The replacement, at least partially, the fossil fuels by renewable ones is a way to remedy the severe situation associated with air pollution and the resulting climate changes. This paper deals with green energy production, i.e. without discharging carbon dioxide in the atmosphere.
The approach is to utilize dissolved hydrogen sulfide in aqueous solution or marine water as a fuel in liquid phase fuel cells. Two-step process is studied: adsorption on activated carbon and consequent oxidation in the fuel cell pattern by catalyst embedded into the matrix of the activated carbon. The generated electromotive force enables the energy supply for fuel cell operation and the excess could be supplied to the electro-distribution grid. Some oxides of transient metals are used as catalysts embedded in the activated carbon. The fuel cell is mem brane-free and it consists anodic compartment where the fluid containing hydrogen sulfide is fed and cathodic one with gas-diffusion electrode containing catalysts enhancing the gas phase oxygen reduction.
The experiments were carried out with aqueous solutions of sodium sulfide at initial concentrations within 20 and 1200 mg dm•3. As supporting electrolyte 16 g dm•3 sodium chloride was used. Both batch and continuous mode of operation were
studied. Ful oxidation of sulfide to sulfate was attained at low initial sulfide concentrations i.e. up to 250 mg ctm•3. At higher sulfide concentrations intermediate reactions occur and products of sulfur at low valences are discovered in the outlet solution i.e. polysulfide, thiosulfate, thionate, sulfite etc.
The approach of liquid phase fuel cell gives the opportunity for simultaneous waste treatment with carbon free methods and electricity generation.
In chemical physics, magnetic isotope effects (MIE) have long been known for a number of the chemical elements. Recently, MIE were discovered in living nature. For example, in experiments with yeast cells S. cerevisiae enriched with different isotopes of magnesium, it was found that the rate constant of post-radiation recovery of the cells, irradiated by X-rays or short-wave UV, is two times higher if the cells are enriched with the magnetic isotope, 25Mg, by comparison with the cells enriched with the nonmagnetic 24Mg (Avdeeva et al. 2019). The catalytic effects of magnetic 25Mg were revealed in enzymatic reactions of ATP hydrolysis driven by myosin. This biomolecular motor performs the mechanical work utilizing the chemical energy of ATP. The rate of ATP hydrolysis with 25Mg, as the enzyme cofactor, is twice higher than the rates with nonmagnetic 24Mg or 26Mg. The effect of the nuclear spin catalysis was also revealed with the magnetic isotope of zinc, 67Zn, as the myosin cofactor (Koltover et al. 2020). As the kinetics phenomenon, MIE indicates that, in the chemo-mechanical process, driven by the biomolecular motor, there is a limiting step which depends on the electron spin state of the reagents, and this “bottle-neck” is accelerated by the nuclear spin of the magnetic 25Mg or 67Zn (Koltover 2023). The nuclear spin catalysis highlight promising applications of the magnetic isotopes in mechanochemistry and medical physics including radiation medicine and biomedical effects of low-frequency electromagnetic fields.
Au nanoparticle (NP)-loaded metal oxides (Au/MOs) are known to exhibit catalytic activity for various important reactions including CO oxidation, hydrogen evolution, alcohol oxidation, hydrogenation, and C–C coupling, while bulk Au is chemically inactive. Au NPs smaller than 10 nm can be formed on the MO surface in a dispersed state by the deposition precipitation (DP) method. The catalytic activity of Au/MOs is strongly affected by the kind of the MO supports as well as the Au particle size. As the support, n-type semiconducting MOs such as TiO2 are most widely used. Although insulating ZrO2-supported Au NP (Au/ZrO2) has also been reported to show catalytic activity for several reactions, the activity is significantly lower than Au/TiO2. Here we report a simply modified DP method (Modified DP) for the preparation of a catalytically active Au/ZrO2 catalyst (Au/ZrO2-MDP). This method involves a preliminary process of the normal DP method where ZrO2 particles are stirred in HAuCl4 solution for a long time. As a test reaction, catalytic production of H2O2 from O2 and HCOOH was carried out at ambient pressure and temperature. HCOOH can be produced from non-edible biomass and from H2 and CO2 under mild conditions. Thus, this process is highly expected as a green and sustainable process for H2O2 production. Au/ZrO2-MDP exhibits an outstanding catalytic activity for H2O2 production. Spectroscopic measurements clarified that the catalytic activity of Au/ZrO2-MDP originates from effective introduction of O-vacancies to the ZrO2 surface.
