The biomechanics of peripheral nerves are determined by the blood-nerve barrier (BNB), together with the epineural barrier, extracellular matrix, and axonal composition, which maintain structural and functional stability. These elements are often ignored in the fabrication of penetrating devices, and the implant process is traumatic due to the mechanical distress, compromising the function of neuroprosthesis for sensory-motor restoration in amputees. Miniaturization of penetrating interfaces offers the unique opportunity of decoding individual nerve fibers associated to specific functions, however, a main issue for their implant is the lack of high-precision standardization of insertion forces. Current automatized electromechanical force sensors are available; however, their sensitivity and range amplitude are limited (i.e. mN), and have been tested only in-vitro. We previously developed a high-precision bi-directional micro-electromechanical force sensor, with a closed-loop mechanism (MEMS-CLFS), that while measuring with high-precision (-211.7μN to 211.5μN with a resolution of 4.74nN), can be used in alive animal. Our technology has an on-chip electrothermal displacement sensor with a shuttle beam displacement amplification mechanism, for large range and high-frequency resolution (dynamic range of 92.9 dB), which eliminates the adverse effect of flexural nonlinearity measurements, observed with other systems, and reduces the mechanical impact on delicate biological tissue. In this work, we use the MEMS-CLFS for in-vivo bidirectional measurement of biomechanics in somatic and autonomic nerves. Furthermore we define the mechanical implications of irrigation and collagen VI in the BNB, which is different for both autonomic and somatic nerves (~ 8.5-8.6 fold density of collagen VI and vasculature CD31+ in the VN vs ScN). This study allowed us to create a mathematical approach to predict insertion forces. Our data highlights the necessity of nerve-customization forces to prevent injury when implanting interfaces, and describes a high precision MEMS technology and mathematical model for their measurements.

This paper introduces a lightweight Blockchain-based architecture for 5G-enabled Internet-of-Thing (IoT) networks that employs a low-complexity consensus algorithm suitable for resource-constrained IoT devices. By combining 5G technology with a lightweight Blockchain consensus algorithm, the proposed architecture guarantees high availability, real-time data delivery, security, reliability, and low-latency connectivity. Two transaction types are considered in this architecture, i.e., local and public. Local transactions are exchanged within devices located in the same Small Cell (SC) or Macro Cell (MC) private Blockchains, while public transactions exchange data among different MCs in the public Blockchain and store verified data in the distributed ledger. Performance evaluation reveals that the proposed architecture outperforms conventional 5G (without Blockchain) regarding security against data manipulation and fraud. The proposed architecture improves hashing and encryption protocols compared to conventional 5G but slightly reduces the data traffic rate and increases local transaction processing time. In contrast, the proposed architecture reduces the consensus processing time in the public Blockchain compared to Proof of Elapsed Time (PoET) by about thirty percent due to adding a Distributed Trust Algorithm (DTA). We evaluate the proposed architecture’s performance against conventional 5G and PoET in terms of processing time and power consumption. The results indicate that the proposed architecture provides superior performance, and the DTA algorithm’s addition enhances the public transaction’s consensus processing time.

Design, mechanical modeling and characterization of a new flexure-guided piezo-electrically actuated nanopositioner are presented in this paper. The scan range of this planar scanner is 5.8µm in both X- and Y-directions with the first resonance frequency being above 15 kHz. Lateral displacements are measured using an interferometer sensor. In this paper, we focus on presenting the novelty of the mechanical design and characterization of the nanopositioner in terms of system dynamics and sensor noise, with the ultimate goal of controller design for high-speed SPM.

We report characterization and control of a novel flexure-guided piezoelectric nanopositioner. The positioning range of this high-speed planar scanner is approximately 5.8 µm in both X and Y-directions with the first resonance frequency being above 15 kHz. An integral resonant controller is designed to augment damping to the dominant mode of the X-axis nanopositioner (fast axis). The damping controller is then augmented by a double integrator to provide better tracking performance. As for the Y-axis scanner (slow axis) where a lower bandwidth is required, a notch filter cascaded with an integrator is used to damp the dominant mode and achieve a satisfactory tracking bandwidth. Tracking performance of the nanopositioner in closed-loop with this control system is investigated through experiments where each axis of the nanopositioner is set to track a triangular input with different frequencies.

We present a control scheme for video-rate atomic force microscopy with rosette pattern. The controller structure involves a feedback internal-model-based controller and a feedforward iterative learning controller. The iterative learning controller is designed to improve tracking performance of the feedback-controlled scanner by rejecting the repetitive disturbances arising from the system nonlinearities. We investigate the performance of two inversion techniques for constructing the learning filter. We conduct tracking experiments using a two-degree-of-freedom microelectromechanical system (MEMS) nanopositioner at frame rates ranging from 5 to 20 frames per second. The results reveal that the algorithm converges rapidly and the iterative learning controller significantly reduces both the transient and steady-state tracking errors. We acquire and report a series of high-resolution time-lapsed video-rate AFM images with the rosette pattern.

