The use of bio-based composites to enhance the methane production in anaerobic digestion has attracted considerable attention. Nevertheless, the study of electron transfer mechanisms and the applications of biochar/MnO2 (MBC) in complex systems remains largely unexplored. Biochar composited with MnO2 at 10:1 mass ratio (MBC10) increased the content of volatile fatty acids by 9.09 % during acidogenic phase. During the methanogenic experiments using acetate, cumulative methane production (CMP) rose by 5.83 %, and in the methanogenic experiments using food waste, CMP increased by 24.32 %. Microbial community analysis indicated an enrichment of Syntrophomonas, Bacilli, and Methanosaetaceae in the MBC10 group. This enrichment occurred mainly due to the redox capability of MnO2 enhancing MBC capacitance, thereby facilitating microbial electron transfer processes. Additionally, under 2 g/L ammonia nitrogen concentration and 30 g/L organic load, the CMP of MBC10 increased by 12.74 % and 9.44 %, respectively, compared to the BC600 group. This study illuminates MBC's electron transfer mechanisms and applications, facilitating its wider practical adoption and fostering future innovations.

Humic acids (HAs), whether naturally present in anaerobic digestion (AD) substrates or HAs newly formed during fermentation, can become inhibitory to methanogenesis as their concentrations reach certain levels. This study delved extensively into the mechanism underlying the alleviation of HAs inhibition in photo-AD by Ndoped carbon quantum dots (NCQDs). These NCQDs were efficiently synthesized from straw using an environmentally friendly pretreatment method. Our proposed method harnessed the combined effect of light exposure and NCQDs, resulting in synergistic enhancement of the cumulative CH4 yield within the HA-inhibited AD system, achieving a remarkable yield of 293.7 +/- 17.7 mL/g VS. In-depth analyses were conducted on the remaining dissolved organic matter (DOM) within digesters using 3D-EEM and ESI FT-ICR MS. Simultaneously, the remaining HAs were extracted and subjected to FT-IR analysis. The findings revealed that NCQDs effectively degraded humic acid-like components in DOM into smaller, more manageable micromolecules characterized by lower carbon numbers and reduced double bond equivalent. Additionally, under the influence of light, NCQDs promoted the degradation of aromatic components within HAs. These resulting micromolecules were made readily available for utilization by microorganisms, further contributing to methanogenesis. Furthermore, photoelectrochemical analysis and specific gene qPCR analysis revealed that the photoelectrons from NCQDs and HAs were received and transferred by Ech (electron acceptors) for methanogenesis. Remarkably, this methanogenesis pathway, akin to photosynthesis, played a pivotal and transformative role in the photo-AD system. This work comprehensively revealed the remarkable potential mechanism of semiconductors within the photoAD system, offering profound insights that can catalyze the development of innovative AD reactors and semiconductor accelerators.

Monophenols form humic acids (HA) through polycondensation reaction in the anaerobic digestion (AD) process, which will inhibit AD process. Currently, metal ions are the option for in-situ relieving HA inhibition during AD, but excess metal ions are harmful to microorganisms. In this study, carbon quantum dots (CQDs, a non-metallic materials) were proposed to relieve HA inhibition in-situ. We investigated the effect of HA on AD acidification and methanation stage, and synthesized CQDs using sodium citrate (s-CQDs) and p-phenylenediamine (p-CQDs) as precursors to relieve the HA inhibition in-situ. Results showed that s-CQDs (3.0 g/L) significantly increased the cumulative CH4 yield from AD of ethanol with 1.0 g/L HA (1.9 times higher than that without s-CQDs). Microbiological analysis indicated the most dominant methanogen was Methanosarcinaceae, with richness of 89.7%. Compared to the HA inhibition system, the relative abundance of Methanosarcinaceae increased by 87.5%. The analysis of interaction mechanism between CQDs and HA indicated that s-CQDs has an in-situ binding effect to HA by reacting with -OH, CC, and -COOH. This study provided a novel means for in-situ relieving HA inhibition, and illustrated the interaction mechanism between CQDs and HA, which will guide the application in production of bioenergy.

