Dynamics Simulations Of Molecules Research Articles

Hydrogen purification via hydrate-based methods: Insights into H2-CO2-CO hydrate structures, thermodynamics, and kinetics

Hydrate-based H2 purification is promising for removing impurities owing to the cage-like structures formed by water molecules. Understanding the competition mechanism of multicomponent gas molecule in hydrate is critical for improving gas purification efficiency. This study investigated the hydrate structure, thermodynamics, and kinetics of ternary gas mixture (H2–CO2–CO) from natural gas reforming products. The results identified H2–CO2–CO hydrate as type sI and determined the lattice parameters using X-ray diffraction. Raman spectroscopy results confirmed the presence of H2, CO2, and CO gas molecules in the hydrate phase. Increasing pressure, compared to cooling, enhanced CO2 content in hydrate phase. The phase equilibrium conditions and average hydrate dissociation enthalpy (53.47 J/g) were determined using a high-pressure microcalorimeter. Gas chromatography identified that the content of CO2 in the hydrate was the highest, followed by H2, and CO was the least abundant. The molecule dynamics simulation results show CO2 molecule numbers reflected trends in 51262 cages, H2 numbers correlated with changes in 512 cages, while CO numbers showed insignificant variation. Under the gas composition studied, the ability of gas molecules to be incorporated within hydrates decreases in the following order: CO2, H2, and CO.

Nano-twinned silicon in Al-Si alloys for high wear-resistance

Wear-failure is the most common damage for power transmission components in the field of engineering materials, constituting approximately one-fourth in service loss. The development of high wear-resistant Al alloys plays a crucial role in reducing energy demand and weight, and then attributes to the achievement of dual-carbon target. Here we report a novel strategy to develop outstanding wear-resistant (the coefficient of friction of 0.31) Al-10 wt%Si alloys at room temperature, based on the formation of multiple parallel {111} twins and hierarchical {111}-{111} double twins by a route of combining ultrahigh pressure solid solution and electropulsing assisted aging (HPEP), which overwhelms all values of Al alloys, even Ti alloys and high entropy alloys reported so far. The microstructure, formation process and wear-resistant mechanism of nano-twinned Si have been clarified by transmission electron microscopy observations, molecule dynamics simulations and the first principles calculations. It demonstrates that the interactive nano-twinned Si structures are mainly introduced through twin-twin collision or the phase/matrix interface prohibition of twin motion, which are effective to restrain atom separation in contrast to eutectic Si perfect crystal, resulting in homogeneous wear-loss and long operation life. Those new results provide insights towards designing wear-resistant materials with high mechanical properties.

Multi-GPU RI-HF Energies and Analytic Gradients─Toward High-Throughput Ab Initio Molecular Dynamics.

This article presents an optimized algorithm and implementation for calculating resolution-of-the-identity Hartree-Fock (RI-HF) energies and analytic gradients using multiple graphics processing units (GPUs). The algorithm is especially designed for high throughput ab initio molecular dynamics simulations of small and medium size molecules (10-100 atoms). Key innovations of this work include the exploitation of multi-GPU parallelism and a workload balancing scheme that efficiently distributes computational tasks among GPUs. Our implementation also employs techniques for symmetry utilization, integral screening, and leveraging sparsity to optimize memory usage. Computational results show that the implementation achieves significant performance improvements, including over 3 × speedups in single GPU AIMD throughput compared to previous GPU-accelerated RI-HF and traditional HF methods. Furthermore, utilizing multiple GPUs can provide superlinear speedup when the additional aggregate GPU memory allows for the storage of decompressed three-center integrals.

