Solvent Effect on Supramolecular Self-Assembly of Chlorophylls a on Chemically Reduced Graphene Oxide.

Solvent plays an important role in the surface interaction of molecules. In this study, we use "chlorophyll a", an archetypical molecule, to investigate its supramolecular self-assembly with chemically reduced graphene oxide in three different types of solvents: polar protic, polar aprotic, and non-polar. It was observed that only a polar protic solvent that can donate protons facilitates the hydrogen bonding between chlorophyll a and chemically reduced graphene oxide nanosheets in a hybrid system. The formation of hydrogen bonds further initiates the other non-covalent interactions such as π-π stacking and hydrophobic interaction, which altogether play a key driving force for supramolecular self-assembly of chlorophylls on chemically reduced graphene oxides. The experimental results are strongly supported by density functional theory calculations, which show robust electron coupling between chlorophylls and chemically reduced graphene oxide.

Detection of Ring and Adatom Defects in Activated Disordered Carbon via Fluctuation Nanobeam Electron Diffraction.

How the structure of disordered porous carbons evolves during their activation is particularly poorly understood. This problem endures primarily because of a lack of high-resolution 3D techniques for the characterization of amorphous and highly disordered structure. To address this, the measurement of the 3D pair-angle distribution function using nanodiffraction patterns from high-energy electrons is demonstrated. These rich multiatom correlations are measured for a disordered carbon and they clearly show the structural evolution during activation. They provide previously inaccessible bond-angle information and direct evidence for the presence of ring and adatom defects. An increase in the short-range order and the number of fivefold ring defects with activation are observed, indicating stress relaxation by increasing curvature. These observations support models of disordered porous carbons based on curved graphene networks and explain how large amounts of free volume can be created with surprisingly small changes in the average ratios of tetrahedral to graphitic bonding.

Energy Landscapes of a Pair of Adsorbed Peptides.

The wide relevance of peptide adsorption in natural and synthetic contexts means it has attracted much attention. Molecular dynamics (MD) simulation has been widely used in these endeavors. Much of this has focused on single peptides due to the computational effort required to capture the rare events that characterize their adsorption. This focus is, however, of limited practical relevance as in reality, most systems of interest operate in the nondilute regime where peptides will interact with other adsorbed peptides. As an alternative to MD simulation, we have used energy landscape mapping (ELM) to investigate two met-enkephalin molecules adsorbed at a gas/graphite interface. Major conformations of the adsorbed peptides and the connecting transition states are elucidated along with the associated energy barriers and rates of exchange. The last of these makes clear that MD simulations are currently of limited use in probing the co-adsorption of two peptides, let alone more. The constant volume heat capacity as a function of temperature is also presented. Overall, this study represents a significant step toward characterizing peptide adsorption beyond the dilute limit.

Energy Landscape Mapping and Replica Exchange Molecular Dynamics of an Adsorbed Peptide.

Adsorption of peptides at the interface between a fluid and a solid occurs widely in both nature and applications. Knowing the dominant conformations of adsorbed peptides and the energy barriers between them is of interest for a variety of reasons. Molecular dynamics (MD) simulation is a widely used technique that can yield such understanding. However, the complexity of the energy landscapes of adsorbed peptides means that comprehensive exploration of the energy landscape by MD simulation is challenging. An alternative approach is energy landscape mapping (ELM), which involves the location of stationary points on the potential energy surface, and its analysis to determine, for example, the pathways and energy barriers between them. In the study reported here, a comparison is made between this technique and replica exchange molecular dynamics (REMD) for met-enkephalin adsorbed at the interface between graphite and the gas phase: the first ever direct comparison of these techniques for adsorbed peptides. Both methods yield the dominant adsorbed peptide conformations. Unlike REMD, however, ELM readily allows the identification of the connectivity and energy barriers between the favored conformations, transition paths, and structures between these conformations and the impact of entropy. It also permits the calculation of the constant volume heat capacity although the accuracy of this is limited by the sampling of high-energy minima. Overall, compared to REMD, ELM provides additional insights into the adsorbed peptide system provided sufficient care is taken to ensure that key parts of the landscape are adequately sampled.