The treatment of organic waste (OW) by anaerobic digestion (AD) conforms to the concept of sustainable development. But AD is facing the issue of low conversion rate. In this work, the photo-AD system using visible light (LED lamp) as the source was constructed and the performances and mechanism of N-doped carbon quantum dots (NCQD) were explored in the system for the first time. The results showed that 0.5 g/L NCQD promoted a 23.1 % increase in cumulative CH4 yield in the photo-AD system. Microbial analysis results showed that in photo-AD with NCQD, the dominant strain was Methanosarciniales, with an abundance of 69.0 %. Microbial activity and structural integrity tests showed that the microorganisms were not damaged by free radicals. In addition, NCQD increased the redox peak intensity of the CV curve and increased photocurrent intensity of photo-AD. Furthermore, it promoted an increase of 18.2 % (0.26 +/- 0.03 mu mol/mL) in ATP concentration. The photoelectrochemical analysis and quantitative analysis of functional genes results indicated that NCQD mainly promoted methanogenesis by providing photoelectrons. This promotion mechanism increased the copynumber (61,652.8 g-1) of EchA in photo-AD, rather than Vht and Hdr related to cytochrome. This work provided new strategies for the enhancement of AD and clarified potential mechanisms.

潜油电泵作为一种常见的人工举升装置,由于其强提液能力而广泛应用在海上油田,但海洋环境复杂且潜油电泵故障类型繁多与故障数据匮乏等原因使其在海上油田应用存在着一定的局限性.针对难以有效地在线诊断与定量分析潜油电泵电流信号等问题,提出了一种需要极少超参数调节的稀疏滤波特征提取方法,该方法对多种工况电流信号进行了有效的特征提取与模式识别,得到了一个准确、高效的实时诊断模型,通过对现场数据进行分析,验证了该方法的有效性.实验结果表明,该方法可有效地提取特征并实现海上油田潜油电泵10种故障状态的故障诊断,诊断准确率高达99.1％.随着数据的不断丰富和故障种类的不断完善,可实现更高效、准确的故障诊断.

Exploring key factors has important guidance for understanding complex anaerobic digestion (AD) systems. This study proposed a multi-layer automated machine learning framework to understand the complex interactions in AD systems and explore key factors at the environmental factor, microorganisms and system levels. The first layer of the framework identified hydraulic residence time (HRT) as the most important environmental factor, with an optimal range of 33-45 d. In the second layer of the framework, Methanocelleus (optimal relative abundance (ORA) = 3.0%) and Candidatus_Caldatribacterium (ORA = 1.7%) were found to be the key archaea and bacteria, respectively. Furthermore, the prediction of key microorganisms based on environmental factors and remaining microbial data showed the essential roles of Methanothermobacter and Acetomicrobium. The third layer for finding the optimal combination of data variables for predicting biogas production demonstrated that combined Archaea genera and environmental factors should be achieved for the most accurate prediction (root mean square error (RMSE) = 84.21). GBM had the best model performance and prediction accuracy among all the built-in models. Based on the optimal GBM model, the analysis at the system level showed that HRT was the most important variable. However the most important microorganism, Methanocelleus, within the appropriate survival range is also essential to achieve optimal biogas production. This research explores key parameters at various levels through automated machine learning techniques, which are expected to provide guidance in understanding the complex architecture of industrial and laboratory AD systems.

