Catalytic CVD synthesis of boron nitride and carbon nanomaterials - synergies between experiment and theory

Experimental and Theoretical Insights into Interfacial Properties of 2D Materials for Selective Water Transport Membranes: A Critical Review

Interfacial properties, such as wettability and friction, play critical roles in nanofluidics and desalination. Understanding the interfacial properties of two-dimensional (2D) materials is crucial in these applications due to the close interaction between liquids and the solid surface. The most important interfacial properties of a solid surface include the water contact angle, which quantifies the extent of interactions between the surface and water, and the water slip length, which determines how much faster water can flow on the surface beyond the predictions of continuum fluid mechanics. This Review seeks to elucidate the mechanism that governs the interfacial properties of diverse 2D materials, including transition metal dichalcogenides (e.g., MoS2), graphene, and hexagonal boron nitride (hBN). Our work consolidates existing experimental and computational insights into 2D material synthesis and modeling and explores their interfacial properties for desalination. We investigated the capabilities of density functional theory and molecular dynamics simulations in analyzing the interfacial properties of 2D materials. Specifically, we highlight how MD simulations have revolutionized our understanding of these properties, paving the way for their effective application in desalination. This Review of the synthesis and interfacial properties of 2D materials unlocks opportunities for further advancement and optimization in desalination.

Chemical vapor deposition of 2D materials: A review of modeling, simulation, and machine learning studies

Chemical vapor deposition (CVD) is extensively used to produce large-area two-dimensional (2D) materials. Current research is aimed at understanding mechanisms underlying the nucleation and growth of various 2D materials, such as graphene, hexagonal boron nitride (hBN), and transition metal dichalcogenides (e.g., MoS₂/WSe₂). Herein, we survey the vast literature regarding modeling and simulation of the CVD growth of 2D materials and their heterostructures. We also focus on newer materials, such as silicene, phosphorene, and borophene. We discuss how density functional theory, kinetic Monte Carlo, and reactive molecular dynamics simulations can shed light on the thermodynamics and kinetics of vapor-phase synthesis. We explain how machine learning can be used to develop insights into growth mechanisms and outcomes, as well as outline the open knowledge gaps in the literature. Our work provides consolidated theoretical insights into the CVD growth of 2D materials and presents opportunities for further understanding and improving such processes

Systematic Investigations of Annealing and Functionalization of Carbon Nanotube Yarns

Carbon nanotube yarns (CNY) are a novel carbonaceous material and have received a great deal of interest since the beginning of the 21st century. CNY are of particular interest due to their useful heat conducting, electrical conducting, and mechanical properties. The electrical conductivity of carbon nanotube yarns can also be influenced by functionalization and annealing. A systematical study of this post synthetic treatment will assist in understanding what factors influences the conductivity of these materials. In this investigation, it is shown that the electrical conductivity can be increased by a factor of 2 and 5.5 through functionalization with acids and high temperature annealing respectively. The scale of the enhancement is dependent on the reducing of intertube space in case of functionalization. For annealing, not only is the highly graphitic structure of the carbon nanotubes (CNT) important, but it is also shown to influence the residual amorphous carbon in the structure. The promising results of this study can help to utilize CNY as a replacement for common materials in the field of electrical wiring.

Boron Nitride Nanotube Nucleation via Network Fusion during Catalytic Chemical Vapor Deposition

Despite boron nitride nanotubes (BNNTs) first being synthesized in the 1990s, their nucleation mechanism remains unknown. Here we report nonequilibrium molecular dynamics simulations showing how BNNT cap structures form during Ni-catalyzed chemical vapor deposition (CVD) of ammonia borane. BN hexagonal ring networks are produced following the catalytic evolution of H₂ from the CVD feedstock, the formation and polymerization of B-N chain structures, and the repeated cleavage of homoelemental B-B/N-N bonds by the catalyst surface. Defect-free BNNT cap structures then form perpendicular to the catalyst surface via direct fusion of adjacent BN networks. This BNNT network fusion mechanism is a marked deviation from the established mechanism for carbon nanotube nucleation during CVD and potentially explains why CVD-synthesized BNNTs are frequently observed having sharper tips and wider diameters compared to CVD-synthesized carbon nanotubes.

