Expanded Group Additivity Framework for Thermochemical Prediction of Fluorocarbons and PFAS from Large-Scale DFT Data

Benchmarking semiempirical quantum chemical methods on liquid water.

Stimulated by the renewed interest and recent developments in semiempirical quantum chemical (SQC) methods for noncovalent interactions, we examine the properties of liquid water under ambient conditions by means of molecular dynamics (MD) simulations, both with the conventional neglect of diatomic differential overlap-type methods, e.g., AM1 and PM6, and with DFTB-type (density-functional tight-binding) methods, e.g., DFTB2 and GFN-xTB (Geometry-Frequency-Noncovalent eXtended Tight-Binding). Besides the original parameter sets, some specifically reparameterized SQC methods (denoted as AM1-W, PM6-fm, and DFTB2-iBi) targeting various smaller water systems ranging from molecular clusters to bulk are considered as well. The quality of these different SQC methods for describing liquid water properties under ambient conditions is assessed by comparison with well-established experimental data and also with BLYP-D3 density functional theory-based ab initio MD simulations. Our analyses reveal that static and dynamic properties of bulk water are poorly described by all considered SQC methods with the original parameters, regardless of the underlying theoretical models, with most of the methods suffering from too weak hydrogen bonds and hence predicting a far too fluid water with highly distorted hydrogen bond kinetics. Meanwhile, the reparameterized force-matched PM6-fm method is shown to be able to quantitatively reproduce the static and dynamic features of liquid water and thus can be used as a computationally efficient alternative to electronic structure-based MD simulations for liquid water that requires extended length and time scales. DFTB2-iBi predicts a slightly overstructured water with reduced fluidity, whereas AM1-W gives an amorphous ice-like structure for water under ambient conditions.

Development and validation of a ReaxFF reactive force field for the pyrolysis of fluorine-containing gas systems

Density functional benchmarks for methylaluminoxane: successes, biases, and transferability limits.

Methylaluminoxane (MAO) is the most widely used cocatalyst for olefin polymerization, yet its molecular structure remains incompletely understood. Computational methods are essential for elucidating the structure and reactivity of MAO, but their accuracy has been difficult to assess. Benchmarking based on trimethylaluminum (TMA) dimerization has proven insufficient because it omits the oxygen environments central to MAO chemistry. Here, we benchmark 25 density functional methods against DLPNO-CCSD(T) and RI-MP2 reference calculations for a set of MAO oligomers, evaluating geometry, electronic energy, vibrational frequencies, and thermodynamic properties. We identify energetic biases toward specific structural motifs (µ4-O and µ-Me) in ten functionals, with errors ranging from under 5 kJ mol-1 to over 45 kJ mol-1. ωB97X-D4 and MN15 show the largest errors and should be avoided for pure MAO systems. Two functionals, ωB97X-V and ωB97M-D4, accurately reproduce reference electronic energies without structural bias. For vibrational properties, quasi-harmonic treatment effectively reduces method-dependent entropy variations, and thermochemical corrections prove robust across functionals. However, extending these methods to metallocene-MAO ion pairs reveals distinct system-dependent behavior that warrants further investigation. Together, these findings highlight that functional performance is system-dependent, with significant implications for computational studies of catalyst activation mechanisms.

A cheminformatics and DFT exploration of a brominated sulfonamide with nonlinear optical response and preliminary in silico bioactivity assessment.

Benchmarking DFT for Chain-Length and Water Effects in Thermal Conia–Ene Cyclization

Reliable density functional theory (DFT) methods for thermally driven cyclization reactions remain insufficiently established, particularly for systems in which proton transfer, conformational preorganization, and weak environmental effects jointly shape the energy landscape. Here, we present a systematic benchmark of DFT exchange–correlation functional/basis-set combinations against CCSD(T) reference energies for the thermal Conia–Ene cyclization, using chain length and explicit water assistance as chemically relevant probes of functional performance. Representative reaction profiles were constructed for two model substrates (hex-5-ynal and hept-6-ynal), considering pathways with and without explicit water, in both gas phase and implicit solvent. The reaction proceeds stepwise through enolization followed by cyclization, with enolization defining the intrinsic kinetic bottleneck in the water-free pathway (ca. 70 kcal mol–1). Explicit water selectively lowers this barrier by up to 30 kcal mol–1 through proton-transfer mediation, whereas the cyclization barrier is primarily controlled by chain length through transition-state preorganization; implicit solvation has only a minor energetic effect. Across 38 approximate exchange–correlation functionals and 14 basis sets, range-separated hybrids provide the most accurate and balanced description of both activation barriers and reaction energies. In particular, ωB97XD and CAM-B3LYP-D3BJ achieve near-chemical accuracy, with mean absolute errors close to 1 kcal mol–1 when combined with triple-ζ basis sets containing polarization and diffuse functions. Comparable accuracy is also achieved by the double-hybrid functionals mPW2PLYP and DSD-PBEP86, albeit at a substantially higher computational cost. Overall, this study establishes a practical CCSD(T)-referenced benchmark and identifies robust DFT protocols for modeling thermal Conia–Ene cyclizations, with expected transferability to more complex substrates and confined environments.

Chain-length-dependent effects of diisopropylamine on phase transfer and clay retention of perfluoroalkyl substances.

Co-contaminants can alter per- and polyfluoroalkyl substance (PFAS) mobility by modifying aqueous association, phase transfer, and retention by aquifer solids, yet how protonated amines influence these processes remains poorly constrained. Here, we investigated interactions between diisopropylamine (DIPA) and two perfluoroalkyl carboxylates with contrasting chain lengths, trifluoroacetate (TFA) and perfluorooctanoate (PFOA), using bottle tests, diffusion-ordered spectroscopy (DOSY) nuclear magnetic resonance (NMR), retention experiments with montmorillonite, and conformer-ensemble COSMO-RS and qualitative molecular-mechanics cluster calculations. At 20-25 °C and 0.1 wt% per solute, aqueous DIPA/TFA mixtures remained optically clear, and DOSY NMR showed no convergence toward a common diffusion coefficient, consistent with weak and/or fast-exchanging association in bulk water rather than a dominant long-lived contact species. BP86/TZP COSMO-RS calculations for independently solvated ions predicted greater aqueous compatibility for DIPA+/TFA- than for DIPA+/PFOA- and a demixing tendency for the PFOA-containing conformer ensemble. In contrast, higher equimolar DIPA/PFOA loadings produced flocs or precipitates; DIPA/PFOS mixtures also precipitated. Montmorillonite retention experiments showed strong removal of DIPA, limited retention of TFA with or without DIPA, and measurable co-retention of PFOA in the presence of DIPA. These results show that favorable PFAS-amine interactions in bulk water do not necessarily translate into co-retention or reduced mobility. Instead, PFAS chain length and interfacial interactions govern whether association remains labile, as for TFA, or promotes phase transfer and mineral co-retention, as for PFOA. Thus, amine co-contaminants can differentially affect PFAS migration in clay-rich subsurface environments.