Elucidation of peptide-directed palladium surface structure for biologically tunable nanocatalysts

Implementing reactivity in molecular dynamics simulations with harmonic force fields

The simulation of chemical reactions and mechanical properties including failure from atoms to the micrometer scale remains a longstanding challenge in chemistry and materials science. Bottlenecks include computational feasibility, reliability, and cost. We introduce a method for reactive molecular dynamics simulations using a clean replacement of non-reactive classical harmonic bond potentials with reactive, energy-conserving Morse potentials, called the Reactive INTERFACE Force Field (IFF-R). IFF-R is compatible with force fields for organic and inorganic compounds such as IFF, CHARMM, PCFF, OPLS-AA, and AMBER. Bond dissociation is enabled by three interpretable Morse parameters per bond type and zero energy upon disconnect. Use cases for bond breaking in molecules, failure of polymers, carbon nanostructures, proteins, composite materials, and metals are shown. The simulation of bond forming reactions is included via template-based methods. IFF-R maintains the accuracy of the corresponding non-reactive force fields and is about 30 times faster than prior reactive simulation methods.

Resolving Atomic-Scale Structure and Chemical Coordination in High-Entropy Alloy Electrocatalysts for Structure-Function Relationship Elucidation

The recent breakthrough in confining five or more atomic species in nanocatalysts, referred to as high-entropy alloy nanocatalysts (HEAs), has revealed the possibilities of multielemental interactions that can surpass the limitations of binary and ternary electrocatalysts. The wide range of potential surface configurations in HEAs, however, presents a significant challenge in resolving active structural motifs, preventing the establishment of structure-function relationships for rational catalyst design and optimization. We present a methodology for creating sub-5 nm HEAs using an aqueous-based peptide-directed route. Using a combination of pair distribution function and X-ray absorption spectroscopy, HEA structure models are constructed from reverse Monte Carlo modeling of experimental data sets and showcase a clear peptide-induced influence on atomic-structure and chemical miscibility. Coordination analysis of our structure models facilitated the construction of structure-function correlations applied to electrochemical methanol oxidation reactions, revealing the complex interplay between multiple metals that leads to improved catalytic properties. Our results showcase a viable strategy for elucidating structure-function relationships in HEAs, prospectively providing a pathway for future materials design.

Accurate Force Fields for Atomistic Simulations of Oxides, Hydroxides, and Organic Hybrid Materials up to the Micrometer Scale

The simulation of metals, oxides, and hydroxides can accelerate the design of therapeutics, alloys, catalysts, cement-based materials, ceramics, bioinspired composites, and glasses. Here we introduce the INTERFACE force field (IFF) and surface models for α-Al2O3, α-Cr2O3, α-Fe2O3, NiO, CaO, MgO, β-Ca(OH)2, β-Mg(OH)2, and β-Ni(OH)2. The force field parameters are nonbonded, including atomic charges for Coulomb interactions, Lennard-Jones (LJ) potentials for van der Waals interactions with 12-6 and 9-6 options, and harmonic bond stretching for hydroxide ions. The models outperform DFT calculations and earlier atomistic models (Pedone, ReaxFF, UFF, CLAYFF) up to 2 orders of magnitude in reliability, compatibility, and interpretability due to a quantitative representation of chemical bonding consistent with other compounds across the periodic table and curated experimental data for validation. The IFF models exhibit average deviations of 0.2% in lattice parameters, <10% in surface energies (to the extent known), and 6% in bulk moduli relative to experiments. The parameters and models can be used with existing parameters for solvents, inorganic compounds, organic compounds, biomolecules, and polymers in IFF, CHARMM, CVFF, AMBER, OPLS-AA, PCFF, and COMPASS, to simulate bulk oxides, hydroxides, electrolyte interfaces, and multiphase, biological, and organic hybrid materials at length scales from atoms to micrometers. The nonbonded character of the models also enables the analysis of mixed oxides, glasses, and certain chemical reactions, and well-performing nonbonded models for silica phases, SiO2, are introduced. Automated model building is available in the CHARMM-GUI Nanomaterial Modeler. We illustrate applications of the models to predict the structure of mixed oxides, and energy barriers of ion migration, as well as binding energies of water and organic molecules in outstanding agreement with experimental data and calculations at the CCSD(T) level. Examples of model building for hydrated, pH-sensitive oxide surfaces to simulate solid-electrolyte interfaces are discussed.