Deep learning model for precise prediction and design of low-melting point phthalonitrile monomers

Phthalonitrile is a widely applied resin due to its outstanding high-temperature resistance and versatility. However, the high melting point of its monomer limits its range of applications. Due to the scarcity of data, traditional deep learning models face challenges in accurately predicting the properties of phthalonitrile monomers. In this work, we propose a novel deep learning model based on techniques such as molecular similarity weighting, pre-training parameter averaging, and hybrid neural networks to address the issue of data sparsity. Our model exhibits exceptionally high accuracy for predicting the melting point of phthalonitrile monomers, e.g., the mean absolute error on the experimental dataset is 15.3 °C. To explore novel low-melting monomers, we develop a high-throughput molecule generation software and use our model to filter the virtual molecules, and ultimately obtain candidates that meet low-melting and synthesizability requirements. Moreover, we have successfully synthesized one candidate molecule, and the high consistency between our predictions and experimental measurements again demonstrates our model’s accuracy. Meanwhile, molecule dynamic simulations are conducted to provide explanations for the reduction in melting point. This study not only provides guidance for designing phthalonitrile monomers, but also proposes an innovative approach for exploring of new materials under conditions of sparse data.

Structure and interactions of CO2 with reline (a 1:2 choline chloride – Urea mixture) according to quantum chemical calculations and molecular dynamics simulation

Quantum chemical DFT calculations [B3LYP+GD3/6-311++g(2d,2p)] of the structure and interactions in various complexes of CO2 molecule with a choline cation, a chloride anion, urea molecules, a choline chloride ion pair and a 1:2 choline chloride – urea complex were carried out. The contributions of Coulomb and van der Waals interactions were calculated. The QTAIM method was used to evaluate the strength of various bonds. A molecular dynamics simulation of CO2 molecules in reline in the NPT ensemble (1 atm, 298 K) was also carried out. The radial distribution functions of the particle centers of mass, local mole fraction functions, spatial distribution functions, and density profiles were calculated. Stronger interactions, compared to the other DES components, were observed in case of the chloride anion and the CO2 molecule according to the DFT calculations. However, in the system, stronger interactions were observed between the chloride anion and the system components, namely NHCl and OHCl hydrogen bonds. This made the chloride anion inaccessible and unable to interact with the CO2 molecule, according to the MD simulation results. Additionally, the presence of a fairly extensive surface layer containing DES and CO2 molecules was shown.

STORMM: Structure and topology replica molecular mechanics for chemical simulations.

The Structure and TOpology Replica Molecular Mechanics (STORMM) code is a next-generation molecular simulation engine and associated libraries optimized for performance on fast, vectorized central processor units and graphics processing units (GPUs) with independent memory and tens of thousands of threads. STORMM is built to run thousands of independent molecular mechanical calculations on a single GPU with novel implementations that tune numerical precision, mathematical operations, and scarce on-chip memory resources to optimize throughput. The libraries are built around accessible classes with detailed documentation, supporting fine-grained parallelism and algorithm development as well as copying or swapping groups of systems on and off of the GPU. A primary intention of the STORMM libraries is to provide developers of atomic simulation methods with access to a high-performance molecular mechanics engine with extensive facilities to prototype and develop bespoke tools aimed toward drug discovery applications. In its present state, STORMM delivers molecular dynamics simulations of small molecules and small proteins in implicit solvent with tens to hundreds of times the throughput of conventional codes. The engineering paradigm transforms two of the most memory bandwidth-intensive aspects of condensed-phase dynamics, particle-mesh mapping, and valence interactions, into compute-bound problems for several times the scalability of existing programs. Numerical methods for compressing and streamlining the information present in stored coordinates and lookup tables are also presented, delivering improved accuracy over methods implemented in other molecular dynamics engines. The open-source code is released under the MIT license.

Atomistic Molecular Dynamics Simulations of ABA-Type Polymer Peptide Conjugates: Insights into Supramolecular Structures and their Circular Dichroism Spectra.

