Palestrante Convidado: Paul Field (ESI)

Resumo:
Large high-quality databases of elemental and isotope ratio measurements are becoming required to better interpret and model geological environments. As a result, high throughput analysis is increasingly important for both solution and solid (insitu) techniques. This presentation will review how advances in automation have not only improved through put, but also data quality.

Advances in the manufacturing of high purity inert hardware combined with software control has resulted in the development of innovative liquid handling systems suitable for sub picogram determination of metal concentrations. These range from simple inline autodilution systems to state of the art chromatographic platforms capable of separating trace elements from difficult matrices ad isolating elements (B, Ca, Fe, Cu, Zn, Sr, Pb, U, and Th) for traditional/non-traditional isotope ratio analysis.

Modern LA-ICPMS instrumentation has achieved increased performance and sensitivity via developments such as larger, more precise, and faster ablation chambers (TwoVol3, Elemental Scientific Lasers, Bozeman, MT, USA) and enhanced aerosol transport capability (Dual Concentric Injector, DCI, Elemental Scientific Lasers, Bozeman, MT, USA). These improvements allow large-scale images to be constructed in reasonable analytical times and at higher resolution. The advent of LIBS-ICPMS (Lumen, Elemental Scientific Lasers, Bozeman, MT, USA) as an analytical technique, which describes the simultaneous analysis of a sample by LA-ICPMS and LIBS (Laser Induced Breakdown Spectroscopy), has further extended the elemental coverage of the LA technique by offering the determination of “difficult” elements such as H, C, O and F. Further, the dynamic range of the technique has been extended such that “majors” within the sample can be determined and utilized as a channel within the data processing steps. These techniques combined with new data processing capabilities (iolite, Elemental Scientific Lasers, Bozeman, MT, USA) allows the researcher to assess whether any given data point, or pixel, is typical of the entire sample, e.g. an anomalous signal can be attributed to an inclusion or overall sample heterogeneity. Data from an entire region can be assessed as a mean value (e.g. summing of signals from homogeneous areas) giving rise to improved counting statistics over the previous approach.

Examples will be given for a variety of solid and solution applications that benefit from automated sample preparation, handling, introduction and data reduction.