| Records |
| Author |
Perreault, P.; Robert, E.; Patience, G.S. |
| Title |
Experimental methods in chemical engineering : mass spectrometry – MS |
Type |
A1 Journal article |
| Year |
2019 |
Publication |
The Canadian journal of chemical engineering |
Abbreviated Journal |
|
Volume  |
97 |
Issue |
5 |
Pages |
1036-1042 |
| Keywords |
A1 Journal article; Engineering sciences. Technology; Sustainable Energy, Air and Water Technology (DuEL) |
| Abstract |
Mass spectrometry identifies the atomic mass of molecules and fragments in the gas phase. The spectrometer ionizes the molecules that then pass through an electric or magnetic field towards a detector. The field modifies the molecule's trajectory and we infer mass from its direction and velocity in a static field or from the stability of its path in a dynamic field. The electric current is amplified and a mass spectrum is generated from the location or timing of the signal from the detector, translated into a plot of the intensity as a function of the mass‐over‐charge ratio. It is field deployable, measures concentrations in real time with a temporal resolution better than 100 ms, and detection limits of fg. However, the signal drifts with time so we have to calibrate it as frequently as every hour. Calibrating requires multiple mixtures with varying concentrations to map the non‐linear response. The Web of Science Core Collection indexed over 60 000 articles that refer to MS (2016 and 2017) with applications ranging from permanent gas analysis, to identifying protein, forensic science, and natural products. The bibliometric software VOSViewer(2010) identified four clusters of research related to MS: (1) proteomics, proteins, plasma, and metabolomics; (2) solid phase extraction together with gas chromatography; (3) tandem mass spectrometry and liquid chromatography; and (4) waste water and toxicity. We expect that the technique will continue to evolve with increased sensitivity, lower drift, and greater specificity. Miniaturization efforts should also continue in order to develop faster field deployable instruments. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
|
Wos |
000468025000001 |
Publication Date |
2019-01-29 |
| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0008-4034; 1939-019x |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
| Impact Factor |
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Times cited |
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Open Access |
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| Notes |
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Approved |
no |
| Call Number |
UA @ admin @ c:irua:162123 |
Serial |
7947 |
| Permanent link to this record |
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| |
| Author |
Van Hoecke, L.; Boeye, D.; Gonzalez‐Quiroga, A.; Patience, G.S.; Perreault, P. |
| Title |
Experimental methods in chemical engineering : computational fluid dynamics/finite volume method–CFD/FVM |
Type |
A1 Journal article |
| Year |
2022 |
Publication |
The Canadian journal of chemical engineering |
Abbreviated Journal |
Can J Chem Eng |
| Volume |
|
Issue |
|
Pages |
1-17 |
| Keywords |
A1 Journal article; Engineering sciences. Technology; Sustainable Energy, Air and Water Technology (DuEL) |
| Abstract |
Computational fluid dynamics (CFD) applies numerical methods to solve transport phenomena problems. These include, for example, problems related to fluid flow comprising the Navier--Stokes transport equations for either compressible or incompressible fluids together with turbulence models and continuity equations for single and multi-component (reacting and inert) systems. The design space is first segmented into discrete volume elements (meshing). The finite volume method, the subject of this article, discretizes the equations in time and space to produce a set of non-linear algebraic expressions that are assigned to each volume element-cell. The system of equations is solved iteratively with algorithms like the semi-implicit method for pressure-linked equations (SIMPLE) and the pressure implicit splitting of operators (PISO). CFD is especially useful for testing multiple design elements because it is often faster and cheaper than experiments. The downside is that this numerical method is based on models that require validation to check their accuracy. According to a bibliometric analysis, the broad research domains in chemical engineering include: (1) dynamics and CFD-DEM (2) fluid flow, heat transfer and turbulence, (3) mass transfer and combustion, (4) ventilation and environment, and (5) design and optimization. Here, we review the basic theoretical concepts of CFD and illustrate how to set up a problem in the open-source software OpenFOAM to isomerize n-butane to i-butane in a notched reactor under turbulent conditions. We simulated the problem with 1000, 4000, and 16000 cells. According to the Richardson extrapolation, the simulation underestimates the adiabatic temperature rise by 7% with 16000 cells. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Wos |
000859840100001 |
Publication Date |
2022-07-26 |
| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0008-4034; 1939-019x |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
| Impact Factor |
2.1 |
Times cited |
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Open Access |
OpenAccess |
| Notes |
|
Approved |
Most recent IF: 2.1 |
| Call Number |
UA @ admin @ c:irua:189284 |
Serial |
7160 |
| Permanent link to this record |
