Physical Chemistry Chemical Physics最新文献

We report experimental absolute total and partial ionization cross sections for electron collisions with chlorotrifluorocarbon (CFC-13, CClF₃) and chlorodifluoromethane (HCFC-22, CHClF₂) in the energy range from 20 to 1000 eV. For CClF₃ the ionic fragments CF₃⁺ and CClF₂⁺ were identified to have the highest ionization cross sections, indicating a high release of chlorine and fluorine atoms. CHClF₂ dissociates primarily into C(H)F₂⁺, C(H)ClF⁺, and C(H)Cl⁺ with the release of Cl and/or F atoms. For CHClF₂ single and double charged species, adiabatic ionization and partial potential energy surface calculations were performed to obtain insights into the formation-dynamics of neutral chlorine and fluorine and the pathways for the formation of metastable dications. While CHClF₂²⁺ is formed in a single-step double-electron emission, unstable CClF₃²⁺ dissociates and CClF₂²⁺ is observed. Both metastable dications have a triangular planar-like shape and show enhanced dipole moments.

Many light-driven chemical processes (for example, excited state proton transfer, twisted intramolecular charge transfer, etc.) involve excited state potential energy surfaces having multiple local minima, driving the course of photochemistry. To unveil ultrafast coherent dynamics in such systems, we theoretically explore the excited-state linear wavepacket interferometry (WPI) upon excitation by time-delayed ultrafast pulse-pairs, modelling the excited state potential as a symmetric double-well potential. The temporal as well as spatiotemporal oscillations in excited-state population resulting from interference between wavepackets are simulated over a long period of time (of several tens of picoseconds), capturing tunnelling and reflection, both at zero temperature and at finite temperature. The influences of tuning molecular and excitation parameters, i.e., height of the barrier separating the wells and interpulse phase-locking frequency, on these oscillations are also explored. The localisation of population in either the left well or the right well as a function of interpulse delay is examined and shown to be controlled by chirping of the pulses. Further, we simulate the differential Shannon entropy as a function of time, replicating the wavepacket dynamics. Finally, we show strategies of quantum control and establish a connection between WPI in a double-well and qubits. We also extend our study to the asymmetric double-well potential to shed light on dynamics in real physical systems. Therefore, our study underscores the importance of WPI in molecular systems, having prospective applications in quantum computation and quantum information.

Targeted covalent inhibitors (TCIs) have become an important modality in modern drug discovery, but computational tools for covalent pose prediction and quantitative affinity ranking remain underdeveloped. We constructed a large, structure and activity-resolved benchmark to systematically evaluate covalent docking and to develop a covalent-aware drug-target affinity (DTA) prediction framework. Starting from CovalentInDB 2.0 and related structural resources, we curated 2172 high quality covalent protein-ligand complexes spanning diverse protein classes and nine electrophilic warhead types, and used them to benchmark four docking engines (AutoDock4, CovDock in the Schrödinger Suite, GNINA and Boltz-2) in a self-docking setting. Boltz-2 shows the strongest pose-reproduction performance on our structure-resolved benchmark. However, because co-folding engines are trained on broad PDB corpora and our benchmark is also derived from PDB-resolved complexes, potential train-test overlap is likely; thus, Boltz-2 results are reported as a reference upper bound rather than a leakage-free estimate of prospective generalization. Across 17 covalent targets with quantitative IC₅₀ data, we further assessed the relationship between docking scores and experimental pIC₅₀ values and found that score-affinity correlations are generally weak and highly target dependent, with |r| < 0.2 for most target-software pairs and even pronounced negative correlations for several systems. We propose CovMTL-DTA to overcome these limitations, a covalent-aware multi-task DTA model that integrates ligand molecular graphs augmented with SMARTS-based warhead descriptors, pretrained protein sequence embeddings, cross-modal ligand-protein attention, and a task-relation module for inter-target transfer. Trained on curated covalent ligand-target pairs, the model outperforms classical machine-learning regressors and state-of-the-art deep DTA baselines, achieving a Pearson correlation of ∼0.77 with reduced RMSE and MAE on an independent test set. In an EGFR-focused virtual screening of ∼14 000 Michael-acceptor-containing compounds, the model prioritizes three clinically relevant EGFR covalent inhibitors within the top 1% of the ranked library and identifies structurally novel, favorable physicochemical properties hits. Our benchmark and model highlight both the strengths and limitations of current covalent docking and demonstrate how covalent-specific representations and multi-task learning can substantially improve affinity prediction and hit prioritization in covalent drug discovery.

