Owing to its advantages such as higher dose rates and shorter time required, ion irradiation, including in-situ ion irradiation of nano-foils on electron microscopes, is being proposed as a surrogate for neutron/reactor irradiation in materials testing for the research of irradiation induced/enhanced degradation of reactor structural materials. This raises a key question: can the microstructural evolution be matched across different irradiation conditions? Here we report our recent study using a rate-theory based cluster dynamics approach on the time dependent defect accumulation in elemental molybdenum under varying ion and neutron irradiation conditions, within a low temperature and low dose regime. The approach solves a large system of coupled differential equations each equation describing the rate of change in the concentration of a particular defect/cluster (defined by its nature and number of constituent point defects) caused by direct production (for primary defects), diffusion flux across spatial grids (for mobile defects, under ion irradiation), and capturing and/or emission interactions with other defects/clusters. Our results suggest that defect evolution under different dose rates can be very well matched in either thin foil ion irradiation or bulk neutron irradiation, by using different irradiation temperatures to counteract the effect of the dose rate variation. Across the two types of irradiation, less perfect matching is obtained mainly due to the strong surface sink effect in the thin foil, but the matching can be improved by combining the temperature shift strategy with selection of a single depth in the foil (as opposed to all depths averaged) for matching, or a greater foil thickness. collision cascades; 2. only point defects are mobile; 3. defect cluster concentrations are not evolving; 4. there are no free surfaces. Here, we are concerned with the temporal evolution of concentrations of all defects (point defects and their clusters) and corresponding size distribution, rather than the steady state rates of particular processes. As detailed below, we also remove the assumptions/simplifications needed in the analytical derivations by Mansur.