Nanomachining Process Research Articles

Surface integrity analysis and inspection for nanochannel sidewalls using the self-affine fractal model-based statistical quality control for the atomic force microscopy (AFM)-based nanomachining process

The atomic force microscopy (AFM) technology is a promising method for nanofabrication due to the high tunability of this affordable platform. The quality inspection and control significantly impact the manufacturing effectiveness for realizing the functionality of the achieved nanochannel. Particularly, the surface characteristics of nanochannel sidewalls, which play a significant role in determining the quality of the nanomachined products, can not be accurately captured using conventional surface integrity metrics (e.g., surface roughness). Therefore, it is necessary to propose a method to quantitatively characterize the surface morphology and detect the abnormal parts/regions of the nanochannel sidewall. This paper presents a statistical process control approach derived from the self-affine fractal model to detect the sidewall surface anomalies. It evaluates changes in the self-affine fractal model parameters (standard deviation, correlation length, and roughness exponent), which can be used to signify the changes on the sidewall surface; the statistical distributions of these parameters are derived and used to develop control charts to allow inspection of the sidewall morphology. The approach was tested on the AFM-based nanomachined samples. The results suggest that the presented approach can effectively reflect the abnormal regions on the machined parts, which opens up a new avenue toward guiding the quality control and rework for process improvement for AFM-based nanomachining.

Nonlinear Damping as the Fourth Dimension in Optical Fiber Anemometry

AbstractIn this study, nonlinear damping is introduced as the fourth dimension in the operation of a fiber tip optomechanical anemometer. The flow sensing element, featuring a 3D rotor measuring 110 µm in diameter and fabricated through a two‐photon nanomachining process, is monolithically integrated onto the cleaved face of the optical fiber, which serves as an integrated waveguide. As the rotor encounters airflow, it spins, and mirrors on its blades reflect light across the fiber core at each pass. This setup permits precise measurement of gaseous fluid flow with minimal sensor footprint at the point of detection and accommodates a variety of optical sources and measurement apparatuses without the need for specific wavelength or broad‐spectrum capabilities. To stabilize the rotation of the rotor and facilitate consistent frequency‐domain analysis, a polydimethylsiloxane hydrocarbon stabilizing agent is infused into the gap between the rotor and stator of the sensing element via dual‐function microfluidic channels. This enhancement allows for the measurement of gaseous nitrogen flow rates from 10 to 20 liters per minute (LPM), with a consistent periodic response. Comprehensive characterizations of the fiber tip anemometer are presented with and without the stabilizing medium, demonstrating its crucial role in regulating the dynamics between the rotor and the stator.

A sensor-based monitoring approach to predict surface profile of vibration-assisted atomic force microscopy (AFM)-based nanofabrication

The vibration-assisted atomic force microscope (AFM)-based nanomachining offers a promising opportunity for low-cost nanofabrication with high tunability. However, critical challenges reside in advancing the throughput and the quality assurance of the process due to extensive offline experimental investigations and characterizations, which in turn hinders the wide industry applications of current AFM-based nanomachining process. Hence, it is necessary to create an in-process monitoring for the nanomachining to allow real-time inspection and process characterizations. This paper reports a sensor-based analytic approach to allow real-time estimations of the AFM-based nanomachining process. The temporal-spectral features of collected acoustic emission (AE) sensor signals are applied to predict the depth morphology of nanomachined trenches under different machining conditions. The experimental case study suggests that the most significant frequency domain information from AE sensor can accurately predict (R-squared value around 92%) the nanomachined depth profile. It, therefore, breaks the current limitation of characterization tools at the nanoscale precision level, and opens up an opportunity to allow real-time estimation for quality inspection of vibration-assisted AFM-based nanofabrication process.