Developing a rational approach to designing recombinant proteins for peptide-directed nanoparticle synthesis

The controlled formation of nanoparticles with optimum characteristics and functional aspects has proven successful via peptide-mediated nanoparticle synthesis. However, the effects of the peptide sequence and binding motif on surface features and physicochemical properties of nanoparticles are not well-understood. In this study, we investigate in a comparative manner how a specific peptide known as Pd4 and its two known variants may form nanoparticles both in an isolated state and when attached to a green fluorescent protein (GFPuv). More importantly, we introduce a novel computational approach to predict the trend of the size and activity of the peptide-directed nanoparticles by estimating the binding affinity of the peptide to a single ion. We used molecular dynamics (MD) simulations to explore the differential behavior of the isolated and GFP-fused peptides and their mutants. Our computed palladium (Pd) binding free energies match the typical nanoparticle sizes reported from transmission electron microscope pictures. Stille coupling and Suzuki-Miyaura reaction turnover frequencies (TOFs) also correspond with computationally predicted Pd binding affinities. The results show that while using Pd4 and its two known variants (A6 and A11) in isolation produces nanoparticles of varying sizes, fusing these peptides to the GFPuv protein produces nanoparticles of similar sizes and activity. In other words, GFPuv reduces the sensitivity of the nanoparticles to the peptide sequence. This study provides a computational framework for designing free and protein-attached peptides that helps in the synthesis of nanoparticles with well-regulated properties.

Bio-Templating: An Emerging Synthetic Technique for Catalysts. A Review

In the last few years, researchers have focused their attention on the synthesis of new catalyst structures based on or inspired by nature. Biotemplating involves the transfer of biological structures to inorganic materials through artificial mineralization processes. This approach offers the main advantage of allowing morphological control of the product, as a template with the desired morphology can be pre-determined, as long as it is found in nature. This way, natural evolution through millions of years can provide us with new synthetic pathways to develop some novel functional materials with advantageous properties, such as sophistication, miniaturization, hybridization, hierarchical organization, resistance, and adaptability to the required need. The field of application of these materials is very wide, covering nanomedicine, energy capture and storage, sensors, biocompatible materials, adsorbents, and catalysis. In the latter case, bio-inspired materials can be applied as catalysts requiring different types of active sites (i.e., redox, acidic, basic sites, or a combination of them) to a wide range of processes, including conventional thermal catalysis, photocatalysis, or electrocatalysis, among others. This review aims to cover current experimental studies in the field of biotemplating materials synthesis and their characterization, focusing on their application in heterogeneous catalysis.

Direct correlation of oxygen adsorption on platinum-electrolyte interfaces with the activity in the oxygen reduction reaction

The oxygen reduction reaction (ORR) on platinum catalysts is essential in fuel cells. Quantitative predictions of the relative ORR activity in experiments, in the range of 1 to 50 times, have remained challenging because of incomplete mechanistic understanding and lack of computational tools to account for the associated small differences in activation energies (<2.3 kilocalories per mole). Using highly accurate molecular dynamics (MD) simulation with the Interface force field (0.1 kilocalories per mole), we elucidated the mechanism of adsorption of molecular oxygen on regular and irregular platinum surfaces and nanostructures, followed by local density functional theory (DFT) calculations. The relative ORR activity is determined by oxygen access to platinum surfaces, which greatly depends on specific water adlayers, while electron transfer occurs at a similar slow rate. The MD methods facilitate quantitative predictions of relative ORR activities of any platinum nanostructures, are applicable to other catalysts, and enable effective MD/DFT approaches.

Recent Advances in Bio-Templated Metallic Nanomaterial Synthesis and Electrocatalytic Applications

Developing metallic nanocatalysts with high reaction activity, selectivity and practical durability is a promising and active subfield in electrocatalysis. In the classical "bottom-up" approach to synthesize stable nanomaterials by chemical reduction, stabilizing additives such as polymers or organic surfactants must be present to cap the nanoparticle to prevent material bulk aggregation. In recent years, biological systems have emerged as green alternatives to support the uncoated inorganic components. One key advantage of biological templates is their inherent ability to produce nanostructures with controllable composition, facet, size and morphology under ecologically friendly synthetic conditions, which are difficult to achieve with traditional inorganic synthesis. In addition, through genetic engineering or bioconjugation, bio-templates can provide numerous possibilities for surface functionalization to incorporate specific binding sites for the target metals. Therefore, in bio-templated systems, the electrocatalytic performance of the formed nanocatalyst can be tuned by precisely controlling the material surface chemistry. With controlled improvements in size, morphology, facet exposure, surface area and electron conductivity, bio-inspired nanomaterials often exhibit enhanced catalytic activity towards electrode reactions. In this Review, recent research developments are presented in bio-approaches for metallic nanomaterial synthesis and their applications in electrocatalysis for sustainable energy storage and conversion systems.

