Molecular Manipulation Lab

Novel devices created in the MoMaLab

Scanning Quantum Dot Microscopy (SQDM)
An outstanding device created with the help of controlled molecular manipulation is the scanning quantum dot microscope. This microscope is a non-contact AFM to the tip of which a molecular quantum dot is attached. The molecule is placed on the tip by controlled lifting from the surface. Remarkably, the molecule stays in a configuration vertical to the tip surface where its frontier orbitals are electronically decoupled from the metal tip. In this configuration the molecule has the properties of a quantum dot. It can be gated by applying a bias voltage to the surface and charged with a single electron. The principle of scanning quantum dot microscopy is that this gating can also be the result of electrostatic potentials of nanostructures on the surface. Depending on the sign and magnitude of the nanostructure’s electric potential more or less bias voltage is required to change the charge state of the molecular quantum dot. The abrupt change of the charge state can be detected in the non-contact AFM frequency signal. SQDM is a very sensitive method to image electrostatic surface potential with unparalleled lateral resolution and/or speed.

SQDM principle



Read the original publications:
[1] C. Wagner et al. Scanning Quantum Dot Microscopy, PRL (2015)
[2] M. F. B. Green et al. Scanning quantum dot microscopy: A quantitative method to measure local electrostatic potential near surfaces, Jap. J. Appl. Phys. (2016)
News

February 15th, 2019

We welcome Joshua Scheidt, computer science student at Maastricht University, who joins the MoMaLab to do his master thesis.

February 4th, 2019

Hand-controlled STM-based atomic manipulation with real-time visual feedback from an MD simulation Read at Beilstein..

October 25th, 2018

We have been granted 2 Mio core‑h on JURECA for our simulation work on molecular adsorption and manipulation.

September 6th, 2018

We are happy that MSc Michael Maiworm joins us till January to work on molecular control algorithms.
Meet us at
▶   IPAM 2nd reunion meeting "Understanding Many-Particle Systems with Machine Learning"Lake Arrowhead, California, 09-14 June 2019