Dimensional Chemistry Research Articles

Experimental and theoretical insights into the supercapacitive performance of interconnected WS2 nanosheets.

Transition metal dichalcogenides (TMDs) are fascinating and prodigious considerations in the electrochemical energy storage sector because of their two dimensional chemistry as well as heterogeneous characteristics. Herein, we synthesized interconnected WS2 nanosheets by a hydrothermal method followed by sulphuration at 850 °C in an argon atmosphere. The ultrathin WS2 nanosheet array is endowed with an excellent specific capacitance of 74 F g-1 at the current density of 3 A g-1 up 7000 cycles. Moreover, a symmetric supercapacitor was fabricated using WS2 nanosheets, which provided the admirable high specific capacity of 6.3 F g-1 at 0.05 A g-1 with the energy and power density of 5.6 × 102 mW h kg-1 and 3.6 × 10 5 mW kg-1, respectively. Density functional theory (DFT) simulations revealed the presence of populated energy states near the Fermi level resulting in a high quantum capacitance value, which supports the experimentally achieved high capacitance value. The attained results recommend interconnected WS2 nanosheets as a novel, robust, and low-cost electrode material for supercapacitor energy storage devices.

A novel method for chemistry tabulation of strained premixed/stratified flames based on principal component analysis

The principal component analysis (PCA) is used to analyze the high dimensional chemistry data of laminar premixed/stratified flames under strain effects. The first few principal components (PCs) with larger contribution ratios are chosen as the tabulated scalars to build the look-up chemistry table. Prior tests show that strained premixed flame structure can be well reconstructed. To highlight the physical meanings of the tabulated scalars in stratified flames, a modified PCA method is developed, where the mixture fraction is used to replace one of the PCs with the highest correlation coefficient. The other two tabulated scalars are then modified with the Schmidt orthogonalization. The modified tabulated scalars not only have clear physical meanings, but also contain passive scalars. The PCA method has good commonality, and can be extended for building the thermo-chemistry table including strain rate effects when different fuels are used.

The CSP/PSR approach in reduced chemistry of premixed ammonia combustion

In order to fire gas turbine engines on ammonia, knowledge is acquired about the combustion characteristics and model possibilities of this carbon free fuel. To this end in this paper the projection of detailed chemistry of ammonia on a low dimensional chemistry model is investigated at atmospheric pressure and temperature conditions. On basis of this turbulent combustion models for ammonia can developed on basis of available modeling procedures for hydrocarbon combustion. These turbulent combustion models are based on a projection of the high dimensional detailed chemistry on a single dimension reaction progress variable. This work describes a methodology to define an optimal expression of the reaction progress variable in the context of tabulated chemistry on basis of laminar premixed combustion. Two methods are used: the Computational Singular Perturbation (CSP) method and a sensitivity analysis of the time scales evaluated with a Perfectly Stirred Reactor (PSR). The thermo-chemical databases computed with these techniques are compared in the cases of a freely propagating flame, in the laminar premixed regime and under stoichiometric conditions. The accuracy of the chemical projection is evaluated on basis of a comparison of predicted species concentration and temperature profiles in a freely propagating flame based on detailed chemistry and the single reaction progress variable. It is found that the projection is very accurate and hence the combustion of ammonia can be predicted on basis of one dimensional tabulated chemistry.

Simulating aerosols over Arabian Peninsula with CHIMERE: Sensitivity to soil, surface parameters and anthropogenic emission inventories

A three dimensional chemistry transport model, CHIMERE, was used to simulate the aerosol optical depths (AOD) over the Arabian Peninsula desert with an offline coupling of Weather Research and Forecasting (WRF) model. The simulations were undertaken with: (i) different horizontal and vertical configurations, (ii) new datasets derived for soil/surface properties, and (iii) EDGAR-HTAP anthropogenic emissions inventories. The model performance evaluations were assessed: (i) qualitatively using MODIS (Moderate-Resolution Imaging Spectroradiometer) deep blue (DB) AOD data for the two local dust events of August 6th and 23rd (2013), and (ii) quantitatively using AERONET (Aerosol Robotic Network) AOD observations, CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) aerosol extinction profiles, and AOD simulations from various forecast models. The model results were observed to be highly sensitive to erodibility and aerodynamic surface roughness length. The use of new datasets on soil erodibility, derived from the MODIS reflectance, and aerodynamic surface roughness length (z0), derived from the ERA-Interim datasets, significantly improved the simulation results. Simulations with the global EDGAR-HTAP anthropogenic emission inventories brought the simulated AOD values closer to the observations. Performance testing of the adapted model for the Arabian Peninsula domain with improved datasets showed good agreement between AERONET AOD measurements and CHIMERE simulations, where the correlation coefficient (R) is 0.6. Higher values of the correlation coefficients and slopes were observed for the dusty periods compared to the non-dusty periods.

