Tracing interfacical nanocrystalline grain defects (NCGD) formation inducing electrical characteristic degradation in thermal remains a challenging issue for polycrystalline silicon (poly-Si) stable and reliable application in engineering. Here, we present a microelectromechanical systems (MEMS) unit, which is composed of tunnel oxide passivating contact poly-Si tandem layer. It is a pioneering work to explore poly-Si NCGD performance in the thermal cycle, which includes three case periods and lasts 2 years. We obtain the thermal expansion deformation of poly-Si and demonstrate it with the thermal cycle finite element model (TC-FEM). Then, we reveal the key factor to be carrier mobility decay, in which the nanocrystal finite element model (NC-FEM) predicts grain displacement (GD) increasing, otherwise electronic mobility data is measured and determined by the Hall method. Specifically, dislocation defection accumulation is induced by grain refinement (GR), grain size (GS), and grain boundary (GB) increasing. Moreover, multiple twinning phenomena are displayed with three-dimensional (3D) structural reconstruction, which provides the basis for the formation of new grains and substantiates the GR phenomena. The periodic lattice strain induces deep trap accumulation and chemical degradation during operation, which restricts the carrier mobility. Ultimately, the electron-hole’s scattering probability is enhanced, promoting the decrease in conductivity. These findings differ from the conventional poly-Si electrical properties changing mechanisms, which enrich our understanding of NCGD in poly-Si materials. Additionally, we obtain insights into the resistance drift and carrier transport mechanisms and unravel the structural and mechanistic hierarchical twinning processes governed by defects. The findings of this work can have significant implications for the stability and reliability of poly-Si field-effect transistors or the pursuit of high-efficiency tandem solar cells.

Since 2021, the concept of the metaverse has gained significant popularity and attention, not only among the general public but also among researchers who are interested in novel technologies and human-machine interfaces. Sensors, a critical component of human-machine interaction, have seen rapid advancements in recent years, particularly graphene-based sensors. These sensors offer a number of benefits, including flexibility, lightweight, ease of integration, and outstanding electrical properties. Over the past decade, our research team has focused on developing advanced graphene sensors for use in human-machine interaction and wearable healthcare. In this review, we showcase our team’s efforts by presenting the design, manufacturing process, and performance of various graphene-based sensors, focusing on their suitability for diverse human-machine interaction needs across the human body. Additionally, we discuss potential future directions for the development of graphene-based sensors in human-machine interaction and share our insights.

The discovery of ferroelectricity in hafnium oxide (HfO₂) based thin films in 2011 renewed the interest in ferroelectrics. These new ferroelectrics possess completely different crystal morphology with conventional perovskite ferroelectrics, and present more robust ferroelectric properties upon aggressive scaling and compatibility with standard integrated circuit fabrication processes. In this article, we give a brief introduction to the conventional ferroelectric memories, then review the basic properties, recent progress, and memory applications of these HfO₂-based ferroelectrics.

Three main ambipolar compact models for Two-Dimensional (2D) materials based Field-Effect Transistors (2D-FETs) are reviewed: (1) Landauer model, (2) 2D Pao-Sah model, and (3) virtual Source Emission-Diffusion (VSED) model. For the Landauer model, the Gauss quadrature method is applied, and it summarizes all kinds of variants, exhibiting its state-of-art. For the 2D Pao-Sah model, the aspects of its theoretical fundamentals are rederived, and the electrostatic potentials of electrons and holes are clarified. A brief development history is compiled for the VSED model. In summary, the Landauer model is naturally appropriate for the ballistic transport of short channels, and the 2D Pao-Sah model is applicable to long-channel devices. By contrast, the VSED model offers a smooth transition between ultimate cases. These three models cover a fairly completed channel length range, which enables researchers to choose the appropriate compact model for their works.