Valence Alignment of Mixed Ni-Fe Hydroxide Electrocatalysts through Preferential Templating on Graphene Edges for Enhanced Oxygen Evolution

Engineering the metal-carbon heterointerface has become an increasingly important route toward achieving cost-effective and high-performing electrocatalysts. The specific properties of graphene edge sites, such as the high available density of states and extended unpaired π-bonding, make it a promising candidate to tune the electronic properties of metal catalysts. However, to date, understanding and leveraging graphene edge-metal catalysts for improved electrocatalytic performance remains largely elusive. Herein, edge-rich vertical graphene (er-VG) was synthesized and used as a catalyst support for Ni-Fe hydroxides for the oxygen evolution reaction (OER). The hybrid Ni-Fe/er-VG catalyst exhibits excellent OER performance with a mass current of 4051 A g^-1 (at overpotential η = 300 mV) and turnover frequency (TOF) of 4.8 s^-1 (η = 400 mV), outperforming Ni-Fe deposited on pristine VG and other metal foam supports. Angle-dependent X-ray absorption spectroscopy shows that the edge-rich VG support can preferentially template Fe-O units with a specific valence orbital alignment interacting with the unoccupied density of states on the graphene edges. This graphene edge-metal interaction was shown to facilitate the formation of undersaturated and strained Fe-sites with high valence states, while promoting the formation of redox-activated Ni species, thus improving OER performance. These findings demonstrate rational design of the graphene edge-metal interface in electrocatalysts which can be used for various energy conversion and chemical synthesis reactions.

Enhanced Hyperbox Classifier Model for Nanomaterial Discovery

Machine learning tools can be applied to peptide-mediated biomineralization, which is an emerging biomimetic technique of creating functional nanomaterials. In particular, they can be used for the discovery of biomineralization peptides, which currently relies on combinatorial enumeration approaches. In this work, an enhanced hyperbox classifier is developed which can predict if a given peptide sequence has a strong or weak binding affinity towards a gold surface. A mixed-integer linear program is formulated to generate the rule-based classification model. The classifier is optimized to account for false positives and false negatives, and clearly articulates how the classification decision is made. This feature makes the decision-making process transparent, and the results easy to interpret for decision support. The method developed can help accelerate the discovery of more biomineralization peptide sequences, which may expand the utility of peptide-mediated biomineralization as a means for nanomaterial synthesis.

Probing the Atomic-Scale Structure of Amorphous Aluminum Oxide Grown by Atomic Layer Deposition

Atomic layer deposition (ALD) is a well-established technique for depositing nanoscale coatings with pristine control of film thickness and composition. The trimethylaluminum (TMA) and water (H₂O) ALD chemistry is inarguably the most widely used and yet to date, we have little information about the atomic-scale structure of the amorphous aluminum oxide (AlO_x) formed by this chemistry. This lack of understanding hinders our ability to establish process-structure-property relationships and ultimately limits technological advancements employing AlO_x made via ALD. In this work, we employ synchrotron high-energy X-ray diffraction (HE-XRD) coupled with pair distribution function (PDF) analysis to characterize the atomic structure of amorphous AlO_x ALD coatings. We combine ex situ and in operando HE-XRD measurements on ALD AlO_x and fit these experimental data using stochastic structural modeling to reveal variations in the Al-O bond length, Al and O coordination environment, and extent of Al vacancies as a function of growth conditions. In particular, the local atomic structure of ALD AlO_x is found to change with the substrate and number of ALD cycles. The observed trends are consistent with the formation of bulk Al₂O₃ surrounded by an O-rich surface layer. We deconvolute these data to reveal atomic-scale structural information for both the bulk and surface phases. Overall, this work demonstrates the usefulness of HE-XRD and PDF analysis in improving our understanding of the structure of amorphous ALD thin films and provides a pathway to evaluate how process changes impact the structure and properties of ALD films.

Probing Dopant Locations in Silicon Nanocrystals via High Energy X-ray Diffraction and Reverse Monte Carlo Simulation

Understanding the locations of dopant atoms in ensembles of nanocrystals is crucial to controlling the dopants' function. While electron microscopy and atom probe tomography methods allow investigation of dopant location for small numbers of nanocrystals, assessing large ensembles has remained a challenge. Here, we are using high energy X-ray diffraction (HE-XRD) and structure reconstruction via reverse Monte Carlo simulation to characterize nanocrystal structure and dopant locations in ensembles of highly boron and phosphorus doped silicon nanocrystals (Si NCs). These plasma-synthesized NCs are a particularly intriguing test system for such an investigation, as elemental analysis suggests that Si NCs can be "hyperdoped" beyond the thermodynamic solubility limit in bulk silicon. Yet, free carrier densities derived from local surface plasmon resonances suggest that only a fraction of dopants are active. We demonstrate that the structural characteristics garnered from HE-XRD and structure reconstruction elucidate dopant location and doping efficacy for doped Si NCs from an atomic-scale perspective.

