Adaptive Extended State Observer for the Dual Active Bridge Converters.

The DC-DC dual active bridge (DAB) converter has become one of the essential units for bidirectional energy distribution and connecting various renewable energy sources. When it comes to regulating the converter's output voltage, integrating an extended state observer (ESO) offers the advantage of eliminating the need for a current sensor, thereby reducing system costs. The ESO with a high observer bandwidth tends to acquire a faster system convergence and greater tracking accuracy. However, its disturbance suppression performance will become poor compared to the ESO with a low observer bandwidth. Based on this, the adaptive ESO (AESO) is proposed in this study to make a compromise between tracking performance and disturbance suppression. When the system is subjected to a high voltage error, the observer bandwidth will increase to improve the tracking performance and decrease to enhance the disturbance suppression. In order to demonstrate that the proposed method is effective, it is compared to the ESO with a fixed observer bandwidth and the improved model-based phase-shift control (MPSC). These comparisons are made through simulation and experimental results in various operation scenarios.

Wafer-scale striped network transistors based on purified semiconducting carbon nanotubes for commercialization.

Highly purified and solution-processed semiconducting carbon nanotubes (s-CNTs) have developed rapidly over the past several decades and are near-commercially available materials that can replace silicon due to its large-area substrate deposition and room-temperature processing compatibility. However, the more s-CNTs are purified, the better their electrical performance, but considerable effort and long centrifugation time are required, which can limit commercialization due to high manufacturing costs. In this work, we therefore fabricated 'striped' CNT network transistor across industry-standard 8 inch wafers. The stripe-structured channel is effective in lowering the manufacturing cost because it can maintain good device performance without requiring high-purity s-CNTs. We evaluated the electrical performances and their uniformity by demonstrating striped CNT network transistors fabricating from various s-CNT solutions (e.g. 99%, 95%, and 90%) in 8 inch wafers. From our results, we concluded that by optimizing the CNT network configurations, CNTs can be sufficiently utilized for commercialization technology even at low semiconducting purity. Our approach can serve as a critical foundation for future low-cost commercial CNT electronics.

Robust Adaptive Control Strategy for a Bidirectional DC-DC Converter Based on Extremum Seeking and Sliding Mode Control.

This paper presents a new control strategy that combines classical control and an optimization scheme to regulate the output voltage of the bidirectional converter under the presence of matched and mismatched disturbances. In detail, a control-oriented modeling method is presented first to capture the system dynamics in a common canonical form, allowing different disturbances to be considered. To estimate and compensate for unknown disturbances, an extended state observer (ESO)-based continuous sliding mode control is then proposed, which can guarantee high tracking precision, fast disturbance rejection, and chattering reduction. Next, an extremum seeking (ES)-based adaptive scheme is introduced to ensure system robustness as well as optimal control effort under different working scenarios. Finally, comparative simulations with classical proportional-integral-derivative (PID) control and constant switching gains are conducted to verify the effectiveness of the proposed adaptive control methodology through three case studies of load resistance variations, buck/boost mode switching, and input voltage variation.

Cost-effective method for fabricating carbon nanotube network transistors by reusing a 99% semiconducting carbon nanotube solution.

Carbon nanotubes (CNTs) are one-dimensional materials that have been proposed to replace silicon semiconductors and have been actively studied due to their high carrier mobility, high current density, and high mechanical flexibility. Specifically, highly purified, pre-separated, and solution-processed semiconducting CNTs are suitable for mass production. These CNTs have advantages, such as room-temperature processing compatibility, while enabling a fast and straightforward manufacturing process. In this paper, CNT network transistors were fabricated on a total of five 8 inch wafers by reusing a highly purified and pre-separated 99% semiconductor-enriched CNT solution. The results confirmed that the density of semiconducting CNTs deposited on the five selected wafers was notably uniform, even though the CNT solution was reused up to four times after the initial CNT deposition. Moreover, there was no significant degradation in the key CNT network transistor metrics. Therefore, we believe that our findings regarding this CNT reuse method may provide additional guidance in the field of wafer-scale CNT electronics and may contribute strongly to the development of practical device applications at an ultralow cost.

Defect spectroscopy of sidewall interfaces in gate-all-around silicon nanosheet FET.