Performance of several readout circuits, when applied to a MEMS-based bulk piezoresistive displacement sensor is compared in this study. The sensor comprises a pair of tilted clamped-guided silicon beams whose bulk piezoresistivity is used for displacement sensing. Wheatstone half-bridge, constant-voltage, and constant-current circuits are implemented to measure resistance changes of this sensor. We report full characterization of the sensor with these circuits and explore the sensor's important characteristics such as linearity, bandwidth, and noise. The results reveal that the constant-current circuit provides the highest sensitivity at equal-power bias condition. We find that the resolution of the sensor is degraded from 1.6 nm with the Wheatstone half-bridge and constant-voltage circuits to about 4.2 nm with the constant-current configuration. In the frequency domain, the sensor captures the full dynamics of the MEMS nanopositioner up to 20 kHz with all readout circuits. [2019-0168]

We present a microelectromechanical system (MEMS)-based closed-loop force sensor, capable of measuring bidirectional forces along one axis of motion. The device comprises an on-chip electrothermal displacement sensor and electrostatic actuators. It features a voltage-controlled stiffness-adjustment mechanism, providing the user with an additional means of tuning the sensor's characteristics. This silicon-on-insulator device is an improvement on our previous design, offering a better dynamic range and a less complex calibration process. The sensor is fabricated based on a standard SOI MEMS process. It is then fully characterized and instrumented with a feedback controller. The closed-loop characterization reveals a 1 sigma-resolution of 4.74 nN and a force sensing range of -211.7 mu N to 211.5 mu N, leading to a dynamic range of 92.9 dB. [2019-0248]

The sensing properties of a microelectromechanical system (MEMS)-based displacement sensor with a constant-current (CC) readout circuit are explored. The sensor comprises a pair of tilted clamped-guided silicon beams whose bulk piezoresistivity are employed for displacement sensing. To investigate the effect of driving the sensor with constant current, a readout circuit is designed and implemented. The characteristics of the sensor with the CC circuit are compared with the results obtained from a previously implemented Wheatstone half-bridge. To ensure a fair comparison, two test scenarios are considered. In the first approach, parameters of CC circuit are tuned such that the same power is delivered to the sensing beams. In the second case, these parameters are chosen so that both circuits achieve equal gains. A thorough characterization of the sensor is preformed in terms of linearity, resolution, bandwidth and noise. The results reveal that the piezoresistive sensor with the CC readout circuit provides a superior linearity compared to the Wheatstone bridge. However, using this circuit comes with challenges including a poor noise performance which are also discussed here.

Atomic force microscope (AFM) provides a unique possibility in nanoscience research and development for interrogation and manipulation of matter at nanoscale. Miniaturization of AFM significantly reduces the manufacturing cost and breaks the barrier to widespread adoption of this scientific instrument. This paper presents the characterization and control of a novel microelectromechanical system (MEMS)-based AFM. For in-plane motion, the device is equipped with a micro stage with integrated electrostatic actuators and electrothermal sensors. For use in taping-mode AFM imaging, a microcantilever is embedded within the device, featuring a piezoelectric layer for actuation. Positive position feedback (PPF) controller is used to attenuate the highly resonant dynamics of the stage. Scanning performance of device is evaluated by tracking a raster pattern where a 50 Hz triangular signal is applied to the actuators along the X axis. To reduce the tracking error, turnaround points of triangular signal are smoothed by using an optimization method. Moreover, the closed-loop bandwidth is increased with inversion-based feedforward technique. A 50Hz optimal reference signal combined with an inversion-based feedforward technique results in a fivefold decrease in root mean square of tracking error compared with triangular reference signal.

We present an analysis and a systematic design methodology for a novel nonraster scan method based on a rosette pattern and demonstrate its application in video-rate atomic force microscopy. This pattern is traced when the lateral axes of a parallel kinematic scanner are commanded to follow a combination of two sinusoids with identical amplitudes and different frequencies. We design an internal-model-based controller to enhance the tracking performance of this pattern and implement the scheme on a microelectromechanical system scanner. The results reveal high-precision tracking of the rosette pattern in order to acquire time-lapsed atomic force microscope images at the rate of 10 frames/s.

