Abstract: The deposition area of the hot filament chemical vapor deposition (HFCVD) method can reach 12 inches, which has the potential to produce larger-sized single crystal diamonds. In this study, single crystal diamond with a size of 3 mm × 3 mm × 1 mm and (100) orientation was used as the substrate. Homoepitaxial growth was carried out using the HFCVD method with methane and hydrogen as precursors, and a small amount of nitrogen gas. The results show that under the conditions of a filament temperature of 2200 °C, a carbon source concentration of 4%, and a chamber pressure of 4 kPa, single crystal diamond grows at a rate of 3.41 μm/h. The surface of the diamond exhibits no defects such as polycrystals, cracks, or holes. The full width half maximum (FWHM) of the epitaxial layer’s X-ray diffraction spectrum at the (400) peak is 0.11°, which is lower than that of the substrate at 0.16°, indicating that the crystal quality of the epitaxial layer is higher than that of the substrate. The introduction of nitrogen can increase the growth rate of single crystal diamond, although it reduces the crystal quality of the epitaxial layer. A higher nitrogen concentration can also shift the growth mode of single crystal diamond change to island growth.
Abstract: With the rise of third-generation semiconductors, electronic devices are evolving towards high-power, miniaturization, and integration. Traditional heat dissipation technologies are no longer sufficient to meet the heat dissipation requirements of high heat flux in third-generation semiconductor devices. Temperature accumulation has become a major cause of device failure. Diamond-based materials have excellent thermal properties. Efficient heat dissipation technology based on these materials has become a key direction to solve the high heat flux dissipation problem. This article summarizes the development of diamond-based materials and the main methods for preparing surface microchannels. It reviews the application and development trends of diamond-based materials in the field of efficient heat dissipation. The development and application of diamond-based materials for efficient heat dissipation technology can provide technical support for addressing the problem of high heat flux dissipation.
Abstract: Porous diamond grinding tools are a new type tools that can provide a space for chip holding and coolant flowing during the grinding process. selective laser melting (SLM) is an effective method for manufacturing porous diamond grinding tools. However, due to the limitations of spot size and layer by layer fabricating process in SLM process, the designed porous diamond tools are difficult to be manufactured accurately. Therefore, it is necessary to study the formability of diamond composite materials feature geometry structures. Based on CuSn20/diamond composites, a series of feature structures such as overhang structures, thin-walled, holes, and sharp angle structures with different fabricating directions and sizes were fabricated by SLM technology. The formability, forming errors, and causes of these structures are analyzed. The results show that the optimal formable length of the overhang structure is 1.0～2.0 mm; The minimum formable size of thin wall structures is 0.70 mm; The minimum formable diameter size of hole structures perpendicular to the fabricating direction is 0.50 mm; The optimal forming diameter size for circular hole structures parallel to the fabricating direction is 1.00～4.00 mm; The formable angle of sharp angle structures should be greater than 10°. The forming error of feature structures is mainly affected by the thermal adsorption of laser on composite powder, the diffusion of laser spot heat affected zone, and the weak support of composite powder. This work provide a certain technical reference for the design and additive manufacturing of complex diamond tools.
Abstract: A new nickel plating process for diamond wire is explored to eliminate the negative impact of dispersants on the production process of diamond wires. The surface of of Ni-plated diamond particles was first hydroxylated with hydrogen peroxide, and then reacted with dimethyloctadecyl [3-trimethoxysilylpropyl] ammonium chloride to prepare positively charged diamond particles. Finally, the preparing process of diamond wires were optimized. Results show that the surface potential of diamond particles increases from −7.50 mV to 14.10 mV or above after reaction, up to 30.68 mV. The best preparing conditions are as follows: The mass ratio of raw sand to hydrogen peroxide is 2 to 1, with treating time of 1 h; The mass ratio of diamond particles to quaternary ammonium salts is 1 to 2, with treating time of 4 h. In the electroplating process, the diamond particles with chemically modified surface would uniformly migrate towards the cathode without dispersants, the sanding capacity of which could be increased by 20% or more.