High contact resistance induced by low quantum tunneling probability (TP) limits the performance of 2D electronic devices, making the modulation of Schottky barrier height (SBH) and contact types crucial. van der Waals heterostructures (vdWHs) composed of 2D transition metal carbides (MXenes) and metallic transition metal dichalcogenides (TMDs) serve as an ideal platform for exploring the interface contact physics in high-performance 2D devices. Via first-principles calculations, this study systematically investigates the geometric structures, stability, and electronic properties of nine XY₂/Sc₂CCl₂ (X = Nb, Ni, Ti, V, Mn, Ta; Y = S, Se) vdWHs. The contact characteristics of these vdWHs were explored using three modulation strategies: semiconductor layer number, vertical electric field, and vertical strain. All vdWHs exhibit good thermodynamic, dynamic, and thermal stability. Except for TiS₂/Sc₂CCl₂, which forms a p-type Schottky contact, the other eight vdWHs form n-type Schottky contacts, with their SBH dominated by the metal work function. In the intrinsic state, all vdWHs show low TP (2.67-4.87%), indicating high contact resistance. The three modulation strategies are effective: increasing the number of Sc₂CCl₂ layers raises SBH and reduces TP; a vertical external electric field induces reversible Schottky-Ohmic transitions (the critical field is related to the metal work function); vertical strain modulates barrier width/height via interlayer coupling, and compressive strain boosts the TP to nearly 100%. This work elucidates the modulation mechanisms of 2D metal-semiconductor interfaces, providing a theoretical basis and design strategies for low-contact-resistance, high-performance 2D electronic devices.

The increasing need for reliable and trace-level detection of hazardous agrochemicals stimulated the development of hybrid surface-enhanced Raman spectroscopy (SERS)-active substrates with improved sensitivity and selectivity. A single-step, facile growth process engineered for fabricating plasmonic silver nanostructures and its application for trace detection of thiram has been explored, and detailed experimental and finite-difference time-domain (FDTD) simulation has been investigated. The SERS measurement along with FDTD simulations identified the silver nanostructure with a particle size and inter-particle gap of ∼61 nm and ∼22 nm, respectively, as the optimal plasmonic structure demonstrating the highest plasmonic coupling, which further showed the limit of detection (LOD) of 10^-10 M for thiram with an enhancement factor (EF) of 4.25 × 10¹⁰. The coupling of graphene with optimal silver nanostructure exhibits a significant enhancement in the SERS signal compared with the bare silver nanostructure substrate, with about one order more increase in the EF due to the enhanced plasmonic coupling induced by the incorporation of graphene and understood from the FDTD analysis. Graphene, with its Fermi level possibly modulated and subsequently tuned to align with HOMO-LUMO levels of thiram could be responsible for improved plasmonic coupling and hence increased SERS performance.

Silicon-containing heterocyclic molecules have emerged as promising candidates in medicinal and agrochemical research. However, the synthesis of silicon-containing heterocycles has remained highly challenging. In this work, we employed the crossed molecular beams technique to elucidate the underlying reaction pathways for the synthesis of a unique class of six-membered cyclic organosilicon molecules in which silicon and nitrogen atoms occupy adjacent positions: methyl-azasilacyclohexadienylidenes - silicon and nitrogen substituted benzenes functionalized with a methyl group. This class was accessed via the reaction of ground-state silicon nitride radicals (SiN, X²Σ⁺) with isoprene (C₅H₈, X¹A') under single-collision conditions at a collision energy of 25 ± 1 kJ mol^-1. Integration of experimental results with electronic structure calculations revealed the formation of at least two cyclic products: 4-methyl-1-aza-2-silacyclohexa-3,5-dien-2-ylidene and 5-methyl-1-aza-2-silacyclohexa-3,5-dien-2-ylidene. The underlying mechanism shows strong similarities to the previously studied reaction of the silicon nitride radicals (SiN, X²Σ⁺) with 1,3-butadiene (C₄H₆, X¹A_g), with the methyl group in isoprene classified as a spectator, thus advancing our fundamental understanding of the organosilicon chemistry through the delivery of synthetic pathways to a distinct class of silicon-containing heterocyclic molecules: methylazasilacyclo-hexadienylidenes.