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In this paper, a fiber-based chromatic dispersion probe for simultaneous measurement of X-axis and Z-axis displacements with nanometric resolutions by using the full width at half maxima (FWHM) of the detected spectral signal has been proposed and demonstrated. For X-axis, FWHM is employed for indicating the X-axis displacement based on the fact that the FWHM remains almost constant with the varying Z-axis displacement of the fiber detector and shows a linear relationship with the X-axis displacement within a specific Z-axis displacement range. For the Z-axis, the linear relationship between the centroid wavelength λ of the detected spectral signal and the Z-axis displacement is employed for indicating the Z-axis displacement based on the fact that the sensitivity (slope of the λ-Z curve) is also linear with X-axis displacement within a certain X-axis displacement range. Theoretical and experimental investigations have verified the feasibility of the proposed chromatic dispersion probe, which yields X- and Z-axis measurement ranges of 2.3 μm and 15 μm and X- and Z-axis measurement resolutions of better than 25 nm and 50 nm, respectively. Experiments were further performed to evaluate the basic performance of the prototype probe and the maximum measurement errors were less than 10 nm and 60 nm for X- and Z-axis displacements, respectively.

This paper presents a fiber-based chromatic dispersion probe for the simultaneous measurement of dual-axis absolute and relative displacement with nanometric resolutions. The proposed chromatic dispersion probe is based on optical dispersion. In the probe, the employed light beam is split into two sub-beams, and then the two sub-beams are made to pass through two optical paths with different optical settings where two identical single-mode fiber detectors are located at different defocused positions of the respective dispersive lenses. In this way, two spectral signals can be obtained to indicate the absolute displacement of each of the dual-axes. A signal processing algorithm is proposed to generate a normalized output wavelength that indicates the relative displacement of the dual-axis. With the proposed chromatic dispersion probe, the absolute and relative displacement measurements of the dual-axis can be realized simultaneously. Theoretical and experimental investigations reveal that the developed chromatic dispersion probe realizes an absolute measurement range and a measurement resolution of approximately 180 μm and 50 nm, respectively, for each axis. Moreover, a relative displacement measurement range and a measurement resolution of about 240 μm and 100 nm, respectively, are achieved for the dual-axis.

Heat shuttling phenomenon is characterized by the presence of a non-zero heat flow between two bodies without net thermal bias on average. It was initially predicted in the context of nonlinear heat conduction within atomic lattices coupled to two time-oscillating thermostats. Recent theoretical works revealed an analog of this effect for heat exchanges mediated by thermal photons between two solids having a temperature dependent emissivity. In this paper, we present the experimental proof of this effect using systems made with composite materials based on phase change materials. By periodically modulating the temperature of one of two solids we report that the system akin to heat pumping with a controllable heat flow direction. Additionally, we demonstrate the effectiveness of a simultaneous modulation of two temperatures to control both the strength and direction of heat shuttling by exploiting the phase delay between these temperatures. These results show that this effect is promising for an active thermal management of solid-state technology, to cool down solids, to insulate them from their background or to amplify heat exchanges. Authors demonstrate a net heat flux between two objects at averagely zero temperature gradient, exploring the nonlinear thermal emissivity based on phase change materials.

A noise-resistant linearization model that reveals the true nonlinearity of the sensor is essential for retrieving accurate physical displacement from the signals captured by sensing electronics. In this paper, we propose a novel information-driven smoothing spline linearization method, which innovatively integrates one new and three standard information criterions into a smoothing spline for the high-precision displacement sensors’ linearization. Using theoretical analysis and Monte Carlo simulation, the proposed linearization method is demonstrated to outperform traditional polynomial and spline linearization methods for high-precision displacement sensors with a low noise to range ratio in the 10−5 level. Validation experiments were carried out on two different types of displacement sensors to benchmark the performance of the proposed method compared to the polynomial models and the the non-smoothing cubic spline. The results show that the proposed method with the new modified Akaike Information Criterion stands out compared to the other linearization methods and can improve the residual nonlinearity by over 50% compared to the standard polynomial model. After being linearized via the proposed method, the residual nonlinearities reach as low as ±0.0311% F.S. (Full Scale of Range), for the 1.5 mm range chromatic confocal displacement sensor, and ±0.0047% F.S., for the 100 mm range laser triangulation displacement sensor.

Atomic Force Microscopy (AFM) is a widely employed tool for micro- and nanoscale topographic imaging. However, conventional AFM scanning struggles to reconstruct complex 3D micro- and nanostructures precisely due to limitations such as incomplete sample topography capturing and tip-sample convolution artifacts. Here, we propose a multi-view neural-network-based framework with AFM, named MVN-AFM, which accurately reconstructs surface models of intricate micro- and nanostructures. Unlike previous 3D-AFM approaches, MVN-AFM does not depend on any specially shaped probes or costly modifications to the AFM system. To achieve this, MVN-AFM employs an iterative method to align multi-view data and eliminate AFM artifacts simultaneously. Furthermore, we apply the neural implicit surface reconstruction technique in nanotechnology and achieve improved results. Additional extensive experiments show that MVN-AFM effectively eliminates artifacts present in raw AFM images and reconstructs various micro- and nanostructures, including complex geometrical microstructures printed via two-photon lithography and nanoparticles such as poly(methyl methacrylate) (PMMA) nanospheres and zeolitic imidazolate framework-67 (ZIF-67) nanocrystals. This work presents a cost-effective tool for micro- and nanoscale 3D analysis. Shuo Chen and colleagues present a cost-effective neural network-based method to deal with tip-sample convolution artifacts in atomic force microscopy. Their method merges multiview atomic force microscopy images into precise 3D models of complex micro- and nanostructures.

