Localized state and charge transfer in nitrogen-doped graphene

Nitrogen-doped epitaxial graphene grown on SiC(000?1) was prepared by exposing the surface to an atomic nitrogen flux. Using Scanning Tunneling Microscopy (STM) and Spectroscopy (STS), supported by Density Functional Theory (DFT) calculations, the simple substitution of carbon by nitrogen atoms has been identified as the most common doping configuration. High-resolution images reveal a reduction of local charge density on top of the nitrogen atoms, indicating a charge transfer to the neighboring carbon atoms. For the first time, local STS spectra clearly evidenced the energy levels associated with the chemical doping by nitrogen, localized in the conduction band. Various other nitrogen-related defects have been observed. The bias dependence of their topographic signatures demonstrates the presence of structural configurations more complex than substitution as well as hole-doping.Comment: 5 pages, accepted in PR

Coherent transport and scanning gate microscopy in graphene devices

In the fields of condensed matter physics and electronics, the advent of new types of materials with unconventional charge carrier dynamics first gives possibilities to explore peculiar physical phenomena, which can then open novel routes for the design of electronic devices. It is the case of graphene, a two-dimensional carbon crystal where charge carriers behave like massless relativistic particles. To benefit from the outstanding properties potentially offered by such a material, the first step is to understand how charge carriers propagate through graphene devices in order to control their motion inside the considered structures. In this thesis, we present experimental results on the electronic transport inside two types of graphene-based devices : (I) nitrogen-incorporated graphene Hall bars and (II) graphene quantum ring (QR) interferometers. A particular attention was brought to the investigation of coherent effects, involving charge carrier interferences. In addition, a scanning probe technique, called scanning gate microscopy (SGM), was used to image and control charge carrier dynamics inside mesoscopic graphene QRs at the local nm-scale. In nitrogen-incorporated graphene, our results evidence the substantial influence of the disorder induced by the presence of nitrogen atoms in the graphene lattice. We then directly observe in real space the effect of disorder in different transport regimes in SGM images of QRs. Beside the influence of disorder, SGM mapping of the charge carrier wave functions inside graphene QRs reveals the formation of scarlike features reminiscent of semi-classical periodic orbits scarring the local density of states along the QRs’ arms. Patterns imaged in SGM are found to be recurrent when varying the charge carrier energy, consistent with theoretical predictions for relativistic quantum scars.(FSA - Sciences de l'ingénieur) -- UCL, 201

Imaging coherent transport in a mesoscopic graphene ring

Mesoscopic graphene devices often exhibit complex transport properties, stemming both from the peculiar electronic band structure of graphene and from the high sensitivity of transport to local disorder in this twodimensional crystal. To disentangle contributions of disorder in the different transport phenomena at play in such devices, it is necessary to devise new local-probe methods and to establish links between transport and the microscopic structure of the devices. Here, we present a spatially resolved investigation of coherent transport inside a graphene quantum ring (QR), where Aharonov-Bohm conductance oscillations are observed. Thanks to scanning gate microscopy (SGM), we first identify spatial signatures of the Coulomb blockade, associated with disorder-induced localized states, and of charge-carrier interferences. We then image resonant states which decorate the QR local density of states (LDOS). Simulations of the LDOS in a model disorder graphene QR and temperature dependence of SGM maps confirm the presence of such scarred states

Recurrent Quantum Scars in a Mesoscopic Graphene Ring

When coherent charge carriers cross micron-scale cavities, their dynamics can be governed by a few resonant states, also called “quantum scars”, determined by the cavity geometry. Quantum scars can be described using theoretical tools but have also been directly imaged in the case of high-quality semiconductor cavities as well as in disordered graphene devices, thanks to scanning gate microscopy (SGM). Here, we discuss spatially resolved SGM images of low-temperature charge transport through a mesoscopic ring fabricated from high-quality monolayer graphene lying on top of hexagonal boron nitride. SGM images are decorated with a pattern of radial scars in the ring area, which is found to evolve smoothly and reappear when varying the charge-carrier energy. The energies separating recurrent patterns are found to be directly related to geometric dimensions of the ring. Moreover, a recurrence is also observed in simulations of the local density of states of a model graphene quantum ring. The observed recurrences are discussed in the light of recent predictions of relativistic quantum scars in mesoscopic graphene cavities

Damage evaluation in graphene underlying atomic layer deposition dielectrics

Based on micro-Raman spectroscopy (μRS) and X-ray photoelectron spectroscopy (XPS), we study the structural damage incurred in monolayer (1L) and few-layer (FL) graphene subjected to tomiclayer deposition of HfO2 and Al2O3 upon different oxygen plasma power levels. We evaluate the damage level and the influence of the HfO2 thickness on graphene. The results indicate that in the case of Al2O3/graphene, whether 1L or FL graphene is strongly damaged under our process conditions. For the case of HfO2/graphene, μRS analysis clearly shows that FL graphene is less disordered than 1L graphene. In addition, the damage levels in FL graphene decrease with the number of layers. Moreover, the FL graphene damage is inversely proportional to the thickness of HfO2 film. Particularly, the bottom layer of twisted bilayer (t-2L) has the salient features of 1L graphene. Therefore, FL graphene allows for controlling/limiting the degree of defect during the PE-ALD HfO2 of dielectrics and could be a good starting material for building field effect transistors, sensors, touch screens and solar cells. Besides, the formation of Hf-C bonds may favor growing highquality and uniform-coverage dielectric. HfO2 could be a suitable high-K gate dielectric with a scaling capability down to sub-5-nm for graphene-based transistor

Real-time online monitoring of insect cell proliferation and baculovirus infection using digital differential holographic microscopy and machine learning

Real-time, detailed online information on cell cultures is essential for understanding modern biopharmaceutical production processes. The determination of key parameters, such as cell density and viability, is usually based on the offline sampling of bioreactors. Gathering offline samples is invasive, has a low time resolution, and risks altering or contaminating the production process. In contrast, measuring process parameters online provides more safety for the process, has a high time resolution, and thus can aid in timely process control actions. We used online double differential digital holographic microscopy (D3HM) and machine learning to perform non-invasive online cell concentration and viability monitoring of insect cell cultures in bioreactors. The performance of D3HM and the machine learning model was tested for a selected variety of baculovirus constructs, products, and multiplicities of infection (MOI). The results show that with online holographic microscopy insect cell proliferation and baculovirus infection can be monitored effectively in real time with high resolution for a broad range of process parameters and baculovirus constructs. The high-resolution data generated by D3HM showed the exact moment of peak cell densities and temporary events caused by feeding. Furthermore, D3HM allowed us to obtain information on the state of the cell culture at the individual cell level. Combining this detailed, real-time information about cell cultures with methodical machine learning models can increase process understanding, aid in decision-making, and allow for timely process control actions during bioreactor production of recombinant proteins