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Battery safety is the number one priority for consumers and manufacturers, particularly for large-scale applications like electric vehicles and distributed energy storage systems, where the consequences of thermal runaway events can be devastating. Here we propose a novel approach to prevent battery thermal runaway by using La and Nb co-doped BaTiO3. The material is incorporated into a battery system as a thin film, having no effects on the room temperature operation, but rapidly switching off the battery current at high temperatures due to the positive temperature coefficient of resistivity (PTCR) exhibited by doped BaTiO3. La and Nb as co-dopants of BaTiO3 are found to be critical to ensure good room temperature conductivity combined with a significant PTCR effect. This work demonstrates the use of a purely inorganic PTCR material for thermal runaway protection for the first time. The high mechanical and chemical stability of the BaTiO3-based material proposed here makes it an advantageous competitor to current polymer-based protective switches.

Two-dimensional (2D) materials and Transition Metal Dichalcogenides (TMD) in particular are at the forefront of nanotechnology. To tailor properties for engineering applications, alloying strategies used for bulk metals in the last century need to be extended to this novel class of materials. Here we present a systematic analysis of the phase behaviour of substitutional 2D alloys in the TMD family on both the metal and chalcogenide site. The phase behaviour is quantified in terms of a metastability metric and benchmarked against systematic computational screening of configurational energy landscapes. The resulting Pettifor maps can be used to identify broad trends across chemical spaces and as starting point for setting up rational search strategies in phase space, thus allowing for targeted computational analysis of properties on likely thermodynamically stable compounds. The results presented here also constitute a useful guideline for synthesis of binary metal 2D TMDs alloys via a range of synthesis techniques., arXiv admin note: substantial text overlap with arXiv:2207.02741

The process of Li intercalation is fundamental to the operation of Li-ion batteries and the computational modelling of this process, as atomic resolution would be of great benefit to the rational design of improved battery materials. Towards this goal, we present an approach and workflow for the simulation of Li intercalation which uses electrostatic considerations. These considerations use the electrostatic potential found from Density Functional Theory (DFT) calculations as a guiding principle to find favourable sites for Li intercalation. We test the method on graphite-based models of anodic carbon, graphite nanoparticles. The study of nanoparticles using first-principles methods is made possible thanks to linear-scaling DFT which allows calculations on larger numbers of atoms than conventional DFT. We show how our approach can reproduce the well-known Li staging and we investigate the electronic structure of the nanoparticle obtained via atomic charges and density of states analysis. We also compute the open circuit voltages of the structures via a convex hull formalism and find reasonable agreement with experiment with respect to the degree of Li intercalation. Our approach provides a novel route to simulating the intercalation process and, combined with linear-scaling DFT, can be used to investigate intercalation in complex nanoscale electrode structures.

Funding Information: We are grateful to B. J. Irving for carefully reading the manuscript. G.Z. thanks the National Science Foundation of China (NSFC, grant nos 11834017 and 61888102) and the Strategic Priority Research Program of CAS (grant no. XDB30000000) for their support. M.L. thanks the ESI Fund and the OPR DE International Mobility of Researchers MSCA-IF III at CTU in Prague (no. CZ.02.2.69/0.0/0.0/20_079/0017983) for their support. L.D. gratefully acknowledges the financial support from the Academy of Finland (grant no. 3333099). D.S. thanks the support from NSFC (grant no. 61734001). K.W. and T.T. acknowledge support from the Elemental Strategy Initiative conducted by the MEXT, Japan, A3 Foresight by JSPS and the CREST (JPMJCR15F3), JST. M.L., P.N. and T.P. acknowledge support from the project Novel Nanostructures for Engineering Applications CZ.02.1.01/0.0/0.0/16_026/0008396. This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic through the e-INFRA CZ (ID:90140). T.P., V.E.P.C. and A.S. acknowledge support from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 721642: SOLUTION. The data and materials are available from the corresponding authors upon request. The authors acknowledge the use of the IRIDIS High Performance Computing Facility, and associated support services at the University of Southampton, in the completion of this work. Publisher Copyright: © 2021, The Author(s), under exclusive licence to Springer Nature Limited. MoS2/graphite and MoS2/h-BN interfaces are shown to have ultra-low friction coefficients, whereas edges and interface steps mainly contribute to the friction force. Two-dimensional heterostructures are excellent platforms to realize twist-angle-independent ultra-low friction due to their weak interlayer van der Waals interactions and natural lattice mismatch. However, for finite-size interfaces, the effect of domain edges on the friction process remains unclear. Here we report the superlubricity phenomenon and the edge-pinning effect at MoS2/graphite and MoS2/hexagonal boron nitride van der Waals heterostructure interfaces. We found that the friction coefficients of these heterostructures are below 10(-6). Molecular dynamics simulations corroborate the experiments, which highlights the contribution of edges and interface steps to friction forces. Our experiments and simulations provide more information on the sliding mechanism of finite low-dimensional structures, which is vital to understand the friction process of laminar solid lubricants.

