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Neutron-capture prompt-gamma-ray activation analysis (PGAA) shares most of the virtues of instrumental neutron activation analysis (INAA) for reference material certification: highly penetrating probe and response radiation, simple physics, and few interelement interferences or matrix related non-linearities. PGAA complements INAA in determining a different suite of elements using the same tools: a neutron source and gamma-ray spectrometry. Several important elements that are difficult to measure by other techniques are measurable by PGAA, notably H, B, C, N, and S. A survey of published applications and NIST Standard Reference Material certification work shows over thirty different SRMs analyzed by PGAA, including biological materials (botanical and food), coal and fly ash, metals, and several other matrices.

The NIST natural-product leaf Standard Reference Materials have been widely used in developing reliable methods of analysis. A small amount of mineral matter present in these materials was separated by flotation, and characterized qualitatively by microscopy and quantiatively by neutron activation analysis. Several elements are concentrated in the mineral fraction, which can lead to analytical error through incomplete dissolution or sampling statistics. Two new candidate materials prepared by the Office of Standard Reference Materials, SRM 1515 Apple Leaves and SRM 1547 Peach Leaves, have been processed with an air-jet mill, resulting in a very finely ground leaf material, with particle size less than 200 mesh. A cyclone classifier in the process discriminates against coarse grit, so that the content of minerals in the ground material is less than in the first-generation materials. Better homogeneity was in fact observed, even down to 100 mg sample size. One must use caution, however, to assure that any inhomogeneity found in real samples are appropriately considered and dealt with.

Spreadsheet programs have become ubiquitous and indispensable in the laboratory. Data may be easily entered and manipulated without the need to learn a programming language or consult a statistician. Spreadsheets are numerically robust and easily altered with a few mouse-clicks to accommodate changing needs. Ease of use, however, implies ease of making errors. Data can be entered in place of equations when a sheet is expanded, sometimes without immediately obvious consequences. Errors can be made less likely to occur by paying attention to the design of the worksheet as it is constructed. Input cells can be formatted to delineate input clearly from output. The sheet can be annotated with titles and notes. Named variables aid understanding and error tracing. Modular blocks of code can add clarity. Logical tests should be included to allow for the occurrence of blank cells, zeroes, and negative numbers. The output should display the values of the important parameters used in the calculation as well as the final result. A finished worksheet needs to be tested to assure accuracy. Standard test data should be used to recheck a sheet‘s reliability after it is modified