Abstract: To improve the microstructure and properties of Cu-Sn-Ti brazing alloy through component control, the effect of Si on the microstructure and properties of Cu-20Sn-15Ti brazing filler metals was studied using scanning electron microscopy, X-ray diffraction, and EDS energy spectrum analysis. The results show that the microstructure of Cu-20Sn-15Ti brazing filler metal is composed of large-sized polygonal CuSn3Ti5 phase, eutectic structure and α-Cu phase. A small amount of Si (≤ 2.0wt%) refines the polygonal-shaped CuSn3Ti5 phase in the brazing filler metal and generates small-sized Si3Ti5 phase. In contrast, a larger amount of Si (≥ 3.0wt%) differentiates the polygonal-shape CuSn3Ti5 phase, reduces the proportion of eutectic structure, and increases the content and size of the Si3Ti5 phase. When the Si content increases to 5.0wt%, the filler metal no longer generates polygonal-shaped CuSn3Ti5 phase and eutectic structure. Instead, Ti primarily forms Ti5Si3 phase, and the microstructure mainly consists of Ti5Si3 phase, α- Cu phase, Cu41Sn11 phase, and a small amount of strip-shaped CuSn3Ti5 phase. Compared with Cu and Sn, Si has a stronger chemical affinity with Ti and preferentially reacts with Ti to form Ti5Si3 phase. The three-dimensional structure of Ti5Si3 phase is prismatic and exhibits agglomerated growth characteristics. The coarse strip Ti5Si3 phase has central or lateral pore defects, which are mainly related to the growth mechanism. As the Si content increases, the shear strength of the filler metals shows a trend of “increasing-decreasing-increasing”, and the fracture morphology transitions from a mixed morphology of quasi-cleavage fracture and cleavage fracture to cleavage fracture. The CuSn3Ti5 phase is prone to breakage and cracking, becoming the source of cracking. The presence of coarse CuSn3Ti5 phase in different states can deteriorate the shear strength of the brazing filler metals to some extent.
Abstract: As a typical hard and brittle material, single-crystal silicon exhibits different strain rates at varying scratching speeds, leading to diverse material removal behaviors. Molecular dynamics was used to study the deformation and removal processes of single-crystal silicon at different scratching speeds from the perspective of strain rate. The results show that the strain rate of the material increases from 1.25 × 1010 s−1 to 1.25 × 1011 s−1 as the scratching speed increases from 25 m/s to 250 m/s. At the same time, the scratching parameters, including scratching force, shear stress, and friction coefficient, decrease while the scratching temperature increases. Additionally, the contour accuracy and roughness of the scratch surface improve with increased scratching speeds. Amorphization and phase transformation during the scratching process are the main mechanisms of nanoscale deformation in single-crystal silicon. The depth of the subsurface damage layer decreases from 2.24 nm to 1.89 nm with the increase of shear stress, while the depth of the amorphous layer increases with the rise in scratching temperature.
Abstract: To investigate the scratch removal mechanism of unidirectional Cf/SiC composite materials, quasi-static scratching tests were carried out using a single diamond abrasive grain to analyze the changes in acoustic emission signals of the scratched materials under different indentation loads. These tests were complemented by SEM images to analyze the removal behavior and scratch removal mechanism of the materials. The test results show that the acoustic emission signal value increases with the increase in indentation load. Under the same parameters, the signal value in the SB direction is larger, and the signal fluctuation is more severe. Combining the acoustic emission signal and SEM morphology analysis, it is concluded that the scratch removal behavior of the material varies in different directions. The material primarily undergoes brittle removal. In the SA direction, fibers mainly experience tensile fracture and fiber pull-out, whereas in the SB direction, the main fracture modes of the fiber are bending fracture and shear fracture. According to the SEM morphology analysis, the formation process of the removal behavior and the material scratch removal mechanism are described.
Abstract: To reveal the grinding removal mechanism of 2D SiCf/SiC composites, according to the weaving structure characteristics of 2D SiCf/SiC composites, scratching experiments were conducted on the woven surface (WS) and stacking surface (SS) of 2D SiCf/SiC along 0°, 45°, and 90° directions. The experiments measured the scratching force and scratching depth and observed the scratching surface morphology. The results show that the removal modes for the SiCf/SiC material on WS0 (0° direction of fiber woven surface) are mainly shear, tensile, and bending fracture of longitudinal fibers (ie. the fiber axis is consistent with the feed rate direction), and shear, bending, and tensile fracture of transverse fibers (ie. the fiber axis is perpendicular to the feed rate direction). On WS45 (45° direction of fiber woven surface), the main removal modes are shear, bending, and tensile fracture. On SS0 (0° direction of fiber stacking surface), the main removal modes are extrusion and bending fractures of normal fibers (ie. the fiber axis is perpendicular to the scratching surface), as well as shear, tensile, and bending fractures of longitudinal fibers. On SS90 (90° direction of fiber stacking surface), the main removal modes are ductile removal, shear and bending fractur of normal fibers, and shear, bending, and tensile fracture of transverse fibers. Due to the anisotropy of SiC fibers, different directions and fracture modes exhibit varying mechanical properties. Shear fracture requires the least force, while tensile fracture requires the most force. At the same scratch depth, due to the different fracture modes in the WS0, WS45, SS0, and SS90 directions and varying proportions of shear, bending, and tensile fractures, the order of scratch forces is FSS0 > FWS45 > FSS90 > FWS0. When abrasive particles penetrate the composite material, the SiC matrix is peeled off and removed along with crack expansion and mutual penetration. Part of the matrix is removed by compression and then re-scratched by abrasive particles to form ductile scratches. When cutting 2D SiCf/SiC composite materials, it is advisable to choose the WS0 direction and avoid the SS0 direction as much as possible.
