Optimising the interface microstructure is crucial for enhancing the thermal boundary conductance (TBC) of thermally conductive composites. This study employs non-equilibrium molecular dynamics simulations to compare the TBC between (100) and (111) diamond crystal planes and their copper substrates at different etched pattern densities. Through analysis of the phonon density of states, the physical mechanism responsible for the differences in TBC has been elucidated. The results indicate that the TBC significantly increases with the density of the etched patterns. Following complete etching, the TBC of diamond/copper interfaces on the (100) and (111) planes reached 2.41 times and 3.18 times that of the unetched interface, respectively. Phonon density of states analysis indicates that the interface etched pattern effectively promotes the migration of high-frequency phonons in diamond towards lower frequencies, thereby enhancing phonon coupling. In addition, the phonon reflection effect generated by the etched pattern further enhances the TBC. Upon reaching saturation, the subsequent increase in TBC primarily comes from the linear growth of the actual contact area. This paper elucidates the physical mechanism by which an etched pattern on the interface enhances thermal transport at the atomic scale, providing a theoretical basis for the design of high-performance thermal management composites.

Fabricating microstructures on diamond particle surfaces is an effective approach to enhance both the interfacial bonding strength and thermal conductivity of composite materials. In this work, the etching behavior of diamond {100} and {111} crystal planes in molten potassium nitrate under different process conditions was investigated using the molten salt method. The etching mechanism was elucidated through combined thermodynamic and kinetic analyses. The results show that within the temperature range of 600-700 degrees C, square etch pits form on the {100} plane of diamond, while triangular etch pits form on the {111} plane. The pit size on the {100} plane was significantly smaller than those on the {111} plane. Both pit density and size increased with rising temperature and prolonged etching time. Thermodynamic analysis identified the dominant reaction pathways and confirmed that elevated temperatures accelerate the reaction kinetics. Kinetic fitting results indicate activation energies of 167.2 kJ/mol for the {100} plane and 198.3 kJ/mol for the {111} plane. Despite the higher activation energy of the {111} plane, its etching rate is markedly higher than that of the {100} plane. This is attributed to the higher density of defects and impurities on the {111} plane, which provide abundant active sites for the etching reaction.

Due to the excellent nonlinear optical properties and high damage threshold of Potassium Dihydrogen Phosphate (KDP) crystal, it is critical for high-power laser systems and inertial confinement fusion. Chemical mechanical polishing (CMP), which synergizes chemical reaction and mechanical micro-cutting actions for high-precision surface finishing, is a predominant method for KDP crystal processing. To elucidate the chemical and mechanical mechanisms, molecular dynamics is employed to investigate both pure mechanical action and chemical-mechanical synergy in CMP of KDP crystal. A molecular dynamics model of single abrasive scratching on KDP crystal was performed to compare material removal mechanism between crystalline and amorphous surfaces, with the amorphous surface serving as a proxy for chemical reaction, and to evaluate the effect of scratching depth on thermomechanical behavior, scratching forces, and surface integrity. The results show that the amorphized KDP surface mitigates the accumulation of thermal and mechanical stresses during scratching, exhibiting lower stress magnitude and a more uniform distribution compared to the crystalline surface. This validates that the chemical contribution enhances surface quality. Optimal chemical-mechanical synergy was achieved at matched amorphous layer thickness and scratching depth (2 nm), yielding atomic-scale surface planarization. These results unravel that chemical reaction facilitates enhanced surface quality, and the synergistic chemical-mechanical effect achieves optimal performance when chemical and mechanical contributions are balanced in CMP of KDP crystal.

