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The structure determination of surface species has long been a challenge because of their rich chemical heterogeneities. Modern tip-based microscopic techniques can resolve heterogeneities from their distinct electronic, geometric, and vibrational properties at the single-molecule level but with limited interpretation from each. Here, we combined scanning tunneling microscopy (STM), noncontact atomic force microscopy (AFM), and tip-enhanced Raman scattering (TERS) to characterize an assumed inactive system, pentacene on the Ag(110) surface. This enabled us to unambiguously correlate the structural and chemical heterogeneities of three pentacene-derivative species through specific carbon-hydrogen bond breaking. The joint STM-AFM-TERS strategy provides a comprehensive solution for determining chemical structures that are widely present in surface catalysis, on-surface synthesis, and two-dimensional materials.

By combining the density functional theory (DFT) and a hierarchical equations of motion (HEOM) approach, we investigate the Kondo phenomena in a composite system consisting of a dehydrogenated cobalt phthalocyanine molecule (d-CoPc) adsorbed on an Au(111) surface. DFT calculations are performed to determine the ground-state geometric and electronic structures of the adsorption system. It is found that the singly occupied dz(2) orbital of Co forms a localized spin, which could be screened by the substrate conduction electrons. This screening leads to the prominent Kondo features as observed in the scanning tunneling microscopy experiments. We then employ the HEOM approach to characterize the Kondo correlations of the adsorption system. The calculated temperature-dependent differential conductance spectra and the predicted Kondo temperature agree well with the experiments, and the universal Kondo scaling behavior is correctly reproduced. This work thus provides important insights into the relevant experiments, and it also highlights the applicability of the combined DFT+HEOM approach to the studies of strongly correlated condensed matter systems.

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Dynamic optimization and multi-objective optimization have separately gained increasing attention from the research community during the last decade. However, few studies have been reported on dynamic multi-objective optimization (dMO) and scarce effective dMO methods have been proposed. In this paper, we fulfill these gabs by developing new dMO test problems and new effective dMO algorithm. In the newly designed dMO problems, Pareto-optimal decision values (i.e., Pareto-optimal solutions: POS) or both POS and Pareto-optimal objective values (i.e., Pareto-optimal front: POF) change with time. A new multi-strategy ensemble multi-objective evolutionary algorithm (MS-MOEA) is proposed to tackle the challenges of dMO. In MS-MOEA, the convergence speed is accelerated by the new offspring creating mechanism powered by adaptive genetic and differential operators (GDM); a Gaussian mutation operator is employed to cope with premature convergence; a memory like strategy is proposed to achieve better starting population when a change takes place. In order to show the advantages of the proposed algorithm, we experimentally compare MS-MOEA with several algorithms equipped with traditional restart strategy. It is suggested that such a multi-strategy ensemble approach is promising for dealing with dMO problems.

The density functional theory calculations with local density approximation have been performed to simulate scanning tunneling microscopy (STM) images of individual molecules in close-packed upright alkanethiol self-assembled monolayers (SAMs) on a Au(111) surface. The internal patterns in the simulated STM images are dependent on bias voltage and alkanethiol chain length and have characteristics of the topographic effect modulated by the electronic effect. The electronic structure of the adsorption system is analyzed for discussing the STM imaging mechanism of alkanethiol SAMs. Besides enhancing the intermixing between the alkyl part and the Au substrate states, the sulfur atom in alkanethiol obviously influences the pattern in the STM image by its chemisorption mode on the Au(111) surface. Simulated images qualitatively reproduce STM experimental results.