Iron-based nanomaterials are increasingly used in environmental applications. Different types of iron-based nanomaterials, namely, zerovalent iron nanoparticles, nanoparticles of iron oxides, and nanoparticles prepared from iron salts and natural extracts by green procedures, are briefly indicated in this presentation, together with their preparation, characterization, and applications in the treatment of pollutants in water, with emphasis on the works performed in the last 10 years. In terms of preparation, top-down procedures such as mechanical milling, nanolithography, laser ablation, sputtering, and thermal decomposition, and bottom-up methods such as chemical synthesis, sol-gel, spinning, chemical vapor deposition (CVD), pyrolysis, and biosynthesis are indicated for nanoparticle production. The most commonly used nanomaterials are inorganic nanoparticles based on metal and metal oxides and, among them, iron-based materials have been widely used in the removal of pollutants in water. Among pollutants, halogenated organics, nitroaromatics, pesticides, dyes, antibiotics, halogenated aromatics, phenolic compounds, PCBs, inorganic anions such as nitrate and heavy metals and metalloids (e.g., Hg, Pb, Cr, Cu, As, Ni, Zn, Cd, and Ag); radioisotopes of Ba, TcO4, and U, and antibacterial activity against Gram-positive and negative bacteria have been successfully treated. In some cases, iron-based nanoparticles have been combined with H2O2 in Fenton processes. In this presentation, examples of emergent contaminants are specially discussed. The advantages of using these materials and the need for their improvement to extend their deployment are remarked.
Standard molecular modeling is traditionally done via Schroedinger equations via the help of powerful tools helping to manage them atom by atom often needing High Performance Computing. When functional domains are known and for instance Plasmon measured in their specific effects, a simple Galerkin simulation, touching all possible configurations for those domains, even allows to forecast unknown mutants as in [1] for Sos1, then discovered. Integrating eXplainable AI in the form of understandable rules Machine Learning [2], one can gain knowledge from data in the predicative logic form if ... then ... else..., immediately integrable to the theoretical priors, summing pros of both inference and deduction. When problems are simpler, like discriminating Myeloid from Lymphoid Leukemias from multivariable microarrays genes expression, the above piece-wise affine hyperplanes orthogonal to the salient intervals of the salient variables becomes a simple hyperplane in the orthonormalized
PCA space, thus allowing the (possibly iterated) cascade of k-means and PCA [3] to outperform [4], also evidencing a few discriminating salient genes among which one not yet known in this respect. The same approach have been more recently instrumental in confirming a path in a rare form of leukemia [5], whose few cases available needed our enhancement of their statistical power in order to really got evidence of the suspected and hypothesized said path. When not just one shot of data is available, but a movie of signals in time, a piecewise affine AutoRegression could feed forward identify hybrid dinamic-logical nonlinear hysteretic processes [6] without the need of ill-conditioned inversions and Tickonow regularization [7] as for instance in blood hormone concentration deconvolution [8] in order to resort to the nanometric unaccessible dynamics of pituitary secretion
Standard molecular modeling is traditionally done via Schroedinger equations via the help of
powerful tools helping to manage them atom by atom often needing High Performance Computing.
When functional domains are known and for instance Plasmon measured in their specific effects, a
simple Galerkin simulation, touching all possible configurations for those domains, even allows to
forecast unknown mutants as in [1] for Sos1, then discovered.
Integrating eXplainable AI in the form of understandable rules Machine Learning [2], one can gain
knowledge from data in the predicative logic form
if ... then ... else...,
immediately integrable to the theoretical priors, summing pros of both inference and deduction.
When problems are simpler, like discriminating Myeloid from Lymphoid Leukemias from
multivariable microarrays genes expression, the above piece-wise affine hyperplanes orthogonal to
the salient intervals of the salient variables becomes a simple hyperplane in the orthonormalized
PCA space, thus allowing the (possibly iterated) cascade of k-means and PCA [3] to outperform [4],
also evidencing a few discriminating salient genes among which one not yet known in this respect.
