Constitutive Equations for Transport of Chemical Species

Author(s):  
Roberto Mauri
Author(s):  
R. H. Duff

A material irradiated with electrons emits x-rays having energies characteristic of the elements present. Chemical combination between elements results in a small shift of the peak energies of these characteristic x-rays because chemical bonds between different elements have different energies. The energy differences of the characteristic x-rays resulting from valence electron transitions can be used to identify the chemical species present and to obtain information about the chemical bond itself. Although these peak-energy shifts have been well known for a number of years, their use for chemical-species identification in small volumes of material was not realized until the development of the electron microprobe.


Author(s):  
J. Barbillat ◽  
M. Delhaye ◽  
P. Dhamelincourt

Raman mapping, with a spatial resolution close to the diffraction limit, can help to reveal the distribution of chemical species at the surface of an heterogeneous sample.As early as 1975,three methods of sample laser illumination and detector configuration have been proposed to perform Raman mapping at the microscopic level (Fig. 1),:- Point illumination:The basic design of the instrument is a classical Raman microprobe equipped with a PM tube or either a linear photodiode array or a two-dimensional CCD detector. A laser beam is focused on a very small area ,close to the diffraction limit.In order to explore the whole surface of the sample,the specimen is moved sequentially beneath the microscope by means of a motorized XY stage. For each point analyzed, a complete spectrum is obtained from which spectral information of interest is extracted for Raman image reconstruction.- Line illuminationA narrow laser line is focused onto the sample either by a cylindrical lens or by a scanning device and is optically conjugated with the entrance slit of the stigmatic spectrograph.


1992 ◽  
Vol 64 (19) ◽  
pp. 931A-940A ◽  
Author(s):  
Totaro Imasaka ◽  
Masami Hozumi ◽  
Nobuhiko Ishibashi

2007 ◽  
Vol 35 (4) ◽  
pp. 276-299 ◽  
Author(s):  
J. C. Cho ◽  
B. C. Jung

Abstract Tread pattern wear is predicted by using an explicit finite element model (FEM) and compared with the indoor drum test results under a set of actual driving conditions. One pattern is used to determine the wear rate equation, which is composed of slip velocity and tangential stress under a single driving condition. Two other patterns with the same size (225/45ZR17) and profile are used to be simulated and compared with the indoor wear test results under the actual driving conditions. As a study on the rubber wear rate equation, trial wear rates are assumed by several constitutive equations and each trial wear rate is integrated along time to yield the total accumulated wear under a selected single cornering condition. The trial constitutive equations are defined by independently varying each exponent of slip velocity and tangential stress. The integrated results are compared with the indoor test results, and the best matching constitutive equation for wear is selected for the following wear simulation of two other patterns under actual driving conditions. Tens of thousands of driving conditions of a tire are categorized into a small number of simplified conditions by a suggested simplification procedure which considers the driving condition frequency and weighting function. Both of these simplified conditions and the original actual conditions are tested on the indoor drum test machines. The two results can be regarded to be in good agreement if the deviation that exists in the data is mainly due to the difference in the test velocity. Therefore, the simplification procedure is justified. By applying the selected wear rate equation and the simplified driving conditions to the explicit FEM simulation, the simulated wear results for the two patterns show good match with the actual indoor wear results.


2017 ◽  
Author(s):  
Benjamin Sanchez-Lengeling ◽  
Carlos Outeiral ◽  
Gabriel L. Guimaraes ◽  
Alan Aspuru-Guzik

Molecular discovery seeks to generate chemical species tailored to very specific needs. In this paper, we present ORGANIC, a framework based on Objective-Reinforced Generative Adversarial Networks (ORGAN), capable of producing a distribution over molecular space that matches with a certain set of desirable metrics. This methodology combines two successful techniques from the machine learning community: a Generative Adversarial Network (GAN), to create non-repetitive sensible molecular species, and Reinforcement Learning (RL), to bias this generative distribution towards certain attributes. We explore several applications, from optimization of random physicochemical properties to candidates for drug discovery and organic photovoltaic material design.


2019 ◽  
Author(s):  
Kazunori Miyamoto ◽  
Shodai Narita ◽  
Yui Masumoto ◽  
Takahiro Hashishin ◽  
Mutsumi Kimura ◽  
...  

Diatomic carbon (C<sub>2</sub>) is historically an elusive chemical species. It has long been believed that the generation of C<sub>2 </sub>requires extremely high “physical” energy, such as an electric carbon arc or multiple photon excitation, and so it has been the general consensus that the inherent nature of C<sub>2 </sub><i>in the ground state </i>is experimentally inaccessible. Here, we present the first “chemical” synthesis of C<sub>2 </sub>in a flask at <i>room temperature or below</i>, providing the first experimental evidence to support theoretical predictions that (1) C<sub>2 </sub>has a singlet biradical character with a quadruple bond, thus settling a long-standing controversy between experimental and theoretical chemists, and that (2) C<sub>2 </sub>serves as a molecular element in the formation of sp<sup>2</sup>-carbon allotropes such as graphite, carbon nanotubes and C<sub>60</sub>.


2018 ◽  
Author(s):  
Z. Gerald Liu ◽  
Devin R. Berg ◽  
Thaddeus A. Swor ◽  
James J. Schauer‡

Two methods, diesel particulate filter (DPF) and selective catalytic reduction (SCR) systems, for controlling diesel emissions have become widely used, either independently or together, for meeting increasingly stringent emissions regulations world-wide. Each of these systems is designed for the reduction of primary pollutant emissions including particulate matter (PM) for the DPF and nitrogen oxides (NOx) for the SCR. However, there have been growing concerns regarding the secondary reactions that these aftertreatment systems may promote involving unregulated species emissions. This study was performed to gain an understanding of the effects that these aftertreatment systems may have on the emission levels of a wide spectrum of chemical species found in diesel engine exhaust. Samples were extracted using a source dilution sampling system designed to collect exhaust samples representative of real-world emissions. Testing was conducted on a heavy-duty diesel engine with no aftertreatment devices to establish a baseline measurement and also on the same engine equipped first with a DPF system and then a SCR system. Each of the samples was analyzed for a wide variety of chemical species, including elemental and organic carbon, metals, ions, n-alkanes, aldehydes, and polycyclic aromatic hydrocarbons, in addition to the primary pollutants, due to the potential risks they pose to the environment and public health. The results show that the DPF and SCR systems were capable of substantially reducing PM and NOx emissions, respectively. Further, each of the systems significantly reduced the emission levels of the unregulated chemical species, while the notable formation of new chemical species was not observed. It is expected that a combination of the two systems in some future engine applications would reduce both primary and secondary emissions significantly.


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