Latest Research

Article  |  2021-08-31

Atomic Force Microscopy Measurement in the Lignosulfonate/Inorganic Silica System: From Dispersion Mechanism Study to Product Design

Designing and preparing high-performance lignin-based dispersants are crucial steps in realizing the value-added utilization of lignin on an industrial scale. Such process depends heavily on an understanding of the dispersion mechanism of lignin-based dispersants. Here, atomic force microscopy (AFM) is employed to quantitatively investigate the dispersion mechanism of a lignosulfonate/silica (LS/SiO2) system under different pH conditions. The results show that the repulsive force between SiO2 particles in LS solution is stronger than it is in water, resulting in better dispersion stability. The Derjaguin–Landau–Verwey–Overbeek (DLVO) formula as well as the DLVO formula combined with steric repulsion is utilized for the fitting of the AFM force/distance (F/D) curves between the SiO2 probe and substrate in water and in LS solution. Based on these fitting results, electrostatic and steric repulsive forces are respectively calculated, yielding further evidence that LS provides strong steric repulsion between SiO2 particles. Further studies indicate that the adsorbance of LS on SiO2 (Q), the normalized interaction constant (A), and the characteristic length (L) are the three critical factors affecting steric repulsion in the LS/SiO2 system. Based on the above conclusions, a novel quaternized grafted-sulfonation lignin (QAGSL) dispersant is designed and prepared. The QAGSL dispersant exhibits good dispersing performance for SiO2 and real cement particles. This work provides a fundamental and quantitative understanding of the dispersion mechanism in the LS/inorganic particle system and provides important guidance for the development of high-performance lignin-based dispersants.

Jingyu Wang ,   Yong Qian   et al.

Article  |  2021-08-31

Selective Laser Melting under Variable Ambient Pressure: A Mesoscopic Model and Transport Phenomena

Recent reports on the selective laser melting (SLM) process under a vacuum or low ambient pressure have shown fewer defects and better surface quality of the as-printed products. Although the physical process of SLM in a vacuum has been investigated by high-speed imaging, the underlying mechanisms governing the heat transfer and molten flow are still not well understood. Herein, we first developed a mesoscopic model of SLM under variable ambient pressure based on our recent laser-welding studies. We simulated the transport phenomena of SLM 316L stainless steel powders under atmospheric and 100 Pa ambient pressure. For typical process parameters (laser power: 200 W; scanning speed: 2 ms-1; powder diameter: 27 μm), the average surface temperature of the cavity approached 2800 K under atmospheric pressure, while it came close to 2300 K under 100 Pa pressure. More vigorous fluid flow (average speed: 4 ms-1) was observed under 100 Pa ambient pressure, because the pressure difference between the evaporation-induced surface pressure and the ambient pressure was relatively larger and drives the flow under lower pressure. It was also shown that there are periodical ripple flows (period: 14 μs) affecting the surface roughness of the as-printed track. Moreover, the molten flow was shown to be laminar because the Reynolds number is less than 400 and is far below the critical value of turbulence; thus, the viscous dissipation is significant. It was demonstrated that under a vacuum or lower ambient pressure, the ripple flow can be dissipated more easily by the viscous effect because the trajectory length of the ripple is longer; thus, the surface quality of the tracks is improved. To summarize, our model elucidates the physical mechanisms of the interesting transport phenomena that have been observed in independent experimental studies of the SLM process under variable ambient pressure, which could be a powerful tool for optimizing the SLM process in the future.

Renzhi Hu ,   Manlelan Luo   et al.

Article  |  2021-09-15

Metagenomic analysis on resistance genes in water and microplastics from a mariculture system

Microplastics existing widely in different matrices have been regarded as a reservoir for emerging contaminants. Mariculture systems have been observed to host microplastics and antibiotic resistance genes (ARGs). However, more information on proliferation of ARGs and metal resistance genes (MRGs) in mariculture system at the presence of microplastics is needed.


Article  |  2021-09-15

Polypropylene microplastics alter the cadmium adsorption capacity on different soil solid fractions

Microplastics (MPs) are widely present in a variety of environmental media and have attracted more and more attention worldwide. However, the effect of MPs on the interaction between heavy metals and soil, especially in soil solid fraction level, is not well understood. In this study, batch experiments were performed to investigate the adsorption characteristics of Cd in bulk soil and three soil solid fractions (i.e. particulate organo matter (POM), organic-mineral compounds (OMC), and mineral) with or without polypropylene (PP) MPs.


Research Articles  |  2021-09-13

Quality-related locally weighted soft sensing for non-stationary processes by a supervised Bayesian network with latent variables

It is necessary to construct an adaptive model to cope with process non-stationaries. In this study, a novel quality-related locally weighted soft sensing method is designed for non-stationary processes based on a Bayesian network with . Specifically, a is proposed where quality-oriented are extracted and further applied to a double-layer similarity measurement algorithm. The proposed soft sensing method tries to find a general approach for non-stationary processes via quality-related information where the concepts of local similarities and window confidence are explained in detail. The performance of the developed method is demonstrated by application to a numerical example and a debutanizer column. It is shown that the proposed method outperforms competitive methods in terms of the accuracy of predicting key quality variables.


Review Article  |  2021-09-13

A review on cyber security named entity recognition

With the rapid development of Internet technology and the advent of the era of big data, more and more texts are provided on the Internet. These texts include not only security concepts, incidents, tools, guidelines, and policies, but also risk management approaches, best practices, assurances, technologies, and more. Through the integration of large-scale, heterogeneous, unstructured information, the identification and classification of entities can help handle issues. Due to the complexity and diversity of texts in the domain, it is difficult to identify security entities in the domain using the traditional methods. This paper describes various approaches and techniques for NER in this domain, including the rule-based approach, dictionary-based approach, and based approach, and discusses the problems faced by NER research in this domain, such as conjunction and disjunction, non-standardized naming convention, abbreviation, and massive nesting. Three future directions of NER in are proposed: (1) application of unsupervised or semi-supervised technology; (2) development of a more comprehensive ontology; (3) development of a more comprehensive model.

Chen Gao ,   Xuan Zhang   et al.