Mass Fraction Research Articles

CFD modeling of spray drying of fresh whey: Influence of inlet air temperature on drying, fluid dynamics, and performance indicators

Whey is a very perishable food and a potent source of protein. It might be more commercialized through the process of spray drying, which would enhance its shelf life. No CFD computational models applied to the drying of fresh sweet whey have been reported in the literature to investigate transport phenomena in spray dryers and to predict crucial design parameters such as deposition, powder recovery, and drying efficiency. Using an Eulerian-Langragean technique, the behavior of multiphase flow as well as heat and mass transfer were investigated. The influence of the inlet air temperature was evaluated in relation to the velocity profiles of the continuous and discrete phases, the residence time distribution, the particle diameter formed, the air temperature near the injection zone, the particle temperature, and the mass fraction of evaporated water. Furthermore, performance parameters such as powder recovery, particle deposition, and drying efficiency were projected for varied air inlet temperatures. The velocity, residence time, and particle size distribution patterns were similar for the different air inlet temperatures. Greater variations might be noticed in the injection zone, especially in the temperature and mass fraction profiles. The lowest drying temperature resulted in the lowest particle deposition and the best thermal efficiency, making it the optimal process condition. This investigation can serve as a benchmark for the design of optimized spray dryers with greater thermal efficiency and yield to produce powdered whey.

Nickel recovery in ferronickel concentrate by green selective reduction of nickel laterite

Nickel laterite is typically processed into ferronickel through a pyrometallurgical method involving high temperatures and the use of fossil fuels, such as coals or cokes. Unfortunately, this process releases emissions like CO2, SO2, and NOx into the environment. This study explores a sustainable approach for nickel laterite processing by investigating low-temperature selective reduction using various biomass reductants. The materials, including saprolitic nickel ore and biomass types (palm kernel shell charcoal or PSC, lamtoro wood charcoal, coconut shell charcoal, and rubber wood charcoal), undergo pelletization, selective reduction at 1150 °C, and wet magnetic separation. PSC biomass is superior to other biomass due to its 217.2 m2/g specific surface area value. Optimal conditions were achieved using 0.3 stoichiometric PSC, along with the addition of 10 wt% of sodium sulfate as an additive. This has led to a nickel mass fraction of 26.0 wt% and a recovery rate of 27.4 %.

Performance optimization of latent heat storage device based on surrogate-assisted multi-objective evolutionary algorithm and CFD method

The design of fin structures and the formulation of heat conductivity enhancers have always been critical factors influencing the performance of latent heat storage devices. However, achieving the optimal parameters of fin structures and the fraction of heat conductivity enhancers when adjusting multiple parameters simultaneously remains a time-consuming and labor-intensive task. In this paper, a combination of machine learning methods and computational fluid dynamics (CFD) was employed to optimize the parameters of fin structures and the mass fraction of expanded graphite with minor computational resources and time costs, thereby obtaining a set of Pareto optimal latent heat storage (LHS) devices that simultaneously considers energy storage power and energy storage capacity. The combination essentially is a surrogate assistant multi-objective evolutionary optimization algorithm, which utilizes batch recommendation strategies to recommend multiple high-quality candidate solutions that achieve a balance between two conflicting optimization objectives in CFD simulations. This method significantly reduces the number of model iterations and saves the time and computational resources required for multi-objective optimization. The results showed that the proposed algorithm only required 80 cases of CFD calculations to obtain two well-fitted Gaussian process models, leading to a 91 % improvement in computational efficiency. According to the recommendations from the algorithm, the LHS device with 78 fins of 2.0 mm thickness and 20 % mass fraction of expanded graphite could achieve the optimal trade-off of energy storage power and energy storage capacity. Compared to the prototype, the energy storage power and total energy storage capacity increased by 46.7 % and 22.1 %, respectively. The method proposed in this study can provide guidance for the optimal configuration design of LHS devices.

