优化和预测罗达胺B吸收到功能化甘包生物炭:基于Krill Herd算法的ANN建模方法

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Neelaambhigai Mayilswamy¹, Balasubramanian Kandasubramanian², Tushar Warjurkar³

¹Department of Metallurgical and Materials Engineering, Defence Institute of Advanced Technology, Girinagar, Pune, Maharashtra, 411025, India.

Environmental science and pollution research international

|July 2, 2025

概括

用氧化处理的甘包生物炭有效地从废水中去除罗达胺B染料. 人工神经网络建模准确预测染料吸附,支持清洁水目标.

科学领域:

环境化学环境化学
材料科学材料科学材料科学
可持续工程可持续工程

背景情况:

织工业的废水通常含有像罗达胺B (RhB) 这样的持久染料.
传统的废水处理方法难以有效地去除染料.
开发可持续吸附剂对于环境保护和联合国可持续发展目标至关重要.

研究的目的:

调查氧化功能化甘包生物炭 (NaOH-SBB) 对罗达胺B染料脱色的疗效.
描述合成的NaOH-SBB吸附剂的物理化学特性.
开发和验证人工神经网络 (ANN) 模型,用于预测染料吸附能力.

主要方法:

使用先进技术合成和描述NaOH-SBB生物炭.
染料吸附实验以确定吸附能力 (qmax).
通过Krill Herd和Levenberg Marquardt反向传播 (LM) 算法优化的ANN建模,以预测吸附性能.

主要成果:

在15 ppm的RhB度下,NaOH-SBB的最大Langmuir吸附能力 (qmax) 为4.8309 mg/g.
该ANN模型显示了高预测准确度,R=0.9531和R2=0.9726.
低误差指标 (MSE: 0.5669,MAE: 0.3884,RMSE: 0.7542) 证实了该模型的可靠性.

结论:

NaOH-SBB是一种有前途的吸收剂,用于从废水中去除Rhodamine B染料.
开发的ANN模型有效地预测着染料吸附,验证了它的可靠性和效率.
这项研究有助于可持续的废水处理,并与联合国关于清洁水和健康的可持续发展目标保持一致.

关键词:

在ANN建模中使用ANN建模.吸附方式是异热的.吸附机制是一种吸附机制.的功能化生物炭.克里尔群群算法优化优化算法罗达胺 B 类型的罗达胺

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