Surface analysis of aluminium by glow-discharge optical emission spectrometry

Surface engineering in solids has become an important field in materials science. Glow-discharge optical emission spectrometry (GD-OES) has proven to be a powerful tool for the rapid analysis of elements in the surface of solids. One may employ GD-OES to determine quantitatively the bulk concentration of elements in a sample, and elemental concentrations as a function of depth. Presented here is an overview of GD-OES analysis and an application to aluminium.

A calibration for surface analysis on aluminium alloys by RF-Glow-Discharge Optical Emission Spectrometry

Glow-Discharge Optical Emission Spectrometry (GD-OES) is a powerful technique for the rapid analysis of elements in a solid surface as a function of depth. DC-GD-OES allows depth profiling on electrically conductive surfaces only, and has proven to be difficult for the analysis of insulating layers, such as oxides. However, the technique of radio-frequency (RF) GD-OES has the advantage of being able to depth profile through multiple layers, both conducting and insulating. In this work, a LECO GDS- 850A spectrometer was calibrated for aluminium, oxygen, and other elements, with the RF source installed. A quantitative depth profile for a sample of tempered aluminium alloy 7475 is presented and compared with earlier work[1,2].

A clustering based hybrid system for mass spectrometry data analysis

Recently, much attention has been given to the mass spectrometry (MS) technology based disease classification, diagnosis, and protein-based biomarker identification. Similar to microarray based investigation, proteomic data generated by such kind of high-throughput experiments are often with high feature-to-sample ratio. Moreover, biological information and pattern are compounded with data noise, redundancy and outliers. Thus, the development of algorithms and procedures for the analysis and interpretation of such kind of data is of paramount importance. In this paper, we propose a hybrid system for analyzing such high dimensional data. The proposed method uses the k-mean clustering algorithm based feature extraction and selection procedure to bridge the filter selection and wrapper selection methods. The potential informative mass/charge (m/z) markers selected by filters are subject to the k-mean clustering algorithm for correlation and redundancy reduction, and a multi-objective Genetic Algorithm selector is then employed to identify discriminative m/z markers generated by k-mean clustering algorithm. Experimental results obtained by using the proposed method indicate that it is suitable for m/z biomarker selection and MS based sample classification.

Method design and validation for the determination of uranium levels in human urine using high-resolution alpha spectrometry

Quantification of uranium in human urine is a valuable technique for assessing occupational and public exposure to uranium. A reliable method has been developed and validated in the ARPANSA Radiochemistry Laboratory by means of standard radiochemical separation and purification techniques and measurement using high-resolution alpha spectrometry. This method can be used to evaluate the levels of naturally occurring ²³⁴U, ²³⁵U and ²³⁸U in urine. Method design and validation is the process of defining an analytical requirement, and then confirming that the method under consideration has performance capabilities consistent with what the application requires. The method was designed to measure levels down to 2 mBq/day of total uranium, corresponding to approximately 1/100th of the annual committed effective dose of 20 mSv. Validation tests were developed to assess selectivity, accuracy, recovery and quantification of uncertainty. The radiochemical recovery of this method was measured using ²³²U tracer. The typical minimum detectable concentration for total uranium for 24-h urine samples is approximately 0.6 mBq/day or 0.019 μg/day.

Investigation of the postcure reaction and surface energy of epoxy resins using time-of-flight secondary ion mass spectrometry and contact-angle measurements

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) was used to investigate correlations between the molecular changes and postcuring reaction on the surface of a diglycidyl ether of bisphenol A and diglycidylether of bisphenol F based epoxy resin cured with two different amine-based hardeners. The aim of this work was to present a proof of concept that ToF-SIMS has the ability to provide information regarding the reaction steps, path, and mechanism for organic reactions in general and for epoxy resin curing and postcuring reactions in particular. Contact-angle measurements were taken for the cured and postcured epoxy resins to correlate changes in the surface energy with the molecular structure of the surface. Principal components analysis (PCA) of the ToFSIMS positive spectra explained the variance in the molecular information, which was related to the resin curing and postcuring reactions with different hardeners and to the surface energy values. The first principal component captured information related to the chemical phenomena of the curing reaction path, branching, and network density based on changes in the relative ion density of the aliphatic hydrocarbon and the C₇H₇O⁺ positive ions. The second principal component captured information related to the difference in the surface energy, which was correlated to the difference in the relative intensity of the C_xH_yN_z⁺ ions of the samples. PCA of the negative spectra provided insight into the extent of consumption of the hardener molecules in the curing and postcuring reactions of both systems based on the relative ion intensity of the nitrogen-containing negative ions and showed molecular correlations with the sample surface energy.

