Metrological investigation of a scanning electrostatic force microscope on a nano-positioning and nano-measuring machine. - In: Measurement science and technology, ISSN 1361-6501, Bd. 32 (2021), 10, 104012, insges. 7 S.
A surface profile measurement system was developed by combining a scanning electrostatic force microscope (SEFM) and a nano-measuring machine (NMM-1) and its characteristics were evaluated. SEFM is a type of scanning probe microscope (SPM) advocated in 2012. In SEFM, eliminating the trade-off between measurement accuracy, measurement speed, and stability has been a problem. As with other SPMs, the positioning accuracy of the probe and sample directly affects the measurement accuracy in SEFM. In this research, the SEFM principle was applied to the NMM-1, which is a high-precision positioning platform that achieves an uncertainty of smaller than 10 nm. In order to improve the force detection sensitivity, a probe polishing and assembling procedures was devised and, as a result, the quality factor of the sensor has been significantly improved. Furthermore, a method for optimizing scan parameters based on a theoretical model was proposed. The noise level of the measurement results was reduced by setting appropriate parameters, which agreed well with the theory. Profile measurements utilizing the developed measurement system were performed on line-and-space samples with an amplitude of 270 nm and a pitch of 10 [my]m. The results were compared with a conventional atomic force microscope as a reference. A surface measurement was performed on the sample, and a complete non-contact scan of a measurement range of 25 [my]m × 25 [my]m was demonstrated.
https://doi.org/10.1088/1361-6501/abf30c
Tip- and laser-based 3D nanofabrication in extended macroscopic working areas. - In: Nanomanufacturing and metrology, ISSN 2520-8128, Bd. 4 (2021), 3, S. 132-148
The field of optical lithography is subject to intense research and has gained enormous improvement. However, the effort necessary for creating structures at the size of 20 nm and below is considerable using conventional technologies. This effort and the resulting financial requirements can only be tackled by few global companies and thus a paradigm change for the semiconductor industry is conceivable: custom design and solutions for specific applications will dominate future development (Fritze in: Panning EM, Liddle JA (eds) Novel patterning technologies. International society for optics and photonics. SPIE, Bellingham, 2021. https://doi.org/10.1117/12.2593229). For this reason, new aspects arise for future lithography, which is why enormous effort has been directed to the development of alternative fabrication technologies. Yet, the technologies emerging from this process, which are promising for coping with the current resolution and accuracy challenges, are only demonstrated as a proof-of-concept on a lab scale of several square micrometers. Such scale is not adequate for the requirements of modern lithography; therefore, there is the need for new and alternative cross-scale solutions to further advance the possibilities of unconventional nanotechnologies. Similar challenges arise because of the technical progress in various other fields, realizing new and unique functionalities based on nanoscale effects, e.g., in nanophotonics, quantum computing, energy harvesting, and life sciences. Experimental platforms for basic research in the field of scale-spanning nanomeasuring and nanofabrication are necessary for these tasks, which are available at the Technische Universität Ilmenau in the form of nanopositioning and nanomeasuring (NPM) machines. With this equipment, the limits of technical structurability are explored for high-performance tip-based and laser-based processes for enabling real 3D nanofabrication with the highest precision in an adequate working range of several thousand cubic millimeters.
https://doi.org/10.1007/s41871-021-00110-w
Dynamic system modelling and process monitoring based on long-term dependency slow feature analysis. - In: Journal of process control, ISSN 0959-1524, Bd. 105 (2021), S. 27-47
Modern industrial processes are large-scale, highly complex systems with many units and equipment. The complex flow of mass and energy, as well as the compensation effects of closed-loop control systems, cause significant cross-correlation and autocorrelation between process variables. To operate the process systems stably and efficiently, it is crucial to uncover the inherent characteristics of both the variance structure and dynamic relationship. Compared with the original slow feature analysis (SFA) that can only model the one-step time dependence, long-term dependency slow feature analysis (LTSFA) proposed in this paper can understand the longer-term dynamics by an explicit expression of latent states of the process. An iterative algorithm is developed for the model parameter optimization and its convergency is proved. The model properties and theoretical comparison with existing dynamic models are presented. A process monitoring strategy is designed based on LTSFA. The results of two simulation case studies show that LTSFA has better system dynamics extraction capability, which reduces the violation rate of the residual for the 95% confidence interval from 40.4% to 3.2% compared to the original SFA, and can disentangle the quickly- and slowly-varying features. Several typical disturbances can be correctly identified by LTSFA. The monitoring results on the Tennessee Eastman process benchmark show the overall advantages of the proposed method both in the dynamic and nominal deviation detection and the monitoring accuracy
https://doi.org/10.1016/j.jprocont.2021.07.007
AES and EDX surface analysis of weathered float glass exposed in different environmental conditions. - In: Journal of non-crystalline solids, ISSN 0022-3093, Bd. 572 (2021), 121083
To characterize the influence of environmental conditions on glass weathering, two different float glasses were subjected to a six-month outdoor experiment that took place in Durres (seacoast, Albania), Ilmenau (rural, Germany) and Pristina (urban, Kosovo), three sites with largely different environmental conditions. Atmospheric deposits and meteorological conditions led this study to receive information about different weathering behaviour of two types of float glasses. Typical glass degradation effects and reaction products at the glass surface are shown and the impact of weathering and air quality parameters on the formation of reaction products and degradation is discussed. Surface changes have been localized using optical microscopy. Further investigations for receiving chemical information on the contaminations include Auger electron spectroscopy (AES) and scanning electron microscopy (SEM/EDX). Surface analyses indicate a high amount of weathering products such as chlorides, sulphates and carbonates followed by severe delamination effects for both types of glass exposed in Durres and Pristina. In contrast to this, low levels of soiling and degradation for the samples exposed in Ilmenau were detected.
