First-Principles Study of Water Nanotubes Captured Inside Carbon/Boron Nitride Nanotubes

Water molecules in boron nitride interlayer space: ice and hydrolysis in super confinement

Development of nano-sized channels and filters in the recent years has made the role of water immensely important as water molecules affect their performance and durability. Here, we take advantage of molecular dynamics and density functional theory methods to demonstrate the shift in behavior of water molecules confined between hexagonal boron nitride (HBN) sheets spaced at 3.0 to 6.5 Å. Our results demonstrate that lower interlayer spaces cause higher amounts of charge transferred between the species, while at extreme degrees of confinement, these interactions cause the disintegration of trapped water molecules. Consequently, the inner face of the HBN sheets is functionalized with hydroxyl groups, releasing hydrogens in the form of protons that travel the interlayer space by Grotthuss mechanism. This is the first-hand evidence of a mechanical form of hydrolysis that corresponds with a nucleophilic attack (on boron atoms) to relieve water from extreme confined conditions. This process unveils a previously unknown behavior of water within extremely confined spaces and reveals new considerations concerning nanofilters and nanochannels.

Ferroelectricity of ice nanotube forests grown in three-dimensional graphene: the electric field effect

Generating diverse ferroelectric ice nanotubes (NTs) efficiently has always been challenging, but matters in nanomaterial synthesis and processing technology. In the present work, we propose a method of growing ice NT forests in a single cooling process. A three-dimensional (3D) graphene structure was selected to behave as a representative container in which a batch of (5, 0) ice NTs was formed simultaneously under the cooling process from molecular dynamics simulation. Other similar 3D graphene structures but with different hole configurations, like uniform triangle or both triangle and pentagon, were also tested, revealing that ice NTs with different tube indices, i.e. both (3, 0) and (5, 0), could also be formed at the same time. Intriguingly, the orientations of the dipole moments of the water molecules of an ice NT formed were independent of each other, making the net ferroelectricity of the whole system weakened or even cancelled. An electric field could help change the orientation of the water molecules of the already obtained ice NTs and even twist the tube to be a spiral (5, 1) one if it was applied during the cooling process, such that the net ferroelectricity was greatly improved. The underlying physical mechanism of all phase transition phenomena, including the improvement of the ferroelectricity under an electric field, were explored in depth from the phase transition curves and structural point of view. The obtained results are of significant application value for improving the preparation efficiency of nano-ferroelectric materials, which are prosperous in nano-devices.

Mechanical hydrolysis imparts self-destruction of water molecules under steric confinement

Decoding behavioral aspects associated with the water molecules in confined spaces such as an interlayer space of two-dimensional nanosheets is key for the fundamental understanding of water-matter interactions and identifying unexpected phenomena of water molecules in chemistry and physics. Although numerous studies have been conducted on the behavior of water molecules in confined spaces, their reach stops at the properties of the planar ice-like formation, where van der Waals interactions are the predominant interactions and many questions on the confined space such as the possibility of electron exchange and excitation state remain unsettled. We used density functional theory and reactive molecular dynamics to reveal orbital overlap and induction bonding between water molecules and graphene sheets under much less pressure than graphene fractures. Our study demonstrates high amounts of charge being transferred between water and the graphene sheets, as the interlayer space becomes smaller. As a result, the inner face of the graphene nanosheets is functionalized with hydroxyl and epoxy functional groups while released hydrogen in the form of protons either stays still or traverses a short distance inside the confined space via the Grotthuss mechanism. We found signatures of a new hydrolysis mechanism in the water molecules, i.e. mechanical hydrolysis, presumably responsible for relieving water from extremely confined conditions. This phenomenon where water reacts under extreme confinement by disintegration rather than forming ice-like structures is observed for the first time, illustrating the prospect of treating ultrafine porous nanostructures as a driver for water splitting and material functionalization, potentially impacting the modern design of nanofilters, nanochannels, nano-capacitators, sensors, and so on.

