The aim of this investigation was to characterise the performance of the gas-cluster ion source (GCIS) for the depth profiling of thick organic multi-layer materials. The sample is composed of 25 repeating units of polystyrene (PS) and polyvinylpyrrolidine (PVP) PS = 288 ± 1.3 and PVP = 328 ± 7 nm on a glass substrate. It has been considered challenging to depth profile thick samples (>1 micron) of soft materials due to the changes which occur under sus-tained X-ray irradiation and bombardment of charged projectiles, however, in this study we describe a methodology to eliminate these issues. The use of fast acquisition, snapshot spectroscopy and sample rotation during etching is presented.

Using a combination of surface analysis tools, different polymer materials were analysed using the Kratos AXIS Supra⁺. A common issue with XPS analysis is that the C 1s envelope can look relatively similar for different polymer materials, making them difficult to distinguish using XPS alone. Plasmon features, such as the π-π* transition, which give information related to the sp² content of a material are also concealed by shifts between different C chemical states. Here, a combination of XPS, UPS and REELS are used as complimentary tools to help understand the chemistry of several polymer materials.

XPS was used to characterize the surface chemistry of layered thin film materials, using monochromated Al Kα (1486.6 eV) X-rays to gain quantitative chemical information from the uppermost 10 nm of the surface. In this study, we illustrate how ARXPS is used as a more surface sensitive approach to probe only the topmost 1-3 nm of a material, and how one can utilize Maximum Entropy Method (MEM) software to recreate a concentration depth profile from the resulting data. How the re-moval of contamination effects the resulting MEM model fit is also explored following gentle sputter cleaning using the GCIS.

Rechargeable metal-based batteries (Li, Na and Al) are among the most versatile platforms for high-energy storage. Unfortunately however there are several pitfalls for these energy storage systems, one of which is deposition and dendrite formation during repeated cycles of charge and discharge. Many studies have been performed in search of a dendrite-free, deposition-free system for lithium batteries using novel materials such as 3D structures and carbon nanofibers.[1,2]  Here we will explore the distribution of Lithium in different chemical environments on electrode surfaces. We employ conventional surface analysis techniques (XPS) to yield large area, quantitative, information regarding the distribution of surface species. To explore the lateral and depth distribution of Li we also utilise XP imaging and Argon cluster depth profiling.