Multilayers of Ti doped diamond-like carbon (Ti-DLC) coatings were deposited on aluminum alloys by filtered cathodic vacuum arc (FCVA) technology using C₂H₂ as a reactive gas. The effect of different Ti transition layer thicknesses on the structure, mechanical and adhesion properties of the coatings, was investigated by scanning electron microscopy (SEM), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), nanoindentation and a scratch tester. The results showed that the Ti transition layer could improve interfacial transition between the coating and the substrate, which was beneficial in obtaining excellent adhesion of the coatings. The Ti transition layer thickness had no significant influence on the composition and structure of the coatings, whereas it affected the distortion of the sp²-C bond angle and length. Nanoindentation and scratch test results indicated that the mechanical and adhesion properties of the Ti-DLC coatings depended on the Ti transition layer thickness. The Ti transition layer proved favorable in decreasing the residual compressive stress of the coating. As the Ti transition layer thickness increased, the hardness value of the coating gradually decreased. However, its elastic modulus and adhesion exhibited an initial decrease followed by an increasing fluctuation. Among them, the Ti-DLC coating with a Ti transition layer thickness of 1.1 μm exhibited superior mechanical properties.
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http://dx.doi.org/10.3390/ma11091742 | DOI Listing |
Nanoscale Adv
January 2025
Department of Condensed Matter Physics, Faculty of Mathematics and Physics, Charles University Ke Karlovu 5, 12116, Prague 2 Czech Republic
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View Article and Find Full Text PDFSci Rep
January 2025
Department of General Psychology and Padova Neuroscience Center, University of Padova, Padova, Italy.
Hierarchical generative models can produce data samples based on the statistical structure of their training distribution. This capability can be linked to current theories in computational neuroscience, which propose that spontaneous brain activity at rest is the manifestation of top-down dynamics of generative models detached from action-perception cycles. A popular class of hierarchical generative models is that of Deep Belief Networks (DBNs), which are energy-based deep learning architectures that can learn multiple levels of representations in a completely unsupervised way exploiting Hebbian-like learning mechanisms.
View Article and Find Full Text PDFNat Commun
January 2025
Joseph Henry Laboratories of Physics, Princeton University, Princeton, NJ, USA.
Colonies of the social bacterium Myxococcus xanthus go through a morphological transition from a thin colony of cells to three-dimensional droplet-like fruiting bodies as a strategy to survive starvation. The biological pathways that control the decision to form a fruiting body have been studied extensively. However, the mechanical events that trigger the creation of multiple cell layers and give rise to droplet formation remain poorly understood.
View Article and Find Full Text PDFNano Lett
January 2025
Department of Physics, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden.
Two-dimensional (2D) transition metal dichalcogenides (TMDs) have received significant interest for use in tunnel field-effect transistors (TFETs) due to their ultrathin layers and tunable band gap features. In this study, we used density functional theory (DFT) to investigate the electronic properties of six TMD heterostructures, namely, MoSe/HfS, MoTe/ZrS, MoTe/HfS, WSe/HfS, WTe/ZrS, and WTe/HfS, focusing on variations in band alignments. We demonstrate that WTe/ZrS and WTe/HfS have the smallest band gaps (close to 0 or broken) from the considered set.
View Article and Find Full Text PDFACS Nano
January 2025
Center for Terahertz Waves and School of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China.
The physical picture for photocurrent injection and coherent control in intrinsic graphene under two-color laser excitation remains obscure. Previously, photocurrent injection of intrinsic graphene was attributed to the quantum interference between two electronic transition pathways of single-photon and two-photon absorptions as well as layer-to-layer coupling. Here, we show that quantum interference between stimulated electronic Raman scattering and single-photon absorption plays a very important role in contributing to the total photocurrent, while interlayer coupling does not sufficiently affect the photocurrent injection, which is in contrast to the previous interpretation of the experimental results on photocurrent injection and coherent control.
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