Molecular simulations of interfacial systems: challenges, applications and future perspectives

Lbadaoui-Darvas, Mária; Garberoglio, Giovanni; Karadima, Katerina S.; Cordeiro, M. Natália D. S.; Nenes, Athanasios; Takahama, Satoshi

doi:10.1080/08927022.2021.1980215

Cited by 25 publications

(14 citation statements)

References 381 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Having shown that the surface tension contribution of ionic species is substantially influenced by the sign of their charge, a systematic investigation of the surface tension contribution of the charged moieties in adlayers consisting of a mixture of cationic and anionic (and, perhaps, also zwitterionic) surfactants would be a natural extension of this work. Such an investigation would also be of great relevance in understanding the atmospheric fate of various aerosol particles, 102 often consisting of such a mixture of surfactants as well as dissolved salts. 103 Thus, according to the Koḧler theory, 104 the reduced surface tension leads to the increased activity of such aerosols as cloud condensation nuclei, altering the optical properties as well as the propensity of precipitation on regional to global scales.…”

Section: Discussionmentioning

confidence: 99%

Contribution of Different Molecules and Moieties to the Surface Tension in Aqueous Surfactant Solutions. II: Role of the Size and Charge Sign of the Counterions

et al. 2021

View full text Add to dashboard Cite

Understanding the role of the counterion species in surfactant solutions is a complicated task, made harder by the fact that, experimentally, it is not possible to vary independently bulk and surface quantities. Here, we perform molecular dynamics simulations at constant surface coverage of the liquid/vapor interface of lithium, sodium, potassium, rubidium, and cesium dodecyl sulfate aqueous solutions. We investigate the effect of counterion type and charge sign on the surface tension of the solution, analyzing the contribution of different species and moieties to the lateral pressure profile. The observed trends are qualitatively compatible with the Hofmeister series, with the notable exception of sodium. We point out a possible shortcoming of what is at the moment, in our experience, the most realistic nonpolarizable force field (CHARMM36) that includes the parametrization for the whole series of alkali counterions. In the artificial system where the counterion and surfactant charges are inverted in sign, the counterions become considerably harder. This charge inversion changes considerably the surface tension contributions of the counterions, surfactant headgroups, and water molecules, stressing the key role of the hardness of the counterions in this respect. However, the hydration free energy gain of the counterions, occurring upon charge inversion, is compensated by the concomitant free energy loss of the headgroups and water molecules, leading to a negligible change in the surface tension of the entire system.

show abstract

Section: Discussionmentioning

confidence: 99%

Contribution of Different Molecules and Moieties to the Surface Tension in Aqueous Surfactant Solutions. II: Role of the Size and Charge Sign of the Counterions

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Another point to mention here is that only single VOC molecules have been considered in the PMF calculation, which cancels out the co-operativity effect that might help to permeate the VOC from the vapor to liquid phase. Finally, not considering the intrinsic solvation free energy profile may induce some random error due to the inefficiency of identifying the exact surface molecules by the non-intrinsic approach. − We have listed the calculated K values for two different regions of the DESs, interface, and bulk values in Table . The smaller K values for TOL suggest that it has the better partitioning efficiency in these DESs.…”

Section: Results and Discussionmentioning

confidence: 99%

Absorption of Volatile Organic Compounds Toluene and Acetaldehyde in Choline Chloride-Based Deep Eutectic Solvents

2022

View full text Add to dashboard Cite

Unrestricted emission of volatile organic compounds (VOCs)a threat to human health and the environmentcan be controlled to a large extent by the capturing mechanism. Few recent experimental studies explored the efficacy of the deep eutectic solvent (DES), a designer solvent with some fascinating properties, as a VOC-capturing medium. Through the partition coefficient measurement, it was found that the choline chloride-based DESs exhibit excellent VOC-capturing potencies. However, a molecular picture of the above absorption process is still lacking. Here, we study the molecular mechanism of the absorption of two commonly occurring VOCs, toluene and acetaldehyde, in two different choline chloride-based DESs with varying donor molecules, urea, and levulinic acid via the molecular dynamics simulation technique. Strong absorption of the VOCs is observed in both the DESs. The free energy profile for the absorption process has been explored using the umbrella sampling method. The VOCs are preferentially solvated near the liquid/vapor interface. The simulated partition coefficients for the VOCs from the vapor to the liquid phase show good agreement with the experimental results. Detailed analyses of the spatial and orientational structure of the VOCs and different components of DESs are performed to elucidate the interaction among them. The above analyses have indicated that DES is a better VOC-capturing medium compared to a room-temperature ionic liquid, which is more extensively studied in the literature.

show abstract

“…These circumstances give opportunities to classify MOFs as “designer” nanomaterials [ 81 ]. The data from HTC screening and molecular simulations [ 82 ] play an essential role in the future to achieve the goal of the desired nanomaterial, but we propose including sensor data at this stage, and the next section presents a particular solution.…”

Section: Data-centric Research Strategymentioning

confidence: 99%

Data-Centric Architecture for Self-Driving Laboratories with Autonomous Discovery of New Nanomaterials

et al. 2021

View full text Add to dashboard Cite

Artificial intelligence (AI) approaches continue to spread in almost every research and technology branch. However, a simple adaptation of AI methods and algorithms successfully exploited in one area to another field may face unexpected problems. Accelerating the discovery of new functional materials in chemical self-driving laboratories has an essential dependence on previous experimenters’ experience. Self-driving laboratories help automate and intellectualize processes involved in discovering nanomaterials with required parameters that are difficult to transfer to AI-driven systems straightforwardly. It is not easy to find a suitable design method for self-driving laboratory implementation. In this case, the most appropriate way to implement is by creating and customizing a specific adaptive digital-centric automated laboratory with a data fusion approach that can reproduce a real experimenter’s behavior. This paper analyzes the workflow of autonomous experimentation in the self-driving laboratory and distinguishes the core structure of such a laboratory, including sensing technologies. We propose a novel data-centric research strategy and multilevel data flow architecture for self-driving laboratories with the autonomous discovery of new functional nanomaterials.

show abstract

Molecular simulations of interfacial systems: challenges, applications and future perspectives

Cited by 25 publications

References 381 publications

Contribution of Different Molecules and Moieties to the Surface Tension in Aqueous Surfactant Solutions. II: Role of the Size and Charge Sign of the Counterions

Contribution of Different Molecules and Moieties to the Surface Tension in Aqueous Surfactant Solutions. II: Role of the Size and Charge Sign of the Counterions

Absorption of Volatile Organic Compounds Toluene and Acetaldehyde in Choline Chloride-Based Deep Eutectic Solvents

Data-Centric Architecture for Self-Driving Laboratories with Autonomous Discovery of New Nanomaterials

Contact Info

Product

Resources

About