Complex Surface Research Articles

Mitigating RGB-D camera errors for robust ultrasonic inspections using a force-torque sensor

ABSTRACT Robot-based phased array ultrasonic testing is widely used for precise defect detection, particularly in complex geometries and various materials. Compact robots with miniature arms can inspect constrained areas, but payload limitations restrict sensor choice. RGB-D cameras, due to their small size and light weight, capture RGB colour and depth data, creating colourised 3D point clouds for scene representation. These point clouds help estimate surface normals to align the ultrasound transducer on complex surfaces. However, sole reliance on RGB-D cameras can lead to inaccuracies, affecting ultrasonic beam direction and test results. This paper investigates the impact of transducer pose and RGB-D camera limitations on ultrasonic inspections and proposes a novel method using force-torque sensors to mitigate errors from inaccurately estimated normals from the camera. The force-torque sensor, integrated into the robot end effector, provides tactile feedback to the controller, enabling joint angle adjustments to correct errors in the estimated normal. Experimental results show the successful application of ultrasound transducers using this method, even with significant misalignment. Adjustments took approximately 4 seconds to correct deviations from 12.55°, with an additional 4 seconds to ensure the probe was parallel to the surface, enhancing ultrasonic inspection accuracy in complex, constrained environments.

Ultrasonic‐assisted activation of clay for efficient removal of U(VI) and Cr(VI)

AbstractThe natural clay mineral was activated using the acid treatment under ultrasonic conditions to improve its adsorption performance. The acid‐activated clay (AAC) was investigated to remove Cr(VI) from wasted lubricant and U(VI) from aqueous solution by batch, spectroscopy, and modeling. Batch experiments showed that the isotherms and adsorption kinetics of Cr(VI)/U(VI) on AAC were satisfactorily followed by Frenudlich and the pseudo‐second‐order model, respectively. The decreased adsorption of U(VI) on AAC with the increase of ion strength indicated the outer surface complexation of U(VI) on AAC. The interaction mechanism of Cr(VI)/U(VI) on AAC was demonstrated to be surface complexation by oxygenated functional groups (e.g., hydroxyl) according to X‐ray photoelectron spectroscopy (XPS) analysis. According to fitting of surface complexation models using three approaches, the adsorption of U(VI) on AAC at different pH can be better fitted by the double‐layer model compared to the constant‐capacitance model and triple‐layer model. These findings are great important for the application of acid activated clay in the removal of heavy metals and radionuclides from the environment.

Binding between Cu2+/Zn2+ and aged polyethylene and polyethylene terephthalate microplastics in swine wastewaters: Adsorption behavior, and mechanism insights

Microplastics (MPs) have aroused growing environmental concerns due to their biotoxicity and vital roles in accelerating the spread of toxic elements. Illuminating the interactions between MPs and heavy metals (HMs) is crucial for understanding the transport and fate of HM-loaded MPs in specific environmentally relevant scenarios. Herein, the adsorption of copper (Cu2+) and zinc (Zn2+) ions over polyethylene (PE) and polyethylene terephthalate (PET) particulates before and after heat persulfate oxidation (HPO) treatment was comprehensively evaluated in simulated and real swine wastewaters. The effects of intrinsic properties (i.e., degree of weathering, size, type) of MPs and environmental factors (i.e., pH, ionic strength, and co-occurring species) on adsorption were investigated thoroughly. It was observed that HPO treatment expedites the fragmentation of pristine MPs, and renders MPs with a variety of oxygen-rich functional groups, which are likely to act as new active sites for binding both HMs. The adsorption of both HMs is pH- and ionic strength-dependent at a pH of 4–6. Co-occurring species such as humic acid (HA) and tetracycline (TC) appear to enhance the affinity of both aged MPs for Cu2+ and Zn2+ ions via bridging complexation. However, co-occurring nutrient species (e.g., phosphate and ammonia) demonstrate different impacts on the adsorption, improving uptake of Cu2+ by precipitation while lowering affinity for Zn2+ owing to the formation of soluble zinc-ammonia complex. Spectroscopic analysis indicates that the dominant adsorption mechanism mainly involves electrostatic interactions and surface complexation. These findings provided fundamental insights into the interactions between aged MPs and HMs in swine wastewaters and might be extended to other nutrient-rich wastewaters.