Recombinant peptide fusion construction for protein-templated catalytic palladium nanoparticles

Although peptide-enabled synthesis of nanostructures has garnered considerable interest for use in catalytic applications, it has so far been achieved mostly via Fmoc based solid phase peptide synthesis. Consequently, the potential of longer peptides in nanoparticle synthesis have not been explored largely due to the complexities and economic constraints of this chemical synthesis route. This study examines the potential of a 45-amino acid long peptide expressed as fusion to green fluorescence protein (GFPuv) in Escherichia coli for use in palladium nanoparticle synthesis. Fed-batch fermentation with E. coli harboring an arabinose-inducible plasmid produced a product containing three copies of Pd4 peptide fused to N-terminus of GFPuv ((Pd4)₃ -GFPuv). Using the intrinsic fluorescence of GFPuv, expression and enrichment of the fusion product was easily monitored. Crude lysate, desalted lysate, and an ion-exchange enriched fraction containing (Pd4)₃ -GFPuv were used to test the hypothesis that high purity of the biologic material used as the nanoparticle synthesis template may not be necessary. Nanoparticles were characterized using a variety of material science techniques and used to catalyze a model Suzuki-Miyaura coupling reaction. Results demonstrated that palladium nanoparticles can be synthesized using the soluble cell extract containing (Pd4)₃ -GFPuv without extensive purification or cleavage steps, and as a catalyst the crude mixture is functional.

Chiral Restructuring of Peptide Enantiomers on Gold Nanomaterials

The use of biomolecules has been invaluable at generating and controlling optical chirality in nanomaterials; however, the structure and properties of the chiral biotemplate are not well understood due to the complexity of peptide-nanoparticle interactions. In this study, we show that the complex interactions between d-peptides and gold nanomaterials led to a chiral restructuring of peptides as demonstrated by circular dichroism and proteolytic cleavage of d-peptides via gold-mediated inversion of peptide chirality. The gold nanoparticles synthesized using d-peptide produce a highly ordered atomic surface and restructured peptide bonds for enzyme cleavage. Differences in gold nanoparticle catalyzed reduction of 4-nitrophenol were observed on the basis of the chiral peptide used in nanoparticle synthesis. Notably, the proteolytic cleavage of d-peptides on gold provides an opportunity for designing nanoparticle based therapeutics to treat peptide venoms, access new chemistries, or modulate the catalytic activity of nanomaterials.

Dynamics of carbohydrate strands in water and interactions with clay minerals: influence of pH, surface chemistry, and electrolytes

Carbohydrate hydrogels are extensively used in pharmaceuticals and engineered biomaterials. Molecular conformations, assembly, and interactions of the carbohydrate strands with stabilizers such as clay minerals in aqueous solution are difficult to quantify in experiments and the hydrogel properties remain largely a result of trial-and-error studies. We analyzed the assembly of gellan gum in aqueous solution and interactions with dispersed clay minerals in all-atomic detail using molecular dynamics simulation, atomic force microscopy (AFM), and comparisons to earlier measurements. Gellan strands associate at low pH values of 2 and gradually disassemble to double strands with weak association of -0.4 kcal per mole carbohydrate ring as the pH values increases to 9. Ionization of the carbonic acid side groups in the backbone extends the chains and accelerates the conformational dynamics via rapidly changing intramolecular ion bridges. Gellan interactions with clay minerals depend on the strength of electric triple layers between clay, cations, and anionic polymer strands, as well as weaker hydrogen bonds along the edges, which are tunable as a function of the clay surface chemistry, local ionic strength, and pH values. Interaction energies range from -4 to +6 kcal per mol carbohydrate ring and were most favorable for electric triple layers with high charge mobility, which can be achieved for intermediate cation exchange capacity of the clay mineral and high pH values to increase ionization of the clay edges and of the polymer. The findings provide understanding and help control the dynamics and stabilization of carbohydrate hydrogels by clay minerals.

Modeling the Cooperative Adsorption of Solid-Binding Proteins on Silica: Molecular Insights from Surface Plasmon Resonance Measurements

Combinatorially selected solid-binding peptides (SBPs) provide a versatile route for synthesizing advanced materials and devices, especially when they are installed within structurally or functionally useful protein scaffolds. However, their promise has not been fully realized because we lack a predictive understanding of SBP-material interactions. Thermodynamic and kinetic binding parameters obtained by fitting quartz crystal microbalance and surface plasmon resonance (SPR) data with the Langmuir model whose assumptions are rarely satisfied provide limited information on underpinning molecular interactions. Using SPR, we show here that a technologically useful SBP called Car9 confers proteins to which is fused a sigmoidal adsorption behavior modulated by partner identity, quaternary structure, and ionic strength. We develop a two-step cooperative model that accurately captures the kinetics of silica binding and provides insights into how SBP-SBP interactions, fused scaffold, and solution conditions modulate adsorption. Because cooperative binding can be converted to Langmuir adhesion by mutagenesis, our approach offers a path to identify and to better understand and design practically useful SBPs.

Reaction mechanisms at the homogeneous–heterogeneous frontier: insights from first-principles studies on ligand-decorated metal nanoparticles

The frontiers between homogeneous and heterogeneous catalysis are progressively disappearing.