A combination of atomistic molecular dynamics (aMD) simulations and circular dichroism (CD) analysis is used to explore supramolecular structures of amphiphilic ABA-type triblock polymer peptide conjugates (PPC). Using the example of a recently introduced PPC with pH- and temperature responsive self-assembling behavior [Otter etal., Macromolecular Rapid Communications 2018, 39, 1800459], this study shows how molecular dynamics simulations of simplified fragment molecules can add crucial information to CD data, which helps to correctly identify the self-assembled structures and monitor the folding/unfolding pathways of the molecules. The findings offer insights into the nature of structural transitions induced by external stimuli, thus contributing to the understanding of the connection of microscopic structures with macroscopicproperties.

Fe-NiO/MoO2 and in-situ reconstructed Fe, Mo-NiOOH with enhanced negatively charges of oxygen atoms on the surface for salinity tolerance seawater splitting

Seawater electrolysis is a promising technique for H2 production on a large scale. However, the electrocatalytic activity and stability will be deteriorated as the increase of salt concentrations which happened in the seawater splitting. Herein, through the electrodeposition and rapid Joule heating method, the Fe-NiO/MoO2 heterostructure is designed as a highly active bifunctional electrocatalyst. During the OER possess, Fe-NiO/MoO2 is reconstructed to the Fe, Mo-NiOOH with Fe and Mo co-doping. Based on the theoretical analysis, more electrons were transferred to the O atoms on the surface of Fe, Mo-NiOOH, thereby forming a more negatively charged surface. Moreover, that surface is found to repel Cl− ions while enriching H2O molecules to form a thin water layer on Fe, Mo-NiOOH surface based on molecule dynamics (MD) simulation, thereby improving the anti-corrosion capacity of Fe, Mo-NiOOH. The reconstructed Fe, Mo-NiOOH achieved an overpotential of 399 mV at 1000 mA cm−2 in alkaline seawater, and the increase of overpotential for Fe, Mo-NiOOH was about 0.02 V at 500 mA cm−2 from 0 M to 3 M NaCl in 1 M KOH electrolyte. For the HER, Fe-NiO/MoO2 achieved an overpotential of 169 mV and 417 mV at 100 and 1000 mA cm−2 in alkaline seawater, respectively, and the increase of overpotential for Fe-NiO/MoO2 was about 0 mV at 500 mA cm−2 from 0 M to 3 M NaCl in 1 M KOH electrolyte. This work sheds fresh light into the development of efficient electrocatalysts for salinity tolerance seawater splitting.

Sequence-Guided Redesign of an Omega-Transaminase from Bacillus megaterium for the Asymmetric Synthesis of Chiral Amines.

ω-Transaminases (ω-TAs) are attractive biocatalysts asymmetrically catalyzing ketones to chiral amines. However, poor non-native catalytic activity and substrate promiscuity severely hamper its wide application in industrial production. Protein engineering efforts have generally focused on reshaping the substrate-binding pockets of ω-TAs. However, hotspots around the substrate tunnel as well as distant sites outside the pockets may also affect its activity. In this study, the ω-TA from Bacillus megaterium (BmeTA) was selected for engineering. The tunnel mutation Y164F synergy with distant mutation A245T which was acquired through a multiple sequence alignment showed improved soluble expression, a 3.7-fold higher specific activity and a 19.9-fold longer half-life at 45 °C. Molecule Dynamics simulation explains the mechanism of improved catalytic activity, enhanced thermostability and improved soluble expression of BmeTAY164F/A245T(2 M). Finally, the resting cells of 2 M were used for biocatalytic processes. 450 mM of S-methoxyisopropylamine (S-MOIPA) was obtained with an ee value of 97.3 % and a conversion rate of 90 %, laying the foundation for its industrial production. Mutant 2 M was also found to be more advantageous in catalyzing the transamination of various ketones. These results demonstrated that sites that are far away from the active center also play an important role in the redesign of ω-TAs.

