Sulfate- and pH-driven metabolic flexibility in sugarcane vinasse dark fermentation stimulates biohydrogen evolution,sulfidogenesis or homoacetogenesis

Dark fermentation of sugarcane vinasse can be used as a “cleaning” step to remove sulfate prior to methanogenesis because sulfidogenic conditions can be successfully established in parallel with biohydrogen production. Using a 2² central composite rotational design (CCRD) and response surface methodology (RSM), this study assessed the impacts of bicarbonate and sulfate availability on the establishment of sulfidogenesis in the thermophilic (55 °C) fermentation of vinasse in batch reactors, equally assessing the impacts on biohydrogen evolution. CCRD-RSM results indicated the favoring of biohydrogen production at the lowest sulfate and bicarbonate concentrations, whilst the opposite was observed for sulfidogenesis. Glycerol, lactate, and hydrogen were the preferential electron donors utilized by sulfate-reducing bacteria (SRB), whilst ethanol was markedly consumed only at high sulfate concentrations. SRB were inhibited by sodium when dosing excess NaHCO₃ and Na₂SO₄. Complementary tests revealed maximum biohydrogen production (2.40 mmol) out of the CCRD, at pH exceeding 7.5 with no interference of sulfidogenesis. Non-efficient biohydrogen production was observed at low pH (<5.0; ～1.90 mmol) because the uptake of lactate was inhibited. Meanwhile, homoacetogenesis was established under intermediate pH range (5.5–6.5), as revealed by the accumulation of acetate (up to 2.5 g L^?1). 16S rRNA gene amplicon sequencing further revealed the genera Thermoanaerobacterium/Pseudoclostridium, Desulfotomaculum/Desulfohalotomaculum and Sporomusaceae/Moorella as the main biohydrogen-producing, sulfate-removing and biohydrogen-consuming (homoacetogens) microbial groups, respectively. Hence, using a single inoculum source, vinasse may provide a butyrate-rich (along with biohydrogen-rich biogas) or a sulfate-free and acetate-rich fermented effluent, depending mainly on proper pH control.     

Use of MALDI-TOF MS technology to evaluate adulteration of small ruminant milk with raw bovine milk

Detection of adulteration of small ruminant milk is very important for health and commercial reasons. New analytical and cost-effective methods need to be developed to detect new adulteration practices. In this work, we aimed to explore the ability of the MALDI-TOF mass spectrometry to detect bovine milk in caprine and ovine milk using samples from 18 dairy farms. Different levels of adulteration (0.5, 1, 5, 10, 20, 40, 60, and 80%) were analyzed during the lactation period of goat and sheep (in May, from 60 to 90 d in milk, and in August, from 150 to 180 d in milk). Two different ranges of peptide-protein spectra (500–4,000 Da; 4–20 kDa) were used to establish a calibration model for predicting the concentration of adulterant using partial least squares and generalized linear model with lasso regularization. The low molecular weight part of the spectra together with the generalized linear model with lasso regularization regression model appeared to have greater potential for our aim of detection of adulteration of small ruminants' milk. The subsequent prediction model was able to predict the concentration of bovine milk in caprine milk with a root mean square error of 11.4 and 17.0% in ovine milk. The results offer compelling evidence that MALDI-TOF can detect the adulteration of small ruminants' milk. However, the method is severely limited by (1) the complexity of the milk proteome resulting from the adulteration technique, (2) the potential degradation of thermolabile proteins, and (3) the genetic variability of tested samples. Additionally, the root mean square error of prediction based only on one individual sample adulteration series can drop down to 6.34% for quantification of adulterated caprine milk and 6.28% for adulterated ovine milk for the full set of concentrations or down to 2.33 and 4.00%, respectively, if we restrict only to low concentrations of adulteration (0, 0.5, 1, 5, 10%).     

分布式多元随机动态场景生成及快速精准场景降维算法

高比例新能源及多源耦合是电力系统发展的重要特征,这也为系统稳定经济运行提出了新挑战。该文以园区型多能系统为对象,研究了分布式多元随机动态场景分析,从多时空角度有效量化不确定因素给系统造成的影响,可为系统灵活重构、多维度协同运行与决策提供有力模型与场景支撑。首先由预测误差驱动拟合多元功率预测误差概率分布,全面反映随机功率出力信息,提高模型泛化性;以时序相关范围参数为数据驱动关联变量,高效动态控制波动强度;最终场景生成利用逆变换映射思想保证置信度。然后针对典型场景提取,提出一种综合递归聚类思想的多段嵌套削减算法,结合改进Wasserstein距离指标,兼具准确、时效、稳定方面的优势。最后由对比实验论证该方法的前沿有效性。     