Adsorption Mechanisms of Nucleobases on the Hydrated Au(111) Surface

The solution environment is of fundamental importance in the adsorption of molecules on surfaces, a process that is strongly affected by the capability of the adsorbate to disrupt the hydration layer above the surface. Here we disclose how the presence of interface water influences the adsorption mechanism of DNA nucleobases on a gold surface. By means of metadynamics simulations, we describe the distinctive features of a complex free-energy landscape for each base, which manifests activation barriers for the adsorption process. We characterize the different pathways that allow each nucleobase to overcome the barriers and be adsorbed on the surface, discussing how they influence the kinetics of adsorption of single-stranded DNA oligomers with homogeneous sequences. Our findings offer a rationale as to why experimental data on the adsorption of single-stranded homo-oligonucleotides do not straightforwardly follow the thermodynamics affinity rank.

Sequence-Specific Control of Inorganic Nanomaterials Morphologies by Biomolecules

Controlling morphologies of nanomaterials such as their shapes and surface features has been a major endeavor in the field of nanoscale science and engineering, because the morphology is a major determining factor for functional properties of nanomaterials. Compared with conventional capping ligands based on organic molecules or polymers, the programmability of biomolecules makes them attractive alternatives for morphology-controlled nanomaterials synthesis. Towards the goal of predictable control of the synthesis, many studies have been performed on using different sequences of biomolecules to generate specific nanomaterial morphology. In this review, we summarize recent studies in the past few years on using DNA and peptide sequences to control inorganic nanomaterial morphologies, focusing on both case studies and mechanistic investigations. The functional properties resulting from such a sequence-specific control are also discussed, along with strengths and limitations of different approaches to achieving the goal.

Interactions between Metal Oxides and Biomolecules: from Fundamental Understanding to Applications

Metallo-oxide (MO)-based bioinorganic nanocomposites promise unique structures, physicochemical properties, and novel biochemical functionalities, and within the past decade, investment in research on materials such as ZnO, TiO₂, SiO₂, and GeO₂ has significantly increased. Besides traditional approaches, the synthesis, shaping, structural patterning, and postprocessing chemical functionalization of the materials surface is inspired by strategies which mimic processes in nature. Would such materials deliver new technologies? Answering this question requires the merging of historical knowledge and current research from different fields of science. Practically, we need an effective defragmentation of the research area. From our perspective, the superficial accounting of material properties, chemistry of the surfaces, and the behavior of biomolecules next to such surfaces is a problem. This is particularly of concern when we wish to bridge between technologies in vitro and biotechnologies in vivo. Further, besides the potential practical technological efficiency and advantages such materials might exhibit, we have to consider the wider long-term implications of material stability and toxicity. In this contribution, we present a critical review of recent advances in the chemistry and engineering of MO-based biocomposites, highlighting the role of interactions at the interface and the techniques by which these can be studied. At the end of the article, we outline the challenges which hamper progress in research and extrapolate to developing and promising directions including additive manufacturing and synthetic biology that could benefit from molecular level understanding of interactions occurring between inanimate (abiotic) and living (biotic) materials.

Prediction of Hydrophobic Reagent for Flotation Process Using Molecular Modeling

The interaction or nonbonded energies of base organic ions and water molecules during the flotation process of minerals have important meanings for organizing hydrophobic and stable collectors. Furthermore, the interaction, cross-term, and valence energies of optimized structures are important for understanding the properties and structures of selective collectors. The simulation of pure scheelite mineral (PSM) surfaces with four different negative ions, using an adsorption locator module is demonstrated. The interaction energies for base organic ions and water molecules were resolved and detected by shaping the best hydrophobic interaction and the most stable suspension over the PSM surface (112) and (101). The adsorption locator results for base organic ions and water molecules on PSM surfaces (112) and (101) using buffer width 0.5 Å and temperature range from 318.15 to 283.15 K confirmed the results obtain from Forcite calculations. The results have demonstrated that the possibilities of using consistent valence force field implemented by Forcite and adsorption locator modules in the selection of flotation reagents are cost saving. Furthermore, hydrophobicity of the main negative ions in soaps were solved by the simulation methods and results are in a good agreement with the experimental methods that proved that mustard soap is more selective on the mineral surfaces than sunflower soap when used as a collector. Increasing the molecular weight of negative ions increases the interaction energy between base collector ions and PSM surfaces (112) and (101) significantly.

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.

