Surface Dilational Viscoelasticity of C14EO8Micellar Solution Studied by Bubble Profile Analysis Tensiometry

Langmuir ◽  
2008 ◽  
Vol 24 (13) ◽  
pp. 6447-6452 ◽  
Author(s):  
V. B. Fainerman ◽  
J. T. Petkov ◽  
R. Miller
Keyword(s):  
Profile Analysis ◽  
Dilational Viscoelasticity ◽  
Surface Dilational Viscoelasticity

Surface dilational viscoelasticity of aqueous surfactant solutions by surface quasi-elastic light scattering

2018 ◽  
Vol 296 (4) ◽  
pp. 781-798 ◽  
Author(s):  
Shusaku Ueno ◽  
Yuichi Takajo ◽  
Shunsuke Ikeda ◽  
Ryo Takemoto ◽  
Yosuke Imai ◽  
...  
Keyword(s):  
Light Scattering ◽  
Elastic Light Scattering ◽  
Surfactant Solutions ◽  
Dilational Viscoelasticity ◽  
Surface Dilational Viscoelasticity

Dilational Viscoelasticity of Adsorption Layers Measured by Drop and Bubble Profile Analysis: Reason for Different Results

Langmuir ◽  
2016 ◽  
Vol 32 (22) ◽  
pp. 5500-5509 ◽  
Author(s):  
V. B. Fainerman ◽  
V. I. Kovalchuk ◽  
E. V. Aksenenko ◽  
R. Miller
Keyword(s):  
Profile Analysis ◽  
Dilational Viscoelasticity ◽  
Adsorption Layers

Applications of SIMS to electronic materials and devices

1992 ◽  
Vol 50 (2) ◽  
pp. 1682-1683
Author(s):  
S.F. Corcoran
Keyword(s):  
Depth Distribution ◽  
Secondary Ion Mass Spectrometry ◽  
Semiconductor Device ◽  
Electronic Materials ◽  
Profile Analysis ◽  
Semiconductor Industry ◽  
Small Diameter ◽  
Depth Resolution ◽  
Detection Sensitivity

Over the past decade secondary ion mass spectrometry (SIMS) has played an increasingly important role in the characterization of electronic materials and devices. The ability of SIMS to provide part per million detection sensitivity for most elements while maintaining excellent depth resolution has made this technique indispensable in the semiconductor industry. Today SIMS is used extensively in the characterization of dopant profiles, thin film analysis, and trace analysis in bulk materials. The SIMS technique also lends itself to 2-D and 3-D imaging via either the use of stigmatic ion optics or small diameter primary beams.By far the most common application of SIMS is the determination of the depth distribution of dopants (B, As, P) intentionally introduced into semiconductor materials via ion implantation or epitaxial growth. Such measurements are critical since the dopant concentration and depth distribution can seriously affect the performance of a semiconductor device. In a typical depth profile analysis, keV ion sputtering is used to remove successive layers the sample.

Identifying Suicide Typologies Among Trauma-Exposed Veterans

Crisis ◽  
2020 ◽  
Vol 41 (4) ◽  
pp. 288-295 ◽  
Author(s):  
Nadia Bounoua ◽  
Jasmeet P. Hayes ◽  
Naomi Sadeh
Keyword(s):  
Latent Profile Analysis ◽  
Suicide Attempts ◽  
Clinical Symptoms ◽  
Profile Analysis ◽  
Risky Behaviors ◽  
Self Report ◽  
Cross Sectional ◽  
Research Priority ◽  
Self Harm ◽  
And Behaviors

Abstract. Background: Suicide among veterans has increased in recent years, making the identification of those at greatest risk for self-injurious behavior a high research priority. Aims: We investigated whether affective impulsivity and risky behaviors distinguished typologies of self-injurious thoughts and behaviors in a sample of trauma-exposed veterans. Method: A total of 95 trauma-exposed veterans (ages 21–55; 87% men) completed self-report measures of self-injurious thoughts and behaviors, impulsivity, and clinical symptoms. Results: A latent profile analysis produced three classes that differed in suicidal ideation, suicide attempts and nonsuicidal self-injury (NSSI): A low class that reported little to no self-injurious thoughts or behaviors; a self-injurious thoughts (ST) class that endorsed high levels of ideation but no self-harm behaviors; and a self-injurious thoughts and behaviors (STaB) class that reported ideation, suicide attempts and NSSI. Membership in the STaB class was associated with greater affective impulsivity, disinhibition, and distress/arousal than the other two classes. Limitations: Limitations include an overrepresentation of males in our sample, the cross-sectional nature of the data, and reliance on self-report measures. Conclusion: Findings point to affective impulsivity and risky behaviors as important characteristics of veterans who engage in self-injurious behaviors.

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