Gamma estimator of Jarzynski equality for recovering binding energies from noisy dynamic data sets

Kuang, Zhen‐Bang; Singh, Kristi M.; Oliver, Daniel J.; Dennis, Patrick B.; Perry, Carole C.; Naik, Rajesh R.

doi:10.1038/s41467-020-19233-7

Cited by 8 publications

(7 citation statements)

References 52 publications

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“…For example, Jaishankar et al used an overall simulation time of more than 1 μs to obtain the PMF describing the adsorption of SA onto hematite from n -hexadecane. A potentially more efficient method to obtain the PMF for surfactants at solid–liquid interfaces is the adaptive biasing force (ABF) algorithm. , The ABF method has been used to study adsorption at solid–liquid interfaces for a range of surfactants from water, such as SDS on graphene, chlorogenic acid on polydimethylsiloxane, lipoic acid on silver, peptides on gold, proteins on hydroxyapatite and graphene, ethylene glycols on calcite and hematite, and a wide range of organic molecules on carbon nanotubes, graphene, and graphene oxide …”

Section: Introductionmentioning

confidence: 99%

“…A potentially more efficient method to obtain the PMF for surfactants at solid−liquid interfaces is the adaptive biasing force (ABF) algorithm. 42,43 The ABF method has been used to study adsorption at solid−liquid interfaces for a range of surfactants from water, such as SDS on graphene, 37 chlorogenic acid on polydimethylsiloxane, 44 lipoic acid on silver, 45 peptides on gold, 46 proteins on hydroxyapatite 47 and graphene, 48 ethylene glycols on calcite 49 and hematite, 50 and a wide range of organic molecules on carbon nanotubes, 51 graphene, 52 and graphene oxide. 53 In this study, we compare the adsorption of different OFMs from hydrocarbon solvents onto iron oxide surfaces.…”

Section: ■ Introductionmentioning

confidence: 99%

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Molecular Simulations of Surfactant Adsorption on Iron Oxide from Hydrocarbon Solvents

et al. 2021

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The performance of organic friction modifiers (OFMs) depends on their ability to adsorb onto surfaces and form protective monolayers. Understanding the relationship between OFM concentration in the base oil and the resulting surface coverage is important for improving lubricant formulations. Here, we use molecular dynamics (MD) simulations to study the adsorption of three OFMsstearic acid (SA), glycerol monoostearate (GMS), and glycerol monooleate (GMO)onto a hematite surface from two hydrocarbon solventsn-hexadecane and poly(α-olefin) (PAO). We calculate the potential of mean force of the adsorption process using the adaptive biasing force algorithm, and the adsorption strength increases in the order SA < GMS < GMO. We estimate the minimum area occupied by OFM molecules on the surface using annealing MD simulations and obtained a similar hard-disk area for GMS and GMO but a lower value for SA. Using the MD results, we determine the adsorption isotherms using the molecular thermodynamic theory (MTT), which agree well with one previous experimental data set for SA on hematite. For two other experimental data sets for SA, lateral interactions between surfactant molecules need to be accounted for within the MTT framework. SA forms monolayers with lower surface coverage than GMO and GMS at low concentrations but also has the highest plateau coverage. We validate the adsorption energies from the MD simulations using high-frequency reciprocating rig friction experiments with different concentrations of the OFMs in PAO. For OFMs with saturated tailgroups (SA and GMS), we obtain good agreement between the simulations and the experiments. The results deviate for OFMs containing Z-unsaturated tailgroups (GMO) due to the additional steric hindrance, which is not accounted for in the current simulation framework. This study demonstrates that MD simulations, alongside MTT, are an accurate and efficient tool to predict adsorption isotherms at solid−liquid interfaces.

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Section: Introductionmentioning

confidence: 99%

Section: ■ Introductionmentioning

confidence: 99%

Molecular Simulations of Surfactant Adsorption on Iron Oxide from Hydrocarbon Solvents

et al. 2021

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“…A potentially more efficient method to obtain the PMF for surfactants at solid-liquid interfaces is the adaptive biasing force (ABF) algorithm. 42,43 The ABF method has been used to study adsorption at solid-liquid interfaces for a range of surfactants from water, such as SDS on graphene, 37 chlorogenic acid on polydimethylsiloxane, 44 lipoic acid on silver, 45 peptides on gold, 46 proteins on hydroxyapatite 47 and graphene, 48 ethylene glycols on calcite 49 and hematite, 50 and a wide range of organic molecules on carbon nanotubes, 51 graphene, 52 and graphene oxide. 53 In this study, we compare the adsorption of different OFMs from hydrocarbon solvents onto iron oxide surfaces.…”

