Quantitative and Qualitative Analyses of Mass Spectra of OEL Materials by Artificial Neural Network and Interface Evaluation: Results from a VAMAS Interlaboratory Study.

Quantitative analysis of binary mixtures of tris(2-phenylpyridinato)iridium(III) (Ir(ppy)3) and tris(8-hydroxyquinolinato)aluminum (Alq3) by using an artificial neural network (ANN) system to mass spectra was attempted based on the results of a VAMAS (Versailles Project on Advanced Materials and Standards) interlaboratory study (TW2 A31) to evaluate matrix-effect correction and to investigate interface determination. Monolayers of binary mixtures having different Ir(ppy)3 ratios (0, 0.25, 0.50, 0.75, and 1.00), and the multilayers containing these mixtures and pure samples were measured using time-of-flight secondary ion mass spectrometry (ToF-SIMS) with different primary ion beams, OrbiSIMS (SIMS with both Orbitrap and ToF mass spectrometers), laser desorption ionization (LDI), desorption/ionization induced by neutral clusters (DINeC), and X-ray photoelectron spectroscopy (XPS). The mass spectra were analyzed using a simple ANN with one hidden layer. The Ir(ppy)3 ratios of the unknown samples and the interfaces of the multilayers were predicted using the simple ANN system, even though the mass spectra of binary mixtures exhibited matrix effects. The Ir(ppy)3 ratios at the interfaces indicated by the simple ANN were consistent with the XPS results and the ToF-SIMS depth profiles. The simple ANN system not only provided quantitative information on unknown samples, but also indicated important mass peaks related to each molecule in the samples without a priori information. The important mass peaks indicated by the simple ANN depended on the ionization process. The simple ANN results of the spectra sets obtained by a softer ionization method, such as LDI and DINeC, suggested large ions such as trimers. From the first step of the investigation to build an ANN model for evaluating mixture samples influenced by matrix effects, it was indicated that the simple ANN method is useful for obtaining candidate mass peaks for identification and for assuming mixture conditions that are helpful for further analysis.

Surface Analysis of Pristine and Cycled NMC/Graphite Lithium-Ion Battery Electrodes: Addressing the Measurement Challenges.

Lithium-ion batteries are the most ubiquitous energy storage devices in our everyday lives. However, their energy storage capacity fades over time due to chemical and structural changes in their components, via different degradation mechanisms. Understanding and mitigating these degradation mechanisms is key to reducing capacity fade, thereby enabling improvement in the performance and lifetime of Li-ion batteries, supporting the energy transition to renewables and electrification. In this endeavor, surface analysis techniques are commonly employed to characterize the chemistry and structure at reactive interfaces, where most changes are observed as batteries age. However, battery electrodes are complex systems containing unstable compounds, with large heterogeneities in material properties. Moreover, different degradation mechanisms can affect multiple material properties and occur simultaneously, meaning that a range of complementary techniques must be utilized to obtain a complete picture of electrode degradation. The combination of these issues and the lack of standard measurement protocols and guidelines for data interpretation can lead to a lack of trust in data. Herein, we discuss measurement challenges that affect several key surface analysis techniques being used for Li-ion battery degradation studies: focused ion beam scanning electron microscopy, X-ray photoelectron spectroscopy, Raman spectroscopy, and time-of-flight secondary ion mass spectrometry. We provide recommendations for each technique to improve reproducibility and reduce uncertainty in the analysis of NMC/graphite Li-ion battery electrodes. We also highlight some key measurement issues that should be addressed in future investigations.

Understanding the bonding mechanisms of organic molecules deposited on graphene for biosensing applications.

