Ultraprecision Real-Time Displacements Calculation Algorithm for the Grating Interferometer System.

Grating interferometry is an environmentally stable displacement measurement technique that has significant potential for identifying the position of the wafer stage. A fast and precise algorithm is required for real-time calculation of six degrees-of-freedom (DOF) displacement using phase shifts of interference signals. Based on affine transformation, we analyze diffraction spot displacement and changes in the internal and external effective optical paths of the grating interferometer caused by the displacement of the wafer stage (DOWS); then, we establish a phase shift-DOWS model. To solve the DOWS in real time, we present a polynomial approximation algorithm that uses the frequency domain characteristics of nonlinearities to achieve model reduction. The presented algorithm is verified by experiment and ZEMAX simulation.

Translational displacement computational algorithm of the grating interferometer without geometric error for the wafer stage in a photolithography scanner.

The translational displacement computational algorithm base on a novel phase-shift model is proposed eliminating the geometric error of the grating interferometer for precision positioning of a multi-degree-of-freedom motion stage. Firstly, the mechanism of the geometric error of the grating interferometer is analyzed, and the novel phase-shift model of the grating interferometer is constructed based on rigid body kinematics and affine geometry transformation. High accuracy of the model is demonstrated by ZEMAX simulation. Then, according to Taylor series expansion, the phase-shift model is simplified by polynomial regression to solve the problems of a large amount of computational effort and inability to derive the translational displacement computational algorithm. The availability and accuracy of the translational displacement computational algorithm are verified by ZEMAX simulation and experiment.

Sinusoidal phase-modulating interferometer with ellipse fitting and a correction method.

In a sinusoidal phase-modulating interferometer, sinusoidal modulation of the phase of the laser or the reference wave is necessary. However, modulation of the phase also involves an intensity modulation of the light, which leads to a measurement error if conventional signal processing is used. In addition, the error of modulation depth and the phase delay of demodulation also increase the measurement error. A novel signal processing, with ellipse fitting and a correction method, is proposed. Numerical simulation results and experimental results prove that the novel signal processing can compensate for the measurement error caused by the intensity modulation, the error of modulation depth, and the phase delay of demodulation.

Sinusoidal phase-modulating laser diode interferometer for wide range displacement measurement.

A sinusoidal phase-modulating laser diode interferometer for wide range displacement measurement is proposed. To realize wide range displacement measurement, a signal processing method utilizing a look-up table to estimate the dynamic value of the effective sinusoidal phase-modulating depth is detailed, and the error caused by the residual amplitude modulation and the effective sinusoidal phase-modulating depth in wide range displacement measurement can be eliminated. It is discussed that the extended measurement range depends on the monotone intervals of several specific functions. The simulation and experimental results prove that the sinusoidal phase-modulating laser diode interferometer with the proposed method could realize centimeter level displacement measurement range.

Safe Reinforcement Learning with Dual Robustness.

Reinforcement learning (RL) agents are vulnerable to adversarial disturbances, which can deteriorate task performance or break down safety specifications. Existing methods either address safety requirements under the assumption of no adversary (e.g., safe RL) or only focus on robustness against performance adversaries (e.g., robust RL). Learning one policy that is both safe and robust under any adversaries remains a challenging open problem. The difficulty is how to tackle two intertwined aspects in the worst cases: feasibility and optimality. The optimality is only valid inside a feasible region (i.e., robust invariant set), while the identification of maximal feasible region must rely on how to learn the optimal policy. To address this issue, we propose a systematic framework to unify safe RL and robust RL, including the problem formulation, iteration scheme, convergence analysis and practical algorithm design. The unification is built upon constrained two-player zero-sum Markov games, in which the objective for protagonist is twofold. For states inside the maximal robust invariant set, the goal is to pursue rewards under the condition of guaranteed safety; for states outside the maximal robust invariant set, the goal is to reduce the extent of constraint violation. A dual policy iteration scheme is proposed, which simultaneously optimizes a task policy and a safety policy. We prove that the iteration scheme converges to the optimal task policy which maximizes the twofold objective in the worst cases, and the optimal safety policy which stays as far away from the safety boundary. The convergence of safety policy is established by exploiting the monotone contraction property of safety self-consistency operators, and that of task policy depends on the transformation of safety constraints into state-dependent action spaces. By adding two adversarial networks (one is for safety guarantee and the other is for task performance), we propose a practical deep RL algorithm for constrained zero-sum Markov games, called dually robust actor-critic (DRAC). The evaluations with safety-critical benchmarks demonstrate that DRAC achieves high performance and persistent safety under all scenarios (no adversary, safety adversary, performance adversary), outperforming all baselines by a large margin.

