W ith rising concerns about global warming, electrification of transport has recently emerged as an important vision in many countries. The successful development of electric vehicles (EVs) depends highly on the cycling performance, cost and safety of the batteries. Rechargeable lithium-ion (Li-ion) batteries are currently the best choice for EVs due to their reasonable energy density and cycle life 1 . Further research and development on Li-ion batteries will lead to even higher energy density and more complicated battery dynamics, where the efficiency and safety of such batteries will become a concern. An advanced battery management system (BMS) that can monitor and optimize battery behaviour and safety is thus essential for the entire electrification system 2 .Today, one of the major barriers to widespread adoption of EVs is range anxiety. The ability of a BMS to accurately determine the state of charge (SOC) and state of health (SOH) of batteries, and hence the estimated driving range, will alleviate this problem. In addition, reliable prediction of remaining useful life (RUL) will allow batteries to be used to their fullest potential and maximum life expectancy before replacement or disposal. Knowledge of the RUL of spent batteries will also enable their redeployment in less demanding, second-life applications such as stationary grid storage. If we are able to sort manufactured cells based on their expected lifetime using early-cycle data, we can further accelerate the testing, validation and development process of new batteries. In summary, accurate prediction of the current and future state of batteries will open up vast opportunities in battery manufacturing, usage and optimization 3,4 . SOC and SOH are the two most important parameters in battery management and are generally defined as:where C curr is the capacity of the battery in its current state, C full is the capacity of the battery in its fully charged state, C nom is the nominal capacity of the brand-new battery 2 . In essence, SOC denotes the capacity of the battery in its current state compared to the capacity in its fully charged state (equivalent of a fuel gauge), while SOH describes the capacity of the battery in its fully charged state compared to the nominal capacity when brand new. By convention, SOC is 100% when the battery is fully charged and 0% when it is empty, while SOH is 100% at the time of manufacture and reaches 80% at end of life (EOL). In the battery manufacturing industry, EOL is often defined as the point at which the actual capacity at full charge drops to 80% of its nominal value 2 . The remaining number of charge/discharge cycles until the battery reaches EOL is the RUL of the battery. Current BMSs can determine the SOC of Li-ion batteries within 0.6% to 6.5% 5 , but are unable to predict the SOH and RUL of batteries accurately 6 .The traditional methods for SOC estimation include ampere hour counting estimation, open-circuit voltage-based estimation, impedance-based estimation, model-based estimation, fuzzy logic, and Kal...

Low-salinity water flooding of formation water in rock cores is, potentially, a promising technique for enhanced oil recovery (EOR), but details of the underlying mechanism remain unclear. The salinity effect on the interface between water and oil was investigated here using the Molecular Dynamics (MD) simulation method. n-Decane was selected as a representative oil component, SPC/E water and OPLS-AA force fields were used to describe the water/oil/ionic interactions for salt water and n-decane molecules. Equilibrium MD simulations were firstly conducted to study the n-decane/vapour and salt-water/vapour interface systems at six different NaCl concentrations (0 M, 0.05 M, 0.10 M, 0.20 M, 0.50 M and 1.00 M). The water/oil interface was then investigated by calculating bulk density distribution, radial distribution function, interface thickness and water/oil interfacial tension (IFT). Sufficiently long MD simulations of water/n-decane/vapour were performed, followed by an analysis of the effect of salinity on the water/oil/vapour interface. The IFT values for the water/vacuum interface, ndecane/vacuum interface and water/n-decane interface were obtained from the pressure tensor distribution after system equilibration, with values of 71.4, 20.5 and 65.3 mN/m, respectively, which agree well with experimental and numerical results reported in the literature. An optimal salinity of ~0.20 M was identified corresponding to a maximum interfacial thickness between water and oil phase, which results in a minimum water/oil IFT value and a maximum value for the oil/water contact angle, a condition beneficial for enhanced oil recovery.

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Physical properties of polyelectrolytes have been shown to be significantly related to their chain conformations. Atomistic simulation has been used as an effective method for studying polymer chain structures, but few has focused on the effects of chain length and tacticity in the presence of monovalent salts. This paper investigated the microscopic conformation behaviours of polyacrylic acid (PAA) with different chain sizes, tacticity and sodium chloride concentrations. The hydrogen behaviours and corresponding radial distribution functions were obtained. The results showed that the increase of salt concentrations led to the collapse of PAA chains, especially for longer chains. It was found that the effects of salt were mainly attributed to the shielding screening effect by sodium ions rather than the hydrogen bonding effect. Two different structure were form by iso-PAA and syn-PAA, respectively, which due to the deprotonation patterns along the PAA chain.

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This is a repository copy of Molecular dynamics investigation of substrate wettability alteration and oil transport in a calcite nanopore.

Elastic turbulence has shown great potential to improve mixing and heat transfer performance. Most of the studies, however, are focused on the mixing behaviour, heat transfer characteristics induced by elastic turbulence are still not well established. This work investigates systematically the flow and heat transfer performance by elastic turbulence in a swirling flow region. The heat transfer enhancements in the bulk fluid and between the fluid and the wall are characterised by the effective thermal conductivity and the Nusselt number, respectively. The variations of statistical properties, such as probability distribution functions and spectra profiles are analysed for the characterization of elastic turbulence. The results indicate that viscoelastic fluid intensifies the heat transfer performance with gradually increasing swirling velocity, and a six-times enhancement comparing to the Newtonian fluid at the maximum given swirling velocity is obtained. Particularly, the statistical properties imply that the flow is still in the transition regime to elastic turbulence at Wi = 5.5.

In this study, classic Molecular Dynamics (MD) simulations with established force fields were first performed to investigate the salinity effects on the static contact angle of a n-decane droplet immersing in the water atmosphere within a calcite nanochannel to advance our microscopic understanding on low salinity flooding. By applying an external body force, dynamic contact angle of n-decane in the water phase was also studied in the presence of various salt concentrations based on Non-Equilibrium MD (NEMD) simulation. The predicted n-decane static contact angles are around 59.68º ± 0.26º, which agree well with experimental results in previous studies. A reduction of the static contact angle of the nanodrop is observed with the increase of salinity, which implies an enhancement of surface hydrophilicity. Under flow conditions, the deformation of nanodrop, as evidenced by the centre of mass analysis, becomes faster by increasing the salt concentration. The recovery/mobility of the n-decane 2 nanodrop is, however, still significantly restricted by the adsorption interaction between the substrate and n-decane phase, which may lead to droplet snapping off and/or breaking up into small droplets.