Modeling Nanostructure in Graphene Oxide: Inhomogeneity and the Percolation Threshold

Sensing of volatile pollutants on reduced graphene oxide-polypyrrole composite: DFT investigation

Air pollutants generated from volatile toxic chemicals pose significant public health concerns. Density functional theory (DFT) computations were used in this research to explore the efficiency and mechanism of harmful gas sensing over the reduced graphene oxide-polypyrrole (rGO-PPy) composite. Volatile molecule sensing was investigated for the NH3, H2CO, CH3OH, and C2H5OH gas molecules over three PPy orientations on the rGO substrate. Results showed that PPy orientation over rGO plays a crucial role in the sensing efficiency of the investigated gas molecules. The rGO-PPy composite, with PPy in a vertical orientation, demonstrated higher stability and enhanced sensing than other orientations. The results indicate that the strong hydrogen bonding of NH3 and CH3OH with both PPy and rGO significantly enhanced the sensing of these gas molecules on rGO by influencing the charge transfer with adsorption energy values of - 0.84 and - 0.92 eV, respectively. The lack of a direct hydrogen bonding with rGO and the weak hydrogen bonding with PPy caused a weak adsorption of H2CO and C2H5OH over rGO as indicated by the adsorption energy values of - 0.60 and - 0.78 eV, respectively. Selectivity analysis for the NH3 and C2H5OH gas molecules showed that NH3 can maintain hydrogen bonding with PPy in the presence of C2H5OH while C2H5OH cannot sustain this interaction. This study highlights the importance of the structural and electronic properties of the rGO-PPy composite in volatile pollutant sensing, providing insights for designing high-performance gas sensors.

Staggered structural dynamic-mediated selective adsorption of H2O/D2O on flexible graphene oxide nanosheets

Graphene oxide (GO) is the one of the most promising family of materials as atomically thin membranes for water-related molecular separation technologies due to its amphipathic nature and layered structure. Here, we show important aspects of GO on water adsorption from molecular dynamics (MD) simulations, in-situ X-ray diffraction (XRD) measurements, and ex-situ nuclear magnetic resonance (NMR) measurements. Although the MD simulations for GO and the reduced GO models revealed that the flexibility of the interlayer spacing could be attributed to the oxygen-functional groups of GO, the ultra-large GO model cannot well explain the observed swelling of GO from XRD experiments. Our MD simulations propose a realistic GO interlayer structure constructed by staggered stacking of flexible GO sheets, which can explain very well the swelling nature upon water adsorption. The transmission electron microscopic (TEM) observation also supports the non-regular staggered stacking structure of GO. Furthermore, we demonstrate the existence of the two distinct types of adsorbed water molecules in the staggered stacking: water bonded with hydrophilic functional groups and "free" mobile water. Finally, we show that the staggered stacking of GO plays a crucial role in H/D isotopic recognition in water adsorption, as well as the high mobility of water molecules.

Large-Scale Molecular Dynamics Elucidates the Mechanics of Reinforcement in Graphene-Based Composites

Using very large-scale classical molecular dynamics, the mechanics of nano-reinforcement of graphene-based nanocomposites are  examined. Simulations show that significant quantities of large, defect-free, and predominantly flat graphene flakes are required for successful enhancement of materials properties in excellent agreement with experimental and proposed continuum shear-lag theories. The critical lengths for enhancement are approximately 500 nm for graphene and 300 nm and for graphene oxide (GO). The reduction of Young's modulus in GO results in a much smaller enhancement of the composite's Young's modulus. The simulations reveal that the flakes should be aligned and planar for optimal reinforcement. Undulations substantially degrade the enhancement of materials properties.

Adsorption Studies at the Graphene Oxide-Liquid Interface: A Molecular Dynamics Study

The adsorption of organic aromatic molecules, namely aniline, onto graphene oxide is investigated using molecular simulations. The effect of the oxidation level of the graphene oxide sheet as well as the presence of two different halide salts, sodium chloride and sodium iodide, were examined. The aniline molecule in the more-reduced graphene oxide case, in the absence of added salt, showed a slightly greater affinity for the graphene oxide-water interface as compared to the oxidized form. The presence of the iodide ion increased the affinity of the aniline molecule in the reduced case but had the opposite effect for the more-oxidized form. The effect of oxidation and added salt on the interfacial water layer was also examined.

