Inelastic Neutron Scattering Study of Confined Surface Water on Rutile Nanoparticles

Control of H-Related Defects in γ-MnO2 in a Hydrothermal Synthesis

Manganese dioxide is a good candidate for effective energy storage and conversion as it possesses rich electrochemistry. The compound also shows a wide polymorphism. The γ-variety, an intergrowth of β- and R-MnO2, has been extensively studied in several types of batteries (e.g., Zn/MnO2, Li-ion) and is a common electrode material for commercial batteries. It is well known that the insertion of protons thermodynamically stabilizes γ-MnO2 with respect to β-MnO2. Protons can enter the structure either by forming groups of 4 hydroxyls around a Mn4+ vacancy, called a Ruetschi defect, or by forming a hydroxyl group near a Mn3+ ion, called a Coleman defect. These defects differently affect the electrochemistry of manganese oxide, and tailoring their amount in the structure can be used to tune the material properties. Previous studies have addressed the proton insertion process, but the role of the synthesis pathway on the amount of defects created is not well understood. We here investigate how the parameters in a hydrothermal synthesis of γ-MnO2 nanoparticles influence the amount and type of H-related defects. Structural investigations are carried out using Pair Distribution Function analysis, X-ray absorption spectroscopy, thermogravimetric analysis, and inelastic neutron scattering. We demonstrate the possibility to control the amount and type of defects introduced during the synthesis. While the amount of Ruetschi defects increases with synthesis temperature, it decreases with extended synthesis time, along with the amount of Coleman defects. Moreover, we discuss the arrangement of the defects in the γ-MnO2 nanoparticles.

Vibrational Analysis of Hydration-Layer Water around Ubiquitin, Unpeeled Layer by Layer: Molecular-Dynamics Perceptions

Classical molecular-dynamics simulations have been performed to examine the interplay between ubiquitin and its hydration-water sub-layers, chiefly from a vibrational-mode and IR viewpoint-where we analyse individual sub-layers characteristics. The vibrational Density of States (VDOS) revealed that the first solvation sub-shell indicates a confined character therein. For layers of increasing distance from the surface, the adoption of greater bulk-like spectral behaviour was evident, suggesting that vibrational harmonisation to bulk occurs within 6-7 Å of the surface.

Energetic Stability and Interfacial Complexity of Ti3C2Tx MXenes Synthesized with HF/HCl and CoF2/HCl as Etching Agents

MXenes are ultra-thin two-dimensional layered early transition-metal carbides and nitrides with potential applications in various emerging technologies, such as energy storage, water purification, and catalysis. MXenes are synthesized from the parent MAX phases with different etching agents [hydrofluoric acid (HF) or fluoride salts with a strong acid] by selectively removing a more weakly bound crystalline layer of Al or Ga replaced by surface groups (-O, -F, -OH, etc.). Ti₃C₂T_x MXene synthesized by CoF₂/HCl etching has layered heterogeneity due to intercalated Al³⁺ and Co²⁺ that act as pillars for interlayer spacings. This study investigates the impacts of etching environments on the compositional, interfacial, structural, and thermodynamic properties of Ti₃C₂T_x MXenes. Specifically, compared with HF/HCl etching, CoF₂/HCl treatment leads to a Ti₃C₂T_x MXene with a broader distribution of interlayer distances, increased number of intercalated cations, and decreased degree of hydration. Moreover, we determine the enthalpies of formation at 25 °C (ΔH_f,25°C) of Ti₃C₂T_x MXenes etched with CoF₂/HCl, ΔH_f,25°C = -1891.7 ± 35.7 kJ/mol Ti₃C₂, and etched with HF/HCl, ΔH_f,25°C = -1978.2 ± 35.7 kJ/mol Ti₃C₂, using high-temperature oxidation drop calorimetry. These energetic data are discussed and compared with experimentally derived and computationally predicted values to elucidate the effects of intercalants and surface groups of MXenes. We find that MXenes with intercalated metal cations have a less exothermic ΔH_f,25°C from an increase in the interlayer space and dimension heterogeneity and a decrease in the degree of hydration leading to reduced layer-layer van der Waals interactions and weakened hydration effects applied on the MXene layers. The outcomes of this study further our understanding of MXene's energetic-structural-interfacial property relationships.

Self-Diffusion of Individual Adsorbed Water Molecules at Rutile (110) and Anatase (101) TiO2 Interfaces from Molecular Dynamics

The distribution of individual water molecules’ self-diffusivities in adsorbed layers at TiO2 surfaces anatase (101) and rutile (110) have been determined at 300 K for inner and outer adsorbed layers, via classical molecular-dynamics methods. The layered-water structure has been identified and classified in layers making use of local order parameters, which proved to be an equally valid method of “self-ordering” molecules in layers. Significant distinctness was observed between anatase and rutile in disturbing these molecular distributions, more specifically in the adsorbed outer layer. Anatase (101) presented significantly higher values of self-diffusivity, presumably due to its “corrugated” structure that allows more hydrogen bonding interaction with adsorbed molecules beyond the first hydration layer. On the contrary, rutile (110) has adsorbed water molecules more securely “trapped” in the region between Ob atoms, resulting in less mobile adsorbed layers.