IRS辅助的SWIPT系统中基于能效优先的波束成形设计与优化

以智能反射面(intelligent reflecting surface,IRS)辅助的无线携能通信(simultaneous wireless information and power transfer,SWIPT)系统为背景,研究了该系统中基于能效优先的多天线发送端有源波束成形与IRS无源波束成形联合设计与优化方法。以最大化接收端的最小能效为优化目标,构造在发送端功率、接收端能量阈值、IRS相移等多约束下的非线性优化问题,用交替方向乘子法(alternating direction method of multipliers,ADMM)求解。采用Dinkelbach算法转化目标函数,通过奇异值分解(singular value decomposition,SVD)和半定松弛(semi-definite relaxation,SDR)得到发送端有源波束成形向量。采用SDR得到IRS相移矩阵与反射波束成形向量。结果表明,该系统显著降低了系统能量收集(energy harvesting,EH)接收端的能量阈值。当系统总电路功耗为?15 dBm时,所提方案的用户能效为300 KB/J。当IRS反射阵源数与发送天线数均为最大值时,系统可达最大能效。     

煤矿水仓清理新工艺

通过调研现场情况以及检测煤泥特性，探寻一种实用性强、方法简单的新工艺来替代劳累的人工和繁琐的机械清淤，解决现实问题。针对实际情况开发清仓新工艺，介绍了该工艺的技术路线选择、设计依据以及实际应用效果。该新工艺具有降低清仓时间、减轻工人劳动强度、设备操作简单、实用性强等特点。     

Techno-economic-environmental evaluation of a combined tri and dry reforming of methane for methanol synthesis with a high efficiency CO2 utilization

Production of methanol, as a green energy, from syngas is coming into focus. However, natural gas based methanol plants, which are used steam reforming of methane for syngas production, have a high CO₂ emission resulting in the global warming. In this study, a novel process for methanol synthesis is proposed to reduce CO₂ emission. In this regard, natural gas and flue gas are fed to a parallel-series system with tri and dry reforming of methane for syngas production with the optimized stoichiometric number. Then, the produced syngas is converted to methanol in a reactor. Finally, the produced methanol is purified by two distillation towers. The proposed method is compared to a referenced method in the view of technological, economic and environmental metrics. The techno-economic-environmental analysis of the processes reveals that not only the proposed method, as compared to the referenced one, increases CO₂ conversion from 20.93% to 99.22%, but also it is more economical and environmentally friendly. In addition, the global warming potential of the proposed method is almost 60% lower than that for the referenced method due to the lower CO₂ emission. Therefore, the proposed method can save above MUS$ 8 a year by CO₂ capture.     

Application of artificial neural network method to predict the breakage properties of PGE bearing chromite ore

In the present investigation, systematic grinding experiments were conducted in a laboratory ball mill to determine the breakage properties of low-grade PGE bearing chromite ore. The population balance modeling technique was used to study the breakage parameters such as primary breakage distribution (B_{i, j}) and the specific rates of breakage (S_i). The breakage and selection function values were determined for six feed sizes. The results stated that the breakage follows the first-order grinding kinetics for all the feed sizes. It was observed that the coarser feed sizes exhibit higher selection function values than the finer feed size. Further, an artificial neural network was used to predict breakage characteristics of low-grade PGE bearing chromite ore. The predicted results obtained from the neural network modeling were close to the experimental results with a correlation of determination R² = 0.99 for both product size and selection function.     

Improvement of gaseous bioenergy production from spent coffee grounds Co-digestion with pulp wastewater by physical/chemical pretreatments

Two steps of hydrolysis and anaerobic biogas production processes was investigated in this study. In the first step, subcritical water (SBW) hydrolysis and chemical (acid/alkali) pretreatments were carried out to enhance hydrolysis efficiency by obtaining and analyzing the total volatile fatty acids (TVFA), chemical oxygen demand (COD), and total sugar productions from spent coffee grounds (SCG) hydrolysate. The subcritical water (SBW) hydrolysis under the condition of temperature 150 °C for 30 min can greatly improve the organic matter breakdown and reached the COD concentration of 1010 g/L which was 30% higher than the untreated raw SCG. For chemical pretreatments, it was found that the alkaline hydrolysis of SCG resulted in the greatest total sugar concentration of 181 g/L whereas the operation conditions were 2.0 M NaOH at 60 °C for 1 h. The peak of TVFA concentration 3725 mg/L was found at the acid hydrolysis of SCG with 1.0 M H₂SO₄ acid, 60 °C for 1 h. The optimal biomethane yield of 115 mL/g COD was obtained when 1.0 M H₂SO₄ acid hydrolysate co-digestion with pulp wastewater which increase methane yield production 8 times of raw pulp wastewater. The pretreatment process was confirmed in this study can significant improve the converting of the biowastes to bioenergy efficiency.     

Techno-economic assessment of hydrogen refueling station: A case study in Croatia

Hydrogen refueling station (HRS) capacity and location depend on the users, which makes it difficult to select the most favorable option before potential users are actually identified. As in Croatia, at least for now, there are no hydrogen users, this study considers a wide range of HRS capacities and their different configurations. These include hydrogen production and charging station within one existing wind farm in Croatia or both nearby the users, the hydrogen production within the wind farm and the charging station nearby the users, while hydrogen is delivered to the station with a tube trailer, and configuration of hydrogen production within the wind farm with a mobile charging station in case of several users in different locations. Each HRS configuration is evaluated by the obtained levelized cost of hydrogen depending on the capital, and operation and maintenance costs within the HRS techno-economic analysis provided.