Krzysztof Krawczyk

With global plastic production creating immense environmental pressure and conventional recycling methods facing limitations, advanced chemical recycling techniques are crucial. This paper presents details of the design, construction, and operation of two fluidized reactors: a laboratory-scale (LS) reactor and a large-scale laboratory reactor (LSLR) for the catalytic pyrolysis of mixed plastic waste. A waste stream simulating municipal collection, consisting of polyethylene (PE), polypropylene (PP), polyethylene terephthalate (PET), and polystyrene (PS), was processed using a custom Ni/γ-Al₂O₃ catalyst and an industrial G-0110 catalyst in a two-stage system. The large-scale reactor demonstrated high efficiency, achieving a 90% yield of valuable pyrolysis oil and waxes, a 2% yield of syngas, and an 8% yield of solid residue containing mainly carbon at operating temperatures between 400 and 453 °C. The resulting liquid and wax fractions contained a rich mixture of aliphatic and aromatic hydrocarbons (such as styrene, indene, benzoic acid, toluene, and cumene), confirming their potential as a feedstock for the chemical industry. These results establish that two-stage catalytic pyrolysis in a fluidized bed reactor is a highly effective and promising technology for upcycling mixed plastic waste into valuable resources.

Nanomaterials are the subject of an increasingly growing number of investigations. Due to their unique characteristics, they have found wide applications in disciplines like electronics, catalysis, and medicine. In the field of catalysis, one can mention their application for the photocatalytic removal of various contaminants, both inorganic (e.g., toxic chromates) and organic (pesticides, dyes, pharmaceuticals, etc.). Such applications are important because the contamination of the natural environment is constantly growing. Distinct nanomaterials, such as quantum dots, have been widely utilized for photo-based wastewater treatment, but the current research activity is directed toward investigations of combined nanometric heterostructures which exhibit additional and useful properties in comparison with standalone components. However, the preparation of such heterostructures may be demanding and more complicated than that of standalone components, and the mechanism of improved photocatalytic performance may vary among different types of heterostructures. The aim of this review is to fill the existing gap in the literature and present mechanisms (type-II, Z-scheme, and S-scheme), methods of preparation (sol–gel, hydrothermal, solvothermal, sonochemical methods, and others), and applications of nanometric heterostructures in the photocatalytic degradation of organic pollutants.

The development of alternative energy is crucial to realizing the goals of the Paris Agreement. Hydrogen is a key energy carrier, and ammonia is considered its practical storage medium due to its high H₂ content and efficient storage and transportation. However, efficient NH₃ decomposition methods are needed to recover stored hydrogen. Plasma-assisted decomposition offers a potential solution, but high energy consumption, mainly due to inefficient power supply systems, remains a challenge. This study examines the impact of varying the driving frequency of a gliding discharge plasma system on ammonia decomposition, comparing low-frequency 50 Hz and high-frequency 20 kHz power supplies. Results show that high-frequency plasma enhances electron density and energy distribution, increasing the amount of vibrationally excited nitrogen molecules. This improves catalyst activation, leading to higher ammonia conversion and hydrogen production. Compared to the thyristor-powered system, the high-frequency system increased ammonia decomposition productivity by 30% and reduced energy consumption by 36% using a coprecipitated catalyst. These findings emphasize the importance of a plasma generator optimizing plasma-assisted ammonia decomposition and improving efficiency in hydrogen production.

Nanomaterials are interesting due to their unexpected and unique properties arising from phenomena occurring at the so-called mesoscale (that is, between single atoms and bulk solids). Among nanomaterials, one may distinguish quantum dots, which are highly crystalline nanocrystals with sizes up to c.a. 10 nm. Due to the quantum confinement effect, quantum dots exhibit extraordinary electronic and optical properties and may be utilized in photocatalysis. Semiconducting quantum dots may absorb photons, which results in the excitation of electrons from valence to conducting bands. Excited electrons in the conducting band and positive holes in the valence band may interact with chemical molecules (e.g., with water molecules), forming highly reactive radicals. Consequently, quantum dots may be utilized in advanced oxidation processes based on the action of light (i.e., photo-based advanced oxidation processes). Furthermore, quantum dots have advantages, such as having a tunable energy band gap and relative cost-effectiveness. Advanced oxidation processes are very important in the context of the constantly increasing pollution of the natural environment. Contaminants of emerging concern, such as pesticides, endocrine-disrupting compounds, and flame retardants, are still being detected in naturally present water. Such compounds may be degraded using advanced oxidation processes, utilizing quantum dots as photocatalysts. However, many operational parameters (such as quantum dots’ properties, including the means of their preparation) influence the efficiency of such processes; thus, detailed studies are being conducted.

