Hadi Ramezani-Dakhel

Tailoring Molecular Specificity Toward a Crystal Facet: a Lesson From Biorecognition Toward Pt{111}

Surfactants with preferential adsorption to certain crystal facets have been widely employed to manipulate morphologies of colloidal nanocrystals, while mechanisms regarding the origin of facet selectivity remain an enigma. Similar questions exist in biomimetic syntheses concerning biomolecular recognition to materials and crystal surfaces. Here we present mechanistic studies on the molecular origin of the recognition toward platinum {111} facet. By manipulating the conformations and chemical compositions of a platinum {111} facet specific peptide, phenylalanine is identified as the dominant motif to differentiate {111} from other facets. The discovered recognition motif is extended to convert nonspecific peptides into {111} specific peptides. Further extension of this mechanism allows the rational design of small organic molecules that demonstrate preferential adsorption to the {111} facets of both platinum and rhodium nanocrystals. This work represents an advance in understanding the organic-inorganic interfacial interactions in colloidal systems and paves the way to rational and predictable nanostructure modulations for many applications.

Exploiting Localized Surface Binding Effects to Enhance the Catalytic Reactivity of Peptide-Capped Nanoparticles

Peptide-based methods represent new approaches to selectively produce nanostructures with potentially important functionality. Unfortunately, biocombinatorial methods can only select peptides with target affinity and not for the properties of the final material. In this work, we present evidence to demonstrate that materials-directing peptides can be controllably modified to substantially enhance particle functionality without significantly altering nanostructural morphology. To this end, modification of selected residues to vary the site-specific binding strength and biological recognition can be employed to increase the catalytic efficiency of peptide-capped Pd nanoparticles. These results represent a step toward the de novo design of materials-directing peptides that control nanoparticle structure/function relationships.

Three-dimensional coordinates of individual atoms in materials revealed by electron tomography

Crystallography, the primary method for determining the 3D atomic positions in crystals, has been fundamental to the development of many fields of science. However, the atomic positions obtained from crystallography represent a global average of many unit cells in a crystal. Here, we report, for the first time, the determination of the 3D coordinates of thousands of individual atoms and a point defect in a material by electron tomography with a precision of ∼19 pm, where the crystallinity of the material is not assumed. From the coordinates of these individual atoms, we measure the atomic displacement field and the full strain tensor with a 3D resolution of ∼1 nm(3) and a precision of ∼10(-3), which are further verified by density functional theory calculations and molecular dynamics simulations. The ability to precisely localize the 3D coordinates of individual atoms in materials without assuming crystallinity is expected to find important applications in materials science, nanoscience, physics, chemistry and biology.

Elucidation of Peptide-Directed Palladium Surface Structure for Biologically Tunable Nanocatalysts

Peptide-enabled synthesis of inorganic nanostructures represents an avenue to access catalytic materials with tunable and optimized properties. This is achieved via peptide complexity and programmability that is missing in traditional ligands for catalytic nanomaterials. Unfortunately, there is limited information available to correlate peptide sequence to particle structure and catalytic activity to date. As such, the application of peptide-enabled nanocatalysts remains limited to trial and error approaches. In this paper, a hybrid experimental and computational approach is introduced to systematically elucidate biomolecule-dependent structure/function relationships for peptide-capped Pd nanocatalysts. Synchrotron X-ray techniques were used to uncover substantial particle surface structural disorder, which was dependent upon the amino acid sequence of the peptide capping ligand. Nanocatalyst configurations were then determined directly from experimental data using reverse Monte Carlo methods and further refined using molecular dynamics simulation, obtaining thermodynamically stable peptide-Pd nanoparticle configurations. Sequence-dependent catalytic property differences for C-C coupling and olefin hydrogenation were then elucidated by identification of the catalytic active sites at the atomic level and quantitative prediction of relative reaction rates. This hybrid methodology provides a clear route to determine peptide-dependent structure/function relationships, enabling the generation of guidelines for catalyst design through rational tailoring of peptide sequences.

Stability, surface features, and atom leaching of palladium nanoparticles: toward prediction of catalytic functionality

Surfactant-stabilized metal nanoparticles have shown promise as catalysts although specific surface features and their influence on catalytic performance have not been well understood. We quantify the thermodynamic stability, the facet composition of the surface, and distinct atom types that affect rates of atom leaching for a series of twenty near-spherical Pd nanoparticles of 1.8 to 3.1 nm size using computational models. Cohesive energies indicate higher stability of certain particles that feature an approximate 60/20/20 ratio of {111}, {100}, and {110} facets while less stable particles exhibit widely variable facet composition. Unique patterns of atom types on the surface cause apparent differences in binding energies and changes in reactivity. Estimates of the relative rate of atom leaching as a function of particle size were obtained by the summation of Boltzmann-weighted binding energies over all surface atoms. Computed leaching rates are in good qualitative correlation with the measured catalytic activity of peptide-stabilized Pd nanoparticles of the same shape and size in Stille coupling reactions. The agreement supports rate-controlling contributions by atom leaching in the presence of reactive substrates. The computational approach provides a pathway to estimate the catalytic activity of metal nanostructures of engineered shape and size, and possible further refinements are described.