Mechanism of arsenic removal using brown seaweed derived impregnated with iron oxide biochar for batch and column studies

Water contaminated with arsenic presents serious health risks, necessitating effective and sustainable removal methods. This article proposes a method for removing arsenic from water by impregnating biochar with iron oxide (Fe2O3) from brown seaweed (Sargassumpolycystum). After the seaweed biomass was pyrolyzed at 400 °C, iron oxide was added to the biochar to increase its adsorptive sites and surface functional groups, which allowed the binding of arsenic ions. Batch studies were conducted to maximize the effects of variables, including pH, contact time, arsenic concentration, and adsorbent dosage, on arsenic adsorption. The maximum arsenic adsorption efficiency of 96.7% was achieved under optimal conditions: pH 6, the adsorbent dosage of 100 mg, the initial arsenic concentration of 0.25 mg/L, and a contact time of 90 min. Langmuir and Freundlich’s isotherms favored the adsorption process, while the kinetics adhered to a pseudo-second-order model, indicating chemisorption as the controlling step. Column studies revealed complete saturation after 200 min, and the adsorption behavior fits both the Adams–Bohart and Thomas models, demonstrating the potential for large-scale application. The primary mechanism underlying the interaction between iron-modified biochar and arsenic ions is surface complexation, enhanced by increased surface area and porosity. This study highlights the significant contribution of iron-modified biochar derived from macroalgae as an effective and sustainable solution for arsenic removal from water.

Improved YOLOv8 Algorithm for Water Surface Object Detection

To address the issues of decreased detection accuracy, false detections, and missed detections caused by scale differences between near and distant targets and environmental factors (such as lighting and water waves) in surface target detection tasks for uncrewed vessels, the YOLOv8-MSS algorithm is proposed to be used to optimize the detection of water surface targets. By adding a small target detection head, the model becomes more sensitive and accurate in recognizing small targets. To reduce noise interference caused by complex water surface environments during the downsampling process in the backbone network, C2f_MLCA is used to enhance the robustness and stability of the model. The lightweight model SENetV2 is employed in the neck component to improve the model’s performance in detecting small targets and its anti-interference capability. The SIoU loss function enhances detection accuracy and bounding box regression precision through shape awareness and geometric information integration. Experiments on the publicly available dataset FloW-Img show that the improved algorithm achieves an mAP@0.5 of 87.9% and an mAP@0.5:0.95 of 47.6%, which are improvements of 5% and 2.6%, respectively, compared to the original model.

Standardization of Chemically Selective Atomic Force Microscopy for Metal Oxide Surfaces.

The structures of metal oxide surfaces and inherent defects are vital for a variety of applications in materials science and chemistry. While scanning probe microscopy can reveal atomic-scale details, elemental discrimination usually requires indirect assumptions and extensive theoretical modeling. Here, atomic force microscopy with O-terminated copper tips on a variety of sample systems demonstrates not only a clear and universal chemical contrast but also immediate access to the atomic configuration of defects. The chemically selective contrast is explained by purely electrostatic interactions between the negatively charged tip-apex and the strongly varying electrostatic potential of metal and oxygen sites. These results offer a standardized methodology for the direct characterization of even the most complex metal oxide surfaces, providing fundamental insight into atomic-scale processes in these material systems.

Adsorption of titanium-aluminum layered hydroxides for removal of fluorine at low concentrations in water

Layered double hydroxides have good application prospects in the fields of water treatment and defluoridation. In this study, Ti-Al layered hydroxides (Ti-Al LDHs) were synthesized by the co-precipitation method at a Ti/Al molar ratio of 2/8 and a medium solution pH of 6.0. The SEM, XRD, and BET results showed that the Ti-Al LDHs showed a uniform stacking of lamellar structure and existed mainly in dispersed amorphous form, with a wide pore size and a larger specific surface area (108.34 m2/g). The results of adsorption experiments showed that the highest capacity could reach 116.2 mg/g, and the adsorption adsorption of Ti-Al LDHs on fluoride was more in line with the proposed second-order model, and the adsorption isotherm was more in line with the Langmuir model.In addition, Ti-Al LDHs can be applied in a wide pH range (4−10), have strong resistance to anionic competition, and have good regeneration performance after five adsorption-desorption cycles where the adsorption capacity is still equivalent to 73 % of the initial capacity. From the FTIR and XPS results, the adsorption process was mainly attributed to ion exchange, electrostatic attraction and surface complexation. Therefore, Ti-Al LDHs is a layered hydroxide fluoride removal adsorbent with good application prospects.

