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Robust correlation curves are essential to decipher structural information from IR-vibrational spectra. However, for surface-adsorbed water and hydroxides, few such correlations have been presented in the literature. In this paper, OH vibrational frequencies are correlated against 12 structural descriptors representing the quantum mechanical or geometrical environment, focusing on those external to the vibrating molecule. A nonbiased fitting procedure based on Gaussian process regression (GPR) was used alongside simple analytical functional forms. The training data consist of 217 structurally unique OH groups from 38 water/metal oxide interface systems for MgO, CaO and CeO2, all optimized at the DFT level, and the fully anharmonic and uncoupled OH vibrational signatures were calculated. Among our results, we find the following: (i) The intermolecular R(H center dot center dot center dot O) hydrogen bond distance is particularly strong, indicating the primary cause of the frequency shift. (ii) Similarly, the electric field along the H-bond vector is also a good descriptor. (iii) Highly detailed machine learning descriptors (ACSF, SOAP) are less intuitive but were found to be more capable descriptors. (iv) Combinations of geometric and QM descriptors give the best predictions, supplying complementary information.

Finding transition metal catalysts for effective catalytic conversion of CO to CO2 has attracted much attention. MXene as a new 2D layered material of early transition metal carbides, nitrides, and carbo-nitrides is a robust support for achoring metal atoms. In this study, the electronic structure, geometries, thermodynamic stability, and catalytic activity of MXene (Mo2CS2) supported single noble metal atoms (NM = Ru, Rh, Pd, Ir, Pt and Au) have been systematically examined using first-principles calculations and ab initio molecular dynamic (AIMD) simulations. First, AIMD simulations and phonon spectra demonstrate the dynamic and thermal stabilities of Mo2CS2 monolayer. Three likely reaction pathways, LangmuirHinshelwood (LH), Eley-Rideal (ER), and Termolecular Eley-Rideal (TER) for CO oxidation on the Ru1- and Ir1 @Mo2CS2 SACs, have been studied in detail. It is found that CO oxidation mainly proceeds via the TER mechanism under mild reaction conditions. The corresponding rate-determining steps are the dissociation of the intermediate (OCO-Ru1-OCO) and formation of OCO-Ir1-OCO intermediate. The downshift d-band center of Ru1- and Ir1@Mo2CS2 help to enhance activity and improve catalytst stability. Moreover, a microkinetic study predicts a maximum CO oxidation rate of 4.01 x 10 2 s-1 and 4.15 x 10 3 s-1 (298.15 K) following the TER pathway for the Ru1- and Ir1 @Mo2CS2 catalysts, respectively. This work provides guideline for fabricating and designing highly efficient SACs with superb catalyts using MXene materials.

We study substitutional fluorine, chlorine and bromine impurities at CeO2(111), and their effects on the oxygen chemistry of the surface, using density functional theory. We find that impurity formation results in a halide ion and one Ce3+ ion for all three halogens, although the formation energy depends strongly on the identity of the halogen; however, once formed, all three halogens exhibit a similar propensity to form impurity-impurity pairs. Furthermore, while the effects of halogen impurities on oxygen vacancy formation are marginal, they are more significant for oxygen molecule adsorption, due to electron transfer from the Ce3+ ion which results in an adsorbed superoxide molecule. We also consider the displacement of a halide ion on to the surface by half of an oxygen molecule, and find that the energy required to do so depends strongly not only on the identity of the halogen, but also on whether or not a second halogen impurity, with its associated Ce3+ ion, is present; if it is, then the process is greatly facilitated. Overall, our results demonstrate the existence of a rich variety of ways in which the oxygen chemistry of CeO2(111) may be modified by the presence of halogen dopants.

The CO2 molecule is weakly bound in water. Here we analyze the influence of a dissolved CO2 molecule on the structure and OH vibrational spectra of the surrounding water. From the analysis of ab initio molecular dynamics simulations (BLYP-D3) we present static (structure, coordination, H-bonding, tetrahedrality) and dynamical (OH vibrational spectra) properties of the water molecules as a function of distance from the solute. We find a weakly oscillatory variation (“ABBA”) in the ‘solution minus bulk water’ spectrum. The origin of these features can largely be traced back to solvent–solute hard-core interactions which lead to variations in density and tetrahedrality when moving from the solute’s vicinity out to the bulk region. The high-frequency peak in the solute-affected spectra is specifically analyzed and found to originate from both water OH groups that fulfill the geometric H-bond criteria, and from those that do not (dangling ones). Effectively, neither is hydrogen-bonded.

