Figure demonstrates a three-stage screening workflow constructed based on the SISSO models selected for the triplet exciton energy. Because of the recent interest in TTA up-conversion of infrared (IR) light to the visible range, we screen for materials, whose triplet excitation energy is in the IR, below 1.6 eV. There are 31 such materials in total in the PAH101 set. The screening thresholds for each stage of the workflow are set to 1.6 eV + n× RMSE, where n=1,2,3 and RMSE refers to the training set RMSE of each model. With n=1, the first-stage model, M 3,1 , correctly classifies all 31 materials with triplet excitation energy in the IR with only 2 false positives. Further screening by the second-stage model, M 3,2 , and subsequently the third-stage model, M 4,3 , provides a marginal improvement by reducing the number of false positives from 2 to 1 without losing any true positives. Setting n to 2 or 3 is not beneficial because it only increases the number of false positives. In this case, we would recommend screening only with M 3,1 because it already delivers robust performance. We note, however, that the Next, we assess whether the 31 materials in the PAH101 set with triplet excitation energies in the IR are likely to undergo TTA. The thermodynamic driving force for TTA is given by the difference between twice the triplet excitation energy and the singlet excitation energy (the opposite of the SF driv- ing force). As discussed in Refs. , GW+BSE systematically underestimates the SF driving force and therefore overestimates the TTA driving force. Hence, we assess the likelihood of a given material to undergo SF/TTA relative to other known SF/TTA materials.