Graphene is an ideal material for biosensors due to the large surface area for multiple bonding sites, the high electrical conductivity allowing for high sensitivity, and the high tensile strength providing durability in fabricated sensor devices. For graphene to be successful as a biosensing platform, selectivity must be achieved through functionalization with specific chemical groups. However, the device performance and sensor sensitivity must still be maintained after functionalization, which can be challenging. We compare phenyl amine and 1,5-diaminonaphthalene functionalization methods for chemical vapor deposition grown graphene, both used to obtain graphene modified with amine groups-which is required for surface attachment of highly selective antibody bio-receptors. Through atomic force microscopy (AFM), Raman spectroscopy, and time-of-flight secondary ion mass spectrometry imaging of co-located areas, the chemistry, thickness, and coverage of the functional groups bound to the graphene surface have been comprehensively analyzed. We demonstrate the modification of functionalized graphene using AFM, which unexpectedly suggests the removal of covalently bonded functional groups, resulting in a "recovered" graphene structure with reduced disorder, confirmed with Raman spectroscopy. This removal explains the decrease in the ID/IG ratio observed in Raman spectra from other studies on functionalized graphene after mechanical strain or a chemical reaction and reveals the possibility of reverting to the non-functionalized graphene structure. Through this study, preferred functionalization processes are recommended to maintain the performance properties of graphene as a biosensor.

Rapid monitoring of graphene exfoliation using NMR proton relaxation.

Graphene is now being produced on an industrial scale and there is a pressing need for rapid in-line measurements of particle size for Quality Assurance and Quality Control (QA/QC). Standardised characterisation techniques such as electron microscopy and scanning probe microscopy can be time consuming and may require pre-processing steps and/or solvent elimination prior to measurements. Herein, we demonstrate the use of nuclear magnetic resonance (NMR) proton relaxation as a powerful method for monitoring the sonication assisted liquid phase exfoliation of graphene. This technique requires little or no sample preparation and the resulting spin-spin relaxation time showed a strong correlation with particle size, exfoliation yield and specific surface area measurements. As the NMR proton relaxation method is rapid, inexpensive, and can potentially be operated in-line, it shows great promise to become a valuable QA/QC method for graphene production methods in liquid.

A Simplified Method for Patterning Graphene on Dielectric Layers.

The large-scale formation of patterned, quasi-freestanding graphene structures supported on a dielectric has so far been limited by the need to transfer the graphene onto a suitable substrate and contamination from the associated processing steps. We report µm scale, few-layer graphene structures formed at moderate temperatures (600-700 °C) and supported directly on an interfacial dielectric formed by oxidizing Si layers at the graphene/substrate interface. We show that the thickness of this underlying dielectric support can be tailored further by an additional Si intercalation of the graphene prior to oxidation. This produces quasi-freestanding, patterned graphene on dielectric SiO2 with a tunable thickness on demand, thus facilitating a new pathway to integrated graphene microelectronics.

Versailles Project on Advanced Materials and Standards interlaboratory study on intensity calibration for x-ray photoelectron spectroscopy instruments using low-density polyethylene.

We report the results of a Versailles Project on Advanced Materials and Standards interlaboratory study on the intensity scale calibration of x-ray photoelectron spectrometers using low-density polyethylene (LDPE) as an alternative material to gold, silver, and copper. An improved set of LDPE reference spectra, corrected for different instrument geometries using a quartz-monochromated Al Kα x-ray source, was developed using data provided by participants in this study. Using these new reference spectra, a transmission function was calculated for each dataset that participants provided. When compared to a similar calibration procedure using the NPL reference spectra for gold, the LDPE intensity calibration method achieves an absolute offset of ∼3.0% and a systematic deviation of ±6.5% on average across all participants. For spectra recorded at high pass energies (≥90 eV), values of absolute offset and systematic deviation are ∼5.8% and ±5.7%, respectively, whereas for spectra collected at lower pass energies (<90 eV), values of absolute offset and systematic deviation are ∼4.9% and ±8.8%, respectively; low pass energy spectra perform worse than the global average, in terms of systematic deviations, due to diminished count rates and signal-to-noise ratio. Differences in absolute offset are attributed to the surface roughness of the LDPE induced by sample preparation. We further assess the usability of LDPE as a secondary reference material and comment on its performance in the presence of issues such as variable dark noise, x-ray warm up times, inaccuracy at low count rates, and underlying spectrometer problems. In response to participant feedback and the results of the study, we provide an updated LDPE intensity calibration protocol to address the issues highlighted in the interlaboratory study. We also comment on the lack of implementation of a consistent and traceable intensity calibration method across the community of x-ray photoelectron spectroscopy (XPS) users and, therefore, propose a route to achieving this with the assistance of instrument manufacturers, metrology laboratories, and experts leading to an international standard for XPS intensity scale calibration.