In the search for alternatives to lithium batteries, aluminium makes a promising negative electrode due to its high theoretical specific energy and energy density. One battery chemistry making use of an aluminium negative electrode is the aluminium–poly(3,4-ethylenedioxythiophene) (PEDOT) battery, which has been shown to have long cycle life and specific energy comparable to other aluminium rechargeable batteries. The battery stores AlCl4− anions in the PEDOT cathode when charged. However, the storage mechanism is not well understood. Here, ab initio molecular dynamics simulations (AIMD) are used to help understand the optimum (relaxed) configuration of AlCl4− anions when stored on a single chain of PEDOT. Two main conclusions arise. Firstly, it is generally not stable to have two anions adsorbed to one monomer unit, and this configuration can be avoided for future work. Secondly, AIMD does not find lower energy configurations for the PEDOT/AlCl4− system than DFT geometry relaxation, providing that the starting geometry does not have two anions on the same monomer unit. Based on our results, we believe it is likely that similar behaviour will be observed in other conducting polymer systems.

Application of Li-ion batteries in electric vehicles requires improved safety, increased lifetime and high charging rates. One of the most commonly used intercalation anode material for Li-ion batteries, graphite, is vulnerable to Li nucleation, a side reaction which competes with the intercalation process and leads to loss of reversible capacity of the battery, ageing and short-circuits. In this study, we deploy a combined grand canonical large-scale electronic density-functional theory (DFT) and Poisson-Boltzmann electrolyte theory to study the nucleation and growth of Li clusters on the graphite anode in the presence of its surrounding electrolyte environment at different applied voltages with respect to the Li metal reference electrode. We find the voltage below which the nucleation energy becomes negative (corresponding to Li nucleation becoming energetically favourable), the ‘potential of zero nucleation energy’ (UPZN). We observe a distinct minimum in the plots of UPZN as a function of the size of nucleated clusters. When the applied voltage on the graphite electrode is below the minimum value of UPZN, the nucleated clusters start growing unbounded on graphite electrode. This potential for cluster growth (UPCG) is found to be −0.12 V on the periodic basal plane of unlithiated graphite and −0.08 V on lithiated graphite. The corresponding potential for the zigzag edge termination is −0.06 V on unlithiated graphite and −0.04 V on lithiated graphite. Thus, the nucleation and cluster growth is favored on the zigzag edge termination of the graphite electrode as compared to the periodic basal plane and on the lithiated graphite as compared to the unlithiated graphite. We find that the surrounding environment plays a significant role and that nucleation is more likely to occur in electrolyte environment than that predicted from calculations in vacuum. We observe that the potentials obtained with grand canonical ensemble DFT method in electrolyte are close to experimentally available data. The study has profound implications for the nucleation, growth and control of metal dendrites in a battery cell.

The strain-dependent oxidation of metals for reactive material warheads is studied with quantum mechanical simulations. A two-stage surface oxidation process was investigated for Titanium, Copper, and Zirconium in unstrained condition and for isotropic compression and tension. The results show exothermic surface oxidation and an increased strain-sensitivity for the pyrophoric materials Titanium and Zirconium in comparison to non-pyrophoric Copper. While tension stabilizes the surface oxidation, compression leads to a destabilization of oxidized surfaces. The release of metal oxides from the oxidized surface is endothermic for all materials in unstrained condition. It was found that the release of metal oxides is stabilized by compression and can even be turned exothermic by sufficient lattice strain.

Experimental and numerical investigations of the penetration of APFSDS projectiles in semi-infinite targets of Mars® 380 and AA 7020 T651 are presented in this work. Two different tungsten heavy alloy penetrator materials with different strengths have been used. In armor steel the material of the penetrator was found to have only a minor influence on the depth of penetration. In the AA 7020 T651 targets the influence of the penetrators strength was found to be important, especially as at lower velocities the penetration process does not lead to an erosion of the projectile. With the numerical simulation the deforming penetration process could be reproduced, but more effort is necessary to evaluate a reliable strength model parameter set.

