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During theDeepwater Horizonoil well blowout in the Gulf of Mexico, the application of 7 million liters of chemical dispersants aimed to stimulate microbial crude oil degradation by increasing the bioavailability of oil compounds. However, the effects of dispersants on oil biodegradation rates are debated. In laboratory experiments, we simulated environmental conditions comparable to the hydrocarbon-rich, 1,100 m deep plume that formed during theDeepwater Horizondischarge. The presence of dispersant significantly altered the microbial community composition through selection for potential dispersant-degradingColwellia,which also bloomed in situ in Gulf deep waters during the discharge. In contrast, oil addition to deepwater samples in the absence of dispersant stimulated growth of natural hydrocarbon-degradingMarinobacter.In these deepwater microcosm experiments, dispersants did not enhance heterotrophic microbial activity or hydrocarbon oxidation rates. An experiment with surface seawater from an anthropogenically derived oil slick corroborated the deepwater microcosm results as inhibition of hydrocarbon turnover was observed in the presence of dispersants, suggesting that the microcosm findings are broadly applicable across marine habitats. Extrapolating this comprehensive dataset to real world scenarios questions whether dispersants stimulate microbial oil degradation in deep ocean waters and instead highlights that dispersants can exert a negative effect on microbial hydrocarbon degradation rates.

To address the characteristic that graphene was difficult to disperse in deionized water, four factors including dispersant type, dispersant content, pH value, and ultrasonic time were selected to construct an orthogonal test combined with signal-to-noise ratio (SNR) analysis for exploring the optimal dispersion parameters of graphene. The orthogonal test results and signal-to-noise ratio analysis results showed that dispersant type and pH value had a higher degree of influence on graphene dispersion. Combined with the characterization results of SEM, LS, and Raman spectrometer, it could be determined that a better dispersion effect was obtained when the mixture with 1% of PVP and Triton X-100 was added to the dispersion with a pH value of about 8 and 80-minute ultrasonication was conducted.

Dispersants, serving as an essential raw material in the formulation of coal water slurry, offer an economical and convenient solution for enhancing slurry concentration, thus stimulating significant interest in the development of novel and efficient dispersants. This paper intends to illuminate the evolution of dispersants by examining both the traditional and the newly conceived types and elaborating on their respective mechanisms of influence on slurry performance. Dispersants can be classified into anionic, cationic, amphoteric, and non-ionic types based on their dissociation properties. They can be produced by modifying either natural or synthetic products. The molecular structure of a dispersant allows for further categorization into one-dimensional, two-dimensional, or three-dimensional structure dispersants. This document succinctly outlines dispersants derived from natural products, three-dimensional structure dispersants, common anionic dispersants such as lignin and naphthalene, and amphoteric and non-ionic dispersants. Subsequently, the adsorption mechanism of dispersants, governed by either electrostatic attraction or functional group effects, is elucidated. The three mechanisms through which dispersants alter the surface properties of coal, namely the wetting dispersion effect, electrostatic repulsion effect, and steric hindrance effect, are also explained. The paper concludes with an exploration of the challenges and emerging trends in the domain of dispersants.

Bacterial biofilms commonly cause chronic and persistent infections in humans. Bacterial biofilms consist of an inner layer of bacteria and an autocrine extracellular polymeric substance (EPS). Biofilm dispersants (abbreviated as dispersants) have proven effective in removing the bacterial physical protection barrier EPS. Dispersants are generally weak or have no bactericidal effect. Bacteria dispersed from within biofilms (abbreviated as dispersed bacteria) may be more invasive, adhesive, and motile than planktonic bacteria, characteristics that increase the probability that dispersed bacteria will recolonize and cause reinfection. The dispersants should be combined with antimicrobials to avoid the risk of severe reinfection. Dispersant-based nanoparticles have the advantage of specific release and intense penetration, providing the prerequisite for further antibacterial agent efficacy and achieving the eradication of biofilms. Dispersant-based nanoparticles delivered antimicrobial agents for the treatment of diseases associated with bacterial biofilm infections are expected to be an effective measure to prevent reinfection caused by dispersed bacteria. Key points • Dispersed bacteria harm and the dispersant’s dispersion mechanisms are discussed. • The advantages of dispersant-based nanoparticles in bacteria biofilms are discussed. • Dispersant-based nanoparticles for cutting off reinfection in vivo are highlighted.

