Jerome Polesel-Maris

dblp:37/10004 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2014
0000-0003-0457-619XORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2Systems, architecture and hardware · 2Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Robot manipulation · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 100%
Human-computer interaction and pervasive computing
1 paper
Immersive interaction · 100%

Topics — the 2 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
micro/nano robotics
0.212014
A Nanorobotic System for In Situ Stiffness Measurements on Membranes · IEEE Trans. Robotics 2014
Robotics › Robot manipulation › micro/nano manipulation
nanomanipulation
0.212014
A Nanorobotic System for In Situ Stiffness Measurements on Membranes · IEEE Trans. Robotics 2014

Methods — techniques the papers use, named apart from their topics

tuning-fork-based dynamic force sensing · 0.6scanning electron microscopy · 0.69-DOF nanomanipulation · 0.6
YearPublicationVenuePosition
2014 A Nanorobotic System for In Situ Stiffness Measurements on Membranes
abstract
In order to characterize the mechanical behavior of fragile resonant microelectromechanical systems (MEMS)/nanoelectromechanical systems (NEMS), nondestructive measurements are required. In this paper, a cartography of local stiffness variations on a suspended micromembrane is established for the first time, by a tuning-fork-based dynamic force sensor inside a scanning electron microscope (SEM). Experiments are conducted individually on a batch of InP membranes 200 nm thin, using a 9-degree-of-freedom (dof) nanomanipulation system, complemented with virtual reality and automation tools. Results provide stiffness values in the range of a few newton per meter, with variations in a single sample depending on the membrane models.
Jean-Ochin Abrahamians, Bruno Sauvet, Jerome Polesel-Maris, Rémy Braive, Stéphane Régnier
IEEE Trans. Robotics3
2013 Robotic in situ stiffness cartography of InP membranes by dynamic force sensing
abstract
Typical methods of measuring mechanical properties at the micro-scale are destructive, and do not allow proper characterisation on resonant MEMS/NEMS. In this paper, a cartography of local stiffness variations on a suspended micromembrane is established for the first time, by a tuning-fork-based dynamic force sensor inside a SEM. Experiments are conducted on InP membranes 200nm thin, using a 9-DoF nano-manipulation system, complemented with virtual reality and automation tools. Results provide stiffness values ranging from 0.6 to 3 N/m on a single sample.
Jean-Ochin Abrahamians, Bruno Sauvet, Jerome Polesel-Maris, Rémy Braive, Stéphane Régnier
IROS3
2010 Tuning fork based in situ SEM nanorobotic manipulation system for wide range mechanical characterization of ultra flexible nanostructures
abstract
In this article, a nanorobotic manipulation system under Scanning Electron Microscope (SEM) is developed for mechanical property characterization of ultra flexible nano-structures. Frequency modulated quartz tuning fork is proposed as gradient force sensing. Helical Nanobelts (HNB) were used as example to demonstrate the capabilities of the proposed system. The stiffness of HNBs were obtained in full tensile elongation experiments, ranging from 0.009 N/m at rest position to 0.297 N/m at full elongation before breaking with a resolution of 0.0031 N/m. The non-linear behavior of the HNB's measured stiffness is clearly revealed for the first time in full range. Furthermore, the stiffness could be transformed into force measurement that ranges from 14.5 nN to 2.96 μN.
Juan Camilo Acosta, Gilgueng Hwang, Francois Thoyer, Jerome Polesel-Maris, Stéphane Régnier
IROS4