Lithium metal plating is a critical safety issue in Li-ion cells with graphite anodes, and contributes significantly to ageing, drastically limiting the lifetime and inducing capacity loss. Nonetheless, the nucleation mechanism of metallic Li on graphite anodes is still poorly understood. But in-depth understanding is needed to rationally design mitigation measures. In this work, we conducted First-Principles studies to elucidate the Li nucleation mechanism on graphite surfaces. These large-scale density-functional-theory (DFT) calculations indicate that nano-particulate Li forms much more readily than classical nucleation theory predicts. Further, our calculations indicate a crucial role of topological surface states near the zigzag edge, lowering the nucleation barrier by a further 1.32 eV relative to nucleation on the basal plane. Li nucleation, therefore, is likely to initiate at or near the zigzag edges of graphitic particles. Finally, we suggest that chemical doping with a view to reducing the effect of the topological surface states might be a potential mitigation strategy to increase nucleation barriers and reduce the propensity to plate Li near the zigzag edge.

We present a multi-scale computational framework suitable for designing solid lubricant interfaces fully in silico. The approach is based on stochastic thermodynamics founded on the classical thermally activated two-dimensional Prandtl-Tomlinson model, linked with First Principles methods to accurately capture the properties of real materials. It allows investigating the energy dissipation due to friction in materials as it arises directly from their electronic structure, and naturally accessing the time-scale range of a typical friction force microscopy. This opens new possibilities for designing a broad class of material surfaces with atomically tailored properties. We apply the multi-scale framework to a class of two-dimensional layered materials and reveal a delicate interplay between the topology of the energy landscape and dissipation that known static approaches based solely on the energy barriers fail to capture.

This work uses an open-source, data-driven, image-based modelling framework; OpenImpala. Lithium Iron Phosphate (LFP) electrode samples were imaged using micro-CT. Two scans were performed using the Zeiss 160 kVp Versa 510 at the University of Southampton. The two scans were both carried out on the same sample and using the same focal point, this is so they could be used as a direct comparison to see how porosity and tortuosity changed with spatial resolution. It is found that the Bruggeman correlation significantly underestimates the tortuosity compared to the OpenImpala calculated results. It is also found that there is a larger statistical variability in the 801 nm results, whereas the 400 nm results have a much smaller standard deviation. These results were compared to computer-generated images based on FIB/SEM tomographic data of a single Nickel Manganese Cobalt Oxide (NMC) porous active particle and found to have the same trends.

We present the implementation of a hybrid continuum-atomistic model for including the effects of a surrounding electrolyte in large-scale density functional theory (DFT) calculations within the Order-N Electronic Total Energy Package (ONETEP) linear-scaling DFT code, which allows the simulation of large complex systems such as electrochemical interfaces. The model represents the electrolyte ions as a scalar field and the solvent as a polarizable dielectric continuum, both surrounding the quantum solute. The overall energy expression is a grand canonical functional incorporating the electron kinetic and exchange-correlation energies, the total electrostatic energy, entropy, and chemical potentials of the surrounding electrolyte, osmotic pressure, and the effects of cavitation, dispersion, and repulsion. The DFT calculation is performed fully self-consistently in the electrolyte model, allowing the quantum-mechanical system and the surrounding continuum environment to interact and mutually polarize. A bespoke highly parallel multigrid Poisson-Boltzmann solver library, DL-MG, deals with the electrostatic problem, solving a generalized Poisson-Boltzmann equation. Our model supports open boundary conditions, which allows the treatment of molecules, entire biomolecules, or larger nanoparticle assemblies in the electrolyte. We have also implemented the model for periodic boundary conditions, allowing the treatment of extended systems such as electrode surfaces in contact with the electrolyte. A key feature of the model is the use of solute size and solvation-shell-aware accessibility functions that prevent the unphysical accumulation of electrolyte charge near the quantum solute boundary. The model has a small number of parameters - here we demonstrate their calibration against experimental mean activity coefficients. We also present an exemplar simulation of an 1634-atom model of the interface between a graphite anode and LiPF 6 electrolyte in an ethylene carbonate solvent. We compare the cases where Li atoms are intercalated at opposite edges of the graphite slab and in solution, demonstrating a potential application of the model in simulations of fundamental processes in Li-ion batteries.

