Intensification of delignification of Tectona grandis saw dust as sustainable biomass using acoustic cavitational devices

Delignification of sawdust was studied using ultrasound assisted alkali peroxide approach using longitudinal horn for the first time and the efficacy compared with more commonly used configurations of ultrasonic reactors. Comparison with the conventional approach based on stirring has also been presented to establish the process intensification benefits. Effect of different operating parameters such as sodium carbonate concentration (0.1, 0.15, 0.2, 0.25 M), hydrogen peroxide concentration (0.2, 0.4, 0.6, 0.8, 1 M) and biomass loading (2, 4, 6, 8, 10 wt%), on the efficacy of lignin extraction has been investigated for different ultrasonic reactors. The optimum conditions for probe type ultrasonic horn were established as 150 W, 50% duty cycle and 80% amplitude with optimum process conditions as Na₂CO₃ concentration as 0.2 M, H₂O₂ concentration as 1 M, biomass loading of 10 wt% and operating time of 70 min. Longitudinal horn resulted in best efficacy (both in terms of yield and energy requirements) followed by ultrasonic horn and ultrasonic bath whereas the conventional approach was least effective. The obtained lignin was also analyzed using different characterization techniques. The presence of peaks at wavelength range of 875–817, 1123–1110, and at 1599 cm⁻¹ for the extracted sample confirmed the presence of lignin. Increase in the crystallinity index of the processed sample (maximum for longitudinal horn) also confirmed the lignin removal as lignin is amorphous in nature. Overall it has been concluded that ultrasound can be effectively used for delignification with longitudinal horn as best configuration.     

BP neural network recognition algorithm for scour monitoring of subsea pipelines based on active thermometry

Scour monitoring is an important concern for subsea pipeline systems. The active-thermometry-based scour monitoring is based on the difference of heat transfer properties between sediment and sand, recognizes the surrounding media though temperature changing patterns during heating and cooling processes, and hence detects the free spans. Based on the scour monitoring system, a two-layer BP neural network was employed to process the monitoring data and achieved media recognition. The network's inputs were normalized temperature time histories. The network's outputs denoted different media: sediment and water. To validate the method, three experiments were conducted; one was used for training the network and the other two for testing. Also, the effect of noise on the network's performance was studied through simulation. The results demonstrated the feasibility and robustness of the neural network.     

Monitoring the manufacturing process of glass fiber reinforced composites with carbon nanotube buckypaper sensor

Buckypapers are free-standing porous mats of entangled CNT ropes cohesively bounded by van der waals interactions, and can be used to monitor the manufacturing process of glass fiber reinforced composite. In this paper, the buckypaper (BP) was fabricated with monodispersion of multi-wall carbon nanotubes via spray-vacuum filtration, and its morphology and pore size distribution were characterized by scanning electron microscope and nitrogen adsorption/desorption. The resistance of the BP sensor was obtained using a four-point probe method, and the resistance changes could be related to phase changes of the resin matrix,. Experimental results show that the BP sensor embedded in the glass/epoxy composite laminates has indicated a relative resistance change from −2.9% to 226.5% during the manufacturing process. In addition, the temperature sensitivity of a pristine BP sensor and a BP sensor embedded in composite were also characterized. The results demonstrate that the effect of resin phase changes on the resistance changes of a BP sensor is greater than that of the temperature during composite manufacturing.     

Real-time assessment of carbon nanotube alignment in a polymer matrix under an applied electric field via polarized Raman spectroscopy

A technique has been developed utilizing polarized Raman spectroscopy to measure alignment of carbon nanotubes in situ in a polymer matrix under an applied electric field. Previous studies of alignment have been restricted to optically transparent solvents or polymerized specimens that prevent accurate analyses of alignment dynamics in polymers. The effects of electric field strength on the degree of alignment and the time to achieve an aligned state are discussed. The use of in situ, real-time polarized Raman spectroscopy provides a non-invasive technique for assessing carbon nanotube alignment, which can assist in determining processing conditions to improve the mechanical and electrical properties of aligned nanocomposites.     