Physics‐Informed Multistage Machine Learning Strategy for the Nanomachining‐Induced Plastic Deformation Behavior

The evolution of the dislocation density induced by the nanomachining process dominates the plastic deformation behaviors of materials, thus affecting the mechanical properties significantly. However, a challenging topic related to how to establish an accurate model for predicting the dislocation density based on the limited simulations and experiments arises due to the complicated thermal–mechanical coupling mechanism during the machining process. Herein, a multistage method integrating machine learning, physics, and high‐throughput atomic simulation is proposed to investigate the effect of cutting speed on the dislocation behavior in polycrystal copper. Compared with the traditional one‐step machine learning method, the constraint of physical features effectively improves the accuracy and generalization ability of the model. The results indicate that the dislocation behaviors depend on the competition between the cutting force and temperature. In the low‐cutting speed, the predominated role of the cutting temperature leads to a rapid decline of the dislocation density. In contrast, the dislocation density tends to be stable under a high‐speed cutting process due to the dynamic balance between the effects of the cutting force and temperature. Notably, the proposed strategy provides a new and universal framework to design the machining parameters to obtain high‐quality products.

Atomic-scale investigation of Pt composition on deformation mechanism of AuPt alloy during nano-scratching process

In this research, we performed molecular dynamics (MD) simulation to investigate the material removal mechanism and subsurface damage formation during nano-scratching of the gold-platinum (AuPt) alloy. In order to comprehend the deformation mechanism of AuPt alloy during nano-scratching, the influences of Pt composition in workpiece on the machining performance were analyzed. The results indicate that the Pt composition has a significant influence on the surface morphology including piling-up of workpiece atoms and elastic recovery on the machined surface. During the deformation process, the average shear strain of workpiece atoms decreases when the Pt composition increases. Besides, the average scratching force increases apparently with obvious fluctuation as the Pt composition increases. For the subsurface damage formation, typical crystal defects including atomic clusters, V-shape stacking fault couples, and stacking faults tetrahedra were observed in the workpiece subsurface. The lengths of perfect dislocations and Shockley partial dislocations gradually increase as Pt composition increases, while the overall length of sessile dislocations decreases obviously. Meanwhile, thinner stacking faults were formed in the workpiece subsurface as the balanced width of stacking fault gradually decreases when the Pt composition increases. This work contributes to a better understanding of the nanoscale deformation mechanism of bimetallic materials during micro or nano machining process.

Nanomachining of van der Waals nanowires: Process and deformation mechanism

The edges of van der Waals materials exhibit unique physical and chemical properties, and they are promising for applications in many fields, such as optoelectronics, energy storage, and catalysis. Van der Waals material nanostructures with a controllable high density of edges are difficult to produce by current fabrication methods. In the present study, a simple nanomachining process to fabricate van der Waals nanowires with a high density of edges is proposed. This method used a linear-edge diamond tool to cut the basal plane of van der Waals film materials into a one-dimensional nanowire at the nanoscale. Experimental tests were performed to investigate the influences of the cutting thickness, film thickness, cutting direction, and material properties on the machining outcomes. The results showed that the van der Waals materials possessed low Young's moduli ranging from 24 to 238 GPa by cutting with a cutting thickness of larger than 30 nm, and the out-of-plane cutting direction led to the best machining quality and controllable preparation of van der Waals nanowires. To support the interpretation of the process outcomes, molecular dynamics simulation and transmission electron microscopy were performed to reveal the material-removal mechanism during nanocutting of van der Waals materials. From analysis of the chip-deformation process, interlayer slipping was found to dominate the plastic processing of the van der Waals materials, accompanied by intralayer bending and intralayer fracture in the out-of-plane cutting direction. By contrast, the brittle removal state occurred when cutting in the in-plane direction. This study provides important insights into the material-removal mechanism of van der Waals materials prepared by nanoscale mechanical cutting.

