From Algorithms to Green Growth: Can Artificial Intelligence Drive Enterprise Energy Transformation?

Economic Analysis and Policy, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Language: Английский

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Insights into Synthesis and Optimization Features of Reverse Osmosis Membrane Using Machine Learning

Materials, Journal Year: 2025, Volume and Issue: 18(4), P. 840 - 840

Published: Feb. 14, 2025

Reverse osmosis membranes have been predominantly made from aromatic polyamide composite thin-films, although significant research efforts dedicated to discovering new materials and synthesis technologies enhance the water-salt selectivity of in past decades. The lack breakthroughs is partly attributed limited comprehensive understanding relationships between membrane features their performance. Insights into intrinsic reverse (RO) based on metadata were obtained using explainable artificial intelligence understand unify efforts. related chemistry, structure, modification methods, performance RO derived dataset more than 1000 membranes. Seven machine learning (ML) models constructed evaluate performances, applicability for tasks was assessed metadata. contribution analyzed, ranking importance revealed. This work holds promise analysis, evaluating against state art developing an inverse design strategy discovery high-performance

Language: Английский

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The nexus of artificial intelligence and sustainability performance: Unveiling the impact of supply chain transparency and customer pressure on ethical conduct

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 379, P. 124847 - 124847

Published: March 6, 2025

Language: Английский

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The Evolving Landscape of Advanced Oxidation Processes in Wastewater Treatment: Challenges and Recent Innovations

Processes, Journal Year: 2025, Volume and Issue: 13(4), P. 987 - 987

Published: March 26, 2025

The increasing presence of persistent pollutants in industrial wastewater underscores the shortcomings conventional treatment methods, prompting adoption advanced oxidation processes (AOPs) for sustainable water remediation. This review examines development AOPs, focusing on their ability to produce hydroxyl radicals and reactive oxygen species (ROS) mineralize complex pollutants. Homogeneous systems such as Fenton’s reagent show high degradation efficiency. However, challenges like pH sensitivity, catalyst recovery issues, sludge generation, energy-intensive operations limit scalability. Heterogeneous catalysts, TiO2-based photocatalysts Fe3O4 composites, offer improved adaptability, visible-light activation, recyclability. Emerging innovations ultraviolet light emitting diode (UV-LED)-driven systems, plasma-assisted oxidation, artificial intelligence (AI)-enhanced hybrid reactors demonstrate progress energy efficiency process optimization. Nevertheless, key remain, including secondary byproduct formation, mass transfer constraints, economic feasibility large-scale applications. Integrating AOPs with membrane filtration or biological treatments enhances synergy, while advances materials science computational modeling refine design reaction mechanisms. Addressing barriers use, durability, practical adaptability requires multidisciplinary collaboration. highlights pivotal solutions security amid growing environmental pollution, urging targeted research bridge gaps between laboratory success real-world implementation.

Language: Английский

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Casuarina seed-packed biofilter for the treatment of gaseous mixture: performance, optimization, synergistic effects, neural model analysis, and kinetics

Journal of environmental chemical engineering, Journal Year: 2025, Volume and Issue: unknown, P. 116689 - 116689

Published: April 1, 2025

Language: Английский

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Artificial Intelligence and Green Collaborative Innovation: An Empirical Investigation Based on a High-Dimensional Fixed Effects Model

Sustainability, Journal Year: 2025, Volume and Issue: 17(9), P. 4141 - 4141

Published: May 3, 2025

This study focuses on the intrinsic mechanisms and sustainable value of artificial intelligence (AI)-driven green collaborative innovation in enterprises amid global low-carbon transition, revealing new pathways for digital technology-enabled development. Based data China’s A-share listed companies jointly applying patents with other entities from 2010 to 2023, this used a high-dimensional fixed effect model empirically find that significantly promotes innovation. promoting proved more pronounced case high macroeconomic uncertainty, large SOEs. A mechanism test revealed drives primarily by reducing transaction costs optimizing labor structure. moderating analysis showed investor entry CEO openness can strengthen facilitating In addition, helps reduce carbon emissions improve ESG performance, driving transformation business ecosystems toward environmental sustainability. From technology–organization–environment co-evolution perspective, research clarifies micro-level operational chain AI-enabled innovation, providing theoretical support developing countries achieve leapfrog transitions through technologies. Practically, it offers actionable insights advancing industries, constructing ecosystems, supporting realization United Nations Sustainable Development Goals (SDGs).

Language: Английский

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Turning trash into treasure: Exploring the potential of AI in municipal waste management - An in-depth review and future prospects

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 373, P. 123658 - 123658

Published: Dec. 9, 2024

Language: Английский

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