In this study, density functional theory (DFT) was used to analyze the processes that govern the interactions among triethylaluminum (TEAL), the Ziegler–Natta (ZN) catalyst, and the inhibitory compounds dimethylamine (DMA) and diethylamine (DEA) during olefin polymerization. The structural and charge characteristics of these inhibitors were examined through steric maps and DFT calculations. Combined DFT calculations (D3-B3LYP/6-311++G(d,p)) and IR spectroscopic analysis show that the most efficient way to deactivate the ZN catalyst is via the initial formation of the TEAL·DMA complex. This step has a kinetic barrier of only 27 kcal mol⁻¹ and a negative ΔG, in stark contrast to the >120 kcal mol⁻¹ required to form TEAL·DEA. Once generated, TEAL·DMA adsorbs onto the TiCl₄/MgCl₂ cluster with adsorption energies of −22.9 kcal mol⁻¹ in the gas phase and −25.4 kcal mol⁻¹ in n-hexane (SMD model), values 5–10 kcal mol⁻¹ more favorable than those for TEAL·DEA. This explains why, although dimethylamine is present at only 140 ppm, its impact on productivity (−19.6%) is practically identical to that produced by 170 ppm of diethylamine (−20%). The persistence of the ν(Al–N) band at ~615 cm⁻¹, along with a >30% decrease in the Al–C/Ti–C bands between 500 and 900 cm⁻¹, the downward shift of the N–H stretch from ~3300 to 3200 cm⁻¹, and the +15 cm⁻¹ increase in ν(C–N) confirm Al←N coordination and blockage of alkyl transfer, establishing the TEAL·DMA → ZN pathway as the dominant catalytic poisoning mechanism.

Phenolic-rich extracts from Satureja montana were evaluated before and after diazomethane treatment to determine how chemical derivatization influences their antioxidant capacity. Native and modified extracts were compared experimentally by measuring total phenolic content, ferric reducing antioxidant power (FRAP), and Fe²⁺-chelating ability. EN1 exhibited the highest concentration of phenolic compounds, reaching 1278.54 mmol/g, whereas EM2 retained only 1.99 mmol/g. In the FRAP assay, reducing power followed the order EN1 (9.36) > EN2 (3.72) > EM2 (2.08), with EM2 still exceeding caffeic, chlorogenic, and ferulic acids. In contrast, the modified extracts showed superior metal chelating capacity, with EM1 and EM2 displaying IC₅₀ values of 0.70 and 0.82 mg/mL, respectively, both markedly lower than those of the native extracts and the pure standards. To rationalize these differences, a DFT study was performed at the B3LYP/6-311++G(d,p) level, examining 18 proposed phenolic acids and their methylated derivatives associated with the extracts. All methylation reactions were thermodynamically favorable, particularly for compounds 18 (−57.10 kcal/mol), 16 (−53.96), 6 (−53.34), and 3, 9, and 11 (−52.71). Solvent effects were found to be structure-dependent: caffeic acid showed BDE values of 72.29, 73.59, and 74.43 kcal/mol in the gas phase, water, and benzene, respectively, whereas syringic acid displayed values of 80.44, 77.09, and 80.65 kcal/mol under the same conditions. Likewise, the ionization potential of caffeic acid decreased from 180.09 kcal/mol in the gas phase to 133.26 kcal/mol in water and 154.22 kcal/mol in benzene. Among all analyzed species, methyl 3,4-dihydroxycinnamate exhibited the lowest BDE (71.60 kcal/mol) as well as the most favorable ΔG°r toward HOO• (−11.06 kcal/mol).