The interface between the electrolyte and graphite anodes plays an important role for lithium (Li) intercalation and has significant impact on the charging/discharging performance of Lithium-Ion Batteries (LIBs). However, atomistic understanding of interface effects that would allow the interface to be rationally optimized for application needs is largely missing. Here we comprehensively study the energetics of Li intercalation near the main non-basal surfaces of graphite, namely the armchair and zigzag edges. We find that edge sites at both surfaces bind Li more strongly than in the bulk of graphite. Therefore, lithiation of these sites is expected to proceed at higher voltages than in the bulk. Furthermore, this effect is significantly more pronounced at the zigzag edge compared to the armchair edge due to its unique electronic structure. The “peculiar” topologically stabilized electronic surface state found at zigzag edges strongly interacts with Li, thereby changing Li diffusion behavior at the surface as well. Finally, we investigate boron (B)/nitrogen (N) doping as a promising strategy to tune the Li intercalation behavior at both edge systems, which could lead to enhanced intercalation kinetics in B/N doped graphite anodes.

Computational modelling is a vital tool in the research of batteries and their component materials. Atomistic models are key to building truly physics-based models of batteries and form the foundation of the multiscale modelling chain, leading to more robust and predictive models. These models can be applied to fundamental research questions with high predictive accuracy. For example, they can be used to predict new behaviour not currently accessible by experiment, for reasons of cost, safety, or throughput. Atomistic models are useful for quantifying and evaluating trends in experimental data, explaining structure-property relationships, and informing materials design strategies and libraries. In this review, we showcase the most prominent atomistic modelling methods and their application to electrode materials, liquid and solid electrolyte materials, and their interfaces, highlighting the diverse range of battery properties that can be investigated. Furthermore, we link atomistic modelling to experimental data and higher scale models such as continuum and control models. We also provide a critical discussion on the outlook of these materials and the main challenges for future battery research.

Progress in electrochemical technologies, such as automotive batteries, supercapacitors, and fuel cells, depends greatly on developing improved charged interfaces between electrodes and electrolytes. The rational development of such interfaces can benefit from the atomistic understanding of the materials involved by first-principles quantum mechanical simulations with Density Functional Theory (DFT). However, such simulations are typically performed on the electrode surface in the absence of its electrolyte environment and at constant charge. We have developed a new hybrid computational method combining DFT and the Poisson-Boltzmann equation (P-BE) capable of simulating experimental electrochemistry under potential control in the presence of a solvent and an electrolyte. The charged electrode is represented quantum-mechanically via linear-scaling DFT, which can model nanoscale systems with thousands of atoms and is neutralized by a counter electrolyte charge via the solution of a modified P-BE. Our approach works with the total free energy of the combined multiscale system in a grand canonical ensemble of electrons subject to a constant electrochemical potential. It is calibrated with respect to the reduction potential of common reference electrodes, such as the standard hydrogen electrode and the Li metal electrode, which is used as a reference electrode in Li-ion batteries. Our new method can be used to predict electrochemical properties under constant potential, and we demonstrate this in exemplar simulations of the differential capacitance of few-layer graphene electrodes and the charging of a graphene electrode coupled to a Li metal electrode at different voltages.

Image-based modelling has emerged as a popular method within the field of lithium-ion battery modelling due to its ability to represent the heterogeneity of the porous electrodes. A common challenge from image-based modelling is the size of 3D tomography datasets, which can be of the order of several billion voxels. Previously, different approximation methods have been used to simplify the computational problem, but each of these come with associated limitations. Here we develop a data-driven, fully parallelisable, image-based modelling framework called OpenImpala. Micro X-ray computed tomography (CT) is used to obtain 3D microstructural data from samples non-destructively. These 3D datasets are then directly used as the computational domain for finite-differences based direct physical modelling (e.g. to solve the diffusion equation directly on the CT obtained datasets). OpenImpala then calculates the equivalent homogenised transport coefficients for the given microstructure. These coefficients are written into parameterised files for direct compatibility with two popular continuum battery models: PyBamm and DandeLiion, facilitating the link between different scales of computational battery modelling. OpenImpala has been shown to scale well with an increasing number of computational cores on distributed memory architectures, making it applicable to large datasets typical of modern tomography.