Blocking Interfacial Proton Transport via Self‐Assembled Monolayer for Hydrogen Evolution‐Free Zinc Batteries

AbstractAqueous Zn‐ion batteries (ZIBs) are promising next‐generation energy storage devices, yet suffer from the issues of hydrogen evolution reaction (HER) and intricate side reactions on the Zn anode surface. The hydrogen (H)‐bond networks play a critical role in interfacial proton transport that may closely relate to HER but are rarely investigated. Herein, we report a self‐assembled monolayer (SAM) strategy which is constructed by anchoring ionic liquid cations on Ti3C2Tx substrate for HER‐free Zn anode. Molecule dynamics simulations reveal that the rationally designed SAM with a high coordination number of water molecules (25–27, 4–6 for Zn2+) largely reduces the interfacial densities of H2O molecules, therefore breaking the connectivity of H‐bond networks and blocking proton transport on the interface, by which the HER is suppressed. Then, a series of in situ characterizations demonstrate that negligible amounts of H2 gas are collected from the Zn@SAM‐MXene anode. Consequently, the symmetric cell enables a long‐cycling life of 3000 h at 1 mA cm−2 and 1000 h at 5 mA cm−2. More significantly, the stable Zn@SAM‐MXene films are successfully used for coin full cells showing high‐capacity retention of over 94 % after 1000 cycles and large‐area (10×5 cm2) pouch cells with desired performance.

Blocking Interfacial Proton Transport via Self-Assembled Monolayer for Hydrogen Evolution-Free Zinc Batteries.

Aqueous Zn-ion batteries (ZIBs) are promising next-generation energy storage devices, yet suffer from the issues of hydrogen evolution reaction (HER) and intricate side reactions on the Zn anode surface. The hydrogen (H)-bond networks play a critical role in interfacial proton transport that may closely relate to HER but are rarely investigated. Herein, we report a self-assembled monolayer (SAM) strategy which is constructed by anchoring ionic liquid cations on Ti3C2Tx substrate for HER-free Zn anode. Molecule dynamics simulations reveal that the rationally designed SAM with a high coordination number of water molecules (25-27, 4-6 for Zn2+) largely reduces the interfacial densities of H2O molecules, therefore breaking the connectivity of H-bond networks and blocking proton transport on the interface, by which the HER is suppressed. Then, a series of in situ characterizations demonstrate that negligible amounts of H2 gas are collected from the Zn@SAM-MXene anode. Consequently, the symmetric cell enables a long-cycling life of 3000 h at 1 mA cm-2 and 1000 h at 5 mA cm-2. More significantly, the stable Zn@SAM-MXene films are successfully used for coin full cells showing high-capacity retention of over 94 % after 1000 cycles and large-area (10×5 cm2) pouch cells with desired performance.

Analysis of the relationship between starch molecular conformation and enzymatic hydrolysis efficiency

Resistant starch (RS) is important in controlling diabetes. The primary objective of this study is to examine the impact of molecular conformation on the enzymatic hydrolysis efficiency of starch by α-amylase. And the interactions between starch molecules with different conformations and α-amylase were analysed by using molecule dynamics simulation and molecular docking. It was found, the natural conformational starch molecule was hydrolysed from the middle of the starch chain by α-amylase, producing polysaccharides. The bent PS-conformational starch molecules with multiple O2-O3 intramolecular hydrogen bonds produced by high-pressure was hydrolysed from the head of the starch chain to produce glucose, which is not conducive to RS formation. The stretched H-conformation without intramolecular hydrogen bonds produced by heat treatment was not hydrolysed by α-amylase. However, it occupied the active groove and formed strong interactions with α-amylase, which prevented other starch molecules from binding to α-amylase, thus reducing hydrolysis efficiency. Moreover, the total interaction energies between the three starch molecules and α-amylase were approximately 78 kJ/mol. And several hydrogen bonds were formed between the starch molecules and α-amylase, which provides evidence for the continuous sliding hydrolysis hypothesis of α-amylase. Moreover, these results provide an important reference for elucidating the mechanism of RS formation.

