Search results

More over the photocatalytic reduction of water into H2 from aqueous methanol solutions under visible-light irradiation are greater due to the narrow band gap 2.72 eV for single crystalline Bi3NbO7 in the presence of Ni/NiO co-catalyst.
In addition using SrTiO3 hollow microspheres, the photocatalytic activity for reduction of Cr (VI) into Cr (III) were high active when compared with Degussa P25 under 300W Xe arc lamp irradiation.
Ag nanoparticles supported on different materials such as ZrO2, zeolite Y and amorphous silica were prepared by solution phase reduction method for photocatalytic degradation of sulforhodamine B under blue light irradiation [173].
The SEM and EDX data for the Bi2O3 and Au/ Bi2O3 nanorods are shown in Fig. 11.
SEM and EDX data for the Bi2O3 (a,b) and Au/Bi2O3 nanorods (c,d) [Ref: 180] Ref: Ind.

The electrolyte-electrode interface is modeled as a resistor in series with a capacitor.[21] With the EIS data, the frequency-dependent capacitive contribution to the total impedance can be calculated by the following equation: (5) where CC is the fraction of capacitive contribution, the absolute value of the ratio of Im Z, the imaginary part, to |Z|, the modulus of the total impedance.
Using Eq.1-Eq.3, the specific capacitance, specific energy, and specific power of the fabricated BSHs are extracted from CV data.
Thus, these said invariant behavior in the relatively high-frequency regime might not be the major concern in comparison to the data between 10 mHz and 1 Hz.
To facilitate further understanding of the data between 10 mHz and 1Hz, another parameter C` is calculated according to the following equation: (9) Here, C` is called real capacitance, whose unit is F.
Data in these plots are from the EIS measurements on Ti3C2 working electrode.

The data used for modelling, the compressive strength model employed the compressive strength of the concrete (CS) (N/mm2) as the dependent variable, whereas the durability model utilized the sorptivity of concrete (SP) (mm/min0.4).
D3​ (0.080251) contributes positively but is not as dominant as D4​. 3.10.3 Model Performance Evaluation and Validation The performances of the models were evaluated using an R-squared score and validated on the validation data.
The training set was used to fit the regression model (i.e., determine the values of the β coefficients) while the testing set was used to evaluate the model’s predictive accuracy on unseen data.
The performance of the models on the validation data was evaluated using Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) as summarized in Table 4.
Summary of the Regression Models’ Performance Metrics Compressive Strength Model Sorptivity Model Train Test Train Test R-squared Score 0.8270 0.7920 0.1080 -0.2132 MAE 0.5971 1.1567 1.1352 1.3300 RMSE 0.7201 1.6533 1.5415 1.5910 From Table4, the compressive strength model demonstrated a strong predictive capability, with an R² of 82.7% on training data and 79.2% on test data, indicating that laterite properties significantly influence compressive strength.

This work used twice of this data which is 0.76 kWh per day per capita for the computation of energy demand Ed for the population of the location for the given year, Pl.
Data for solar radiation, wind speed and biomass resources adapted from [12, 13, 14].
The mean annual solar radiation data, wind speed and biomass availability for each location were obtained from the literature as shown in table 2.
Data in Brief, 10. 10.1016/j.dib.2018.04.144 [16] http://www.enerdata.net/estore/energymarket/Nigeria/: :text=Nigeria/20Total20Energy /20Consumption,to/20174/20Mtoe/20in/202023 [17] Alireza Tajeddin and Elham Roohi (2019).
Analysis of wind speed data and wind energy potential in three selected locations in South-East Nigeria.

Korschun, et al. [62] explored CSR from a business purchasing context, as they mention factors such as environmental impact of products and production processes, avoiding child labor, stimulating employee volunteerism, codes of conduct and pressures from consumers as drivers of CSR strategies 3.0 Methods We employ two testing methodologies namely simple linear regression and method of least square regression as follows: Simple linear regression Simple linear regression analysis describes the linear relationship between two variables by fitting a straight line through the set of data that best represents them; hence such a line is usually called the line of best fit.
Since and are unknown parameters, they are estimated from sample data.
Geometrically, the least squares equation represents a straight line that best fits the data.
Conditions for Making Inferences in Regression Analysis In regression analysis, we often go beyond the fitting of an equation to data and make inference about the population from which the data were drawn.
For organizations that dutifully engage in proactive corporate social responsibility, they can even benefit in the form of exemptions in policies such as tax reduction and others that can give them some favorable support either in the present or in the future.

However, it was only the further technical accomplishment of the Jenamap p dyn series of interference microscopes by the Carl Zeiss Jena GmbH and the introduction of powerful computers and data analysis [27, 32, 33] that, eventually, enabled the measurement of transient intracrystalline concentration profiles.
The thin lines represent the best fits of the analytical solution (with constant diffusivity and permeability [43]) to the experimental data .
As a unifying feature, both IR micro-imaging and interference microscopy yield integrals over the concentration of the guest molecules in observation direction, as the primary data of the measurement.
Details of data analysis and the different ways leading to the underlying transport parameters, notably to the diffusivities and permeabilities, may be found in refs. [34, 47, 48].
The plain presents the best fit of the experimental data to a function of the mean concentration (ceq + csurf)/2 as a sole parameter.

The lack of thermodynamic and thermophysical data on the properties of alloys is one of the important problems in the development of new advanced materials of a complex chemical composition.
Most of the experimental data were obtained at certain temperatures and pressures.
Analysis of obtained data.
For Ni, Cr, Fe, the changes of which are the most reflexive and significant, the data are given in Table 4.
This is evidenced by the data on the range of distribution of microhardness of the specimens (Table 2) and statistics of the specimens fracture during mechanical tests (Table 3).

From XRD data X-ray diffraction patterns which illustrated the well maintained topological structure during the cation exchange process.
Pai, Synthesis of Cs-Ag/Fe2O3 Nanoparticles Using Vitis labrusca Rachis Extract as Green Hybrid Nanocatalyst for the Reduction of Arylnitro Compounds. 

The diffraction pattern of the products of SHS (50% WC and 50% TiC, simple stirring, the excess carbon black – 2 times) Table 2 shows data on the phase composition of all samples after SHS.
Table 3 presents data on the specific surface area and size of crystallites.
Table 5 presents data on the composition, method of production and concentration of modifiers, as well as Brinell hardness (HB) and hardness change (%) of cast iron samples SCH20.
Table 6 presents data on the composition, method of production and concentration of modifiers, as well as Brinell hardness (HB) and hardness change (%) of samples of cast iron SCH25, treated with these modifiers.
From the data obtained it follows that corrosion resistance, as well as other properties of cast iron, depend on the grade of cast iron, on the composition of the modifier, its quantity and on the aggressive medium.

The inserted blue dash line represented the couple couple sample which mean those sample have both non-VTA and VTA data.
It is convinced by our data that by having the same deposition time, the film quality may be improved to the same as those grown at high temperature (HT) deposition.
As mentioned before that Se element should be appeared in EDX spectrum if this data was confirmed with XRD pattern, surprisingly it is not.
Despite the device was set for a data collection up to a temperature of 8K, but in the real time the lowest temperature point that could be reached was 15K.
In consequent, if there is a transitional forms and symptoms that occurred below 15K automatically became undefined due to imprecise data.