From nanohole to ultralong straight nanochannel fabrication in graphene oxide with swift heavy ions

Porous architectures based on graphene oxide with precisely tailored nm-sized pores are attractive for biofluidic applications such as molecular sieving, DNA sequencing, and recognition-based sensing. However, the existing pore fabrication methods are complex, suffer from insufficient control over the pore density and uniformity, or are not scalable to large areas. Notably, creating vertical pores in multilayer films appears to be particularly difficult. Here, we show that uniform 6-7 nm-sized holes and straight, vertical nanochannels can be formed by simply irradiating graphene oxide (GO) films with high-energy heavy ions. Long penetration depths of energetic ions in combination with localized energy deposition and effective self-etching processes enable the creation of through pores even in 10 µm-thick GO films. This fully scalable fabrication provides a promising possibility for obtaining innovative GO track membranes.

Integrating structure annotation and machine learning approaches to develop graphene toxicity models

Modern nanotechnology provides efficient and cost-effective nanomaterials (NMs). The increasing usage of NMs arises great concerns regarding nanotoxicity in humans. Traditional animal testing of nanotoxicity is expensive and time-consuming. Modeling studies using machine learning (ML) approaches are promising alternatives to direct evaluation of nanotoxicity based on nanostructure features. However, NMs, including two-dimensional nanomaterials (2DNMs) such as graphenes, have complex structures making them difficult to annotate and quantify the nanostructures for modeling purposes. To address this issue, we constructed a virtual graphenes library using nanostructure annotation techniques. The irregular graphene structures were generated by modifying virtual nanosheets. The nanostructures were digitalized from the annotated graphenes. Based on the annotated nanostructures, geometrical nanodescriptors were computed using Delaunay tessellation approach for ML modeling. The partial least square regression (PLSR) models for the graphenes were built and validated using a leave-one-out cross-validation (LOOCV) procedure. The resulted models showed good predictivity in four toxicity-related endpoints with the coefficient of determination (R2) ranging from 0.558 to 0.822. This study provides a novel nanostructure annotation strategy that can be applied to generate high-quality nanodescriptors for ML model developments, which can be widely applied to nanoinformatics studies of graphenes and other NMs.

Development of Nanoscale Graphene Oxide Models for the Adsorption of Biological Molecules

Graphene oxide (GO), a nanomaterial with promising applications that range from water purification to enzyme immobilization, is actively present in scientific research since its discovery. GO studies with computational methodologies such as molecular dynamics are frequently reported in the literature; however, the models used often rely on approximations, such as randomly placing functional groups and the use of generalized force fields. Therefore, it is important to develop new MD models that provide a more accurate description of GO structures and their interaction with an aqueous solvent and other adsorbate molecules. In this paper, we derived new force field non-bonded parameters from linear-scaling density functional theory calculations of nanoscale GO sheets with more than 10,000 atoms through an atoms-in-molecules (AIM) partitioning scheme. The resulting GAFF2-AIM force field, derived from the bonded terms of GAFF2 parameterization, reproduces the solvent structure reported in ab initio MD simulations better than the force field nowadays widely used in the literature. Additionally, we analyzed the effect of the ionic strength of the medium and of the C/O ratio on the distribution of charges surrounding the GO sheets. Finally, we simulated the adsorption of natural amino acid molecules to a GO sheet and estimated their free energy of binding, which compared very favorably to their respective experimental values, validating the force field presented in this work.

Mechanically Stable Ultrathin Layered Graphene Nanocomposites Alleviate Residual Interfacial Stresses: Implications for Nanoelectromechanical Systems

Advanced nanoelectromechanical systems made from polymer dielectrics deposited onto 2D-nanomaterials such as graphene are increasingly popular as pressure and touch sensors, resonant sensors, and capacitive micromachined ultrasound transducers (CMUTs). However, durability and accuracy of layered nanocomposites depend on the mechanical stability of the interface between polymer and graphene layers. Here we used molecular dynamics computer simulations to investigate the interface between a sheet of graphene and a layer of parylene-C thermoplastic polymer during large numbers of high-frequency (MHz) cycles of bending relevant to the operating regime. We find that important interfacial sliding occurs almost immediately in usage conditions, resulting in more than 2% expansion of the membrane, a detrimental mechanism which requires repeated calibration to maintain CMUTs accuracy. This irreversible mechanism is caused by relaxation of residual internal stresses in the nanocomposite bilayer, leading to the emergence of self-equilibrated tension in the polymer and compression in the graphene. It arises as a result of deposition-polymerization processing conditions. Our findings demonstrate the need for particular care to be exercised in overcoming initial expansion. The selection of appropriate materials chemistry including low electrostatic interactions will also be key to their successful application as durable and reliable devices.

