Interaction of CO with an Au monatomic chain at different strains: electronic structure and ballistic transport

We study the energetics, the electronic structure, and the ballistic transport of an infinite Au monatomic chain with an adsorbed CO molecule. We find that the bridge adsorption site is energetically favored with respect to the atop site, both at the equilibrium Au-Au spacing of the chain and at larger spacings. Instead, a substitutional configuration requires a very elongated Au-Au bond, well above the rupture distance of the pristine Au chain. The electronic structure properties can be described by the Blyholder model, which involves the formation of bonding/antibonding pairs of 5{\sigma} and 2{\pi}* states through the hybridization between molecular levels of CO and metallic states of the chain. In the atop geometry, we find an almost vanishing conductance due to the 5{\sigma} antibonding states giving rise to a Fano-like destructive interference close to the Fermi energy. In the bridge geometry, instead, the same states are shifted to higher energies and the conductance reduction with respect to pristine Au chain is much smaller. We also examine the effects of strain on the ballistic transport, finding opposite behaviors for the atop and bridge conductances. Only the bridge geometry shows a strain dependence compatible with the experimental conductance traces

Effect of stretching on the ballistic conductance of Au nanocontacts in presence of CO: a density functional study

CO adsorption on an Au monatomic chain is studied within density functional theory in nanocontact geometries as a function of the contact stretching. We compare the bridge and atop adsorption sites of CO, finding that the bridge site is energetically favored at all strains studied here. Atop adsorption gives rise to an almost complete suppression of the ballistic conductance of the nanocontact, while adsorption at the bridge site results in a conductance value close to 0.6 G0, in agreement with previous experimental data. We show that only the bridge site can qualitatively account for the evolution of the conductance as a function of the contact stretching observed in the experimental conductance traces. The numerical discrepancy between the theoretical and experimental conductance slopes is rationalized through a simple model for the elastic response of the metallic leads. We also verify that our conductance values are not affected by the specific choice of the nanocontact geometry by comparing two different atomistic models for the tips

Transformational leadership and work engagement in remote work settings: the moderating role of the supervisor’s digital communication skills

PurposeThis study explores the impact of transformational leadership on work engagement within remote work settings. More specifically, we investigate whether supervisor's perceived digital communication skills moderate the relationship between perceived supervisor support and work engagement.Design/methodology/approachModerated mediation model has been tested using a sample of 410 consultants in Italy who worked within a fully remote work setting during Covid-19 pandemic.FindingsDrawing on construal level theory and social presence theory, our study provides insights into the dynamics of leadership and work engagement in remote work settings. We demonstrate that, despite the challenges posed by physical distance, transformational leaders can effectively stimulate the work engagement of remote collaborators. Moreover, our findings suggest that the perceived digital communication skills of supervisors play a crucial role in moderating the relationship between perceived supervisor support and work engagement. This underscores the importance of supervisors' adept use of digital tools in conveying psychological presence and fostering employee engagement in remote work environments.Practical implicationsOur study highlights the importance of developing supervisors' digital communication skills to support and stimulate employee engagement in remote work settings.Originality/valueThis study contributes to the literature by providing one of the first empirical tests of the relationship between transformational leadership, perceived supervisor support, supervisor's digital communication skills and work engagement within a remote work setting. By challenging prior assumptions and offering novel insights, our research enhances understanding of leadership dynamics and provides practical guidance for organizations navigating the challenges of remote work

DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking

Predicting the binding structure of a small molecule ligand to a protein -- a task known as molecular docking -- is critical to drug design. Recent deep learning methods that treat docking as a regression problem have decreased runtime compared to traditional search-based methods but have yet to offer substantial improvements in accuracy. We instead frame molecular docking as a generative modeling problem and develop DiffDock, a diffusion generative model over the non-Euclidean manifold of ligand poses. To do so, we map this manifold to the product space of the degrees of freedom (translational, rotational, and torsional) involved in docking and develop an efficient diffusion process on this space. Empirically, DiffDock obtains a 38% top-1 success rate (RMSD<2A) on PDBBind, significantly outperforming the previous state-of-the-art of traditional docking (23%) and deep learning (20%) methods. Moreover, DiffDock has fast inference times and provides confidence estimates with high selective accuracy.Comment: Under revie

Interaction of a CO molecule with a Pt monatomic wire: electronic structure and ballistic conductance

We carry out a first-principles density functional study of the interaction between a monatomic Pt wire and a CO molecule, comparing the energy of different adsorption configurations (bridge, on top, substitutional, and tilted bridge) and discussing the effects of spin-orbit (SO) coupling on the electronic structure and on the ballistic conductance of two of these systems (bridge and substitutional). We find that, when the wire is unstrained, the bridge configuration is energetically favored, while the substitutional geometry becomes possible only after the breaking of the Pt-Pt bond next to CO. The interaction can be described by a donation/back-donation process similar to that occurring when CO adsorbs on transition-metal surfaces, a picture which remains valid also in presence of SO coupling. The ballistic conductance of the (tipless) nanowire is not much reduced by the adsorption of the molecule on the bridge and on-top sites, but shows a significant drop in the substitutional case. The differences in the electronic structure due to the SO coupling influence the transmission only at energies far away from the Fermi level so that fully- and scalar-relativistic conductances do not differ significantly.Comment: 12 pages, 12 figures; figure misplacement and minor syntax issues fixed, some references updated and correcte

EigenFold: Generative Protein Structure Prediction with Diffusion Models

Protein structure prediction has reached revolutionary levels of accuracy on single structures, yet distributional modeling paradigms are needed to capture the conformational ensembles and flexibility that underlie biological function. Towards this goal, we develop EigenFold, a diffusion generative modeling framework for sampling a distribution of structures from a given protein sequence. We define a diffusion process that models the structure as a system of harmonic oscillators and which naturally induces a cascading-resolution generative process along the eigenmodes of the system. On recent CAMEO targets, EigenFold achieves a median TMScore of 0.84, while providing a more comprehensive picture of model uncertainty via the ensemble of sampled structures relative to existing methods. We then assess EigenFold's ability to model and predict conformational heterogeneity for fold-switching proteins and ligand-induced conformational change. Code is available at https://github.com/bjing2016/EigenFold.Comment: ICLR MLDD workshop 202