Characterizing vibration-assisted atomic force microscopy (AFM)-based nanomachining via perception of acoustic emission phenomena using a sensor-based real-time monitoring approach

The emerging atomic force microscope (AFM)-based nanolithography offers promising opportunities for nanopatterning applications. However, critical issues reside in the nanomachining process because the heterogeneous material properties and machine tool (AFM tip) quality variations can create significant uncertainties at this nanoscale. Therefore, in-process monitoring is essential for timely anomaly detection and real-time process characterizations. This paper reports a sensor-based monitoring approach that allows classifications of different conditions of vibration-assisted nanopatterning in real-time by automatically selecting acoustic emission spectral responses that distinguish different amounts of material removal. It opens up an avenue toward process characterizations and mechanisms discovery in vibration-assisted nanoscale manufacturing.

Damage Control of Ultra-Thin YAG Crystal in Nano-Machining Process

Yttrium aluminum garnet (YAG) crystal is one of the most widely used laser crystals because of its excellent properties. Thin disk laser with ultra-thin YAG crystal as gain medium is widely used in micromachining, imaging, military, medical, scientific research, and so on. Ultra-thin crystals with nanometer precision surface quality are easily damaged in nano-machining process. From the fracture mechanics, the critical fracture stress of ultra-thin YAG crystal was analyzed. The model of ultra-thin YAG crystal in chemical mechanical polishing (CMP) process, one of important nano-machining technologies, was established, and the effect of sticking mode and pressure on the stress magnitude and distribution of crystal were investigated. It was confirmed that the damage phenomenon in CMP process can be effectively controlled by using the edge padding sticking method. The optimized process parameters are as follows: the pressure should be less than 65 kPa, the optimized size of the edge pad crystal for YAG crystal with 10 mm × 10 mm is 10 mm × 20 mm, and the right-angle damage limit of the edge padding crystal is 3 mm. Finally, the optimization results were experimentally verified and the high-efficiency and high-quality nano-machining of ultra-thin YAG crystal with surface roughness S a 2.85 nm and the thickness 0.175 mm was achieved.

Data-driven online detection of tip wear in tip-based nanomachining using incremental adaptive support vector machine

This paper presented an online statistical pattern recognition method to detect the severe tip wear in nanomachining using an incremental adaptive support vector machine (IASVM). From the time series data of the collected nanomachining force, the two feature variables (i.e., peak-to-peak force and variance of each machining cycle) were calculated to classify the state of the nanomachining process. To enable online detection, the data was collected in the form of a moving window, sliding once every 0.2 s to add 20 sets of new feature data to update the data set each time. For each data window, the support vector machine (SVM) was restructured by modifying the regularization parameter and the Kernel parameter adaptively. The solution structure of the updated SVM was calculated to classify the incremental data and the disturbing data with the best accuracy. The number of tip failure points in each window was counted to determine the tip wear severity and the moment when the AFM tip needs to be replaced by monitoring the trend of tip failure points. From experimental data, it was shown that the average accuracy of IASVM's recognition of the tip wear conditions was 95% and the average calculation time was 0.166 s, which makes it a promising approach for online detection of tip damage in nanomachining process.

Study of the Absorption of Electromagnetic Radiation by 3D, Vacuum-Packaged, Nano-Machined CMOS Transistors for Uncooled IR Sensing.

There is an ongoing effort to fabricate miniature, low-cost, and sensitive thermal sensors for domestic and industrial uses. This paper presents a miniature thermal sensor (dubbed TMOS) that is fabricated in advanced CMOS FABs, where the micromachined CMOS-SOI transistor, implemented with a 130-nm technology node, acts as a sensing element. This study puts emphasis on the study of electromagnetic absorption via the vacuum-packaged TMOS and how to optimize it. The regular CMOS transistor is transformed to a high-performance sensor by the micro- or nano-machining process that releases it from the silicon substrate by wafer-level processing and vacuum packaging. Since the TMOS is processed in a CMOS-SOI FAB and is comprised of multiple thin layers that follow strict FAB design rules, the absorbed electromagnetic radiation cannot be modeled accurately and a simulation tool is required. This paper presents modeling and simulations based on the LUMERICAL software package of the vacuum-packaged TMOS. A very high absorption coefficient may be achieved by understanding the physics, as well as the role of each layer.

