We investigated molecular interactions involved in the selective binding of several short peptides derived from phage-display techniques (8−12 amino acids, excluding Cys) to surfaces of Au, Pd, and Pd−Au bimetal. The quantitative analysis of changes in energy and conformation upon adsorption on even {111} and {100} surfaces was carried out by molecular dynamics simulation using an efficient computational screening technique, including 1000 explicit water molecules and physically meaningful peptide concentrations at pH = 7. Changes in chain conformation from the solution to the adsorbed state over the course of multiple nanoseconds suggest that the peptides preferably interact with vacant sites of the face-centered cubic lattice above the metal surface. Residues that contribute to binding are in direct contact with the metal surfaces, and less-binding residues are separated from the surface by one or two water layers. The strength of adsorption ranges from 0 to −100 kcal/(mol peptide) and scales with the surface energy of the metal (Pd surfaces are more attractive than Au surfaces), the affinity of individual residues versus the affinity of water, and conformation aspects, as well as polarization and charge transfer at the metal interface (only qualitatively considered here). A hexagonal spacing of ∼1.6 Å between available lattice sites on the {111} surfaces accounts for the characteristic adsorption of aromatic side groups and various other residues (including Tyr, Phe, Asp, His, Arg, Asn, Ser), and a quadratic spacing of ∼2.8 Å between available lattice sites on the {100} surface accounts for a significantly lower affinity to all peptides in favor of mobile water molecules. The combination of these factors suggests a “soft epitaxy” mechanism of binding. On a bimetallic Pd−Au {111} surface, binding patterns are similar, and the polarity of the bimetal junction can modify the binding energy by ∼10 kcal/mol. The results are semiquantitatively supported by experimental measurements of the affinity of peptides and small molecules to metal surfaces as well as results from quantum-mechanical calculations on small peptide and surface fragments. Interfaces were modeled using the consistent valence force field extended for Lennard-Jones parameters for fcc metals which accurately reproduce surface and interface energies [Heinz, H.; Vaia, R. A.; Farmer, B. L.; Naik, R. R. J. Phys. Chem. C 2008, 112, 17281−17290].

Density functional theory (DFT) electronic structure calculations were carried out to predict the structures and ground-state spectra for zinc complexes of porphyrin (ZnP), tetraazaporphyrin (ZnTAP), tetrabenzoporphyrin (ZnTBP), and phthalocyanine (ZnPc). All four porphyrins are found to have stable D4h structures. Structurally, meso-tetraaza substitutions significantly reduce the central hole in ZnTAP and ZnPc compared to ZnP. The excitation energies and oscillator strengths, computed by time-dependent DFT, provide a good account of the observed spectra of all four compounds. The TDDFT spectrum of ZnPc has a number of bands in the Soret region, in agreement with the experimental spectra that have been determined through spectral deconvolution. The low energy n→π* transition (Q′) reported for ZnPc, however, was not found in the computed spectrum. The effects of meso-tetraaza substitutions and tetrabenzo annulations on the spectrum of ZnP are discussed.

The Joint Automated Repository for Various Integrated Simulations (JARVIS) is an integrated infrastructure to accelerate materials discovery and design using density functional theory (DFT), classical force-fields (FF), and machine learning (ML) techniques. JARVIS is motivated by the Materials Genome Initiative (MGI) principles of developing open-access databases and tools to reduce the cost and development time of materials discovery, optimization, and deployment. The major features of JARVIS are: JARVIS-DFT, JARVIS-FF, JARVIS-ML, and JARVIS-tools. To date, JARVIS consists of ≈40,000 materials and ≈1 million calculated properties in JARVIS-DFT, ≈500 materials and ≈110 force-fields in JARVIS-FF, and ≈25 ML models for material-property predictions in JARVIS-ML, all of which are continuously expanding. JARVIS-tools provides scripts and workflows for running and analyzing various simulations. We compare our computational data to experiments or high-fidelity computational methods wherever applicable to evaluate error/uncertainty in predictions. In addition to the existing workflows, the infrastructure can support a wide variety of other technologically important applications as part of the data-driven materials design paradigm. The JARVIS datasets and tools are publicly available at the website: https://jarvis.nist.gov.

Relationships between structures and properties (energy gaps, vertical ionization potentials (IP v ), vertical electron affinities (EA v ), and ligand binding energies) in small capped CdSe/CdTe nanoparticles (NPs) are poorly understood. We have performed the first systematic density functional theory (DFT) (B3LYP/Lanl2dz) study of the structural (geometries and ligand binding energies) and electronic (HOMO/LUMO energy gaps, IPs v , and EAs v ) properties of Cd n Se n /Cd n Te n NPs (n = 6, 9), both bare and capped with NH 3 , SCH 3 , and OPH 3 ligands. NH 3 and OPH 3 ligands cause HOMO/LUMO energy destabilization in capped NPs, more pronounced for the LUMOs than for the HOMOs. Orbital destabilization drastically reduces both the IP v and EA v of the NPs compared with the bare species. For SCH 3 -capped Cd 6 X 6 NPs, formation of expanded structures was found to be preferable to crystal-like structures. SCH 3 groups cause destabilization of the HOMOs of the capped NPs and stabilization of their LUMOs, which indicates a reduction of the IP v of the capped NPs compared with the bare species. For the Cd 9 X 9 NPs, similar trends in stabilization/destabilization of frontier orbitals were observed in comparison with the capped Cd 6 X 6 species. Also, pinning of the HOMO energies was observed for the NH 3 -and SCH 3 -capped NPs as a function of a NP size.