Spectral neutron imaging methods provide valuable insights into the characterization of hydrogenous materials, including battery electrolytes. However, their application is constrained by sample geometry, setup parameters, and material chemistries, especially when studying physico-chemical changes in battery electrolytes. To address these limitations, we present a framework for simulating and optimizing the investigation of hydrogenous materials. Our approach combines quantitative modeling with experimental data to predict and optimize the contrast achievable in wavelength-resolved neutron imaging methods, thereby maximizing the information obtained in specific neutron imaging setups. While initially demonstrated at the BOA beamline of the Paul Scherrer Institute, this framework is applicable to any continuous source with spectral neutron imaging capabilities with a chopper disk. This work establishes a pathway for accurate studies of hydrogenous materials and their physico-chemical behavior, paving the way for advancements in the field of material characterization with wavelength-resolved neutron imaging.