Material removal mechanism of FCC single-crystalline materials at nano-scales: Chip removal & ploughing

In machining operations, investigating the transformation between chip removal and ploughing is crucial to understand the material removal mechanism, which is also the basis for analyzing the machining process, such as calculating cutting force and predicting minimum uncut chip thickness (MUCT). In this study, an analytical model was proposed to predict the chip thickness and ploughing width for FCC crystal materials under arbitrary crystal orientations in nano-machining. The molecular dynamics (MD) simulation methods and the nano-scratching experiments were conducted to verify the theoretical model under two representative crystal orientations. The results indicate that the crystal orientation determines the transformation between chip removal and ploughing. Moreover, according to surface crystal orientation, machining direction, tool radius, and uncut chip thickness, the chip thickness and ploughing width can be calculated in nano-machining. The model can be applied to the nano-machining process of FCC crystals that achieve the plastic deformation by the (110){111} slip system, where tool size and uncut chip thickness are at the nanoscale.

Observation of a modified superficial layer on heavily loaded contacts under grease lubrication

Several industrial applications require bearings to work under slow oscillating motions and very high contact pressures (aircraft actuators, wind turbine, robotic arms, etc.). Hence, a boundary lubrication regime predominates. However, grease provides the lubrication essential to assure bearing integrity. In this study, the mechanisms involved in protecting the contact surfaces are investigated. High loaded oscillating movements have been applied on a commercial greased deep groove ball bearing. The morphology of its contact was observed using Scanning Electron Microscopy (SEM), revealing superficial transformations. Further, with an extreme surface X-Ray Photoelectron Spectroscopy (XPS) analysis, three cross-sections made by a nanomachining process (FIB) were investigated using Transmission Electron Microscopy (TEM). The analyses revealed a modified layer at the contacts generated by grease interactions.

Effect of nano-void position on surface integrity in nanomachining of single crystal copper

In this paper, molecular dynamics simulations were performed to study the effect of nano-size voids in different locations relative to the surface on nanomachining characteristics and surface integrity. Using EAM potential, MD simulations were performed with two approaches: material removal and relaxation of the work material, to find a low defect permanent configuration after the rigid tool has traversed the machined area. Results show that high hydrostatic pressure induced by tool edge diffuses atoms into the void during the machining process. Investigation of residual stress for subsurface void workpiece represents that higher compressive stress remains in the surface due to the tendency of void for spring back. Besides, in the nanomachining process, surface atoms are greatly disordered and dislocation loops glide deep into substrate atoms. After relaxation, if void pitting contains no other atoms, the machined surface is reorganised as FCC lattice similar to a pure workpiece.

Nano-tribological behavior of high-entropy alloys CrMnFeCoNi and CrFeCoNi under different conditions: A molecular dynamics study

Attributed to their superior properties over the conventional alloys, high-entropy alloys (HEAs) have attracted considerable interest. One of HEAs' attractive properties is their high wear resistance. Although considerable research on wear of HEAs can be found in the literature, understanding of the responses of HEAs to different wearing conditions needs to be enhanced in order to utilize HEAs effectively. For instance, studies on nano-wear and nano/micro-machining under different conditions are rare, which influences the extension of HEAs' applications to nanotechnological areas, e.g., nano/micro-devices and nano-manufacturing. In this study, we conducted molecular dynamics simulations to investigate responses of CrMnFeCoNi and CrFeCoNi HEAs to wear under unidirectional and bi-directional sliding conditions, respectively, for two nano-wearing processes. One process is similar to nano-machining and the other is sliding wear on nano-scale under a light normal force. Due to its higher hardness, the Mn-free HEA is more resistant to wear than the Mn-containing one. During the simulated nano-machining process, both the alloys were worn more under the bi-directional sliding condition. While the situation was reversed during the sliding wear process, in which the bi-directional sliding caused less wear. Bauschinger's effect plays a role in influencing the wear behavior of the HEAs under the different conditions. This work provides an insight into nano-tribological behaviors of the alloys under different wearing conditions, helping either mitigate wear of HEAs or improve their machining efficiency.

