Identifying the Atomic-Level Effects of Metal Composition on the Structure and Catalytic Activity of Peptide-Templated Materials

Biomimetic Control over Bimetallic Nanoparticle Structure and Activity via Peptide Capping Ligand Sequence

The controlled design of bimetallic nanoparticles (BNPs) is a key goal in tailoring their catalytic properties. Recently, biomimetic pathways demonstrated potent control over the distribution of different metals within BNPs, but a direct understanding of the peptide effect on the compositional distribution at the interparticle and intraparticle levels remains lacking. We synthesized two sets of PtAu systems with two peptides and correlated their structure, composition, and distributions with the catalytic activity. Structural and compositional analyses were performed by a combined machine learning-assisted refinement of X-ray absorption spectra and Z-contrast measurements by scanning transmission electron microscopy. The difference in the catalytic activities between nanoparticles synthesized with different peptides was attributed to the details of interparticle distribution of Pt and Au across these markedly heterogeneous systems, comprising Pt-rich, Au-rich, and Au core/Pt shell nanoparticles. The total amount of Pt in the shells of the BNPs was proposed to be the key catalytic activity descriptor. This approach can be extended to other systems of metals and peptides to facilitate the targeted design of catalysts with the desired activity.

Pd sub-nanolayer on Au core for enhanced catalytic hydrogenation reduction of oxyanions pollutants: Synergistic effect of Pd and Au

Oxyanion pollutants in industrial wasterwater, such as (Cr(VI)), BrO3- (Br(V)) and SeO32- (Se(IV)) have detrimental or toxic effects on individual health when their concentrations accumulated to a certain level. The conversion of these oxyanions into harmless/industrial-valuable products or removal from wastewater is of significance. Herein, we designed Pd sub-nanolayer on Au core catalysts supported on Al2O3 (sub-Pd-Au/Al2O3) for highly effective catalytic hydrogenation reduction of oxyanions under ambient conditions. The sub-Pd(0.049)-Au(0.927)/Al2O3 catalyst exhibited the highest catalytic activity and TOF value for Cr(VI), Br(V) and Se(IV) reduction, respectively, by optimizing the Pd loading amount. The synergistic effect between Pd sub-nanolayer and Au core enhanced catalytic activity by regulating the Pd dispersion and site property, according to thorough characterizations that included high-angle annular dark-field transmission electron microscopy (HAADF-TEM) image, in-situ CO-IR adsorption, CO chemisorption, and X-ray photoelectron spectroscopy (XPS). This work might provide some new lights on design of highly efficient catalysts for the elimination of oxyanion pollutants.

Biomimetic mineralization based on self-assembling peptides

Biomimetic science has attracted great interest in the fields of chemistry, biology, materials science, and energy. Biomimetic mineralization is the process of synthesizing inorganic minerals under the control of organic molecules or biomolecules under mild conditions. Peptides are the motifs that constitute proteins, and can self-assemble into various hierarchical structures and show a high affinity for inorganic substances. Therefore, peptides can be used as building blocks for the synthesis of functional biomimetic materials. With the participation of peptides, the morphology, size, and composition of mineralized materials can be controlled precisely. Peptides not only provide well-defined templates for the nucleation and growth of inorganic nanomaterials but also have the potential to confer inorganic nanomaterials with high catalytic efficiency, selectivity, and biotherapeutic functions. In this review, we systematically summarize research progress in the formation mechanism, nanostructural manipulation, and applications of peptide-templated mineralized materials. These can further inspire researchers to design structurally complex and functionalized biomimetic materials with great promising applications.

Reconciling structure prediction of alloyed, ultrathin nanowires with spectroscopy

A number of complementary, synergistic advances are reported herein. First, we describe the 'first-time' synthesis of ultrathin Ru2Co1 nanowires (NWs) possessing average diameters of 2.3 ± 0.5 nm using a modified surfactant-mediated protocol. Second, we utilize a combination of quantitative EDS, EDS mapping (along with accompanying line-scan profiles), and EXAFS spectroscopy results to probe the local atomic structure of not only novel Ru2Co1 NWs but also 'control' samples of analogous ultrathin Ru1Pt1, Au1Ag1, Pd1Pt1, and Pd1Pt9 NWs. We demonstrate that ultrathin NWs possess an atomic-level geometry that is fundamentally dependent upon their intrinsic chemical composition. In the case of the PdPt NW series, EDS mapping data are consistent with the formation of a homogeneous alloy, a finding further corroborated by EXAFS analysis. By contrast, EXAFS analysis results for both Ru1Pt1 and Ru2Co1 imply the generation of homophilic structures in which there is a strong tendency for the clustering of 'like' atoms; associated EDS results for Ru1Pt1 convey the same conclusion, namely the production of a heterogeneous structure. Conversely, EDS mapping data for Ru2Co1 suggests a uniform distribution of both elements. In the singular case of Au1Ag1, EDS mapping results are suggestive of a homogeneous alloy, whereas EXAFS analysis pointed to Ag segregation at the surface and an Au-rich core, within the context of a core-shell structure. These cumulative outcomes indicate that only a combined consideration of both EDS and EXAFS results can provide for an accurate representation of the local atomic structure of ultrathin NW motifs.