Through time-dependent defect spectroscopy and low-frequency noise measurements, we investigate and characterize the differences of carrier trapping processes occurred by different interfaces (top/sidewall) of the gate-all-around silicon nanosheet field-effect transistor (GAA SiNS FET). In a GAA SiNS FET fabricated by the top-down process, the traps at the sidewall interface significantly affect the device performance as the width decreases. Compare to expectations, as the width of the device decreases, the subthreshold swing (SS) increases from 120 to 230 mV/dec, resulting in less gate controllability. In narrow-width devices, the effect of traps located at the sidewall interface is significantly dominant, and the 1/f 2 noise, also known as generation-recombination (G-R) noise, is clearly appeared with an increased time constant (τ i ). In addition, the probability density distributions for the normalized current fluctuations (ΔI D) show only one Gaussian in wide-width devices, whereas they are separated into four Gaussians with increased in narrow-width devices. Therefore, fitting is performed through the carrier number fluctuation-correlated with mobility fluctuations model that separately considered the effects of sidewall. In narrow-width GAA SiNS FETs, consequently, the extracted interface trap densities (N T ) distribution becomes more dominant, and the scattering parameter ([Formula: see text]) distribution increases by more than double.

Wafer-scale carbon nanotube network transistors.

Highly purified, preseparated semiconducting carbon nanotubes (CNTs) hold great potential for high-performance CNT network transistors due to their high electrical conductivity, high mechanical strength, and room-temperature processing compatibility. In this paper, we report our recent progress on CNT network transistors integrated on an 8-inch wafer. We observe that the key device performance parameters of CNT network transistors at various locations on an 8-inch wafer are highly uniform and that the device yield is impressive. Therefore, this work validates a promising path toward mass production and will make a significant contribution to the future field of wafer-scale CNT electronics.

Directly drawn top-gate semiconducting carbon nanotube thin-film transistors and complementary inverters.

As the emerging demand for electronic devices that are simple, cost effective and capable of rapid fabrication has increased, novel fabrication techniques for designing and manufacturing such devices have attracted remarkable research interest. One method for prototyping these electronic devices is to draw them using a handwriting tool that is commonly available. In this work, we demonstrate a transistor and complementary logic inverter that are directly drawn using a brush and that are based on solution-based materials such as semiconducting carbon nanotubes (CNTs), silver ink and paste, and cross-linked poly(4-vinylphenol) (cPVP). The directly drawn CNT thin-film transistor (TFT) has p-type behavior due to the adsorption of oxygen and moisture, a high current on/off ratio (approximately 103), and a low operating voltage. By employing a solution-based chemical doping treatment with an amine-rich polymer, polyethyleneimine (PEI), that has strong electron-donating ability, the drawn p-type CNT-TFT is successfully converted to an n-type CNT-TFT. Therefore, we fabricate a drawn complementary logic inverter consisting of the p-type CNT-TFT and PEI-treated n-type CNT-TFT and evaluate its electrical performance.

Ultrasensitive Electrical Detection of Hemagglutinin for Point-of-Care Detection of Influenza Virus Based on a CMP-NANA Probe and Top-Down Processed Silicon Nanowire Field-Effect Transistors.

Rather than the internal genome nucleic acids, the biomolecules on the surface of the influenza virus itself should be detected for a more exact and rapid point-of-care yes/no decision for influenza virus-induced infectious diseases. This work demonstrates the ultrasensitive electrical detection of the HA1 domain of hemagglutinin (HA), a representative viral surface protein of the influenza virus, using the top-down complementary metal oxide semiconductor (CMOS) processed silicon nanowire (SiNW) field-effect transistor (FET) configuration. Cytidine-5'-monophospho-N-acetylneuraminic acid (CMP-NANA) was employed as a probe that specifically binds both to the aldehyde self-aligned monolayer on the SiNWs and to HA1 simultaneously. CMP-NANA was serially combined with two kinds of linkers, namely 3-aminopropyltriethoxysilane and glutaraldehyde. The surface functionalization used was verified using the purification of glutathione S-transferase-tagged HA1, contact angle measurement, enzyme-linked immunosorbent assay test, and isoelectric focusing analysis. The proposed functionalized SiNW FET showed high sensitivities of the threshold voltage shift (ΔVT) ~51 mV/pH and the ΔVT = 112 mV (63 mV/decade) with an ultralow detectable range of 1 fM of target protein HA1.

Synaptic Device Network Architecture with Feature Extraction for Unsupervised Image Classification.