The role of puff volume in vaping emissions, inhalation risks, and metabolic perturbations: a pilot study

Secondhand vaping exposure is an emerging public health concern that remains understudied. In this study, saliva and exhaled emissions from ENDS users (secondhand) and non-ENDS users (baseline) were collected, firsthand emissions were generated using an automated ENDS aerosol generation system programmed to simulate puffing topography profiles collected from ENDS users. Particulate concentrations and sizes along with volatile organic compounds were characterized. We revealed puffing topography metrics as potential mediators of firsthand and secondhand particle and chemical exposures, as well as metabolic and respiratory health outcomes. Particle deposition modeling revealed that while secondhand emissions displayed smaller deposited mass, total and pulmonary particle deposition fractions were higher than firsthand deposition levels, possibly due to smaller secondhand emission particle diameters. Lastly, untargeted metabolomic profiling of salivary biomarkers of lung injury due to firsthand ENDS exposures revealed potential early indicators of respiratory distress that may also be relevant in bystanders exposed to secondhand vaping scenarios. By leveraging system toxicology, we identified 10 metabolites, including leukotriene D4, that could potentially serve as biomarkers for ENDS use, exposure estimation, and the prediction of vaping-related disease. This study highlights characterization of vaping behavior is an important exposure component in advancing our understanding of potential health effects in ENDS users and bystanders.

Kinetic Properties of Combustion and Pyrolysis of Masson Pine with Synergistic Flame Retardancy by GUP-APP-silica Sol

ABSTRACT In order to investigate the effect of guanylurea phosphate-ammonium polyphosphate-silica sol on the combustion and pyrolysis characteristics of Masson Pine, UL-94 horizontal and vertical burner, LOI tester, cone calorimeter, and thermogravimetric analysis were used to study the flame retardant wood, and Coats-Redfern model was used to analyze its pyrolysis kinetics. The results showed that the combined use of guanylurea phosphate-ammonium polyphosphate-silica sol had a significant synergic flame retardant effect on Masson pine. When the mass ratio of guanylurea phosphate, ammonium polyphosphate, and silica sol was 2:1:1, the heat release rate and total heat release of flame retardant pine were decreased by 54.7% and 44.7% compared with pure Masson pine, and the LOI was increased by 77.8% compared with the control group. In addition, the addition of silica sol in the flame retardant reduces the effect of flame retardant on the mechanical properties of wood. Raman analysis of carbon layer showed that the R-value of char residue decreased by 5% and 13% when the mass fraction ratio of guanylurea phosphate, ammonium polyphosphate, and silica sol was 5:1:2 and 2:1:1, respectively, indicating that the compound flame retardant effectively promoted the conversion of amorphous carbon into graphite structure. The TG results of the 5:1:2 and 2:1:1 ratios of guanylurea phosphate, ammonium polyphosphate, and silica sol groups showed that the pyrolysis temperature of flame-retardant pine advanced by about 100°C at the heating rate of 15 ℃/min, and the final char residue rate and apparent activation energy were 15.22%, 18.61%, 24.35 kJ/mol, and 23.76 kJ/mol, respectively. These results indicated that the synergistic flame retardant system of guanylurea phosphate-ammonium polyphosphate-silica sol reduced the apparent activation energy of pine pyrolysis, effectively inhibited the pyrolysis of Masson Pine, and enhanced the thermal stability, char forming ability, and flame retardant property.

A hybrid machine learning-CFD method for the innovative analysis of Al2O3 nanoparticle deposition in shell-and-tubes heat exchangers

This study examines the intricate dynamics surrounding the deposition of Al2O3 nanoparticles within a heat exchanger, with the aim of optimizing heat transfer efficiency and gaining insights into gas dynamics. A comprehensive investigation of various parameters is conducted, including nanoparticle diameter ranging from 10 to 100 nm, heat flux variations from 500 to 3000 W/m2, Reynolds numbers spanning from 308 to 1540, and mass fractions ranging from 0.5 to 8 %. The methodology integrates machine learning algorithms with Eulerian and Lagrange methods, leveraging Python programming to deepen the understanding of complex deposition processes. Through the integration of random forest algorithms and SHAP values, the study achieves a model accuracy of 96.74 %, supported by minimal mean absolute error (6E-06) and root mean square error (2.5E-03). Key findings reveal the profound impact of heat flux, particularly at 3000 W/m2, on enhancing nanoparticle deposition. Furthermore, a direct correlation is observed between mass fraction and sedimentation, peaking at a mass fraction of 8 %. In laminar flow regimes, the Reynolds number profoundly influences sedimentation, with the sedimentation rate reaching its apex as the Reynolds number decreases. The diameter of nanoparticles also emerges as a crucial factor, with larger diameters correlating with increased sedimentation.

