scholarly journals Novel in situ sensing surface forces apparatus for measuring gold versus gold, hydrophobic, and biophysical interactions

2021 ◽  
Vol 39 (2) ◽  
pp. 023201
Author(s):  
Valentina Wieser ◽  
Pierluigi Bilotto ◽  
Ulrich Ramach ◽  
Hui Yuan ◽  
Kai Schwenzfeier ◽  
...  
Wear ◽  
2000 ◽  
Vol 245 (1-2) ◽  
pp. 190-195 ◽  
Author(s):  
Yuval Golan ◽  
Carlos Drummond ◽  
Jacob Israelachvili ◽  
Reshef Tenne

Author(s):  
J. Liu ◽  
K. Xiao ◽  
J.-N. Deng ◽  
A. Zaslavsky ◽  
S. Cristoloveanu ◽  
...  
Keyword(s):  

2014 ◽  
Vol 85 (1) ◽  
pp. 013702 ◽  
Author(s):  
Gutian Zhao ◽  
Qiyan Tan ◽  
Li Xiang ◽  
Di Zhang ◽  
Zhonghua Ni ◽  
...  

2018 ◽  
Vol 43 (1) ◽  
pp. 129-143 ◽  
Author(s):  
Jake R. Nelson ◽  
Tony H. Grubesic

Following the Deepwater Horizon oil spill of 2010, a substantial body of research has focused on the development of computational tools and analytical frameworks for modeling oil spill events. Much of this work is dedicated to deepening our understanding of the interactions between oil, fragile ecosystems, and the environment, as well as the impacts of oil on human settlements which are vulnerable to spill events. These advances in oil spill modeling and associated analytics have not only increased the efficiency of spill interdiction and mitigation efforts, they have also helped to nurture proactive, versus reactive, response strategies and plans for local and regional stakeholders. The purpose of this paper is to provide a progress report on the wide range of computational tools, analytical frameworks, and emerging technologies which are necessary inputs for a complete oil spill modeling package. Specifically, we explore the use of relatively mature tools, such as dedicated spill modeling packages, geographic information systems (GIS), and remote sensing, as well emerging technologies such as aerial and aquatic drones and other in-situ sensing technologies. The integration of these technologies and the advantages associated with using a geographic lens for oil spill modeling are discussed.


Soft Matter ◽  
2011 ◽  
Vol 7 (19) ◽  
pp. 9366 ◽  
Author(s):  
Qingye Lu ◽  
Jing Wang ◽  
Ali Faghihnejad ◽  
Hongbo Zeng ◽  
Yang Liu

Sign in / Sign up

Export Citation Format

Share Document