A learning approach of wafer temperature control in a rapid thermalprocessing system

This paper presents a learning approach for wafer temperature control in a rapid thermal processing system (RTP). RTP is very important for semiconductor processing system and requires an accurate trajectory following. Numerous studies have addressed this problem and most research on this problem requires exact knowledge of the system dynamics. The various approaches do not guarantee the desired performance in practical applications when there exist some modeling errors between the model and the actual system. In this paper, iterative learning control scheme is applied to RTP without exact information on the dynamics. The learning gain of the iterative learning law is estimated by neural networks instead of a mathematical model. In addition, the control information obtained by the iterative learning controller (ILC) is accumulated in the feedforward neuro controller (FNC) for generalization to various reference profiles. Through numerical simulations, it is demonstrated that the proposed method can achieve an accurate output tracking even without an exact RTP model. The output errors decrease rapidly through iterations when using the learning gain estimated and the FNC yields a reduced initial error, and so requires small iterations     

Stator-flux-oriented control of induction motor considering ironloss

Research to consider the influences of iron loss has been made in the vector control of an induction motor. However, little work has been done in the area of a stator-flux-oriented control system of an induction motor. This paper investigates the effects of iron loss in the direct stator-flux-oriented control system of an induction motor, and proposes a control algorithm considering iron loss. The iron loss is modeled by equivalent iron loss resistance in parallel to the magnetizing inductance. Torque control capability is much improved and the speed estimation error for a speed-sensorless drive is reduced by the proposed control algorithm. The effectiveness of the proposed method is verified by simulation and experimental results     

3D Printable One-Part Carbon Nanotube-Elastomer Ink for Health Monitoring Applications

3D printing of conductive elastomers is a promising route to personalized health monitoring applications due to its flexibility and biocompatibility. Here, a one-part, highly conductive, flexible, stretchable, 3D printable carbon nanotube (CNT)-silicone composite is developed and thoroughly characterized. The one-part nature of the inks: i) enables printing without prior mixing and cures under ambient conditions; ii) allows direct dispensing at ≈100 µm resolution printability on nonpolar and polar substrates; iii) forms both self-supporting and high-aspect-ratio structures, key aspects in additive biomanufacturing that eliminate the need for sacrificial layers; and iv) lends efficient, reproducible, and highly sensitive responses to various tensile and compressive stimuli. The high electrical and thermal conductivity of the CNT-silicone composite is further extended to facilitate use as a flexible and stretchable heating element, with applications in body temperature regulation, water distillation, and dual temperature sensing and Joule heating. Overall, the facile fabrication of this composite points to excellent synergy with direct ink writing and can be used to prepare patient-specific wearable electronics for motion detection and cardiac and respiratory monitoring devices and toward advanced personal health tracking and bionic skin applications.     

Modeling and Simulation of New Encoding Schemes for High‐Speed UHF RFID Communication

In this paper, we present novel high‐speed transmission schemes for high‐speed ultra‐high frequency (UHF) radio‐frequency identification communication. For high‐speed communication, tags communicate with a reader using a high‐speed Miller (HS‐Miller) encoding and multiple antennas, and a reader communicates with tags using extended pulse‐interval encoding (E‐PIE). E‐PIE can provide up to a two‐fold faster data rate than conventional pulse‐interval encoding. Using HS‐Miller encoding and orthogonal multiplexing techniques, tags can achieve a two‐ to three‐fold faster data rate than Miller encoding without degrading the demodulation performance at a reader. To verify the proposed transmission scheme, the MATLAB/Simulink model for high‐speed backscatter based on an HS‐Miller modulated subcarrier has been designed and simulated. The simulation results show that the proposed transmission scheme can achieve more than a 3 dB higher BER performance in comparison to a Miller modulated subcarrier.     

Unveiled Ferroelectricity in Well-Known Non-Ferroelectric Materials and Their Semiconductor Applications

Ferroelectric materials are considered ideal for emerging memory devices owing to their characteristic remanent polarization, which can be switched by applying a sufficient electric field. However, even several decades after the initial conceptualization of ferroelectric memory, its applications are limited to a niche market. The slow advancement of ferroelectric memories can be attributed to several extant issues, such as the absence of ferroelectric materials with complementary metal–oxide–semiconductor (CMOS) compatibility and scalability. Since the 2010s, ferroelectric memories have attracted increasing interest because of newly discovered ferroelectricity in well-established CMOS-compatible materials, which are previously known to be non-ferroelectric, such as fluorite-structured (Hf,Zr)O₂ and wurtzite-structured (Al,Sc)N. With advancing material fabrication technologies, for example, accurate chemical doping and atomic-level thickness control, a metastable polar phase, and switchable polarization with a reasonable electric field can be induced in (Hf,Zr)O₂ and (Al,Sc)N. Nonetheless, various issues still exist that urgently require solutions to facilitate the use of the ferroelectric (Hf,Zr)O₂ and (Al,Sc)N in emerging memory devices. Thus, ferroelectric (Hf,Zr)O₂ and (Al,Sc)N are comprehensively reviewed herein, including their fundamental science and practical applications.     