Surface generation mechanism of monocrystalline materials under arbitrary crystal orientations in nanoscale cutting

Crystal orientation of monocrystalline materials has a significant and complex effect on the surface generation process in nano-fabrication. Based on the slip system theory, a theoretical model is proposed to analyze the surface generation mechanism of monocrystalline materials with arbitrary crystal orientations in nano-cutting, including material pile-up, defect evolution and atomic stress distribution. To verify the correctness of the model, a series of molecular dynamics (MD) simulations of nano-cutting are performed at various crystal orientations. Simulation results show that the Miller indices of the workpiece surface and cutting direction determine the shape of the material pile-up and the propagating direction of the defects, and the tool width and uncut chip thickness determine the range of pile-up and subsurface defects. The theoretical model contributes to a better understanding of the nano-machining process of monocrystalline materials and obtaining high machined surface quality.

Vibration Assisted AFM-Based Nanomachining under Elevated Temperatures using Soft and Stiff Probes

Atomic force microscope (AFM)-based nanomanufacturing, as a low-cost and easy-to-setup technique, enables high-resolution maskless nanofabrication processes for arbitrary nanopatterns, but there are strong needs to advance the nanopatterning processes. Thermal-mechanical AFM-based nanomachining process lower the normal forces to few hundreds of nanonewtons, but it requires special thermal probes. Vibration-assisted nanomachining process increases the tip lifetime but forces are still in the range of few hundreds of nanonewtons. We have innovated a system with both vibration and heated sample to achieve nanomachining process with lower normal forces. To provide cantilever selection guidance for this novel nanomachining system and to understand the effect of cantilever stiffness and sample temperature on feature dimensions, we used both soft and stiff probes for the nanomachining processes in this paper. We fabricated nanostructures with controllable shape dimensions were fabricated on 200 nm depth polymethyl methacrylate (PMMA) films by using both soft and stiff AFM probes with a few tens of nanonewtons normal forces in this novel AFM-based nanomachining system. Besides, we analyzed the effects of different machining parameters on the lithography performance, which helps to understand the machining parameters for fabricating nanopatterns of different dimensions. We also found that other than the setpoint force, the probe category and sample heating temperature significantly affect the dimensions of fabricated nanopatterns. And there is a statistically significant interaction effect between the spring constants of probes and the sample temperatures.

Integrated Nanomanipulator With In-Process Lithography Inspection

Nanomanipulation techniques are extensively in use not only to reveal more characteristics of nano, micro and mesoscopic phenomena but also to build functional nano-devices that can bridge components between two or more scales to diversify the functions. In this paper, a novel integrated and numerically controlled instrument for nanomanipulation, imaging, in-process inspection using lithography with AFM back-to-back probes and characterization of materials at nanoscale is presented. A feature of common datum to all operations to avoid accuracy degradation between references is set. Robotic arms secure nanometre accuracy in the manipulation. The variety of operations is supported by multiple end-effector tools, e.g. force and temperature measurement. Examples are discussed. The availability of such an instrument with integrated functions appeared to be extremely helpful in addressing various fundamental problems in science and engineering such as understanding, modelling and testing nano-machining process, biomimetic design, exact construction of nano-structure arrays, and inspection of devices with complex features.