The cooperative effect of the sorption of volatile molecules into metal-oxide frameworks as a function of the dielectric constant

The separation of volatile molecules into metal-oxide frameworks (MOxF) is possible with the combination of two approaches: spatial confinement and sorption-desorption equilibria. We have shown that nanoporous MOxF, namely giant POMs with Keplerate or toroidal structures, have a specific sorption behaviour towards different volatile substances that can be generalized through the dependence of the limit sorption on the dielectric constant and molecular polarizability. Assisted by the Hildebrand and Hansen solubility parameters and the Snyder polarity index, an analysis of sorption behaviour shows that the contributions of hydrogen bonding, hydrophobic forces and polar and dispersion interactions can be expressed through a cooperative phenomenon (the formation of a quasi-liquid layer) correlated with dielectric constant as a major parameter. The obtained data can be used to predict the separation of volatile substances using MOxF-embedded hybrid materials, such as selective membranes.

From Behavior of Water on Hydrophobic Graphene Surfaces to Ultra-Confinement of Water in Carbon Nanotubes

In recent years and with the achievement of nanotechnologies, the development of experiments based on carbon nanotubes has allowed to increase the ionic permeability and/or selectivity in nanodevices. However, this new technology opens the way to many questionable observations, to which theoretical work can answer using several approximations. One of them concerns the appearance of a negative charge on the carbon surface, when the latter is apparently neutral. Using first-principles density functional theory combined with molecular dynamics, we develop here several simulations on different systems in order to understand the reactivity of the carbon surface in low or ultra-high confinement. According to our calculations, there is high affinity of the carbon atom to the hydrogen ion in every situation, and to a lesser extent for the hydroxyl ion. The latter can only occur when the first hydrogen attack has been achieved. As a consequence, the functionalization of the carbon surface in the presence of an aqueous medium is activated by its protonation, then allowing the reactivity of the anion.

Molecular modeling and computational study of the chiral-dependent structures and properties of the self-assembling diphenylalanine peptide nanotubes, containing water molecules

DFT (VASP) and semi-empirical (HyperChem) calculations for the L- and D-chiral diphenylalanine (L-FF and D-FF) nanotube (PNT) structures, empty and filled with water/ice clusters, are presented and analyzed. The results obtained show that after optimization, the dipole moment and polarization of both chiral type L-FF and D-FF PNT and embedded water/ice cluster are enhanced; the water/ice cluster acquire the helix-like structure similar as L-FF and D-FF PNT. Ferroelectric properties of tubular water/ice helix-like-cluster obtained after optimization inside L-FF and D-FF PNT and total L-FF and D-FF PNT with embedded water/ice cluster are discussed.

Structures and Properties of the Self-Assembling Diphenylalanine Peptide Nanotubes Containing Water Molecules: Modeling and Data Analysis

The structures and properties of the diphenylalanine (FF) peptide nanotubes (PNTs), both L-chiral and D-chiral (L-FF and D-FF) and empty and filled with water/ice clusters, are presented and analyzed. DFT (VASP) and semi-empirical calculations (HyperChem) to study these structural and physical properties of PNTs (including ferroelectric) were used. The results obtained show that after optimization the dipole moment and polarization of both chiral type L-FF and D-FF PNT and embedded water/ice cluster are enhanced; the water/ice cluster acquire the helix-like structure similar as L-FF and D-FF PNT. Ferroelectric properties of tubular water/ice helix-like cluster, obtained after optimization inside L-FF and D-FF PNT, as well of the total L-FF and D-FF PNT with embedded water/ice cluster, are discussed.