Sniffing Like a Wine Taster: Multiple Overlapping Sniffs (MOSS) Strategy Enhances Electronic Nose Odor Recognition Capability.

As highly promising devices for odor recognition, current electronic noses are still not comparable to human olfaction due to the significant disparity in the number of gas sensors versus human olfactory receptors. Inspired by the sniffing skills of wine tasters to achieve better odor perception, a multiple overlapping sniffs (MOSS) strategy is proposed in this study. The MOSS strategy involves rapid and continuous inhalation of odorants to stimulate the sensor array to generate feature-rich temporal signals. Computational fluid dynamics simulations are performed to reveal the mechanism of complex dynamic flows affecting transient responses. The proposed strategy shows over 95% accuracy in the recognition experiments of three gaseous alkanes and six liquors. Results demonstrate that the MOSS strategy can accurately and easily recognize odors with a limited sensor number. The proposed strategy has potential applications in various odor recognition scenarios, such as medical diagnosis, food quality assessment, and environmental surveillance.

In vivo bioprinting: Broadening the therapeutic horizon for tissue injuries.

Tissue injury is a collective term for various disorders associated with organs and tissues induced by extrinsic or intrinsic factors, which significantly concerns human health. In vivo bioprinting, an emerging tissue engineering approach, allows for the direct deposition of bioink into the defect sites inside the patient's body, effectively addressing the challenges associated with the fabrication and implantation of irregularly shaped scaffolds and enabling the rapid on-site management of tissue injuries. This strategy complements operative therapy as well as pharmacotherapy, and broadens the therapeutic horizon for tissue injuries. The implementation of in vivo bioprinting requires targeted investigations in printing modalities, bioinks, and devices to accommodate the unique intracorporal microenvironment, as well as effective integrations with intraoperative procedures to facilitate its clinical application. In this review, we summarize the developments of in vivo bioprinting from three perspectives: modalities and bioinks, devices, and clinical integrations, and further discuss the current challenges and potential improvements in the future.

Cascaded iterative learning motion control of precision maglev planar motor with experimental investigation.

Cascaded iterative learning control (CILC) is explored for a magnetically levitated (maglev) planar motor to achieve excellent tracking motion performance in this paper. The CILC control method is based on traditional iterative learning control (ILC) with deeper iterations. CILC solves the difficulty of ILC in constructing perfect learning filter and low-pass filter to obtain excellent accuracy. Specifically, in CILC, the traditional ILC strategy is implemented several times by the operation of feedforward signal registering and clearing in a cascaded structure, which makes the motion error reach an accuracy level superior to traditional ILC even though the filters are imperfect. The fundamental principle, convergence and stability of CILC strategy are explicitly presented and analyzed. Through the structure of CILC, the repetitive component of the convergence error can be completely eliminated in theory, while the non-repetitive component is accumulated but the sum is bounded. Simulation investigation and comparative experimental investigation on maglev planar motor are both conducted. The results consistently show that the CILC strategy is not only superior to PID and model-based feedforward control, but also obviously outperforms traditional ILC. The CILC investigations on maglev planar motor also provide a clue that CILC has appreciable application prospect for precision/ultra-precision systems requiring extreme motion accuracy.

Printing Three-Dimensional Refractory Metal Patterns in Ambient Air: Toward High Temperature Sensors.

Refractory metals offer exceptional benefits for high temperature electronics including high-temperature resistance, corrosion resistance and excellent mechanical strength, while their high melting temperature and poor processibility poses challenges to manufacturing. Here this work reports a direct ink writing and tar-mediated laser sintering (DIW-TMLS) technique to fabricate three-dimensional (3D) refractory metal devices for high temperature applications. Metallic inks with high viscosity and enhanced light absorbance are designed by utilizing coal tar as binder. The printed patterns are sintered into oxidation-free porous metallic structures using a low-power (<10 W) laser in ambient environment, and 3D freestanding architectures can be rapidly fabricated by one step. Several applications are presented, including a fractal pattern-based strain gauge, an electrically small antenna (ESA) patterned on a hemisphere, and a wireless temperature sensor that can work up to 350 °C and withstand burning flames. The DIW-TMLS technique paves a viable route for rapid patterning of various metal materials with wide applicability, high flexibility, and 3D conformability, expanding the possibilities of harsh environment sensors.

Real-time time-optimal continuous multi-axis trajectory planning using the trajectory index coordination method.

