Abstract

Stress measurement on samples with texture and large grains is always a challenge. The diffraction peak intensity varies dramatically with different sample orientation. The macroscopic elasticity becomes anisotropic due to strong preferred orientation. The large grains may results in a big error in 2θ due to poor sampling statistics. The fitting results of the conventional sin2ψ method is extremely sensitive to texture and large grains. When stress is measured with a 2D detector, most of the above adverse effects can be minimized or eliminated. The data integration helps to smooth out rough diffraction profiles due to large grain size, texture, small sample area or weak diffraction. The large angular coverage and multiple diffraction rings can minimize the effect of the macroscopic anisotropy. The weighted least squares regression and intensity threshold can further reduce the effect of poor statistics associated with texture and large grains. Multiple {hkl} rings may be used to measure the stress to improve the statistics and minimize the elastic anisotropy effect.

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