Jin-Woo Choi

Maintaining upright stability in tandem-wheel robotic systems is particularly challenging during stationary and low-speed operation, where steering-induced stabilization and gyroscopic effects become limited. Also, alternative mechanisms such as reaction wheels, control-moment gyroscopes, and movable balancing masses can increase mass and mechanical complexity. To address these limitations, this paper proposes an elevated, vectored differential-propeller-thrust approach for active roll stabilization and presents the design, prototyping, and experimental validation of a self-balancing tandem-wheel mobile robotic system employing the proposed principle. Two laterally oriented ducted propeller fans are mounted above the vehicle’s center of mass to increase the available roll-moment arm, while thrust vectoring provides an additional contribution to the corrective rolling moment. The system integrates a perpendicular drivetrain, front-wheel steering mechanism, inertial sensing, wireless communication, and a real-time proportional–integral–derivative (PID) controller utilizing direct gyroscope roll-rate feedback. The system is characterized through geometry-based roll-moment and dynamic analyses, including open-loop pole analysis and a Routh–Hurwitz assessment of the PID-controlled roll dynamics. A Python-based supervisory interface provides wireless command generation, real-time telemetry visualization, and data logging. Experimental evaluation includes static stability, dynamic roll-reference tracking, and variable-speed driving-performance tests. The analytical results identify an open-loop unstable upright equilibrium and reveal the mechanical and actuator parameter conditions for local asymptotic stability under PID-controlled differential thrust. The results of the experiments demonstrate effective upright stabilization, accurate roll-reference tracking, smooth differential-thrust allocation, and reliable attitude regulation during stationary and low-speed operation. The principal contribution is the development and experimental demonstration of an elevated, vectored differential-thrust stabilization architecture for active roll control of a slender tandem-wheel robotic platform, providing a foundation for further development of dynamically stabilized single-track robotic systems.

In this study, a low-profile and saw-tooth-shaped slot antenna sensor is proposed for liquid characterization, demonstrating sensitivity to dielectric variations in glucose, saline, and alcohol-based solutions. The antenna consists of a single-layer Rogers 4003C substrate with a rectangular slot integrated with multiple saw-tooth perturbations on the top side and a modified microstrip feedline with a quarter-wavelength transformer on the bottom side. The saw-tooth geometry enhances electric field concentration within the slot region, thereby improving sensitivity to variations in dielectric properties. When liquids with different dielectric constants are deposited on the saw-tooth region of the antenna, measurable resonance frequency shifts occur, enabling material detection. The sensor demonstrated sensitivity in detecting methanol, ethanol, isopropyl alcohol, saline, and glucose solutions. This configuration with dimensions 48 × 48 × 0.508 mm3 (0.78 λo × 0.78 λo × 0.0083 λo at 4.9 GHz, λo represents the free-space wavelength evaluated at the center frequency of the antenna's impedance bandwidth) feasibility for chemical characterization and biomedical sensing applications using an antenna structure.

This paper presents the design of a batteryless near-field communication (NFC) multi-sensor node with an integrated adaptive power-management system for sensing applications. The work focuses on harvesting energy from a 13.56 MHz NFC field to power an ultra-low power sensing platform. The design consists of the TI RF430FRL152H, an integrated NFC transponder with an embedded MSP430 microcontroller core and ferroelectric random-access memory (FRAM) non-volatile memory. The system combines an ISO/IEC 15693 NFC front end, a tuned loop antenna for optimized power harvesting, and multiple analog and digital sensor interfaces, and a firmware architecture for intermittent harvested energy operation. The aforementioned design performs on-demand data acquisition, logs measurements in the FRAM, and communicates the measured results through an ISO15693 compliant NFC link while powered entirely by the reader’s radio-frequency (RF) field. Since NFC provides only limited harvested power, efficient energy management is critical. The proposed scheme continuously monitors the storage capacitor voltage and activates each sensor only when sufficient energy is available. After every measurement, the system reassesses the stored charge before triggering the next acquisition, ensuring stable multi-sensor operation. A BMP390 temperature and pressure sensor and the on-chip temperature sensor demonstrate the platform’s capability. Experimental results show that the system harvests 1.064 mW (1.85 V, 560 µA), achieves a wireless operating range of up to 40 mm, and delivers a response time of 800 ms, demonstrating its suitability for low-power temperature and pressure sensing applications.

In this study, we propose an optimized inkjet printing process to improve the insertion loss of inkjet-printed coplanar waveguide (CPW) transmission lines. The process involves varying the drying temperature and adjusting the number of printing steps to investigate their effects on the electrical characteristics of the printed CPW. The relationships between surface roughness, surface cavities, morphological changes, and insertion loss are studied by conducting atomic force microscopy analysis and by examining the insertion loss up to 3 GHz. The printed CPW that underwent low-temperature drying after the first printing and high-temperature drying after the second printing before sintering showed improved results in terms of insertion loss, surface microcavities, and surface morphology compared to the CPWs prepared under different drying conditions. In particular, the proposed process led to an improvement in the insertion loss from 0.167 dB to 0.082 dB at 3 GHz. These findings provide valuable insights for improving the reliability and efficiency of printed electronics used in high-frequency applications.

