A simulation programme based on the nucleation-and-growth model of latent-image formation was used to study how trap depth and trap density at various tabular grain thicknesses affected quantum sensitivity and reciprocity failure. Using a 1.2x0.2 µm model ‘grain’, the unsensitized case was simulated with 0.05 eV traps located on both the face and the core of the grain, the latter to simulate the effect of twin planes on latent-image location. The trap densities were adjusted to achieve a higher internal speed than surface speed, as seen experimentally with the emulsion used to validate the simulation. To simulate the effects of chemical sensitization, these parameters were held fixed while edge traps of depths 0.2–0.6 eV were added at various trap densities for grain thicknesses of 50, 100 and 200 nm. All but the lowest trap densities at 0.2 eV changed the situation to complete or almost complete edge domination for latent-image location. Maximum efficiencies for latent-image formation were six to eight absorbed photons/grain for a 0.01 s exposure, although the trap density had to be decreased as the trap depth increased to achieve these maximum values. A decrease in efficiency with decreasing thickness as well as with decreasing diameter was seen for the lower trap depth values. These grain diameter and thickness effects disappeared for simulations using a 10^–6 s exposure, indicating that the decreasing efficiency at 0.01 s was due to differences in the onset of low-irradiance reciprocity failure. Reciprocity failure was simulated for chosen trap depth/density combinations. These data were compared with experimental reciprocity failure data to help validate the model. Reasonable agreement was obtained for trap depths in the range of those deduced from the experimental phase of the project. However, uncertainties regarding other parameters that affect the position of the reciprocity failure curve with respect to exposure time must be reduced before this agreement can be considered a validation of the model (Refer to PDF file for exact formulas).
Department, Program, or Center
Chester F. Carlson Center for Imaging Science (COS)
Imaging Science Journal 52N3 (2004) 164-175
RIT – Main Campus