We have investigated the CGL (carrier generation layer)/CTL (carrier transport layer) interface, where photocarriers are extrinsically produced, from a microscopic viewpoint. From cross-sectional TEM (transmissiom electron microscope) micrographs of layered photoreceptors, the photocarrier generation site is revealed to be formed as a result of CTM (carrier transport material) penetration from CTL during the wet-coatings. This phenomenon was interpreted based on diffusion. From the measurement of CGM (carrier generation meterial) photoluminescence quenching by the CTM, only the CTMs that make contact with CGM particles are known to promote the photocarriers. The electron-transfer reaction for photocarrier generation is proven to occur adiabatically.

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The authors have studied the charging characteristics of a corona charging device for the

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An accurate color printer model for nonlinear printer is required to apply flexible gray component replacement (GCR). Conventional method to create color printer model, such as Neugebauer-Yule, high order polynomial, or ordinary neural network do not have enough capability to meet the quality which flexible GCR needs, and as a result, color transformation quality was poor. So, we modified ordinary neural network and successed to make more accurate color printer model. In this paper, the detail of this modification is described.
The effects on predictability by the size of neural network and the number of training patterns (number of printed colors) are also discussed. Our experiment shows the fact that larger network has worse predictability than smaller network when small size of patterns is used.

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