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微波辐射预处理小球藻生物质发酵生产生物乙醇:响应面法和人工神经网络技术的比较分析。

Microwave irradiation pretreated fermentation of bioethanol production from Chlorella vulgaris Biomasses: Comparative analysis of response surface methodology and artificial neural network techniques.

机构信息

Engine Testing Laboratory, School of Mechanical Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India.

Engine Testing Laboratory, School of Mechanical Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India.

出版信息

Bioresour Technol. 2023 Dec;390:129867. doi: 10.1016/j.biortech.2023.129867. Epub 2023 Oct 12.

Abstract

Bioethanol is a promising biofuel for replacing gasoline due to its sustainability. This work uses microwave irradiation and acid hydrolysis to produce bioethanol from Chlorella vulgaris. The hydrolysis procedure used 1%-3% sulfuric acid (HSO). The maximum output of reducing sugar was 6.773 g/L after 5 min of irradiation. This study used RSM and ANN to optimize bioethanol production. The study predicted bioethanol yield using three factors: fermentation duration (12-36 h), temperature (28-32 °C), and inoculum concentration (0.5-1.5 g/L). The highest bioethanol yield was achieved using fermentation conditions of 36 h, 30 °C temperature, and 1.5 g/L inoculum concentration. The ANN model predicted the best ethanol output compared to the RSM model. The leftover biomass from biofuel synthesis was characterized for its potential for other energy production. The current study examined the feasibility of employing biomass in an environmentally sustainable manner to enhance the production of biofuels.

摘要

生物乙醇是一种有前途的生物燃料,可替代汽油,因为它具有可持续性。本工作使用微波辐射和酸水解从普通小球藻中生产生物乙醇。水解过程使用 1%-3%的硫酸(HSO)。经 5 分钟辐射后,还原糖的最大产量为 6.773 g/L。本研究使用 RSM 和 ANN 来优化生物乙醇的生产。该研究使用三个因素预测生物乙醇的产量:发酵时间(12-36 小时)、温度(28-32°C)和接种物浓度(0.5-1.5 g/L)。在发酵时间 36 小时、温度 30°C 和接种物浓度 1.5 g/L 的条件下,生物乙醇的产量最高。与 RSM 模型相比,ANN 模型预测的最佳乙醇产量更高。对生物燃料合成后的剩余生物质进行了表征,以研究其在其他能源生产方面的潜力。本研究探讨了以环境可持续的方式利用生物质来提高生物燃料产量的可行性。

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