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Supplementary Materials for “From Chemical Space to Observational Priority: Predicting Detectable Molecules in IRC+10216” Guangping Li1, Chao Ou1, Zhao Wang1, Yong Zhang2, Junzhi Wang1 1Laboratory for Relativistic Astrophysics, Department of Physics, Guangxi University, Nanning 530004, China 2School of Physics and Astronomy, Sun Yat-sen University, Zhuhai 519082, China 1 Molecular Line Search and Column Density Analysis This appendix provides the detailed results of the molecular line search and analysis described in the main text (Section 3.2 (Molecular detection)). We present the upper limits of column density 3σ calculated for the non-detected candidate molecules, together with the column densities measured for detected species (such as HC3N and HS2). Table 1: The parameters Rin and Rout represent the inner and outer radii, respectively, measured from the same central coordinates. For band 3, the central coordinates are RA = 146.98941569◦and Decl. = 13.27885622◦while for band 6, they are RA = 146.98972589◦and Decl. = 13.27926713◦. Species Transitions νrest (GHz) Eu (K) Sµ2 10−36 Q(Tex)Rin (′′ ) Rout (′′ ) Rref (′′ ) Tpeak (K) VLSR range (km/s) Flux (K km/s) Nobs 1013 cm−2 Nref 1013 cm−2 HC3N J=11-10 100.076 28.8 152.6 1374.9 26 35 30 1.23 [-47, -7] 31.19 2.252 3.69 CCS 8-7, 7-6 99.866 28.1 57 2844.2 26 35 30 0.02 [-48, -6] 0.403 0.247 0.4 c-C3HCCH J=2-1 99.748 13.5 33.1 45664 26 35 30 – – <0.046 <0.66 – HS233/2-31/2 253.486 226.3 85.2 25868 – 0.42 30 2.04 [-30, -18] 10.0 12.2 6.22e4 NS 11/2-9/2 253.570 38.7 20.7 2194.5 – 0.42 30 – – <8.2 <128.1 6.54e5 In Table 1, the species such as HC3N and CCS, the derived upper limits agree with observational constraints, confirming their detectability. The model predicts column densities of 7.24 ×1013, 10.78 ×1013, and 4.21 ×1013 cm−2for c−C3HCCH, HS2, and NS, respectively, corresponding to overall rankings of 418, 331, and 522 among predicted species. Some higher-ranked molecules remain unconfirmed, either because they have zero dipole moments, making them undetectable in the millimeter/submillimeter range, or due to the absence of laboratory spectroscopic data. c-C3HCCH exhibits a model-predicted column density exceeding the observational upper limit by roughly an order of magnitude. This discrepancy mainly reflects the assumptions made in deriving the observational column density, such as the source size, excitation temperature, and the optically thin approximation, rather than the shortcomings of the model itself. Within these uncertainties, the model prediction and the observational upper limit are reasonably consistent. For NS, the predicted value is below the detection threshold, in agreement with its non-detection. For HS2, the predicted column density differs from the upper limit of the observed value by about 13%, and the observational uncertainty is sufficient to account for this deviation, indicating consistency between the two within the overall uncertainty range. 1
2 Selection and Prioritization of Molecular Lines for ALMA Observations The model initially predicted 1,133 candidate molecules potentially present in the circumstellar envelope of IRC+10216. However, this number is too large to practically guide future astronomical observation plans. To provide a focused and observationally useful target list, we conducted a rigorous screening of this extensive catalog.The candidate list was cross-referenced with the Splatalogue database to retrieve precise spectroscopic data from the CDMS and JPL catalogs. We filtered the dataset to retain only transitions falling within the frequency coverage of ALMA Bands 1 through 10. For each candidate species, we extracted the rest frequencies (ν), upper state energies (Eu), and catalog intensities (Icat).Since Icat is conventionally reported at a reference temperature of T0= 300 K, it does not accurately reflect the excitation conditions in the circumstellar envelope. To estimate the realistic signal strength, we recalculated the line intensities at a representative excitation temperature of T= 75 K. The intensity at 75 K, I(75K), was derived from the catalog intensity I(300K) using the Boltzmann distribution and the partition function ratio, calculated as follows: I(T)=I(T0)Q(T0) Q(T) exp(−Eu/kBT)[1 −exp(−hν/kBT)] exp(−Eu/kBT0)[1 −exp(−hν/kBT0)] where Q(T) represents the rotational partition function at temperature T,kBis the Boltzmann constant, and his the Planck constant.We then defined a composite Ranking Score (S) to identify the most significant emission features. This score weights the calculated line intensity by the specific molecular abundance: Si=Ii(75K) ×Ntot, species where Ii(75K) is the linear integrated intensity of transition iat 75 K, and Ntot, species is the sourcespecific column density. This metric ensures that intrinsically weaker lines from highly abundant species are prioritized correctly against intrinsically strong lines from rare species. We identified the 30 species with the highest cumulative scores. These are listed in Table 2. 2
3 DFT Benchmarking and Reliability Analysis To ensure the reliability of the Density Functional Theory (DFT) methodology employed in this work for predicting molecular properties, we performed a benchmark analysis against the established QM9 database. We specifically compared two fundamental parameters essential for spectroscopic identification: Zero Point Energy (ZPE) and Rotational Constants. As shown in Figure 1, our calculated values exhibit excellent agreement with the QM9 reference data. The regression analysis yields a coefficient of determination (R2) of 0.99 for ZPE and 0.98 for Rotational Constants. These high correlation coefficients demonstrate that our computational framework provides sufficient accuracy for the subsequent selection and prioritization of molecular lines in ALMA observations. 0.00 0.05 0.10 0.15 Zero Point Energy (DFT) 0.00 0.05 0.10 0.15 Zero Point Energy (QM9) R 2 = 0.99 0 20 40 60 80 100 Rotational Constant (DFT) 0 20 40 60 80 100 Rotational Constant (QM9) R 2 = 0.98 Figure 1: Comparison of calculated molecular properties between our DFT methodology and the QM9 database. 3
