The built environment faces increasing pressures from climate change, resource limitations, and rapid urbanisation.

More aggressive feature scaling and increasingly complex transistor structures are driving a steady increase in process complexity, increasing the risk that a specified pattern may not be ...

AI and machine learning are revolutionizing drug discovery, development, and lifecycle management, addressing industry ...

Less instrumentation. More insight. Physics-informed virtual sensors are shifting condition monitoring from isolated pilots ...

The integration of machine learning techniques into microstructure design and the prediction of material properties has ushered in a transformative era for materials science. By leveraging advanced ...

How AI is accelerating development of software. Various ways the electronics industry could benefit from AI-driven workflows. The continued emergence of wearables, printed electronics, and green ...

Industrial automation is entering a new era with physical AI, where machine learning meets real-world motion control. AI-driven robotics and digital twins are closing the gap between simulation and ...

Researchers developed a fully numerical design method using differential equations and genetic algorithms to optimize WPT systems. This approach ensures stable output voltage, high efficiency, and ...

For decades, scientists have relied on structure to understand protein function. Tools like AlphaFold have revolutionized how researchers predict and design folded proteins, allowing for new ...

The semiconductor industry is entering an era of unprecedented complexity, driven by advanced architectures such as Gate-All-Around (GAA) transistors, wide-bandgap materials like GaN and SiC, and ...