Simultaneously 'pushing' and 'pulling' graphene oxide into low-polar solvents through a designed interface.

Dispersing graphene oxide (GO) in low-polar solvents can realize a perfect self-assembly with functional molecules and application in removal of organic impurities that only dissolve in low-polar solvents. The surface chemistry of GO plays an important role in its dispersity in these solvents. The direct transfer of hydrophilic GO into low-polar solvents, however, has remained an experimental challenge. In this study, we design an interface to transfer GO by simultaneously 'pushing and pulling' the nanosheets into low-polar solvents. Our approach is outstanding due to the ability to obtain monolayers of chemically reduced GO (CRGO) with designed surface properties in the organic phase. Using the transferred GO or CRGO dispersions, we have fabricated GO/fullerene nanocomposites and assessed the ability of CRGOs for dye adsorption. We hope our work can provide a universal approach for the phase transfer of other nanomaterials.

Characterizing the Switching Transitions of an Adsorbed Peptide by Mapping the Potential Energy Surface.

Peptide adsorption occurs across technology, medicine, and nature. The functions of adsorbed peptides are related to their conformation. In the past, molecular simulation methods such as molecular dynamics have been used to determine key conformations of adsorbed peptides. However, the transitions between these conformations often occur too slowly to be modeled reliably by such methods. This means such transitions are less well understood. In the study reported here, discrete path sampling is used for the first time to study the potential energy surface of an adsorbed peptide (polyalanine) and the transition pathways between various stable adsorbed conformations that have been identified in prior work by two of the authors [ Mijajlovic , M. ; Biggs , M. J. J. Phys. Chem. C 2007 , 111 , 15839 - 15847 ]. Mechanisms for the switching of adsorbed polyalanine between the stable conformations are elucidated along with the energetics of these switches.

Partial breaking of the Coulombic ordering of ionic liquids confined in carbon nanopores.

Ionic liquids are composed of equal quantities of positive and negative ions. In the bulk, electrical neutrality occurs in these liquids due to Coulombic ordering, in which ion shells of alternating charge form around a central ion. Their structure under confinement is far less well understood. This hinders the widespread application of ionic liquids in technological applications. Here we use scattering experiments to resolve the structure of a widely used ionic liquid (EMI-TFSI) when it is confined inside nanoporous carbons. We show that Coulombic ordering reduces when the pores can accommodate only a single layer of ions. Instead, equally charged ion pairs are formed due to the induction of an electric potential of opposite sign in the carbon pore walls. This non-Coulombic ordering is further enhanced in the presence of an applied external electric potential. This finding opens the door for the design of better materials for electrochemical applications.

Single-Walled Carbon Nanotubes Enhance the Efficiency and Stability of Mesoscopic Perovskite Solar Cells.

Carbon nanotubes are 1D nanocarbons with excellent properties and have been extensively used in various electronic and optoelectronic device applications including solar cells. Herein, we report a significant enhancement in the efficiency and stability of perovskite solar cells (PSCs) by employing single-walled carbon nanotubes (SWCNTs) in the mesoporous photoelectrode. It was found that SWCNTs provide both rapid electron transfer and advantageously shifts the conduction band minimum of the TiO2 photoelectrode and thus enhances all photovoltaic parameters of PSCs. The TiO2-SWCNTs photoelectrode based PSC device exhibited a power conversion efficiency (PCE) of up to 16.11%, while the device fabricated without SWCNTs displayed an efficiency of 13.53%. More importantly, we found that the SWCNTs in the TiO2 nanoparticles (TiO2 NPs) based photoelectrode suppress the hysteresis behavior and significantly enhance both the light and long-term storage stability of the PSC devices. The present work provides important guidance for future investigations in utilizing carbonaceous materials for solar cells.

Carbon Nanotubes in TiO2 Nanofiber Photoelectrodes for High-Performance Perovskite Solar Cells.