Effects of Moisture and Synthesis-Derived Contaminants on the Mechanical Properties of Graphene Oxide: A Molecular Dynamics Investigation

This paper reports on the effects of the chemical composition of graphene oxide (GO) sheets on the mechanical properties of bulk GO. Three key factors were analyzed: (i) the oxygenated functional groups' concentration, (ii) the content of intersheet water (moisture), and (iii) the presence of residual contaminants observed from the synthesis of GO. Molecular dynamics simulations using the reactive force field ReaxFF were conducted to model tensile strength, indentation, and shear stress tests. The structural integrity of the carbon basal plane was the primary variable that determined mechanical behavior of GO slabs. Hydrogen-bond networks played an essential role in the tensile fracture mechanism, delaying the onset of fracture whenever strong hydrogen bonds existed in the intersheet space. The presence of interlayer sulfate ion contaminants negatively impacted the tensile strength, stiffness, and toughness of GO. Moreover, it was observed that intersheet sulfate ions improved the resistance to fracture of GO at low sulfur concentrations, while lower fracture strains were observed beyond a critical concentration. Alike the tensile stress findings, the indentation properties were determined by the integrity of the carbon basal plane. Our findings agree with experimental mechanical property measurements and reveal the importance of considering synthesis-derived contaminants in molecular models of GO.

Graphene Oxide-Induced Substantial Strengthening of High-Entropy Alloy Revealed by Micropillar Compression and Molecular Dynamics Simulation

Plastic deformation mechanisms at micro/nanoscale of graphene oxide-reinforced high-entropy alloy composites (HEA/GO) remain unclear. In this study, small-scale mechanical behaviors were evaluated for HEA/GO composites with 0.0 wt.%, 0.3 wt.%, 0.6 wt.%, and 1.0 wt.% GO, consisting of compression testing on micropillar and molecular dynamics (MD) simulations on nanopillars. The experimental results uncovered that the composites exhibited a higher yield strength and flow stress compared with pure HEA micropillar, resulting from the GO reinforcement and grain refinement strengthening. This was also confirmed by the MD simulations of pure HEA and HEA/GO composite nanopillars. The immobile <100> interstitial dislocations also participated in the plastic deformation of composites, in contrast to pure HEA counterpart where only mobile 1/2 <111> perfect dislocations dominated deformation, leading to a higher yield strength for composite. Meanwhile, the MD simulations also revealed that the flow stress of composite nanopillar was significantly improved due to GO sheet effectively impeded dislocation movement. Furthermore, the mechanical properties of HEA/1.0 wt.% GO composite showed a slight reduction compared with HEA/0.6 wt.% GO composite. This correlated with the compositional segregation of Cr carbide and aggregation of GO sheets, indicative of lower work hardening rate in stress-strain curves of micropillar compression.

Wettability of graphene oxide functionalized with N-alkylamines: a molecular dynamics study

The wettability of graphene oxide functionalized with N-alkylamines was studied by molecular dynamics simulations. Six different N-alkylamines and two functionalization degrees were reviewed. The nucleophilic ring-opening reaction mechanism between the N-alkylamines and epoxy functional groups of graphene oxide was considered to generate the atomistic models. Water contact angles increased with both the alkyl chain length and substitution degree. The Wenzel model was used to access the effect of both the surface roughness and alkyl chain length on wettability. The results indicated that functionalization introduces an important increase of surface roughness but its effect on wettability is countered by the alkyl chain length.

Exploring Molecular and Electronic Property Predictions of Reduced Graphene Oxide Nanoflakes via Density Functional Theory

In this research, we perform a theoretical interpretation of molecular and electronic properties of reduced graphene oxide (rGO) nanoflakes through the density functional theory. Here, two pristine graphene nanoflake systems were passivated by hydrogen atoms at their edges, armchair (C58H20) and zigzag (C54H20); besides, we implemented 12 rGO systems with a range of low oxide coverage (1, 3, and 4%). Computational calculations were carried out employing the functional hybrid B3LYP and the basis 6-31G(d, p) and 6-311G(d, p) levels of theory. We brought the proposed molecular structures to a stable minimum. We determined the global reactivity descriptors through chemical potential, hardness, softness, and index of electrophilicity. Besides, the maps of electrostatic potential were generated. We found that the hydroxyl and epoxy functional groups dope the graphene molecule in p-type and n-type forms, respectively. In addition, we could attribute the increases of the oxide coverage and the chemical potential to the softness of the molecule. These results suggest that structures with this type of doping can help in developing advanced electronics of sensors and devices.

