Molecular dynamics study on evaporation of high-salinity wastewater droplet

Zhan, Lingxiao; Chen, Heng; Zhou, Hao; Feng, Qianyuan; Gu, Liyan; Yang, Linjun; Sun, Zhenyu

doi:10.1016/j.applthermaleng.2022.118752

Cited by 13 publications

(5 citation statements)

References 58 publications

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“…If one considers the coalescence of drops of such polymers where such strongly negatively charged entities and hydrogen atoms (with partial positive charges) are present, hydrogen bonding will play a significant role in affecting the drop coalescence. There have been large number of studies probing drop dynamics using all-atom MD simulations for water drops (including several papers by the present group), − metallic drops − (Li et al probed the coalescence of lead drops on wrinkled surfaces and inside two-wall confinement, and coalescence of gallium drops on stripy surfaces), and polymeric drops: − In all these studies, these different forces have indeed been accounted for while modeling drop behavior. For example, the effect of hydrogen bonding in affecting water drop dynamics was discussed in several of these papers. − Similarly, there have been several papers probing the effect of electrostatic interactions in the spreading of water drops containing inorganic ions. − Indeed, the present problem considers drop sizes where these forces are relatively less significant.…”

Section: Discussionmentioning

confidence: 89%

Coalescence of 3D Polymeric Drops in the Presence of In Situ Photopolymerization

et al. 2023

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We develop a combined numerical (using direct numerical simulation) and scaling model to study the dynamics of two identical photocurable, shear-thinning polymeric drops undergoing spreading and coalescence (on a substrate) in the presence of in situ curing. We only consider the shear-thinning nature of the drops but do not account for any changes in the drop elasticity during the in situ photocuring process. Two separate cases are studied: (1) τs ≪ τp (case 1) and (2) τs ∼ τp (case 2) (τs and τp represent the spreading and photocuring timescales, respectively). Photopolymerization-driven increase in the drop viscosity significantly delays the spreading and the coalescence events for case 2. Furthermore, for case 2, at any given time during the coalescence process, both the height and the width of the “bridge” that forms due to coalescence are always smaller than those for case 1. Our scaling analysis establishes three distinct regimes characterizing the bridge growth for both cases 1 and 2: the initial regime (viscous and capillary forces balance each other, and the bridge growth rate is weak), the intermediate regime (inertia and capillary forces balance each other, and the bridge growth rate is enhanced), and the late regime (viscous and capillary forces balance each other, and the bridge growth rate is weak). Also, in regimes where viscous forces play a role (initial and late regimes), the bridge growth is weaker for case 2, while in the intermediate regime, the rate of bridge growth is similar between cases 1 and 2. We also provide the temperature variation and the evolution of the curing front inside the coalescing drops for cases 1 and 2: the significantly rapid rate of polymerization for case 2 manifests in a noticeable temperature drop, fast propagation of the curing front, and the fluid flow (associated with coalescence) affecting the migration of the curing front inside the coalescing drops. We anticipate that our study will be crucial in designing polymeric droplet-based additive manufacturing systems and understanding the behavior of polymeric blends and polymeric emulsions.

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Section: Discussionmentioning

confidence: 89%

Coalescence of 3D Polymeric Drops in the Presence of In Situ Photopolymerization

et al. 2023

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Section: Simulation Methodsmentioning

confidence: 99%

“…In fact, this is a common technique used in MD studies to accelerate the process that is concerned as the typical time scale that MD simulations can handle currently is on the order of nanosecond. For example, Zhan et al 27 investigated the evaporation of a 6 nm single wastewater droplet surrounded by N 2 using MD simulations, in which the ambient pressure of N 2 was set at ∼15 atm instead of 1 atm. For each evaporation case, we start the MD simulation with potential energy minimization using the conjugated gradient (CG) algorithm to eliminate possible irrational initial geometries, which may be induced by assembling the nanodroplet with the surrounding N 2 molecules.…”

Section: Simulation Setupmentioning

confidence: 99%

“…In addition, an H 2 O molecule will be removed if one of its atoms enters the thermostat region, so that the influence of vapor phase water molecules on the droplet evaporation process is eliminated, and the evaporation of the nanodroplet can be thought of as taking place in an infinite space. 16,17,27 A 1.0 fs time step is used during the droplet evaporation simulation. The total simulation time for evaporation depends on the specific simulation conditions listed in Table 1 and is in the range of 1 to 10 ns.…”

Section: Simulation Setupmentioning

confidence: 99%

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Molecular dynamics study on evaporation of metal nitrate-containing nanodroplets in flame spray pyrolysis

et al. 2023

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“…Disregarded in most surveys due to its sophistication, multiple droplet impacts (simultaneous, nonsimultaneous, and successive) on liquid films, liquid pools, and solid surfaces have numerous applications, including spray cooling 22 , inkjet printing 23 , spray coating 24 , desalination 25 , and so forth. Liang et al 26 studied the simultaneous and non-simultaneous impact of a droplet pair at room temperature.…”

Section: List Of Symbolsmentioning

confidence: 99%

Multi-objective optimization of multiple droplet impacts on a molten PCM using NSGA-II optimizer and artificial neural network

Faghiri

Poureslami

Aria

et al. 2023

Sci Rep

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Embracing an interaction between the phase change material (PCM) and the droplets of a heat transfer fluid, the direct contact (DC) method suggests a cutting-edge solution for expediting the phase change rates of PCMs in thermal energy storage (TES) units. In the direct contact TES configuration, when impacting the molten PCM pool, droplets evaporate, provoking the formation of a solidified PCM area (A). Then, they reduce the created solid temperature, leading to a minimum temperature value (Tmin). As a novelty, this research intends to maximize A and minimize Tmin since augmenting A expedites the discharge rate, and by lowering Tmin, the generated solid is preserved longer, resulting in a higher storage efficacy. To take the influences of interaction between droplets into account, the simultaneous impingement of two ethanol droplets on a molten paraffin wax is surveyed. Impact parameters (Weber number, impact spacing, and the pool temperature) govern the objective functions (A and Tmin). Initially, through high-speed and IR thermal imaging, the experimental values of objective functions are achieved for a wide range of impact parameters. Afterward, exploiting an artificial neural network (ANN), two models are fitted to A and Tmin, respectively. Subsequently, the models are provided for the NSGA-II algorithm to implement multi-objective optimization (MOO). Eventually, utilizing two different final decision-making (FDM) approaches (LINMAP and TOPSIS), optimized impact parameters are attained from the Pareto front. Regarding the results, the optimum amount of Weber number, impact spacing, and pool temperature accomplished by LINMAP and TOPSIS procedures are 309.44, 2.84 mm, 66.89 °C, and 294.98, 2.78 mm, 66.89 °C, respectively. This is the first investigation delving into the optimization of multiple droplet impacts for TES applications.

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Molecular dynamics study on evaporation of high-salinity wastewater droplet

Cited by 13 publications

References 58 publications

Coalescence of 3D Polymeric Drops in the Presence of In Situ Photopolymerization

Coalescence of 3D Polymeric Drops in the Presence of In Situ Photopolymerization

Molecular dynamics study on evaporation of metal nitrate-containing nanodroplets in flame spray pyrolysis

Multi-objective optimization of multiple droplet impacts on a molten PCM using NSGA-II optimizer and artificial neural network

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