Nanomaterials, including quantum dots, have gained more and more attention in the past few decades due to their extraordinary properties that make them useful for many applications, ranging from catalysis, energy generation and storage, biotechnology, and medicine to quantum informatics. Mathematical descriptions of the phenomena in which nanostructures are involved are of great demand because they may be utilized for the purpose of controlling these phenomena (e.g., the growth of nanostructures with certain sizes, shapes, and other properties). Such models may be of distinct nature, including calculations from first principles, ordinary and partial differential equations, and machine learning models (including artificial intelligence) as well. The aim of this article is to review the most important and useful computational and mathematical approaches for the description and control of processes involving nanostructures.

The chemical transport method is a process that occurs naturally; however, it is also very useful in the chemical laboratory environment for the synthesis of inorganic crystals. It was successfully used for the syntheses of simple and complex inorganic compounds, from binary (e.g., ZnS, CdSe) to quaternary (e.g., Cu₂ZnSnS₄) compounds. Many experimental parameters influence the quality of products of chemical transport reactions, and among them, one may distinguish the used precursors and applied temperature gradient. The careful selection of experimental conditions is crucial for the production of high-quality crystals. Mathematical descriptions of the chemical transport phenomena, however, may potentially help in the design of proper conditions.

The crystalline state of matter serves as a reference point in the context of studies of properties of a variety of chemical compounds. This is due to the fact that prepared crystalline solids of practically useful materials (inorganic or organic) may be utilized for the thorough characterization of important properties such as (among others) energy bandgap, light absorption, thermal and electric conductivity, and magnetic properties. For that reason it is important to develop mathematical descriptions (models) of properties and structures of crystals. They may be used for the interpretation of experimental data and, as well, for predictions of properties of novel, unknown compounds (i.e., the design of novel compounds for practical applications such as photovoltaics, catalysis, electronic devices, etc.). The aim of this article is to review the most important mathematical models of crystal structures and properties that vary, among others, from quantum models (e.g., density functional theory, DFT), through models of discrete mathematics (e.g., cellular automata, CA), to machine learning (e.g., artificial neural networks, ANNs).

A sonochemical synthesis of SnS₂ quantum dots using acetone as a solvent is investigated. Two different tin sources (SnCl₂∙2H₂O or SnCl₄∙5H₂O) as well as two different sulfur sources (thioacetamide or Na₂S₂O₃) were applied. The sonication time was also varied between 60 and 120 min. Resulting products of syntheses were characterized with the following techniques: powder X-ray diffraction, electron microscopy (SEM and HR-TEM), Raman and FT-IR spectroscopies, the Tauc method, and X-ray photoelectron spectroscopy. Obtained SnS₂ nanostructures were in the form of quantum dots in the case of synthesis lasting 60 min (size of crystallites in the range of 3.5–7 nm) and in the form of elongated nanorods of length ca. 25–30 nm and width of 5–6 nm in the case of synthesis lasting 120 min. XPS analyses revealed that the surface of the obtained products contained a significant amount of tin at the second oxidation state (i.e., SnS). The quantum dots produced in the synthesis lasting 60 min showed a value of energy bandgap of 2.7 eV indicating potential applications in photocatalysis.

A sonochemical synthesis of SnS2 quantum dots using acetone as a solvent is investigated. Two different tin sources (SnCl2∙2H2O or SnCl4∙5H2O) as well as two different sulphur sources (thioacetamide or Na2S2O3) were applied. The sonication time was also varied between 60 and 120 minutes. Resulting products of syntheses were characterized with the following techniques: powder X-ray diffraction, electron microscopy (SEM and HR-TEM), Raman and FT-IR spectroscopies, the Tauc method, and X-ray photoelectron spectroscopy. Obtained SnS2 nanostructures were in the form of quantum dots in the case of synthesis lasting 60 minutes (size of crystallites in the range of 3.5 – 7 nm) and in the form of elongated nanorods of length c.a. 25-30 nm and width of 5-6 nm in the case of synthesis lasting 120 minutes. XPS analyses revealed that the surface of the obtained products contained significant amount of tin at the second oxidation state (i. e. SnS). The quantum dots produced in the synthesis lasting 60 minutes showed value of energy bandgap of 2.7 eV indicating potential applications in photocatalysis.

Sonochemical synthesis is becoming a popular method of preparing various nanomaterials, including metals, carbons, oxides, and chalcogenides. This method is relatively cheap and responds to the challenges of green chemistry as it typically does not involve high temperatures, high pressures, inert atmospheres, or long reaction times in comparison to other conventional methods. The utilization of ultrasound in synthesis makes the elimination of toxic solvents possible, as well as the execution of the synthesis without the use of reducing and stabilizing agents, while receiving products with the same or even better properties. The application of ultrasound allows for the synthesis of various nanomaterials with different properties for use in fields such as catalysis, electrochemistry, medicine, and biosensors. The final product is influenced by multiple variables such as temperature, pH, reagents, capping agents, time of reaction, and the addition of dopants.