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Published on: August 17, 2016
Sustainable and Energy-Efficient Hydrogen Generation from NaBH4 Methanolysis Enabled by Nb2O5 Synthesized through a
Fábio C Riemke1, Cristiane Raubach1, Bruno Noremberg1
1Programa de Pós-Graduação em Ciência e Engenharia de Materiais, Centro de Desenvolvimento Tecnológico, Universidade Federal de Pelotas, Pelotas, RS 96010-000, Brasil.
Abstract:
A pressureless microwave-assisted hydrothermal route is presented for the synthesis of highly active amorphous niobium pentoxide (Nb2O5·nH2O) nanostructures and their application as metal oxide catalysts for hydrogen generation via sodium borohydride methanolysis. The synthesis, conducted at sub-boiling temperature (75 °C) under open-vessel conditions, produces a microporous Nb2O5 material with a very high specific surface area (230 m2 g-1), abundant surface hydroxyl groups, and a predominance of weak-to-moderate acidic sites. Structural and surface analyses reveal a disordered NbO6 network enriched with terminal NbO species and undercoordinated oxygen environments, which are absent in crystalline commercial Nb2O5. In NaBH4 methanolysis, the amorphous Nb2O5 catalyst achieves a hydrogen generation rate of 22,781.7 mL min-1 g-1 at 25 °C with a low apparent activation energy of 21.95 kJ mol-1, outperforming many reported noble-metal-based catalysts. Reaction kinetics follow a first-order dependence on NaBH4 concentration, and the catalyst maintains stable activity over multiple reuse cycles. In addition, machine learning-assisted analysis was employed to process particle segmentation data and correlate morphological descriptors with catalytic performance, enabling quantitative assessment of particle size distributions, skewness, kurtosis, and aggregation behavior. These data-driven insights corroborate the experimentally observed structure-activity relationships, linking controlled nucleation under microwave irradiation to enhanced catalytic efficiency. The results establish amorphous Nb2O5 as a cost-effective and sustainable catalyst for on-demand hydrogen generation and highlight pressureless microwave synthesis combined with machine learning as a powerful framework for rational catalyst design.
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