For the efficient recognition and classification of numerous images, neuroinspired deep learning algorithms have demonstrated their substantial performance. Nevertheless, current deep learning algorithms that are performed on von Neumann machines face significant limitations due to their inherent inefficient energy consumption. Thus, alternative approaches (i.e., neuromorphic systems) are expected to provide more energy-efficient computing units. However, the implementation of the neuromorphic system is still challenging due to the uncertain impacts of synaptic device specifications on system performance. Moreover, only few studies are reported how to implement feature extraction algorithms on the neuromorphic system. Here, a synaptic device network architecture with a feature extraction algorithm inspired by the convolutional neural network is demonstrated. Its pattern recognition efficacy is validated using a device-to-system level simulation. The network can classify handwritten digits at up to a 90% recognition rate despite using fewer synaptic devices than the architecture without feature extraction.

Automatic image fusion of real-time ultrasound with computed tomography images: a prospective comparison between two auto-registration methods.

Background A major drawback of conventional manual image fusion is that the process may be complex, especially for less-experienced operators. Recently, two automatic image fusion techniques called Positioning and Sweeping auto-registration have been developed. Purpose To compare the accuracy and required time for image fusion of real-time ultrasonography (US) and computed tomography (CT) images between Positioning and Sweeping auto-registration. Material and Methods Eighteen consecutive patients referred for planning US for radiofrequency ablation or biopsy for focal hepatic lesions were enrolled. Image fusion using both auto-registration methods was performed for each patient. Registration error, time required for image fusion, and number of point locks used were compared using the Wilcoxon signed rank test. Results Image fusion was successful in all patients. Positioning auto-registration was significantly faster than Sweeping auto-registration for both initial (median, 11 s [range, 3-16 s] vs. 32 s [range, 21-38 s]; P < 0.001] and complete (median, 34.0 s [range, 26-66 s] vs. 47.5 s [range, 32-90]; P = 0.001] image fusion. Registration error of Positioning auto-registration was significantly higher for initial image fusion (median, 38.8 mm [range, 16.0-84.6 mm] vs. 18.2 mm [6.7-73.4 mm]; P = 0.029), but not for complete image fusion (median, 4.75 mm [range, 1.7-9.9 mm] vs. 5.8 mm [range, 2.0-13.0 mm]; P = 0.338]. Number of point locks required to refine the initially fused images was significantly higher with Positioning auto-registration (median, 2 [range, 2-3] vs. 1 [range, 1-2]; P = 0.012]. Conclusion Positioning auto-registration offers faster image fusion between real-time US and pre-procedural CT images than Sweeping auto-registration. The final registration error is similar between the two methods.

Compact Two-State-Variable Second-Order Memristor Model.

A key requirement for using memristors in functional circuits is a predictive physical model to capture the resistive switching behavior, which shall be compact enough to be implemented using a circuit simulator. Although a number of memristor models have been developed, most of these models (i.e., first-order memristor models) have utilized only a one-state-variable. However, such simplification is not adequate for accurate modeling because multiple mechanisms are involved in resistive switching. Here, a two-state-variable based second-order memristor model is presented, which considers the axial drift of the charged vacancies in an applied electric field and the radial vacancy motion caused by the thermophoresis and diffusion. In particular, this model emulates the details of the intrinsic short-term dynamics, such as decay and temporal heat summation, and therefore, it accurately predicts the resistive switching characteristics for both DC and AC input signals.

The Analysis of Characteristics in Dry and Wet Environments of Silicon Nanowire-Biosensor.

Our study investigates differences in sensitivity of dry and wet environment in the field of biosensing experiment in detail and depth. The sensitivity of biosensing varies by means of surrounding conditions of silicon nanowire field effect transistor (SiNW FET). By examining charged polymer reaction in the silicon nanowire transistor (SiNW), we have discovered that the threshold voltage (V(T)) shift and change of subthreshold slope (SS) in wet environment are smaller than that of the air. Furthermore, we analyzed the sensitivity through modifying electrolyte concentration in the wet condition, and confirmed that V(T) shift increases in low concentration condition of phosphate buffered saline (PBS) due to the Debye length. We believe that the results we have found in this study would be the cornerstone in contributing to advanced biosensing experiment in the future.

The effects of modified constraint-induced movement therapy combined with trunk restraint in subacute stroke: a double-blinded randomized controlled trial.