Real-time time-optimal trajectory planning exists in a wide range of applications such as computer numerical control (CNC) manufacturing, robotics and autonomous vehicles. Generally, the methods to generate time-optimal trajectory can be categorized as non-real-time methods and real-time methods. Non-real-time methods such as direct optimization method tend to generate time-optimal trajectory through nonlinear or linear programming while it is computationally prohibitive for high frequency real-time applications. Current real-time methods are computationally efficient but either deal with the sparse waypoint trajectories or sacrifice the time optimality a lot. This paper innovatively proposed a time-optimal switching trajectory index coordination (TOS-TIC) framework to solve the real-time time-optimal planning problem for continuous multi-axis trajectories. The proposed method is able to generate time-optimal trajectory for continuous geometric paths while considering the axial velocity and acceleration constraints. The time-optimality of the trajectory planned by TOS-TIC is nearly the same as the offline planned optimal results. Meanwhile, the proposed method is computationally efficient for even 5kHz real-time applications. The main idea of TOS-TIC is coordinating several one-axis time-optimal switching controls to generate a modified control that decreases the state deviation from the desired trajectory. Several comparative experiments are carried out on an industrial biaxial linear motor stage. And the experimental results consistently verify that the proposed TOS-TIC real-time planner generates faster trajectory compared with the real-time lookahead method. In addition, the trajectory running time and final tracking error of the proposed method are nearly the same as the offline direct optimization method.

Laser Direct-Write Sensors on Carbon-Fiber-Reinforced Poly-Ether-Ether-Ketone for Smart Orthopedic Implants.

Mechanically close-to-bone carbon-fiber-reinforced poly-ether-ether-ketone (CFR-PEEK)-based orthopedic implants are rising to compete with metal implants, due to their X-ray transparency, superior biocompatibility, and body-environment stability. While real-time strain assessment of implants is crucial for the postsurgery study of fracture union and failure of prostheses, integrating precise and durable sensors on orthopedic implants remains a great challenge. Herein, a laser direct-write technique is presented to pattern conductive features (minimum sheet resistance <1.7 Ω sq-1 ) on CRF-PEEK-based parts, which can act as strain sensors. The as-fabricated sensors exhibit excellent linearity (R2  = 0.997) over the working range (0-2.5% strain). While rigid silicon- or metal-based sensor chips have to be packaged onto flat surfaces, all-carbon-based sensors can be written on the complex curved surfaces of CFR-PEEK joints using a portable laser mounted on a six-axis robotic manipulator. A wireless transmission prototype is also demonstrated using a Bluetooth module. Such results will allow a wider space to design sensors (and arrays) for detailed loading progressing monitoring and personalized diagnostic applications.

In Situ H2O Meter by Visualization in Hydrogels.

The solvent content strongly affects the viscoelastic properties and network structure of hydrogels. Because of the gels' structural susceptibility and autofluorescence background, there is still no visual method to evaluate the water content in micropores. Herein, a colorimetric molecular probe (DHBYD) was synthesized for in situ visualization of water content in the micropores of hydrogels. The rapid and reversible colorimetric responses of DHBYD to solvents were obtained, which resulted a full linearity range (0 to 100%) for detecting water content in real time. Demonstrated by theoretical calculations, the sensing was attributed to changes in intramolecular charge transfer via deprotonation of phenol group. A cubic polynomial, on correlation of RGB values with water content, was established for real detection of water content in hydrogels. It reveals a new pathway for simple, in situ, and full-range evaluation of solvent content in micropores of hydrogels without any complicated procedures or expensive instruments. This would achieve fast and in situ monitoring of hydrogels to improve gel properties for better applications. It can be extended to evaluate the solvent content in other fields such as synthesis and industrial applications.

Modeling and analysis of a negative stiffness magnetic suspension vibration isolator with experimental investigations.

This paper presents a negative stiffness magnetic suspension vibration isolator (NSMSVI) using magnetic spring and rubber ligaments. The positive stiffness is obtained by repulsive magnetic spring while the negative stiffness is gained by rubber ligaments. In order to study the vibration isolation performance of the NSMSVI, an analytical expression of the vertical stretch force of the rubber ligament is constructed. Experiments are carried out, which demonstrates that the analytical expression is effective. Then an analytical expression of the vertical stiffness of the rubber ligament is deduced by the derivative of the stretch force of the rubber ligament with respect to the displacement of the inner magnetic ring. Furthermore, the parametric study of the magnetic spring and rubber ligament are carried out. As a case study, the size dimensions of the magnetic spring and rubber ligament are determined. Finally, an NSMSVI table was built to verify the vibration isolation performance of the NSMSVI. The transmissibility curves of the NSMSVI are subsequently calculated and tested by instruments. The experimental results reveal that there is a good consistency between the measured transmissibility and the calculated ones, which proves that the proposed NSMSVI is effective and can realize low-frequency vibration isolation.