Synergetic effect between Pd2+ and Ir4+ species promoting direct ethane dehydrogenation into ethylene over bimetallic PdIr/AC catalysts

This work reported the efficient Pd–Ir pairs on the Pd7Ir2/AC-B catalyst achieved a TOF (C2H4) of 756.6 h−1 at 500 °C, and the direct ethane dehydrogenation (EDH) rationale and deactivation mechanism were proposed.

Principles governing control of aggregation and dispersion of aqueous graphene oxide

Controlling the structure of graphene oxide (GO) phases and their smaller analogues, graphene (oxide) quantum dots (GOQDs), is vitally important for any of their widespread intended applications: highly ordered arrangements of nanoparticles for thin-film or membrane applications of GO, dispersed nanoparticles for composite materials and three-dimensional porous arrangements for hydrogels. In aqueous environments, it is not only the chemical composition of the GO flakes that determines their morphologies; external factors such as pH and the coexisting cations also influence the structures formed. By using accurate models of GO that capture the heterogeneity of surface oxidation and very large-scale coarse-grained molecular dynamics that can simulate the behaviour of GO at realistic sizes of GOQDs, the driving forces that lead to the various morphologies in aqueous solution are resolved. We find the morphologies are determined by a complex interplay between electrostatic, [Formula: see text]-[Formula: see text] and hydrogen bonding interactions. Assembled morphologies can be controlled by changing the degree of oxidation and the pH. In acidic aqueous solution, the GO flakes vary from fully aggregated over graphitic domains to partial aggregation via hydrogen bonding between hydroxylated domains, leading to the formation of planar extended flakes at high oxidation ratios and stacks at low oxidation ratios. At high pH, where the edge carboxylic acid groups are deprotonated, electrostatic repulsion leads to more dispersion, but a variety of aggregation behaviour is surprisingly still observed: over graphitic regions, via hydrogen bonding and "face-edge" interactions. Calcium ions cause additional aggregation, with a greater number of "face-face" and "edge-edge" aggregation mechanisms, leading to irregular aggregated structures. "Face-face" aggregation mechanisms are enhanced by the GO flakes possessing distinct domains of hydroxylated and graphitic regions, with [Formula: see text]-[Formula: see text] and hydrogen bonding interactions prevalent between these regions on aggregated flakes respectively. These findings furnish explanations for the aggregation characteristics of GO and GOQDs, and provide computational methods to design directed synthesis routes for self-assembled and associated applications.

Adsorption of Single and Multiple Graphene-Oxide Nanoparticles at a Water-Vapor Interface

The adsorption of graphene-oxide (GO) nanoparticles at the interface between water and vapor was analyzed using all-atom molecular simulations for single and multiple particles. For a single GO particle, our results indicate that the adsorption energy does not scale linearly with the surface coverage of oxygen groups, unlike typically assumed for Janus colloids. Our results also show that the surface activity of the particle depends on the number of surface oxygen groups as well as on their distribution: for a given number of oxygen groups, a GO particle with a patched surface was found to be more surface active than a particle with evenly distributed groups. Then, to understand what sets the thickness of GO layers at interfaces, the adsorption energy of a test GO particle was measured in the presence of multiple GO particles already adsorbed at the interface. Our results indicate that in the case of high degree of oxidation, particle-particle interactions at the water-vapor interface hinder the adsorption of the test particle. In the case of a low degree of oxidation, however, clustering and stacking of GO particles dominate the adsorption behavior, and particle-particle interactions favor the adsorption of the test particle. These results highlight the complexity of multiple particle adsorption and the limitations of single-particle adsorption models when applied to GO at a relatively high surface concentration.