Study of tip wear for AFM-based vibration-assisted nanomachining process

Nanofabrication technologies have many applications in science and engineering. Among different nanofabrication technologies, the tip-based vibration-assisted nanomachining using an Atomic Force Microscope (AFM) provides a low-cost, easy-to-setup approach for the production of nano-scale structures. As the resolution and quality of the machined features are greatly affected by the radius and sharpness of the tip, it is critical to investigate the behavior of tip wear during the nanomachining process and to estimate the tip life. In this work, the evolvement of the tip wear was characterized and modeled to predict tip wear and tip life for the nanomachining process. Besides the direct inspection of the tip radius using a Scanning Electron Microscope (SEM), the pull-off force between the AFM tip and the sample surface was found to correlate well with the tip radius, which enabled the measurement of tip wear directly without unloading the tip from the AFM. To study the tip wear at different conditions, the tip radius was measured from the pull-off force under a wide range of machining conditions. The change rates of the tip radius were significantly affected by the machining parameters, such as setpoint force and feed rate. Moreover, during the nanomachining process, three regions were identified for the tip wear evolvement as initial tip wear region, transition region, and tip failure region. Regression models were developed to describe the tip wear at different stages, and to estimate the tip life (i.e. when the tip needs to be changed), which provide usefully information for future process planning and process optimization.

Controlled Focused Ion Beam Milling of Composite Solid State Nanopore Arrays for Molecule Sensing.

Various nanoscale fabrication techniques are elaborated to form artificial nanoporous/nanochannel membranes to be applied for biosensing: one of the most prevalent is the micro-electromechanical systems (MEMS) compatible focused ion beam (FIB) milling. This technique can be easily adopted in micro- and nanomachining process sequences to develop composite multi-pore structures, although its precision and reproducibility are key points in the case of these thick multi-layered membranes. This work is to demonstrate a comprehensive characterisation of FIB milling to improve the reliability of the fabrication of solid state nanopore arrays with precisely predetermined pore geometries for a targeted molecule type to be recognised. The statistical geometric features of the fabricated nanopores were recorded as the function of the process parameters, and the resulting geometries were analysed in detail by high resolution scanning electron microscope (SEM), transmission electron microscope (TEM) and ion scanning microscopy. Continuous function of the pore diameter evolution rate was derived from the experimental results in the case of different material structures, and compared to former dissentient estimations. The additional metal layer was deposited onto the backside of the membrane and grounded during the ion milling to prevent the electrical charging of dielectric layers. The study proved that the conformity of the pore geometry and the reliability of their fabrication could be improved significantly. The applicability of the developed nanopore arrays for molecule detection was also considered by characterising the pore diameter dependent sensitivity of the membrane impedance modulation based measurement method.

Damage evolution in vibration assisted nano impact machining by loose abrasives at elevated temperatures: A numerical study

In this research, a numerical study is conducted to investigate the effects of different machining parameters at elevated operating temperatures in a novel nanomachining process, Vibration Assisted Nano Impact machining by Loose Abrasives (VANILA). In this novel VANILA machining process, an atomic force microscope (AFM) is used as a platform and the nano abrasives slurry is injected between the vibrating AFM probe and the silicon workpiece. These nano abrasives are accelerated by vibration of the AFM probe and hit the workpiece and finally generate nano cavities on the top surface of workpiece. In this study, diamond particles are used as loose abrasives and the ductile mode machining is employed to describe the behavior of the brittle workpiece. The commercial finite element method (FEM) software package ABAQUS is employed to create numerical models for simulations. In addition to experimental validation, the FEM model is validated by comparing the numerical solutions against the analytic solutions to the impact problem between a semi-infinite stationary workpiece and a rigid particle at the impact speeds of 25 and 12.5 m/s. The percentage error is under 4.4%. This validated FEM model is then used to investigate the influence of the machining parameters (impact speed, impact angle, and friction coefficient between the nano particles and silicon workpiece) and the number of impact hits at elevated operating temperatures. It is found that the impact speed, impact angle, and friction coefficient between the silicon workpiece and nano particles have big influence on the damage volume and damage value (D) of the silicon workpiece at elevated temperatures. The research results show that by increasing the level of operating temperature, the machinability of silicon in the VANILA process can be improved substantially.