The Internet of Things (IoT) technology will soon become an integral part of our daily lives to facilitate the control and monitoring of processes and objects and revolutionize the ways that human interacts with the physical world. For all features of IoT to become fully functional in practice, there are several obstacles on the way to be surmounted and critical challenges to be addressed. These include, but are not limited to cybersecurity, data privacy, energy consumption, and scalability. The Blockchain decentralized nature and its multi-faceted procedures offer a useful mechanism to tackle several of these IoT challenges. However, applying the Blockchain protocols to IoT without considering their tremendous computational loads, delays, and bandwidth overhead can let to a new set of problems. This review evaluates some of the main challenges we face in the integration of Blockchain and IoT technologies and provides insights and high-level solutions that can potentially handle the shortcomings and constraints of both IoT and Blockchain technologies.

We demonstrate high-speed tracking of a self-repeating non-raster scan AFM pattern known as rosette. To generate this pattern, the lateral axes of the scanner trace the sum of two sinusoids with different frequencies but identical amplitudes. An iterative learning controller (ILC) is combined with a feedback controller to track this repetitive pattern. The feedback controller is designed based on the internal model principle and incorporates the fundamental reference frequencies while the ILC is employed to eliminate the repeating deterministic disturbances that appear in the tracking error. To verify the efficacy of the control approach, an experiment is conducted using a two-degree-of-freedom microelectromechanical system nanopositioner to track a rosette pattern sequentially at the rate of five frames per second. The experimental results show that the root-mean-square value of tracking error has been reduced by more than 38 % owing to the ILC.

This paper presents the design and characterization of a microelectromechanical systems (MEMS)-based probe scanner proposed to function as an on-chip atomic force microscope (AFM). The device comprises an in-plane stage with electrostatic actuators and electrothermal displacement sensors. The stage is able to precisely position an AFM probe over a sample to perform tapping-mode AFM imaging. For implementation, a standard silicon-on-insulator (SOI) microfabrication process is used. In a previously reported design, the embedded AFM probe featured only one piezoelectric transducer for simultaneous actuation and sensing, making its use in imaging problematic. To address this issue, the new design features separate actuation and sensing AlN piezoelectric transducers. An extra electrode is also incorporated on the probe that enables canceling the electrical feedthrough from the actuation to sensing. To accommodate the extra signal routing paths, mechanical design of the probe scanner is modified. Device characterization reveals an in-plane displacement range of 8 μm × 7 μm with a bandwidth of up to 2.7 kHz. The frequency-domain behavior of the AFM probe is also studied and feedthrough cancellation is performed at the resonant frequency of 127.35 kHz.

We demonstrate high-performance tracking of a cycloid trajectory for video-rate atomic force microscopy imaging by employing internal model control. To acquire sequential images using cycloid scanning, the stage needs to follow a slow periodic triangular wave superimposed on a sinusoidal signal along one axis with the remaining axis tracking a purely sinusoidal signal. The sharp turnarounds in the triangular signal result in a large tracking error. We utilize a trapezoidal signal to address this issue. To obtain high-precision positioning, the controller comprises the internal model of harmonic waveforms and the ramp signal plus additional integrator to compensate for stage nonlinearities. The controller is implemented on a two degree of freedom microelectromechanical system nanopositioner and operated at scan frequencies ranging from 500 Hz to 2580 Hz in a window size of 5 μm by 10 μm. While the pitch size of the trajectory is set to be 46 nm, the RMS value of tracking error remains below 7 nm. The highest scan rate of 20 frames per second is achieved at f=2580 Hz with the maximum transient tracking error of 15 nm.

Purpose Fabric structural parameters play an important role on the thermal comfort of clothing. The purpose of this paper is to investigate the effect of weave pattern and also the length of warp float in each weave pattern on the thermal properties of woven fabrics. Design/methodology/approach Cotton woven fabrics with 23 different weave patterns were produced with identical linear densities of warp and weft yarns as well as constant warp and weft nominal densities. Thereafter, their thermal properties were studied. Findings Statistical analysis demonstrated that the weave pattern significantly influences on the thermal properties of woven fabrics. Plain fabric exhibited the lowest thermal resistance and the highest thermal conductivity, and hopsack 2/2(4) weave fabric demonstrated the highest thermal resistance and the lowest thermal conductivity. Moreover, except hopsack (4) weave fabric, in all weave patterns, the length of warp float had a significant effect on the thermal characteristics of the fabrics, as increasing the warp float led to increase in the thermal resistance of the fabrics. Originality/value Weave pattern as one of the structural parameters of the fabric has a determinant role on the thermal properties of fabric and subsequently, the comfort of clothing produced from it. Owing to the lack of investigation in this area, this research considers the effect of weave pattern and the length of warp float in each weave pattern on the thermal properties of woven fabrics.

