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Artificial intelligence is profoundly influencing various facets of our lives, indicating its potential to significantly impact sustainability. Nevertheless, capturing the productivity gains stemming from artificial intelligence in macro-level data poses challenges, leading to the question of whether artificial intelligence is reminiscent of the “Solow paradox”. This study employs micro-level manufacturing data to investigate the impact of artificial intelligence on firms’ productivity. The study finds that every 1% increase in artificial intelligence penetration can lead to a 14.2% increase in total factor productivity. This conclusion remains robust even after conducting endogeneity analysis and a series of robustness tests. The study identifies that the positive impact of artificial intelligence on productivity is primarily achieved through the value-added enhancement effect, skill-biased enhancement effect, and technology upgrading effect. Furthermore, the study reveals that the effects of artificial intelligence on productivity vary across different property rights and industry concentration contexts. Additionally, the structure of factor endowments within firms can also influence the productivity gains from artificial intelligence. Our study presents compelling evidence demonstrating the role of artificial intelligence in fostering economic sustainability within the framework of Industry 4.0.

A new method to dope Fe 3+ ions only onto the surface of S- or N-doped TiO 2 is proposed. The photocatalytic activities of Fe 3+ ions adsorbed on S- or N-doped TiO 2 photocatalysts for oxidation of 2-propanol are markedly improved compared to those of S- or N-doped TiO 2 without treatment of Fe 3+ ions under a wide range of incident light wavelengths, including UV light and visible light. When the amount of Fe 3+ ions adsorbed on S-doped TiO 2 particles was 0.90 wt.%, photocatalytic activity reached maximum. In the case of N-doped TiO 2 with Fe 3+ ions, the optimum amount of Fe 3+ ions was 0.36 wt.%. The photocatalytic activities of Fe 3+ ions adsorbed on S- or N-doped TiO 2 photocatalysts decreased gradually when the amount of Fe 3+ ions was greater than 1.0 wt.%. In addition, when S- or N-doped TiO 2 photocatalysts adsorbed with Fe 3+ ions was observed after reduction by NaBH 4 followed by air oxidation, further improvement in their photocatalytic activities were observed. In this case, the optimum amounts of Fe 3+ adsorbed on the surfaces of S- and N-doped TiO 2 photocatalysts were 2.81 and 0.88 wt.%, respectively. During the treatment, Fe 3+ ions adsorbed on S- or N-doped TiO 2 were reduced to generate metal Fe, and Fe was reoxidized again to form Fe 3+ ions under an aerated condition. After the treatment, the crystal structure of Fe 3+ ions adsorbed on S-doped TiO 2 and adsorbtivity of 2-propanol on the photocatalyst were changed.