Section: Introductionmentioning

confidence: 99%

Molecular Simulations of Surfactant Adsorption on Iron Oxide from Hydrocarbon Solvents

Acero

Mohr

Bernabei

et al. 2021

Preprint

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The performance of lubricant additives, such as organic friction modifiers (OFMs), depends critically on their ability to adsorb onto the surfaces of moving components and form protective self-assembled layers (SAMs). Therefore, understanding the relationship between the concentration of the additive in the base oil and the resulting surface coverage is extremely important for lubricant formulations, as well as many other surfactant applications. Here, we use molecular dynamics (MD) simulations to study the adsorption isotherms of three different OFMs, stearic acid (SA), glycerol monoostearate (GMS), and glycerol monooleate (GMO), onto a hematite surface from hydrocarbon solvents, n-hexadecane and poly-α-olefin (PAO). First, we calculate the potential of mean force (PMF) of the adsorption process using MD simulations with the adaptive biasing force (ABF) algorithm. Our MD simulations show that SA has the weakest adsorption energy on hematite, followed by GMS, and finally GMO, due to the increasing number of functional groups available to bind to the surface. We also estimate the area occupied by each OFM molecule on the surface in the high-coverage limit using MD simulations of the annealing of OFM films with different initial surface coverages. We obtain a similar hard-disk area for GMS and GMO, but a lower value for SA, which is due to its smaller headgroup size. Based on the adsorption energy and surface area, we determine the corresponding adsorption isotherms using the molecular thermodynamic theory (MTT), which agree well with one available experimental data-set for SA. Two other experimental data-sets for SA require lateral interactions between surfactant molecules to be accounted for. SA forms monolayers with lower surface coverage than GMO and GMS at low concentrations (due to a smaller adsorption energy), but also has the highest plateau coverage (due to a smaller hard-disk area). We validate the adsorption energies from the MD simulations using high frequency reciprocating rig (HFRR) friction experiments with different concentrations of the OFMs in PAO. We use the Jahanmir and Beltzer model to estimate the surface coverage at each concentration and the adsorption energy of each OFM from the HFRR friction data. For OFMs with saturated tailgroups (SA and GMS), we obtain good agreement between the predictions made by the simulations and the experiments. The MD simulation and experimental results deviate for OFMs containing Z-unsaturated tailgroups (GMO), with the former suggesting stronger adsorption for GMO than GMS, while the latter predicts the opposite trend. We suggest that this is can be attributed to the higher steric barrier of adsorption of the OFMs with kinked Z-unsaturated tailgroup through a partially formed monolayer, an aspect which was not captured in the current simulations. This study demonstrates that MD simulations with the ABF algorithm, alongside MTT, are an accurate and efficient tool to predict adsorption isotherms at solid-liquid interfaces.

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“…SMD stands for the process whereby a harmonic potential with moving center is applied to the adsorbate so as to pull it away from the surface. The SMD process highly resembles the experimental atomic force microscopy (AFM) technique, and allows for quantification of energy profile, rupture force, unbinding pathway, etc [153,154]. For example, Lecot et al [115] used SMD to investigate the adsorption of streptavidinbiotin complex on SiO2 surface functionalized with different silane SAMs.…”

Section: Steered Molecular Dynamics (Smd)mentioning

confidence: 99%

“…Estimated free energy values from four datasets all converged to a value of roughly 17𝑘 𝐵 𝑇, indicating the excellent robustness of gamma estimator for SMD. Adapted from [154].…”

Section: Steered Molecular Dynamics (Smd)mentioning

confidence: 99%

Investigation of membrane fouling using molecular dynamics simulation

Ma¹

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Gamma estimator of Jarzynski equality for recovering binding energies from noisy dynamic data sets

Cited by 8 publications

References 52 publications

Molecular Simulations of Surfactant Adsorption on Iron Oxide from Hydrocarbon Solvents

Molecular Simulations of Surfactant Adsorption on Iron Oxide from Hydrocarbon Solvents

Molecular Simulations of Surfactant Adsorption on Iron Oxide from Hydrocarbon Solvents

Investigation of membrane fouling using molecular dynamics simulation

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