In the elliptical vibration cutting process, the elliptical locus is considered to be a vital factor that affects cutting performance. Besides the cutting speed and vibration amplitudes, the phase shift (i.e., the phase difference between the two-directional output harmonic vibrations forming the elliptical locus) is an intrinsic parameter that determines the shape and inclination of the elliptical locus with respect to the cutting direction. In this paper, a numerical recursive search method is proposed to investigate the effect of phase shift in elliptical vibration cutting. It has been shown that the critical speed ratio for considerably improving the cutting performance has a sinusoidal correlation with the phase shift. For elliptical loci with arbitrary shapes, the developed model theoretically predicts the maximal influential thickness of cut, surface roughness, and the tool-workpiece contact ratio as a function of phase shifts. Experiments were conducted to validate the developed model through the evaluation of the machined surface profile, roughness, and dynamic cutting force. The obtained results offer a method to determine the proper machining variables in cutting hard and brittle materials during the elliptical vibration cutting process with an arbitrary locus.

Accurate and non-destructive technology for detection of subsurface defect has become a key requirement with the emergence of various ultra-precision machining technologies and the application of ultra-precision components. The combination of acoustic technique for sub-surface detection and atomic force microscopy (AFM) for measurement with high resolution is a potential method for studying the subsurface structure of workpiece. For this purpose, contact-resonance AFM (CR-AFM) is a typical technique. In this paper, a CR-AFM system with a different principle from commercially available instruments is set up and used for the detection of sub-surface Si samples with grating structures and covered by different thickness of highly oriented pyrolytic graphite (HOPG). The influence of subsurface burial depth on the detection capability is studied by simulations and experiments. The thickest HOPG film allowing for sub-surface measurement by the proposed method is verified to be about 30 μm, which is much larger than the feature size of the subsurface microstructure. The manuscript introduces the difference between this subsurface topography measurement principle and the commercially available AFM measurement principle, and analyzes its advantages and disadvantages. The experimental results demonstrates that the technique has the capability to reveal sub-surface microstructures with relatively large buried depth and is potential for engineering application in ultra-precision technologies.

Carbide tools are widely used to cut high-strength and corrosion-resistant aluminum alloys. However, aluminum chips tend to adhere to the cutting edge and rake face, influencing machined surface quality and even leading to tool failure. This paper proposes an innovative application of the ultrasonic elliptical vibration texturing (UEVT) process with properly selected elliptical locus for generating superior microgrooves on the carbide tool’s rake face using polycrystalline diamond (PCD) tools, in order to create a micropool-like lubrication effect at the chip-tool interface. Two microtextured carbide tools with a channel pitch of 400 and 200 μm and a depth of 12 μm were generated by UEVT. An experimental comparison between nontextured and UEVT tools in turning tubular aluminum alloy workpieces has demonstrated that microtextured tools with a pitch of 200 μm show a clear reduction in chip adhesion. The corresponding cutting performance is also improved due to the anti-adhesive property at the chip-tool interface. This work has demonstrated that ultrasonic elliptical vibration texturing has the potential for the mass production of microtextured tools for adhesion and friction reduction with high efficiency and accuracy.

This paper presents a novel method for inner profile measurement and geometric parameter evaluation, such as the radius of the bottom, steepness and straightness of the steep sidewall of a high aspect ratio aspheric workpiece, by utilizing a two-probe measuring system, which includes a lateral displacement gauge for the inner steep sidewall profile measurement and an axial displacement gauge for the inner deep underside profile measurement. To qualify the measurement accuracy, the systematic errors associated with the measurement procedure, including the miscalibration, misalignment and the roundness error of the gauge probes, as well as the slide motion error of the four-axis motion platform, are all evaluated and separated from the measurement results. A point cloud registration algorithm is employed to stitch the evaluated inner sidewall profile and the inner underside profile to form an entire inner profile of the workpiece. To verify the performance of the newly proposed method, the inner profile of a high aspect ratio aspheric workpiece, which has a tapered cone shape with a maximum inner radius of 40 mm, a maximum inner depth of 140 mm and a steep sidewall angle approaching 85°, is measured in experiments. The measurement result is compared with that of a coordinate measuring machine (CMM), and the comparison verifies the feasibility of the proposed measurement system.

This paper presents a self-evaluation method for sub-micrometer accuracy measurement of the cutting edge contour of a micro diamond tool with a force sensor-integrated fast tool servo (FS-FTS) on an ultra-precision lathe without using any accurate reference artifacts and additional surface form measuring instruments. At first, a series of grooves is cut side by side along the Z -direction over the outer surface of a cylindrical artifact mounted on the lathe spindle by the micro tool of the FS-FTS, which is mounted on the X -directional cross-slide ( X -slide) of the lathe, to form a number of sharp line structures. The FS-FTS is then switched to a force feedback control mode for the cutting edge of the micro tool to scan across the line structures as a measuring stylus by moving the artifact with the Z -directional carriage slide ( Z -slide) of the spindle. During the scanning, the contact force between the micro tool and the line structures is maintained constant by controlling the X -directional displacement of the cutting tool with the FS-FTS so that the tool cutting edge contour can be obtained from the tool scan trace profile provided by the linear encoder of the Z -slide and the displacement sensor of the FS-FTS. Measurement experiments of a micro tool with a nominal nose radius of 120 μm are carried out to demonstrate the feasibility of the proposed method.