Clean coal technology is the important thrust to the achievement of "carbon neutralization"; clearing the transformation mechanism of thiophene, the dominant organic sulfur species in coal, is conducive to promoting the development of sulfur removal technology. DFT calculations were performed, and 28 reaction paths were proposed in this research, clarifying the decomposition mechanism of thiophene and the fixation mechanism of H₂S. Thiophene is pyrolyzed mainly through the hydrogen-transfer reaction, which occurs at above 2000 K rather than 800 K. The hydrogen transfer between the C-C bond rather than the C-S bond causes the ring opening. Hydrogen promotes the decomposition of thiophene, which happens at 800 K, with a molar ratio of hydrogen to thiophene of 5. Therefore, thiophene is decomposed at 800 K mainly through the hydrogenation reaction that occurs at para carbons and the C-S bond, the H₂S elimination reaction, and the generation of ethane. Furthermore, H₂S can be converted into thiophene through the addition reaction with unsaturated hydrocarbon, or the dehydration reaction with hydroxyl or carboxyl groups. The combination between H₂S and the aliphatic compound occurs at 800 K, which is mainly influenced by the species of the functional group rather than the composition and morphology of the carbon chain. Meanwhile, the conversion of aromatic compounds tends to the generation of aryl mercaptan rather than thiophene at around 800 K.

In this study, an experiment is conducted to explore the potential to protect both the environment and resource shortage of soybean straw, for combustion in a tubular furnace. Then, the combustion characteristics, gas emissions, and energy consumption of soybean straw are analyzed at a combustion temperature range of 773–1173 K. The results show that the total emissions of CO and NO_X are the largest at a temperature of 873 K. For NO_X, the emission time is significantly improved at temperatures of 973–1173 K. At high temperatures, the reaction of NO_X with CO and coke reduces the total emission of NO_X. The average weight loss rate at combustion temperatures of 973, 1073, and 1173 K increased by 27.38%, 61.47% and 77.97%, respectively, relative to that of 873 K. However, the energy consumption increases with the increase in combustion temperature, resulting in unnecessary waste. To get an optimal characteristic between energy utilization and pollutant discharge, a temperature range of 873–973 K is determined as the appropriate temperature for burning soybean straw.

To investigate the aerodynamic performance of exhaust passage under multi-phase flow, an actual case is conducted in the low-pressure double exhaust passages of 600 MW steam turbine. Then, the flow field is compared and analyzed with and without the built-in extraction pipelines based on the Eulerian–Eulerian homogenous medium multiphase method. Results show that the upstream swirling flow and downstream mixed swirling flow are the main causes to induce the entropy-increase in the exhaust passage. Moreover, the flow loss and static-pressure recovery ability in the exhaust hood are greater than those in the condenser neck. Compared with the flow field without the steam extraction pipelines, the entropy-increase increases, the static pressure recovery coefficient decreases, and the spontaneous condensation rates of wet steam decrease in the downstream area of the pipelines. With the increase of steam turbine loads, an increment in entropy-increase in the exhaust passage is 0.98 J/(kg·K) lower than that without steam extraction pipelines. Moreover, the incrementing range of uniformity coefficient is increased from 14.5% to 40.9% at the condenser neck outlet. It can be concluded that the built-in exhaustion pipeline can improve the aerodynamic performance of exhaust passage and better reflect the real state of the flow field. These research results can serve as a reference for turbine passage design.

The thermal degradation characteristics of microalgae were investigated in highly purified N₂ and CO₂ atmospheres by a thermogravimetric analysis (TGA) under different heating rates (10, 20, and 40°C/min). The results indicated that the total residual mass in CO₂ atmosphere (16.86%) was less than in N₂ atmosphere (23.12%); in addition, the kinetics of microalgae in N₂ and CO₂ atmospheres could be described by the pseudo bicomponent separated state model (PBSM) and pseudo-multi-component overall model (PMOM), respectively. The kinetic parameters calculated by Coats-Redfern method showed that, in CO₂ atmosphere, the apparent activation energy (E) of microalgae was between 9.863 and 309.381 kJ mol⁻¹ and the reaction order (n) was varied from 1.1 to 7. The kinetic parameters (E,n) of the second stage in CO₂ atmosphere were quite similar to those in N₂ atmosphere.

Biomass energy is recognized as a clean and sustainable energy source and is leveraged as a key enabler for driving the low-carbon transition of the energy system and achieving sustainable development. The higher heating value of solid biomass fuels (HHV-SBF) is a key parameter in its catalytic conversion process, and HHV-SBF is of great significance for catalyst design and matching, as well as the selection of reaction process parameters. To address the limitations in accuracy and generalization capability of traditional prediction methods for estimating the HHV-SBF, a dataset is constructed in this study that correlates chemical elements, proximate analysis parameters, and biochemical components with the HHV-SBF. Key hyperparameters of the deep neural network (DNN) are optimized using the Bayesian optimization algorithm. A Bayesian optimization-based deep neural network (BO-DNN) model is developed for the intelligent prediction of the HHV-SBF. Results show that the coefficient of determination (R²) of the BO-DNN model reaches 92.6%. Compared to multiple mainstream deep learning algorithms, its performance is improved by approximately 11.61%, and the mean square error is significantly reduced. The BO-DNN model demonstrates excellent generalization capability and stability. The findings of this study provide a theoretical basis for the rapid and accurate prediction of the HHV-SBF.