Agglomerated ultrafine diamond (AUD) wheels were developed to enhance the processing stability of ultrafine-grained wheels. Their grinding mechanism, focusing on how the secondary particle size affects performance, was studied using a cutting-edge model and grinding experiments on fused quartz. The grinding behavior of AUD wheels is jointly governed by primary working edges (PWEs), which dominate material removal and bear the major wear, and non-primary working edges (NPWEs), which help alleviate machining damage induced by the PWEs. Increasing the secondary particle size moderately raises the number of NPWEs, thereby improving AUD wheels' grinding quality. Experiments confirmed the AUD wheel's superior processing stability. When AUD abrasives with a 2 mu m primary particle size and a 46-56 mu m secondary particle size were incorporated into the wheel at a 150% concentration, the transverse surface roughness of the ground workpieces remained stable at approximately 80 nm throughout the experiment.

Fixed abrasive lapping is a critical process that affects the surface accuracy of optical components, its machining accuracy directly determines the overall imaging performance of optical parts. However, the surface shape of the workpiece during lapping is time-varying, and the convergence timing is judged by the operator's experience and offline measurement results, which introduces great uncertainty into subsequent process control. To acquire the surface shape status of the workpiece and improve its controllability, this study established a multi-source information acquisition platform for swing fixed abrasive lapping (SFAL). The spindle motor current signal U1, eccentric wheel motor current signal U2, and acoustic emission (AE) signal were fused at the feature level based on multi-sensor information fusion technology. A random forest classification model optimized by the sparrow search algorithm (SSA-RF) was employed to achieve in-situ monitoring of workpiece surface shape category (convex, flat, concave). Based on the kinematic model of SFAL, the distribution of abrasive sliding distance under different parameter combinations was investigated, and process regulation strategies were proposed for convex and concave workpieces. The results indicated that when the fused signal features were used as input, the prediction accuracy of the SSA-RF model improved by more than 15 %, and a classification accuracy of 89.83 % for workpiece surface shape was achieved. For workpieces that do not meet the convergence condition, process regulation can be adopted to change the distribution of abrasive sliding distance on the workpiece surface, thereby facilitating the evolution toward surface flattening. After process regulation, the peak-to-valley (PV) value of the convex workpiece surface profile converged to 1.72 mu m; The surface shape convergence efficiency of the concave workpiece in the early processing stage was improved, and the surface profile PV value finally converged to 1.29 mu m. This study provides a theoretical foundation and technical approach for the high-precision machining and intelligent development of optical components.

This study investigates the evolution of material removal mechanisms during fixed abrasive (FA) lapping using acoustic emission (AE) analysis. The wavelet synchro-squeezing transform (WSST) and marginal spectrum analysis were employed to analyze AE signals collected during lapping with single crystal diamond (SCD), agglomerated diamond (AD), and non-abrasive pads. The material-removal rate for SCD fell from 0.62 to 0.18 μm/min over sixty minutes, whereas AD remained high, starting at 5.2 and ending between 3.9 and 4.1 μm/min. The fused quartz wafer surface roughness Ra after lapping reached 15.6 nm with SCD and 52.6 nm with AD. Results revealed distinct shifts in material removal modes as diamond particles underwent wear and blunting. The root mean square of AE signal rose and fell in step with MRR for both SCD and AD, confirming a strong positive correlation between signal magnitude and material removal. Characteristic AE frequencies were identified for micro-cutting, plowing, debris movement, and AD micro-fracturing, enabling non-contact monitoring of these processes. Analysis revealed a distinct peak near 0.22 MHz, attributable to micro-cutting, and another around 0.28 MHz, corresponding to plowing. Additionally, frequencies in the 0.60–0.75 MHz range observed in the AD pad indicate micro-fracturing associated with self-sharpening behavior. This non-destructive technique offers significant potential for optimizing FA lapping parameters to achieve desired material removal rates and surface finishes.