We demonstrate the application of the internal model principle in tracking a sequential cycloid trajectory to achieve video-rate atomic force microscope (AFM) imaging. To generate a sequential cycloid pattern, one axis of the nanopositioner traces a sinusoidal signal superimposed on a slow triangular wave. Discontinuities at turning points induce large peaks in the steady-state tracking error. To address this issue, a smooth trajectory is designed to reduce the magnitude of error by 60 nm compared with the triangular wave. This trajectory reduces the magnitude of error 10 times. The tracking controller includes the dynamics of the harmonic waveforms and the ramp signal as well as higher order harmonics of the scanning frequency, and an integrator to cope with the system nonlinearities at low frequencies. We perform experiments on a two degree of freedom microelectromechanical system nanopositioner at various scanning frequencies ranging from 500 to 2580 Hz within a scan area of 5 mu m x 10 mu m. The root-mean-square value of tracking error remains below 6.1 nm with a pitch size of 44.2 nm. We acquire time-lapse AFM images in contact mode at scan rates as high as 20 frames per second.

We report sequential atomic force microscope (AFM) imaging with a cycloid scan pattern where one lateral axis of the nanopositioner follows a sinusoid superimposed on a slow triangular signal. Due to the abrupt slope change in a triangular signal, large peaks appear in the tracking error. To smoothen the sharp turning points and reduce the error, an optimization technique is employed. To achieve a highperformance tracking, we utilized an internal model controller which includes a model of the reference signals while additional internal models are also added to the controller to deal with the system nonlinearities. The experiment is conducted on a two degrees of freedom microelectromechanical system nanopositioner within a scan area of $5 \ \mu\mathrm{m}\times 10 \ \mu\mathrm{m}$ and the pitch size of 44.2 nm as the scanning time is 80.6 msec. The peak of tracking error in x-axis is negligible due to the optimal trajectory while the root mean square value of tracking error is obtained as 4.9 nm and 4.4 nm for x- and y-axis, respectively. A sequence of contact mode constant height AFM images are acquired at 12.4 fps.

This paper presents a novel one-degree-of-freedom microelectromechanical systems (MEMS) force sensor. The high-bandwidth device contains on-chip sensing and actuation mechanisms, enabling open- and closed-loop modalities. An active compliance mechanism is incorporated to render the device more conducive to characterization of soft samples. When operated in closed loop, the adjustable stiffness enables the sensor to attain a larger dynamic range and minimize the nonlinearities originating from flexures. Analytical models are employed to design and calibrate the sensor. In open loop, the sensing resolution of 23.3 nN within a bandwidth of 2.35 kHz and a full-scale range of +/- 42.6 mu N are experimentally obtained. The resolution is enhanced to 9.3 nN by employing an active compliance mechanism. When operated in closed loop, a resolution of 12.9 nN is achieved within a dynamic range of 71.2 dB and a sensing bandwidth of 3.6 kHz is demonstrated. The sensor performance is tested by obtaining the stiffness of an atomic force microscope probe and measuring the force produced by a self-actuated piezoelectric microcantilever.

We report a new non-raster scan method based on a rosette pattern for high-speed atomic force microscopy (AFM). In this method, the lateral axes of the scanner are driven by the sum of two sinusoids with identical amplitudes and different frequencies. We formulate the problem so as to generate the rosette pattern and calculate scan parameters and resolution. To achieve high performance tracking, a controller is designed based on the internal model principle. The controller includes the dynamic modes of the reference signals and higher harmonics to cope with the system nonlinearities. We conduct an experiment employing the proposed method and a two degree of freedom microelectromechanical system nanopositioner to scan a circular-shaped area with a diameter of 6μm in 0.2 sec. The steady state tracking error is less than 4.48nm, i.e. only 9% of the selected resolution. AFM scanning is performed in contact mode constant height and high quality images are obtained.

Microcantilevers featuring separate built-in actuation and displacement sensing capabilities allow effective and simple implementation of control methods, opening a pathway to achieving higher scan speeds in tapping-mode atomic force microscopy. Such active cantilevers are a significant milestone to eventually obtain video-rate on-chip atomic force microscopes (AFMs) that can even surpass the functionality and imaging speed of their macroscale counterparts at a significantly lower cost. In this brief, we present an active AFM cantilever with an on-chip actuator and two built-in displacement sensors, designed to be integrated into on-chip AFMs. The common feedthrough problem present in this type of architecture is addressed by a differential sensing configuration, and the revealed dynamics are used for the system identification. A positive position feedback controller is designed to actively tailor the $Q$ factor of the cantilever. The imaging performance of the microcantilever with and without $Q$ control is compared by attenuating the cantilever’s $Q$ factor from 177 to 15 using the feedback loop. A common artifact in high-speed scans, the parachuting effect, is mitigated, rendering higher imaging speeds achievable.