A systematic study of the valence electronic structure of cyclo(Gly–Phe), cyclo(Trp–Tyr) and cyclo(Trp–Trp) dipeptides in the gas phase
Literature Information
Giuseppe Mattioli, Paola Alippi, Lorenzo Avaldi, Paola Bolognesi, Laura Carlini, Rocio Borrego Varillas, Manjot Singh, Robert Richter
The electronic energy levels of cyclo(glycine–phenylalanine), cyclo(tryptophan–tyrosine) and cyclo(tryptophan–tryptophan) dipeptides are investigated with a joint experimental and theoretical approach. Experimentally, valence photoelectron spectra in the gas phase are measured using VUV radiation. Theoretically, we first obtain low-energy conformers through an automated conformer–rotamer ensemble sampling scheme based on tight-binding simulations. Then, different first principles computational schemes are considered to simulate the spectra: Hartree–Fock (HF), density functional theory (DFT) within the B3LYP approximation, the quasi-particle GW correction, and the quantum-chemistry CCSD method. Theory allows assignment of the main features of the spectra. A discussion on the role of electronic correlation is provided, by comparing computationally cheaper DFT scheme (and GW) results with the accurate CCSD method.
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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.











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