Absorption Spectra of Acetylene, Vinylidene, and Their Deuterated Isotopologues on Ab Initio Potential Energy and Dipole Moment Surfaces

Bridging the gap: viable reaction pathways from tetrahedrane to benzyne

The addition of sp-carbon-containing molecules to polycyclic sp3 tetrahedrane (c-C4H4) results in the formation of both o-benzyne (c-C6H4) and benzene (c-C6H6). Since both c-C6H4 and c-C6H6 have been detected in the interstellar medium (ISM), providing additional pathways for their possible astrochemical formation mechanisms can lead to the discovery of other molecules, such as c-C4H4, benzvalyne, and vinylidene (:CCH2). Addition of diatomic carbon (C2), the ethynyl radical (C2H), vinylidene, and acetylene (HCCH) to c-C4H4 is undertaken in individual pathways through high-level quantum chemical computations at the CCSD(T)-F12b/cc-pVTZ-F12 level of theory. The resulting C2 addition pathway proceeds barrierlessly through benzvalyne as an intermediate and reaches a true minimum at c-C6H4, but no leaving groups are produced which is required to dissipate excess energy within an interstellar chemical scheme. Similarly, the C2H addition to c-C4H4 produces benzvalyne as well as its related isomers. This pathway allows for the loss of a hydrogen leaving group to dissipate the resulting energy. Lastly, the HCCH and :CCH2 addition pathways follow through both benzvalene and benzvalyne in order to reach c-C6H6 (benzene) and c-C6H4 (o-benzyne) as well as H2 as the required leaving group. Although there is a barrier to the HCCH addition, the :CCH2 addition presents the contrary with only submerged barriers. These proposed mechanisms provide alternative possibilities for the formation of complex organic molecules in space.

A highly accurate full-dimensional ab initio potential surface for the rearrangement of methylhydroxycarbene (H3C-C-OH)

We report here a full-dimensional machine learning global potential surface (PES) for the rearrangement of methylhydroxycarbene (H₃C-C-OH, 1t). The PES is trained with the fundamental invariant neural network (FI-NN) method on 91 564 ab initio energies calculated at the UCCSD(T)-F12a/cc-pVTZ level of theory, covering three possible product channels. FI-NN PES has the correct symmetry properties with respect to permutation of four identical hydrogen atoms and is suitable for dynamics studies of the 1t rearrangement. The averaged root mean square error (RMSE) is 11.4 meV. Six important reaction pathways, as well as the energies and vibrational frequencies at the stationary geometries on these pathways are accurately preproduced by our FI-NN PES. To demonstrate the capacity of the PES, we calculated the rate coefficient of hydrogen migration in -CH₃ (path A) and hydrogen migration of -OH (path B) with instanton theory on this PES. Our calculations predicted the half-life of 1t to be 95 min, which is excellent in agreement with experimental observations.

Quantitative structure-property relationship of the photoelectrochemical oxidation of phenolic pollutants at modified nanoporous titanium oxide using supervised machine learning

Here we report on an advanced photoelectrochemical (PEC) oxidation of 22 phenolic pollutants based on modified nanoporous TiO2, which was directly grown on a titanium substrate electrochemically. Their degradation rate constants were experimentally determined and their physicochemical properties were computaionally calculated. The quantitative structure-property relationship (QSPR) was elucidated by employing multiple linear regression (MLR) method. A supervised machine learning approach was employed to build QSPR models. The high predictive abilities of the QSPR model were validated via leave-one-out (LOO) method and a strict regimen of statistical validation tests. The significant descriptors identified in the QSPR Model for the phenolic compounds were also assessed using a typical dye pollutant Rhodamine B, further confirming the high effectiveness and predictability of the optimized model. Our study has shown that the integrated effect of the structural, hydrophobic and topological properties along with electronic property should be considered in order to design an efficient PEC catalytic approach for environmental applications.