Industrial-scale garage dry fermentation systems areextremelynonlinear, and traditional machine learning algorithms have low predictionaccuracy. Therefore, this study presents a novel intelligent systemthat employs two automated machine learning (AutoML) algorithms (AutoGluonand H2O) for biogas performance prediction and Shapleyadditive explanation (SHAP) for interpretable analysis, along withmultiobjective particle swarm optimization (MOPSO) for early warningguidance of industrial-scale garage dry fermentation. The stackedensemble models generated by AutoGluon have the highest predictionaccuracy for digester and percolate tank biogas performances. Basedon the interpretable analysis, the optimal parameter combinationsfor the digester and percolate tank were determined in order to maximizebiogas production and CH4 content. The optimal conditionsfor the digester involve maintaining a temperature range of 35-38 degrees C, implementing a daily spray time of approximately 10 min anda pressure of 1000 Pa, and utilizing a feedstock with high total solidscontent. Additionally, the percolate tank should be maintained ata temperature range of 35-38 degrees C, with a liquid level of1500 mm, a pH range of 8.0-8.1, and a total inorganic carbonconcentration greater than 13.8 g/L. The software developed basedon the intelligent system was successfully validated in productionfor prediction and early warning, and MOPSO-recommended guidance wasprovided. In conclusion, the novel intelligent system described inthis study could accurately predict biogas performance in industrial-scalegarage dry fermentation and guide operating condition optimization,paving the way for the next generation of intelligent industrial systems.

Summary In the full life cycle of a well, thermal and mechanical loads may yield serious issues for the cement sheath integrity. However, the information for the integrity assessment, such as temperature and strain, is difficult to acquire underground. In this study, a full-scale experimental facility is used, allowing us to mimic the casing-cement sheath-formation (CCSF) system of a well. The system is monitored by fiber Bragg grating (FBG), enabling a real-time, high-accuracy, nondestructive measurement of temperature and strain inside the cement sheath in the sequence of setting and completion stage. Our observation reveals that the temperature of the cement sample cured in the mold is 22.3°C higher than the curing temperature; however, this temperature difference is not observed in the cement sheath cured in the CCSF system. This implies that the data obtained from the cement sample may overestimate the early-age performance of the cement sheath. Besides, the FBG measures a free strain of the tested cement during the hydration to be −370 με. This shrinkage can yield an internal stress in the CCSF system, which leads the cement sheath to swell circumferentially during the setting stage. During the completion stage, when the cement sheath is subjected to cyclic loading at three casing pressure levels, (i i.e., 10, 20, and 50 MPa), the maximum increment of circumferential strain reaches 160, 270, and 850 με, respectively. A plastic strain is observed for the 50 MPa pressure level, but not for the two other pressure levels (10 and 20 MPa). Unlike the observations in cyclic loading tests on cement samples, the plastic strain in the CCSF system accumulates linearly in the first 10 cycles and then increases slowly afterward. This difference is suggested to be attributed to the redistribution of internal stress along with the accumulation of plastic strain. Finally, the strains measured by the FBG are validated by the simulation, demonstrating the promising applicability of the FBG technology for monitoring the integrity of cement sheath.

Ethyl acetate and isopropanol, as essential chemical ingredients and organic solvents, play an important role in the industry. At atmospheric pressure, ethyl acetate and isopropanol form an azeotrope, which can be separated by extractive distillation. The choice of extractant is critical in extractive distillation. Low transition temperature mixtures (LTTMs), which are emerging as efficient green solvents, are used as extractants in this work. The effect of type and structure on separation performance were studied, and three LTTMs were selected for the separation of the ethyl acetate-isopropanol system. The vapor-liquid equilibrium (VLE) data of ethyl acetate-isopropanol-LTTMs was measured by experiments, and the results showed that when the mole fraction of LTTMs was 0.1, all three LTTMs could break the azeotrope of ethyl acetate and isopropanol, especially LTTM1 (tetrabutylammonium bromide: ethanolamine = 1:2) having the best selectivity. To acquire the binary interaction parameters, the NRTL model was used to fit the experimental data, and the regression data was in good agreement with the experimental data. In addition, a quantum chemical method was used to investigate the interactions between molecules to gain insights into the microscopic mechanism. Results showed that the weak hydrogen bonding and van der Waals forces are formed between ethyl acetate and other systems, while moderate or weak hydrogen bonding are formed between isopropanol and other systems.(c) 2022 Elsevier B.V. All rights reserved.

