This paper investigates the use of Fourier transform infrared spectroscopy (FT-IR) for quantitative analysis of bio-crudes from hydrothermal liquefaction (HTL) of biomass. HTL is a versatile process rendering virtually all biomasses suitable for conversion into bio-crude and side-streams. However, continuous processes require rapid analytical methods applicable to highly diverse bio-crudes. Bio-crudes were obtained from two different continuous HTL reactors (lab scale and pilot scale) and in some cases with recirculation of water. The bio-crudes originated from a diverse range of feedstocks including lignocellulosics (pine, Miscanthus), microalgae (Spirulina, Chlorella vulgaris), and residues (sludge, dried distiller grains with solubles). Quantitative analysis of water content, total acid number, and total content of phenolics was performed using FT-IR. Principal component analysis indicated a potential correlation between quantitative measurements and FT-IR. Partial least-squares regression was used to develop predictive models that performed well considering the high diversity of the bio-crudes. The content of phenolics was in the range of 83.1–254.6 mg g^–1 (gallic acid equivalent), and the model calibration was good (Root Mean Square Error, RMSE = 19.7, slope = 0.81, y-exp = 81.2%). A diverse set of test samples were subjected to the models. The relative difference for measured and predicted phenolic content was generally <15%. Total acid numbers (TAN) were 7–98 mg_KOH g^–1, and the model calibration was found to be satisfactory considering the titration method used (RMSE = 18.5, slope = 0.53, y-exp = 52.6%). The relative difference for measured and predicted TAN was generally <20%. The water content (Karl Fischer titration) was 1–24%, and the model calibration was very good (RMSE = 2.0, slope = 0.93, y-exp = 92.6%). The water content was generally predicted within 1.5%, and the relative difference for measured and predicted water content was large (2.7–16.6%) due to the small values. All models included samples that deviated and could be considered outliers; however, their deviations were explained from their composition and were retained in the models. Overall, the results show the potential of FT-IR as a universal technique to obtain rapid quantitative results from a variety of bio-crudes processed using different reactors.

中文翻译：

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红外光谱法快速测定生物质水热液化过程中生物原油中的水，总酸值和酚含量

本文研究了利用傅里叶变换红外光谱（FT-IR）定量分析生物质的水热液化（HTL）中的生物原油的方法。HTL是一种多用途的过程，几乎使所有生物质都适合转化为生物原油和支流。但是，连续过程需要适用于高度多样化的生物原油的快速分析方法。从两个不同的连续HTL反应器（实验室规模和中试规模）中获得了生物粗品，在某些情况下还利用了水的再循环。该生物原油源自多种原料，包括木质纤维素（松树，芒草），微藻类（螺旋藻，小球藻））和残留物（淤泥，干酒糟和可溶物）。使用FT-IR进行水含量，总酸值和酚醛总含量的定量分析。主成分分析表明定量测量和FT-IR之间存在潜在的相关性。考虑到生物原油的高度多样性，使用偏最小二乘回归来开发预测模型，该模型表现良好。酚类化合物的含量在83.1–254.6 mg g ^-1（没食子酸当量）的范围内，并且模型校准良好（均方根误差，RMSE = 19.7，斜率= 0.81，y-exp = 81.2％）。对各种测试样本进行模型处理。测量和预测的酚含量的相对差异通常<15％。总酸值（TAN）为7–98 mg _KOH g ^–1，考虑到所使用的滴定方法，模型校准令人满意（RMSE = 18.5，斜率= 0.53，y -exp = 52.6％）。测量和预测的TAN的相对差异通常<20％。含水量（卡尔·费休滴定法）为1–24％，模型校准非常好（RMSE = 2.0，斜率= 0.93，y-exp = 92.6％）。通常将水含量预测在1.5％以内，由于测量值和预测水含量的相对值较小，因此其相对差异较大（2.7–16.6％）。所有模型都包含有偏差的样本，可以认为是离群值；但是，它们的偏差已从其组成中得到解释，并保留在模型中。总体而言，结果表明，FT-IR作为一种通用技术具有潜力，可以从使用不同反应器处理的多种生物原油中获得快速定量结果。