Plastic pollution, driven by the durability and widespread use of polyolefins such as polypropylene (PP) and high-density polyethylene (HDPE), poses a formidable environmental challenge. To address this issue, we have developed an integrated multiscale framework that combines thermocatalytic experimentation, process-scale simulation, and molecular-level modeling to optimize the catalytic pyrolysis of PP and HDPE waste. Under the identified optimal conditions (300 °C, 10 wt % HMOR zeolite), liquid-oil yields of 60.8% for PP and 87.3% for HDPE were achieved, accompanied by high energy densities (44.2 MJ/kg, RON 97.5 for PP; 43.7 MJ/kg, RON 115.2 for HDPE). These values significantly surpass those typically reported for uncatalyzed pyrolysis, demonstrating the efficacy of HMOR in directing product selectivity toward valuable liquids. Above 400 °C, the process undergoes a pronounced shift toward gas generation, with gas fractions exceeding 50 wt % by 441 °C, underscoring the critical influence of temperature on product distribution. Gas-phase analysis revealed that PP-derived syngas contains primarily methane (20%) and ethylene (19.5%), whereas HDPE-derived gas features propylene (1.9%) and hydrogen (1.5%), highlighting intrinsic differences in bond-scission pathways governed by polymer architectures. Aspen Plus process simulations, calibrated against experimental data, reliably predict product distributions with deviations below 20%, offering a rapid, cost-effective tool for reactor design and scale-up. Complementary density functional theory (DFT) calculations elucidate the temperature-dependent energetics of C–C bond cleavage and radical formation, revealing that system entropy increases sharply at 500–550 °C, favoring the generation of both liquid and gaseous intermediates. By directly correlating catalyst acidity, molecular reaction mechanisms, and process-scale performance, this study fills a critical gap in plastic-waste valorization research. The resulting predictive platform enables rational design of catalysts and operating conditions for circular economy applications, paving the way for scalable, efficient recovery of fuels and chemicals from mixed polyolefin waste.

The adsorption and activation of CO₂ on Cu_xSc_y nanoclusters with x + y equal to 4 were analyzed using DFT and PDOS and TDOS signatures. The geometries of Cu₃Sc, Cu₂Sc₂, and CuSc₃ were optimized in the gas phase, and the minima were verified by frequencies in ORCA using M06-2X/def2-TZVP. Multiplicities 1, 3, and 5, temperatures between 298 and 400 K, and four CO₂ coordination modes R1 to R4 were evaluated. Naked and complex cluster comparison panels were constructed, and two energy windows, −18 to −10 eV and −8 to 6 eV around the Fermi level, were analyzed, complemented by frontier orbitals and charge maps. Thermodynamics indicated that mode and multiplicity control the adsorption energy, with ANOVA p-values of 0.002 and 0.008, while temperature was not significant (p = 0.682). In Cu₃Sc–C₂v(1), the R1 singlet at 298 K showed E_ads −33.43 kcal·mol⁻¹ with spin contamination, while alternative modes in the singlet were unfavorable. In PDOS and TDOS, the bare cluster exhibits a Cu d band at −11 to −10 eV and a valley around −5 eV. The exergonic complexes show CO₂ signals near the Fermi level, superimposed on Cu and Sc states, with state filling and broadening. Transferable indicators based on CO₂ intensity in the −8 to 6 eV range and metal–adsorbate overlap are proposed as predictors of exergonic adsorption.

Converting carbon dioxide (CO₂) into value-added chemicals and/or capturing it before emission are complementary strategies to mitigate rising atmospheric CO₂ levels. Copper-based materials are widely investigated for CO₂ conversion because Cu can bind and electronically activate CO₂ and related intermediates. In this computational research, an evaluation of CO₂ activation in Cu_xSc_γ nanoclusters (Cu₃Sc, Cu₂Sc₂, and CuSc₃) anchored on a graphene bilayer doped with three nitrogen atoms (graphene-3N) was performed using conformational screening and thermochemical adsorption analysis at 298.15, 300, and 400 K. Initially, the Cu₃Sc, Cu₂Sc₂, and CuSc₃ nanoclusters were optimized and characterized (relative energy, multiplicity, and electronic characteristics), and the support model (graphene-3N bilayer) was validated by comparing free geometry with partially restricted geometry, corroborating minima through vibrational analysis. Subsequently, CO₂ adsorption/activation on Cu_xSc_γ @graphene-3N was evaluated, and ΔH and ΔG values were calculated. Ultimately, based on the ΔG(T) values, the Sabatier regimes were established, where it was observed that Cu₃Sc exhibits moderate exergonic adsorption (ΔG = −76.07, −67.31, and −58.92 kJ·mol⁻¹ at 298.15, 350, and 400 K). In contrast, Cu₂Sc₂ exhibits intense adsorption (−165.02, −156.36, and −148.04 kJ·mol⁻¹), and CuSc₃ results in practically irreversible fixation (−293.98, −287.32, and −279.09 kJ·mol⁻¹), giving priority to Cu₃Sc as the most optimal cluster in terms of activation-regeneration.