The prevention of thermal runaway (TR) in lithium‐ion batteries is vital as the technology is pushed to its limit of power and energy delivery in applications such as electric vehicles. TR and the resulting fire and explosion have been responsible for several high‐profile accidents and product recalls over the past decade. Herein, the causes of TR are described and novel preventative methods are examined, approaching the problem from different angles by altering the internal structure of the battery to undergo thermal shutdown or developing the battery and thermal management systems so that they can detect and prevent TR. Ultimately, a variety of different technologies is needed to address the emerging market of highly specialized lithium‐ion batteries. Key innovations discussed include positive temperature coefficient (PTC) materials, self‐healing polymer electrolytes, and hybrid liquid–solid‐state electrolytes. Mist cooling achieves a highly uniform temperature inside the battery pack without the need for pumps to circulate a coolant. The development of battery management systems (BMSs) which model the internal temperature of the cell from real‐time data and prevent the cell reaching a critical temperature is an essential area for further research.

A facile scalable strategy is reported for the synthesis of a hybrid of lithium titanate (Li4Ti5O12 or LTO) and 1-pyrenecarboxylic acid decorated multiwalled carbon nanotubes (PCA@CNTs). LTO platelets comprising of quasi-spherical nanoparticles afford short diffusion paths for electrolyte ions. PCA@CNTs, enhance the electrical conductivity of the nearly insulating LTO by 3 orders of magnitude, thus maximizing the ion-uptake capability of the hybrid. Symmetric and asymmetric supercapacitors with the LTO/PCA@CNTs hybrid supported over Ni foam substrates are assembled with a novel Li+ conducting alginate gel, in air without any inert conditions that are typically used for all LTO based devices. The gel shows an average ionic conductivity of ∼8.4 mS cm−1 at room temperature, and is found to be electrochemically stable over a wide operational voltage window of ∼2.5 V. Benefitting from the synergy of electrical double layer (EDL) storage afforded by PCA@CNTs, ion-storage by LTO through a redox reaction and EDL, and the ease ion-movement across the cell due to the open architecture of CNTs, the asymmetric LTO/PCA@CNTs hybrid cell outperforms the symmetric cells by a large margin. The best areal specific capacitance (SC), volumetric SC and energy density are ∼54 mF cm−2, ∼4.3 F cm−3 (at 0.5 mA cm−2) and ∼3.7 mWh cm−3 (at a power density of 49.6 mW cm−3) significantly enhanced for the asymmetric LTO/PCA@CNTs hybrid cell, compared to the symmetric- PCA@CNTs and hybrid cells. The design is simple to implement and can serve as a prototype to develop a range of yet unexplored LTO/carbon nanomaterial based supercapacitors.

While 2D materials attract considerable interests for their exotic electronic and mechanical properties, their phase behaviour is still largely not understood. This work focuses on (Mo:Ti) S2 binary alloys which have captured the interest of the tribology community for their good performance in solid lubrication applications and whose chemistry and crystallography is still debated. Using electronic structures calculations and statistical mechanics we predict a phase-separating behaviour for the system and trace its origin to the energetics of the d-band manifold due to crystal field splitting. Our predicted solubility limits as a function of temperature are in accordance with experimental data and demonstrate the utility of this protocol in understanding and designing TMD alloys.

Cell voltage is a fundamental quantity used to monitor and control Li-ion batteries. The open circuit voltage (OCV) is of particular interest as it is believed to be a thermodynamic quantity, free of kinetic effects and history and, therefore, "simple" to interpret. Here we show that the OCV characteristics of graphite show hysteresis between charge and discharge that does not solely originate from Li dynamics and that the OCV is in fact history dependent. Combining First Principles calculations with temperature-controlled electrochemical measurements, we identify a residual hysteresis that persists even at elevated temperatures of greater than 50°C due to differences in the phase succession between charge and discharge. Experimental entropy profiling, as well as energies and volume changes determined from First Principles calculations, suggest that the residual hysteresis is associated with different host lattice stackings of carbon and is related to Li disorder across planes in stage II configurations.

