Systematic Molecular Dynamics Simulations Research Articles

Transport of lithium droplets between two nonparallel iron plates: A molecular dynamics study

The use of bionic structures for the efficient and passive directional transportation of liquid droplets is crucial in numerous industrial applications. Compared with conventional fluids, liquid metals are stable under a wide range of environmental conditions owing to their excellent physicochemical properties. However, the directional transportation of liquid metals remains challenging. Herein, inspired by the pecking feeding mode of shorebirds, we performed a series of systematic molecular dynamics simulations to study the directional transport of liquid lithium (Li) between non-parallel iron (Fe) plates. The simulations demonstrate that cyclically closing and opening the Fe plates induces the movement of Li droplets toward the tip of the beak-shaped plate. Increasing the opening angle and applying a positive strain of the Fe plates can increase the transport velocity of the Li droplets. Nevertheless, the dissolution of Fe atoms in the liquid Li due to corrosion hinders the transportation of Li droplet across the Fe plate. We simulated the impact of two surface nanostructures on Li transport behavior and found that saw-tooth nanostructures decrease transport efficiency and lead to droplet breakup, whereas nanogrooves improve transport capacity by promoting the capillary effect. This work indicates that understanding the mechanism and influencing factors of liquid Li transport between non-parallel plates is essential for the design of bionic structures for the efficient transport of liquid metals.

The formation mechanism of metal cluster fullerenes Sc3N@Cn: force field development and molecular dynamics simulations.

Metal cluster fullerenes are a class of molecular nanomaterials with complex structures and novel properties. An in-depth study of their formation mechanism is a key topic for developing new high-yield synthesis methods and promoting the practical application of such molecular nanomaterials. To elucidate the formation mechanism of Sc3N@Cn, a representative sub-class of metal cluster fullerenes, this study developed a ReaxFF force field parameter set CNSc.ff using a single parameter optimization method and conducted systematic molecular dynamics simulations on a C-N-Sc mixed system using the newly developed force field parameter set. The results show that atomic nitrogen has strong attraction to both C and Sc atoms, and it plays a key role in the formation of Sc3N@Cn; the formation of Sc3N@Cn includes carbon cluster growth, Sc-based cluster growth and their encapsulation; temperature, carbon density, and atomic ratio all affect the relative yield of Sc3N@Cn; and the final products are a mixture of amorphous carbon, fullerenes, metallofullerenes, and metal cluster fullerenes. This study rationalizes the phenomena observed in the synthesis experiments and provides insights for the development of selective and high-yield synthesis methods for metal cluster fullerenes.

Engineering enzyme conformation within liquid-solid hybrid microreactors for enhanced continuous-flow biocatalysis

The artificial engineering of an enzyme’s structural conformation and dynamic properties to promote its catalytic activity and stability outside cellular environments is highly pursued in industrial biotechnology. Here, we describe an elegant strategy of combining the rationally designed liquid-solid hybrid microreactor with a tailor-made polyethylene glycol functional ionic liquid (PEG-IL) microenvironment to exercise a high level of control over the configuration of enzymes for practical continuous-flow biocatalysis. As exemplified by a lipase driven kinetic resolution reaction, the obtained system exhibits a 2.70 to 30.35-fold activity enhancement compared to their batch or traditional IL-based counterparts. Also, our results demonstrate that the thermal stability of encapsulated lipase can be significantly strengthened in the presence of PEG groups, showcasing a long-term continuous-flow stability even up to 1000 h at evaluated temperature of 60 oC. Through systematic experiment and molecular dynamics simulation studies, the conformational changes of the active site cavity in the modified lipases are correlated with enzymatic properties alteration, and the pronounced effects of PEG-groups in stabilizing enzyme’s secondary structures by delaying unfolding at elevated temperatures are identified. We believe that this study will guide the design of high-performance enzymatic systems, promoting their utilization in real-world biocatalysis applications.

