Polyethylene oxide (PEO) complexed with molecular iodine (
I
2
) forming PEO/
I
2
complex composites stand‐free films were investigated using dielectric relaxation, X-ray photoelectron spectroscopy ...(XPS), UV–Vis spectrophotometry, structural and morphological techniques. Scanning electron microscopy was used to monitor the variation in the surface morphology and the related roughness. 2D Energy-dispersive X-ray spectroscopy (EDX) measurements enabled to observe the distribution of iodine on the film surface. High resolution XPS measurements were used to define the iodine anion types and the metallic iodine existence, as well as the relevant concentrations based on the binding energies. The dielectric relaxation measurements were carried out over the frequency range from 0.1 to 10
7
Hz and temperature range from 155 to 330 K. Dielectric loss (ε′′) curves were fitted to the Havriliak–Negami (HN) model for one and/or two relaxation peaks (α and β), with and without the electrical conductivity contribution term, in order to deduce the relaxation time (τ) and the dielectric strengths (Δ
ε
), in addition to the electrical conductivities (
σ
). The temperature-dependent data of β- and σ- relaxations follow the law of Arrhenius thermal activation indicating the presence of typical glass-forming polymers. Δ
ε
of α-relaxation obeys the curvature pattern of Vogel-Tammann-Fulcher (VTF) thermal activation law. The electrical conductivity of the system increases 6000 folds by doping PEO with 5 wt% of iodine at the same temperature (293 K).
Surface studies of developed fingerprints have aided in the elimination of criminal cases before moving to the court. The combination of X-ray photoelectron spectroscopy (XPS) with the aryldiazonium ...gold(III), 4-O2NC6H4N2 +AuCl4 –, surface modifier has been shown to be a novel approach in latent fingerprint detection and development for the quantification of film elements. The robust gold–aryl film was developed on the reducing chemicals excreted in the sebaceous fingerprints without the need for external stimuli and at a lesser extent after contacting the free metal surface. The concurrent reduction of the diazonium functional group and gold(III) from AuCl4‑ developed a robust gold–aryl film, which showed increasing gold(0) quantity in the time range of 30–120 min over copper coins and model flat sheets. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) support the presence of reduced gold on the top of the latent fingerprints and the presence of CuO resulting from the reaction of the diazonium salt with copper metal. This research combines the quantification of deposits using XPS, a surface-sensitive technique for chemical analysis, in addition to surface imaging.
Modified colloids and flat surfaces occupy an important place in materials science research due to their widespread applications. Interest in the development of modifiers that adhere strongly to ...surfaces relates to the need for stability under ambient conditions in many applications. Diazonium salts have evolved as the primary choice for the modification of surfaces. The term “diazonics” has been introduced in the literature to describe “the science and technology of aryldiazonium salt-derived materials”. The facile reduction of diazonium salts via chemical or electrochemical processes, irradiation stimuli, or spontaneously results in the efficient modification of gold surfaces. Robust gold–aryl nanoparticles, where gold is connected to the aryl ring through bonding to carbon and films modified by using diazonium salts, are critical in electronics, sensors, medical implants, and materials for power sources. Experimental and theoretical studies suggest that gold–carbon interactions constructed via chemical reactions with diazonium salts are stronger than nondiazonium surface modifiers. This invited feature article summarizes the conceptual development of recent studies of diazonium salts in our laboratories and others with a focus on the surface modification of gold nanostructures, flat surfaces and gratings, and their applications in nanomedicine engineering, sensors, energy, forensic science, and catalysis.