Two-dimensional heterostructures are excellent platforms to realize twist-angle-independent ultra-low friction due to their weak interlayer van der Waals interactions and natural lattice mismatch. However, for finite-size interfaces, the effect of domain edges on the friction process remains unclear. Here we report the superlubricity phenomenon and the edge-pinning effect at MoS

The effect of doping Cr on the electrocatalytic activity of Co

Density functional theory (DFT) is often used for simulating extended materials such as infinite crystals or surfaces, under periodic boundary conditions (PBCs). In such calculations, when the simulation cell has non-zero charge, electrical neutrality has to be imposed, and this is often done via a uniform background charge of opposite sign ("jellium"). This artificial neutralization does not occur in reality, where a different mechanism is followed as in the example of a charged electrode in electrolyte solution, where the surrounding electrolyte screens the local charge at the interface. The neutralizing effect of the surrounding electrolyte can be incorporated within a hybrid quantum-continuum model based on a modified Poisson-Boltzmann equation, where the concentrations of electrolyte ions are modified to achieve electroneutrality. Among the infinite possible ways of modifying the electrolyte charge, we propose here a physically optimal solution, which minimizes the deviation of concentrations of electrolyte ions from those in open boundary conditions (OBCs). This principle of correspondence of PBCs with OBCs leads to the correct concentration profiles of electrolyte ions, and electroneutrality within the simulation cell and in the bulk electrolyte is maintained simultaneously, as observed in experiments. This approach, which we call the Neutralization by Electrolyte Concentration Shift (NECS), is implemented in our electrolyte model in the Order-N Electronic Total Energy Package (ONETEP) linear-scaling DFT code, which makes use of a bespoke highly parallel Poisson-Boltzmann solver, DL_MG. We further propose another neutralization scheme ("accessible jellium"), which is a simplification of NECS. We demonstrate and compare the different neutralization schemes on several examples.

A simple, modified Metal–Organic Chemical Deposition (MOCD) method for Pt, PtRu and PtCo nanoparticle deposition onto a variety of support materials, including C, SiC, B4C, LaB6, TiB2, TiN and a ceramic/carbon nanofiber, is described. Pt deposition using Pt(acac)2 as a precursor is shown to occur via a mixed solid/liquid/vapour precursor phase which results in a high Pt yield of 90–92% on the support material. Pt and Pt alloy nanoparticles range 1.5–6.2 nm, and are well dispersed on all support materials, in a one-step method, with a total catalyst preparation time of ∼10 hours (2.4–4× quicker than conventional methods). The MOCD preparation method includes moderate temperatures of 350 °C in a tubular furnace with an inert gas supply at 2 bar, a high pressure (2–4 bar) compared to typical MOCVD methods (∼0.02–10 mbar). Pt/C catalysts with Pt loadings of 20, 40 and 60 wt% were synthesised, physically characterised, electrochemically characterised and compared to commercial Pt/C catalysts. TEM, XRD and ex situ EXAFS show similar Pt particle sizes and Pt particle shape identifiers, namely the ratio of the third to first Pt coordination numbers modelled from ex situ EXAFS, between the MOCD prepared catalysts and commercial catalysts. Moreover, electrochemical characterisation of the Pt/C MOCD catalysts obtained ORR mass activities with a maximum of 428 A gPt−1 at 0.9 V, which has similar mass activities to the commercial catalysts (80–160% compared to the commercial Pt/C catalysts).

We present the implementation of a hybrid continuum-atomistic model for including the effects of surrounding electrolyte in large-scale density functional theory (DFT) calculations within the ONETEP linear-scaling DFT code, which allows the simulation of large complex systems such as electrochemical interfaces. The model represents the electrolyte ions as a scalar field and the solvent as a polarisable dielectric continuum, both surrounding the quantum solute. The overall energy expression is a grand canonical functional incorporating the electron kinetic and exchange correlation energies, the total electrostatic energy, entropy and chemical potentials of surrounding electrolyte, osmotic pressure, and the effects of cavitation, dispersion and repulsion. The DFT calculation is performed fully self-consistently in the electrolyte model, allowing the quantum mechanical system and the surrounding continuum environment to interact and mutually polarize. A bespoke parallel Poisson-Boltzmann solver library, DL_MG, deals with the electrostatic problem, solving a generalized Poisson-Boltzmann equation. Our model supports open boundary conditions, which allows the treatment of molecules, entire biomolecules or larger nanoparticle assemblies in electrolyte. We have also implemented the model for periodic boundary conditions, allowing the treatment of extended systems such as electrode surfaces in contact with electrolyte. A key feature of the model is the use of solute-size and solvation-shell-aware accessibility functions that prevent the unphysical accumulation of electrolyte charge near the quantum solute boundary. The model has a small number of parameters: here we demonstrate their calibration against experimental mean activity coefficients. We also present an exemplar simulation of a 1634-atom model of the interface between a graphite anode and LiPF6 electrolyte in ethylene carbonate solvent. We compare the cases where Li atoms are intercalated at opposite edges of the graphite slab and in solution, demonstrating a potential application of the model in simulations of fundamental processes in Li-ion batteries.

