Reviews & Analysis

Discovering improved semiconductor materials is essential for optimal device fabrication. In this Perspective, data-driven computational frameworks for semiconductor discovery and device development are discussed, including the challenges and opportunities moving forward.

While there is a clear opportunity for digital twins to bring value in mechanical and aerospace engineering, they must be considered as an asset in their own right so that their full potential can be realized.

The application of digital twins in industry has become increasingly common, but not without important challenges to be addressed by the research community.

Although digital twins first originated as models of physical systems, they are rapidly being applied to social systems, such as cities. This Perspective discusses the development and use of digital twins for urban planning.

The digital twin concept, while initially formulated and developed in industry and engineering, has compelling potential applications in medicine. There are, however, major challenges that need to be overcome to fully embrace digital twin technology in the medical context.

As computation is increasingly integrated into drug research and development, this Perspective analyzes company business models, funding and deals to provide unique insights into risks and opportunities in this quickly maturing industry, which aims to expedite the creation of life-saving therapeutics.

Language models offer promises in encoding quantum correlations and learning complex quantum states. This Perspective discusses the advantages of employing language models in quantum simulation, explores recent model developments, and offers insights into opportunities for realizing scalable and accurate quantum simulation.