The same approach have been more recently instrumental in confirming a path in a rare form of
leukemia [5], whose few cases available needed our enhancement of their statistical power in order
to really got evidence of the suspected and hypothesized said path.
When not just one shot of data is available, but a movie of signals in time, a piecewise affine
AutoRegression could feed forward identify hybrid dinamic-logical nonlinear hysteretic processes
[6] without the need of ill-conditioned inversions and Tickonow regularization [7] as for instance in
blood hormone concentration deconvolution [8] in order to resort to the nanometric unaccessible
dynamics of pituitary secretion
It is widely believed that pyrolysis of low rank coal is more reliable and cleaner than direct combustion of coal. This study aims to predict the yield of pyrolysis products in an accurate way, and investigate the optimal factors for pyrolysis of coal under isothermal conditions. A new scheme is proposed to predict the composition of pyrolytic products based on a new model for coal pyrolysis. This novel model has included thermal decomposition of coal into primary products such as gases, tar, and char, and further decomposition of the primary tar into char and gases, The extent of primary/secondary reactions is varied according to the affecting factors, such as temperature, pyrolysis time et al. The product yields of pyrolysis are simulated and accessed in a wide temperature range. Useful information is obtained from this model, which compares well with experimental results.
Semiconductor based photochemical and photoelectrochemical water splitting is an ultimate source of hydrogen generation as renewable green energy for tackling the ongoing fuel crisis. g-C3N4 is an ideal candidate for overall water splitting as a result of the excellent alignment of its band edges with water redox potentials. However, a single catalyst with a limited number of active sites does not exhibit significant photo/electrocatalytic activity for hydrogen production. Therefore, we have developed the semiconductor heterostructures of g-C3N4 with CuFe2O4 , Cu2O, CdSe, CdS and MoS2 NPs and QDs as the highly efficient nanocatalysts for enhanced hydrogen evolution reactions. The monophasic heterostructures have been designed in different weight ratios with fairly uniform distribution of nearly spherical particles and high specific surface area which creates an interfacial charge transfer between two semiconductors. As prepared heterostructures showed significant hydrogen evolution which is evident by observing high apparent quantum yield, low onset potential, lower overpotential and high electrochemical active surface area that will be presented in detail.
In sulfuric acid manufacture and hydrogenation of unsaturated hydrocarbons catalyst like nitrogen(II) oxide, platinum and nickel, platinum, or palladium are used. Actually catalysts are not consumed in chemical reactions, they can be used repeatedly over an indefinite period of time. In practice, however, poisons, which come from the reacting substances or products of the reaction itself, accumulate on the surface of solid catalysts and cause their effectiveness to decrease. For this reason, when the effectiveness of a catalyst has reached a certain low level, steps are taken to to purify the catalyst. Commonly encountered poisons include carbon on the silica–alumina catalyst in the cracking of petroleum; sulfur, arsenic, or lead on metal catalysts in hydrogenation or dehydrogenation reactions; and oxygen and water on iron catalysts used in ammonia synthesis.