Corrosion occurring in reinforced concrete has turned into a primary concern of the current century, concrete being the most ubiquitous and predominant material used in the construction industry. Among the many interrelated processes that trigger corrosion of metallic reinforcements, the penetration of chloride ions into the concrete matrix is the most insidious threat. Herein, we developed the first electrochemical device entirely made of paper that allows for the direct, prompt, and noninvasive evaluation of free chloride ion contamination in concrete-based constructions. Our device is based on a three-layer wax-modified filter paper, consisting of two Ag/AgCl screen-printed electrodes that are interfaced by a junction pad in a sandwich-like configuration. Filter paper allows for generating a vertical-flow potentiometric device capable of measuring the electrochemical potential between two solutions containing different concentrations of chloride ions, which are separately drop-cast on the top and bottom layers. After demonstrating the analytical performance of the device, the same principle was applied to the evaluation of the chloride contents in different concrete samples, exploiting paper as a suitable interfacing material for potentiometric measurements on the cement solid surface. Laboratory-prepared concrete samples with known chloride contents were first assessed, and then, the paper-based vertical-flow device was applied to real concrete structures at the Giacomo Manzu Museum (Ardea, Italy) for the evaluation of chloride contamination caused by the proximity to the seaside. The capability of our device to provide timely warning of the risk conditions of concrete-based artifacts was demonstrated.

Batteries and supercapacitors are electrochemical energy storage systems which involve multiple time-scales and length-scales. In terms of the electrolyte which serves as the ionic conductor, a molecular-level understanding of the corresponding transport phenomena, electrochemical (thermal) stability and interfacial properties is crucial for optimizing the device performance and achieving safety requirements. To this end, atomistic machine learning is a promising technology for bridging microscopic models and macroscopic phenomena. Here, we provide a timely snapshot of recent advances in this area. This includes technical considerations that are particularly relevant for modelling electrolytes as well as specific examples of both bulk electrolytes and associated interfaces. A perspective on methodological challenges and new applications is also discussed.

Water on metal oxides interfaces generate a variety of ordered motifs that depend on the structural properties of the exposed solid surfaces. Here we emphasize the importance of considering the thermodynamic state of the surrounding liquid to find the interface structures in real systems. In particular, using ab initio molecular dynamics, we have studied the thermodynamic behavior of the water induced reconstructed (WIR) anatase (0 0 1) surface under full hydration. The long standing issue of the reconstruction symmetry in this facet of the anatase, that is the TiO2 stable phase at the nanoscale, is addressed showing that the stable state for a WIR surface in vacuum and in bulk water are different, the latter depending on the thermodynamic state of the system. Thermally activated surface phase transitions between (2x4) and (2x3) symmetries are lead by the surface relaxation caused by the molecular adsorption and release phenomena at the interface. Our approach enables the validation to aqueous environment of surface-confined water structures derived in vacuum, emphasizing the role of the thermodynamics conditions for characterizing solid-liquid interfaces especially for nano sized systems.

BATTERY 2030+ targets the development of a chemistry neutral platform for accelerating the development of new sustainable high-performance batteries. Here, a description is given of how the AI-assisted toolkits and methodologies developed in BATTERY 2030+ can be transferred and applied to representative examples of future battery chemistries, materials, and concepts. This perspective highlights some of the main scientific and technological challenges facing emerging low-technology readiness level (TRL) battery chemistries and concepts, and specifically how the AI-assisted toolkit developed within BIG-MAP and other BATTERY 2030+ projects can be applied to resolve these. The methodological perspectives and challenges in areas like predictive long time- and length-scale simulations of multi-species systems, dynamic processes at battery interfaces, deep learned multi-scaling and explainable AI, as well as AI-assisted materials characterization, self-driving labs, closed-loop optimization, and AI for advanced sensing and self-healing are introduced. A description is given of tools and modules can be transferred to be applied to a select set of emerging low-TRL battery chemistries and concepts covering multivalent anodes, metal-sulfur/oxygen systems, non-crystalline, nano-structured and disordered systems, organic battery materials, and bulk vs. interface-limited batteries.

