomeration, degradation, and the resulting oxidative stress induced by the particle degradation. All particles, including bare IONs (BIONs), are highly cytocompatible (>70%) and show no significant toxicity towards smooth muscle cells. Small-angle X-ray scattering profiles visualize the aggregation behavior of nanoparticles and yield primary particle sizes of around 20 nm for the investigated nanoparticles. A combined experimental setup of dynamic light scattering and phenanthroline assay was used to analyze the long-term agglomeration and degradation profile of IONs in simulated body fluids, allowing fast screening of multiple candidates. All particles degraded in simulated endosomal and lysosomal fluid, confirming the pH-dependent dissolution. The degradation rate decreased with the shrinking size of particles leading to a plateau. The fastest Fe2+ release could be measured for the polyvinyl-coated IONs. The analytical setup is ideal for a quick preclinical study of IONs, giving often neglected yet crucial information about the behavior and toxicity of nanoparticles in the human body. Moreover, this study allows for the development and evaluation of novel ferroptosis-inducing agents.

Impact of Degradation of Polyethylene Particles on Their Cytotoxicity

Microplastics are ubiquitous in the environment, including in the ocean, soil, and air. Therefore, there are concerns regarding human exposure. Since it is known that the surface of microplastics in various environments is chemically deteriorated by external factors such as ultraviolet rays and waves, it is essential to evaluate the biological effects of degraded microplastics. In this study, we experimented by accelerating the degradation of polyethylene (PE) using vacuum ultraviolet light and prepared PE samples with different degrees of degradation. Then, we evaluated the effects of undegraded and variously degraded PE on cells using cytotoxicity tests. Based on the cytotoxicity test results, we saw a tendency for increased cytotoxicity with increasing degradation. Therefore, this study substantially links the deterioration of microplastics with their biological effects.

Purification and biochemical characterization of SM14est, a PET-hydrolyzing enzyme from the marine sponge-derived Streptomyces sp. SM14.

The successful enzymatic degradation of polyester substrates has fueled worldwide investigation into the treatment of plastic waste using bio-based processes. Within this realm, marine-associated microorganisms have emerged as a promising source of polyester-degrading enzymes. In this work, we describe the hydrolysis of the synthetic polymer PET by SM14est, a polyesterase which was previously identified from Streptomyces sp. SM14, an isolate of the marine sponge Haliclona simulans. The PET hydrolase activity of purified SM14est was assessed using a suspension-based assay and subsequent analysis of reaction products by UV-spectrophotometry and RP-HPLC. SM14est displayed a preference for high salt conditions, with activity significantly increasing at sodium chloride concentrations from 100 mM up to 1,000 mM. The initial rate of PET hydrolysis by SM14est was determined to be 0.004 s-1 at 45°C, which was increased by 5-fold to 0.02 s-1 upon addition of 500 mM sodium chloride. Sequence alignment and structural comparison with known PET hydrolases, including the marine halophile PET6, and the highly efficient, thermophilic PHL7, revealed conserved features of interest. Based on this work, SM14est emerges as a useful enzyme that is more similar to key players in the area of PET hydrolysis, like PHL7 and IsPETase, than it is to its marine counterparts. Salt-tolerant polyesterases such as SM14est are potentially valuable in the biological degradation of plastic particles that readily contaminate marine ecosystems and industrial wastewaters.

A Lidar SLAM based on Improved Particle Filter and Scan Matching for Unmanned Delivery Robot

With the rapid development of robotics, intelligent robots have gradually entered human daily life and take responsibility for specific tasks, which brings tremendous convenience to people’s lives. In indoor places such as restaurants, hotels, logistics warehouses, SLAM technology can guide mobile robots to complete delivery tasks. Aiming at solving the problems of particle degradation in the traditional RBPF-based two-dimensional SLAM algorithm, our algorithm firstly proposes an improved particle filter method based on cross-mutation, which changes the information of the small weight particles in the system by designing cross-mutation operators. Thus, a certain amount of small weight particles are retained in the system to increase the diversity of particles. Secondly, our algorithm proposes a scan matching method based on point and line features, which makes full use of the geometric information of the two-dimensional point cloud by designing a new error function. Compared with traditional matching methods that only rely on point features, it has better matching accuracy. We conduct Two-dimensional SLAM experiments in the Gazebo simulation environment and the real natural environment. The results show that the proposed algorithm has higher mapping accuracy than the commonly used two-dimensional SLAM algorithm Gmapping at this stage. Using improved A* algorithm to conduct path planning experiments on the two-dimensional grid map built with our algorithm, the results prove the effectiveness of our algorithm.

