Hydrothermal liquefaction (HTL) is an effective biomass thermochemical conversion technology that can convert organic waste into energy products. However, the HTL process is influenced by various complex factors such as operating conditions, feedstock properties, and reaction pathways. Machine learning (ML) methods can utilize existing HTL data to develop accurate models for predicting product yields and properties, which can be used to optimize HTL operation conditions. This paper presents a bibliometric review on ML applications in HTL from 2020 to 2024. CiteSpace, VOSviewer, and Bibexcel were used to analyze seven key bibliometric attributes: annual publication output, author co-authorship networks, country co-authorship networks, co-citation of references, co-citation of journals, collaborating institutions, and keyword co-occurrence networks, as well as time zone maps and timelines, to identify the development of ML in HTL research. Through the detailed analysis of co-occurring keywords, this study aims to identify frontiers, research gaps, and development trends in the field of ML-aided HTL.

The corrosion behavior of X70 steel under the coupling effect of pressure and erosion in simulated seawater was investigated by using corrosion loss, electrochemical tests, SEM, AFM, XPS, and Raman spectroscopy. The coupling effect of pressure and erosion could induce changes in the amounts and compositions of the corrosion products and increase pitting. The rate of the combined corrosion of X70 steel represents a downtrend, which still displays a higher corrosion rate than only immersion at the same pressure. This means that the coupling of pressure and erosion will accelerate corrosion, but the effect of erosion is weakened by pressure. The larger the pressure is, the more erosion is weakened. The pressure reduces the water cutting force by increasing the liquid viscosity and reduces the surface hardness changes under high pressure by generating magnetite, which is closely bound to the substrate.

The early formation of phosphate oxide formed on 316 stainless steel (316 SS), nickel-based Alloy 625, and titanium alloy TA8 exposed in supercritical water (400 °C, 25 MPa) containing phosphate, chloride, and oxygen was investigated. Phosphate corrosion products of austenitic stainless steel displayed the severest spallation. Stable phosphates oxide films were inclined to form on Alloy 625. TiO₂ and Ti₂O₃ are the two main components of oxide films on TA8. There is a strong synergistic effect between phosphates, oxygen, and supercritical water, leading to severe corrosion. The corrosion behavior of the three alloys at the top and bottom of the reaction tube was compared. Both at the top of the reaction tube and at the bottom of the reaction tube, TA8 showed an increase in mass. 316 SS and alloy 625 showed mass gain at the top and mass loss at the bottom. The alloys’ detailed molten corrosion mechanism after exposure to supercritical water is discussed.

Hydrothermal liquefaction (HTL) and supercritical water gasification (SCWG) are promising technologies for clean renewable energy production from biomass. This study investigated the process and mechanism of water hyacinth treatment by HTL and SCWG to prepare clean biodiesel and combustible gas. The optimal HTL reaction conditions were 350°C, 50 min, 20 wt % stock concentration, and 0.60 g/mL water density. The liquid products were analyzed by Gas chromatograph-mass spectrometer and infrared radiation spectra analysis. The fat was hydrolyzed into fatty acids and the fatty acid decarboxylate formed alkanes. The protein undergoes C-N peptide bond hydrolysis and Maillard reaction with aldose to form ketones and nitrogenous compounds. The polysaccharides were hydrolyzed and cycled to form phenols. The optimal SCWG reaction conditions were 480°C, 20 min, 23.10% stock concentration, and a pressure between 25 and 27 MPa. The effects of process parameters on the content of H₂ and CH₄ in the gas products were studied. This work is helpful for resource utilization of water hyacinth hydrothermal treatment. The energy conversion efficiency of SCWG of water hyacinth in this experiment is lower compared with HTL.