Text mining assisted review of the literature on Li-O2 batteries

The high theoretical capacity of Li-O2 batteries attracts a lot of attention and this field has expanded significantly in the last two decades. In a more general way, the large number of articles being published daily makes it difficult for researchers to keep track of the progress in science. Here we develop a text mining program in an attempt to facilitate the process of reviewing the literature published in a scientific field and apply it to Li-O2 batteries. We analyze over 1800 articles and use the text mining program to extract reported discharge capacities, for the first time, which allows us to show the clear progress made in recent years. In this paper, we focus on three main challenges of Li-O2 batteries, namely the stability-cyclability, the low practical capacity and the rate capability. Indeed, according to our text mining program, articles dealing with these issues represent 86% of the literature published in the field. For each topic, we provide a bibliometric analysis of the literature before focusing on a few key articles which allow us to get insights into the physics and chemistry of such systems. We believe that text mining can help readers find breakthrough papers in a field (e.g. by identifying papers reporting much higher performances) and follow the developments made at the state of the art (e.g. by showing trends in the numbers of papers published—a decline in a given topic probably being the sign of limitations). With the progress of text mining algorithms in the future, the process of reviewing a scientific field is likely to become more and more automated, making it easier for researchers to get the 'big picture' in an unfamiliar scientific field

Importance of Incorporating Explicit 3D-Resolved Electrode Mesostructures in Li–O2 Battery Models

Lithium-oxygen batteries are attractive for reversible energy storage because of their theoretically high capacities. Practically, high capacities are challenging to achieve due to key issues such as the transport and growth of the Li2O2 discharge product. Numerous carbon-based cathode mesostructures have been studied experimentally and computationally aiming to reach higher capacities. One-dimensional continuum models are widely used to study the discharge capacities of electrode mesostructures. Here, we investigate the capabilities and shortcomings of such models to represent different electrode mesostructures, Li2O2 growth mechanisms, and their impact on the discharge performance by comparing them to pore network models which consider an explicit representation of the three-dimensional pore mesostructure. The continuum model can accurately predict discharge capacities when the discharge products grow through surface mechanism, but fails to provide reasonable results when this growth includes a solution mechanism. Conversely, the pore network model results are in agreement with experiments. We attribute the better accuracy of the pore network model to a more accurate representation of the electrode mesostructures, particularly the explicit consideration of the pore interconnectivity. The pore network model allows us to reconcile, within a single theoretical framework, the scattered correlations between discharge capacity and electrode mesostructure descriptors reported in the literature

Stochasticity of Pores Interconnectivity in Li–O2 Batteries and its Impact on the Variations in Electrochemical Performance

While large dispersions in electrochemical performance have been reported for lithium oxygen batteries in the literature, they have not been investigated in any depth. The variability in the results is often assumed to arise from differences in cell design, electrode structure, handling and cell preparation at different times. An accurate theoretical framework turns out to be needed to get a better insight into the mechanisms underneath and to interpret experimental results. Here, we develop and use a pore network model to simulate the electrochemical performance of three-dimensionally resolved lithium−oxygen cathode mesostructures obtained from TXM nanocomputed tomography. We apply this model to the 3D reconstructed object of a Super P carbon electrode and calculate discharge curves, using identical conditions, for four different zones in the electrode and their reversed configurations. The resulting galvanostatic discharge curves show some dispersion, (both in terms of capacity and overpotential) which we attribute to the way pores are connected with each other. Based on these results, we propose that the stochastic nature of pores interconnectivity and the microscopic arrangement of pores can lead, at least partially, to the variations in electrochemical results observed experimentally

Polar surface structure of oxide nanocrystals revealed with solid-state NMR spectroscopy