Agglomerated diamond (AD) wheels, which integrate the advantages of fine-grained abrasives with enhanced wear resistance, were employed to overcome the wear limitations of conventional fine-grained wheels in precision grinding of hard and brittle materials. The grinding mechanism of AD wheels was systematically investigated through theoretical modeling and numerical analysis, using single-crystal diamond (SCD) wheels for comparative evaluation. The thickest chip models were established for both the AD wheel and the SCD wheel, followed by numerical simulations and experimental validation involving the grinding of fused quartz. The results demonstrated that the AD wheel features a higher density of protruding abrasives, reduced abrasive spacing, and more uniform abrasive heights, leading to thinner chip formation. Significant variations in undeformed chip thickness among quasi-equal-height micro-edges on a single active AD abrasive resulted in their functional differentiation into primary and non-primary working micro-edges. From 30 to 90 grinding passes, the surface roughness (Ra) of the workpiece processed with the SCD wheel increased by 56.1 %, whereas that of the workpiece processed with the AD wheel decreased by 10.2 %. Throughout the grinding process, the AD wheel consistently maintained superior surface quality and stability. The micro-fracture of AD abrasives during grinding enables sharp non-primary working micro-edges to replace dulled primary working micro-edges, with this renewal continuing as new primary working micro-edges degrade. This self-sharpening mechanism ensures the processing stability of AD wheels and highlights the significant potential of ultrafine abrasives for further applications in precision grinding.

This study employs the fixed agglomerated diamond abrasive pad (FADAP) to enhance the processing efficiency and surface quality of 4H-SiC. The effects of voltage on real-time current density, interface resistance, material removal rate (MRR), and surface roughness Ra during the electrochemical mechanical polishing (ECMP) process are investigated, providing both theoretical and experimental insights for process optimization. A fixed abrasive ECMP equipment was developed, and polishing experiments on 4H-SiC were conducted using the slurry composed of 10 % NaNO3 and 7 % H2O2. The variations in real-time current density, interface resistance, MRR, and surface roughness Ra were measured and analyzed within the voltage range of 0-9 V. The results indicate that as the voltage increases, both real-time current density and interface resistance rise, while their growth amplitude gradually declines. When the voltage increased from 0 V to 9 V, the MRR improved from 20.736 mu m/h to 25.261 mu m/h, representing an approximately 22 % increase compared to the no-voltage condition. Within the experimental range, a linear correlation is observed between current density and MRR, while the surface roughness Ra gradually decreases and stabilizes at approximately 23 nm. By analyzing the effects of voltage on the electronic activation energy of the 4H-SiC surface and the electro-Fenton reaction in the polishing slurry, the mechanism by which voltage enhances MRR in ECMP was elucidated. This study provides systematic theoretical and experimental support for 4H-SiC ECMP, contributing to the optimization of process parameters and the improvement of semiconductor processing quality.

Due to Silicon carbide (SiC) wafer favorable characteristics, including a wide bandgap, high thermal conductivity and a high breakdown field strength, it is widely utilized in the development of power semiconductor devices. Presently, the processing flow of SiC wafers consists of four steps: rough lapping, precision lapping, rough polishing and precision polishing, which is a complex and less efficient method. Fixed abrasive chemical mechanical polishing (FA-CMP) technology was employed for polishing of SiC wafers,to replace the conventional process of precision lapping and rough polishing in a single step. The benefits are simplified procedures, a reduction in polishing time and an increase in efficiency. The effect of additive type and concentration in the abrasive-free slurry, as well as abrasive size and concentration in the fixed abrasive pad (FAP), on the polishing outcome were investigated. The results indicated that the surface polished with ethylene glycol (EG) exhibited no discernible scratches and attained the optimal surface quality. As the concentration of ethylene glycol increased, the material removal rate (MRR) declined, while the surface roughness initially decreased and then increased. At a concentration of 4 vol%, the MRR was 13.1 mu m/h, while the surface roughness Sa was 1.6 nm. Furthermore, both the MRR and surface roughness exhibited an inverse relationship with the abrasive size, whereas they demonstrated a direct correlation with the abrasive concentration. When the abrasive size was 3-5 mu m and the concentration was 125 %, the surface quality of the polished SiC wafers was excellent and scratch-free, and the surface roughness Sa reached 1.13 nm, while the MRR was 7.4 mu m/h. Therefore, SiC wafer FA-CMP will significantly increase the efficiency and improve the surface quality. Thus, the efficient and high-quality processing of SiC wafers will be achieved.

