Air Molecules Research Articles

Physical characteristics of nickel thin-films and nickel thin-film foams as Li-air batteries anode and cathode current collectors

Lithium-air batteries (LABs) are in the research and development stage between 2020 and 2030 as the future of lithium-ion batteries, and knowledge about their components provides the necessary data for commercializing. Current research investigates the physical characteristics of nickel (Ni) thin-films and Ni thin-film foams as anode and cathode current collectors, respectively, for LABs using the molecular dynamics simulation method. The obtained results provide helpful theoretical guidance for researchers to understand the physical attributes of current collectors and the interfacial interaction of air and electrolyte with cathode current collectors. Results indicate that the maximum service temperature of Ni thin-films and their foams with a 2.82–5.63 nm thickness equals 1200 and 1088 K, respectively, because the physical characteristics change significantly after these temperatures. Evaluation of the mechanical properties of Ni thin-films and their foams show that the mechanical attributes of these materials are in the acceptable region of current collectors. Therefore, Ni thin-films and their foams provide the required thermal and mechanical characteristics as anode and cathode current collectors, respectively. However, interfacial interaction between Ni thin-film foams with air and (CH3)2SO/LiPF6 non-aqueous electrolyte reveals that the presence of oxygen selective membrane is necessary for LABs cells. This membrane must not only block the flow of N2 and H2O toward the battery but also must impede the leakage of electrolytes. In addition, results depict that Ni thin-film foams have suitable applications as cathode current collectors for Li-N2 batteries due to more permeation depth of N2 molecules in comparison with other air molecules.

Converting N2 molecules into NH3 with TiO2/Fe3O4 composite covered with a thin water layer under ambient condition

As ammonia manufacture today require huge energy and very pure hydrogen gas and moreover emit large quantities of CO2, researches for new ammonia synthesis methods are actively performed. Here, author reports the novel method through which N2 molecules in air is reduced into ammonia with TiO2/Fe3O4 composite having thin water layer on composite’s surface under ambient condition (less than 100 °C and atmospheric pressure). The composites were composed of both nm-sized TiO2 particles and μm-sized Fe3O4 ones. First, composites were held in refrigerator, mainly at that time, N2 molecules in air adsorbed onto surface of composite. Next, the composite was irradiated with various lights including solar light, 365 nm LED light and tungsten light through thin water layer formed by condensation of water vapour in air. Reliable amount of ammonia was obtained under 5 min’s irradiation of solar light or of both 365 m LED light and 500 W tungsten light. This reaction was catalytic reaction promoted by photocatalytic one. In addition, holding in freezer instead of refrigerator provided larger amount of ammonia. Maximum ammonia yield was approximately 18.7 μmol/g 5 min under irradiation of 300 W tungsten light only.

A method for evaluation of aerodynamic lift and drag based on statistical mechanics

Despite intensive applications of Navier–Stokes equations in computational-fluid-dynamics (CFD) to understand aerodynamics, fundamental questions remain open since the statistical nature of discrete air molecules with random thermal motion is not considered in CFD. Here, we introduce an approach based on statistical mechanics, termed as “volume-element” method, for numerical evaluation of aerodynamic lift and drag. Pressure and friction as a function of angle of attack have been obtained for canonical flat-plate airfoils, and the method is applicable to convex-shape airfoils directly and viable for concave-shape airfoils if combined with Monte Carlo simulations. This approach opens a door not only for aerodynamic applications, but also for further applications in Boson or Fermi gases.

TRIC EXPLOSION OF AEROSOLS. TO THE 115TH ANNIVERSARY OF THE TUNGUSKA METEORITE

A hypothesis has been proposed according to which the preserved traces of the impact on the nature caused by the explosion of the Tunguska meteorite are the result of electrical discharges in a cloud of solid particles, which, when moving at the space velocity in the upper atmosphere, were heated up to a high temperature and, due to thermionic emission, acquired large positive charges. The released thermo-electrons attached to air molecules and lagged behind the charged particles. The separation of the charges in the cloud caused powerful discharges similar to horizontal lightnings in clouds. The consequences of the discharges in the cloud of highly charged solid particles, which gave rise to the generation of hard ionizing radiation, are discussed.