Efficient removal of direct dyes by SA-Er biopolymer gel spheres: Equilibrium isotherms, kinetics and regeneration performance study

Biomass-based adsorbent materials are characterized by their low cost, environmental friendliness, and ease of design and operation. In this study, biomass-based hydrogel microspheres erbium alginate (SA/Er) with high stability and adsorption properties were prepared by a one-step synthesis method. The prepared materials were characterized and analyzed by SEM-EDS, XRD, TGA, FT-IR, UV–Vis, BET-BJH and XPS, and the adsorption performance of SA/Er was investigated for high concentrations of azo dyes in water. The results showed that the adsorption performance of SA/Er on the azo dyes of direct violet N (DV 1) and direct dark green NB (DG 6) with concentrations of 850 mg/L and 1100 mg/L under the optimal conditions was very high, and the adsorption amount could be up to 692 mg/g and 864 mg/g, respectively. The adsorption process was in accordance with the quasi-secondary kinetic model, which was accomplished by physical and chemical adsorption; the Langmuir isothermal model was able to better respond to the adsorption equilibrium, and the adsorption was dominated by the adsorption of surface monolayers; after seven desorption cycles, the removal of both azo dyes by the adsorbent material could reach >79.7 %. Combined with the results of FT-IR, UV–vis and XPS analysis before and after the adsorption, it was revealed that the adsorption of SA/Er with the dye molecules mainly consisted of hydrogen bonding, electrostatic adsorption and surface complexation, which resulted in the significant adsorption effect on the two azo dyes, and the above results can provide a reference for the treatment of dye wastewater.

Patching Non-Uniform Extraordinary Points.

Smooth surfaces from an arbitrary topological control grid have been widely studied, which are mostly generalized from splines with uniform knot intervals. These methods fail to work well on extraordinary points (EPs) whose edges have varying knot intervals. This article presents a patching solution for arbitrary topological 2-manifold control grid with non-uniform knots that defines one bi-cubic Bézier patch per control grid face except those faces with EPs. Experimental results demonstrate that the new solution can improve the surface quality for non-uniform parameterization. Applications in surface reconstruction, arbitrary sharp features on the complex surface and tool path planning for the new surface representation are also provided in the paper.

Phosphate adsorption characteristics of CeO2-loaded, Eucommia ulmoides leaf residue biochar

In this study, a Ce-loading biochar (Ce-BC) was synthesized by the optimal modification method of pre-pyrolysis impregnation, a pyrolysis temperature at 600 °C, and a CeCl3 concentration of 1.00 mol·L-1 for efficient adsorption phosphorus (P) from wastewater. The results revealed that Ce-BC could achieve a maximum P removal rate of 100% under specific conditions: an adsorbent concentration of 2.00 g·L-1, an initial solution pH of 3.00, an adsorption temperature of 25°C, and an initial P concentration of 20.00 mg·L-1. The adsorption process followed the quasi-secondary kinetic model, suggesting the Ce-BC was particularly effective in acidic environments. Meanwhile, Ce-BC has a strong resistance to anion interference and good cycling performance (the P adsorption capacity of Ce-BC was 59.77% of its initial value after four cycles). Field emission scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS), Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), and X-ray diffraction (XRD) indicated that Ce-BC contained a porous structure and rich functional groups (hydroxyl and carboxyl), and compounds of CeO2 and MgCeO3 were formed. The Ce loading favored the exchange with P through ligands, inner-sphere complexation, ion exchange, and electrostatic interaction to form inner-sphere complex-cerium P (CePO4), and surface complex of Ce-O-P replaced O-H. In addition, the Ce-BC adsorption columns had a substantial effect on P removal in actual wastewater. Overall, Ce-BC is a promising material for the treating P-containing acidic wastewater.