Vitrification-enabled enhancement of proton conductivity in hydrogen-bonded organic frameworks

Hydrogen-bonded organic frameworks (HOFs) are versatile materials with potential applications in proton conduction. Traditional approaches involve incorporating humidity control to address grain boundary challenges for proton conduction. This study finds vitrification as an alternative strategy to eliminate grain boundary effect in HOFs by rapidly melt quenching the kinetically stable HOF-SXU-8 to glassy state HOF-g. Notably, a remarkable enhancement in proton conductivity without humidity was achieved after vitrification, from 1.31 × 10−7 S cm−1 to 5.62× 10−2 S cm−1 at 100 °C. Long term stability test showed negligible performance degradation, and even at 30 °C, the proton conductivity remained at high level of 1.2 × 10−2 S cm−1. Molecule dynamics (MD) simulations and X-ray total scattering experiments reveal the HOF-g system is consisted of three kinds of clusters, i.e., 1,5-Naphthalenedisulfonic acid (1,5-NSA) anion clusters, N,N-dimethylformamide (DMF) molecule clusters, and H+-H2O clusters. In which, the H+ plays an important role to bridge these clusters and the high conductivity is mainly related to the H+ on H3O+. These findings provide valuable insights for optimizing HOFs, enabling efficient proton conduction, and advancing energy conversion and storage devices.

The optimization of evaporation rate in graphene-water system by machine learning algorithm

Solar interfacial evaporation, as a novel practical freshwater production method, requires continuous research on how to improve the evaporation rates to increase water production. In this study, sets of data were obtained from molecule dynamics simulation and literature, in which the parameters included height, diameter, height–radius ratio, evaporation efficiency, and evaporation rate. Initially, the correlation between the four input parameters and the output of the evaporation rate was examined through traditional pairwise plots and Pearson correlation analysis, revealing weak correlations. Subsequently, the accuracy and generalization performance of the evaporation rate prediction models established by neural network and random forest were compared, with the latter demonstrating superior performance and reliability confirmed via random data extraction. Furthermore, the impact of different percentages (10%, 20%, and 30%) of the data on the model performance was explored, and the result indicated that the model performance is better when the test set is 20% and all the constructed model converge. Moreover, the mean absolute error and mean squared error of the evaporation rate prediction model for the three ratios were calculated to evaluate their performance. However, the relationship between the height- radius ratio and optimal evaporation rate was investigated using the enumeration method, and it was determined that the evaporation efficiency was optimal when the height–radius ratio was 6. Finally, the importance of height, diameter, height– radius ratio, and evaporation efficiency were calculated to optimize evaporator structure, increase evaporation rate, and facilitate the application of interfacial evaporation in solar desalination.

Simulating chemical reaction dynamics on quantum computer.

The electronic energies of molecules have been successfully evaluated on quantum computers. However, more attention is paid to the dynamics simulation of molecules in practical applications. Based on the variational quantum eigensolver (VQE) algorithm, Fedorov et al. proposed a correlated sampling (CS) method and demonstrated the vibrational dynamics of H2 molecules [J. Chem. Phys. 154, 164103 (2021)]. In this study, we have developed a quantum approach by extending the CS method based on the VQE algorithm (labeled eCS-VQE) for simulating chemical reaction dynamics. First, the CS method is extended to the three-dimensional cases for calculation of first-order energy gradients, and then, it is further generalized to calculate the second-order gradients of energies. By calculating atomic forces and vibrational frequencies for H2, LiH, H+ + H2, and Cl- + CH3Cl systems, we have seen that the approach has achieved the CCSD level of accuracy. Thus, we have simulated dynamics processes for two typical chemical reactions, hydrogen exchange and chlorine substitution, and obtained high-precision reaction dynamics trajectories consistent with the classical methods. Our eCS-VQE approach, as measurement expectations and ground-state wave functions can be reused, is less demanding in quantum computing resources and is, therefore, a feasible means for the dynamics simulation of chemical reactions on the current noisy intermediate-scale quantum-era quantum devices.