Nanoscale Structure-Property Relationships of Polyacrylonitrile/CNT Composites as a Function of Polymer Crystallinity and CNT Diameter

Polyacrylonitrile (PAN)/carbon nanotube (CNT) composites are used as precursors for ultrastrong and lightweight carbon fibers. However, insights into the structure at the nanoscale and the relationships to mechanical and thermal properties have remained difficult to obtain. In this study, molecular dynamics simulation with accurate potentials and available experimental data were used to describe the influence of different degrees of PAN preorientation and CNT diameter on the atomic-scale structure and properties of the composites. The inclusion of CNTs in the polymer matrix is favored for an intermediate degree of PAN orientation and small CNT diameter whereas high PAN crystallinity and larger CNT diameter disfavor CNT inclusion. The glass transition at the CNT/PAN interface involves the release of rotational degrees of freedom of the polymer backbone and increased mobility of the protruding nitrile side groups in contact with the carbon nanotubes. The glass-transition temperature of the composite increases in correlation with the amount of CNT/polymer interfacial area per unit volume, i.e., in the presence of CNTs, for higher CNT volume fraction,  and inversely with CNT diameter. The increase in glass-transition temperature upon CNT addition is larger for PAN of lower crystallinity than for PAN of higher crystallinity. Interfacial shear strengths of the composites are higher for CNTs of smaller diameter and for PAN with preorientation, in correlation with more favorable CNT inclusion energies. The lowest interfacial shear strength was observed in amorphous PAN for the same CNT diameter. PAN with ∼75% crystallinity exhibited hexagonal patterns of nitrile groups near and far from the CNT interface which could influence carbonization into regular graphitic structures. The results illustrate the feasibility of near-quantitative insights into macroscale properties of polymer/CNT composites from simulations of nanometer-scale composite domains. Guidance is most effective when key assumptions in experiment and simulation are closely aligned, such as exfoliation versus bundling of CNTs, size, type, potential defects of CNTs, and precise measures for polymer crystallinity.

Carbon Nanotube Dispersion in Solvents and Polymer Solutions: Mechanisms, Assembly, and Preferences

Debundling and dispersion of carbon nanotubes (CNTs) in polymer solutions play a major role in the preparation of carbon nanofibers due to early effects on interfacial ordering and mechanical properties. A roadblock toward ultrastrong fibers is the difficulty to achieve homogeneous dispersions of CNTs in polyacrylonitrile (PAN) and poly(methyl methacrylate) (PMMA) precursor solutions in solvents such as dimethyl sulfoxide (DMSO), N,N-dimethylacetamide (DMAc), and N,N-dimethylformamide (DMF). In this contribution, molecular dynamics simulations with accurate interatomic potentials for graphitic materials that include virtual π electrons are reported to analyze the interaction of pristine single wall CNTs with the solvents and polymer solutions at 25 °C. The results explain the barriers toward dispersion of SWCNTs and quantify CNT-solvent, polymer-solvent, as well as CNT-polymer interactions in atomic detail. Debundling of CNTs is overall endothermic and unfavorable with dispersion energies of +20 to +30 mJ/m² in the pure solvents, + 20 to +40 mJ/m² in PAN solutions, and +20 to +60 mJ/m² in PMMA solutions. Differences arise due to molecular geometry, polar, van der Waals, and CH-π interactions. Among the pure solvents, DMF restricts CNT dispersion less due to the planar geometry and stronger van der Waals interactions. PAN and PMMA interact favorably with the pure solvents with dissolution energies of -0.7 to -1.1 kcal per mole monomer and -1.5 to -2.2 kcal per mole monomer, respectively. Adsorption of PMMA onto CNTs is stronger than that of PAN in all solvents as the molecular geometry enables more van der Waals contacts between alkyl groups and the CNT surface. Polar side groups in both polymers prefer interactions with the polar solvents. Higher polymer concentrations in solution lead to polymer aggregation via alkyl groups and reduce adsorption onto CNTs. PAN and PMMA solutions in DMSO and dilute solutions in DMF support CNT dispersion more than other combinations whereby the polymers significantly adsorb onto CNTs in DMSO solution. The observations by molecular simulations are consistent with available experimental data and solubility parameters and aid in the design of carbon nanofibers. The methods can be applied to other multiphase graphitic materials.

Probing nano-patterned peptide self-organisation at the aqueous graphene interface

The peptide sequence GrBP5, IMVTESSDYSSY, is found experimentally to bind to graphene, and ex situ atomic force microscopy indicates the formation of an ordered over-layer on graphite. However, under aqueous conditions neither the molecular conformations of the adsorbed peptide chains, nor the molecular-level spatial ordering of the over-layer, has been directly resolved. Here, we use advanced molecular dynamics simulations of GrBP5, and related mutant sequences, to elucidate the adsorbed structures of both the peptide and the adsorbed peptide over-layer at the aqueous graphene interface. In agreement with a previous hypothesis, we find GrBP5 binds at the aqueous graphene interface chiefly via the tyrosine-rich C-terminal region. Our simulations of the adsorbed peptide over-layers reveal that the peptide chains form an aggregate that does not evolve further into ordered patterns. Instead, we find that the inter-chain interactions are driven by hydrogen bonding and charge-charge interactions that are not sufficiently specific to support pattern formation. Overall, we suggest that the experimentally-observed over-layer pattern may be due to the drying of the sample, and may not be prevalent at the solvated interface. However, our simulations indicate sequence modifications of GrBP5 to promote over-layer ordering under aqueous conditions.