Open access to research data is increasingly important for accelerating research. Grant authorities therefore request detailed plans for how data is managed in the projects they finance. We have recently developed such a plan for the EU-H2020 BIG-MAP project – a cross-disciplinary project targeting disruptive battery-material discoveries. Essential for reaching the goal is extensive sharing of research data across scales, disciplines and stakeholders, not limited to BIG-MAP and the European BATTERY 2030+ initiative but within the entire battery community. The key challenges faced in developing the data management plan for such a large and complex project were to generate an overview of the enormous amount of data that will be produced, to build an understanding of the data flow within the project and to agree on a roadmap for making all data FAIR. This paper describes the process we followed and how we structured the plan.

Herein, we present the first paper-based device for facing one of the worldwide concerns of the Modern age: the corrosion-induced deterioration of reinforced concrete. Indeed, the monitoring of corrosion extent in reinforced concrete constructions has been acknowledged as a priority for public safety. In this work, the porosity properties of a paper-based screen-printed Ag/AgCl electrode were exploited for realising a smart analytical tool to be directly applied on the solid surface of concrete for the evaluation of corrosion. The analysis was carried out by measuring the electrochemical potential between the metallic reinforcement and the sensor, needing only 70 mu L of electrolyte solution. The sensor was firstly tested in the laboratory using reinforced concrete samples and then applied on the real outdoor artwork Music Collection Session by Arman (Milan, Italy). A summary of the main available non-destructive techniques for corrosion monitoring is reported to provide a critic overview.

It has been suggested in the literature that keto-to-enol tautomerization plays a vital role for lignin fragmentation under mild conditions. On the other hand, previous modelling has shown that the adsorbed keto form is more stable than enol on the Pd(111) catalyst. The current density functional theory study of lignin model molecules shows that, in the gas-phase, keto is more stable than enol, but on the Pd surface, we find enol conformers that are at least as stable as keto. This supports the experimental result that the favourable reaction pathway for lignin depolymerization involves keto-enol tautomerization. An energy decomposition analysis gives insights concerning the origin of the fine energy balance between the keto and enol forms, where the molecule–surface interaction (−7 eV) and the molecular strain energy (+3 eV) are the main contributors to the adsorption energy.

The rational design of ideal catalysts for the oxygen reduction reaction (ORR) is of great significance for solving the electrocatalytic potential problems in proton exchange membrane fuel cells (PEMFCs). Pt-n(n= 1-4) and Pt3Au alloy subnanoclusters supported on a defective Ti(2)CO(2)monolayer with oxygen vacancies (denoted as v-Ti2CO2) are simulated by using density functional theory to investigate their ORR performance. The geometries, energetics, and electronic properties of the different systems are analyzed. It is found that the supported Pt3Au alloy subnanocluster possesses the best ORR activity. The underlying mechanisms of the improved ORR activity originates from the moderate hybridization between the O 2p and the 5d orbitals of Au and Pt according to the density of states analysis. Our study suggests a facile route for designing low-cost MXene-based electrocatalysts by alloying transition metals with Pt catalysts, which may stimulate realization of suitable alternative catalysts for ORR catalysis.

Alkaline electrolyte solutions are important components in rechargeable batteries and alkaline fuel cells. As the ionic conductivity is thought to be a limiting factor in the performance of these devices, which are often operated at elevated temperatures, its temperature dependence is of significant interest. Here we use NaOH as a prototypical example of alkaline electrolytes, and for this system we have carried out reactive molecular dynamics simulations with an experimentally verified high-dimensional neural network potential derived from density-functional theory calculations. It is found that in concentrated NaOH solutions elevated temperatures enhance both the contributions of proton transfer to the ionic conductivity and deviations from the Nernst-Einstein relation. These findings are expected to be of practical relevance for electrochemical devices based on alkaline electrolyte solutions.

Density functional theory calculations (DFT), coupled with microkinetic modelling, have been used to simulate Temperature Programmed Desorption (TPD) experiments for calcined ceria nanopowders with the aim to gain insight into the chemistry governing their high redox activity. Our simulations consider two main nanoparticle models. One is a perfect ceria octahedron supercharged with adsorbed oxygen molecules turned into superoxide ions, as has previously been used to explain the enhanced oxygen storage capacity (OSC) in nanoceria. The other model is a variant where we have introduced oxygen vacancies under ridge Ce ions, thereby reducing their coordination numbers to five. The results from our microkinetic modelling suggest that including such five-coordinated Ce adsorption sites results in a TPD spectrum that better matches the experimental counterpart in terms of both peak position and width. In addition, this new structural model allows for the co-existence of Ce3+ ions, superoxide ions and O-2 molecules, as seen in experiments in the literature.