Time-of-flight secondary ion mass spectrometry investigation of epoxy resin curing behavior in real time

Time-of-flight secondary ion mass spectrometry and principal components analysis were used in real time to monitor the progress of curing reactions on the surface of a diglycidyl ether of bisphenol A (DGEBA) and diglycidyl ether of bisphenol F (DGEBF) epoxy resin blend reacted with the diamine hardener isophorone diamine at different time intervals. Molecular ions in the mass spectra that characterized the curing reactions steps, including blocking, coupling, branching, and crosslinking, were identified. The aliphatic hydrocarbon ions were correlated to the curing reaction rate, and this indicated that coupling and branching occurred much faster than the blocking and crosslinking curing reactions steps. The total conversion of the coupling and branching reaction steps were followed on the basis of changes with time in the relative ion intensity of molecular ions assigned to the DGEBA/DGEBF, aliphatic hydrocarbon, epoxide, and aromatic ring structures. Indicative measures of crosslinking density were monitored through the observation of changes in the ratio of the relative intensities of the aliphatic hydrocarbon and hydroxyl molecular ions over time. The curing reaction conversion was established by the observation of the changes in the relative ion intensity of the molecular ions that were related to the DGEBA/ DGEBF molecules.

Analysis of self-assembled monolayer interfaces by electrospray mass spectrometry : a gentle approach

A general mass spectrometry technique for the characterization of alkanethiol-modified surfaces is presented. Alkanethiol self-assembled onto a gold surface (in this case, peptides were attached to the gold surface via a thiolate bond) was reductively desorbed in 0.05 M KOH in the presence of octadecyl-derivatized silica gel. The peptide adsorbed onto the silica gel, whereupon it could be filtered, washed to remove any salts, and then eluted using a mixture of 4:1 v/v methanol/water. The eluant containing the peptide was injected into a Fourier transform ion-cyclotron resonance mass spectrometer (FTICR/MS) via electrospray ionization. The spectrum showed no fragmentation of the peptide, demonstrating the gentleness of the technique. This simple procedure is not limited to FTICR/MS and could be adapted to other mass spectrometers.

Organic compounds present in the natural Amazonian aerosol : characterization by gas chromatography–mass spectrometry

[1] As part of the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA)-Cooperative LBA Airborne Regional Experiment (CLAIRE) 2001 campaign in July 2001, separate day and nighttime aerosol samples were collected at a ground-based site in Amazonia, Brazil, in order to examine the composition and temporal variability of the natural “background” aerosol. We used a high-volume sampler to separate the aerosol into fine (aerodynamic diameter, AD < 2.5 μm) and coarse (AD > 2.5 μm) size fractions and quantified a range of organic compounds in methanolic extracts of the samples by a gas chromatographic-mass spectrometric technique. The carbon fraction of the compounds could account for an average of 7% of the organic carbon (OC) in both the fine and coarse aerosol fractions. We observed the highest concentrations of sugars, sugar alcohols, and fatty acids in the coarse aerosol samples, which suggests that these compounds are associated with primary biological aerosol particles (PBAP) observed in the forest atmosphere. Of these, trehalose, mannitol, arabitol, and the fatty acids were found to be more prevalent at night, coinciding with a nocturnal increase in PBAP in the 2–10 μm size range (predominantly yeasts and other small fungal spores). In contrast, glucose, fructose, and sucrose showed persistently higher daytime concentrations, coinciding with a daytime increase in large fungal spores, fern spores, pollen grains, and, to a lesser extent, plant fragments (generally >20 μm in diameter), probably driven by lowered relative humidity and enhanced wind speeds/convective activity during the day. For the fine aerosol samples a series of dicarboxylic and hydroxyacids were detected with persistently higher daytime concentrations, suggesting that photochemical production of a secondary organic aerosol from biogenic volatile organic compounds may have made a significant contribution to the fine aerosol. Anhydrosugars (levoglucosan, mannosan, galactosan), which are specific tracers for biomass burning, were detected only at low levels in the fine aerosol samples. On the basis of the levoglucosan-to-OC emission ratio measured for biomass burning aerosol, we estimate that an average of ∼16% of the OC in the fine aerosol was due to biomass burning during CLAIRE 2001, indicating that the major fraction was associated with biogenic particles.

Dimensionality reduction of protein mass spectrometry data using random projection

Protein mass spectrometry (MS) pattern recognition has recently emerged as a new method for cancer diagnosis. Unfortunately, classification performance may degrade owing to the enormously high dimensionality of the data. This paper investigates the use of Random Projection in protein MS data dimensionality reduction. The effectiveness of Random Projection (RP) is analyzed and compared against Principal Component Analysis (PCA) by using three classification algorithms, namely Support Vector Machine, Feed-forward Neural Networks and K-Nearest Neighbour. Three real-world cancer data sets are employed to evaluate the performances of RP and PCA. Through the investigations, RP method demonstrated better or at least comparable classification performance as PCA if the dimensionality of the projection matrix is sufficiently large. This paper also explores the use of RP as a pre-processing step prior to PCA. The results show that without sacrificing classification accuracy, performing RP prior to PCA significantly improves the computational time.