Influence of moisture on the migration of asphalt components and the adhesion between asphalt binder and aggregate

The performance degradation of asphalt pavement by moisture intrusion has been widely concerned. This paper investigated the effect of moisture on asphalt fractions and interface failure mechanism by moisture-induced using inclined shear test. Fourier transform infrared spectroscopy (FTIR) showed reduction of asphalt aromaticity by moisture led to the decline of asphalt cohesion. Fluorescence microscopy (FM) images indicated humid environment aggravated degradation of polymer particles in modified asphalt. Failure surface analysis confirmed moisture damage extended from asphalt to asphalt-aggregate interface. Although moisture enhanced the polarity of asphalt, moisture intrusion into the interface seriously weakened adhesion capability of asphalt and aggregate.

Influence of Nafion-Coating of Ag/Ag2O/C Electrodes on Long-Term Performance of an Electroosmotic Pump

Ag/Ag2O electrodes were fabricated on both carbon fiber paper (CP) and carbon fiber cloth (CC) substrates via galvanostatic electrodeposition to develop an electroosmotic (EO) pump. The results showed that Ag was deposited along the carbon fibers and further grew into Ag particles. The Ag loading on CP was higher than that of CC at the same current density, and the difference increased further with the current density increase. Nafion coating was applied on the as-electrodeposited Ag/Ag2O/CP electrode to prevent the degradation of Ag particles using dip coating, followed by drop coating. The Nafion-coated Ag/Ag2O/CP electrodes showed much better electroosmotic pump performance and long-term stability than the uncoated electrodes, revealing that the Nafion ionomer can enhance the proton conductivity and mitigate the degradation of Ag particles during the electrochemical reactions. The EO pumps built with Nafion-modified Ag/Ag2O/CP electrodes with an active area of 0.28 cm2 generated a maximum pressure of 157 kPa and a maximum flow rate of 28.21 ul min−1. The Postmortem analysis of the pumped working fluids collected from the EO pumps operated at a constant potential for three days was performed to further investigate the effects of Nafion coating on Ag degradation.

Facet‐dependent Thermal and Electrochemical Degradation of Lithium‐rich Layered Oxides

Lithium‐rich layered oxides (LLOs) are promising candidate cathode materials for safe and inexpensive high‐energy‐density Li‐ion batteries. However, oxygen dimers are formed from the cathode material through oxygen redox activity, which can result in morphological changes and structural transitions that cause performance deterioration and safety concerns. Herein, a flake‐like LLO is prepared and aberration‐corrected scanning transmission electron microscopy (STEM), in situ high‐temperature X‐ray diffraction (HT‐XRD), and soft X‐ray absorption spectrum (sXAS) are used to explore its crystal facet degradation behavior in terms of both thermal and electrochemical processes. Void‐induced degradation behavior of LLO in different facet reveals significant anisotropy at high voltage. Particle degradation originates from side facets, such as the (010) facet, while the close (003) facet is stable. These results are further understood through ab initio molecular dynamics calculations, which show that oxygen atoms are lost from the {010} facets. Therefore, the facet degradation process is that oxygen molecular formed in the interlayer and accumulated in the ab plane during heating, which result in crevice‐voids in the ab plane facets. The study reveals important aspects of the mechanism responsible for oxygen ‐anionic activity‐based degradation of LLO cathode materials used in lithium‐ion batteries. In particular, this study provides insight that enables precise and efficient measures to be taken to improve the thermal and electrochemical stability of an LLO.

State-of-Charge and State-of-Health Joint Estimation of Lithium-Ion Battery Based on Iterative Unscented Kalman Particle Filtering Algorithm With Fused Rauch–Tung–Striebel Smoothing Structure

Abstract Traditional particle filtering has a large estimation error in the state of charge and Lithium-ion battery health of electric vehicle lithium batteries. For the above-mentioned problems, the lithium battery second-order resistance capacitance (RC) equivalent circuit model is established, and then, the model parameters are identified using the multi-innovation least square algorithm (MILS). Finally, an iterative unscented Kalman particle filtering algorithm with fused Rauch–Tung–Striebel Smoothing Structure (RTS-IUPF) applied to Li-ion battery state-of-charge (SOC) and state-of-health (SOH) joint estimation is proposed. The algorithm is based on the identification of battery parameters; the controller reads the sensor data and predicts the state results. RTS smoothing structure can do posterior estimation, and a significant probability density function is generated to select the optimal particle, and unscented Kalman algorithm regularized particles. The algorithm reduces the effect of the process noise covariance matrix and the measured noise covariance matrix on the filter accuracy and response time in traditional unselected Kalman filters. The algorithm proposed in the paper improves particle degradation and increases the estimation accuracy. Finally, the RTS-IUPF algorithm performs simulation analysis in Pulse current discharge condition and dynamic current condition (NEDC), respectively. The pulse current experimental results show that the mean absolute value error of UKF and particle filter (PF (number of particles N is 300)) is 1.26% and 1.24%, respectively, while the error of the RTS-IUPF is 0.748%. The root-mean-square error (RMSE) of the RTS-IUPF is reduced by 66.5% and 77.8% compared with UKF and PF. Furthermore, the error of joint estimation using this algorithm is smaller than that of single estimation. The RMSE of the RTS-IUPF joint is reduced by 27.4% compared with RTS-IUPF. The feasibility and effectiveness of the algorithm for the joint estimation of SOC and SOH of lithium batteries were verified.