Agglomerated ultrafine diamond (AUD) abrasives were developed to enhance the grinding stability of ultrafinegrained wheels for hard-brittle materials. Grinding characteristics of AUD wheels utilizing AUD abrasives with a primary particle size of 2 mu m were investigated. Average undeformed chip thickness models were established to correlate the grain size characteristics of AUD wheels with those of single-crystal diamond (SCD) wheels. Under conditions of comparable average undeformed chip thicknesses for the two wheel types and using fused silica as the workpiece material, a combination of molecular dynamics (MD) simulations, ball-on-disk friction tests, and precision grinding experiments was conducted. The models revealed that the average undeformed chip thickness of AUD wheels with a primary particle size of 2 mu m and a secondary particle size of 40 mu m is approximately equivalent to that of SCD wheels with particle sizes in the range of 6.6-10.2 mu m. Simulations revealed that the multi-micro-edge cutting behavior of AUD abrasives offers significant advantages in reducing machining damage. In friction tests, the AUD ball maintained a higher and more stable coefficient of friction and exhibited greater material removal efficiency than the SCD ball under precision processing scenarios. Furthermore, the grinding experiments revealed significantly improved surface quality and enhanced processing stability with the AUD wheel. These advantages are attributed to the multi-micro-edge cutting behavior and the self-sharpening effect caused by the micro-fracturing of AUD abrasives. Therefore, AUD wheels provide a practical and effective solution for facilitating the application of ultrafine abrasives in the precision grinding of hard-brittle materials.

Silicon carbide (SiC) crystal is a third-generation semiconductor material, which is widely used in the fields of radio frequency components, aerospace, new energy vehicles, etc. The anisotropy of 4H–SiC leads to differences in material removal characteristics of different crystal surfaces, which influences the design of process parameters for SiC crystal polishing. A model of single abrasive scratching 4H–SiC crystal was established using molecular dynamics. The effect of scratching speed and depth on the material removal characteristics and the wafer surface morphology was investigated when a single abrasive scratches the C surface and Si surface. Scratching experiments were conducted to verify the model by measuring scratch cross-sectional area, scratch profile, and surface roughness. The simulation results reveal that compared to the Si surface, the distribution range of high hydrostatic stress of the C surface is less, resulting in fewer amorphous atoms and easier dislocation, which means the C surface is more favorable for getting plastic removal and obtaining better surface quality. The experiment data suggested that the C surface has a smaller surface roughness and a friction coefficient, and the cross-sectional area of the scratch is larger than that of the Si surface. Under low-speed conditions, the influence of anisotropy is more pronounced. Consistent with the simulation result, the material removal characteristics of the C surface are better than those of the Si surface when single abrasive scratching 4H–SiC crystal.

Laser cutting can achieve ultra-precision cutting of materials by using appropriate parameters. In order to optimize processing parameters and obtain better processing quality, conducted experimental research on laser cutting of Glass fiber reinforced plastic (GFRP). In this study, the impact of four process parameters (laser power, cutting speed, assistant gas pressure and focus position) on quality characteristics (kerf width, kerf taper and kerf section roughness) was evaluated through analysis of variance (ANOVA), the regression relationship between laser processing parameters and quality characteristics was analyzed. And an integrative model for predicting and optimizing the quality characteristics of fiber laser cutting was constructed. In the proposed integrative model, Back-Propagation Neural Network (BPNN) was used to build a prediction model for quality characteristics. Through Non-dominated Sorting Genetic Algorithm (NSGAII) optimizes and outputs the complete optimal solution set of processing parameters, and finally realizes the nonlinear optimization of multi-objective parameters. The fitness value of BPNN model can reach 97.814%, and the maximum prediction relative error is 8.614%. And the set of suggested optimal solutions can be used as most of them are showing certain improvements in the quality characteristics. The results indicate that the integrative modeling strategy has the ability to predict and optimize laser cutting of composite materials.

