Johnson Matthey Technology Review - Volume 64, Issue 2, 2020

Portable electronic devices, electric vehicles and stationary energy storage applications, which encourage carbon-neutral energy alternatives, are driving demand for batteries that have concurrently higher energy densities, faster charging rates, safer operation and lower prices. These demands can no longer be met by incrementally improving existing technologies but require the discovery of new materials with exceptional properties. Experimental materials discovery is both expensive and time consuming: before the efficacy of a new battery material can be assessed, its synthesis and stability must be well-understood. Computational materials modelling can expedite this process by predicting novel materials, both in stand-alone theoretical calculations and in tandem with experiments. In this review, we describe a materials discovery framework based on density functional theory (DFT) to predict the properties of electrode and solid-electrolyte materials and validate these predictions experimentally. First, we discuss crystal structure prediction using the ab initio random structure searching (AIRSS) method. Next, we describe how DFT results allow us to predict which phases form during electrode cycling, as well as the electrode voltage profile and maximum theoretical capacity. We go on to explain how DFT can be used to simulate experimentally measurable properties such as nuclear magnetic resonance (NMR) spectra and ionic conductivities. We illustrate the described workflow with multiple experimentally validated examples: materials for lithium-ion and sodium-ion anodes and lithium-ion solid electrolytes. These examples highlight the power of combining computation with experiment to advance battery materials research.

Waste biomass, a renewable resource, is a reasonable choice for green clean power generation using advanced thermal treatment technologies such as gasification. In this research, dried-densified olive pomace residues from olive oil production have been applied as biomass feedstock in a new gasification process for synthesis gas (syngas) generation using a 500 kg h⁻¹ throughput capacity autothermal modified updraft gasifier system. The product syngas generation rate is found to be approximately 2.5 Nm³ kg⁻¹ of olive pomace, with a calorific value (CV) between 5.0 MJ Nm⁻³ and 7.0 MJ Nm⁻³. More than 85% of carbon in pomace is converted to produced syngas by the gasification system. The gasification reactor generates syngas which passes through a specially designed swirl hot gas burner and is then burned directly in a thermal oil boiler retrofitted to an organic Rankine cycle (ORC) turbine generator. As a result, the produced syngas at around 350°C is directly combusted with tars so that a great deal of chemical energy loss is prevented. The thermal oil heater has a thermal energy capacity of 1.77 MWh. The generated 1.6 MWh thermal energy from the thermal oil heater is transferred to the ORC turbine to generate 240 kW electrical power.

The work presented here introduces the topic of plasma catalysis through selected work in scientific literature and commercial applications, as well as identifying some of the key challenges faced when attempting to utilise non-thermal atmospheric plasma catalysis across multidisciplinary boundaries including those of physics, chemistry and electrical engineering. Plasma can be generated by different methods at many energy levels and can initiate chemical reactions; the main challenges are to selectively initiate desirable reactions either within a process stream or at the surface of a material. The material, which may have intrinsic catalytic properties, the nature of the process gas and the geometry of the reactor will influence the products formed. Previous work has shown that the mechanism for plasma-initiated reactions can be different to that occurring from more traditional thermally stimulated reactions, which opens up possibilities of using different catalytic materials to optimise the reaction rate and product speciation. In addition, the influence of a plasma at the surface of a material and the effects that can be introduced will be discussed.

The adsorption and diffusion of species in activated carbons is fundamental to many processes in catalysis and energy storage. Nuclear magnetic resonance (NMR) gives an insight into the molecular-level mechanisms of these phenomena thanks to the unique magnetic shielding properties of the porous carbon structure, which allows adsorbed (in-pore) species to be distinguished from those in the bulk (ex-pore). In this work we investigate exchange dynamics between ex-pore and in-pore solvent species in microporous carbons using a combination of one-dimensional (1D) and two-dimensional (2D) NMR experiments. We systematically compare the effects of four variables: particle size, porosity, solvent polarity and solvent viscosity to build up a picture of how these factors influence the exchange kinetics. We show that exchange rates are greater in smaller and more highly activated carbon particles, which is expected due to the shorter in-pore–ex-pore path length and faster diffusion in large pores. Our results also show that in-pore–ex-pore exchange of apolar solvents is slower than water, suggesting that the hydrophobic chemistry of the carbon surface plays a role in the diffusion kinetics, and that increased viscosity also reduces the exchange kinetics. Our results also suggest the importance of other parameters, such as molecular diameter and solvent packing in micropores.

Understanding the manufacture and operation of automotive emissions control particulate filters is important in the optimised design of these emissions control systems. Here we show how magnetic resonance imaging (MRI) can be used to understand the drying process, which is part of the manufacture of catalysed particulate filters. Comparison between a wall-flow particulate filter substrate and a flow-through monolith (FTM) has been performed, with MRI giving spatial information on the drying process. We have also used MRI to study the fluid dynamics of a gasoline particulate filter (GPF). Inlet and outlet channel gas velocities have been measured for a clean GPF and two GPF samples loaded with particulate matter (PM) to understand the effect of PM on the filter flow profiles and porous wall permeability as soot is deposited.

This study focuses on new technologies for the production of medical implants using a combination of robotics and microplasma coatings. This involves robot assisted microplasma spraying (MPS) of a multilayer surface structure on a biomedical implant. The robot motion design provides a consistent and customised plasma coating operation. Based on the analytical model results, certain spraying modes were chosen to form the optimised composition and structure of the titanium/hydroxyapatite (HA) multilayer coatings. It is desirable that the Ti coated lower layer offer a dense layer to provide the implant with suitable structural integrity and the Ti porous layer and HA top layer present biocompatible layers which are suitable for implant and tissue integration. Scanning electron microscopy (SEM), transmission electron microscopy (TEM) and X-ray diffraction (XRD) were used to analyse the structure of the coatings. The new robot assisted MPS technique resulting from this research provides a promising solution for medical implant technology.

Zinc oxide has emerged as an attractive material for various applications in electronics, optoelectronics, biomedical and sensing. The large excitonic binding energy of 60 meV at room temperature as compared to 25 meV of gallium nitride, an III-V compound makes ZnO an efficient light emitter in the ultraviolet (UV) spectral region and hence favourable for optoelectronic applications. The high conductivity and transparency of ZnO makes it important for applications like transparent conducting oxides (TCO) and thin-film transistors (TFT). In this paper, the optoelectronic, electronic and other properties that make ZnO attractive for a variety of applications are discussed. Various applications of ZnO thin film and its devices such as light-emitting diodes (LED), UV sensors, biosensors, photodetectors and TFT that have been described by various research groups are presented.

Ceramics are traditionally sintered at high temperatures (~80% melting temperature (Tm)). There are numerous incentives to reduce processing temperature: the reduction in processing energy; integration of polymeric and non-noble metals; greater control of microstructure and final component geometries. ‘Cold sintering’ has been developed as a novel method of densification which uses a transient liquid phase, pressure and heat to achieve dense ceramics. This review explores the process of cold sintering and its potential to densify various ceramic materials and components at low temperatures (<300°C), primarily describing recent results at The University of Sheffield, UK.