Uncertainty quantification in classical molecular dynamics

Molecular dynamics simulation is now a widespread approach for understanding complex systems on the atomistic scale. It finds applications from physics and chemistry to engineering, life and medical science. In the last decade, the approach has begun to advance from being a computer-based means of rationalizing experimental observations to producing apparently credible predictions for a number of real-world applications within industrial sectors such as advanced materials and drug discovery. However, key aspects concerning the reproducibility of the method have not kept pace with the speed of its uptake in the scientific community. Here, we present a discussion of uncertainty quantification for molecular dynamics simulation designed to endow the method with better error estimates that will enable it to be used to report actionable results. The approach adopted is a standard one in the field of uncertainty quantification, namely using ensemble methods, in which a sufficiently large number of replicas are run concurrently, from which reliable statistics can be extracted. Indeed, because molecular dynamics is intrinsically chaotic, the need to use ensemble methods is fundamental and holds regardless of the duration of the simulations performed. We discuss the approach and illustrate it in a range of applications from materials science to ligand-protein binding free energy estimation. This article is part of the theme issue 'Reliability and reproducibility in computational science: implementing verification, validation and uncertainty quantification in silico'.

Mechanistic aspects of functional layer formation in hybrid one-step designed GOx/Nafion/Pd-NPs nanobiosensors

Amperometric nanobiosensors are crucial time and cost effective analytical tools for the detection of a wide range of bioanalytes, viz. glucose present in complex environments at very low concentrations. Although the excellent analytical performance of nanobiosensors is undoubted, their exact molecular structure often remains unclear. Here, by combining advanced nanoanalytical approaches with theoretical modeling, we conducted a comprehensive study towards the investigation of the molecular structure of a hybrid GOx/Nafion/Pd-NPs layer deposited by electroplating from the multicomponent electrolyte solution on the surface of screen printed electrodes modified with graphene oxide. Specifically, we revealed that Pd²⁺ cations were adsorbed on GOx amino acid residues, forming the GOx·nPd²⁺ enzymatic complex. The highest adsorption energy of Pd²⁺ cations on GOx was found during their interaction with the side chains of basic amino acids and methionine. In addition, we showed and fully validated the end-structure of the one-step designed GOx/Nafion/Pd-NPs nanobiosensor as a structural model mainly composed of GOx and water molecules incorporated into the metal-polymer scaffold. Our approach will thus serve as a guideline for the study of molecular interactions occurring in complex systems and will contribute to the design of the next generation of hybrid nanobiosensors. The proposed mechanism, driving the self-assembly of the hybrid layer, will allow us to construct modular enzymatic nanoanalytical devices with tailored sequences in the future.

Effect of Oxidation Level on the Interfacial Water at the Graphene Oxide-Water Interface: From Spectroscopic Signatures to Hydrogen-Bonding Environment

The interfacial region of the graphene oxide (GO)-water system is nonhomogenous due to the presence of two distinct domains: an oxygen-rich surface and a graphene-like region. The experimental vibrational sum-frequency generation (vSFG) spectra are distinctly different for the fully oxidized GO-water interface as compared to the reduced GO-water case. Computational investigations using ab initio molecular dynamics were performed to determine the molecular origins of the different spectroscopic features. The simulations were first validated by comparing the simulated vSFG spectra to those from the experiment, and the contributions to the spectra from different hydrogen bonding environments and interfacial water orientations were determined as a function of the oxidation level of the GO sheet. The ab initio simulations also revealed the reactive nature of the GO-water interface.

Principles Governing Control of Aggregation and Dispersion of Graphene and Graphene Oxide in Polymer Melts

Controlling the structure of graphene and graphene oxide (GO) phases is vitally important for any of its widespread intended applications: highly ordered arrangements of nanoparticles are needed for thin-film or membrane applications of GO, dispersed nanoparticles for composite materials, and 3D porous arrangements for hydrogels. By combining coarse-grained molecular dynamics and newly developed accurate models of GO, the driving forces that lead to the various morphologies are resolved. Two hydrophilic polymers, poly(ethylene glycol) (PEG) and poly(vinyl alcohol) (PVA), are used to illustrate the thermodynamically stable morphologies of GO and relevant dispersion mechanisms. GO self-assembly can be controlled by changing the degree of oxidation, varying from fully aggregated over graphitic domains to intercalated assemblies with polymer bilayers between sheets. The long-term stability of a dispersion is extremely important for many commercial applications of GO composites. For any degree of oxidation, GO does not disperse in PVA as a thermodynamic equilibrium product, whereas in PEG dispersions are only thermodynamically stable for highly oxidized GO. These findings-validated against the extensive literature on GO systems in organic solvents-furnish quantitative explanations for the empirically unpredictable aggregation characteristics of GO and provide computational methods to design directed synthesis routes for diverse self-assemblies and applications.