  Identifying the constituting materials of concealed objects is crucial in a
wide range of sectors, such as medical imaging, geophysics, nonproliferation,
national security investigations, and so on. Existing methods face limitations,
particularly when multiple materials are involved or when there are challenges
posed by scattered radiation and large areal mass. Here we introduce a novel
brute-force statistical approach for material identification using high
spectral resolution detectors, such as HPGe. The method relies upon updated
semianalytic formulae for computing uncollided flux from source of gamma
radiation, shielded by a sequence of nested spherical or cylindrical materials.
These semianalytical formulae make possible rapid flux estimation for material
characterization via combinatorial search through all possible combinations of
materials, using a high-resolution HPGe counting detector. An important
prerequisite for the method is that the geometry of the objects is known (for
example, from X-ray radiography). We demonstrate the viability of this material
characterization technique in several use cases with both simulated and
experimental data.