A design kinetic and hydrodynamic study of a coupled dual fluidized bed MTO reactor-regenerator system

The methanol-to-olefin (MTO) process, employing a dual-fluidized bed system, has introduced a new and reliable route for producing light olefins. This study intends to employ a comprehensive approach to simultaneously design and evaluate the reactor and regenerator performance. Namely, an inclusive design for a pilot-scale MTO system, encompassing the reactor, regenerator, interconnected catalyst transfer pipelines, and other critical operational aspects, is presented. The computational fluid dynamics (CFD) method using the Eulerian-Eulerian model was used to evaluate hydrodynamics, while the coupled reactor-regenerator kinetic model was developed by combining reaction kinetics with the two-phase model. The models were validated against experimental data and demonstrated a promising agreement. More importantly, an innovative procedure was devised to apply these modelling techniques to design this dual-fluidized bed system—the final design for the 10 kg catalyst inventory in the reactor at the pilot scale. The system achieves methanol conversion of 98.87 %, with ethylene and propylene product mass fractions of 45.51 % and 37.79 %, respectively.

The influence of the molecular structure of binary block‐type styrene‐butadiene rubber on dynamic mechanical properties under normal and high‐pressure conditions

AbstractThrough anionic two‐stage polymerization, block‐type styrene‐butadiene rubber (SSBR) with systematically regulable low‐temperature loss peaks is successfully prepared. The influence of 1,2‐Bd unit in the soft segment of block‐type SSBR on mechanical properties, dynamic mechanical properties, and microscopic morphology is studied, while pressure factors are introduced into dynamic mechanical studies. The block‐type SSBR with a soft segment containing 21.9 wt% of 1,2‐Bd exhibits the highest tensile strength, elongation at break, and tear strength. Under atmospheric pressure, the soft segment 1,2‐Bd unit influences the dynamic mechanical properties by altering the chain segment's motion loss capability. As the mass fraction of 1,2‐Bd increases from 21.9 to 58.6 wt%, tanδmax increases, the glass transition temperature of the soft segment increases from −59.0 to −18.9°C. Additionally, influenced by thermodynamic compatibility, the microscopic morphology transitions from strong separation to weak separation. Pressure affects dynamic mechanical properties by altering the free volume of the chain segments. Pressure reduces tanδmax, increases Tg, and raises the average Tg of the soft segment by 11°C. The K value of the linear equation representing the relationship between the soft segment Tg and the mass fraction of 1,2‐Bd is unaffected by pressure.

Characterization of occupational inhalation exposures to particulate and gaseous straight and water-based metalworking fluids

Exposure assessments to metalworking fluids (MWF) is difficult considering the complex nature of MWF. This study describes a comprehensive exposure assessment to straight and water-based MWFs among workers from 20 workshops. Metal and organic carbon (OC) content in new and used MWF were determined. Full-shift air samples of inhalable particulate and gaseous fraction were collected and analysed gravimetrically and for metals, OC, and aldehydes. Exposure determinants were ascertained through observations and interviews with workers. Determinants associated with personal inhalable particulate and gaseous fractions were systematically identified using mixed models. Similar inhalable particle exposure was observed for straight and water-based MWFs (64–386 µg/m3). The gaseous fraction was the most important contributor to the total mass fraction for both straight (322–2362 µg/m3) and water-based MWFs (101–699 µg/m3). The aerosolized particles exhibited low metal content irrespective of the MWF type; however, notable concentrations were observed in the sumps potentially reaching hazardous concentrations. Job activity clusters were important determinants for both exposure to particulate and gaseous fractions from straight MWF. Current machine enclosures remain an efficient determinant to reduce particulate MWF but were inefficient for the gaseous fraction. Properly managed water-based MWF meaning no recycling and no contamination from hydraulic fluids minimizes gaseous exposure. Workshop temperature also influenced the mass fractions. These findings suggest that exposures may be improved with control measures that reduce the gaseous fraction and proper management of MWF.