To improve the roughness prediction accuracy of Al2O3-based ceramic insulation coating on bearing surfaces, a method based on the spectral confocal principle was proposed for measuring the surface of grinding wheels and quantifying the characteristic parameters of abrasive particles. The abrasive characteristic parameter K of the grinding wheel surface, the grinding wheel line speed vs, the workpiece feed speed f, the cutting depth ap, and the normal grinding force F were taken as input parameters. A BP neural network prediction model of workpiece surface roughness, which directly reflects the time-varying state of the grinding wheel surface, was established. The prediction performance of the network model was verified using known grinding samples and four groups of unknown samples after grinding wheel wear. The results show that the predicted roughness results of the BP network model with known samples are consistent with the actual roughness results in terms of regularity and numerical values, with network output errors are all less than ± 0.04 μm. The network prediction accuracy for the four unknown samples decreases, but the absolute value of the maximum relative error does not exceed 20.00%. The neural network prediction model, which includes the characteristic parameters of abrasive particles on the grinding wheel surface , can be used to predict the roughness of Al2O3-based ceramic insulation coating on the bearing surface under the time-varying state of abrasive wear on the grinding wheel. It also demonstrates a certain generalization ability for unknown samples.
Abstract: To study the removal mechanism of ITO conductive glass materials, this paper uses a single abrasive particle to simulate the cutting process of the materials and establishes a material model for ITO glass. Based on the analysis of processed surface morphology, stress, and cutting force, the material removal mechanism of ITO glass is examined. Additionally, the influence of cutting parameters on cutting force and residual stress is studied and compared with soda-lime glass. The results show that during the cutting process of abrasive particle, material removal is influenced by the ITO film layer, the glass substrate, and cohesive contact behavior, leading to failure forms such as delamination, channel cracking, and interlayer fracture. With the feed of the abrasive particle, the cutting force fluctuates within a certain range, exhibiting a pattern of growth, stability, and decrease. The cutting force of the abrasive particle is positively correlated with both cutting speed and cutting depth. Compared to the glass substrate, the residual stress on the ITO film is larger and fluctuates more dramatically. The presence of the ITO film significantly influences cutting behavior, especially when the cutting depth approaches the thickness of the ITO film.
Abstract: An intelligent tool wear prediction model has been proposed for the micro-grinding tool, optimized using a genetic algorithm (GA) based BP neural network. The GA-BP prediction model is applied with in-situ tool wear detection to obtain training set data and combines cluster analysis to divide the tool wear stages. To represent the uncertainty in wear characteristics, the loss of cross-sectional area of the micro-grinding tool has been selected as an index to evaluate tool wear loss. The K-means clustering algorithm is used to cluster and analyze the tool wear stages under different process parameters. The GA-BP neural network includes five neurons in the input layer: rotating speed, feed rate, cutting depth, grinding length, and the initial cross-sectional area of the tool. The output layer neuron predicts the loss of the tool's cross-sectional area. To validate the method, a series of micro-grinding experiments were performed under different parameters for the micro-groove array of monocrystalline silicon. The loss of the tool's cross-sectional area was measured by a self-made visual inspection system, providing learning samples for the prediction model. The predicted results of the GA-BP neural network model were compared with the traditional Gaussian process regression method. The results show that the GA-BP neural network model can correctly predict tool wear loss and identify wear stages under different process parameters and grinding lengths. It has higher prediction accuracy during the self-learning process, with an average error of 5% .