Development of a Machine Learning Forecast Model for Global Horizontal Irradiation Adapted to Tibet Based on Visible All-Sky Imaging

The Qinghai-Tibet Plateau is rich in renewable solar energy resources. Under the background of China’s “dual-carbon” strategy, it is of great significance to develop a global horizontal irradiation (GHI) prediction model suitable for Tibet. In the radiation balance budget process of the Earth-atmosphere system, clouds, aerosols, air molecules, water vapor, ozone, CO2 and other components have a direct influence on the solar radiation flux received at the surface. For the descending solar shortwave radiation flux in Tibet, the attenuation effect of clouds is the key variable of the first order. Previous studies have shown that using Artificial intelligence (AI) models to build GHI prediction models is an advanced and effective research method. However, regional localization optimization of model parameters is required according to radiation characteristics in different regions. This study established a set of AI prediction models suitable for Tibet based on ground-based solar shortwave radiation flux observation and cloud cover observation data of whole sky imaging in the Yangbajing area, with the key parameters sensitively tested and optimized. The results show that using the cloud cover as a model input variable can significantly improve the prediction accuracy, and the RMSE of the prediction accuracy is reduced by more than 20% when the forecast horizon is 1 h compared with a model without the cloud cover input. This conclusion is applicable to a scenario with a forecast horizon of less than 4 h. In addition, when the forecast horizon is 1 h, the RMSE of the random forest and long short-term memory models with a 10-min step decreases by 46.1% and 55.8%, respectively, compared with a 1-h step. These conclusions provide a reference for studying GHI prediction models based on ground-based cloud images and machine learning.

Thermal and wind devices for multisensory human-computer interaction: an overview

In order to create immersive experiences in virtual worlds, we need to explore different human senses (sight, hearing, smell, taste, and touch). Many different devices have been developed by both industry and academia towards this aim. In this paper, we focus our attention on the researched area of thermal and wind devices to deliver the sensations of heat and cold against people’s skin and their application to human-computer interaction (HCI). First, we present a review of devices and their features that were identified as relevant. Then, we highlight the users’ experience with thermal and wind devices, highlighting limitations either found or inferred by the authors and studies selected for this survey. Accordingly, from the current literature, we can infer that, in wind and temperature-based haptic systems (i) users experience wind effects produced by fans that move air molecules at room temperature, and (ii) there is no integration of thermal components to devices intended for the production of both cold or hot airflows. Subsequently, an analysis of why thermal wind devices have not been devised yet is undertaken, highlighting the challenges of creating such devices.

Implementation of Permanent Magnet Propelling Phenomenon in Traditional Vertical Axis Wind Turbine System to Enhance the Performance and Efficiency

It is generally acknowledged that the energy as we now use, will not be adequate to meet the needs of all people on the planet in future, hence cleaner and more plentiful alternative energy sources are required which may be in the form of hybrid energy also. Renewable energy sources will certainly become more prominent. Modern civilizations need cheap, plentiful energy to survive, therefore, it is crucial for human civilization to create a sustainable, affordable, and environmentally benign alternative sources of energy. The global energy dilemma may have an efficient solution in the form of wind power. In current state of affairs, the air could seem like insignificant to any or all. However, we tend to all grasp that, the planet has shaped up with associate uneven surface, which suggest that the sunrays could strike these surfaces with variable intensities at numerous spot on its uneven surface. This creates associated degree of unequal degree of heating of the earth surface, that which causes variation in part of atmospheric pressure thereon. Then it leads to wind. The Kinetic energy of these air molecules is nothing but wind energy. A mechanical mechanism known as a wind turbine which transforms, kinetic energy which is there in the air around it into the required form of mechanical energy. Here in this research, we focused on the repellent qualities of permanently magnetized objects with similar poles. These innate qualities of magnetic propulsion are used here as an energy sources. Due to the inclusion of this components like magnetic repulsion, our VAWT system will operate more effectively even at lower wind speeds circumstance also. This magnet will produce a repulsive force that will add various sorts of kinetic energies to the wind turbines as they convert wind energy's kinetic energy of into the necessary mechanical power when it’s employed as an extra source of energy in a VAWT.