Thermal Management of Electronics under Cyclic Heat Loads Using Graphite-Assisted Heat Sink

The primary objective of this experimental study is to establish a methodology for enhancing the operational duration and concurrently reducing thermal fluctuations within cyclically functioning electronic devices. In instances where electronic devices operate with intermittent duty cycles, they are susceptible to temperature fluctuations. This, in turn, can induce thermal fatigue, ultimately posing a risk of malfunction. This study introduces a novel square-shaped heat sink design integrated with phase change material (PCM) and enhanced by vertical fins. The experimental evaluation involves subjecting this design to various heat loads characterized by sinusoidal, triangular, sawtooth, and square profiles. Initially, when different constant heat load values were employed, surprisingly, despite its lower melting point temperature, Eicosane consistently outperformed Docosane by a remarkable 37% in terms of heat sink performance in enhancing operating time. However, when cyclic heat loads with intermittently varying profiles were introduced, Docosane demonstrated superior performance. To extend the operational time and improve thermal management, expanded graphite was introduced as a thermal conductivity enhancer into PCMs at various mass fractions. Four distinct PCM mixtures were prepared, each with different expanded graphite (EG) proportions, namely: 70% PCM-30% EG, 75% PCM-25% EG, 80% PCM-20% EG, and 90% PCM-10% EG. These mixtures were rigorously tested under the cyclic heat loads defined in the study.

A double-sided coating paper antibacterial indicator card based on polyvinyl alcohol/sodium carboxymethyl cellulose-anthocyanins and chitosan-halloysite nanotubes loaded essential oil to monitor fish freshness

This study developed a multifunctional paper-based freshness antibacterial indicator card by dual-sided coating on conventional filter paper. The indicator coating was composed of anthocyanins from purple cabbage, and polyvinyl alcohol and sodium carboxymethyl cellulose as substrates while the antibacterial coating contained halloysite nanotubes for loaded thyme essential oil and chitosan. FT-IR, XRD, and SEM analyses revealed that the components were well-mixed, and the paper was tightly bound to the coatings through hydrogen bonds. Additionally, the coating effectively filled the porous fiber gaps in the paper, significantly enhancing the mechanical properties of the paper. The tensile strength of the coated paper was enhanced from 14.28 MPa to a range of 42.25–47.71 MPa, and the bending resistance was increased from 0.35 N·mm to a range of 1.72–1.99 N·mm compared to the uncoated paper. The addition of anthocyanins provided excellent sensitivity to pH and ammonia for the indicator card. Furthermore, the coating including halloysite nanotubes for loaded thyme essential oil exhibited antimicrobial resistance against Escherichia coli and Staphylococcus aureus. When used on fresh carp, the antibacterial indicator card not only indicated the freshness of the carp but also extended the best before date of the fish meat by 1–2 days. The indicator exhibited the most pronounced color transformation and optimal freshness indication performance when the mass fraction of anthocyanins was 2 %.

Enhanced NH3-SCR performance using hydrothermally synthesized cell-like MnOx loaded rectorite catalysts

This study evaluates the catalytic performance of hydrothermally synthesized MnOx loaded rectorite catalysts (MnOx/REC-HP) in the selective catalytic reduction of NH3-SCR. Comparative analyses were conducted with catalysts synthesized via pore-volume impregnation, coprecipitation, and in-situ deposition methods, all yielding comparable manganese mass fractions. Results reveal that catalysts derived from hydrothermal synthesis outperform others in NH3-SCR activity across the 100–300 °C temperature spectrum. MnOx/REC-HP exhibits a distinctive cell-like structure of supported MnOx atop the rectorite substrate, diverging from the particulate patterns observed in other synthesis methods. Hydrothermal synthesis of metal precursors into their respective metal oxides effectively meets the fundamental requirements for SCR composites. This method enables the production of composites that are uniformly attached to nanostructures with high purity and controlled crystallinity. The rectorite surface is embellished with a meticulously arranged honeycomb structure of MnOx, augmenting the BET surface area, intensifying redox capability, enhancing NH3 and NOx adsorption, and amplifying the Mn4+ molar ratio on the catalyst surface. Consequently, MnOx/REC-HP showcases remarkable low-temperature NH3-SCR performance.

