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.

Conformation-dependent charge transport through short peptides.

We report on charge transport across single short peptides using the Mechanically Controlled Break Junction (MCBJ) method. We record thousands of electron transport events across single-molecule junctions and with an unsupervised machine learning algorithm, we identify several classes of traces with multifarious conductance values that may correspond to different peptide conformations. Data analysis shows that very short peptides, which are more rigid, show conductance plateaus at low conductance values of about 10-3G0 and below, with G0 being the conductance quantum, whereas slightly longer, more flexible peptides also show plateaus at higher values. Fully stretched peptide chains exhibit conductance values that are of the same order as that of alkane chains of similar length. The measurements show that in the case of short peptides, different compositions and molecular lengths offer a wide range of junction conformations. Such information is crucial to understand mechanism(s) of charge transport in and across peptide-based biomolecules.

Can One Define the Conductance of Amino Acids?

We studied the electron-transport properties of ten different amino acids and one dimer (di-methionine) using the mechanically controlled break-junction (MCBJ) technique. For methionine and cysteine, additional measurements were performed with the scanning tunneling microscope break-junction (STM-BJ) technique. By means of a statistical clustering technique, we identified several conductance groups for each of the molecules considered. Ab initio calculations revealed that the observed broad conductance distribution stems from the possibility of various binding geometries which can be formed during stretching combined with a multitude of possible conformational changes. The results suggest that it would be helpful to explore different experimental techniques such as recognition tunneling and conditions to help identify the nature of amino-acid-based junctions even further, for example, with the goal to establish a firm platform for their unambiguous recognition by tunneling break-junction experiments.

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 atomic-layer 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 high-quality 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 transistors.