An in-silico proof-of-concept of electrohydrodynamic air amplifier for low-energy airflow generation

Electrohydrodynamic (EHD) technology generates airflow without moving parts, making it a reliable solution for various low-energy applications. EHD-based airflow devices enhance airflow patterns, resulting in significant energy savings in air-moving systems. This airflow, also known as ionic wind, is created through Corona discharge, which accelerates electrically charged air molecules in a strong electric field. Currently, EHD's low electrical-to-mechanical energy conversion rate still limit its ability to generate large flow rates. The objective of this study is to enhance the flow rate of EHD-based devices, for applications where EHD can be used as an effective auxiliary technology with low pressure lift, to enhance airflow distribution and circulation. To this end, a novel bladeless air propulsion device is proposed that combines ionic wind with air amplification based on the Coanda phenomenon to amplify EHD-generated flow rates. We assess the performance of the bladeless air propulsion device to generate airflow by investigating fluid dynamics, electrostatics, and energy consumption. We demonstrate the proof-of-concept with an innovative fully-coupled simulation approach for corona discharge and EHD modeling. We explore different design parameters on the conceptual EHD air amplifier, such as the electric potential (10–30 kV) of the discharge electrode, the electrode spacing (5–25 mm), and the channel height (30–150 mm). The studies are performed on a 2D constrained channel flow and a 2D-axisymmetric open space design, respectively. In order to quantify the benefit of air amplification on EHD, the results are benchmarked to a regular EHD setup without amplifying vane as well as to a comparable commercial axial fan. We assess the performance in terms of flow rate per electric power input. Here, the EHD air amplifier in the constrained flow configuration increases the total flow rate by 59% compared to regular EHD and 48% compared to the axial fan for the same electrical energy input. Amplification factors of 16.5–19 are achieved for the constrained configuration and 5.5 to 6.4 for the open space configuration. The predicted energy consumption is 4–17.5 W for the open space configuration, resulting in flow rates up to 140 m3 h−1. These results show that EHD air amplification is a promising way to generate high flow rates with low pressure rise at a low electrical cost, by which it can provide a more sustainable alternative to conventional fans in specific applications..

PAUT of CRA Cladded Pipe Circumferential Dissimilar Welds

Ultrasonic testing (UT) is a technical way of communicating with materials, but what does that mean? To be able to understand this, we should think about how people communicate with each other—by talking. Humans have vocal cords in their throats, also known as vocal folds, a band of highly elastic connective tissue. When someone wants to talk, their brain sends a signal to the vocal fold, and after receiving the electrical signal, the folds start to vibrate and cause the air molecules flowing around them vibrate as well. This vibration flows through the air molecules to the ears of the other people, causing tiny bones within the ear to vibrate. This mechanical vibration is converted into an electrical signal by stimulation of the sensory cells in the ear and nerve impulses sent to the brain. Through this complex conversion of electrical signal to vibration, and then vibration back to the electrical signal, two human beings talk to each other. In general, the human ear can detect sounds with frequencies between 20 and 20 000 Hz, which is called an audio range. (Frequency means the number of vibrations against the unit time and is expressed in cycles per seconds). Frequencies below 20 Hz are called infrasound and above 20 000 Hz are called ultrasound. The industrial application of ultrasound is the answer to the question, “How can we talk to material?”, which forms the basis of UT. UT is widely used as a nondestructive testing method to examine materials and welds, as well as bondings between the materials. In this article, UT of dissimilar welds shall be discussed.

Определение оптимальной системы скачков воздухозаборного устройства с учетом диссоциации молекул набегающего воздуха

Определение оптимальной системы скачков воздухозаборного устройства с учетом диссоциации молекул набегающего воздуха

Control of the sensitivity of the detection of ionized air using photonic crystal waveguides

Ionized air is used in various industries to control electrostatic charge. On the other hand, ionized air molecules can also cause various problems since electrification of materials can induce electrostatic discharges. Therefore, compact sensors that enable a quantitative detection of ionized air will help to improve industrial processes and safety. Here we report on the detection of negatively ionized air using a photonic crystal (PC) waveguide with a length of 800 µm. In this type of detector, the PC is exposed to a flux of air ions that transfers a part of the excess charges to the PC. The light transmitted through the waveguide is then attenuated by free carrier absorption due to the excess charges from the ionized air molecules. We show that the electron density in the PC can be estimated from the magnitude of the attenuation, and that this magnitude depends on the wavelength of the light propagating in the PC waveguide. Due to the wavelength dispersion of the group velocity, light at longer wavelengths is subject to stronger attenuation than light at shorter wavelengths. This property is useful for the development of ionized-air sensors with a variable detection range.