Machine learning potentials for complex aqueous systems made simple

Understanding complex materials, in particular those with solid–liquid interfaces, such as water on surfaces or under confinement, is a key challenge for technological and scientific progress. Although established simulation approaches have been able to provide important atomistic insight, ab initio techniques struggle with the required time and length scales, while force field methods can often be limited in terms of their accuracy. Here we show how these limitations can be overcome in a simple and automated machine learning procedure to provide accurate models of interactions at the ab initio level, as illustrated for a variety of complex aqueous systems. These developments open up the prospect of the straightforward exploration of many technologically relevant systems by molecular simulations.

Simulation techniques based on accurate and efficient representations of potential energy surfaces are urgently needed for the understanding of complex systems such as solid–liquid interfaces. Here we present a machine learning framework that enables the efficient development and validation of models for complex aqueous systems. Instead of trying to deliver a globally optimal machine learning potential, we propose to develop models applicable to specific thermodynamic state points in a simple and user-friendly process. After an initial ab initio simulation, a machine learning potential is constructed with minimum human effort through a data-driven active learning protocol. Such models can afterward be applied in exhaustive simulations to provide reliable answers for the scientific question at hand or to systematically explore the thermal performance of ab initio methods. We showcase this methodology on a diverse set of aqueous systems comprising bulk water with different ions in solution, water on a titanium dioxide surface, and water confined in nanotubes and between molybdenum disulfide sheets. Highlighting the accuracy of our approach with respect to the underlying ab initio reference, the resulting models are evaluated in detail with an automated validation protocol that includes structural and dynamical properties and the precision of the force prediction of the models. Finally, we demonstrate the capabilities of our approach for the description of water on the rutile titanium dioxide (110) surface to analyze the structure and mobility of water on this surface. Such machine learning models provide a straightforward and uncomplicated but accurate extension of simulation time and length scales for complex systems.

The logarithmic relaxation process and the critical temperature of liquids in nano-confined states

The logarithmic relaxation process is the slowest of all relaxation processes and is exhibited by only a few molecular liquids and proteins. Bulk salol, which is a glass-forming liquid, is known to exhibit logarithmic decay of intermediate scattering function for the β-relaxation process. In this article, we report the influence of nanoscale confinements on the logarithmic relaxation process and changes in the microscopic glass-transition temperature of salol in the carbon and silica nanopores. The generalized vibrational density-of-states of the confined salol indicates that the interaction of salol with ordered nanoporous carbon is hydrophilic in nature whereas the interaction with silica surfaces is more hydrophobic. The mode-coupling theory critical temperature derived from the QENS data shows that the dynamic transition occurs at much lower temperature in the carbon pores than in silica pores. The results of this study indicate that, under nano-confinements, liquids that display logarithmic β-relaxation phenomenon undergo a unique glass transition process.

The effect of hydrazine intercalation on the structure and capacitance of 2D titanium carbide (MXene)

Herein we show that hydrazine intercalation into 2D titanium carbide (Ti3C2-based MXene) results in changes in its surface chemistry by decreasing the amounts of fluorine, OH surface groups and intercalated water. It also creates a pillaring effect between Ti3C2Tx layers pre-opening the structure and improving the accessability to active sites. The hydrazine treated material has demonstrated a greatly improved capacitance of 250 F g(-1) in acidic electrolytes with an excellent cycling ability for electrodes as thick as 75 μm.

Nanoscale effects on thermodynamics and phase equilibria in oxide systems

Because different solid materials (phases) have different surface energies, equilibria among them will be significantly affected by particle size. This Minireview summarizes experimental (calorimetric) data for the surface energies of oxides and discusses shifts in the stability of polymorphs, the thermodynamics of hydration, and oxidation-reduction reactions in nanoscale oxide systems.

Determination of the magnetic contribution to the heat capacity of cobalt oxide nanoparticles and the thermodynamic properties of the hydration layers

We present low temperature (11 K) inelastic neutron scattering (INS) data on four hydrated nanoparticle systems: 10 nm CoO·0.10H(2)O (1), 16 nm Co(3)O(4)·0.40H(2)O (2), 25 nm Co(3)O(4)·0.30H(2)O (3) and 40 nm Co(3)O(4)·0.026H(2)O (4). The vibrational densities of states were obtained for all samples and from these the isochoric heat capacity and vibrational energy for the hydration layers confined to the surfaces of these nanoparticle systems have been elucidated. The results show that water on the surface of CoO nanoparticles is more tightly bound than water confined to the surface of Co(3)O(4), and this is reflected in the reduced heat capacity and vibrational entropy for water on CoO relative to water on Co(3)O(4) nanoparticles. This supports the trend, seen previously, for water to be more tightly bound in materials with higher surface energies. The INS spectra for the antiferromagnetic Co(3)O(4) particles (2-4) also show sharp and intense magnetic excitation peaks at 5 meV, and from this the magnetic contribution to the heat capacity of Co(3)O(4) nanoparticles has been calculated; this represents the first example of use of INS data for determining the magnetic contribution to the heat capacity of any magnetic nanoparticle system.