INCREASING THE EFFICIENCY OF PALEOINTENSITY ANALYSES BY SELECTION OF SAMPLES USING FIRST-ORDER REVERSAL CURVE DIAGRAMS

Abstract

The global paleointensity database is restricted by the high failure rate of paleointensity analyses. Excluding thermal alteration, failure is usually caused by the presence of multidomain grains and interactions among grains, two properties that can be identified using first-order reversal curve (FORC) diagrams. We measured FORC diagrams on sister samples of about 200 samples that had been used for Thellier paleointensity determinations and determined criteria to discriminate samples that gave acceptable paleointensity results from those that did not. The three most discriminating criteria are the vertical spread of the FORC distribution (indicative of interactions), expressed as the full width at half maximum (FWHM), the spread of the FORC distribution along the Hc = 0 axis (width), and the bulk coercivity Hc (both indicative of domain state). Setting thresholds at 132 mT for the width of the distribution and 29 mT for the FWHM maximizes the number of unsuccessful rejected samples. Using an additional threshold of Hc, = 5.4 mT results in rejection of 32% of unsuccessful samples. Seven samples that barely satisfy the paleointensity selection criteria would also be rejected using these selection criteria. Most of the samples that fail the paleointensity experiment without being detected by our selection criteria have ideal noninteracting single-domain magnetic properties but fail because of the thermal alteration that results from repeated heating. Being able to eliminate at least one third of unsuccessful samples using our FORC diagram-based prescreening procedure should provide a significant improvement in efficiency of paleointensity measurements. Copyright 2006 by the American Geophysical Union.