Cidong Jiang , Pengjun Chen , Yu Cheng , Qiang Liu , Chenping Deng , Halefom G. Desta , Dong Tian , Bin Lin
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引用次数: 0
Abstract
The sustainable valorization of coal gangue, a significant industrial byproduct, represents an urgent environmental challenge and opportunity for resource recovery. Herein, we report a machine learning-optimized hydrothermal synthesis of high-purity NaP zeolite directly from untreated coal gangue for developing an efficient phosphorus slow-release fertilizer. Through precise control of crystallization parameters (160 °C, 36 h in 2 mol L−1 NaOH), spherical NaP zeolite crystals with uniform morphology and exceptional structural integrity were achieved without energy-intensive pre-calcination steps. Phosphorus nutrient loading via mechanical activation created a composite with controlled release kinetics, demonstrating a cumulative P release of only 39.4% over 30 days—significantly lower than conventional fertilizers. Mechanistic analysis revealed a biphasic release profile characterized by an initial burst (first week) followed by sustained nutrient delivery, directly attributable to the unique pore architecture of NaP zeolite (pore dimensions: 0.31 × 0.44 nm and 0.26 × 0.49 nm). In comparative rice cultivation studies, plants treated with our zeolite-based fertilizer exhibited 45.2% longer root systems than urea-treated seedlings despite lower initial shoot growth, indicating preferential allocation of resources to root development. This work establishes a closed-loop strategy for transforming coal waste into high-value agricultural materials while addressing critical challenges in nutrient management and environmental sustainability. Our machine learning approach to parameter optimization provides a blueprint for accelerating discovery in sustainable resource recovery.