The Production of Industrial-Grade Oxygen from Air by Pressure Swing Adsorption

Oxygen, an odorless and colorless gas constituent of the atmosphere, is a vital gas component for the Earth, as it makes up 21% of the composition of the air we breathe. Apart from the importance of oxygen for human breathing, its highly pure form is demanding for industrial applications. As such, several technologies have been established to increase the oxygen purity from 21% to somewhat higher than 95%. One of the competitive technologies for producing this high-purity oxygen from the air is through pressure swing adsorption (PSA), which has the advantages of low cost and energy while being highly efficient. Also, PSA is a simple and flexible system due to its ability to start up and shut down more rapidly since its operation occurs at ambient temperature, which is enabled through the use of adsorbents to bind and separate the air molecules. The enhancement of the PSA’s performances was reported through the modification of PSA step cycles and material (zeolite) tailoring. A simplified complete set of a mathematical model is included for modelling the PSA system, aiming to ease the experimental burden of the process design and optimization of an infinite modification of PSA step cycles. Finally, some technological importance of oxygen production via PSA, particularly for onboard oxygen generation system and oxy-enriched incineration of municipal solid waste, was discussed. Continuous development of PSA will make significant contributions to a wide range of chemical industries in the near future, be it for oxygen production or other gas separation applications.

Transition from triggered super-radiance to seed amplification in N2 + lasing.

Air lasing induced by laser filamentation opens a new route for research on atmospheric molecular physics and remote sensing. The generation of air lasing is composed of two processes, i.e., building up optical gain of air molecules in femtosecond time scale and emitting coherent radiation in picosecond time scale. Here, we focus on the emission mechanisms of N2 + air lasing and reveal, by examining the intensities and temporal profiles of N2 + lasing at 391 nm generated respectively in a time-varying polarization-modulated and a linearly polarized pump laser field under different nitrogen gas pressures, that the N2 + lasing can emit through either triggered super-radiance or seed amplification. We find that the two pressure-sensitive factors, i.e., the dipole dephasing time T2 and the population inversion density n, determine which of these two mechanisms dominates the N2 + lasing emission process, enabling manipulation of the transition from triggered super-radiance to seed amplification or vice versa. Our findings clarify the emission mechanism of N2 + lasing under different pressures and provide a deeper understanding of N2 + air lasing not only in the establishment of optical gain but also in the lasing emission process.

Visualizing ultrafast weak-field-induced rotational revivals of air molecules at room temperature.

The ability to observe quantum coherence and interference is crucial for understanding quantum effects in nonlinear optical spectroscopy and is of fundamental interest in quantum mechanics. Here, we present an experimental study combined with theoretical analysis and numerical simulations to identify the underlying process behind the rotational revivals induced by a pair of time-delayed ultrafast femtosecond laser pulses for air molecules under ambient conditions. Our time-resolved two-dimensional alignment measurements confirm that one-step non-resonant Raman transitions from initial states of mixed molecules play a dominant role, showing a signature of weak-field-induced rotational revivals. Furthermore, we demonstrate that such rotational revival spectra can simultaneously measure the entire pure rotational Raman spectra and observe the quantum interference between two transition pathways from a given initial state. This work provides a powerful tool to observe, control, and identify the rotational dynamics of mixed molecular samples under weak-field excitations.

Analytical capabilities of a thermodesorption spectrometer with a surface-ionization detection of organic molecules in air

This paper presents the results of research on the development of a mathematical model of thermal desorption spectrometry with a surface ionization method for detecting molecules of organic substances, as well as an analysis of the capabilities of a thermal desorption spectrometer operating on the basis of this method. The mathematical model of the method was developed on the basis of the regularities of thermal desorption spectrometry, as well as the regularities of surface ionization of molecules of organic substances under non-stationary conditions. The spectrometer consists of a surface ionization detector and an evaporator of substances heated in a thermally programmed mode. The adjustment and selection of the operating mode of the spectrometer were carried out on the basis of the mathematical model of the method. The analytical capabilities of the spectrometer were studied by comparing the thermodesorption spectra of a mixture of chromatographically pure cannabinoids and an extract of the biological fluids of a marijuana user (blood, urine), as well as the spectra of chromatographically pure morphine and urine extracts of a heroin user. The results of the analysis showed the perspectives of the proposed method and instrument for the detection and analysis of drugs and psychotropic drugs in extracts of biomaterials of consumers of these substances without chromatographic separation. Keywords: biosamples of drug users, mathematical model of the method, thermal desorption spectrum, identification and quantitative analysis.

Electrical and optoelectronic anisotropy and surface electron accumulation in ReS2 nanostructures.

