Splitting water into hydrogen and oxygen using sunlight offers a route to renewable fuel, but translating this reaction into systems suitable for industrial implementation remains difficult. Photocatalyst sheets can overcome key limitations of common direct water-splitting approaches (photoelectrochemical devices and photocatalyst dispersions), but existing photocatalyst sheets rely on inorganic semiconductor nanoparticles and processing techniques that can be difficult to scale. Here we show that solution-processed organic semiconductors can form water-splitting photocatalyst sheets by simply tailoring the charge extraction layer beneath the light-absorbing film. A single organic semiconductor active layer (deposited as a bulk heterojunction blend) drives either hydrogen or oxygen evolution depending on its underlying molecular contact, yielding photocathode and photoanode half-cells with well-matched photocurrents. Combining both reactions on one substrate using a microdomain-patterned molecular underlayer affords a photocatalyst sheet that achieves unassisted water splitting under simulated sunlight for over 2 h and generates hydrogen at a stabilized rate of 1.3 µmol h−1 cm−2, which corresponds to a solar-to-hydrogen conversion efficiency of 0.1%. Solar water splitting offers a route to renewable hydrogen, but developing photocatalyst sheets from scalable, solution-processable materials remains a challenge. Here the authors use underlayer engineering to build an organic semiconductor photocatalyst sheet that enables unassisted overall water splitting under simulated sunlight.
Rapid artificial intelligence growth is driving energy-intensive data centre expansion, but its consequences for energy burdens and household welfare remain understudied. Here we show how data centre expansion asymmetrically deepens energy burdens across the USA through different channels, using causal analysis of price records, together with transmission plans and regulatory cost-allocation dockets. In wholesale markets, cumulative price increases attributable to data centres exceed 10% in the most exposed hubs by 2025. In regulated tariffs, residential users are allocated a median of 47% of costs despite contributing far less to demand growth. These channels produce compounding asymmetric energy burdens. Spatially, cost sharing forces rural communities to bear burden increases 76% larger than urban communities. Economically, the lowest-income households face extra energy burdens up to 28 percentage points. Fiscally, local economic returns are almost unrelated to spending, with a spending elasticity of 0.16. The states absorbing the largest energy burden increases capture the smallest returns. As data centres increase pressure on power systems, the costs of accommodating their growth are becoming a concern. Here the researchers show that data centres raise wholesale prices and shift transmission costs onto households, with the largest burden increases in rural and low-income communities.