https://doi.org/10.1016/j.jnoncrysol.2021.121083
On the role of arkypallidal and prototypical neurons for phase transitions in the external pallidum. - In: The journal of neuroscience, ISSN 1529-2401, Bd. 41 (2021), 31, S. 6673-6683
The external pallidum (globus pallidus pars externa [GPe]) plays a central role for basal ganglia functions and dynamics and, consequently, has been included in most computational studies of the basal ganglia. These studies considered the GPe as a homogeneous neural population. However, experimental studies have shown that the GPe contains at least two distinct cell types (prototypical and arkypallidal cells). In this work, we provide in silico insight into how pallidal heterogeneity modulates dynamic regimes inside the GPe and how they affect the GPe response to oscillatory input. We derive a mean-field model of the GPe system from a microscopic spiking neural network of recurrently coupled prototypical and arkypallidal neurons. Using bifurcation analysis, we examine the influence of dopamine-dependent changes of intrapallidal connectivity on the GPe dynamics. We find that increased self-inhibition of prototypical cells can induce oscillations, whereas increased inhibition of prototypical cells by arkypallidal cells leads to the emergence of a bistable regime. Furthermore, we show that oscillatory input to the GPe, arriving from striatum, leads to characteristic patterns of cross-frequency coupling observed at the GPe. Based on these findings, we propose two different hypotheses of how dopamine depletion at the GPe may lead to phase-amplitude coupling between the parkinsonian beta rhythm and a GPe-intrinsic y rhythm. Finally, we show that these findings generalize to realistic spiking neural networks of sparsely coupled Type I excitable GPe neurons. - SIGNIFICANCE STATEMENT Our work provides (1) insight into the theoretical implications of a dichotomous globus pallidus pars externa (GPe) organization, and (2) an exact mean-field model that allows for future investigations of the relationship between GPe spiking activity and local field potential fluctuations. We identify the major phase transitions that the GPe can undergo when subject to static or periodic input and link these phase transitions to the emergence of synchronized oscillations and cross-frequency coupling in the basal ganglia. Because of the close links between our model and experimental findings on the structure and dynamics of prototypical and arkypallidal cells, our results can be used to guide both experimental and computational studies on the role of the GPe for basal ganglia dynamics in health and disease.
https://doi.org/10.1523/JNEUROSCI.0094-21.2021
Gas-flow-assisted wrinkle-free transfer of a centimeter-scale ultrathin alumina membrane onto arbitrary substrates. - In: ACS applied materials & interfaces, ISSN 1944-8252, Bd. 13 (2021), 29, S. 35124-35132
The transfer of an ultrathin membrane onto arbitrary substrates is important in different practical fields. Conventional wet-transfer methods inevitably induce wrinkle defects as a result of the large contact angle of the trapped droplet between the membrane and the substrate. Here, we demonstrate a gas flow-assisted method (GFAM) to transfer centimeter (cm)-scale ultrathin membranes onto arbitrary substrates (including a curved substrate) without wrinkles. GFAM makes use of contact angle hysteresis to bulge the trapped droplet between the substrate and the ultrathin membrane and simultaneously stretch the ultrathin membrane during rapid dewetting driven by gas flow. Moreover, GFAM can be easily fulfilled by using compressed air for seconds. Compared with conventional hydrophilic treatments or organic liquid wetting, this method has no durability concern and does not change the surface nature of substrates. Taking a widely used ultrathin anodic aluminum oxide (AAO) membrane as an example, we successfully demonstrate the application of a large-area wrinkle-free ultrathin AAO membrane to defect-free ordered nanostructure array fabrication and investigate the micro-scale details of macro-scale wrinkles generated by the conventional ways. In addition, its corresponding superiority over the defective counterpart is further studied in optical sensing. This method is highly valuable for promoting the simplicity of large-area ultrathin membrane transfer in practice.
