Editor-Curated Robotics Industry Briefing - RobotToday

AI and Self-Driving Labs to Transform Semiconductor Materials Discovery Process

The semiconductor industry is facing significant challenges as it approaches physical limits in material performance, particularly as linewidths shrink below 2 nanometers. Traditional methods of discovering new semiconductor materials are outdated, often taking 10 to 20 years to bring a new material from the lab to market. This slow pace is due to the linear approach of hypothesis formation, synthesis, and characterization, which does not keep up with the complex requirements of modern materials. The need for new materials is critical for advancing device and chip architectures, especially as conventional materials like copper are becoming inadequate. Innovations such as hafnium oxide (HfO2) have previously enabled breakthroughs, but the current methods for material discovery have not evolved. Robotics and automation present a solution to these bottlenecks, offering the potential to accelerate the discovery process significantly. As the industry continues to evolve, companies that embrace automation in materials discovery will likely gain a competitive edge. The reluctance of some firms to adopt these technologies could result in them falling behind as first movers capitalize on the efficiencies and innovations that AI and self-driving labs can provide. No further timeline was disclosed at the time of publication.

RoboticsAndAutomationNews.com By David Edwards Aug 14, 2026 Autonomous Vehicles Computing Materials advanced materials ai artificial intelligence

Arizona State University Develops Innovative HARP Artificial Muscle for Versatile Applications

A research team led by Professor Sun Jiefeng at Arizona State University has developed a new artificial muscle structure known as HARP (Helical Anisotropic Reinforced Actuator). Unlike traditional artificial muscles that compromise on performance, HARP offers modularity and flexibility, allowing for adjustments in materials and design parameters to meet various application needs. This innovation is significant as it addresses the limitations of existing artificial muscles, which often excel in specific scenarios but struggle to meet multiple requirements simultaneously. HARP achieves an impressive power density of 1.93 kW/kg, a contraction rate of up to 75%, and the ability to lift weights up to 100 times its own weight, making it suitable for diverse and complex applications. Looking ahead, the HARP's modular design allows for customization and optimization of its components, enhancing its adaptability in extreme environments. The research team demonstrated HARP's durability in wear resistance tests, showcasing its potential for reliable operation in harsh industrial settings. No further timeline was disclosed at the time of publication.