Abstract 4388: Tumor-associated RhoA mutants interact with effectors in both GDP- and GTP-bound states

Abstract RhoA is the founding member of the Ras-homology (Rho) small GTPase family and is a master regulator for multiple cell functions. Recurrent RhoA mutations have been identified in several human cancers, particularly in leukemia/lymphoma and gastric cancer. Intriguingly, both gain-of-function and loss-of-function mutations of RhoA are present, suggesting that RhoA GTPase may have a more sophisticated role in cancer and requires more rigorous investigations. Here, we have focused on two of the gain-of-function RhoA mutations identified in Adult T cell Leukemia/lymphoma (ATLL) at residue A161 (A161P and A161V) and aim to reveal the underlying mechanistic basis for their function by biochemical and structural analyses. We found that in contrast to conventional gain-of-function RhoA mutants such as RhoAG14V and RhoAQ63L which affect the GTP-hydrolysis activity, RhoAA161P and RhoAA161Vare both fast-cycling with drastically increased nucleotide dissociation and association rates, but only slightly reduced GTP-hydrolysis activity. We solved the crystal structures of GDP-bound RhoAA161P and RhoAA161V and saw that while RhoAA161P displays impaired solvent-mediated interactions to the bound nucleotide, RhoAA161V has a more exposed nucleotide binding pocket compared to RhoAWT and RhoAA161P. Interestingly, RhoAA161P and RhoAA161Vcan interact with effector targets in the GDP-bound states. Further 1H-15N HSQC NMR study provides evidence of the active population in GDP-bound RhoAA161V. Molecule dynamics (MD) simulations show that the dynamic properties of RhoA switch regions are affected differently by the two mutations. Thus, RhoAA161V and RhoAA161P are fast-cycling mutants with distinct mechanisms, and both likely endow their GDP-bound state towards an active conformation. These findings provide a better understanding of the oncogenic role of RhoA mutations in cancer and shine light on how changes in RhoA protein dynamic properties caused by mutations may affect its function. Citation Format: Yuan Lin, Theresa A. Ramelot, Simge Senyuz, Attila Gursoy, Hyunbum Jang, Ruth Nussinov, Ozlem Keskin, Yi Zheng. Tumor-associated RhoA mutants interact with effectors in both GDP- and GTP-bound states [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4388.

Aqueous-phase chemistry of glyoxal with multifunctional reduced nitrogen compounds: a potential missing route for secondary brown carbon

Abstract. The aqueous-phase chemistry of glyoxal (GL) with reduced nitrogen compounds (RNCs) is a significant source for secondary brown carbon (SBrC), which is one of the largest uncertainties in climate predictions. However, a few studies have revealed that SBrC formation is affected by multifunctional RNCs, which have a non-negligible atmospheric abundance. Hence, we assessed theoretical and experimental approaches to investigate the reaction mechanisms and kinetics of the mixtures for ammonium sulfate (AS), multifunctional amine monoethanolamine (MEA), and GL. Our experiments indicate that light absorption and growth rate are enhanced more efficiently in the MEA–GL mixture relative to AS–GL and MEA–AS–GL mixtures and MEA reactions of the chromophores than in the analogous AS reactions. Quantum chemical calculations show that the formation and propagation of oligomers proceed via four-step nucleophilic addition reactions in three reaction systems. The presence of MEA provides the two extra branched chains that affect the natural charges and steric hindrance of intermediates, facilitating the formation of chromophores. Molecule dynamics simulations reveal that the interfacial and interior attraction on the aqueous aerosols with MEA is more pronounced for small α-dicarbonyls to facilitate further engagement in the aqueous-phase reactions. Our results show a possible missing source for SBrC formation on urban, regional, and global scales.

Closing the Gap between Experiment and Simulation─A Holistic Study on the Complexation of Small Interfering RNAs with Polyethylenimine.

