Science and technology

Battery performance shapes the future of electric vehicles, renewable energy storage, consumer electronics, and grid resilience. Two metrics dominate progress: energy density, which determines how much energy a battery can store per unit of weight or volume, and cycle life, which measures how many charge–discharge cycles a battery can endure before significant degradation. Innovations that improve both are accelerating electrification while lowering lifetime costs and environmental impact.Advanced Cathode Materials Driving Higher Energy DensityCathodes largely determine a battery’s energy density. Recent innovations focus on increasing the amount of lithium that can be reversibly stored while maintaining structural stability.High-nickel layered oxides (such…

Green hydrogen was once portrayed as a transformative answer capable of decarbonizing almost every corner of the global economy, inspiring government master plans, a surge of investor funding for electrolyzer ventures, and bold forecasts of swift cost reductions; now, the storyline has become more restrained, with green hydrogen steadily carving out a role in select, high‑value niches where it addresses challenges that electricity alone cannot resolve, and this evolution from broad hype to focused deployment reflects hard‑earned insights about costs, infrastructure demands, and practical limitations.Understanding Green Hydrogen and the Early HypeGreen hydrogen is created by using renewable electricity to drive…

The rapid expansion of digital compute—driven by cloud services, artificial intelligence, high-performance computing, and edge processing—has become one of the fastest-growing sources of electricity demand. Large data centers now rival heavy industry in power intensity, while smaller edge facilities are proliferating across cities. Training and operating advanced models can require continuous, high-density power with tight reliability requirements. As a result, electric grids that were designed for predictable growth and centralized generation are adapting to a more volatile, location-specific, and time-sensitive load profile.How demand attributes are evolvingCompute-driven demand varies from conventional loads in numerous respects:Density: Modern data centers can exceed 50…

Modern AI systems are no longer limited chiefly by sheer computational power, as both training and inference in deep learning demand transferring enormous amounts of data between processors and memory. As models expand from millions to hundreds of billions of parameters, the memory wall—the widening disparity between processor speed and memory bandwidth—emerges as the primary constraint on performance.Graphics processing units and AI accelerators can execute trillions of operations per second, but they stall if data cannot be delivered at the same pace. This is where memory innovations such as High Bandwidth Memory (HBM) become critical.What makes HBM fundamentally differentHBM is…