Search

We report an investigation of the friction mechanisms of MoS2 thin films under changing environments and contact conditions using a variety of computational and experimental techniques. Molecular dynamics simulations were used to study the effects of water and molecular oxygen on friction and bonding of MoS2 lamellae during initial sliding. Characterization via photoelectron emission microscopy (PEEM) and Kelvin probe force microscopy (KPFM) were used to determine work function changes in shear modified material within the top few nanometers of MoS2 wear scars. The work function was shown to change with contact conditions and environment, and shown by density functional theory (DFT) calculations and literature reports to be correlated with lamellae size and thickness of the basally oriented surface layer. Results from nanoscale simulations and macroscale experiments suggest that the evolution of the friction behavior of MoS2 is linked primarily to the formation or inhibition of a basally oriented, molecularly thin surface film with long-range order. [ABSTRACT FROM AUTHOR]

We examine the vibrational properties and Raman spectra of Si-Ge core-shell nanostructures using real-space pseudopotentials constructed within density functional theory. Our method uses no empirical parameters, unlike many popular methods for predicting Raman spectra for nanocrystals.We find the dominant features of the Raman spectrum for the Si-Ge core-shell structure to be a superposition of the Raman spectra of the Ge and Si nanocrystals with optical peaks around 300 and 500 cm-1, respectively. We also find a Si-Ge "interface" peak at 400 cm-1. The Ge shell causes the Si core to expand from the equilibrium structure. This strain induces significant redshift in the Si contribution to the vibrational and Raman spectra, while the Ge shell is largely unstrained and does not exhibit this shift. We find that the ratio of peak heights is strongly related to the relative size of the core and shell regions. This finding suggests that Raman spectroscopy may be used to characterize the size of the core and shell in these structures. [ABSTRACT FROM AUTHOR]

We examine the electronic properties of Sb and F doped SnO2 nanocrystals up to 2.4 nm in diameter. A real-space pseudopotential implementation of density functional theory is employed within the local density approximation. We calculate electron binding energies and dopant formation energies as function of nanocrystal size, dopant concentration, and dopant species. Structural changes for different dopant species are also investigated. Our study should provide useful information for the design of transparent conducting oxides at the nanoscale. [ABSTRACT FROM AUTHOR]

Zinc oxide is often used as a popular inexpensive transparent conducting oxide. Here, we employ density functional theory and local density approximation to examine the effects of quantum confinement in doped nanocrystals of this material. Specifically, we examine the addition of Ga and Al dopants to ZnO nanocrystals on the order of 1.0 nm. We find that the inclusion of these dopants is energetically less favorable in smaller particles and that the electron binding energy, which is associated with the dopant activation, decreases with the nanocrystal size. We find that the introduction of impurities does not alter significantly the Kohn-Sham eigenspectrum for small nanocrystals of ZnO. The added electron occupies the lowest existing state, i.e., no new bound state is introduced in the gap. We verify this assertion with hybrid functional calculations. [ABSTRACT FROM AUTHOR]

We present a fast and accurate, semi-analytical method for predicting hydrogen adsorption in nanoporous materials. For any temperature and pressure, the adsorbed amount is calculated as an integral over the energy density of adsorption sites (guest-host interactions) plus an average guest-guest term. The guest-host interaction energy is calculated using a classical force field with hydrogen modelled as a single-site probe. The guest-guest interaction energy is approximated using an average coordination number, which is regressed using Gaussian Process Regression (GPR). Local adsorption at each site is then modelled using a Langmuir isotherm, which when weighted with its probability density gives an accurate description of hydrogen adsorption. The method is tested on 933 metal-organic frameworks (MOFs) from the Computation-Ready Experimental (CoRE) MOF database at 77 K from 10 − 5 to 100 bar, and the results are compared against GCMC predictions. To demonstrate the utility of the method, we calculated hydrogen adsorption isotherms for 12,914 existing MOF structures, at two different temperatures at a speed about 100 times that of GCMC simulations and analyzed the results. We found 13 MOFs with predicted deliverable capacities exceeding the DOE target of 50 g/L for adsorption at 100 bar, 77 K and desorption at 5 bar, 160 K. [ABSTRACT FROM AUTHOR]

Hydrogen is an appealing energy storage solution for electric vehicles due to its low environmental impact and faster recharge times compared to batteries. However, there are many engineering challenges involved in safely storing a sufficient amount of hydrogen onboard a vehicle with a reasonable volumetric density. Nanoporous materials such as metal–organic frameworks (MOFs) have the potential to store hydrogen at high density and only moderate pressure. Considerable research has been devoted to finding new MOFs for hydrogen storage in recent years; however, a MOF that provides sufficient hydrogen density and is suitable to commercial applications has not yet been found. Much of this research makes use of molecular modelling to screen thousands of materials in a high-throughput way. Computational screening can be an effective tool for gaining insight into structure-performance relationships as well as finding specific candidates for an application. Recently, some research groups have also used machine learning to analyze data more effectively and accelerate the screening process. In this review, we discuss some recent advances in using molecular modelling and machine learning to find materials for hydrogen storage. We also discuss and compare some popular models for the hydrogen molecule and the accuracy of different equations of state, which are important considerations for accurate molecular simulations. [ABSTRACT FROM AUTHOR]