Self‐Healing Reduced Graphene Oxide Films by Supersonic Kinetic Spraying

The industrial scale application of graphene and other functional materials in the field of electronics has been limited by inherent defects, and the lack of simple deposition methods. A simple spray deposition method is developed that uses a supersonic air jet for a commercially available reduced graphene oxide (r‐GO) suspension. The r‐GO flakes are used as received, which are pre‐annealed and pre‐hydrazine‐treated, and do not undergo any post‐treatment. A part of the considerable kinetic energy of the r‐GO flakes entrained by the supersonic jet is used in stretching the flakes upon impact with the substrate. The resulting “frozen elastic strains” heal the defects (topological defects, namely Stone‐Wales defect and C₂ vacancies) in the r‐GO flakes, which is reflected in the reduced ratio of the intensities of the D and G bands in the deposited film. The defects can also be regenerated by annealing.     

Personalized Healthcare System for Chronic Disease Care in Cloud Environment

The rapid increase in the number of patients with chronic diseases is an important public healthcare issue in many countries, which accelerates many studies on a healthcare system that can, whenever and wherever, extract and process patient data. A patient with a chronic disease conducts self‐management in an out‐of‐hospital environment, particularly in an at‐home environment, so it is important to provide integrated and personalized healthcare services for effective care. To help provide effective care for chronic disease patients, we propose a service flow and a new cloud‐based personalized healthcare system architecture supporting both at‐home and at‐hospital environments. The system considers the different characteristics of at‐hospital and at‐home environments, and it provides various chronic disease care services. A prototype implementation and a predicted cost model are provided to show the effectiveness of the system. The proposed personalized healthcare system can support cost‐effective disease care in an at‐hospital environment and personalized self‐management of chronic disease in an at‐home environment.     

The muscle activation method: an approach to impedance control of brain-machine interfaces through a musculoskeletal model of the arm

Current demonstrations of brain-machine interfaces (BMIs) have shown the potential for controlling neuroprostheses under pure motion control. For interaction with objects, however, pure motion control lacks the information required for versatile manipulation. This paper investigates the idea of applying impedance control in a BMI system. An extraction algorithm incorporating a musculoskeletal arm model was developed for this purpose. The new algorithm, called the muscle activation method (MAM), was tested on cortical recordings from a behaving monkey. The MAM was found to predict motion parameters with as much accuracy as a linear filter. Furthermore, it successfully predicted limb interactions with novel force fields, which is a new and significant capability lacking in other algorithms.     

High Efficiency Perovskite Solar Cells Exceeding 22% via a Photo-Assisted Two-Step Sequential Deposition

One of the most effective methods to achieve high-performance perovskite solar cells (PSCs) is to employ additives as crystallization agents or to passivate defects. Tri-iodide ion has been known as an efficient additive to improve the crystallinity, grain size, and morphology of perovskite films. However, the generation and control of this tri-iodide ion are challenging. Herein, an efficient method to produce tri-iodide ion in a precursor solution using a photoassisted process for application in PSCs is developed. Results suggest that the tri-iodide ion can be synthesized rapidly when formamidinium iodide (FAI) dissolved isopropyl alcohol (IPA) solution is exposed to LED light. Specifically, the photoassisted FAI–IPA solution facilitates the formation of fine perovskite films with high crystallinity, large grain size, and low trap density, thereby improving the device performance up to 22%. This study demonstrates that the photoassisted process in FAI dissolved IPA solution can be an alternative strategy to fabricate highly efficient PSCs with significantly reduced processing times.     

Unraveling the Significance of Li+/e−/O2 Phase Boundaries with a 3D-Patterned Cu Electrode for Li–O2 Batteries

The reaction kinetics at a triple-phase boundary (TPB) involving Li⁺, e⁻, and O₂ dominate their electrochemical performances in Li–O₂ batteries. Early studies on catalytic activities at Li⁺/e⁻/O₂ interfaces have enabled great progress in energy efficiency; however, localized TPBs within the cathode hamper innovations in battery performance toward commercialization. Here, the effects of homogenized TPBs on the reaction kinetics in air cathodes with structurally designed pore networks in terms of pore size, interconnectivity, and orderliness are explored. The diffusion fluxes of reactants are visualized by modeling, and the simulated map reveals evenly distributed reaction areas within the periodic open structure. The 3D air cathode provides highly active, homogeneous TPBs over a real electrode scale, thus simultaneously achieving large discharge capacity, unprecedented energy efficiency, and long cyclability via mechanical/electrochemical stress relaxation. Homogeneous TPBs by cathode structural engineering provide a new strategy for improving the reaction kinetics beyond controlling the intrinsic properties of the materials.