Solution Effects on Peptide-Mediated Reduction and Stabilization of Au Nanoparticles

Biomimetic methods for the preparation and application of inorganic nanomaterials represent a unique avenue to sustainably generating functional materials with long-term activity. Typically, for the fabrication of these structures, the peptide is mixed with metal ions in solution prior to the addition of an exogenous reductant such as NaBH₄, leading to nanoparticle nucleation and growth. In biological systems, strong reductants such as NaBH₄ are not available, thus different metal ion reduction methods must be exploited. Recent work has shown that the AuBP1 peptide (WAGAKRLVLRRE), a Au binding peptide with an N-terminal tryptophan, can spontaneously reduce Au³⁺ without an exogenous reductant. Remarkably, this system initially demonstrated the formation of large Au aggregates that disassemble to form individual Au nanoparticles, stabilized by the peptide bound to the inorganic surface. In this contribution, we demonstrate the significant effects of aqueous solvent-processing conditions (pH, ionic strength, and ion composition) on the rate of particle evolution. Understanding how such effects alter the metal ion reduction process and subsequent nanoparticle fabrication is important in controlling the final structure/function relationship of the resultant peptide-capped materials. This work identifies conditions that may enhance nanoparticle synthesis using biomimetic approaches where the peptide has complete control over the complexation, reduction, nucleation, and growth of nanomaterials.

Shape control in concave metal nanoparticles by etching

The shape control of nanoparticles constitutes one of the main challenges in today's nanotechnology. The synthetic procedures are based on trial-and-error methods and are difficult to rationalize as many ingredients are typically used. For instance, concave nanoparticles exhibiting high-index facets can be obtained from Pt with different HCl treatments. These structures present exceptional capacities when are employed as catalysts in electrochemical processes, as they maximize the activity per mass unit of the expensive material. Here we show how atomistic simulations based on density functional theory that take into account the environment can predict the morphology for the nanostructures and how it is even possible to address the appearance of concave structures. To describe the control by etching, we have reformulated the Wulff construction through the use of a geometric model that leads to concave polyhedra, which have a larger surface-to-volume ratio compared to that for nanocubes. Such an increase makes these sorts of nanoparticles excellent candidates to improve electrocatalytic performance.

A computational method for selecting short peptide sequences for inorganic material binding

Discovering or designing biofunctionalized materials with improved quality highly depends on the ability to manipulate and control the peptide-inorganic interaction. Various peptides can be used as assemblers, synthesizers, and linkers in the material syntheses. In another context, specific and selective material-binding peptides can be used as recognition blocks in mining applications. In this study, we propose a new in silico method to select short 4-mer peptides with high affinity and selectivity for a given target material. This method is illustrated with the calcite (104) surface as an example, which has been experimentally validated. A calcite binding peptide can play an important role in our understanding of biomineralization. A practical aspect of calcite is a need for it to be selectively depressed in mining sites.

In situ electrochemical high-energy X-ray diffraction using a capillary working electrode cell geometry

The ability to generate new electrochemically active materials for energy generation and storage with improved properties will likely be derived from an understanding of atomic-scale structure/function relationships during electrochemical events. Here, the design and implementation of a new capillary electrochemical cell designed specifically for in situ high-energy X-ray diffraction measurements is described. By increasing the amount of electrochemically active material in the X-ray path while implementing low-Z cell materials with anisotropic scattering profiles, an order of magnitude enhancement in diffracted X-ray signal over traditional cell geometries for multiple electrochemically active materials is demonstrated. This signal improvement is crucial for high-energy X-ray diffraction measurements and subsequent Fourier transformation into atomic pair distribution functions for atomic-scale structural analysis. As an example, clear structural changes in LiCoO₂ under reductive and oxidative conditions using the capillary cell are demonstrated, which agree with prior studies. Accurate modeling of the LiCoO₂ diffraction data using reverse Monte Carlo simulations further verifies accurate background subtraction and strong signal from the electrochemically active material, enabled by the capillary working electrode geometry.

Nature of peptide wrapping onto metal nanoparticle catalysts and driving forces for size control

Colloidal metal nanocrystals find many applications in catalysis, energy conversion devices, and therapeutics. However, the nature of ligand interactions and implications on shape control have remained uncertain at the atomic scale. Large differences in peptide adsorption strength and facet specificity were found on flat palladium surfaces versus surfaces of nanoparticles of 2 to 3 nm size using accurate atomistic simulations with the Interface force field. Folding of longer peptides across many facets explains the formation of near-spherical particles with local surface disorder, in contrast to the possibility of nanostructures of higher symmetry with shorter ligands. The average particle size in TEM correlates inversely with the surface coverage with a given ligand and with the strength of ligand adsorption. The role of specific amino acids and sequence mutations on the nanoparticle size and facet composition is discussed, as well as the origin of local surface disorder that leads to large differences in catalytic reactivity.