A Rational Biomimetic Approach to Structure Defect Generation in Colloidal Nanocrystals

Controlling the morphology of nanocrystals (NCs) is of paramount importance for both fundamental studies and practical applications. The morphology of NCs is determined by the seed structure and the following facet growth. While means for directing facet formation in NC growth have been extensively studied, rational strategies for the production of NCs bearing structure defects in seeds have been much less explored. Here, we report mechanistic investigations of high density twin formation induced by specific peptides in platinum (Pt) NC growth, on the basis of which we derive principles that can serve as guidelines for the rational design of molecular surfactants to introduce high yield twinning in noble metal NC syntheses. Two synergistic factors are identified in producing twinned Pt NCs with the peptide: (1) the altered reduction kinetics and crystal growth pathway as a result of the complex formation between the histidine residue on the peptide and Pt ions, and (2) the preferential stabilization of {111} planes upon the formation of twinned seeds. We further apply the discovered principles to the design of small organic molecules bearing similar binding motifs as ligands/surfactants to create single and multiple twinned Pd and Rh NCs. Our studies demonstrate the rich information derived from biomimetic synthesis and the broad applicability of biomimetic principles to NC synthesis for diverse property tailoring.

SSAGES: Software Suite for Advanced General Ensemble Simulations

Molecular simulation has emerged as an essential tool for modern-day research, but obtaining proper results and making reliable conclusions from simulations requires adequate sampling of the system under consideration. To this end, a variety of methods exist in the literature that can enhance sampling considerably, and increasingly sophisticated, effective algorithms continue to be developed at a rapid pace. Implementation of these techniques, however, can be challenging for experts and non-experts alike. There is a clear need for software that provides rapid, reliable, and easy access to a wide range of advanced sampling methods and that facilitates implementation of new techniques as they emerge. Here we present SSAGES, a publicly available Software Suite for Advanced General Ensemble Simulations designed to interface with multiple widely used molecular dynamics simulations packages. SSAGES allows facile application of a variety of enhanced sampling techniques-including adaptive biasing force, string methods, and forward flux sampling-that extract meaningful free energy and transition path data from all-atom and coarse-grained simulations. A noteworthy feature of SSAGES is a user-friendly framework that facilitates further development and implementation of new methods and collective variables. In this work, the use of SSAGES is illustrated in the context of simple representative applications involving distinct methods and different collective variables that are available in the current release of the suite. The code may be found at: https://github.com/MICCoM/SSAGES-public.

Segregation of liquid crystal mixtures in topological defects

The structure and physical properties of liquid crystal (LC) mixtures are a function of composition, and small changes can have pronounced effects on observables, such as phase-transition temperatures. Traditionally, LC mixtures have been assumed to be compositionally homogenous. The results of chemically detailed simulations presented here show that this is not the case; pronounced deviations of the local order from that observed in the bulk at defects and interfaces lead to significant compositional segregation effects. More specifically, two disclination lines are stabilized in this work by introducing into a nematic liquid crystal mixture a cylindrical body that exhibits perpendicular anchoring. It is found that the local composition deviates considerably from that of the bulk at the interface with the cylinder and in the defects, thereby suggesting new assembly and synthetic strategies that may capitalize on the unusual molecular environment provided by liquid crystal mixtures.

Improving Thermo-mechanical Properties of Styrene Butadiene Rubber Nanocomposites Using Eggshell Bio-filler

In this work, styrene butadiene rubber (SBR) nanocomposites were produced at three (5, 10, 15 phr) different levels of loading by using after hatching eggshells (AHES) as bio-fillers and their thermo-mechanical properties were well compared with those prepared by calcium carbonate (CA) nanofillers. AHES fillers were first surface modified by stearic acid and consequently were used while CA nanofillers were coated by provider. Tensile strength and elongation at break data showed considerable improvement through employing AHES nanofillers. In addition, thermogravimetric analysis onto produced samples showed higher thermal stability of samples which were fed with AHES at 5 phr loading than that of CA nanofillers and similar thermal stability of nanocomposites were obtained when 10 and 15 phr of both kinds of nanofillers were used separately.

Insight into induced charges at metal surfaces and biointerfaces using a polarizable Lennard–Jones potential

Metallic nanostructures have become popular for applications in therapeutics, catalysts, imaging, and gene delivery. Molecular dynamics simulations are gaining influence to predict nanostructure assembly and performance; however, instantaneous polarization effects due to induced charges in the free electron gas are not routinely included. Here we present a simple, compatible, and accurate polarizable potential for gold that consists of a Lennard–Jones potential and a harmonically coupled core-shell charge pair for every metal atom. The model reproduces the classical image potential of adsorbed ions as well as surface, bulk, and aqueous interfacial properties in excellent agreement with experiment. Induced charges affect the adsorption of ions onto gold surfaces in the gas phase at a strength similar to chemical bonds while ions and charged peptides in solution are influenced at a strength similar to intermolecular bonds. The proposed model can be applied to complex gold interfaces, electrode processes, and extended to other metals.Molecular dynamics models for predicting the behavior of metallic nanostructures typically do not take into account polarization effects in metals. Here, the authors introduce a polarizable Lennard–Jones potential that provides quantitative insight into the role of induced charges at metal surfaces and related complex material interfaces.