1D semiconducting oxides are unique structures that have been widely used for photovoltaic (PV) devices due to their capability to provide a direct pathway for charge transport. In addition, carbon nanotubes (CNTs) have played multifunctional roles in a range of PV cells because of their fascinating properties. Herein, the influence of CNTs on the PV performance of 1D titanium dioxide nanofiber (TiO2 NF) photoelectrode perovskite solar cells (PSCs) is systematically explored. Among the different types of CNTs, single-walled CNTs (SWCNTs) incorporated in the TiO2 NF photoelectrode PSCs show a significant enhancement (≈40%) in the power conversion efficiency (PCE) as compared to control cells. SWCNTs incorporated in TiO2 NFs provide a fast electron transfer within the photoelectrode, resulting in an increase in the short-circuit current (Jsc) value. On the basis of our theoretical calculations, the improved open-circuit voltage (Voc) of the cells can be attributed to a shift in energy level of the photoelectrodes after the introduction of SWCNTs. Furthermore, it is found that the incorporation of SWCNTs into TiO2 NFs reduces the hysteresis effect and improves the stability of the PSC devices. In this study, the best performing PSC device constructed with SWCNT structures achieves a PCE of 14.03%.

Analysis of Adsorbate-Adsorbate and Adsorbate-Adsorbent Interactions to Decode Isosteric Heats of Gas Adsorption.

A qualitative interpretation is proposed to interpret isosteric heats of adsorption by considering contributions from three general classes of interaction energy: fluid-fluid heat, fluid-solid heat, and fluid-high-energy site (HES) heat. Multiple temperature adsorption isotherms are defined for nitrogen, T=(75, 77, 79) K, argon at T=(85, 87, 89) K, and for water and methanol at T=(278, 288, 298) K on a well-characterized polymer-based, activated carbon. Nitrogen and argon are subjected to isosteric heat analyses; their zero filling isosteric heats of adsorption are consistent with slit-pore, adsorption energy enhancement modelling. Water adsorbs entirely via specific interactions, offering decreasing isosteric heat at low pore filling followed by a constant heat slightly in excess of water condensation enthalpy, demonstrating the effects of micropores. Methanol offers both specific adsorption via the alcohol group and non-specific interactions via its methyl group; the isosteric heat increases at low pore filling, indicating the predominance of non-specific interactions.

Immersion Calorimetry: Molecular Packing Effects in Micropores.

Repeated and controlled immersion calorimetry experiments were performed to determine the specific surface area and pore-size distribution (PSD) of a well-characterized, microporous poly(furfuryl alcohol)-based activated carbon. The PSD derived from nitrogen gas adsorption indicated a narrow distribution centered at 0.57±0.05 nm. Immersion into liquids of increasing molecular sizes ranging from 0.33 nm (dichloromethane) to 0.70 nm (α-pinene) showed a decreasing enthalpy of immersion at a critical probe size (0.43-0.48 nm), followed by an increase at 0.48-0.56 nm, and a second decrease at 0.56-0.60 nm. This maximum has not been reported previously. After consideration of possible reasons for this new observation, it is concluded that the effect arises from molecular packing inside the micropores, interpreted in terms of 2D packing. The immersion enthalpy PSD was consistent with that from quenched solid density functional theory (QSDFT) analysis of the nitrogen adsorption isotherm.

Carbon Nanotubes for Dye-Sensitized Solar Cells.

As one type of emerging photovoltaic cell, dye-sensitized solar cells (DSSCs) are an attractive potential source of renewable energy due to their eco-friendliness, ease of fabrication, and cost effectiveness. However, in DSSCs, the rarity and high cost of some electrode materials (transparent conducting oxide and platinum) and the inefficient performance caused by slow electron transport, poor light-harvesting efficiency, and significant charge recombination are critical issues. Recent research has shown that carbon nanotubes (CNTs) are promising candidates to overcome these issues due to their unique electrical, optical, chemical, physical, as well as catalytic properties. This article provides a comprehensive review of the research that has focused on the application of CNTs and their hybrids in transparent conducting electrodes (TCEs), in semiconducting layers, and in counter electrodes of DSSCs. At the end of this review, some important research directions for the future use of CNTs in DSSCs are also provided.

Carbonaceous Dye-Sensitized Solar Cell Photoelectrodes.