The traditional aqueous-based polishing slurries have been extensively used in the ultra-precision machining process of SiC substrates, but their processing efficiency remains a major challenge in making SiC wafers with high surface quality. SiC polishing slurries based on non-aqueous solvents have been explored and reported, however, the mechanism for the accelerated SiC material removal rate (MRR) remains unknown. In this work, the Si-face and C-face of the SiC wafer were polished with water and methanol as polishing liquid carriers, respectively. The MRR of Si-face using the methanol-based slurry, can reach 260.9 nm/h, and the polished Si-face surface roughness Ra reduces to 0.150 nm. In contrast, the MRR of Si-face by using the aqueous-based slurry, is 66.8 nm/h, the polished Si-face surface roughness Ra is 0.691 nm. However, the results of MRR and Ra for C-face are opposite. The reaction between the polishing liquid carriers and the atomic structures of Si-face and C-face lead to differences of the MRRs by analyzing contact angle, XPS, and molecular dynamics (MD) simulation results. The newly revealed polishing mechanisms shined light for speeding up the development of SiC polishing slurries based on the specific aspects of the polishing surface of SiC.

本文通过固结磨料球与KDP晶体对磨的单因素试验探究固结磨料球中反应物种类、磨粒浓度、反应物浓度、基体硬度对摩擦系数、磨痕截面积和磨痕处粗糙度的影响,试验结果表明:KHCO3固结磨料球对磨后磨痕对称性好,磨痕处的粗糙度值低;磨痕截面积随磨粒和反应物浓度的增加而增大,随基体硬度的增大而降低;磨痕处粗糙度随磨粒和反应物浓度的增加先降低后上升,随基体硬度的增大先上升后降低;摩擦系数受磨粒和反应物浓度影响不明显,随基体硬度的增大而降低.选择KHCO3作为反应物,Ⅰ基体,磨粒浓度为基体质量的100％,反应物浓度为15％制备固结磨料球与KDP晶体对磨后的磨痕轮廓对称度好且磨痕处粗糙度值低,以该组分制备固结磨料垫干式抛光KDP晶体,可实现晶体表面粗糙度Sa值为18.50 nm,材料去除率为130 nm/min的高效精密加工.

Gallium oxide crystal is one of the most representative fourth generation semiconductor materials with the advantages of high band gap, high voltage resistance and short absorption cutoff edge. It has broad application prospects. Micro-cracks, scratches and other surface defects are prone to appear in the polishing process of Gallium oxide crystal, which is difficult to achieve high-quality surface processing and cannot meet the requirements of corresponding devices. Moreover, the existing polishing process of gallium oxide crystal is complex and inefficient. Fixed abrasive polishing technology has the advantages of controllable abrasive distribution and depth of cut, and high utilization rate of abrasive. In this study, fixed abrasive polishing of gallium oxide crystal was adopted, and the effect of matrix hardness, abrasive concentration of polishing pad, the additives of polishing slurry on material removal rate and surface quality were investigated. The results show that when the hardness of the polishing pad is moderate II, the abrasive concentration is 100%, and the slurry additive is oxalic acid, the material removal rate is 68 nm/min and the surface roughness Sa value is 3.17 nm in fixed abrasive polishing of gallium oxide crystal. Fixed abrasive polishing technology can achieve high-efficient and high-quality polishing of gallium oxide crystal.