Phase transition and mechanical properties of cesium bismuth silver halide double perovskites (Cs2AgBiX6, X = Cl, Br, I): a DFT approach

Double perovskite-based silver and bismuth Cs₂AgBiX₆ (X = Cl, Br, I) have shown a bright future for the development of low-risk photovoltaic devices due to their high stability and non-toxicity of their elements, unlike Pb-based perovskites. Despite the great focus on the optoelectronic properties of Cs₂AgBiX₆ double perovskites, there are limited studies on the behavior of their structural properties. Herein, we carefully examined the cubic structure of Cs₂AgBiX₆ double perovskites, identifying a pseudo-cubic (ps-cubic) phase, which is similar to the initial cubic phase. The observed pseudo-cubic phase is more consistent with previous experimental results demonstrating higher elastic properties, which are useful for designing optoelectronic devices.

Electro-Optical Properties of Monolayer and Bilayer Pentagonal BN: First Principles Study

Two-dimensional hexagonal boron nitride (hBN) is an insulator with polar covalent B-N bonds. Monolayer and bilayer pentagonal BN emerge as an optoelectronic material, which can be used in photo-based devices such as photodetectors and photocatalysis. Herein, we implement spin polarized electron density calculations to extract electronic/optical properties of mono- and bilayer pentagonal BN structures, labeled as B2N4, B3N3, and B4N2. Unlike the insulating hBN, the pentagonal BN exhibits metallic or semiconducting behavior, depending on the detailed pentagonal structures. The origin of the metallicity is attributed to the delocalized boron (B) 2p electrons, which has been verified by electron localized function and electronic band structure as well as density of states. Interestingly, all 3D networks of different bilayer pentagonal BN are dynamically stable unlike 2D structures, whose monolayer B4N2 is unstable. These 3D materials retain their metallic and semiconductor nature. Our findings of the optical properties indicate that pentagonal BN has a visible absorption peak that is suitable for photovoltaic application. Metallic behavior of pentagonal BN has a particular potential for thin-film based devices and nanomaterial engineering.

Deep Learning to Speed up the Development of Structure-Property Relations For Hexagonal Boron Nitride and Graphene

Structure-property maps play a key role in accelerated materials discovery. The current norm for developing these maps includes computationally expensive physics-based simulations. Here, the capabilities of deep learning agents are explored such as convolutional neural networks (CNNs) and multilayer perceptrons (MLPs) to predict structure-property relations and reduce dependence on simulations. This study contains simulated hexagonal boron nitride (h-BN) microstructures damaged by various levels of radiation and temperature, with the objective to predict their residual strengths from the final atomic positions. By developing low dimensional physical descriptors to statistically describe the defects, these results show that purpose-specific microstructure representation can help in achieving a good prediction accuracy at low computational cost. Furthermore, the adaptability of the trained deep learning agents is explored to predict structure-property maps of other 2D materials using transfer learning. It is shown that in order to achieve good predictions accuracy (≈95% R² ), an agent that is training for the first time ("learning from scratch") requires 23-45% of simulated data, whereas an agent adapting to a different material ("transfer learning") requires only about 10% or less. This suggests that transfer learning is a potential game changer in material discovery and characterization approaches.

Boron nitride nanochannels encapsulating a water/heavy water layer for energy applications

Water interaction and transport through nanochannels of two-dimensional (2D) nanomaterials hold great promises in several applications including separation, energy harvesting and drug delivery. However, the fundamental underpinning of the electronic phenomena at the interface of such systems is poorly understood. Inspired by recent experiments, herein, we focus on water/heavy water in boron nitride (BN) nanochannels – as a model system – and report a series of ab initio based density functional theory (DFT) calculations on correlating the stability of adsorption and interfacial properties, decoding various synergies in the complex interfacial interactions of water encapsulated in BN nanocapillaries. We provide a comparison of phonon vibrational modes of water and heavy water (D₂O) captured in bilayer BN (BLBN) to compare their mobility and group speed as a key factor for separation mechanisms. This finding, combined with the fundamental insights into the nature of the interfacial properties, provides key hypotheses for the design of nanochannels.

Single layer water (SLW) on BN layer and encapsulated between bilayer BN (BLBN) as nanochannel.