Direct and indirect salt effects on homotypic phase separation

The low-complexity domain of hnRNPA1 (A1-LCD) phase separates in a salt-dependent manner. Unlike many intrinsically disordered proteins (IDPs) whose phase separation is suppressed by increasing salt concentrations, the phase separation of A1-LCD is promoted by >100 mM NaCl. To investigate the atypical salt effect on A1-LCD phase separation, we carried out all-atom molecular dynamics simulations of systems comprising multiple A1-LCD chains at NaCl concentrations from 50 to 1000 mM NaCl. The ions occupy first shell as well as more distant sites around the IDP chains, with Arg sidechains and backbone carbonyls the favored partners of Cl– and Na+, respectively. They play two direct roles in driving A1-LCD condensation. The first is to neutralize the high net charge of the protein (+9) by an excess of bound Cl– over Na+; the second is to bridge between A1-LCD chains, thereby fortifying the intermolecular interaction networks in the dense phase. At high concentrations, NaCl also indirectly strengthens π–π, cation–π, and amino–π interactions, by drawing water away from the interaction partners. Therefore, at low salt, A1-LCD is prevented from phase separation by net charge repulsion; at intermediate concentrations, NaCl neutralizes enough of the net charge while also bridging IDP chains to drive phase separation. This drive becomes even stronger at high salt due to strengthened π-type interactions. Based on this understanding, four classes of salt dependence of IDP phase separation can be predicted from amino-acid composition.

Direct and indirect salt effects on homotypic phase separation.

The low-complexity domain of hnRNPA1 (A1-LCD) phase separates in a salt-dependent manner. Unlike many intrinsically disordered proteins (IDPs) whose phase separation is suppressed by increasing salt concentrations, the phase separation of A1-LCD is promoted by >100 mM NaCl. To investigate the atypical salt effect on A1-LCD phase separation, we carried out all-atom molecular dynamics simulations of systems comprising multiple A1-LCD chains at NaCl concentrations from 50 to 1000 mM NaCl. The ions occupy first shell as well as more distant sites around the IDP chains, with Arg sidechains and backbone carbonyls the favored partners of Cl- and Na+, respectively. They play two direct roles in driving A1-LCD condensation. The first is to neutralize the high net charge of the protein (+9) by an excess of bound Cl- over Na+; the second is to bridge between A1-LCD chains, thereby fortifying the intermolecular interaction networks in the dense phase. At high concentrations, NaCl also indirectly strengthens π-π, cation-π, and amino-π interactions, by drawing water away from the interaction partners. Therefore, at low salt, A1-LCD is prevented from phase separation by net charge repulsion; at intermediate concentrations, NaCl neutralizes enough of the net charge while also bridging IDP chains to drive phase separation. This drive becomes even stronger at high salt due to strengthened π-type interactions. Based on this understanding, four classes of salt dependence of IDP phase separation can be predicted from amino-acid composition.

A molecular insight into the aggregation of cisplatin in aqueous solutions

Cisplatin (CPT), recognized as a widely used metallodrug, is a prevalent therapeutic agent for the treatment of various cancers. Given the diverse biological conditions in humans, as well as the hydrated environment within cells and the toxicity associated with CPT in cancer treatment, it is imperative to assess and optimize the solvation of CPT under various conditions. In this study, the influence of CPT on the structure of water is explored. In this regard, a systematic molecular dynamics (MD) simulation is employed to investigate the structure and dynamics of CPT in aqueous media, encompassing a range of concentrations from much diluted (0.05 M) to concentrated (5 M). The disruption of water structure by CPT molecules is determined using radial distribution function (RDF), mean-squared displacement (MSD), and combined radial/angular distribution function (CDF). Notably, the CPT aggregates exhibit an impact on the average number of water-water hydrogen bonds. Through calculations of apparent and partial molal volumes of CPT at various concentrations, we observed a sudden and dramatic change in the solution structures up to the critical aggregation concentration of CPT (0.5 molal), a finding corroborated by the calculations of diffusion coefficients. In summary, the self-aggregation of CPT molecules commences at 0.5 molal, leading to increased apparent and partial molal volumes with rising concentration. However, beyond 0.5 molal, the change in volumes becomes less significant, suggesting that while the number of CPT aggregates continues to increase, their size remains relatively constant above this concentration.