Piezoresistive nanocomposite sensing using electrical impedance tomography and machine learning

Strain measurements have traditionally been accomplished by connecting many gauges to crucial spots on structures. Installing strain gauges can be costly and limited in providing ‎comprehensive data for large surface areas or complex structures, posing significant challenges. This work explores the use of piezoresistive nanocomposite sensors as a cost-effective and informative solution for wide surface area strain detection. Piezoresistive sensors are created using two methodologies: film-coated and pellet-fed 3D printing technique (PF3DP), with variable gauge factors achieved by using 6 and 10 wt% multi-wall carbon nanotubes (MWCNTs), respectively. An electrical impedance tomography (EIT) setup is utilized to analyze electrical changes with respect to strain and predict the conductivity distribution across the sensor’s surface. This study employs two efficient machine learning (ML) techniques, artificial neural networks (ANN) and convolutional neural networks (CNN), to analyze and compare image reconstruction resolution at different loads. The machine learning models are designed to reconstruct images quickly and reliably. The study demonstrates that the hybrid-ML model, which combines ANN and CNN models, achieves high-resolution image construction with minimal errors compared to outcomes obtained through EIT for the experimental measurements. Sensors created using 3D printing provide higher image resolution and data stability than film-coated sensors. This technology has the potential for accurate strain sensing and measuring the structural health of complex surfaces.

Promisingly prioritized elimination performance of europium and uranium from industrial wastewater by recyclable polydopamine functionalized hydroxyapatite/ZIF-67 hybrids

In recent decades, the nuclear industry has undergone robust growth leading to an increasingly severe issues of radionuclide contaminants in wastewater. Consequently, the development of a novel, efficient, regenerative and environmentally friendly adsorbent has become a significant challenge. In this study, recyclable polydopamine functionalized hydroxyapatite/ZIF-67 (HAP/ZIF-67/PDA) hybrids with a mass of functional groups, were successfully synthesized using the ultrasonic-assisted method. The especially characterized techniques illustrated that the HAP/ZIF-67/PDA hybrids were outstanding stable, excellent physicochemical properties and abundant functional groups. The elimination performances of Eu(III) and U(VI) from wastewater were also explored and deliberated through macroscopic experiment under diverse wastewater chemistry environment. The optimal adsorption capacity of HAP/ZIF-67/PDA was approximately 1.33 × 10-3 mol/g for Eu(III) and 8.85 × 10-4 mol/g for U(VI), surpassing those reported materials in previous literatures. The particular adsorption isotherms of Eu(III) and U(VI) were favorably fitted by Langmuir model, illustrating that the adsorption Eu(III) and U(VI) were totally endothermic reaction. The remarkable adsorption performance of HAP/ZIF-67/PDA hybrids (within 80 min for Eu(III) and 100 min for U(VI)) was verified through dynamic model, and then the kinetics results were well simulated through pseudo-second-order kinetic model, which further illustrated outstanding performance for rapidly treating Eu(III) and U(VI) under extreme emergency conditions. The primary adsorption mechanisms HAP/ZIF-67/PDA hybrids towards Eu(III) and U(VI) were surface complexation, competitive interaction, cation change, π-π* bonds and electrostatic interaction. Based on the excellent adsorption performance and recyclability of HAP/ZIF-67/PDA, it holds significantly potential and promising prospects for the efficient elimination of lanthanide and actinium contaminants from the practical treatments and disposals fields of industrial wastewater.

Online nonlinearity elimination for fringe projection profilometry using slope intensity coding

The nonlinearity effect in the system of fringe projection profilometry can cause the non-sinusoidal deviation of the fringe patterns, inducing ripple-like phase errors and further affecting measurement accuracy. This paper presents an online nonlinearity elimination method based on slope intensity coding. Two sequences of sinusoidal phase-shifting fringe patterns with different frequencies, and one slope intensity pattern with one uniform intensity pattern are projected. The equations for the nonlinearity response are established using the defined mean and modulation parameters, the captured uniform intensity and two extracted background intensities. The nonlinearity response coefficients determined by solving the equations are used for pixel-wise nonlinearity correction on the captured images, which are employed for computing the wrapped phase, and further obtaining continuous phase by the multi-frequency phase unwrapping method. Experimental results demonstrate that the proposed method can eliminate the nonlinearity-induced phase error online by using fewer images and maintain the reliability of phase unwrapping in the measurement of isolated objects with complex surfaces.