High photovoltaic efficiency is one of the most important keys to the commercialization of dye sensitized solar cells (DSSCs) in the quickly growing renewable electricity generation market. The heart of the DSSC system is a wide bandgap semiconductor based photoelectrode film that helps to adsorb dye molecules and transport the injected electrons away into the electrical circuit. However, charge recombination, poor light harvesting efficiency and slow electron transport of the nanocrystalline oxide photoelectrode film are major issues in the DSSC's performance. Recently, semiconducting composites based on carbonaceous materials (carbon nanoparticles, carbon nanotubes (CNTs), and graphene) have been shown to be promising materials for the photoelectrode of DSSCs due to their fascinating properties and low cost. After a brief introduction to development of nanocrystalline oxide based films, this Review outlines advancements that have been achieved in the application of carbonaceous-based materials in the photoelectrode of DSSCs and how these advancements have improved performance. In addition, several of the unsolved issues in this research area are discussed and some important future directions are also highlighted.

Molecular-level understanding of protein adsorption at the interface between water and a strongly interacting uncharged solid surface.

Although protein adsorption on solids is of immense relevance, experimental limitations mean there is still a remarkable lack of understanding of the adsorption mechanism, particularly at a molecular level. By subjecting 240+ molecular dynamics simulations of two peptide/water/solid surface systems to statistical analysis, a generalized molecular level mechanism for peptide adsorption has been identified for uncharged surfaces that interact strongly with the solution phase. This mechanism is composed of three phases: (1) biased diffusion of the peptide from the bulk phase toward the surface; (2) anchoring of the peptide to the water/solid interface via interaction of a hydrophilic group with the water adjacent to the surface or a strongly interacting hydrophobic group with the surface; and (3) lockdown of the peptide on the surface via a slow, stepwise and largely sequential adsorption of its residues, which we term 'statistical zippering'. The adsorption mechanism is dictated by the existence of water layers adjacent to the solid and orientational ordering therein. By extending the solid into the solution by ~8 Å and endowing it with a charged character, the water layers ensure the peptide feels the effect of the solid at a range well beyond the dispersion force that arises from it, thus inducing biased diffusion from afar. The charging of the interface also facilitates anchoring of the peptide near the surface via one of its hydrophilic groups, allowing it time it would otherwise not have to rearrange and lockdown. Finally, the slowness of the lockdown process is dictated by the need for the peptide groups to replace adjacent tightly bound interfacial water.

Free energy of adsorption for a peptide at a liquid/solid interface via nonequilibrium molecular dynamics.

Protein adsorption is of wide interest including in many technological applications such as tissue engineering, nanotechnology, biosensors, drug delivery, and vaccine production among others. Understanding the fundamentals of such technologies and their design would be greatly aided by an ability to efficiently predict the conformation of an adsorbed protein and its free energy of adsorption. In the study reported here, we show that this is possible when data obtained from nonequilibrium thermodynamic integration (NETI) combined with steered molecular dynamics (SMD) is subject to bootstrapping. For the met-enkephalin pentapeptide at a water-graphite interface, we were able to obtain accurate predictions for the location of the adsorbed peptide and its free energy of adsorption from around 50 and 80 SMD simulations, respectively. It was also shown that adsorption in this system is both energetically and entropically driven. The free energy of adsorption was also decomposed into that associated with formation of the cavity in the water near the graphite surface sufficient to accommodate the adsorbed peptide and that associated with insertion of the peptide into this cavity. This decomposition reveals that the former is modestly energetically and entropically unfavorable, whereas the latter is the opposite in both regards to a much greater extent.

On potential energy models for EA-based ab initio protein structure prediction.

Ab initio protein structure prediction involves determination of the three-dimensional (3D) conformation of proteins on the basis of their amino acid sequence, a potential energy (PE) model that captures the physics of the interatomic interactions, and a method to search for and identify the global minimum in the PE (or free energy) surface such as an evolutionary algorithm (EA). Many PE models have been proposed over the past three decades and more. There is currently no understanding of how the behavior of an EA is affected by the PE model used. The study reported here shows that the EA behavior can be profoundly affected: the EA performance obtained when using the ECEPP PE model is significantly worse than that obtained when using the Amber, OPLS, and CVFF PE models, and the optimal EA control parameter values for the ECEPP model also differ significantly from those associated with the other models.

Effect of pore wall model on prediction of diffusion coefficients for graphitic slit pores.