ABSTRACT
Gas metallicity (Z) and the related dust-to-gas ratio (fd) can influence the growth of H ii regions via metal line cooling and ultraviolet (UV) absorption. We model these effects in ...star-forming regions containing massive stars. We compute stellar feedback from photoionization and radiation pressure (RP) using Monte Carlo radiative transfer coupled with hydrodynamics, including stellar and diffuse radiation fields. We follow a $10^{5}\, \mathrm{M}_{\odot }$ turbulent cloud with Z/Z⊙ = 2, 1, 0.5, and 0.1, and $f_\textrm{d} = 0.01\, Z/Z_{\odot }$ with a cluster-sink particle method for star formation. The models evolve for at least 1.5 Myr under feedback. Lower Z results in higher temperatures and therefore larger H ii regions. For Z ≥ Z⊙, RP (Prad) can dominate locally over the gas pressure (Pgas) in the inner half-parsec around sink particles. Globally, the ratio of Prad/Pgas is around 1 (2 Z⊙), 0.3 (Z⊙), 0.1 (0.5 Z⊙), and 0.03 (0.1 Z⊙). In the solar model, excluding RP results in an ionized volume several times smaller than the fiducial model with both mechanisms. Excluding RP and UV attenuation by dust results in a larger ionized volume than the fiducial case. That is, UV absorption hinders growth more than RP helps it. The radial expansion velocity of ionized gas reaches +15 km s−1 outwards, while neutral gas has inward velocities for most of the runtime, except for 0.1 Z⊙ that exceeds +4 km s−1. Z and fd do not significantly alter the star formation efficiency, rate, or cluster half-mass radius, with the exception of 0.1 Z⊙ due to the earlier expulsion of neutral gas.
Polyethylene oxide‐poly(3,4‐ethylenedioxythiophene) (PEO‐PEDOT) nanocomposite films ‐ incorporated with NiZnFeO4 nanoparticles (NPs) were deposited using a dip‐coating technique. X‐ray diffraction ...(XRD) analysis revealed peaks at 35.4, 43.2, 54.5, and 56.3° diffraction angles, corresponding to NiZnFeO4NPs diffraction planes of 311, 400, 422, and 511, respectively. The PEO‐PEDOT film exhibited a smooth amorphous nature with a sheet nanostructure behavior. The incorporation of NiZnFeO4NPs NPs into the PEO‐PEDOT nanocomposite films led to an increase in surface roughness and thermal stability. The nanocomposite films also exhibited sheet nanostructure behavior as observed by SEM micrographs. The bandgap energies of the films, as deduced from the Tauc plot, exhibited a monotonic decrease from 3.91 to 3.60 eV as the NiZnFeO4NPs concentration increased from 0 to 8 wt%. A mathematical model was formulated to predict the bandgap energies versus NiZnFeO4NPs concentration. Additionally, the electrical conductivity of the nanocomposite films increased monotonically from 0.46 to 1.30 mS cm−1 as the NiZnFeO4NPs concentration increased from 0 to 8 wt%, as determined by 4‐point probe. The observed correlation between the optical and electrical properties of the nanocomposite films indicates promising prospects for utilizing these materials in optoelectronic devices.
Characterizations of PEO‐PEDOT/NiZnFeO4 NPs nanocomposite films.
Bamboo, an abundant and inexpensive natural resource in Malaysia was used to prepare activated carbon by physiochemical activation with potassium hydroxide (KOH) and carbon dioxide (CO
2) as the ...activating agents at 850
°C for 2
h. The adsorption equilibrium and kinetics of methylene blue dye on such carbon were then examined at 30
°C. Adsorption isotherm of the methylene blue (MB) on the activated carbon was determined and correlated with common isotherm equations. The equilibrium data for methylene blue adsorption well fitted to the Langmuir equation, with maximum monolayer adsorption capacity of 454.2
mg/g. Two simplified kinetic models including pseudo-first-order and pseudo-second-order equation were selected to follow the adsorption processes. The adsorption of methylene blue could be best described by the pseudo-second-order equation. The kinetic parameters of this best-fit model were calculated and discussed.