Sophie Hermans and Thierry Visart de Bocarmé (eds.): Atomically-Precise Methods for Synthesis of Solid Catalysts

indeed delivered a relatively comprehensive, well organized survey of state of the art methods to synthesize (primarily) metal catalysts. The sequencing of the material brought to my mind the classic review of the late, great Jim Schwarz, ‘‘Methods for Preparation of Catalytic Materials’’ (Chem. Rev. 95, 1995, 477) in which ‘‘3 dimensional chemistry’’ or synthesis of metal particles in the solution phase, was distinguished from ‘‘2 dimensional chemistry’’ in which metal is deposited and nanoparticles are formed on the support surface. In fact, the material swung back and forth between surface deposition and bulk formation techniques in something of a conical helix as depicted in the figure below. A clever unifying element is that as the chapter numbers increase, the catalysts grow in size and scale.

Using Graph Indices for the Analysis and Comparison of Chemical Datasets.

In cheminformatics, compounds are represented as points in multidimensional space of chemical descriptors. When all pairs of points found within certain distance threshold in the original high dimensional chemistry space are connected by distance-labeled edges, the resulting data structure can be defined as Dataset Graph (DG). We show that, similarly to the conventional description of organic molecules, many graph indices can be computed for DGs as well. We demonstrate that chemical datasets can be effectively characterized and compared by computing simple graph indices such as the average vertex degree or Randic connectivity index. This approach is used to characterize and quantify the similarity between different datasets or subsets of the same dataset (e.g., training, test, and external validation sets used in QSAR modeling). The freely available ADDAGRA program has been implemented to build and visualize DGs. The approach proposed and discussed in this report could be further explored and utilized for different cheminformatics applications such as dataset diversification by acquiring external compounds, dataset processing prior to QSAR modeling, or (dis)similarity modeling of multiple datasets studied in chemical genomics applications.

Global two dimensional chemistry model and simulation of atmospheric chemical composition

A global two-dimensional zonally averaged chemistry model is developed to study the chemi-cal composition of atmosphere. The region of the model is from 90°S to 90°N and from the ground to the altitude of 20 km with a resolution of 5° x 1 km. The wind field is residual circulation calcu-lated from diabatic rate. 34 species and 104 chemical and photochemical reactions are considered in the model. The sources of CH4, CO and NOx, which are divided into seasonal sources and non-seasonal sources, are parameterized as a function of latitude and time. The chemical composi-tion of atmosphere was simulated with emission level of CH4, CO and NOx in 1990. The results are compared with observations and other model results, showing that the model is successful to simu-late the atmospheric chemical composition and distribution of CH4.

Assessment of tropical OH seasonality using atmospheric 14CO measurements from Barbados

14CO can be used to assess the mean OH concentration if the atmospheric inventory is determined. However, atmospheric transport must be well represented. The dependence on transport has previously been predicted in model studies to be much smaller in the tropics than in the middle latitudes. To test this, we made weekly measurements of 14CO from a tropical station in the Atlantic (Barbados, West Indies, 13°10′N, 53°26′W) from July 1996 to July 1997. These data are compared with the 14CO seasonal cycle predicted from a zero dimensional chemistry model. Results show that the observed seasonal cycle correlates well with predicted 14CO from the chemistry model during the summer and fall, however significant deviation from the chemistry model becomes apparent in the wintertime, which is probably largely a result of 14CO being transported to the tropics from the middle latitudes, and is in contrast to earlier modeling studies. Transport has a stronger effect in the winter months because the latitudinal gradient in 14CO is large and the lifetime is long, since OH concentrations are at their seasonal low.

The Seasonal and Long Term Changes in Mesospheric Water Vapor

This study explores the feasibility of identifying long term changes in mesospheric water vapor as a result of increasing level of methane in the atmosphere and the solar cycle variation of Lyman α. The study is based on recent measurements of water vapor in the mesosphere and the solar Lyman α flux from the UARS (Upper Atmosphere Research Satellite) HALOE (Halogen Occultation Experiment) and the SOLSTICE (Solar Stellar Iradiance Comparison Experiment) instruments during the declining phase of the solar cycle 22. The solar activity during this period decreased from a near maximum to a near minimum level. The analysis of these data sets, in conjunction with the NASA/GSFC two dimensional chemistry and transport model suggests that on a seasonal time scale, the temporal changes in mesospheric water vapor are largely controlled by the vertical advection associated with the meridional circulation. On the time scale of a solar cycle, H2O may vary by about 30–40 % near the mesopause height (∼80 km) to about 1–2% in the lower mesosphere (60–65 km) caused by the solar cycle modulation of Lyman α. In comparison, the secular increase in H2O related to methane increase in the atmosphere is about 0.4% /year at all heights in the mesosphere.