To address the challenges of high grinding force and poor processing quality in grinding zirconia ceramics with traditional grinding wheels, this study explores the use of leaf vein bionic fractal textured diamond grinding wheels. These wheels, designed with fractal angles of 30.0°, 45.0°, and 60.0°, leverage the leaf vein bionic fractal texture's capabilities in reducing drag, guiding flow, heat dissipation, and mass transfer. The effects of the original grinding wheel and the three types of bionic fractal grinding wheels on the surface roughness (Ra), grinding force, and grinding force ratio of zirconia ceramics were compared and analyzed. The results show that the bionic fractal grinding wheels outperform the original grinding wheel. Specifically, compared to the original grinding wheel, the normal grinding force of the bionic fractal grinding wheel is reduced by 12.7% to 55.8%, and the tangential grinding force is reduced by 8.1% to 40.3%. The bionic fractal grinding wheels have not obvious effects on the surface roughness Ra. When the fractal angle is 30.0°, the minimum grinding force ratio is 1.4 to 3.0, and the minimum surface roughness Ra is 1.824 μm.
To study the surface morphology of Si3N4 ceramics using rotary ultrasonic grinding, changes in the surface morphology under different machining parameters were analyzed based on fractal theory. Orthogonal experiments were designed to compare and analyze the effects of various processing parameters on the fractal dimensions and multifractal spectra of the Si3N4 ceramic surface. Additionally, single-factor experiments were conducted to study the roughness, fractal dimensions, and multifractal spectra of the Si3N4 ceramic surface under different processing parameters. The results show that fractal dimensions can effectively characterize the defect state of the processed surface of Si3N4 ceramics during rotary ultrasonic grinding, while multifractal spectra can better represent the degree of fluctuation in surface defects.
Abstract: To prepare structured fish scale surfaces on brittle and difficult-to-process materials, the topological features of fish scale surfaces are first extracted, and a surface model of fish scale units is established. This fish scale model is then used to construct the structured fish scale surface. Next, based on the principle of micro-abrasive air jet processing, the feasibility of air jet processing for topological fish scale experiments and the important process parameters affecting the morphology of the structured fish scale surface are analyzed. Finally, using the single-factor experimental method, the important processing parameters are experimentally analyzed to obtain a better topological fish scale surface unit, and the structured surface is arranged accordingly. The research results show that a reasonable combination of process parameters for micro-abrasive jet machining of structured topological fish scale surfaces includes a machining time of 10s, a machining pressure of 0.5 MPa, a stand-off distance of 10 mm, and a jet angle of 30°. Despite the potential for certain effects on the morphology and size of the fish scale surface, the topological properties of the fish scale surface remain unchanged using the proposed machining method.
Abstract: To precisely forecast the power of a tower combined diamond circular saw blade during material sawing, a model for sawing power was established using the average thickness of an undeformed chip from a single grinding grain of an individual saw blade within the combination saw as a medium. This model was then refined to enhance accuracy. A fast and accurate prediction model, requiring only a small number of samples, was developed. Sawing power was measured through various parameter combinations via sawing experiments, and model coefficients were obtained by fitting the data using multivariate linear regression techniques. An optimization model was subsequently established, with sawing parameters as optimization variables. The objectives of this model were to minimize sawing specific energy and reduce sawing time. An optimized particle swarm algorithm was adopted to solve the model. The experimental results reveal that the parameter model can comprehensively elucidate the influence of various sawing parameters on sawing power, with the model accurately forecasting the sawing power under different saw blade combinations. The improved particle swarm algorithm demonstrates strong optimization performance, with optimized parameters contributing to significant reductions in sawing power.
Abstract: Solid-state nanopores have become the most promising single-molecule sequencing tools due to their adjustable pore size, stable physical and chemical properties, strong adaptability to extreme environments, and high integration. In the area of solid-state nanopores research, improving the detection accuracy of single molecules has always been the core concern of researchers. In recent years, the double-layer nanopores has attracted wide attention. Compared with traditional single-layer nanopore, the "pore-cavity-pore" structure of double-layer nanopores provides two molecular recognition sites and nanoconfined space. The two molecular recognition sites provided by the two nanopores can obtain two target signals in a single translocation event, which not only enrich the detection information but also provide the most direct comparison information source for signal analysis. In addition, the "cavity" in the double-layer nanopores can be used as a single-molecule chemical reactor. Therefore, the appearance of double-layer nanopores broadens the application range of nanopore sensors and has an important application prospect in single molecule detection. In this paper, the development history of nanopores is summarized, and the fabrication methods of double-layer nanopores and their applications in the field of single-molecule detection are emphatically introduced.
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