Fiber Bragg grating (FBG) sensing technology is a new structure monitoring technology. Aiming at the influence of hydration and cyclic casing pressure on cement sheath integrity in real wellbore conditions, firstly, the temperature and strain variation regularities of cement sheath in setting stage are investigated by FBG and a test device for evaluating cement sheath integrity. Then the circumferential strains of cement sheath and casing under cyclic casing pressure are studied. Furthermore, the applicability of FBG technology is verified. The results show that the temperature and strain of cement slurry change rapidly in 5 hours after pouring. In cyclic casing pressure stage, circumferential strains of cement sheath and casing are both tensile strains. In addition, circumferential strain of cement sheath and casing increases with the increase of casing pressure. The FBG sensors have high sensitivity that can reflect the change of casing pressure in time. The FBG technology is a scientific temperature and strain monitoring method for cement sheath. The results of this study are of great significance to the application of FBG technology for cement sheath integrity.

As an emerging green and sustainable solvent, a deep eutectic solvent (DES) applied to the carbon capture process is considered to be a promising absorbent. This work aims to comprehensively evaluate the potential and effectiveness of DESs for CO2 capture. First, a hydrophobic DES, which is composed of tetrabutylammonium bromide as the hydrogen bond acceptor (HBA) and decanoic acid as the hydrogen bond donor (HBD) with a molar ratio of 1:2, was screened out from 280 DESs by the conductor-like screening models-segment activity coefficient (COSMO-SAC) model. Then, quantum chemistry methods were used to investigate the interaction mechanism between the DES and CO2. The results show that the interactions between CO2 and the DES are mainly weak hydrogen bonds and van der Waals dispersion attraction forces. Next, gas-liquid equilibrium experiments were performed to investigate the effects of temperature and pressure, the types of HBAs and HBDs, and the molar ratios of HBA to HBD on the solubility of CO2. The results show that the process of DES absorbing CO2 obeys Henry's law and confirm the reliability of the COSMO-SAC model prediction. Finally, a rigorous rate-based model for the DES-based postcombustion CO2 capture process was simulated, and the life cycle environmental sustainability was evaluated and compared with that of the traditional solvent monoethanolamine, confirming the advantages of the negligible vapor pressure, thermal stability, and low ecological toxicity of the DES. This study provides a technical reference for applying new solvents developed in the laboratory to practical industrial processes.

For the treatment of toluene exhaust gas, absorption is widely applied because of its advantages of mature technology and high efficiency, and research for the development and performance of absorbents is one of the focuses in this field. Deep eutectic solvents (DESs), which are emerging as efficient green solvents, were introduced as the toluene absorbent in this work. The effects of the structures and compositions of hydrogen bond acceptors (HBAs) and hydrogen bond donors (HBDs) on toluene affinities were explored. It was found that both the HBAs and HBDs with longer alkyl chains have higher affinities to toluene; in addition, the solubility of toluene in DESs increases with the increase of the ratio of long-chain-fatty-acid HBDs. Tetraethylammonium chloride (TEACl) and oleic acid (OA) were selected as the HBA and HBD, respectively, in a molar ratio of 1:3 to form DES TEACl-OA. A quantum chemistry method was adopted to study the noncovalent interactions between molecules to gain insights into the microscopic mechanism. Results demonstrated that weak hydrogen bonds (HBs) dominated by the dispersion attraction are formed between toluene and other systems, while strong HBs of the nature of the electrostatic interaction are formed between the HBA and HBD. In addition, the interaction between toluene and DES is stronger than that between toluene molecules, which is the essential reason for toluene removal by TEACl-OA. Furthermore, the excellent absorption performance of the DES was confirmed by experiments of solubility and dynamic absorption, in which Henry's law constant at 298.2 K is 2.53 Pa.m(3)/mol and the removal efficiency in the first 10 min of the continuous bubbing absorption process can reach 99.7%. The proposed DES TEACl-OA is proved to be a promising solvent for toluene absorption; furthermore, the theoretical research and experimental data are significant for the development of DES absorbents and revealing the absorption mechanism on a molecular scale.