No abstract

Lithium-air batteries are considered to be a potential alternative to lithium-ion batteries for transportation applications, owing to their high theoretical specific energy. So far, however, such systems have been largely restricted to pure oxygen environments (lithium-oxygen batteries) and have a limited cycle life owing to side reactions involving the cathode, anode and electrolyte. In the presence of nitrogen, carbon dioxide and water vapour, these side reactions can become even more complex. Moreover, because of the need to store oxygen, the volumetric energy densities of lithium-oxygen systems may be too small for practical applications. Here we report a system comprising a lithium carbonate-based protected anode, a molybdenum disulfide cathode and an ionic liquid/dimethyl sulfoxide electrolyte that operates as a lithium-air battery in a simulated air atmosphere with a long cycle life of up to 700 cycles. We perform computational studies to provide insight into the operation of the system in this environment. This demonstration of a lithium-oxygen battery with a long cycle life in an air-like atmosphere is an important step towards the development of this field beyond lithium-ion technology, with a possibility to obtain much higher specific energy densities than for conventional lithium-ion batteries.

Moving mechanical interfaces are commonly lubricated and separated by a combination of fluid films and solid 'tribofilms', which together ensure easy slippage and long wear life. The efficacy of the fluid film is governed by the viscosity of the base oil in the lubricant; the efficacy of the solid tribofilm, which is produced as a result of sliding contact between moving parts, relies upon the effectiveness of the lubricant's anti-wear additive (typically zinc dialkyldithiophosphate). Minimizing friction and wear continues to be a challenge, and recent efforts have focused on enhancing the anti-friction and anti-wear properties of lubricants by incorporating inorganic nanoparticles and ionic liquids. Here, we describe the in operando formation of carbon-based tribofilms via dissociative extraction from base-oil molecules on catalytically active, sliding nanometre-scale crystalline surfaces, enabling base oils to provide not only the fluid but also the solid tribofilm. We study nanocrystalline catalytic coatings composed of nitrides of either molybdenum or vanadium, containing either copper or nickel catalysts, respectively. Structurally, the resulting tribofilms are similar to diamond-like carbon. Ball-on-disk tests at contact pressures of 1.3 gigapascals reveal that these tribofilms nearly eliminate wear, and provide lower friction than tribofilms formed with zinc dialkyldithiophosphate. Reactive and ab initio molecular-dynamics simulations show that the catalytic action of the coatings facilitates dehydrogenation of linear olefins in the lubricating oil and random scission of their carbon-carbon backbones; the products recombine to nucleate and grow a compact, amorphous lubricating tribofilm.

An accurate and computationally efficient molecular level description of mesoscopic behavior of ice-water systems remains a major challenge. Here, we introduce a set of machine-learned coarse-grained (CG) models (ML-BOP, ML-BOPdih, and ML-mW) that accurately describe the structure and thermodynamic anomalies of both water and ice at mesoscopic scales, all at two orders of magnitude cheaper computational cost than existing atomistic models. In a significant departure from conventional force-field fitting, we use a multilevel evolutionary strategy that trains CG models against not just energetics from first-principles and experiments but also temperature-dependent properties inferred from on-the-fly molecular dynamics (~ 10’s of milliseconds of overall trajectories). Our ML BOP models predict both the correct experimental melting point of ice and the temperature of maximum density of liquid water that remained elusive to-date. Our ML workflow navigates efficiently through the high-dimensional parameter space to even improve upon existing high-quality CG models (e.g. mW model).