Multibarrier Collaborative Modulation Devices with Ultra-High Logic Operation Density.

The demands for highly miniaturized and multifunctional electronics are rapidly increasing. As scaling-down processes of transistors are restricted by physical limits, reconfigurable electronics with switchable operation functions for different tasks are developed for higher function integration based on split- or vertical-dual-gate structures. To promote the present reconfigurable electronics and exceed the function integration limit, the critical issue is to integrate complex operations into simple circuit forms by establishing more control dimensions. This work proposes a multibarrier collaborative (MBC) modulation architecture to increase the control dimension by multiple forms of potential barriers and achieves combinational and reconfigurable logic operations by a single MBC device. The MBC architecture exhibits ultrahigh logic operation density, including 58.8% area reduction for multiplexer operations and 71.4% area reduction for 4-logic reconfigurable operations. Besides, a hardware security module composed of 4 MBC devices implementing 8 types of logic operations is demonstrated. This work reveals an effective design of function integration for next-generation electronics.

Simulation of Novel Nano Low-Dimensional FETs at the Scaling Limit.

The scaling of bulk Si-based transistors has reached its limits, while novel architectures such as FinFETs and GAAFETs face challenges in sub-10 nm nodes due to complex fabrication processes and severe drain-induced barrier lowering (DIBL) effects. An effective strategy to avoid short-channel effects (SCEs) is the integration of low-dimensional materials into novel device architectures, leveraging the coupling between multiple gates to achieve efficient electrostatic control of the channel. We employed TCAD simulations to model multi-gate FETs based on various dimensional systems and comprehensively investigated electric fields, potentials, current densities, and electron densities within the devices. Through continuous parameter scaling and extracting the sub-threshold swing (SS) and DIBL from the electrical outputs, we offered optimal MoS2 layer numbers and single-walled carbon nanotube (SWCNT) diameters, as well as designed structures for multi-gate FETs based on monolayer MoS2, identifying dual-gate transistors as suitable for high-speed switching applications. Comparing the switching performance of two device types at the same node revealed CNT's advantages as a channel material in mitigating SCEs at sub-3 nm nodes. We validated the performance enhancement of 2D materials in the novel device architecture and reduced the complexity of the related experimental processes. Consequently, our research provides crucial insights for designing next-generation high-performance transistors based on low-dimensional materials at the scaling limit.

Recent Progress in Biosensors for Depression Monitoring-Advancing Personalized Treatment.

Depression is currently a major contributor to unnatural deaths and the healthcare burden globally, and a patient's battle with depression is often a long one. Because the causes, symptoms, and effects of medications are complex and highly individualized, early identification and personalized treatment of depression are key to improving treatment outcomes. The development of wearable electronics, machine learning, and other technologies in recent years has provided more possibilities for the realization of this goal. Conducting regular monitoring through biosensing technology allows for a more comprehensive and objective analysis than previous self-evaluations. This includes identifying depressive episodes, distinguishing somatization symptoms, analyzing etiology, and evaluating the effectiveness of treatment programs. This review summarizes recent research on biosensing technologies for depression. Special attention is given to technologies that can be portable or wearable, with the potential to enable patient use outside of the hospital, for long periods.

Recent Progress in Long-Term Sleep Monitoring Technology.

Sleep is an essential physiological activity, accounting for about one-third of our lives, which significantly impacts our memory, mood, health, and children's growth. Especially after the COVID-19 epidemic, sleep health issues have attracted more attention. In recent years, with the development of wearable electronic devices, there have been more and more studies, products, or solutions related to sleep monitoring. Many mature technologies, such as polysomnography, have been applied to clinical practice. However, it is urgent to develop wearable or non-contacting electronic devices suitable for household continuous sleep monitoring. This paper first introduces the basic knowledge of sleep and the significance of sleep monitoring. Then, according to the types of physiological signals monitored, this paper describes the research progress of bioelectrical signals, biomechanical signals, and biochemical signals used for sleep monitoring. However, it is not ideal to monitor the sleep quality for the whole night based on only one signal. Therefore, this paper reviews the research on multi-signal monitoring and introduces systematic sleep monitoring schemes. Finally, a conclusion and discussion of sleep monitoring are presented to propose potential future directions and prospects for sleep monitoring.

Understanding the Origin of Tensile Response in a Graphene Textile Strain Sensor with Negative Differential Resistance.

The flexible strain sensors based on the textile substrate have natural flexibility, high sensitivity, and wide-range tensile response. However, the textile's complex and anisotropic substructure leads to a negative differential resistance (NDR) response, lacking a deeper understanding of the mechanism. Therefore, we examined a graphene textile strain sensor with a conspicuous NDR tensile response, providing a requisite research platform for mechanism investigation. The pioneering measurement of single fiber bundles confirmed the existence of the NDR effect on the subgeometry scale. Based on the in situ characterization of tensile morphology and measurement, we conducted quantitative behavior analyses to reveal the origin of tensile electrical responses in the full range comprehensively. The results showed that the dominant factor in generating the NDR effect is the relative displacement of fibers within the textile bundles. Based on the neural spiking-like tensile response, we further demonstrated the application potential of the textile strain sensor in threshold detection and near-sensor signal processing. The proposed NDR behavior model would provide a reference for the design and application of wearable intelligent textiles.