Wollo University

Adding a morphology input channel to an organic-photovoltaic prediction pipeline that previously held only molecular descriptors raises the blended PCE prediction for the 3HT decamer:JSM5 blend from about 4.0% to about 4.5%, and the PCNN alone from about 2.4% to about 3.7%. The channel is a set of latent placeholder slots learned from device-target residuals and filled at prediction time with molecular-dynamics morphology descriptors; because the latents are target-derived, the shift reflects the pipeline's response to MD inputs and cannot be attributed to a physical morphology effect.

Adding a morphology input channel to an organic-photovoltaic prediction pipeline that previously held only molecular descriptors raises the blended PCE prediction for the 3HT decamer:JSM5 blend from about 4.0% to about 4.5%, and the PCNN alone from about 2.4% to about 3.7%. The channel is a set of latent placeholder slots learned from device-target residuals and filled at prediction time with molecular-dynamics morphology descriptors; because the latents are target-derived, the shift reflects the pipeline's response to MD inputs and cannot be attributed to a physical morphology effect.