'Nano on micro' hierarchical porous all carbon structures: an insight into interfacial interactions with bacteria

Micron long carbon nanofibers (CNFs) were grown on porous carbon beads to give an active surface for rapid immobilization of guest molecules. The fabrication of nanostructures using a catalytic route involving chemical vapour deposition on a porous substrate was accomplished by the controlled synthesis of iron nanoclusters on the surface of porous carbon beads. The challenge of catalyst nanoparticle diffusion into the porous substrate was addressed by using iron coordinated ligand complexes and optimizing the loading percentage of metal salts onto beads. The effect of using tethered bottom up surface processed CNFs on the porous beads' morphologies was established using structural characterization. The protruding architecture of CNFs on the porous carbon surface was subjected to bacterial colonisation in order to determine the efficiency of cell conjugation onto hairy structures, particularly at a low concentration. The interfaces of immobilized bacteria on the textured surface were studied by varying the pH and external physical stimuli to check the biofilm formation. The strategy of fabricating all carbon porous beads, which had topologically controlled 'nano on micro' geometries, to give fast immobilization of guest molecules could be useful in the future for developing an active disinfectant surface.

Fabrication and application of BN nanoparticles, nanosheets and their nanohybrids

Smart implementation of novel advanced nanomaterials is the key for the solution of many complex problems of modern science. In recent years, there has been a great interest in the synthesis and application of boron nitride (BN) nanotubes because of their unique physical, chemical, and mechanical properties. By contrast, the synthesis, characterization and exploration of other morphological types of BN nanostructure - BN nanoparticles and BN nanosheets - have received less attention. However, the detailed investigations on advantages of every morphological BN type for specific applications have only recently been started. One of the promising directions is the utilization of BN-based nanohybrids. This review is dedicated to the in-depth analysis of recently published works on the fabrication and application of BN nanoparticles, nanosheets, and their nanohybrids. It covers a variety of developed synthetic methods toward fabrication of such nanostructures, and their specific application potentials in catalysis, drug delivery, tribology and structural materials. Finally, the review focuses on the theoretical aspects of this quickly emerging field.

Inducing regioselective chemical reactivity in graphene with alkali metal intercalation

First principles calculations demonstrate that alkali metal atoms, intercalated between metal substrates and adsorbed graphene monolayers, induce localised regions of increased reactivity. The extent of this localisation is proportional to the size of the alkali atom and the strength of the graphene-substrate interaction. Thus, larger alkali atoms are more effective (e.g. K > Na > Li), as are stronger-interacting substrates (e.g. Ni > Cu). Despite the electropositivity of these alkali metal adsorbates, analysis of charge transfer between the alkali metal, the substrate and the adsorbed graphene layer indicates that charge transfer does not give rise to the observed regioselective reactivity. Instead, the increased reactivity induced in the graphene structure is shown to arise from the geometrical distortion of the graphene layer imposed by the intercalated adsorbed atom. We show that this strategy can be used with arbitrary adsorbates and substrate defects, provided such structures are stable, towards controlling the mesoscale patterning and chemical functionalisation of graphene structures.

Simulations of the synthesis of boron-nitride nanostructures in a hot, high pressure gas volume

We performed nanosecond timescale computer simulations of clusterization and agglomeration processes of boron nitride (BN) nanostructures in hot, high pressure gas, starting from eleven different atomic and molecular precursor systems containing boron, nitrogen and hydrogen at various temperatures from 1500 to 6000 K. The synthesized BN nanostructures self-assemble in the form of cages, flakes, and tubes as well as amorphous structures. The simulations facilitate the analysis of chemical dynamics and we are able to predict the optimal conditions concerning temperature and chemical precursor composition for controlling the synthesis process in a high temperature gas volume, at high pressure. We identify the optimal precursor/temperature choices that lead to the nanostructures of highest quality with the highest rate of synthesis, using a novel parameter of the quality of the synthesis (PQS). Two distinct mechanisms of BN nanotube growth were found, neither of them based on the root-growth process. The simulations were performed using quantum-classical molecular dynamics (QCMD) based on the density-functional tight-binding (DFTB) quantum mechanics in conjunction with a divide-and-conquer (DC) linear scaling algorithm, as implemented in the DC-DFTB-K code, enabling the study of systems as large as 1300 atoms in canonical NVT ensembles for 1 ns time.