We synthesize and optically characterize pure PMMA and PMMA incorporated with metal oxides nanoparticles (MO NPs) such as ZnO, CuO, TiO2 and SiO2 NPs nanocomposite thin films with weight ...concentration of 10% using dip-coating technique. SEM images of MO NPs show that all NPs have nearly an average size of around 50 nm. The optical parameters such as, optical parameters (n and k), optoelectronics properties, dispersion, band-gap energy and band structure of as-prepared nanocomposite thin films were determined by analyzing the transmittance and reflectance spectra. Mainly, optical band-gap energy (Eg) and the thickness of thin films are evaluated to a high degree of accuracy by utilizing Q-functional derived using a mathematical model recently published. The Q(E) is a functional containing experimental transmission and reflection data and the incident photon energy. The Eg value of un-doped PMMA thin films is found to be 4.273 eV. This value decreases as pre-selected MO NPs are introduced into thin films. These values are in excellent agreement with those determined using Tauc method. The FTIR technique is employed to elucidate the vibrational bands of the nanocomposites and the intermolecular bonding between PMMA matrix and the MOs NPs. Thermal stability is investigated by employing thermogravimetric analysis (TGA) at temperatures up to 400 °C. The obtained TGA thermograms indicate that adding MOs NPs to PMMA yield thin films of better thermal stability. The obtained doped thin films show a great promise for fabricating high-efficient optoelectronic devices.
Polymethyl methacrylate (PMMA); metal oxides nanoparticles (MO NPs); zinc oxide (ZnO); copper oxide (CuO); silicon dioxide (SiO2); Titanium dioxide (TiO2); optical properties; bandgap energy; FTIR; TGA
The process evaluation of zinc oxide nanoparticle
(
ZnO NP) was added to enhance the degradation of petroleum wastewater (PWW) fermentation system with different mixing ratios for enhancing methane ...production. The results showed that the highest methane yield and total solids (TS) removal ratio reached 485 mL/g-VS L PWW added and 81.9% at the ZnO NP g-VS L PWW ratio of 4.5:15, respectively. The proposed model CO
2
sequester 545 mL CO
2
/L PWW, production rate 750 mL CH
4
g-VS L PWW/h, and CH
4
yield was 4.85 L CH
4
g-VS L PWW at 4.5:15 of ZnO NP g-VS L PWW. The kinetic analysis indicated that the modified Gompertz model best fitted the actual evolution of methane yields, as evidenced by the low root mean square prediction error (RMSPE) as well as high correlation difference between (Diff.%) the predicted and actual values. The parameters analyses were highlighted that the PWW digestion with ZnO NP substantially enhanced the hydrolysis rate (
k
hyd
), methanogenesis potential (
f
d
), lag phase time h (
λ
), and methane production rate (Rm) of PWW. The evolution of soluble metabolites, utilization of ZnO NP and carbohydrates were also improved by co-fermentation.
Quinoline Silicate Lewatit Composite and activated Lewatit were prepared and tested for uranium removal from sulfate solution. Uranium sorption capabilities of the tested adsorbents was estimated ...under different conditions; uranium initial concentration, pH, contact time, temperature, adsorbent dose and interfering ions. Experimental data obeyed Langmuir isotherm model with 69.44 mg/g and 217.39 mg/g theoretical capacity for AL and QSLC, respectively. Thermodynamic studies indicated an exothermic behavior with a decrease in randomness. Kinetics studies showed that the adsorption process obeyed pseudo-second order model. Optimum conditions were carried out for uranium recovery from a rock sample, producing uranium concentrate with 93.33% purity.
With the development of deep representation learning, the domain of reinforcement learning (RL) has become a powerful learning framework now capable of learning complex policies in high dimensional ...environments. This review summarises deep reinforcement learning (DRL) algorithms and provides a taxonomy of automated driving tasks where (D)RL methods have been employed, while addressing key computational challenges in real world deployment of autonomous driving agents. It also delineates adjacent domains such as behavior cloning, imitation learning, inverse reinforcement learning that are related but are not classical RL algorithms. The role of simulators in training agents, methods to validate, test and robustify existing solutions in RL are discussed.
PDF