https://doi.org/10.1021/acsami.1c07574
Automatic segmentation of skin cells in multiphoton data using multi-stage merging. - In: Scientific reports, ISSN 2045-2322, Bd. 11 (2021), 14534, S. 1-19
We propose a novel automatic segmentation algorithm that separates the components of human skin cells from the rest of the tissue in fluorescence data of three-dimensional scans using non-invasive multiphoton tomography. The algorithm encompasses a multi-stage merging on preprocessed superpixel images to ensure independence from a single empirical global threshold. This leads to a high robustness of the segmentation considering the depth-dependent data characteristics, which include variable contrasts and cell sizes. The subsequent classification of cell cytoplasm and nuclei are based on a cell model described by a set of four features. Two novel features, a relationship between outer cell and inner nucleus (OCIN) and a stability index, were derived. The OCIN feature describes the topology of the model, while the stability index indicates segment quality in the multi-stage merging process. These two new features, combined with the local gradient magnitude and compactness, are used for the model-based fuzzy evaluation of the cell segments. We exemplify our approach on an image stack with 200 × 200 × 100 [my]m^3, including the skin layers of the stratum spinosum and the stratum basale of a healthy volunteer. Our image processing pipeline contributes to the fully automated classification of human skin cells in multiphoton data and provides a basis for the detection of skin cancer using non-invasive optical biopsy.
https://doi.org/10.1038/s41598-021-93682-y
Monolayer and bilayer graphene on Ru(0001): layer-specific and moiré-site-dependent phonon excitations. - In: The journal of physical chemistry letters, ISSN 1948-7185, Bd. 12 (2021), 29, S. 6889-6894
Graphene phonons are excited by the local injection of electrons and holes from the tip of a scanning tunneling microscope. Despite the strong graphene-Ru(0001) hybridization, monolayer graphene unexpectedly exhibits pronounced phonon signatures in inelastic electron tunneling spectroscopy. Spatially resolved spectroscopy reveals that the strength of the phonon signal depends on the site of the moiré lattice with a substantial red-shift of phonon energies compared to those of free graphene. Bilayer graphene gives rise to more pronounced spectral signatures of vibrational quanta with energies nearly matching the free graphene phonon energies. Spectroscopy data of bilayer graphene indicate moreover the presence of a Dirac cone plasmon excitation.
https://doi.org/10.1021/acs.jpclett.1c01802
Microfluidically supported characterization of responses of Rhodococcus erythropolis strains isolated from different soils on Cu-, Ni-, and Co-stress. - In: Brazilian journal of microbiology, ISSN 1678-4405, Bd. 52 (2021), 3, S. 1405-1415
We present a new methodological approach for the assessment of the susceptibility of Rhodococcus erythropolis strains from specific sampling sites in response to increasing heavy metal concentration (Cu2+, Ni2+, and Co2+) using the droplet-based microfluid technique. All isolates belong to the species R. erythropolis identified by Sanger sequencing of the 16S rRNA. The tiny step-wise variation of metal concentrations from zero to the lower mM range in 500 nL droplets not only provided accurate data for critical metal ion concentrations but also resulted in a detailed visualization of the concentration-dependent response of bacterial growth and autofluorescence activity. As a result, some of the isolates showed similar characteristics in heavy metal tolerance against Cu2+, Ni2+, and Co2+. However, significantly different heavy metal tolerances were found for other strains. Surprisingly, samples from the surface soil of ancient copper mining areas supplied mostly strains with a moderate sensitivity to Cu2+, Ni2+, and Co2+, but in contrast, a soil sample from an excavation site of a medieval city that had been covered for about eight centuries showed an extremely high tolerance against cobalt ion (up to 36 mM). The differences among the strains not only may be regarded as results of adaptation to the different environmental conditions faced by the strains in nature but also seem to be related to ancient human activities and temporal partial decoupling of soil elements from the surface. This investigation confirmed that microfluidic screening offers empirical characterization of properties from same species which has been isolated from sites known to have different human activities in the past.
https://doi.org/10.1007/s42770-021-00495-2
Directed energy deposition-arc (DED-Arc) and numerical welding simulation as a hybrid data source for future machine learning applications. - In: Applied Sciences, ISSN 2076-3417, Bd. 11 (2021), 15, 7075, S. 1-16
This research presents a hybrid approach to generate sample data for future machine learning applications for the prediction of mechanical properties in directed energy deposition-arc (DED-Arc) using the GMAW process. DED-Arc is an additive manufacturing process which offers a cost-effective way to generate 3D metal parts, due to its high deposition rate of up to 8 kg/h. The mechanical properties additively manufactured wall structures made of the filler material G4Si1 (ER70 S-6) are shown in dependency of the t8/5 cooling time. The numerical simulation is used to link the process parameters and geometrical features to a specific t8/5 cooling time. With an input of average welding power, welding speed and geometrical features such as wall thickness, layer height and heat source size a specific temperature field can be calculated for each iteration in the simulated welding process. This novel approach allows to generate large, artificial data sets as training data for machine learning methods by combining experimental results to generate a regression equation based on the experimentally measured t8/5 cooling time. Therefore, using the regression equations in combination with numerically calculated t8/5 cooling times an accurate prediction of the mechanical properties was possible in this research with an error of only 2.6%. Thus, a small set of experimentally generated data set allows to achieve regression equations which enable a precise prediction of mechanical properties. Moreover, the validated numerical welding simulation model was suitable to achieve an accurate calculation of the t8/5 cooling time, with an error of only 0.3%.
https://doi.org/10.3390/app11157075