Nanoimprint Mold Consisting of an Adhesive Lap Joint between a Nanopatterned Metal Sleeve and a Carbon Composite Roll.

Roll-to-roll nanoimprinting is an emerging technology that has revolutionized the sectors of flexible electronics, thin films, and solar cells with its high throughput. However, there is still room for improvement. In this study, a FEM analysis (in ANSYS) was carried out on a large-area roll-to-roll nanoimprint system in which the master roller consists of a large nanopatterned nickel mold joined to a carbon fiber reinforced polymer (CFRP) base roller using epoxy adhesive. Deflections and pressure uniformity of the nano-mold assembly were analyzed under loadings of different magnitudes in a roll-to-roll nanoimprinting setup. Optimization of deflections was performed with applied loadings, and the lowest deflection value was 97.69 nm. The adhesive bond viability was assessed under a range of applied forces. Finally, potential strategies to reduce deflections were also discussed, which can be helpful in increasing pressure uniformity.

Utilizing EEG and fNIRS for the detection of sleep-deprivation-induced fatigue and its inhibition using colored light stimulation.

Drowsy driving is a common, but underestimated phenomenon in terms of associated risks as it often results in crashes causing fatalities and serious injuries. It is a challenging task to alert or reduce the driver's drowsy state using non-invasive techniques. In this study, a drowsiness reduction strategy has been developed and analyzed using exposure to different light colors and recording the corresponding electrical and biological brain activities. 31 subjects were examined by dividing them into 2 classes, a control group, and a healthy group. Fourteen EEG and 42 fNIRS channels were used to gather neurological data from two brain regions (prefrontal and visual cortices). Experiments shining 3 different colored lights have been carried out on them at certain times when there is a high probability to get drowsy. The results of this study show that there is a significant increase in HbO of a sleep-deprived participant when he is exposed to blue light. Similarly, the beta band of EEG also showed an increased response. However, the study found that there is no considerable increase in HbO and beta band power in the case of red and green light exposures. In addition to that, values of other physiological signals acquired such as heart rate, eye blinking, and self-reported Karolinska Sleepiness Scale scores validated the findings predicted by the electrical and biological signals. The statistical significance of the signals achieved has been tested using repeated measures ANOVA and t-tests. Correlation scores were also calculated to find the association between the changes in the data signals with the corresponding changes in the alertness level.

Lag Synchronization of Noisy and Nonnoisy Multiple Neurobiological Coupled FitzHugh-Nagumo Networks with and without Delayed Coupling.

This paper presents a methodology for synchronizing noisy and nonnoisy multiple coupled neurobiological FitzHugh-Nagumo (FHN) drive and slave neural networks with and without delayed coupling, under external electrical stimulation (EES), external disturbance, and variable parameters for each state of both FHN networks. Each network of neurons was configured by considering all aspects of real neurons communications in the brain, i.e., synapse and gap junctions. Novel adaptive control laws were developed and proposed that guarantee the synchronization of FHN neural networks in different configurations. The Lyapunov stability theory was utilized to analytically derive the sufficient conditions that ensure the synchronization of the FHN networks. The effectiveness and robustness of the proposed control laws were shown through different numerical simulations.

Nanofabrication Techniques: Challenges and Future Prospects.

Nanofabrication of functional micro/nano-features is becoming increasingly relevant in various electronic, photonic, energy, and biological devices globally. The development of these devices with special characteristics originates from the integration of low-cost and high-quality micro/nano-features into 3D-designs. Great progress has been achieved in recent years for the fabrication of micro/nanostructured based devices by using different imprinting techniques. The key problems are designing techniques/approaches with adequate resolution and consistency with specific materials. By considering optical device fabrication on the large-scale as a context, we discussed the considerations involved in product fabrication processes compatibility, the feature's functionality, and capability of bottom-up and top-down processes. This review summarizes the recent developments in these areas with an emphasis on established techniques for the micro/nano-fabrication of 3-dimensional structured devices on large-scale. Moreover, numerous potential applications and innovative products based on the large-scale are also demonstrated. Finally, prospects, challenges, and future directions for device fabrication are addressed precisely.

Lag synchronization of coupled time-delayed FitzHugh-Nagumo neural networks via feedback control.

Synchronization plays a significant role in information transfer and decision-making by neurons and brain neural networks. The development of control strategies for synchronizing a network of chaotic neurons with time delays, different direction-dependent coupling (unidirectional and bidirectional), and noise, particularly under external disturbances, is an essential and very challenging task. Researchers have extensively studied the synchronization mechanism of two coupled time-delayed neurons with bidirectional coupling and without incorporating the effect of noise, but not for time-delayed neural networks. To overcome these limitations, this study investigates the synchronization problem in a network of coupled FitzHugh-Nagumo (FHN) neurons by incorporating time delays, different direction-dependent coupling (unidirectional and bidirectional), noise, and ionic and external disturbances in the mathematical models. More specifically, this study investigates the synchronization of time-delayed unidirectional and bidirectional ring-structured FHN neuronal systems with and without external noise. Different gap junctions and delay parameters are used to incorporate time-delay dynamics in both neuronal networks. We also investigate the influence of the time delays between connected neurons on synchronization conditions. Further, to ensure the synchronization of the time-delayed FHN neuronal networks, different adaptive control laws are proposed for both unidirectional and bidirectional neuronal networks. In addition, necessary and sufficient conditions to achieve synchronization are provided by employing the Lyapunov stability theory. The results of numerical simulations conducted for different-sized multiple networks of time-delayed FHN neurons verify the effectiveness of the proposed adaptive control schemes.