Automated line scan profilometer based on the surface recognition method

Existing high-precision measurement devices face numerous challenges when dealing with complex surfaces, including high manual involvement, low measurement efficiency, and high costs. It is even more difficult to obtain complete surface data, particularly when confronted with unknown surfaces. This paper combines a fringe projection sensor with a high-precision line-structured light sensor to construct a line scan profiler. It proposes a surface recognition measurement method to overcome these challenges. This method fully leverages the fringe projection sensor's wide-field advantage to identify the object's surface shape and pose quickly. Subsequently, through the point cloud extraction and path planning algorithms proposed in this paper, efficient and complete line scan measurement paths are automatically generated, thus achieving the automation of the measurement process. Experimental measurements of aspherical lenses, freeform reflective mirrors, and artificial knee joint models validate the advantages of this method over existing methods in terms of measurement efficiency, automation capability, and applicability.

Highly Robust and Self-Adhesive Soft Strain Gauge via Interface Design Engineering.

Highly robust soft strain gauges are rapidly emerging as a promising candidate in the fields of vital signs and machine conditions monitoring. However, it is still a key challenge to achieve high-performance strain sensing in these sensors with mechanical/electrical robustness for long-term usage. The multilayer structural design of sensors enhances sensing performance while the interfacial connection of heterogeneous materials between different layers is weak. Herein, inspired by the efficient perception mechanism of scorpion slit sensilla with tough interface interconnections, the synergy of ultra-high electrical performance and mechanical robustness is successfully achieved via interface design engineering. The developed multilayer soft strain gauge (MSSG) exhibits a strain sensitivity beyond 105, a lower detection limit of 8.3µm, a frequency resolution within 0.1Hz, and cyclic stability over 63000 strain cycles. Also, the tough interface improves the level of heterogeneous integration in the MSSG which allows to endure different stresses. Furthermore, an MSSG-based wireless strain monitoring system is developed that enables applications on different complex dynamic surfaces, including accurate identification of human throat activity and monitoring of rolling bearing conditions.

Advancements in Coordination Chemistry and Trends in the Chemical Industry: Applications and Implications

Abstract: Metal foams offer a compelling combination of properties, including low density, sound absorption, high compressive strength, and stiffness. This project focuses on the damping behavior of aluminum foams for applications in automobiles and various industries. Aluminum foams excel in being lightweight, exhibiting high compressive strength, and offering excellent stiffness. However, their wear resistance is a limitation. To address this and enhance durability, a diamond-like carbon (DLC) coating is applied to the surface. The complex geometry and surface of aluminum foams pose a challenge for the coating process. Therefore, the project employs the well-established cataphoretic deposition technique, an electro-chemical process. This research investigates the potential of carbon-coated aluminum foam for vibration mitigation in automobiles and industrial applications by analyzing its damping properties and improved wear resistance through the DLC coating

Efficient removal of Cr6+ by magnetically modified biochar from aqueous solution:Removal mechanism investigation

The magnetic biochar is prepared by one-pot method using waste wooden building formwork as feedstock in the existence of the FeCl3 for Cr6+ removal form wastewater. Characterization analysis indicates that magnetic biochar exists Fe3O4 with specific surface area of the 333.89–496.35 m2/g, contributing to Cr6+ removal. Cr6+ removal process can be well analyzed by the Pseudo-second order and Hill models with adsorption capacity of 30.41 mg/g. The adsorption process analysis indicates that Cr6+ removal mechanism includes surface complexation, electrostatic attraction, reduction and pore filling. The influence of Fe2+ on Cr6+ removal is analyzed, indicating Fe2+ participation into Cr6+ removal by reduction. The magnetic biochar has excellent reusability after three cycles. The Cr6+ removal process is also investigated using column adsorption experiment, indicating that magnetic biochar has column adsorption amount of the 56.64 mg/g. The economic feasibility of the magnetic biochar is investigated and calculated with the production cost of $2.48/1kg. The waste wooden building formwork is converted into the efficient magnetic biochar for Cr6+ removal from wastewater.