Molecular Dynamics Calculation of Interfacial Tension in a Two-Phase Liquid Hydrocarbon–Water–Surfactant System: From Rarefied to Superdense Surfactant Monolayer

A method is proposed for calculating low interfacial tension (IFT) based on molecular dynamics simulation of systems with superdense packing of surfactant molecules at the water–liquid hydrocarbon interface. The interfacial tension was calculated by the molecular dynamics method using the all-atom and coarse-grained models in water–alkane (decane, dodecane) two-phase systems in the presence of various individual surfactants. The following ionic and nonionic surfactants were considered: sodium dodecyl sulfate (SDS), cetyltrimethylammonium chloride (CTAC), sodium dodecylbenzenesulfonate (SDBS), sodium decet-6 sulfate C10E6SO4Na, hexaethylene glycol monodecyl ether (C10E6), triethylene glycol monononadecyl ether (C19E3), and octapropoxypentaethylene glycol monododecyl ether (C12P8E5). It was shown that the interfacial tension decreases to zero when surfactant adsorption increases to the limiting values.

A correct, reversible Trotter splitting for the evolution operator in molecular dynamics simulations of molecular systems with constraints

For generating an isobaric–isothermal ensemble in molecular dynamics simulations of atomic systems a correct ensemble distribution can be obtained by the approach of Martyna, Tobias and Klein [J. Chem. Phys. 101, 4177–4189 (1994)]. The constituting equations of the latter approach have been also generalised to molecular systems [M. E. Tuckerman, Statistical Mechanics: Theory and Molecular Simulation, Oxford Graduate Texts (2010)] using the molecular virial instead of the atomic one. An isothermal–isobaric method for systems with holonomic molecular constraints has been also introduced in the past [G. Kalibaeva, M. Ferrario and G. Ciccotti, Mol. Phys. 101 765–778 (2003)] but the factorisation was not worked out completely, resulting in a non-reversible first-order algorithm. Here, we propose the correct factorisation and implement a reversible integrator based on Martyna, Tobias and Klein equations for a system of molecules subjected to holonomic constraints. We add to the algorithm the Suzuki–Yoshida treatment that improves the energy conservation or permits to go to larger time steps. Finally, we test our algorithm by applying it to the dynamics of a Ortotherphenyl model.

Molecular insight on CO2/C3H8 mixed hydrate formation from the brine for sustainable hydrate-based desalination

Systematic molecular dynamics simulations have been performed to investigate the formation of CO2/C3H8 mixed hydrate in brine, to search for the optimal C3H8 content and elucidate the microscopic mechanism for hydrate-based desalination process. Simulation results indicate that the desalination process is significantly affected by the formation kinetics of CO2/C3H8 mixed hydrates due to the diverse physical properties of CO2 and C3H8 molecules in the brine. Specifically, CO2 molecules are more likely to leave the mixed gas nanobubbles and form hydrates, whereas most of C3H8 molecules remain in gas nanobubbles for a prolonged period. Interestingly, ions can form abnormal CO2-occupied and C3H8-occupied hydrate cages by replacing the water molecule in cages, and some ions can also be adsorbed on the surfaces of the cage-like hydrogen bond network or encapsulated between the hydrate solids. The presence of these ions presents a challenge to separating them due to the strong attraction from the water in hydrate solids. On the other hand, it is confirmed that the C3H8 content with 10 % is optimal for CO2/C3H8 mixed hydrate-based desalination, as it promotes the decomposition of mixed gas nanobubbles to form hydrates by suppressing the structural fluctuations in the system. These molecular insights into the effect of C3H8 content on CO2/C3H8 mixed hydrate formation in brine may help to develop hydrate-based desalination technology.

Atomistic description of the OCTN1 recognition mechanism via in silico methods.

