An artificial neural network chip based on two-dimensional semiconductor.

Recently, research on two-dimensional (2D) semiconductors has begun to translate from the fundamental investigation into rudimentary functional circuits. In this work, we unveil the first functional MoS2 artificial neural network (ANN) chip, including multiply-and-accumulate (MAC), memory and activation function circuits. Such MoS2 ANN chip is realized through fabricating 818 field-effect transistors (FETs) on a wafer-scale and high-homogeneity MoS2 film, with a gate-last process to realize top gate structured FETs. A 62-level simulation program with integrated circuit emphasis (SPICE) model is utilized to design and optimize our analog ANN circuits. To demonstrate a practical application, a tactile digit sensing recognition was demonstrated based on our ANN circuits. After training, the digit recognition rate exceeds 97%. Our work not only demonstrates the protentional of 2D semiconductors in wafer-scale integrated circuits, but also paves the way for its future application in AI computation.

Engineering Top Gate Stack for Wafer-Scale Integrated Circuit Fabrication Based on Two-Dimensional Semiconductors.

In recent years, two-dimensional (2D) semiconductors have attracted considerable attention from both academic and industrial communities. Recent research has begun transforming from constructing basic field-effect transistors (FETs) into designing functional circuits. However, device processing remains a bottleneck in circuit-level integration. In this work, a non-destructive doping strategy is proposed to modulate precisely the threshold voltage (VTH) of MoS2-FETs in a wafer scale. By inserting an Al interlayer with a varied thickness between the high-k dielectric and the Au top gate (TG), the doping could be controlled. The full oxidation of the Al interlayer generates a surplus of oxygen vacancy (Vo) in the high-k dielectric layer, which further leads to stable electron doping. The proposed strategy is then used to optimize an inverter circuit by matching the electrical properties of the load and driver transistors. Furthermore, the doping strategy is used to fabricate digital logic blocks with desired logic functions, which indicates its potential to fabricate fully integrated multistage logic circuits based on wafer-scale 2D semiconductors.

Wafer-scale functional circuits based on two dimensional semiconductors with fabrication optimized by machine learning.

Triggered by the pioneering research on graphene, the family of two-dimensional layered materials (2DLMs) has been investigated for more than a decade, and appealing functionalities have been demonstrated. However, there are still challenges inhibiting high-quality growth and circuit-level integration, and results from previous studies are still far from complying with industrial standards. Here, we overcome these challenges by utilizing machine-learning (ML) algorithms to evaluate key process parameters that impact the electrical characteristics of MoS2 top-gated field-effect transistors (FETs). The wafer-scale fabrication processes are then guided by ML combined with grid searching to co-optimize device performance, including mobility, threshold voltage and subthreshold swing. A 62-level SPICE modeling was implemented for MoS2 FETs and further used to construct functional digital, analog, and photodetection circuits. Finally, we present wafer-scale test FET arrays and a 4-bit full adder employing industry-standard design flows and processes. Taken together, these results experimentally validate the application potential of ML-assisted fabrication optimization for beyond-silicon electronic materials.

Soft and Stretchable Optical Waveguide: Light Delivery and Manipulation at Complex Biointerfaces Creating Unique Windows for On-Body Sensing.

Over the past few decades, optical waveguides have been increasingly used in wearable/implantable devices for on-body sensing. However, conventional optical waveguides are stiff, rigid, and brittle. A mismatch between conventional optical waveguides and complex biointerfaces makes wearable/implantable devices uncomfortable to wear and potentially unsafe. Soft and stretchable polymer optical waveguides not only inherit many advantages of conventional optical waveguides (e.g., immunity to electromagnetic interference and without electrical hazards) but also provide a new perspective for solving the mismatch between conventional optical waveguides and complex biointerfaces, which is essential for the development of light-based wearable/implantable sensors. In this review, polymer optical waveguides' unique properties, including flexibility, biocompatibility and biodegradability, porosity, and stimulus responsiveness, and their applications in the wearable/implantable field in recent years are summarized. Then, we briefly discuss the current challenges of high optical loss, unstable signal transmission, low manufacturing efficiency, and difficulty in deployment during implantation of flexible polymer optical waveguides, and propose some possible solutions to these problems.