One-step removal of anionic/cationic heavy metal ions from wastewater by magnetic amphoteric adsorbent

Simultaneous treatment of wastewater containing anionic and cationic pollutants in an easy-to-operate and environmentally friendly manner is a formidable challenge in environmental remediation. This work designed a low-cost and high-efficient amphoteric adsorbent Fe3O4/Mg-Al LDOs/AlS (SMA) for the simultaneous removal of Cr (VI) and Cu (II) pollutants from wastewater in one step. SMA is prepared with waterworks aluminum-containing sludge (AlS) from typical municipal engineering waste as the base material and loaded with magnetic nanoparticles to enhance recycling process after adsorption. SMA exhibits large specific surface area (~418 m2/g), thereby providing sufficient adsorption active sites. Adsorption studies indicate that the adsorption of SMA on two pollutants conforms to the pseudo-second-order kinetic model, while the Langmuir model was used to simulate the adsorption isotherm. The maximum adsorption capacity is calculated to be 235.3 mg/g for Cr (VI) and 669.2 mg/g for Cu (II). Thermodynamic studies reveal the process's spontaneous nature. The main adsorption mechanisms involve electrostatic attraction, surface complexation, isomorphic replacement, and chemical precipitation. Notably, SMA exhibits excellent adsorption performance in a wide pH range and water system containing multiple anions and cations. Moreover, the strong magnetic property facilitates easy separation and recovery through an external magnetic field, maintaining stable adsorption performance even after five cycles. Therefore, this study provides a win-win strategy for promoting environmental safety, not only proposing feasible approaches for the high value-added utilization of waste sludge, but also efficiently addressing the purification problem of complex anionic and cationic coexisting wastewater.

QRNet: Query-based reparameterization net for real-time detection of power adapter surface defects

In industrial production, automated surface defect detection holds paramount importance. While current techniques can handle complex background power adapter surface defect detection with high precision, they have many parameters, low speed, slow convergence, and complex post-processing (such as non-maximum suppression). To this end, this study aims to develop a more efficient and effective method for surface defect detection. The primary objective of this research is to enhance the speed of detection without sacrificing accuracy. This paper designs the Separable-reparam Feature Module (SFM), which is based on depth-wise convolution, to fuse multi-branch features through reparameterization techniques. SFM has low parameters and excels in feature extraction without increasing the model’s Memory Access Cost (MAC). SFM combines cross-stage fusion to construct the backbone, enabling the extraction of multi-scale features. Following the standard query decoder architecture, a QRNet was built to learn the query set of objects, and predict the surface defect set for power adapter. Additionally, a novel two-stage mixed-supervised transfer-learning approach is proposed to expedite the convergence process. Experimental results on the power adapter defect dataset demonstrate QRNet’s remarkable performance. It achieved a mean average precision (mAP) of 98.94 % with just 0.841 M parameters and a latency of 5.72 ms. In conclusion, QRNet represents an advancement in surface defect detection, offering a balance between accuracy and efficiency.

Создание и развитие высоконадежных информационно-управляющих систем с элементами искусственного интеллекта для перспективных технологических комплексов

Methods and means of improving complex technological equipment are shown through the operational assessment of the quality of implemented technologies realtime. This is proved by the fact that implementing technological operations on universal equipment each time requires modeling dynamic processes and taking into account a large number of uncertainty factors that affect the geometry generation quality. It is not possible to be a priori aware of these factors. There is a need to create new information technologies with the possibilities of universal application for immediate understanding of various dynamic processes in diagnostic, identification and control systems. Standard computer systems for statistical analysis and optimization of dynamic processes with the possibilities of universal application for various implementations of modern technologies have been introduced. The possibility of using integrative criteria and methods of artificial intelligence for diagnostic systems, identification and control of advanced technological complexes is shown. The implementation of information systems for the management of complex objects of various technological purposes is presented. The proposed modeling methods and approaches have been tested at various machine-building enterprises when processing parts on turning, milling and grinding machines, both universal and CNC. The research results made it possible to implement new principles of automated control and optimal adjustment of technological processes in real time and create an automated system for evaluating their quality, which allows increasing the efficiency and reliability of management decisions by conducting optimization directly on operating equipment. Based on the methods and approaches described above, new results have been obtained in the implementation of plasma technologies for the modification of geometrically complex surfaces of mechanical engineering products aimed at increasing wear resistance, hardness and other technical characteristics of the working surfaces of precision engineering products. A fairly complete approbation of methods, approaches, procedures and decision-making criteria for various technologies allows them to be recommended for universal applicability.