The Organic Cation Transporter Novel 1 (OCTN1), also known as SLC22A4, is widely expressed in various human tissues, and involved in numerous physiological and pathological processes remains. It facilitates the transport of organic cations, zwitterions, with selectivity for positively charged solutes. Ergothioneine, an antioxidant compound, and acetylcholine (Ach) are among its substrates. Given the lack of experimentally solved structures of this protein, this study aimed at generating a reliable 3D model of OCTN1 to shed light on its substrate-binding preferences and the role of sodium in substrate recognition and transport. A chimeric model was built by grafting the large extracellular loop 1 (EL1) from an AlphaFold-generated model onto a homology model. Molecular dynamics simulations revealed domain-specific mobility, with EL1 exhibiting the highest impact on overall stability. Molecular docking simulations identified cytarabine and verapamil as highest affinity ligands, consistent with their known inhibitory effects on OCTN1. Furthermore, MM/GBSA analysis allowed the categorization of substrates into weak, good, and strong binders, with molecular weight strongly correlating with binding affinity to the recognition site. Key recognition residues, including Tyr211, Glu381, and Arg469, were identified through interaction analysis. Ach demonstrated a low interaction energy, supporting the hypothesis of its one-directional transport towards to outside of the membrane. Regarding the role of sodium, our model suggested the involvement of Glu381 in sodium binding. Molecular dynamics simulations of systems at increasing levels of Na+ concentrations revealed increased sodium occupancy around Glu381, supporting experimental data associating Na+ concentration to molecule transport. In conclusion, this study provides valuable insights into the 3D structure of OCTN1, its substrate-binding preferences, and the role of sodium in the recognition. These findings contribute to the understanding of OCTN1 involvement in various physiological and pathological processes and may have implications for drug development and disease management.

Efficient Alcoholysis of Poly(ethylene terephthalate) by Using Supercritical Carbon Dioxide as a Green Solvent.

In order to reduce the environmental impact of poly(ethylene terephthalate) (PET) plastic waste, supercritical fluids were used to facilitate effective recovery via improved solvent effects. This work focuses on the mechanisms of supercritical CO2 (ScCO2) during the alcoholysis processing of PET using systematic experiments and molecular dynamics (MD) simulations. The results of the alcoholysis experiment indicated that PET chips can be completely depolymerized within only an hour at 473 K assisted with ScCO2 at an optimal molar ratio of CO2/ethanol of 0.2. Random scission of PET dominates the early stage of the depolymerization reaction process, while specific scission dominates the following stage. Correspondingly, molecular dynamics (MD) simulations revealed that the solubilization and self-diffusion properties of ScCO2 facilitate the transportation of alcohol molecules into the bulk phase of PET, which leads to an accelerated diffusion of both oligomers and small molecules in the system. However, the presence of excessive CO2 has a negative impact on depolymerization by weakening the hydrogen bonding between polyester chain segments and ethanol, as well as decreasing the swelling degree of PET. These data provide a deep understanding of PET degradation by alcohols and the enhancement of ScCO2. It should be expected to achieve an efficient and high-yield depolymerization process of wasted polyesters assisted with ScCO2 at a relatively low temperature.

Molecular dynamics simulations of interaction of cascade damage with self-interstitial atom-loaded grain boundaries in tungsten

In this study, we conducted systematic molecular dynamics simulations to investigate the radiation resistance of grain boundaries (GBs) in tungsten with/without self-interstitial atoms (SIAs) loaded on them. The simulation results show that the presence of SIAs can extend the width of the Σ3<110>{112} twin GB compared to the SIA-free GB. When cascade damage occurs near Σ3, the presence of SIAs at Σ3 enhances radiation resistance. Specifically, it inhibits producing residual defects, particularly vacancies and prevents their aggregating into clusters. The radiation-resistant performance is most excellent when the SIA concentration at Σ3 is approximately 5 %. The influence of temperature and primary knock-on atom energy on radiation damage is also discussed. However, SIA-loaded high angle GBs and low angle GBs do not significantly enhance their radiation-resistant performance compared to their SIA-free counterparts. This study provides valuable insights into the radiation damage behaviors near GBs and contributes to understanding their radiation-resistant mechanisms.

CO Intermediate-Assisted Dynamic Cu Sintering During Electrocatalytic CO2 Reduction on Cu-N-C Catalysts.

