Pierpaolo  Belardinelli

Dr. Pierpaolo Belardinelli

Faculty 3mE, Department Precision and Microsystems Engineering, TU Delft, Mekelweg 2, 2628 CD Delft, The Netherlands
orcid

Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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25 January 2019 in Nano Letters
Verified
Journal Article
Open access
RDRobin Dolleman
Robin Dolleman
PBPierpaolo Belardinelli
Pierpaolo Belardinelli
SHSamer Houri
Samer Houri
HZHerre S. J. van der Zant
Herre S. J. van der Zant
FAFarbod Alijani
Farbod Alijani
PSPeter Steeneken
Peter Steeneken
Stochastic switching between the two bistable states of a strongly driven mechanical resonator enables detection of weak signals based on probability distributions, in a manner that mimics biological systems. However, conventional silicon resonators at the microscale require a large amount of fluctuation power to achieve a switching rate in the order of a few Hertz. Here, we employ graphene membrane resonators of atomic thickness to achieve a stochastic switching rate of 4.1 kHz, which is 100 times faster than current state-of-the-art. The (effective) temperature of the fluctuations is approximately 400 K, which is 3000 times lower than the state-of-the-art. This shows that these membranes are potentially useful to transduce weak signals in the audible frequency domain. Furthermore, we perform numerical simulations to understand the transition dynamics of the resonator and use analytical expressions to investigate the relevant scaling parameters that allow high-frequency, low-temperature stochastic switching to be achieved in mechanical resonators.

1 November 2018 in Carbon
Verified
Journal Article
Open access
BSBanafsheh Sajadi
Banafsheh Sajadi
SHSimon van Hemert
Simon van Hemert
BABehrouz Arash
Behrouz Arash
PBPierpaolo Belardinelli
Pierpaolo Belardinelli
PSPeter Steeneken
Peter Steeneken
FAFarbod Alijani
Farbod Alijani

19 December 2018 in Small
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Journal Article
Open access
PDF file
ASAndré F. Sartori
André F. Sartori
PBPierpaolo Belardinelli
Pierpaolo Belardinelli
RDRobin Dolleman
Robin Dolleman
PSPeter G. Steeneken
Peter G. Steeneken
MGMurali Krishna Ghatkesar
Murali Krishna Ghatkesar
Josephus BuijnstersJosephus Buijnsters
Josephus Buijnsters
Diamond is a highly desirable material for state‐of‐the‐art micro‐electromechanical (MEMS) devices, radio‐frequency filters and mass sensors, due to its extreme properties and robustness. However, the fabrication/integration of diamond structures into Si‐based components remain costly and complex. In this work, a lithography‐free, low‐cost method is introduced to fabricate diamond‐based micro‐resonators: a modified home/office desktop inkjet printer is used to locally deposit nanodiamond ink as ∅50–60 µm spots, which are grown into ≈1 µm thick nanocrystalline diamond film disks by chemical vapor deposition, and suspended by reactive ion etching. The frequency response of the fabricated structures is analyzed by laser interferometry, showing resonance frequencies in the range of ≈9–30 MHz, with Q ‐factors exceeding 10 4 , and ( f 0 × Q ) figure of merit up to ≈2.5 × 10 11 Hz in vacuum. Analysis in controlled atmospheres shows a clear dependence of the Q ‐factors on gas pressure up until 1 atm, with Q ∝ 1/ P . When applied as mass sensors, the inkjet‐printed diamond resonators yield mass responsivities up to 981 Hz fg −1 after Au deposition, and ultrahigh mass resolution up to 278 ± 48 zg, thus outperforming many similar devices produced by traditional top‐down, lithography‐based techniques. In summary, this work demonstrates the fabrication of functional high‐performance diamond‐based micro‐sensors by direct inkjet printing.

1 August 2013 in International Journal of Engineering Science
Verified
Journal Article
Closed access
PBPierpaolo Belardinelli
Pierpaolo Belardinelli
MBMaurizio Brocchini
Maurizio Brocchini
LDL. Demeio
L. Demeio
SLStefano Lenci
Stefano Lenci

25 May 2016 in Nonlinear Dynamics
Verified
Journal Article
Closed access
PDF file
PBPierpaolo Belardinelli
Pierpaolo Belardinelli
SLStefano Lenci
Stefano Lenci

5 April 2022 in Nanoscale Advances
Verified
Journal Article
Open access
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ACAbhilash Chandrashekar
Abhilash Chandrashekar
PBPierpaolo Belardinelli
Pierpaolo Belardinelli
MBMiguel A. Bessa
Miguel A. Bessa
USUrs Staufer
Urs Staufer
FAFarbod Alijani
Farbod Alijani
In this article we make use of data-science and machine learning to distil physically interpretable models from AFM measurements and predict nanoscale interaction forces with sub-microsecond resolution directly from experimental data.