To solve this problem and purify metal catalyst solvent extraction technique is used. Consider a method, Separation of Platinum(IV) from alloys, Pharmaceuticals, and mutual separation of Platinum,Palladium(II), Nickel using P-Methylphenyl Thiourea (PMPT) by solvent extraction. A method for the solvent extraction spectrophotometric determination has been developed for determination of microgram amount of platinum(IV) using para-methylphenyl thiourea (PMPT) as a chromogenic reagent is developed. The basis of proposed protocol is pink colored Pt(IV)-PMPT complex was formed in 0.03 mol dm?3 potassium iodate media at room temperature and shows maximum absorption at 506nm. The colored complex obeys Beer’s law up to 5.0 ?g cm?3 for platinum. The molar absorptivity and sandell’s sensitivity were found to be 6.78 x 103 dm3 mol?1 cm?1 and 0.029 ?g cm?1 . Stability of platinum(IV)-PMPT complex was >48 hours. Various experimental parameters for the extraction and determination of platinum(IV) have been checked and optimal conditions are developed. The developed method is selective for determination
of platinum(IV) in presence of large number of interfering ions The method finds applications viz. the determination of platinum(IV) from pharmaceutical sample, synthetic mixtures corresponding to alloys, binary and ternary mixtures. The method also permits the sequential separation of palladium(II), platinum(IV) and nickel(II)
Drinking water pollution is one of the global problems that needs to be addressed. The aim of our
research is to develop materials for the treatment of dye effluents. In this case, we have chosen
Engelhard Titanium Silicate 4 (ETS-4), deciding to replace part of the Titanium with Zirconium of
different ratios, for the treatment of crystal violet (CV) and methylene blue (MB) wastewater. Na-
K-ETS-4/xZr with different amount of zirconia were synthesized, the image with 6 wt% Zr was best
for photodegradation of crystal violet from polluted waters, and the materials with 6 and 9 wt% Zr
was best for methylene blue purification. As for 6 wt% Zr for CV we have 76.6 wt% conversion
which is maintained after 5 cycles of regeneration, while for MB we have 86.6 wt% conversion for
6 and 9 wt% Zr, for 6 wt% after cycling we have a decrease to 54.6 wt%, while for 9 wt% Zr we
have a slight decrease in photodegradation to 77.4 wt%. After a simple ethanol wash complete
regeneration of efficiency. Comparison was made of the widely used pseudo first and second order
kinetic models. The kinetic studies showed that the removal of CV and MB was a rapid process,
which obeyed the non-linear pseudo-first-order model. The kinetics of the photodegradation process
for the sample containing 9 wt % Zr (Na-K-ETS-4/9Zr) appeared to be faster than those for the
sample containing 6 wt % Zr for MB. Photodegradation for MB is more efficient than that for CV
This study attempted to identify the active site by developing an eco-friendly antibacterial material to replace the tin compound antifouling agent that disturbs the marine ecosystem and finding the correlation with photocatalytic activity. Cu0.1Zn0.9O nanoparticles containing 10% Cu ions in ZnO were synthesized by hydrothermal synthesis, and Ag nanoparticles (Ag NP) were loaded by size to obtain Ag@Cu0.1Zn0.9O. As a result of conducting hydrogen production performance and antibacterial tests of these catalysts, it was proved that excellent photocatalytic activity does not always provide good antibacterial activity, and reaction sites exhibiting photocatalytic activity and antibacterial activity may not be the same.
The fact that the material has various functions has very industrially useful values such as economy and usability. In this study, we tried to develop a dual-functional photocatalyst that decomposes organic matter using OH radicals in the hole of valence band and reduces heavy metals using electrons of the conduction band. In addition, secondary contamination can be prevented by completely separating and recovering the catalyst used after the catalytic reaction by a magnet.
The synthesized 10% rGO-WO3/Fe3O4 ternary junction catalyst showed effective performance in treating the two pollutants by reducing 100 ppm of malachite green dye and Cr6+ to Cr3+ for 2 hours. The photocurrent of 10% rGO-WO3/Fe3O4 ternary junction photocatalyst increased more than 10 times compared to a single photocatalyst, and photoluminescence decreased more than 7 times. The performance of the photocatalyst is due to the Z-scheme charge transfer. By utilizing the photocatalyst, it is expected to be useful in the environmental industry that can treat various wastewater mixed with heavy metals and organic pollutants.
In this study, the ORR activity of three-way catalysts based on PtNiZn was investigated. Recently, as the importance of ORR catalysts has been highlighted in the field of fuel cells and metal-air batteries, various catalysts have been studied. Catalysts based on Pt show high activity, but development of complexes with other elements is required due to cost andlimited resources. In this study, a catalyst with an appropriate ratio of Pt, Ni, and Zn was synthesized and its activity was evaluated. The synthesized PtNiZn catalyst was prepared in the form of nanoparticles by solvothermal synthesis. The surface and structural properties of this catalyst were analyzed by XRD, TEM and XPS. As a result, the PtNiZn catalyst showed a higher ORR activity than the conventional Pt/C catalyst, which suggests that Ni enhances the electrochemical activity of Pt and Zn enhances stability.