Rational design is pivotal in the modern development of nucleic acid nanocarrier systems. With the rising prominence of polymeric materials as alternatives to lipid-based carriers, understanding their structure-function relationships becomes paramount. Here, we introduce a newly developed coarse-grained model of polyethylenimine (PEI) based on the Martini 3 force field. This model facilitates molecular dynamics simulations of true-sized PEI molecules, exemplified by molecules with molecular weights of 1.3, 5, 10, and 25 kDa, with degrees of branching between 50.0 and 61.5%. We employed this model to investigate the thermodynamics of small interfering RNA (siRNA) complexation with PEI. Our simulations underscore the pivotal role of electrostatic interactions in the complexation process. Thermodynamic analyses revealed a stronger binding affinity with increased protonation, notably in acidic (endosomal) pH, compared to neutral conditions. Furthermore, the molecular weight of PEI was found to be a critical determinant of binding dynamics: smaller PEI molecules closely enveloped the siRNA, whereas larger ones extended outward, facilitating the formation of complexes with multiple RNA molecules. Experimental validations, encompassing isothermal titration calorimetry and single-molecule fluorescence spectroscopy, aligned well with our computational predictions. Our findings not only validate the fidelity of our PEI model but also accentuate the importance of in silico data in the rational design of polymeric drug carriers. The synergy between computational predictions and experimental validations, as showcased here, signals a refined and precise approach to drug carrier design.

Density functional theory and molecular dynamics simulation of water molecules confined between parallel graphene oxide surfaces using new interaction potentials

In this study, the interaction potential of water molecule with a graphene oxide (GO) plate containing OH and O groups has been calculated using the M06-2X/6-31g(d,p) level of theory at different orientations and intermolecular distances and fitted to the Born-Huggins-Meyer (BHM) model. There are good agreements between the calculated and the OPLS-AA and Dreiding models, especially for the GO(O)-H2O interactions. To examine the new computed models, we have used the closer potentials to the OPLS-AA and Dreiding models in the molecular dynamics (MD) simulations. We have calculated several properties using the different obtained interaction potentials including average number of hydrogen bonds per water molecule (〈HB〉) between confined water molecules and between water and GO-surfaces, radial distribution function (RDF), self-diffusion coefficient, and angle distribution function of the confined water molecules between the GO plates. Our results showed good agreements between the OPLS-AA and Dreiding models and some calculated potentials. However, some calculated models showed completely different behavior which discussed in details. According to the results, we concluded that the OH-2 and O1-OH2 models show totally better agreement with the famous force fields than the other calculated potentials. This work provides a simple method for the development of new force fields specifically for these types of systems which are in good agreement with the well-known force fields.

Maintaining the concentration equilibrium of proton and hydroxide ions by construction of bis(2-aminoethyl)amine-based inner helmholtz plane toward long-life zinc metal anodes

Despite the merits of high safety and low cost, the development of rechargeable aqueous Zn metal batteries is oppressed by the short cycling life of Zn metal anodes, due to the hydrogen evolution reaction (HER) and the formation of irreversible Zn4SO4(OH)6·nH2O that are caused by the decomposition of H2O molecules adsorbed in the inner Helmholtz plane (IHP) of Zn metal anodes. To solve this issue, we herein use bis(2-aminoethyl)amine (B2AA) organic molecules as additives to suppress Zn corrosion and HER via reconstructing the IHP and maintaining the concentration equilibrium of protons and hydroxide ions, thus achieving long-term and highly reversible Zn metal batteries. Density functional theory calculations and molecule dynamics simulations reveal that B2AA are preferentially adsorbed on the interface of Zn anode owing to the high adsorption energy, forming a water-deficient IHP via repelling ≈19% of H2O molecules. Additionally, the −NH2/−NH− groups of B2AA can reversibly capture H+ derived from the decomposition of H2O and dynamically neutralize OH−, thus suppressing the corrosion reaction. Using an aqueous electrolyte involving B2AA, symmetric Zn//Zn cells exhibit a long cycling life of 2400 h at 10 mA cm−2. Matched with a NH4V4O10 (NVO) cathode, the Zn//NVO full cell delivers a high initial capacity of 147.24 mAh/g at 10 A/g, and maintains a high capacity retention of 66% after 3000 cycles.