Two interesting electronic transport properties including in-plane anisotropy and nonhomogeneous carrier distribution were observed in ReS2 nanoflakes. The electrical conductivity defined by the current parallel to the b-axis (‖b) is 32 times higher than that perpendicular to the b-axis (⊥b). Similar anisotropy was also observed in optoelectronic properties in which the ratio of responsivity ‖b to ⊥b reaches 20. In addition, conductivity and thermal activation energy with substantial thickness dependence were observed, which indicates a surface-dominant 2D transport in ReS2 nanoflakes. The presence of surface electron accumulation (SEA) in ReS2 has been confirmed by angle-resolved photoemission spectroscopy and scanning tunneling spectroscopy. The electron concentration (∼1019 cm-3) at the surface is over three orders of magnitude higher than that of the bulks. Sulfur vacancies which are sensitive to air molecules are suggested to be the major factor resulting in SEA and high conductivity in ReS2 nanostructures.

Uses for the HEC BB Bag in Physics Instruction

In this article, we will present the HEC BB bag, a simple but elegant model originally invented to help students imagine how air molecules move around in vacuum. The HEC BB bag is made by packing 20 to 30 BBs in a resealable plastic bag of several tens of square centimeters (see Fig. 1). When inflated fully via a straw, the volume of the bag is about 5 L in volume (see below for specifications).

Surfactant Assisted In Situ Synthesis of Nanofibrillated Cellulose/Polymethylsilsesquioxane Aerogel for Tuning Its Thermal Performance

Back Cover: In article 2200628, Pradip K. Maji and co-worker show that the thermal conductivity depends upon solid and gaseous conductivity. The red and blue color gradients in aerogel slab distinguish hot and cold region. Green color fibers and spherical particles symbolize nanofibrillated cellulose and polymethylsilsesquioxane, respectively. The navy blue color air molecules diffuse into aerogel pores due to Knudsen effect. The structure of aerogel slab represents the thermal insulator.

Formation and Stability of Cs<sub>2</sub>SnBr<sub>6</sub> Perovskite Nanocrystals from CsSn<sub>2</sub>Br<sub>5</sub> Nanocubes

Lead-free Sn(II) based, CsSn2Br5, perovskite nanocubes were synthesized using a modified hot-injection method by tuning the injection temperature and reaction conditions. The formation of Sn(IV) based, Cs2SnBr6, perovskite nanocrystals (PNCs) from CsSn2Br5 perovskite nanocubes was observed. X-ray diffraction measurements revealed that oxygen or water molecules in air gradually react with CsSn2Br5 perovskite nanocubes to form Cs2SnBr6 NCs. The stability of Cs2SnBr6 NCs was monitored by time-dependent absorption measurements. Both oxygen and water molecules react with the Cs2SnBr6 NCs to degrade, however water molecules appears largely to react with the NCs. The stability has been improved by dispersing the Cs2SnBr6 NCs in degassed anhydrous solvent.

Machine learning based Air Pollution Monitoring and predicting cause for pollution

Over the past few decades, due to human activities, industrialization, and urbanization, air pollution has become a life-threatening factor in many countries around the world. Air pollution has a direct impact on human health through the exposure of pollutants and particulates, which has increased the interest in air pollution and its impacts among the scientific community. The main causes associated with air pollution are the burning of fossil fuels, agriculture, exhaust from factories and industries, residential heating, and natural disasters. The Environmental Protection Agency (EPA) tracks the pollution level by calculating the amount of ground-level ozone (O3), Sulphur dioxide (SO2), particulates matter (PM10 and PM2.5), carbon monoxide (CO), carbon dioxide (CO2), and nitrogen dioxide (NO2) present in the air molecule. These substances are in compositions of a common index, called the Air Quality Index (AQI), indicating how clean or polluted the air is currently or forecasted to become in areas. This work deliberates the implementation of cloud based IoT system for air quality monitoring in which the sensors are used to calculate CO, PM2.5 and PM10, O3, SO2 and NOx pollution level with environmental condition like temperature and humidity. The obtained information can be updated in cloud platform using Lora nodes and Lora Gateway. The information fetched from the cloud is transmitted to the Machine learning models which contains the detailed dataset for the pollutants and these models accurately predict the day-wise pollutant concentrations and display them using an application. This work presents the detailed analysis for predicting the cause of pollution by using Support Vector Machine (SVM), Random forest algorithm and K-nearest neighbours (KNN) algorithm.