Reversed‐phase liquid chromatography with electrospray mass detection and 1H and 13C NMR characterization of new process‐related impurities,including forced degradants of Efavirenz: Related substances correlated to the synthetic pathway

In this study, a stability‐indicating reversed‐phase liquid chromatographic electrospray mass spectrometric method was developed and validated for the determination of process‐related impurities and forced degradants of Efavirenz in bulk drugs. Efavirenz was subjected to acid, alkaline hydrolysis, H₂O₂ oxidation, photolysis, and thermal stress. Significant degradation was observed during alkaline hydrolysis, and the degradants were isolated on a mass‐based purification system and characterized by high‐resolution mass spectrometry, positive electrospray ionization tandem mass spectrometry, and ¹H and ¹³C NMR spectroscopy. Accurate mass measurement and NMR spectroscopy revealed the possible structure of process‐related impurities and degradant under stress conditions. The acceptable separation was accomplished on Waters bondapak C₁₈ column (250 mm × 4.6 mm; 5 μm), using 5 mM ammonium acetate and acetonitrile as a mobile phase in a gradient elution mode at a flow rate of 1.0 mL/min. The eluents were monitored by diode array detector at 247 nm and quantitation limits were obtained in the range of 0.1–2.5 μg/mL for Efavirenz, degradants, and process‐related impurities. The liquid chromatography method was validated with respect to accuracy, precision, linearity, robustness, and limits of detection and quantification as per International Conference on Harmonization guidelines.     

Fuzzy logic modifications of the Analytic Hierarchy Process

The Analytic Hierarchy Process (AHP) is a measurement methodology based on pair-wise comparisons that relies on judgment to derive priority scales. During its implementation, one constructs hierarchies, then makes judgments or performs measurements on pairs of elements with respect to a criterion to derive preference scales, which are then synthesized throughout the structure to select the preferred alternative.One of the areas where the AHP finds application is in the subjective phases of risk assessment (RA), where it is used to structure and prioritize diverse risk factors, including the judgments of experts. Since fuzzy logic (FL) has been shown to be an effective tool for accommodating human experts and their communication of linguistic variables, there has been research aimed at modeling the fuzziness in the AHP (FAHP), and recently the focus of some of that modeling has been with respect to RA.The literature discusses more than one FAHP model, which raises the question as to which are the prominent models and what are their characteristics. In response to this question, we examine three of the most influential FAHP models. The article proceeds as follows. It begins with a brief overview of the AHP and its limitations when confronted with a fuzzy environment. This is followed by a discussion of FL modifications of the AHP. A RA-based likelihood score example is used throughout. The article ends with a commentary on the findings.     

Atomically Dispersed Iron Regulating Electronic Structure of Iron Atom Clusters for Electrocatalytic H2O2 Production and Biomass Upgrading

The integration of highly active single atoms (SAs) and atom clusters (ACs) into an electrocatalyst is critically important for high-efficiency two-electron oxygen reduction reaction (2e⁻ ORR) to hydrogen peroxide (H₂O₂). Here we report a tandem impregnation-pyrolysis-etching strategy to fabricate the oxygen-coordinated Fe SAs and ACs anchored on bacterial cellulose-derived carbon (BCC) (FeSAs/ACs-BCC). As the electrocatalyst, FeSAs/ACs-BCC exhibits superior electrocatalytic activity and selectivity toward 2e⁻ ORR, affording an onset potential of 0.78 V (vs. RHE) and a high H₂O₂ selectivity of 96.5 % in 0.1 M KOH. In a flow cell reactor, the FeSAs/ACs-BCC also achieves high-efficiency H₂O₂ production with a yield rate of 12.51±0.18 mol g_cat⁻¹ h⁻¹ and a faradaic efficiency of 89.4 %±1.3 % at 150 mA cm⁻². Additionally, the feasibility of coupling the produced H₂O₂ and electro-Fenton process for the valorization of ethylene glycol was explored in detail. The theoretical calculations uncover that the oxygen-coordinated Fe SAs effectively regulate the electronic structure of Fe ACs which are the 2e⁻ ORR active sites, resulting in the optimal binding strength of *OOH intermediate for high-efficiency H₂O₂ production.     

GPS技术在金川露天矿边坡变形监测中的应用

本文结合金川露天矿边坡变形GPS监测研究，主要论述监测基点的选择，基点WGS-84坐标的确定，变形监测网的布设，GPS数据采集、处理和质量，坐标转换的实施等，给出反演推出的若干四等三角点及其它控制点的变形数据，这些数据和造成变形的物理成因符合得很好，最后概括出GPS技术应用于变形观测的若干优点。     

基于非对称漂移双gamma跳-扩散过程的创新幂型期权定价模型

针对假设股价的对数收益率布朗运动在期权定价时产生的无法解释股价对数收益率的尖峰厚尾和序列相关性的缺陷,采用了Zhang提出的非对称漂移双gamma跳-扩散过程来描述资产(股价)的对数收益率运动形态(该过程是kou提出的双指数跳-扩散过程的推广),并利用Esscher风险中性变换,研究了幂型期权的定价公式.还设计了两种创新的幂型期权,在非对称漂移双gamma跳-扩散过程下给出了相应的定价公式.