Abstract: DNA G‐quadruplex structures were recently discovered to provide reliable scaffolding for two‐dimensional organic frameworks due to the strong hydrogen‐bonding ability of guanine. Herein, 2,7‐diaryl pyrene building blocks with high HOMO energies and large optical gaps are incorporated into G‐quadruplex organic frameworks. The adjustable substitution on the aryl groups provides an opportunity to elucidate the framework formation mechanism; molecular non‐planarity is found to be beneficial for restricting interlayer slippage, and the framework crystallinity is highest when intermolecular interaction and non‐planarity strike a fine balance. When guanine‐functionalized pyrenes are co‐crystallized with naphthalene diimide, charge‐transfer (CT) complexes are obtained. The photophysical properties of the pyrene‐only and CT frameworks are characterized by UV/Vis and steady‐state and time‐resolved photoluminescence spectroscopies, and by EPR spectroscopy for the CT complex frameworks. [ABSTRACT FROM AUTHOR]

Owing to the vast diversity of linkers, nodes, and topologies, metal–organic frameworks can be tailored for specific tasks, such as chemical separations or catalysis. Accordingly, these materials have attracted significant interest for capture and/or detoxification of toxic industrial chemicals and chemical warfare agents. In this paper, we review recent experimental and computational work pertaining to the capture of several industrially-relevant toxic chemicals, including NH3, SO2, NO2, H2S, and some volatile organic compounds, with particular emphasis on the challenging issue of designing materials that selectively adsorb these chemicals in the presence of water. We also examine recent research on the capture and catalytic degradation of chemical warfare agents such as sarin and sulfur mustard using metal–organic frameworks. [ABSTRACT FROM AUTHOR]

Engineered carbon molecular sieves (CMSs) with tapered pores, high surface area, and high total pore volume were investigated for their CO 2 , CH 4 , water, and acetone adsorption properties at 288.15, 298.15, 308.15 K, and pressures of <1 bar. The results were compared with BPL carbon. The samples exhibited higher adsorption capacity for CO 2 compared to BPL carbon, with Carboxen 1005 being the highest due to the presence of ultramicropores (pores smaller than 0.8 nm). Similar observations were made for CH 4 except at 288.15 K. Although the CMSs exhibited higher hydrophobicity than BPL carbon, the latter had the highest acetone uptake for all investigated temperatures due to its higher oxygen content, which facilitates stronger interactions with polar VOC molecules. Heats of adsorption were calculated using the Clausius-Clapeyron equation after fitting the isotherms with the dual-site Langmuir-Freundlich model, and results largely corroborated the order of adsorption capacities of CO 2 , CH 4 , and water on the carbon materials., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

Molybdenum disulfide (MoS 2 ) is a 2D material widely used as a dry lubricant. However, exposure to water and oxygen is known to reduce its effectiveness, and therefore an understanding of the uptake of water is important information for mitigating these effects. Here we use grand canonical Monte Carlo simulations to rigorously study water adsorption on MoS 2 surfaces and edges with different concentrations of defects under realistic atmospheric conditions ( i.e. various temperatures and humidity levels). We find that the amount of water adsorbed depends strongly on the number of defects. Simulations indicate that defect sites are generally saturated with water even at low ppm levels of humidity. Water binds strongly to S vacancies on interlamellar surfaces, but generally only one water molecule can fit on each of these sites. Defects on surfaces or edges of lamellae also strongly attract water molecules that then nucleate small clusters of water bonded via hydrogen bonding. We demonstrate that water preferentially binds to surface defects, but once those are saturated at a critical humidity level of about 500-1000 ppm water, water binds to edge sites where it negatively impacts the tribological performance of MoS 2 ., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Molybdenum disulfide (MoS 2 ) is a lamellar solid lubricant often used in aerospace applications because of its extremely low friction coefficient (∼0.01) in inert environments. The lubrication performance of MoS 2 is significantly impaired by exposure to even small amounts of water and oxygen, and the mechanisms behind this remain poorly understood. We use density functional theory calculations to study the binding of water on MoS 2 sheets with and without defects. In general, we find that pristine MoS 2 is slightly hydrophilic but that defects greatly increase the binding affinity for water. Intercalated water disrupts the crystal structure of bulk MoS 2 due to the limited space between lamellae (∼3.4 Å), and this leads to generally unfavorable adsorption, except in the cases where water molecules are located on the sites of sulfur vacancies. We also find that water adsorption is more favorable directly below a surface layer of MoS 2 compared to in the bulk.

Real space pseudopotentials have a number of advantages in solving for the electronic structure of materials. These advantages include ease of implementation, implementation on highly parallel systems, and great flexibility for describing partially periodic systems. One limitation of this approach, shared by other electronic structure methods, is the slow convergence of interatomic forces when compared to total energies. For real space methods, this requires a fine grid to converge a solution of the Kohn-Sham problem, which is accompanied by concurrent increase in memory and additional matrix-vector multiplications. Here we introduce a method to expedite the computation of interatomic forces by employing a high order integration technique. We demonstrate the usefulness of this technique by calculating accurate bond lengths and vibrational frequencies for molecules and nanocrystals without using fine real space grids.