XRF is only one of several available methods. While it is widely accessible and provides an initial indication, it is prone to errors and primarily examines only the surface. Therefore, it should be considered merely a preliminary step. To achieve a reliable assessment of an object's material composition at an affordable cost, especially for amateurs, it would be sensible to establish a series of tests—including chemical, optical, magnetic, and other measurement methods.
There is no single non-destructive method that can definitively identify the metallic composition of an object in 3D. (Although some studies use advanced techniques like MRI, these are generally beyond the budgets of most users.) Imagine scanning a thin vein exposed by a crack: if only the 0.2 mm surface is analyzed, the remainder of the material goes unchecked.
I want to address the ongoing criticism on this board regarding the use of XRF. I see it as one of many testing methods that provide a directional hint toward the true composition. After conducting an XRF analysis, one should follow up with chemical tests on pulverized material to further narrow down the composition. Advanced methods like fire assay or comprehensive laboratory analyses are costly and not feasible for everyone; they should be reserved as the final step in a thorough assessment. Preliminary techniques like XRF can help determine whether further testing is necessary and worthwhile.
I have always regarded this forum as a space for amateur enthusiasts rather than for industrial users with unlimited budgets. In that spirit, we need to incorporate all feasible testing methods while being mindful not to overestimate their individual outcomes.
So, I suggest to develop and establish a chain of tests or a process chart (which may incorporate XRF) for such tasks as "gold standard" or "best practice" in this forum —one that is both affordable and doable without fancy equipment. This approach serves both the holder of an unknown material and the users who are asked to comment on the findings, allowing them to provide their assumptions or assessments based on a more comprehensive set of data.