Peptide-templated noble metal catalysts: syntheses and applications

Noble metal catalysts have been widely used in many applications because of their high activity and selectivity. However, a controllable preparation of noble metal catalysts still remains as a significant challenge. To overcome this challenge, peptide templates can play a critical role in the controllable syntheses of catalysts owing to their flexible binding with specific metallic surfaces and self-assembly characteristics. By employing peptide templates, the size, shape, facet, structure, and composition of obtained catalysts can all be specifically controlled under the mild synthesis conditions. In addition, catalysts with spherical, nanofiber, and nanofilm structures can all be produced by associating with the self-assembly characteristics of peptide templates. Furthermore, the peptide-templated noble metal catalysts also reveal significantly enhanced catalytic behaviours compared with conventional catalysts because the electron conductivity, metal dispersion, and reactive site exposure can all be improved. In this review, we summarize the research progresses in the syntheses of peptide-templated noble metal catalysts. The applications of the peptide-templated catalysts in organic reactions, photocatalysis, and electrocatalysis are discussed, and the relationship between structure and activity of these catalysts are addressed. Future opportunities, including new catalytic materials designed by using biological principles, are indicated to achieve selective, eco-friendly, and energy neutral synthesis approaches.

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.

Elucidating the influence of materials-binding peptide sequence on Au surface interactions and colloidal stability of Au nanoparticles

Peptide-mediated synthesis and assembly of nanostructures opens new routes to functional inorganic/organic hybrid materials. However, understanding of the many factors that influence the interaction of biomolecules, specifically peptides, with metal surfaces remains limited. Understanding of the relationship between peptide sequence and resulting binding affinity and configurations would allow predictive design of peptides to achieve desired peptide/metal interface characteristics. Here, we measured the kinetics and thermodynamics of binding on a Au surface for a series of peptide sequences designed to probe specific sequence and context effects. For example, context effects were explored by making the same mutation at different positions in the peptide and by rearranging the peptide sequence without changing the amino acid content. The degree of peptide-surface contact, predicted from advanced molecular simulations of the surface-adsorbed structures, was consistent with the measured binding constants. In simulations, the ensemble of peptide backbone conformations showed little change with point mutations of the anchor residues that dominate interaction with the surface. Peptide-capped Au nanoparticles were produced using each sequence. Comparison of simulations with nanoparticle synthesis results revealed a correlation between the colloidal stability of the Au nanoparticles and the degree of structural disorder in the surface-adsorbed peptide structures for this family of sequences. These findings suggest new directions in the optimization and design of biomolecules for in situ peptide-based nanoparticle growth, binding, and dispersion in aqueous media.

Interface modulation of bacteriogenic Ag/AgCl nanoparticles by boosting the catalytic activity for reduction reactions using Co2+ ions

Co²⁺ can coordinate with surface peptides coated on Ag/AgCl NPs, and boosts the catalytic activity for p-nitrophenol reduction.

Seed-Mediated Growth of Colloidal Metal Nanocrystals

Seed-mediated growth is a powerful and versatile approach for the synthesis of colloidal metal nanocrystals. The vast allure of this approach mainly stems from the staggering degree of control one can achieve over the size, shape, composition, and structure of nanocrystals. These parameters not only control the properties of nanocrystals but also determine their relevance to, and performance in, various applications. The ingenuity and artistry inherent to seed-mediated growth offer extensive promise, enhancing a number of existing applications and opening the door to new developments. This Review demonstrates how the diversity of metal nanocrystals can be expanded with endless opportunities by using seeds with well-defined and controllable internal structures in conjunction with a proper combination of capping agent and reduction kinetics. New capabilities and future directions are also highlighted.

Remote Optically Controlled Modulation of Catalytic Properties of Nanoparticles through Reconfiguration of the Inorganic/Organic Interface

We introduce here a concept of remote photoinitiated reconfiguration of ligands adsorbed onto a nanocatalyst surface to enable reversible modulation of the catalytic activity. This is demonstrated by using peptide-ligand-capped Au nanoparticles with a photoswitchable azobenzene unit integrated into the biomolecular ligand. Optical switching of the azobenzene isomerization state drives rearrangement of the ligand layer, substantially changing the accessibility and subsequent catalytic activity of the underlying metal surface. The catalytic activity was probed using 4-nitrophenol reduction as a model reaction, where both the position of the photoswitch in the peptide sequence and its isomerization state affected the catalytic activity of the nanoparticles. Reversible switching of the isomerization state produces reversible changes in catalytic activity via reconfiguration of the biomolecular overlayer. These results provide a pathway to catalytic materials whose activity can be remotely modulated, which could be important for multistep chemical transformations that can be accessed via nanoparticle-based catalytic systems.

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.