Abstract: Compared to nanomaterials exposing nonpolar facets, polar-faceted nanocrystals often exhibit unexpected and interesting properties. The electrostatic instability arising from the intrinsic dipole moments of polar facets, however, leads to different surface configurations in many cases, making it challenging to extract detailed structural information and develop structure-property relations. The widely used electron microscopy techniques are limited because the volumes sampled may not be representative, and they provide little chemical bonding information with low contrast of light elements. With ceria nanocubes exposing (100) facets as an example, here we show that the polar surface structure of oxide nanocrystals can be investigated by applying 17O and 1H solid-state NMR spectroscopy and dynamic nuclear polarization, combined with DFT calculations. Both CeO4-termination reconstructions and hydroxyls are present for surface polarity compensation and their concentrations can be quantified. These results open up new possibilities for investigating the structure and properties of oxide nanostructures with polar facets

Towards a Selective Heterogeneous Catalyst for Glucose Dehydration to 5-Hydroxymethylfurfural in Water: CrCl2 Catalysis in a Thin Immobilized Ionic Liquid Layer

Sugar it up: Stabilization of the CrCl2 active phase in a thin layer of an ionic liquid covalently grafted to mesoporous silica results in a highly selective catalyst for the dehydration of glucose to 5-hydroxymethylfurfural (HMF) in an aqueous medium. Glucose dehydration in water by using the CrCl2-Im-SBA-15 catalyst leads to a 50 % HMF selectivity that can be further increased to up to 70 % by modifying the solvent system

Mesoporous SSZ-13 zeolite prepared by a dual-template method with improved performance in the methanol-to-olefins reaction

Hierarchical SSZ-13 zeolites were synthesized by combining N,N,N-trimethyl-1-adamantanammonium hydroxide (TMAdOH) as the structure-directing agent for chabazite formation with mono- and diquaternary ammonium-type and organosilane mesoporogens and extensively characterized for their structural, textural, and catalytic properties. Mesoporous SSZ-13 zeolites can be synthesized in one step by combining TMAdOH and the diquaternary ammonium-type surfactant C22-4-4Br2. The mesopore volume increases with the mesoporogen/SDA ratio. The hierarchical zeolites are highly crystalline and exhibit similar Brønsted acidity as SSZ-13. Hierarchical SSZ-13 zeolites display increased lifetime in packed-bed MTO experiments than conventional SSZ-13 at similar light olefins yield. The increased lifetime is due to better utilization of the micropore space. With increasing mesoporosity, the micropore space is used more efficiently, but also the rate of coke formation at the crystal periphery increases. Accordingly, the most stable zeolite is obtained at a relatively low C22-4-4Br2/SDA ratio. These zeolite catalysts can be regenerated without substantial loss of activity

Modelling amorphous materials via a joint solid-state NMR and X-ray absorption spectroscopy and DFT approach: application to alumina

Understanding electronic structure is a crucial component in the development of many functional materials including semiconductors, transparent-conducting oxides, and batteries, and is necessarily directly dependent on their underlying atomistic structure. The elucidation of atomistic structure is impeded, both experimentally and computationally, by structural disorder, presenting a huge challenge for designing functional amorphous materials. Amorphous materials may be characterised through their local atomic arrangements using, for example, solid-state NMR and X-Ray Absorption Spectroscopy (XAS). By using these two spectroscopy methods to inform the sampling of configurations from ab initio molecular dynamics we devise and validate an amorphous model, choosing amorphous alumina to illustrate the approach due to its wide range of technological uses. Our model predicts two distinct geometric arrangements of AlO5 coordination polyhedra and determines the origin of the pre-edge features in the Al K-edge XAS. We finally construct an average electronic density of states for amorphous alumina, and identify localized states at the conduction band minimum (CBM). We show that the CBM is comprised of Al 3s states and connect this localization and the presence of the pre-edge in the XAS. Deconvoluting this XAS by coordination geometry reveals contributions from both AlO4 and AlO5 geometries at the CBM give rise to the pre-edge, which provides insight into the role of AlO5 in the electronic structure of alumina. This work represents an important advance within the field of solid-state amorphous modelling, providing a method for developing amorphous models through comparison of experimental and computationally derived spectra, which may then be used to determine the electronic structure of amorphous materials