Remote controlled optical manipulation of bimetallic nanoparticle catalysts using peptides

Remote optical manipulation of peptide ligands on bimetallic nanoparticle surfaces allows for tunable catalytic reactivity.

Peptide-directed Pd-decorated Au and PdAu nanocatalysts for degradation of nitrite in water

In this work, a palladium binding peptide, Pd4, has been used for the synthesis of catalytically active palladium-decorated gold (Pd-on-Au) nanoparticles (NPs) and palladium–gold (Pd_xAu_100−x) alloy NPs exhibiting high nitrite degradation efficiency. Pd-on-Au NPs with 20% to 300% surface coverage (sc%) of Au showed catalytic activity commensurate with sc%. Additionally, the catalytic activity of Pd_xAu_100−x alloy NPs varied based on palladium composition (x = 6–59). The maximum nitrite removal efficiency of Pd-on-Au and Pd_xAu_100−x alloy NPs was obtained at sc 100% and x = 59, respectively. The synthesized peptide-directed Pd-on-Au catalysts showed an increase in nitrite reduction three and a half times better than monometallic Pd and two and a half times better than Pd_xAu_100−x NPs under comparable conditions. Furthermore, peptide-directed NPs showed high activity after five reuse cycles. Pd-on-Au NPs with more available activated palladium atoms showed high selectivity (98%) toward nitrogen gas production over ammonia.

In this work, a palladium binding peptide, Pd4, has been used for the synthesis of catalytically active palladium-decorated gold (Pd-on-Au) nanoparticles (NPs) and palladium–gold (Pd_xAu_100−x) alloy NPs exhibiting high nitrite degradation efficiency.

Neural network assisted analysis of bimetallic nanocatalysts using X-ray absorption near edge structure spectroscopy

Trained neural networks are used to extract the first partial coordination numbers from XANES spectra. In bimetallic nanoparticles, the four local structure descriptors provide rich information on structural motifs.

Reverse Monte Carlo modeling for local structures of noble metal nanoparticles using high-energy XRD and EXAFS

Reverse Monte Carlo (RMC) modeling based on the total structure factor S(Q) obtained from high-energy X-ray diffraction (HEXRD) and the k 3 χ(k) obtained from extended X-ray absorption fine structure (EXAFS) measurements was employed to determine the 3-dimensional (3D) atomic-scale structure of Pt, Pd, and Rh nanoparticles, with sizes less than 5 nm, synthesized by photoreduction. The total structure factor and Fourier-transformed PDF showed that the first nearest neighbor peak is in accordance with that obtained from conventional EXAFS analysis. RMC constructed 3D models were analyzed in terms of prime structural characteristics such as metal-to-metal bond lengths, first-shell coordination numbers and bond angle distributions. The first-shell coordination numbers and bond angle distributions for the RMC-simulated metal nanoparticles indicated a face-centered cubic (fcc) structure with appropriate number density. Modeling disorder effects in these RMC-simulated metal nanoparticles also revealed substantial differences in bond-length distributions for respective nanoparticles.

Solving the Structure and Dynamics of Metal Nanoparticles by Combining X-Ray Absorption Fine Structure Spectroscopy and Atomistic Structure Simulations

Extended X-ray absorption fine structure (EXAFS) spectroscopy is a premiere method for analysis of the structure and structural transformation of nanoparticles. Extraction of analytical information about the three-dimensional structure and dynamics of metal-metal bonds from EXAFS spectra requires special care due to their markedly non-bulk-like character. In recent decades, significant progress has been made in the first-principles modeling of structure and properties of nanoparticles. In this review, we summarize new approaches for EXAFS data analysis that incorporate particle structure modeling into the process of structural refinement.

Probing Atomic Distributions in Mono- and Bimetallic Nanoparticles by Supervised Machine Learning

Properties of mono- and bimetallic metal nanoparticles (NPs) may depend strongly on their compositional, structural (or geometrical) attributes, and their atomic dynamics, all of which can be efficiently described by a partial radial distribution function (PRDF) of metal atoms. For NPs that are several nanometers in size, finite size effects may play a role in determining crystalline order, interatomic distances, and particle shape. Bimetallic NPs may also have different compositional distributions than bulk materials. These factors all render the determination of PRDFs challenging. Here extended X-ray absorption fine structure (EXAFS) spectroscopy, molecular dynamics simulations, and supervised machine learning (artificial neural-network) method are combined to extract PRDFs directly from experimental data. By applying this method to several systems of Pt and PdAu NPs, we demonstrate the finite size effects on the nearest neighbor distributions, bond dynamics, and alloying motifs in mono- and bimetallic particles and establish the generality of this approach.

