Inter-laboratory comparison of fission track confined length and etch figure measurements in apatite
Inter-laboratory comparison of fission track confined length and etch figure measurements in apatite
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磷灰石裂变径迹限制长度和蚀刻图测量的实验室间比较
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
A. Hurford
中科院分区：
文献类型：
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作者：
R. Ketcham;A. Carter;A. Hurford
摘要：磷灰石裂变径迹长度和蚀刻图数据是获取热历史信息的有力工具，但两者都需要人工分析人员进行人工测量，并且不能保证再现性。我们报告了一项实验室间研究的结果，该研究旨在澄清这些测量的一致性和差异区域，并为评估最佳实践提供基础，以增强数据集的互兼容性。来自墨西哥杜兰戈的四个巨晶磷灰石样品，具有诱导径迹，一个未经纳米退火，三个不同量的热退火，在国际上分布。总共有30个实验室小组的55名分析人员参加了实验。在所有分析人员中，样本的相对平均轨迹长度是一致的，但是对每个样本的测量显示，实验室和分析人员之间的分散程度大大超出了统计预期。使用未退火样品对退火样品进行归一化测量提高了一致性，使用c轴投影对轨迹角进行归一化也是如此。蚀刻图数据也显示出超出统计预期的可变性，并通过归一化提高一致性。基于这些数据，我们建议对分析人员进行严格的长度和蚀刻图测量培训，包括标准测量，并且在使用热历史逆建模作为解释过程的一部分时，每个分析人员的未知数据由该分析人员自己对标准的测量归一化。
Abstract Apatite fission-track length and etch figure data are powerful tools for obtaining thermal history information, but both require human analysts making manual measurements and reproducibility is not assured. We report the results of an inter-laboratory study designed to clarify areas of congruence and divergence for these measurements and provide a basis for evaluating best practices to enhance intercompatibility of data sets. Four samples of megacrystic apatite from Durango, Mexico, with induced tracks, one unnannealed and three thermally annealed by varying amounts, were distributed internationally. In all, 55 analysts in 30 laboratory groups participated in the experiment. Relative mean track lengths among the samples were consistent across all analysts, but measurements for each sample showed scatter among labs and analysts considerably in excess of statistical expectation. Normalizing measurements of annealed samples using the unannealed sample improved consistency, as did normalizing for track angle using c-axis projection. Etch figure data also showed variability beyond statistical expectation, and consistency was improved by normalizing. Based on these data we recommend rigorous analyst training for length and etch figure measurement that includes measurement of standards, and that each analyst’s data on unknowns be normalized by that analyst’s own measurements on standards when using thermal history inverse modeling as part of the interpretation process.