OBJECTIVE: To investigate the effects of a modified constraint-induced movement therapy (mCIMT) with trunk restraint in subacute stroke patients. DESIGN: Double-blind, randomized controlled trial. SETTING: Rehabilitation clinic. PARTICIPANTS: Eighteen subacute stroke patients with moderate motor impairment. INTERVENTIONS: The patients were treated with either mCIMT combined with trunk restraint or mCIMT for 5 days per week for 4 weeks. The mCIMT combined with trunk restraint group participated in structured intervention sessions for use of the more affected upper-extremity in task-oriented activities with trunk restraint for 1 hour per day, and with the less affected upper-extremity restrained for 5 hours per day weeks. The mCIMT group followed the same protocol without trunk restraint. MAIN OUTCOME MEASURES: The outcome measures included the action research arm test (ARAT), the Fugl-Meyer assessment (FMA), the modified Barthel index (MBI), the motor activity log (MAL) and the maximal elbow extension angle during reaching (MEEAR) were completed at baseline and post intervention. RESULTS: The mCIMT combined with trunk restraint group exhibited more improved in the ARAT, FMA, MBI, MAL and MEEAR compared with the mCIMT group. Statistical analyses showed significantly different in ARAT (P = 0.046), FMA (P = 0.008), MBI (P = 0.001), MAL-AOU (P = 0.024), MAL-QOM (P = 0.010) and MEEAR (P = 0.001) between groups. CONCLUSIONS: These results suggest that mCIMT combined with trunk restraint is more helpful to improve upper-extremity function than mCIMT only in subacute stroke patients with moderate motor impairment.

Comparison of the effect of weight-bearing and non-weight-bearing positions on knee position sense in patients with chronic stroke.

[Purpose] The purpose of this study was to investigate the knee joint proprioception in weight-bearing (WB) and non-weight-bearing (NWB) positions and to study the difference between the methods in chronic stroke patients. [Subjects and Methods] The subjects were 15 stroke patients who were randomly scheduled to perform both positions by a physical therapist not involved in the study. The subjects performed the positions (WB and NWB) based on a randomized controlled cross-sectional design. WB subjects were positioned in one-leg standing to assess the knee joint position sense. NWB subjects were instructed to sit comfortably in a chair and maintain the knees at 90° of flexion with the leg out of the plinth. [Results] The results revealed that the WB position showed a significant difference in knee position sense. The proprioception sense in the WB position was a higher than that in the NWB position. [Conclusion] The knee proprioception of chronic stroke patients differs between the weight-bearing and non-weight-bearing positions.

Structural insights into the dual nucleotide exchange and GDI displacement activity of SidM/DrrA.

GDP-bound prenylated Rabs, sequestered by GDI (GDP dissociation inhibitor) in the cytosol, are delivered to destined sub-cellular compartment and subsequently activated by GEFs (guanine nucleotide exchange factors) catalysing GDP-to-GTP exchange. The dissociation of GDI from Rabs is believed to require a GDF (GDI displacement factor). Only two RabGDFs, human PRA-1 and Legionella pneumophila SidM/DrrA, have been identified so far and the molecular mechanism of GDF is elusive. Here, we present the structure of a SidM/DrrA fragment possessing dual GEF and GDF activity in complex with Rab1. SidM/DrrA reconfigures the Switch regions of the GTPase domain of Rab1, as eukaryotic GEFs do toward cognate Rabs. Structure-based mutational analyses show that the surface of SidM/DrrA, catalysing nucleotide exchange, is involved in GDI1 displacement from prenylated Rab1:GDP. In comparison with an eukaryotic GEF TRAPP I, this bacterial GEF/GDF exhibits high binding affinity for Rab1 with GDP retained at the active site, which appears as the key feature for the GDF activity of the protein.

Effect of training with whole body vibration on the sitting balance of stroke patients.

[Purpose] The purpose of this study was to determine the effects of task-oriented training with whole body vibration (WBV) on the sitting balance of stroke patients. [Subjects] The subjects were 30 stroke patients who were randomly divided into experimental (n1=15) and control (n2=15) groups. [Methods] Subjects in both groups received general training five times per week. Subjects in the experimental group practiced an additional task-oriented training program with WBV, which was performed for 15 minutes, five times per week, for four weeks. The center of pressure (COP) path length and average velocity were used to assess subjects static sitting balance, and the Modified Functional Reach Test (MFRT) was used to assess their dynamic sitting balance. The paired t-test was performed to test the significance of differences between before and after the intervention. The independent t-test was conducted to test the significance of differences between the groups. [Results] Following the intervention, the experimental group showed a significant change in MFRT. [Conclusion] The results of this study suggest that task-oriented training with WBV is feasible and efficacious for stroke patients.