Predicting the entire pyrolysis process of representative charring material infiltrated with kerosene using an improved artificial neural network

It is crucial to predict the entire pyrolysis process of charring materials infiltrated with flammable liquids to provide guidance for reducing the fire hazards and implementing numerical simulations of fire accidents caused by the leakage of flammable liquids. In the present study, pyrolysis data obtained from the thermogravimetric experiments were preprocessed using linear interpolation and data normalization methods. The processed data set was then used to train the artificial neural network (ANN) framework to predict the pyrolysis behaviors of typical charring material (Mongolian Scots pine) infiltrated with typical flammable liquid (kerosene) under three different conditions: (1) pyrolysis at a constant mass fraction of kerosene with multiple heating rates; (2) pyrolysis at multiple mass fractions of kerosene with a constant heating rate; and (3) pyrolysis at multiple mass fractions of kerosene and multiple heating rates. The ANN, with the double hidden layer structure (6−3), was capable to well predict the entire pyrolysis behaviors of Mongolian Scots pine under all the three scenarios. Besides, five data transformation function (multiplication, exponential function with base e, logarithmic function with base e, square root, and exponentiation function) were applied to the present three input variables (temperature, mass fraction of kerosene, and heating rate) to generate new input variables in order to extract more characteristics among the pyrolysis data. Therein, the ANN utilizing the data transformation functions of multiplication and exponential function with base e exhibited the best predictive ability. Among the three input variables in the ANN (temperature, mass fraction of kerosene, and heating rate), temperature was identified as the most sensitive one to the prediction performance, followed by mass fraction of kerosene, with heating rate being the least sensitive.

Analysis of Longitudinal Cracking and Mold Flux Optimization in High-Speed Continuous Casting of Hyper-Peritectic Steel Thin Slabs

Longitudinal crack defects are a frequent occurrence on the surface of thin slabs during the high-speed continuous casting process. Therefore, this study undertakes a detailed analysis of the solidification characteristics of hyper-peritectic steel thin slabs. By establishing a three-dimensional heat transfer numerical model of the thin slab, the formation mechanism of longitudinal cracks caused by uneven growth of the initial shell is determined. Based on the mechanism of longitudinal crack formation, by adjusting the performance parameters of the mold flux, the contradiction between the heat transfer control and lubrication improvement of the mold flux is fully coordinated, further reducing the incidence of longitudinal cracks on the surface of the casting thin slab. The results show that, using the optimized mold flux, the basicity increases from 1.60 to 1.68, the F- mass fraction increases from 10.67% to 11.22%, the Na2O mass fraction increases from 4.35% to 5.28%, the Li2O mass fraction increases from 0.68% to 0.75%, and the carbon mass fraction reduces from 10.86% to 10.47%. The crystallization performance and rheological properties of the mold flux significantly improve, reducing the heat transfer performance while ensuring the lubrication ability of the molten slag. After optimizing the mold flux, a surface detection system was used to statistically analyze the longitudinal cracks on the surface of the casting thin slab. The proportion of longitudinal cracks (crack length/steel coil length, where each coil produced is about 32 m long) on the surface of the thin slab decreases from 0.056% to 0.031%, and the surface quality of the thin slab significantly improves.

Process optimization and scale-up of toluene nitration in a microchannel reactor using HNO3-AC2O as nitrating agent

Aromatic nitro compounds are an important class of basic chemical raw materials, while traditional nitration methods may cause safety accidents and environmental pollution due to strong exothermicity and presence of sulfuric acid. In this work, aiming to alleviate these issues, the nitration of toluene was conducted in a microchannel reactor with nitric acid and acetic anhydride. The effect of temperature, molar ratio of nitric acid to toluene, mass fraction of acetic anhydride, and residence time on the conversion and selectivity of reaction were systematically investigated, and response surface methodology was used to optimize the process. A mononitrotoluene yield of 99.21 % can be achieved under optimum condition. Meanwhile, in order to better understand the exothermic behavior, toluene nitration by HNO3-AC2O was investigated in the semi-batch calorimeter. Finally, the optimized process was scaled up and effect of volumetric flow rate was investigated. At the selected maximum volumetric flow rate, the overtemperature of the system was 10.9 °C with a 98.3 % yield of mononitrotoluene. Continuous flow mode had a space-time yield nearly two orders of magnitude greater than semi-batch mode. This work can provide guidance for safe, efficient and green synthesis of mononitrotoluene.

