Facultad de Ingeniería en Tecnología de la Madera, Universidad Michoacana de San Nicolás de Hidalgo, Edif. D. Cd. Universitaria, Santiago Tapia No. 403, Centro, Morelia 58000, Mexico.
Instituto de Investigaciones Económicas y Empresariales, Universidad Michoacana de San Nicolás de Hidalgo, Edif. D. Cd. Universitaria, Santiago Tapia No. 403, Centro, Morelia 58000, Mexico.
Molecules. 2024 May 31;29(11):2587. doi: 10.3390/molecules29112587.
Diverse methodologies exist to determine the chemical composition, proximate analysis, and calorific value of biomass. Researchers select and apply a specific methodology according to the lignocellulosic material they study and the budgetary resources available. In this project, we determined the primary chemical constitution and proximate analysis of (Humb. & Bonpl.) Jonhst wood using a traditional chemical method and a novel procedure based on the deconvolution of the DTG signal produced by TGA. The highest calorific value was verified using a calorimetric pump based on mathematical models. We also conducted elemental analysis and a microanalysis of ash, and applied Fourier transform infrared spectroscopic analysis (FT-IR). The means of the results obtained by the chemical method and TGA-DTG, respectively, were: hemicelluloses 7.36%-(8.72%), cellulose 48.28%-(46.08%), lignin 30.57%-(32.44%), extractables 13.53%-(12.72%), moisture 2.03%-(4.96%), ash 1.77%-(1.90%), volatile matter 75.16%-(74.14%), and fixed carbon 23.05%-(18.93%). The procedure with the calorimetric pump generated a calorific value above 20.16 MJ/kg. The range generated by the various models was 18.23-21.07 MJ/kg. The results of the elemental analysis were: carbon 46.4%, hydrogen 6.79%, oxygen 46.43%, nitrogen 0.3%, and sulfur 0.5%. The microanalysis of ash identified 18 elements. The most abundant ones were potassium ˃ calcium ˃ sodium. Based on the infrared spectrum (FT-IR) of wood, we detected the following functional groups: OH, C-H, C=O, CH CH, C-O-C, C-OH, and C4-OH. Our conclusion is that the TGA-DTG method made it possible to obtain results in less time with no need for the numerous reagents that chemical procedures require. The calorific value of wood is higher than the standards. Finally, according to our results, proximate analysis provides the best model for calculating calorific value.
存在多种方法来确定生物质的化学成分、近似分析和热值。研究人员根据他们研究的木质纤维素材料和可用的预算资源选择和应用特定的方法。在这个项目中，我们使用传统的化学方法和基于 TGA 产生的 DTG 信号解卷积的新程序来确定 （Humb. & Bonpl.）Jonhst 木材的主要化学组成和近似分析。最高热值通过基于数学模型的量热泵进行验证。我们还进行了元素分析和灰分的微观分析，并应用了傅里叶变换红外光谱分析（FT-IR）。化学方法和 TGA-DTG 分别获得的结果的平均值为：半纤维素 7.36%-(8.72%)、纤维素 48.28%-(46.08%)、木质素 30.57%-(32.44%)、提取物 13.53%-(12.72%)、水分 2.03%-(4.96%)、灰分 1.77%-(1.90%)、挥发物 75.16%-(74.14%)和固定碳 23.05%-(18.93%)。量热泵产生的热值超过 20.16 MJ/kg。各种模型产生的范围为 18.23-21.07 MJ/kg。元素分析的结果为：碳 46.4%、氢 6.79%、氧 46.43%、氮 0.3%和硫 0.5%。灰分的微观分析鉴定出 18 种元素。最丰富的是钾˃钙˃钠。基于 木材的红外光谱（FT-IR），我们检测到以下官能团：OH、C-H、C=O、CH CH、C-O-C、C-OH 和 C4-OH。我们的结论是，TGA-DTG 方法使得在不需要化学方法所需的大量试剂的情况下，能够更快地获得结果。 木材的热值高于标准。最后，根据我们的结果，近似分析为计算热值提供了最佳模型。
