Infrared Spectroscopy and Photochemistry of Aromatic Nitriles in Para-Hydrogen Matrices

Motivated by recent detections of several aromatic nitriles in Taurus Molecular Cloud-1, we report laboratory and theoretical investigations of the vibrational spectroscopy and photochemistry of singly and doubly cyano-substituted benzene in solid para-hydrogen matrices. We compare the photochemistry of cyanobenzene (benzonitrile) and three dicyanobenzene isomers initiated by excitations at 193 nm. In addition, we report the photochemistry of deuterated cyanobenzene (d5-cyanobenzene), enabling us to determine the major products produced during the cyanobenzene photodissociation. The major products observed in the photolysis of all the nitriles are HCN and HNC, which are likely produced by hydrogen abstraction from para-H2 by the CN radical. This indicates that the major photodissociation channel involves cleavage of the bond between the ring and the nitrile group, forming the phenyl (or cyanophenyl) radical + CN. We observe secondary photoproducts similar to those found during benzene photolysis. Our findings may aid the interpretation of recent JWST mid-infrared observations of aromatics in photodissociation regions.

Improvements to AI Systems:

1. Astrochemical Reaction Pathway Predictor

• Improvement: Train a model on the photodissociation product distributions (HCN, HNC, phenyl/cyanophenyl radicals) and their branching ratios for cyano-substituted benzenes in solid para-H2.

• Capability: Predict dominant photochemical channels for other aromatic nitriles (e.g., cyano-naphthalenes, cyano-PAHs) under interstellar conditions, enabling rapid screening of candidate molecules for JWST spectral matching without lab experiments.

2. Vibrational Spectral Simulator with Matrix Effects

• Improvement: Incorporate the laboratory-measured IR band positions and intensities of benzonitrile, dicyanobenzenes, and their photoproducts in para-H2 into a generative model that accounts for matrix-induced shifts and line broadening.

• Capability: Generate synthetic mid-infrared spectra for arbitrary cyano-aromatic molecules in astrophysical ices, directly comparable to JWST NIRSpec/MIRI observations, improving automated identification of aromatic features in photodissociation regions.

3. Isotope-Sensitive Photochemistry Model

• Improvement: Use the deuterated cyanobenzene (d5) data to train a model that distinguishes H/D abstraction pathways and CN vs. C–N bond cleavage kinetics.

• Capability: Predict isotope fractionation patterns (e.g., D/H ratios in HCN/HNC) in interstellar clouds, aiding interpretation of ALMA and JWST observations of deuterated species and refining chemical network models.

4. Secondary Photoproduct Analog Generator

• Improvement: Leverage the observation that secondary products resemble benzene photolysis (e.g., ring-opening or H-loss products) to build a transfer-learning model that maps known benzene photochemistry to substituted aromatics.

• Capability: Automatically propose plausible secondary photoproducts and their IR fingerprints for any aromatic nitrile, reducing manual spectral assignment time and improving completeness of astrochemical databases.

5. Context-Aware JWST Spectral Interpreter

• Improvement: Integrate the paper’s findings (CN radical + H2 → HCN/HNC as a major channel) into an AI that cross-references observational spectra with laboratory photolysis data.

• Capability: Given a JWST spectrum of a photodissociation region, the AI can flag the presence of aromatic nitriles, estimate their abundance ratios (e.g., benzonitrile vs. dicyanobenzene), and infer local UV field strength or H2 density from the HCN/HNC ratio, providing quantitative physical conditions directly from spectra.