During the Deepwater Horizon disaster, a substantial fraction of the 600,000–900,000 tons of released petroleum liquid and natural gas became entrapped below the sea surface, but the quantity entrapped and the sequestration mechanisms have remained unclear. We modeled the buoyant jet of petroleum liquid droplets, gas bubbles, and entrained seawater, using 279 simulated chemical components, for a representative day (June 8, 2010) of the period after the sunken platform’s riser pipe was pared at the wellhead (June 4–July 15). The model predicts that 27% of the released mass of petroleum fluids dissolved into the sea during ascent from the pared wellhead (1,505 m depth) to the sea surface, thereby matching observed volatile organic compound (VOC) emissions to the atmosphere. Based on combined results from model simulation and water column measurements, 24% of released petroleum fluid mass became channeled into a stable deep-water intrusion at 900- to 1,300-m depth, as aqueously dissolved compounds (∼23%) and suspended petroleum liquid microdroplets (∼0.8%). Dispersant injection at the wellhead decreased the median initial diameters of simulated petroleum liquid droplets and gas bubbles by 3.2-fold and 3.4-fold, respectively, which increased dissolution of ascending petroleum fluids by 25%. Faster dissolution increased the simulated flows of water-soluble compounds into biologically sparse deep water by 55%, while decreasing the flows of several harmful compounds into biologically rich surface water. Dispersant injection also decreased the simulated emissions of VOCs to the atmosphere by 28%, including a 2,000-fold decrease in emissions of benzene, which lowered health risks for response workers.

Carbon nanotubes (CNTs) have been recognized as a promising material in a wide range of applications from biotechnology to energy-related devices. However, the poor solubility in aqueous and organic solvents hindered the applications of CNTs. As studies have progressed, the methodology for CNT dispersion was established. In this methodology, the key issue is to covalently or non-covalently functionalize the surfaces of the CNTs with a dispersant. Among the various types of dispersions, polymer wrapping through non-covalent interactions is attractive in terms of the stability and homogeneity of the functionalization. Recently, by taking advantage of their stability, the wrapped-polymers have been utilized to support and/or reinforce the unique functionality of the CNTs, leading to the development of high-performance devices. In this review, various polymer wrapping approaches, together with the applications of the polymer-wrapped CNTs, are summarized.

With the increasing scarcity of conventional light crude oil resources in our country, the efficient development of heavy oil resources is of great strategic significance for ensuring national energy security. Asphaltene, as the component with the strongest polarity and the largest molecular weight in heavy crude oil, is prone to association deposition phenomena due to internal component changes and the influence of external temperature and pressure environments, generating various engineering and technical problems. In this paper, the molecular dynamics simulation method is adopted to systematically reveal the interaction between asphaltene model compounds and dispersants, and analyze the interaction energy of the dissolution system. The simulation results show that the molecular weight, the number of conjugated rings, the length and quantity of alkyl side chains in asphaltene molecules all have significant effects on the aggregation behavior of asphaltene molecules. When the polarity of the solvent increases, the solubility of different asphaltenes decreases. In particular, for organic solvents, the interaction energy of perylene model compounds modified by benzene rings is relatively low, and for inorganic solvents, the interaction energy of perylene model compounds modified by heteroatoms is also relatively low. When a dispersant is present in the dissolution system, the solubility will further increase, but the degree of solubilization varies due to the influence of different molecular structures, the amount of dispersant and temperature. Therefore, these asphaltene model compounds can be utilized for simulation analysis to better explore the dissolution law and influencing factors of asphaltenes. It can also provide corresponding simulation methods for exploring the selection of asphaltene dispersants in the laboratory later, and offer guiding directions for the screening of efficient asphaltene dispersants.

The mixing of a powder of 10- to 50-μm primary particles into a liquid to form a dispersion with the highest possible solid content is a common industrial operation. Building on recent advances in the rheology of such “granular dispersions,” we study a paradigmatic example of such powder incorporation: the conching of chocolate, in which a homogeneous, flowing suspension is prepared from an inhomogeneous mixture of particulates, triglyceride oil, and dispersants. Studying the rheology of a simplified formulation, we find that the input of mechanical energy and staged addition of surfactants combine to effect a considerable shift in the jamming volume fraction of the system, thus increasing the maximum flowable solid content. We discuss the possible microscopic origins of this shift, and suggest that chocolate conching exemplifies a ubiquitous class of powder–liquid mixing.

The design rules for materials are clear for applications with a single objective. For most applications, however, there are often multiple, sometimes competing objectives where there is no single best material and the design rules change to finding the set of Pareto optimal materials. In this work, we leverage an active learning algorithm that directly uses the Pareto dominance relation to compute the set of Pareto optimal materials with desirable accuracy. We apply our algorithm to de novo polymer design with a prohibitively large search space. Using molecular simulations, we compute key descriptors for dispersant applications and drastically reduce the number of materials that need to be evaluated to reconstruct the Pareto front with a desired confidence. This work showcases how simulation and machine learning techniques can be coupled to discover materials within a design space that would be intractable using conventional screening approaches. Identifying optimal materials in multiobjective optimization problems represents a challenge for new materials design approaches. Here the authors develop an active-learning algorithm to optimize the Pareto-optimal solutions successfully applied to the in silico polymer design for a dispersant-based application.