Sodium Alginate/bentonite clay composites of different compositions were prepared by solution casting method. The electrical properties (Conductivity, Dielectric constant) of the composites were investigated by standard methods with Impedance Analyzer. The electrical properties were found to improve with the incorporation of bentonite clay. The thermal, physical and mechanical properties of sodium alginate/bentonite clay composite were investigated by Thermo-Mechanical Analyzer (TMA), X-ray Deffraction (XRD), and Universal Testing Machine respectively. . Tensile Strength (TS) and Elongation at break (Eb) of 2% clay containing composite film were found to be 7.6 MPa and 55% respectively. The XRD demonstrates the enhancing crystallinity of sodium alginate/bentonite clay composite with the increasing clay content. TMA results showed a higher thermal stability in the composite. Water absorption properties of the sodium alginate/clay composite were studied and found to decrease with the increase of clay content. . The inter action between sodium alginate and bentonite clay were studied by Fourier transform infrared spectroscopy (FT-IR). All of the results indicate that the developed composite is promising for use in a wide variety of optoelectronic applications.
The convection differential models play an essential role in studying different chemical process and effects of the diffusion process. This paper intends to provide optimized numerical results of such equations based on the conformable fractional derivative. Subsequently, a well-known heuristic optimization technique, differential evolution algorithm, is worked out together with the Taylor's series expansion, to attain the optimized results. In the scheme of the Taylor optimization method (TOM), after expanding the functions with the Taylor's series, the unknown terms of the series are then globally optimized using differential evolution. Moreover, to illustrate the applicability of TOM, some examples of linear and non-linear fractional convection diffusion equations are exemplified graphically. The obtained assessments and comparative demonstrations divulged the rapid convergence of the estimated solutions towards the exact solutions. Comprising with an effective expander and efficient optimizer, TOM reveals to be an appropriate approach to solve different fractional differential equations modeling various problems of engineering.
A break
in the traditional pore morphology approach in anodic alumina is presented
here to see its niche merit over the conventional sensors for water
vapor detection. The cylindrical pore structure was replaced with
a normal cone for trace-level and inverse cone for RH-level detection.
The normal conical pore was fabricated by sheer manipulation of the
reaction rates of electrolytes, anodic polarization, rate and time;
the procedure was reversed in the case of the inverse cone structure.
A sensor with a normal cone geometry exhibits excellent response at
the ppm level and slightly extended to low RH level with a detection
range of 120 ppm–30% RH, having response and recovery times
of 6 and 255 s, measured at 120 ppm. Lowering of the minimum detection
limit further requires alteration of the conical geometric parameters,
in tandem with the molecular dynamics of water vapor molecules within
the pore. In contrast, a sensor developed from an inverse conical
structure shows response only at the RH level, from 20% RH to 90%
RH with response and recovery times of less than 60 s over the entire
range. Limitations such as nonlinear response, large response-recovery
time, and high hysteresis as observed in conventional anodic alumina-based
humidity sensors have been removed. The sensor response in conical
and inverse conical pore morphologies is compared with that of standard sensors having a cylindrical
pore morphology, with a top pore diameter identical with that of the
reported sensors. The standard sensors were found to detect in the
RH range only, with response and recovery times below 20s. The sensing
mechanisms in both structures have been suitably demonstrated and
ratified with experimental data. Trace level detection is interpreted
with the statistical probabilistic approach in the light of the kinetic
theory of gases and Brownian energy. A correlation between top surface
pore diameter (through which water molecules enter) and the optimized
mean free path of vapor molecule is established, and its effectiveness
has been demonstrated for humidity detection at a trace level. The
results are encouraging, and the same concept may be tried for the
detection of other gaseous stimuli, including organic vapors.
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