The effect of the pore wall model on the self-diffusion coefficient and transport diffusivity predicted for methane in graphitic slit pores by equilibrium molecular dynamics (EMD) and non-equilibrium MD (NEMD) is investigated. Three pore wall models are compared--a structured wall and a smooth (specular) wall, both with a thermostat applied to the fluid to maintain the desired temperature, and a structured wall combined with the diffuse thermalizing scattering algorithm of MacElroy and Boyle (Chem. Eng. J., 1999, 74, 85). Pore sizes ranging between 7 and 35 angstroms and five pressures in the range of 1-40 bar are considered. The diffuse thermalizing wall yields incorrect self-diffusion coefficients and transport diffusivities for the graphitic slit pore model and should not be used. Surprisingly, the smooth specular wall gives self-diffusion coefficients inline with those obtained using the structured wall, indicating that this computationally much faster wall can be used for studying this phenomenon provided the fluid-wall interactions are somewhat weaker than the fluid-fluid interactions. The structured wall is required, however, if the transport diffusivity is of interest.

Switching in of Ac-(Ala)10-NHMe at a solid surface.

Using molecular simulation, we show how Ac-(Ala)(10)-NHMe adsorbed on a solid surface switches between three conformations at distinct surface energies. The first switch is from an alpha-helix to a 3.1(10)-helix. The second involves further stretching to a 2(7)-helix. This switching has several potential applications including memory in molecular computers to motility elements in nanotechnology, and could be relevant to biological activity of proteins near solid surfaces (e.g., nano and aerosol particles) and disease processes induced by such interactions.

On use of the Amber potential with the Langevin dipole method.

Inclusion of solvent effects in biomolecular simulations is most ideally done using explicit methods, as they are able to capture the heterogeneous environment typical of biomolecules and systems involving them (e.g., proteins at solid interfaces). Common explicit methods based on molecular solvent models (e.g., TIP and SPC models) and molecular dynamic or Monte Carlo simulation are computationally expensive and are, therefore, not well-suited to situations where many simulations are required (e.g., in the ab initio structure prediction or design contexts). In such cases, more coarse-grained explicit approaches such as the Langevin dipole (LD) method of Warshel and co-workers are more appropriate. The recent incarnations of the LD method appear to produce good solvation free energy estimates. These incarnations use charges and solute structures obtained from high-level quantum mechanics simulations. As such an approach is clearly not possible for larger solutes or when many structures are to be considered, an alternative must be sought. One possibility is to use structures and charges derived from an existing analytical potential model-we report on such a coupling here with the Amber potential model. The accuracy and computational performance of this hybrid approach, which we term LD-Amber to distinguish it from previous incarnations of the LD method, was assessed by comparing results obtained from the approach with those from experiment and other theoretical methods for the solvation of 18 amino acid analogues and the alanine dipeptide. This comparison shows that the LD-Amber approach can yield results in line with experiment both qualitatively and quantitatively and is as accurate as other explicit methods while being computationally much cheaper.

Ab initio protein fold prediction using evolutionary algorithms: influence of design and control parameters on performance.

True ab initio prediction of protein 3D structure requires only the protein primary structure, a physicochemical free energy model, and a search method for identifying the free energy global minimum. Various characteristics of evolutionary algorithms (EAs) mean they are in principle well suited to the latter. Studies to date have been less than encouraging, however. This is because of the limited consideration given to EA design and control parameter issues. A comprehensive study of these issues was, therefore, undertaken for ab initio protein fold prediction using a full atomistic protein model. The performance and optimal control parameter settings of twelve EA designs where first established using a 15-residue polyalanine molecule-design aspects varied include the encoding alphabet, crossover operator, and replacement strategy. It can be concluded that real encoding and multipoint crossover are superior, while both generational and steady-state replacement strategies have merits. The scaling between the optimal control parameter settings and polyalanine size was also identified for both generational and steady-state designs based on real encoding and multipoint crossover. Application of the steady-state design to met-enkephalin indicated that these scalings are potentially transferable to real proteins. Comparison of the performance of the steady state design for met-enkephalin with other ab initio methods indicates that EAs can be competitive provided the correct design and control parameter values are used.