Electrospinning is a straightforward approach for efficiently creating continuous fibers within the submicron to nanometer size range. Electrospun fibers possess excellent properties like high porosity, large specific surface area, tunable morphology, small diameter, etc., making them desirable in various applications. Because of its various properties, polymer is one of the most used materials as the spinning solution in electrospinning. Electrospun polymeric fibers, by themselves, may serve limited applications. Therefore, they are usually mixed with other materials to serve many applications. There are many ways in which these other materials are mixed with polymers in electrospinning, like doping, surface treatment, functionalization, etc. There are several studies published that report on the various composite fibers produced using electrospinning. However, a review focused solely on the production of heterogeneous fibers, where the electrospun fibers are intrinsically made of more than one material, is lacking. Herein, we review different heterogeneous fibers synthesized using electrospinning and their fabrication methods.

Adiabatic logic has been proposed as a method for drastically reducing power consumption in specialized low-power circuits. They often require specialized clock drivers that also function as the main power supply, in contrast to standard CMOS logic, and these power clocks are often a point of difficulty in the design process. A novel, stepwise charging driver circuit for four-phase adiabatic logic is proposed and validated through a simulation study. The proposed circuit consists of two identical driver circuits each driving two opposite adiabatic logic phases. Its performance relative to ideal step-charging and a standard CMOS across mismatched phase loads is analyzed, and new best practices are established. It is compared to a reference circuit consisting of one driver circuit for each phase along with a paired on-chip tank capacitor. The proposed driver uses opposite logic phases to act as the tank capacitor for each other in a “self-tanked” fashion. Each circuit was simulated in 15 nm FinFET across a variety of frequencies for an arbitrary logic operation. Both circuits showed comparable power consumption at all frequencies tested, yet the proposed driver uses fewer transistors and control signals and eliminates the explicit tank capacitors entirely, vastly reducing circuit area, complexity, and development time.

Microfluidic impedance cytometry has been demonstrated as an effective platform for single cell analysis, taking advantage of microfabricated features and dielectric cell sensing methods. In this study, we present a simple microfluidic device to improve the sensitivity, accuracy, and throughput of single suspension cell viability analysis using vertical sidewall electrodes fabricated by a widely accessible negative manufacturing method. A microchannel milled through a 75 µm platinum wire, which was embedded into poly-methyl-methacrylate (PMMA), created a pair of parallel vertical sidewall platinum electrodes. Jurkat cells were interrogated in a custom low-conductivity buffer (1.2 ± 0.04 mS/cm) to reduce current leakage and increase device sensitivity. Confirmed by live/dead staining and electron microscopy, a single optimum excitation frequency of 2 MHz was identified at which live and dead cells were discriminated based on the disruption in the cell membrane associated with cell death. At this frequency, live cells were found to exhibit changes in the impedance phase with no appreciable change in magnitude, while dead cells displayed the opposite behavior. Correlated with video microscopy, a computational algorithm was created that could identify cell detection events and determine cell viability status by application of a mathematical correlation method.

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Understanding hand and wrist forces during activities of daily living (ADLs) are pertinent when modeling prosthetics/orthotics, preventing workplace-related injuries, and understanding movement patterns that make athletes, dancers, and musicians elite. The small size of the wrist, fingers, and numerous joints creates obstacles in accurately measuring these forces. In this study, 14 FlexiForce sensors were sewn into a glove in an attempt to capture forces applied by the fingers. Participants in this study wore the glove and performed grasp and key turn activities. The maximal forces produced in the study were 9 N at the distal middle finger phalanx and 24 N at the distal thumb phalanx, respectively, for the grasp and key turn activities. Results from this study will help in determining the minimal forces of the hand during ADLs so that appropriate actuators may be placed at the appropriate joints in exoskeletons, orthotics, and prosthetics.

As the tremendous advances in the biosensing technology, the biometric authentication approach has been adopted to replace the conventional password-based systems. Due to their harmless nature, photoplethysmogram (PPG) related applications have been quite intriguing in recent years. PPG can measure volumetric blood-flow changes in the peripheral circulation. Because PPG signals are very easy to acquire, compared to other biometrics (fingerprints, iris/retina, etc.), especially by low-cost wearable electronic devices, they are widely adopted to measure heart rates. In this paper, we devise a novel robust PPG based authentication system, which is capable of continuously authenticating the user instead of one-time authentication as carried out by the conventional techniques. This new system consists of preprocessing and filtering, motion artifact (MA) removal, template and feature extraction, and training. The associated multiwavelet-based feature extraction mechanism facilitates more reliable features than the conventional scalar-wavelet schemes so that it allows the learning model to better distinguish users. The associated autoencoder perfectly transforms the input PPG signal into the latent space. Finally, any distance measure can be adopted to classify or authenticate users. In order to build a sufficiently large dataset, we have combined three public datasets and our own dataset collected by ourselves locally together to create a new dataset consisting of 120 subjects totally. We have already built the hardware prototype successfully for real-time training data collection and real-time authentication. The equal-error-rate at the authentication stage reaches 5.5% and the identification accuracy reaches 98% at the identification stage.