Recent research showed that the rotational degree of freedom in stacking 2D materials yields great changes in the electronic properties. Here, we focus on an often overlooked question: are twisted geometries stable and what defines their rotational energy landscape? Our simulations show how epitaxy theory breaks down in these systems, and we explain the observed behavior in terms of an interplay between flexural phonons and the interlayer coupling, governed by the moiré superlattice. Our argument, applied to the well-studied MoS2/graphene system, rationalizes experimental results and could serve as guidance to design twistronic devices.

The electrokinetic properties of Pt nanoparticles supported on Carbon (Pt/C) and Boron Carbide-Graphite composite (Pt/BC) are compared over a wide potential range. The influence of the support on the electronic state of Pt was investigated via in-situ X-ray Absorption Spectroscopy. Pt d-band filling, determined from XANES white line analysis, was lower and nearly constant between 0.4 and 0.95 V vs. RHE for Pt/BC, indicating more positively charged particles in the double layer region and a delay in the onset of oxide formation by about 0.2 V compared to the Pt/C catalyst, which showed a marked increase in d-band vacancies above 0.8 V vs. RHE. Moreover, Δμ analysis of the XANES data indicated a lack of sub-surface oxygen for the Pt/BC catalyst compared to the Pt/C catalyst above 0.9 V vs. RHE. Additional anion adsorption on the Pt/BC in the double layer region, detected by CO displacement, was also confirmed by XANES analysis of the d-band occupancy. The H2 oxidation activities of electrodes with low catalyst loadings were assessed under high mass transport conditions using the floating electrode methodology. The metal-support interaction between the Pt and BC support improved the maximum hydrogen oxidation current density by 1.4 times when compared to Pt/C.

In-situ diagnostic tools have become established to as a means to understanding the aging processes that occur during charge/discharge cycles in Li-ion batteries (LIBs). One electrochemical thermodynamic technique that can be applied to this problem is known as entropy profiling. Entropy profiles are obtained by monitoring the variation in the open circuit potential as a function of temperature. The peaks in these profiles are related to phase transitions, such as order/disorder transitions, in the lattice. In battery aging studies of cathode materials, the peaks become suppressed but the mechanism by which this occurs is currently poorly understood. One suggested mechanism is the formation of point defects. Intentional modifications of LIB electrodes may also lead to the introduction of point defects. To gain quantitative understanding of the entropy profile changes that could be caused by point defects, we have performed Monte Carlo simulations on lattices of variable defect content. As a model cathode, we have chosen manganese spinel, which has a well-described order-disorder transition when it is half filled with Li. We assume, in the case of trivalent defect substitution (M = Cr,Co) that each defect M permanently pins one Li atom. This assumption is supported by Density Functional Theory (DFT) calculations. Assuming that the distribution of the pinned Li sites is completely random, we observe the same trend in the change in partial molar entropy with defect content as observed in experiment: the peak amplitudes become increasing suppressed as the defect fraction is increased. We also examine changes in the configurational entropy itself, rather than the entropy change, as a function of the defect fraction and analyse these results with respect to the ones expected for an ideal solid solution. We discuss the implications of the quantitative differences between some of the results obtained from the model and the experimentally observed ones.

Today, the Internet of Things (IoT) comprises vertically oriented platforms for things. Developers who want to use them need to negotiate access individually and adapt to the platform-specific API and information models. Having to perform these actions for each platform often outweighs the possible gains from adapting applications to multiple platforms. This fragmentation of the IoT and the missing interoperability result in high entry barriers for developers and prevent the emergence of broadly accepted IoT ecosystems. The BIG IoT (Bridging the Interoperability Gap of the IoT) project aims to ignite an IoT ecosystem as part of the European Platforms Initiative. As part of the project, researchers have devised an IoT ecosystem architecture. It employs five interoperability patterns that enable cross-platform interoperability and can help establish successful IoT ecosystems.