Physics-data fusion for digital metering of gas-liquid two-phase flow in oil nozzles

Oil well production metering is an important basis for assessing resource reserves and production capacity. Existing metering methods require high investment and involve significant implementation difficulties and high computational costs. A new method of multiphase flow metering method was proposed by combining the fluctuation of pressure drop and temperature difference generated after throttling through the oil nozzle. The throttling equation coupling differential pressure, flow rate and gas fraction was derived. By regulating the gas and liquid superficial velocity, we carried out the experimental test for true nozzle aperture of 10 mm in the loop system, covering various flow patterns. In addition, the deep neural network was constructed for inversion prediction of mass gas fraction. The proposed flow metering equation has an adaptable gas mass fraction range of 0 to 100%, unaffected by the variations in flow patterns, gas-liquid velocities, and system pressure changes. The metering errors of gas mass fraction and mass flow rate is below ±10%. The proposed metering method only relies on the existing temperature and pressure measurement system in the gathering and transportation system, and no additional measuring devices are required. It can be widely used in oil filed production to realize the virtual metering.

Advancements in Dry Coating for Battery Electrodes: Scalable Extrusion Mixing for Control of Electrode Microstructure and Electrochemical Performance

Dry coating of battery electrodes is emerging as a promising alternative technology to the prevailing slurry coating and drying process widely adopted in the lithium-ion battery industry.1,2,3 To date, the most energy-intensive step in cell manufacturing is the drying of slurry-coated electrodes,1 and the adoption of dry coating aims to mitigate both the environmental impact and production costs associated with electrode production. Beyond environmental and economic concerns, producing higher mass-loading electrodes, a crucial aspect for increasing cell energy density, faces inherent challenges with the slurry-coating process: the drying of thick coatings often leads to issues such as electrode cracking and the formation of inhomogeneous electrode microstructures.Bühler and Empa have collaboratively developed and are in the process of scaling up a dry-coating manufacturing method.4 Our process centers around the extrusion mixing of electrode components, followed by calendering of the dry mixture to produce the final electrode and direct lamination onto a current collector. In this presentation, we showcase the adaptability of extrusion mixing in inducing shear fibrillation of polytetrafluoroethylene (PTFE) binder, crucial for achieving the desired electrode microstructures (see Figure 1a and 1b). Furthermore, we demonstrate the capability of our dry-coating technology to produce high-mass loading electrodes with areal capacities of 5 mAh cm-2 or more (see Figure 1c).The presentation encompasses a thorough characterization of dry-coated electrodes, including their microstructure and electrochemical performance in lab-scale batteries. Key aspects, such as rate capability and capacity retention, are evaluated. A comprehensive comparison with slurry-coated electrodes, fabricated using identical active electrode materials, mass fractions, and mass loading, reveals that our dry-coated electrodes exhibit comparable performance to their slurry-coated counterparts.5 The scalability of our dry-coating technology is underscored, highlighting the achievable throughputs necessary for gigafactory-scale production with a single extruder.