The electrochemical CO2 reduction reaction (eCO2RR) to multicarbon products has been widely recognized for Cu-based catalysts. However, the structural changes in Cu-based catalysts during the eCO2RR pose challenges to achieving an in-depth understanding of the structure-activity relationship, thereby limiting catalyst development. Herein, we employ constant-potential density functional theory calculations to investigate the sintering process of Cu single atoms of Cu-N-C single-atom catalysts into clusters under eCO2RR conditions. Systematic constant-potential ab initio molecular dynamics simulations revealed that the leaching of Cu-(CO)x moieties and subsequent agglomeration into clusters can be facilitated by synergistic adsorption of H and eCO2RR intermediates (e.g., CO). Increasing the Cu2+ concentration or the applied potential can efficiently suppress Cu sintering. Both microkinetic simulations and experimental results further confirm that sintered Cu clusters play a crucial role in generating C2 products. These findings provide significant insights into the dynamic evolution of Cu-based catalysts and the origin of their activity toward C2 products during the eCO2RR.

A machine learning interatomic potential for high entropy alloys

High entropy alloys (HEAs) possess a vast compositional space, providing exciting prospects for tailoring material properties yet also presenting challenges in their rational design. Efficiently achieving a well-designed HEA often necessitates the aid of atomistic simulations, which rely on the availability of high-quality interatomic potentials. However, such potentials for most HEA systems are missing due to the complex interatomic interaction. To fundamentally resolve the challenge of the rational design of HEAs, we propose a strategy to build a machine learning (ML) interatomic potential for HEAs and demonstrate this strategy using CrFeCoNiPd as a model material. The fully trained ML model can achieve remarkable prediction precision (>0.92 R2) for atomic forces, comparable to the ab initio molecular dynamics (AIMD) simulations. To further validate the accuracy of the ML model, we implement the ML potential for CrFeCoNiPd in parallel molecular dynamics (MD) code. The MD simulations can predict the lattice constant (1 % error) and stacking fault energy (10 % error) of CrFeCoNiPd HEAs with high accuracy compared to experimental results. Through systematic MD simulations, for the first time, we reveal the atomic-scale deformation mechanisms associated with the stacking fault formation and dislocation cross-slips in CrFeCoNiPd HEAs under uniaxial compression, which are consistent with experimental observations. This study can help elucidate the underlying deformation mechanisms that govern the exceptional performance of CrFeCoNiPd HEAs. The strategy to establish ML interatomic potentials could accelerate the rational design of new HEAs with desirable properties.

Systematic Coarse Graining of Environments for the Nonperturbative Simulation of Open Quantum Systems.

Conducting precise electronic-vibrational dynamics simulations of molecular systems poses significant challenges when dealing with realistic environments composed of numerous vibrational modes. Here, we introduce a technique for the construction of effective phonon spectral densities that capture accurately open-system dynamics over a finite time interval of interest. When combined with existing nonperturbative simulation tools, our approach can reduce significantly the computational costs associated with many-body open-system dynamics.

Wettability-modulated behavior of polymers under varying degrees of nano-confinement

Extreme confinement in nanochannels results in unconventional equilibrium and flow behavior of polymers. The underlying flow physics dictating such paradigms remains far from being understood and more so if the confining substrate is composed of two-dimensional materials, such as graphene. In this study, we conducted systematic molecular dynamics simulations to explore the effect of wettability, confinement, and chain length on polymer flow through graphene-like nanochannels. Altering the wetting properties of these membranes that structurally represent graphene results in substantial changes in the behavior of polymers of disparate chain lengths. Longer hydrocarbon chains (n-dodecane) exhibit negligible wettability-dependent structuring in narrower nanochannels compared to shorter chains (n-hexane) culminating in higher average velocities and interfacial slippage of n-dodecane under less wettable conditions. We demonstrate that the wettability compensation comes from chain entanglement attributed to entropic factors. This study reveals a delicate balance between wettability-dependent enthalpy and chain-length-dependent entropy, resulting in a unique nanoscale flow paradigm, thus not only having far-reaching implications in the superior discernment of polymeric flow in sub-micrometer regimes but also potentially revolutionizing various applications in the oil industry, including innovative oil transport, oil extraction, ion transport polymers, and separation membranes.

Macroscale and durable near-zero wear performance on steel surfaces achieved by natural ternary deep eutectic solvents

Macroscale and durable near-zero wear performance of ternary deep eutectic solvent-based lubricants was elaborated by systematic experimental analysis and molecular dynamics simulation.

Passive fractionating mechanism for oil spill using shear-wettability modulation.