Rapid pattern-recognition capabilities are very challenging tasks to fulfill while essential steps for the ultimate mission of achieving in-time security response, hazardous disaster prevention, structural failure prediction, and intelligent manufacturing applications. Mechanistic manifestation of a machining process through pattern recognition is even more daunting since one has to gain full understanding at the very fundamental level of the manufacturing processes, but it would be the most beneficial should it be accomplished. We designed and built an in-situ Acoustic Emission (AE) monitoring system, and successfully applied this newly developed AE system to manifest the lapping removal mechanisms of a novel fixed abrasive pad embedded with agglomerated diamond (AD) abrasives. To successfully extract valuable mechanistic information, the time-frequency spectrum of collected AE signals in a sapphire lapping process was decomposed by Wavelet Packet Transform (WPT) into three characteristically patterned bands, each representing rubbing, ploughing and cutting action in the lapping process correspondingly. We creatively applied Point Density Fuzzy C-Means (PD-FCM) algorithm for self-identifying clustering centers to classify contributions from rubbing, ploughing and cutting actions in the lapping process. By rapid intelligent pattern recognition analysis (RIPRA) of AE signals, the lapping removal mechanisms using fixed abrasive pads were clearly identified and quantitatively monitored in-situ throughout the whole lapping processes. Such a capable approach implicates a great potential in a wide range of ultra-precision manufacturing applications.

In pursuing high precision and high-quality surface of silicon carbide (SiC) substrates for electronic applications, however, the processing efficiency on Si-face has long been a difficult challenge compared to that of the C-face. Conventional polishing slurries are aqueous-based due to its unparalleled compatibility with most of chemical reagents, and have been widely studied and well understood. The chemical reactivity of all added accelerating agents in aqueous polishing systems is constrained by the prevalent presence of water as a solvent. On the other hand, non-aqueous polishing systems have not been well explored. In this report, reactive non-aqueous organic systems containing polar hydroxyl groups are evaluated as a high efficiency processing vehicle for Si-face polishing of SiC on fixed abrasive pads (FAPs). The surface quality of SiC is surprisingly improved while the polishing efficiency is accelerated on a diamond FAP in presence of methanol compared to those using water, and are further improved when organic acids are introduced to the reactive non-aqueous fluids. Contact angle measurement and X-ray photoelectron spectroscopy (XPS) analysis on the polished SiC surface are completed to assist us to shed light on the removal behavior and to explore and elucidate the removal mechanism of non-aqueous system fluids on FAPs. The initial positive results from this reactive non-aqueous polishing system serves our community as a promising approach for the ultra-precision polishing on other hard-to-process semiconductor and ceramic materials.

为探究单摆参数对抛光工件平面度的影响,提出一种基于速度和压强分布耦合的抛光微元材料去除模型,以预测工件表面平面度.从单颗磨粒的材料去除出发,建立工件表面各微元单位时间内材料去除厚度模型,并将工件相对抛光垫速度和工件表面压强分布耦合代入模型;根据工件初始面形提取微元高度值,结合各微元材料去除的厚度,计算抛光后的工件表面平面度;试验验证平面度预测方法.结果表明:仿真与实际抛光后的面形的变化趋势相同,平面度PV20值绝对偏差小于12.0％,平面度预测可靠.

A microelement material removal model was proposed to explore the influence of single pendulum parameters on the polishing flatness of workpiece. Based on the coupling of velocity and pressure distribution, the model could predict the polishing flatness. Starting from the material removal of single abrasive particle, the model of material removal height of each microelement on the workpiece surface in unit time was established. The velocity of workpiece relative to polishing pad and pressure distribution of workpiece surface was coupled and inserted into the model. According to the initial surface shape of workpiece, the height value of microelement was extracted, and the flatness of the workpiece after polishing was calculated combined with the thickness of microelement material removal. Experiments were carried out to validate the flatness prediction method. The results show that the change trend of the surface shape after simulated polishing is same as actual polishing, and the absolute deviation of flatness PV20 is less than 12.0%. The flatness prediction is reliable.