Ontology Creation and Database Implementation for Lab-Scale Solid-State Battery Cells

New developments and publications on alkali metal solid-state batteries are being published at a high rate, with the total number of publications now in the thousands, but the search and analysis of the data in these publications is still largely done using key words and through careful reading of the article and the supporting information. The challenges of efficiently searching and extracting data from thousands of publications in a field are also present in other fields, such as perovskite solar cells, for which a large (>15,000) set of cell data has been entered into a database that continues to be updated.1 A database for alkali metal (e.g., based on Na+ and Li+ conduction) solid-state cells that could be easily searched and that facilitated advanced forms of data analysis could accelerate research progress, and is consistent with efforts such as definition of the “Principles of the Battery Data Genome” and the BIG-MAP project.2 In this talk, we describe our approach to creating an ontology and database for lab-scale solid-state cells, along with results to date. Key areas for the ontology include component material identities, material properties, component properties (e.g., active material loading, mass fractions, thicknesses), processing conditions for materials and the cell itself (e.g., ball milling time, sintering time), and both performance (e.g., rate capability) and degradation (e.g., cycle life). Results based on several hundred solid state cells in our database are presented in terms of histogram plots, violin plots, correlation plots, and other representations. We also describe our efforts to integrate our ontology and tool with broader efforts in the field, and to make it broadly useful to battery researchers.1. Nature Energy, volume 7, pages 107–115 (2022) and https://www.perovskitedatabase.com/2. Joule 6, 2253–2271, October 19, 2022 and https://www.big-map.eu/dissemination/battinfo

Micropatterning MXene/TiO2 Nanocomposite Ink for Gas Sensing

This work describes the preparation, characterization and micropatterning of MXene (Ti3C2/TiO2) nanocomposite inks. The MXene nanopowder was oxidized to Ti3C2/TiO2 nanocomposite powder by stirring in air for 3 hours using air aging method. The Ti3C2/TiO2 nanocomposite powder was then dispersed into Dimethyl Sulfoxide (DMSO) solvent, and the Ti3C2/TiO2 ink was prepared by using 1% mass fraction of Polyvinylpyrrolidone (PVP) solution as dispersant. The two-dimensional layered nanostructure of MXene and the characteristic peaks of TiO2 were observed by Raman and XRD results. SEM and TEM results show the layered structure of MXene nanoparticles as well as TiO2 nanoparticles with a diameter of about 2 nm on a single layer of MXene. FTIR results confirms that Ti-O bonds and Ti-C bonds indicating that part of Ti3C2 was oxidized to TiO2. The results of Brunauer Emmett Teller (BET) test on Ti3C2/TiO2 nanocomposite ink show that the specific surface area of the ink is 10.7194 m²/g and the maximum adsorption of N2 is 32.039cm3/g. Thermogravimetric analysis (TGA) indicate that Ti3C2/TiO2 exhibited excellent thermal stability, with a mass loss of only 15% at 800°C. In order to achieve the optimal printing effect, plasma surface treatment was carried out on the gold-plated silicon wafers, Polyethylene terephthalate (PET), and glass substrates, which decreases the contact angle of the ink on these substrates. The printing of Ti3C2/TiO2 nanocomposite ink on the substrate using the atomized printing technique with a mask plate enables printing of straight lines with a line width of 5µm. Film thickness can be controlled by adjusting the distance between the printhead and the substrate, as well as the pressure of the atomized printing jet.

Seeding as a Decisive Tool for Increasing Space-Time-Yields in the Preparation of High-Quality Cu/ZnO/ZrO2 Catalysts

Aging is one of the key steps in the preparation of highly active Cu/ZnO-based catalysts for use in the production of methanol. If certain pH and temperature specifications are met, an initially amorphous precipitate transforms into the crystalline precursor phase of zincian malachite, which is characterized by a periodic arrangement of Cu and Zn atoms and has proven advantageous for the quality of the final catalyst. However, aging generally takes between 30 min and multiple hours until the desired phase transformation is completed. With our study, we show that aging can be significantly accelerated by seeding the freshly precipitated suspension with already aged zincian malachite crystals: the necessary aging time was reduced by 41% for seeding mass fractions as low as 3 wt.% and from 83 min to less than 2 min for 30 wt.% seeds. No negative influence of seeding on the phase composition, specific surface area, molar metal ratios, or the morphology of the aged precursor could be identified. Consequently, the catalyst performance in the synthesis of methanol from CO2, as well as from a CO/CO2 mixture, was identical to a catalyst from an unseeded preparation and showed small advantages compared to a commercial sample. Thus, we conclude that seeding is a vital tool to accelerate the preparation of all Cu/Zn-based catalysts while maintaining product quality, presumably also on an industrial scale.