In the growing area of neuromorphic and in-memory computing, there are multiple reviews
available. Most of them cover a broad range of topics, which naturally comes at the cost of …

Two-dimensional (2D) transition metal dichalcogenides (TMDs) with layered crystal
structures have been attracting enormous research interest for their atomic thickness …

Costly data movement in terms of time and energy in traditional von Neumann systems is
exacerbated by emerging information technologies related to artificial intelligence. In …

CMOS-RRAM integration holds great promise for low energy and high throughput
neuromorphic computing. However, most RRAM technologies relying on filamentary …

We investigate whether large language models can perform the creative hypothesis
generation that human researchers regularly do. While the error rate is high, generative AI …

The increased demand of high‐performance computing systems has exposed the inherent
limitations of the current state‐of‐the‐art von Neumann architecture. Therefore, developing …

With the advent of the big data era and the Internet of Things, promising hardware
techniques for data storage and energy-efficient data processing are in great demand. This …

Silicon CMOS-based computing-in-memory encounters design and power challenges,
especially in logic-in-memory scenarios requiring nonvolatility and reconfigurability. Here …

Abstract Gallium oxide (Ga 2 O 3) is an ultrawide-bandgap semiconductor material that has
gained attention in recent years owing to its potential applications in optoelectronic devices …

The ultrathin thickness of 2D layered materials affords the control of their properties through
defects, surface modification, and electrostatic fields more efficiently compared with bulk …