热解机制研究通过结合实验,化学反应神经网络和密度函数理论来研究粉
Yu Zhong1, Wei Gao2, Changhai Li2
1Faculty of Engineering, China University of Geosciences, Wuhan 430074, China; Institute for Natural Disaster Risk Prevention and Emergency Management, China University of Geosciences, Wuhan 430074, China.
Bioresource technology
|April 13, 2025
概括
这项研究将化学反应神经网络 (CRNN) 和密度函数理论 (DFT) 整合起来,以阐明二氧化硫溶解. 它揭示了西洛斯最容易发生环开反应,推进了半纤维素溶解模型.
科学领域:
- 生物质热解是生物质的热解.
- 化学动力学 化学动力学
- 计算化学是一种计算化学.
背景情况:
- 生物质热解机制通常基于单一的方法和专家知识.
- 克西洛斯是一种模范性半纤维素化合物,对于理解生物质分解至关重要.
- 为了有效的生物质转化,需要准确的运动模型.
研究的目的:
- 通过多方法方法来研究氧化糖的热解机制.
- 开发和验证一个化学反应神经网络 (CRNN) 模型用于酸盐热解.
- 用密度函数理论 (DFT) 阐明详细的反应路径和能量障碍.
主要方法:
- 热重力测量-里埃变换红外光谱学 (TG-FTIR) 用于产品识别.
- 化学反应神经网络 (CRNN) 用于动态建模.
- 密度函数理论 (DFT) 用于反应路径和能量屏障计算.
主要成果:
- 建立了一个具有8个物种和10个反应的CRNN模型,实现了高精度 (MAE < 2x10^-2).
- DFT计算提供了对反应路径和潜在能量表面的详细见解.
- 确定了环开放,环凝结和脱水的激活能量 (152.78,485.81,320.01 kJ/mol).
- CRNN的结果显示与DFT计算的良好一致 (偏差<37%).
结论:
- 氧化最容易发生环开反应,形成d-氧化.
- d-酸盐经历进一步的反应,如半乙化,异构化和脱水.
- 通过循环凝结形成furfural也是一个关键的途径.
- 这些发现增强了半纤维素热解运动模型,并为其他生物质热解研究提供了洞察力.
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