Simulation of a randomly percolated CNT network for an improved analog physical unclonable function.

Carbon nanotube networks (CNTs)-based devices are well suited for the physically unclonable function (PUF) due to the inherent randomness of the CNT network, but CNT networks can vary significantly during manufacturing due to various controllable process conditions, which have a significant impact on PUF performance. Therefore, optimization of process conditions is essential to have a PUF with excellent performance. However, because it is time-consuming and costly to fabricate directly under various conditions, we implement randomly formed CNT network using simulation and confirm the variable correlation of the CNT network optimized for PUF performance. At the same time, by implementing an analog PUF through simulation, we present a 2D patterned PUF that has excellent security and can compensate for error occurrence problems. To evaluate the performance of analog PUF, a new evaluation method different from the existing digital PUF is proposed, and the PUF performance is compared according to two process variables, CNT density and metallic CNT ratio, and the correlation with PUF performance is confirmed. This study can serve as a basis for research to produce optimized CNT PUF by applying simulation according to the needs of the process of forming a CNT network.

Gate Capacitance Coupling of Double-Gate Carbon Nanotube Network Transistors.

Carbon nanotube (CNT) network channels constructed using a high-purity CNT solution for use in CNT thin-film transistors have the advantages of the possibility of requiring a low-temperature process and needing no special equipment. However, there are empty spaces between individual CNTs, resulting in unexpected effects. In this study, double-gate (DG) CNT network transistors were fabricated and measured in four different configurations to observe the capacitive coupling effects between the top gate (TG) and bottom gate (BG) in the DG structure. As a result, the electrical characteristics measured with the BG with a thicker gate oxide while floating the TG were similar to those measured with the TG with a thinner gate oxide. A comparison of the measured transfer curves showed that TG and BG were strongly coupled through the empty spaces in the channels. In addition, we evaluated the capacitance coupling effect due to changes in the CNT density, which is closely related to the empty space of the network channel. Finally, we proposed a method to determine the effective gate capacitance by considering the empty spaces between CNTs, which enabled the accurate evaluation of mobility. The effects of these materials were demonstrated by fabricating transistors using Al2O3, HfO2, and ZrO2 as TG oxide materials. By focusing on considerations based on the properties of CNT materials, our study provides valuable insights into accurate electrical modeling and potential advancements in CNT-based devices.

Self-aligned nanoforest in silicon nanowire for sensitive conductance modulation.

A self-aligned and localized nanoforest structure is constructed in a top-down fabricated silicon nanowire (SiNW). The surface-to-volume ratio (SVR) of the SiNW is enhanced due to the local nanoforest formation. The conductance modulation property of the SiNWs, which is an important characteristic in sensor and charge transfer based applications, can be largely enhanced. For the selective modification of the channel region, localized Joule-heating and subsequent metal-assisted chemical etching (mac-etch) are employed. The nanoforest is formed only in the channel region without misalignment due to the self-aligned process of Joule-heating. The modified SiNW is applied to a porphyrin-silicon hybrid device to verify the enhanced conductance modulation. The charge transfer efficiency between the porphyrin and the SiNW, which is caused by external optical excitation, is clearly increased compared to the initial SiNW. The effect of the local nanoforest formation is enhanced when longer etching times and larger widths are used.

A nanoforest structure for practical surface-enhanced Raman scattering substrates.

A nanoforest structure for surface-enhanced Raman scattering (SERS) active substrates is fabricated and analyzed. The detailed morphology of the resulting structure can be easily controlled by modifying the process parameters such as initial gold layer thickness and etching time. The applicability of the nanoforest substrate as a label-free SERS immunosensor is demonstrated using influenza A virus subtype H1N1. Selective binding of the H1N1 surface antigen and the anti-H1 antibody is directly detected by the SERS signal differences. Simple fabrication and high throughput with strong in-plane hot-spots imply that the nanoforest structure can be a practical sensing component of a chip-based SERS sensing system.