Oil spillage and organic solvent leakage have been a frequent occurrence in recent years, which pose a significant threat not only to the aquatic ecosystems but also result in substantial economic burdens. This has necessitated the search for materials capable of separating oil from water at enhanced efficiency with superior mechanical and thermal properties. In this study, we conduct a set of systematic molecular dynamics simulations to investigate the potential of two-dimensional graphene-like channels under extreme confinement to achieve efficient oil-water separation. Effective modulation of the wetting characteristics of graphene-like surfaces juxtaposed with unconventional flow behavior at the nanoscale unveils differential interaction of water and oil molecules towards the wall, thereby resulting in distinct separation zones for varying compositions of the oil-water mixture. Such separation zones have been observed to be highly correlated with mixture temperature, which provides effective separation pathways across diverse environmental conditions. Our study offers a paradigm shift in oil-water separation strategies, which not only provides deeper insights into the equilibrium and dynamic behavior of a two-phase mixture but also holds immense implications for the development of smart, wettability-based oil separation devices.

Elucidating the microscopic origin of observed anti-correlation between the protein-protein and protein-water interaction energies

Water as a solvent plays an important role in dictating the structure and dynamics of the large biomolecules like proteins. It has been proposed that the protein dynamics and energetics are closely coupled to the water molecules in the hydration shell. In particular, it has been shown earlier that the fluctuations in intra-protein (protein-protein) interaction energy is strongly anti-correlated with the protein-water interaction energy (solvation energy). Moreover, the dynamical signatures of water gets reflected into the protein dynamics in terms of a dominant power law behavior. In this work, we have carried out systematic molecular dynamics (MD) simulations of three different protein systems to understand the key physical factors that contribute to such anti-correlations. First, we compare the dynamics in globular folded proteins like Lysozyme with intrinsically disordered peptides (IDPs) like Amyloid beta to show that enhanced conformational fluctuations lead to significantly stronger anti-correlation. Trp-cage miniprotein shows a similar behavior distributed over two sub-ensembles of folded and unfolded states. We also investigate what type of interactions and molecular processes are responsible for the observed anti-correlation. In particular, we observe that the extent of correlation decreases significantly in the order of charged, polar and non-polar amino acid residues. Charged residues that form salt bridge interactions show a dominant anti-correlation. Surprisingly, a few non-polar (hydrophobic and buried) residues demonstrate significant anti-correlation as well. We attribute this to the structural fluctuations that lead to an equilibrium between buried and solvent exposed states of these residues, where the protein-protein and protein-water interactions compensate each other. Our studies indicate that the molecular origin of the observed anti-correlation can be vary depending on the type of the interaction. The overall coupling/correlation is dominated by the electrostatic interactions and charged residues due to a general dielectric screening effect, whereas a few buried hydrophobic residues may also show such coupling due to structural dynamics between buried and exposed states.

Towards understanding the crack suppression mechanism in brittle materials with high grinding speed at different temperatures

Ductile-regime grinding has been used to eliminate the formation of subsurface cracks by setting an extremely small depth of cut (DOC). The critical DOC is affected by multiple factors, including the grinding speed and material temperature. The underlying mechanism of DOC affected by the grinding speed is still unclear. To reveal the role of grinding speed and material temperature during the formation of cracks, we conducted a series of single-point grinding experiments with the different grinding speeds (26.7–192.3 m/s) and the initial material temperatures (25–200 °C). The experimental results showed that cracks were suppressed with an increase in the grinding speed and initial material temperature even when the DOC was much deeper than the critical DOC determined by the ductile-regime grinding. To understand the mechanisms underlying crack nucleation and suppression, we conducted systematic molecular dynamics simulations. Both simulation and experimental results showed that a crack can be formed by a single slip band. The crack nucleates from a microvoid within the slip band. With the aid of the local tensile stress on one side of the slip band tip, the crack nucleation forms an opening crack. The crack suppression is primarily caused by the high‐pressure field during high‐speed grinding, where the high‐pressure field superposes the local tensile stress to forming a compressive stress state that prevents crack nucleation. In addition, the brittle‐ductile transition is induced by the high temperature on the surface during high‐speed grinding. This study provides insights into building the DOC criterion for different grinding speeds and temperatures based on a ‘bottom-up’ approach.