Solid State Material Driven Turbine to Reduce Segregation during Bunker Filling

For most applications and their following processes, an evenly distributed bunker outflow is desired in terms of particle size. Various discrete element simulations were performed to analyze the current state of an existing bunker used for storage of blast furnace sinter, which is simply filled with a discharging belt conveyor. Great segregation effects could be determined, which are mainly caused by the filling method and further intensified by the core flow effect and bunker geometry.Several concepts and devices to reduce segregation in bunkers were evaluated using DEM. The particle size distributions at the bunker outflow were each compared with the current state without a device. A solid state material driven turbine is presented, which reduces segregation effects during bunker filling and leads to a significant improvement during the discharge. The results show a more evenly distributed bunker outflow in terms of particle size.As sinter is a very abrasive material, the wear at the turbine has also been evaluated. Furthermore, the power output in this case and the potential of energy recovery were investigated, which could be of interest in many other applications.Additionally, the particle degradation at the solid state material driven turbine is evaluated in this case. A newly developed breakage model for DEM is used. The model is based on the particle replacement method, combined with the voronoi tessellation algorithm and breakage probabilities to achieve a high accuracy in terms of fragment size distribution.

Quantitative Immunofluorescence to Study Phagosome Maturation and Resolution.

Cells such as macrophages and neutrophils can internalize a diverse set of particulate matter, illustrated by bacteria and apoptotic bodies through the process of phagocytosis. These particles are sequestered into phagosomes, which then fuse with early and late endosomes and ultimately with lysosomes to mature into phagolysosomes, through a process known as phagosome maturation. Ultimately, after particle degradation, phagosomes then fragment to reform lysosomes through phagosome resolution. As phagosomes change, they acquire and divest proteins that are associated with the various stages of phagosome maturation and resolution. These changes can be assessed at the single-phagosome level by using immunofluorescence methods. Typically, we use indirect immunofluorescence methods that rely on primary antibodies against specific molecular markers that track phagosome maturation. Commonly, progression of phagosomes into phagolysosomes can be determined by staining cells for Lysosomal-Associated Membrane Protein I (LAMP1) and measuring the fluorescence intensity of LAMP1 around each phagosome by microscopy or flow cytometry. However, this method can be used to detect any molecular marker for which there are compatible antibodies for immunofluorescence.

Research on Multi-Sensor Fusion SLAM Algorithm Based on Improved Gmapping

Simultaneous Localization and Mapping (SLAM) is the core technology of the intelligent robot system, and it is also the basis for its autonomous movement. In recent years, it has been found that SLAM using a single sensor has certain limitations, such as Inertial Measurement Unit (IMU) noise and serious drift, and 2D radar can only detect environmental information on the same horizontal plane. In this regard, this paper constructs a multi-sensor back-end fusion SLAM algorithm that combines vision, laser, encoder and IMU information. Experiments have proved that compared with using a single sensor, the application of a multi-sensor fusion system makes the edges of the constructed map clearer and the noise reduced. Aiming at the problem of increased calculation caused by particle degradation and too many particles, this paper improves the Gmappping algorithm, and uses the combination of selective resampling and Kullback-Leibler Distance (KLD) sampling to complete resampling. It has been proved by experiments that compared with the original algorithm of Gmapping, the application of the improved algorithm increases the particle convergence speed by 39.85% in the process of indoor mapping. Aiming at the problems that the traditional loop detection algorithm is easily affected by environmental factors, resulting in low detection accuracy, and the loop detection algorithm based on deep convolutional neural network has a large amount of calculation and takes a long time to detect. The main research of this paper is to apply a deep learning-based loop detection algorithm on the multi-sensor fusion framework, and use the combination of high-dimensional and low-dimensional features of the image for loop detection. This paper uses different algorithms to conduct comparative experiments on the dataset CityCentre. The experimental results show that compared with the traditional algorithms Bag of Words (BoW), AlexNet algorithm, VGG19 algorithm, and ResNet32 algorithm, the accuracy of the algorithm proposed in this paper has increased by 31.26%, 14.21%, 3.05%, and 1.56%, respectively. In addition, the comparison experiment results of SLAM mapping with the original Real-Time Appearance-Based Mapping (RTAB-MAP) algorithm prove that the loop closure detection algorithm based on deep learning proposed in this paper can enable the system to better build a globally consistent map, including more environmental information.