Effects of Metal Composition and Ratio on Peptide-Templated Multimetallic PdPt Nanomaterials

It can be difficult to simultaneously control the size, composition, and morphology of metal nanomaterials under benign aqueous conditions. For this, bioinspired approaches have become increasingly popular due to their ability to stabilize a wide array of metal catalysts under ambient conditions. In this regard, we used the R5 peptide as a three-dimensional template for formation of PdPt bimetallic nanomaterials. Monometallic Pd and Pt nanomaterials have been shown to be highly reactive toward a variety of catalytic processes, but by forming bimetallic species, increased catalytic activity may be realized. The optimal metal-to-metal ratio was determined by varying the Pd:Pt ratio to obtain the largest increase in catalytic activity. To better understand the morphology and the local atomic structure of the materials, the bimetallic PdPt nanomaterials were extensively studied by transmission electron microscopy, extended X-ray absorption fine structure spectroscopy, X-ray photoelectron spectroscopy, and pair distribution function analysis. The resulting PdPt materials were determined to form multicomponent nanostructures where the Pt component demonstrated varying degrees of oxidation based upon the Pd:Pt ratio. To test the catalytic reactivity of the materials, olefin hydrogenation was conducted, which indicated a slight catalytic enhancement for the multicomponent materials. These results suggest a strong correlation between the metal ratio and the stabilizing biotemplate in controlling the final materials morphology, composition, and the interactions between the two metal species.

Peptide-Directed PdAu Nanoscale Surface Segregation: Toward Controlled Bimetallic Architecture for Catalytic Materials

Bimetallic nanoparticles are of immense scientific and technological interest given the synergistic properties observed when two different metallic species are mixed at the nanoscale. This is particularly prevalent in catalysis, where bimetallic nanoparticles often exhibit improved catalytic activity and durability over their monometallic counterparts. Yet despite intense research efforts, little is understood regarding how to optimize bimetallic surface composition and structure synthetically using rational design principles. Recently, it has been demonstrated that peptide-enabled routes for nanoparticle synthesis result in materials with sequence-dependent catalytic properties, providing an opportunity for rational design through sequence manipulation. In this study, bimetallic PdAu nanoparticles are synthesized with a small set of peptides containing known Pd and Au binding motifs. The resulting nanoparticles were extensively characterized using high-resolution scanning transmission electron microscopy, X-ray absorption spectroscopy, and high-energy X-ray diffraction coupled to atomic pair distribution function analysis. Structural information obtained from synchrotron radiation methods was then used to generate model nanoparticle configurations using reverse Monte Carlo simulations, which illustrate sequence dependence in both surface structure and surface composition. Replica exchange with solute tempering molecular dynamics simulations were also used to predict the modes of peptide binding on monometallic surfaces, indicating that different sequences bind to the metal interfaces via different mechanisms. As a testbed reaction, electrocatalytic methanol oxidation experiments were performed, wherein differences in catalytic activity are clearly observed in materials with identical bimetallic composition. Taken together, this study indicates that peptides could be used to arrive at bimetallic surfaces with enhanced catalytic properties, which could be leveraged for rational bimetallic nanoparticle design using peptide-enabled approaches.

Peptide Binding for Bio-Based Nanomaterials

Peptide-based strategies represent transformative approaches to fabricate functional inorganic materials under sustainable conditions by modeling the methods exploited in biology. In general, peptides with inorganic affinity and specificity have been isolated from organisms and through biocombinatorial selection techniques (ie, phage and cell surface display). These peptides recognize and bind the inorganic surface through a series of noncovalent interactions, driven by both enthalpic and entropic contributions, wherein the biomolecules wrap the metallic nanoparticle structure. Through these interactions, modification of the inorganic surface can be accessed to drive the incorporation of significantly disordered surface metal atoms, which have been found to be highly catalytically active for a variety of chemical transformations. We have employed synthetic, site-directed mutagenesis studies to reveal localized binding effects of the peptide at the metallic nanoparticle structure to begin to identify the biological basis of control over biomimetic nanoparticle catalytic activity. The protocols described herein were used to fabricate and characterize peptide-capped nanoparticles in atomic resolution to identify peptide sequence effects on the surface structure of the materials, which can then be directly correlated to the catalytic activity to identify structure/function relationships.