MXene-Based Elastomer Mimetic StretchableSensors: Design, Properties, and Applications

Flexible sensors based on MXene-polymer composites are highly prospective for next-generation wearable electronics used in human-machine interfaces.One of the motivating factors behind the progress of flexible sensors is the steady arrival of new conductive materials.MXenes,a new family of 2D nanomaterials,have been draw-ing attention since the last decade due to their high electronic conduc-tivity,processability,mechanical robustness and chemical tunability.In this review,we encompass the fabrication of MXene-based polymeric nanocomposites,their structure-property relationship,and applications in the flexible sensor domain.Moreover,our discussion is not only lim-ited to sensor design,their mechanism,and various modes of sensing platform,but also their future perspective and market throughout the world.With our article,we intend to fortify the bond between flexible matrices and MXenes thus promoting the swift advancement of flexible MXene-sensors for wearable technologies.

Surface-enhanced Raman scattering on nanodiamond-derived carbon onions

Annealing nanodiamonds(ND) at high temperatures up to 1700 ℃ is a common method to synthesize carbon onions. The transformation from NDs to carbon onions is particularly interesting because of carbon onions' potential in the field of tribology and their application in ultra-charge/discharge devices. In this paper, a novel surface-enhanced Raman scattering technique that involves coating the sample with nanoscopic gold particles is proposed to characterize the NDs after different annealing treatments. Conventional Raman and surfaceenhanced Raman spectra were obtained, and the changes of peak parameters as the function of annealing temperature were evaluated. It was found that the widths of the D and the G peaks decreased with increasing annealing temperature, reflecting an improved order in the sp^2-hybridized carbon during the transformation from NDs to carbon onions. After annealing at 1700 ℃, the sp^2?carbon was highly ordered, indicating desirable electrical conductivity and lubricity. With increasing annealing temperature, the D peak showed a blue shift of almost30 cm^(-1), while the G peak merely shifted by 5 cm^(-1). For annealing temperatures above 1100 ℃, an increase of intensity ratio ID/IGwas observed. Compared to the uncoated area, red shifts of 0.5-2 cm^(-1) and of 5-9 cm^(-1) for the G and D peaks, respectively, were detected for the gold-coated area, which was due to the coupling of the plasmons and the phonons of the samples.

Erratum to:Tribological behaviour of Ti_(3)C_(2)T_(x)nano-sheets:Substrate-dependent tribo-chemical reactions

Erratum to Alberto Rota,Nicolas Bellina,Bo Wang&Andreas Rosenkranz.Tribological behaviour of Ti_(3)C_(2)T_(x)nano-sheets:Substratedependent tribo-chemical reactions.Friction 11(8):1522–1533(2023).

Predicting EHL film thickness parameters by machine learning approaches

Non-dimensional similarity groups and analytically solvable proximity equations can be used to estimate integral fluid film parameters of elastohydrodynamically lubricated(EHL)contacts.In this contribution,we demonstrate that machine learning(ML)and artificial intelligence(AI)approaches(support vector machines,Gaussian process regressions,and artificial neural networks)can predict relevant film parameters more efficiently and with higher accuracy and flexibility compared to sophisticated EHL simulations and analytically solvable proximity equations,respectively.For this purpose,we use data from EHL simulations based upon the full-system finite element(FE)solution and a Latin hypercube sampling.We verify that the original input data are required to train ML approaches to achieve coefficients of determination above 0.99.It is revealed that the architecture of artificial neural networks(neurons per layer and number of hidden layers)and activation functions influence the prediction accuracy.The impact of the number of training data is exemplified,and recommendations for a minimum database size are given.We ultimately demonstrate that artificial neural networks can predict the locally-resolved film thickness values over the contact domain 25-times faster than FE-based EHL simulations(R^(2) values above 0.999).We assume that this will boost the use of ML approaches to predict EHL parameters and traction losses in multibody system dynamics simulations.

Tribological behaviour of Ti_(3)C_(2)T_(x) nano-sheets: Substrate-dependent tribo-chemical reactions

MXenes,a newly emerging class of layered two dimensional(2D)materials,are promising solid lubricants due to their 2D structure consisting of weakly-bonded layers with a low shear strength and ability to form beneficial tribo-layers.This work aims at evaluating for the first time MXenes lubrication performance and tribofilm formation ability on different metallic substrates(mirror-lapped Fe and Cu discs).After depositing MXenes via ethanol(1 wt%)on the substrates,pronounced differences in the resulting substrate-dependent frictional evolution are observed.While MXenes are capable to reduce friction for both substrates after the full evaporation of ethanol,MXenes lubricating effect on Cu is long-lasting,with a 35-fold increased lifetime compared to Fe.Raman spectra acquired in the wear-tracks of the substrates and counter-bodies reveal notable differences in the friction-induced chemical changes depending on the substrate material.In case of Fe,the progressive failure of MXenes lubrication generates different Fe oxides on both the substrate and the ball,resulting in continuously increasing friction and a poor lubrication effect.For Cu,sliding induces the formation of a Ti_(3)C_(2)-based tribofilm on both rubbing surfaces,enabling a long-lasting lubricating effect.This work boosts further experimental and theoretical work on MXenes involved tribo-chemical processes.

Tailored surface textures to increase friction-A review

Surface textures with micro-scale feature dimensions still hold great potential to enhance the frictional performance of tribological systems.Apart from the ability of surface texturing to reduce friction,surface textures can also be used to intentionally increase friction in various applications that rely on friction for their adequate functioning.Therefore,this review aims at presenting the state-of-the-art regarding textured surfaces for high-friction purposes.After a brief general introduction,the recent trends and future paths in laser surface texturing are summarized.Then,the potential of surface textures to increase friction in different applications including adhesion,movement transmission and control,biomimetic applications,and road-tire contacts is critically discussed.Special emphasis in this section is laid on the involved mechanisms responsible for friction increase.Finally,current short-comings and future research directions are pointed out thus emphasizing the great potential of(laser-based)surface texturing methods for innovations in modern surface engineering.

Numerical micro-texture optimization for lubricated contacts-A critical discussion

Despite numerous experimental and theoretical studies reported in the literature,surface micro-texturing to control friction and wear in lubricated tribo-contacts is still in the trial-and-error phase.The tribological behaviour and advantageous micro-texture geometries and arrangements largely depend on the contact type and the operating conditions.Industrial scale implementation is hampered by the complexity of numerical approaches.This substantiates the urgent need to numerically design and optimize micro-textures for specific conditions.Since these aspects have not been covered by other review articles yet,we aim at summarizing the existing state-of–the art regarding optimization strategies for micro-textures applied in hydrodynamically and elastohydrodynamically lubricated contacts.Our analysis demonstrates the great potential of optimization strategies to further tailor micro-textures with the overall aim to reduce friction and wear,thus contributing toward an improved energy efficiency and sustainability.

Unprecedented differences in the diamond nucleation density between carbon-and silicon-faces of 4H-silicon carbides

4H-silicon carbides deposited by diamond films have wide applications in many fields such as semiconductor heterojunction,heat sink and mechanical sealing.Nucleation plays a critical role in the deposition of the diamond film on 4H-silicon carbides.Nevertheless,as a typical polar material,the fundamental mechanism of diamond nucleation on different faces of 4H-silicon carbides has not been fully understood yet.In this contribution,nucleation of diamond was performed on the carbon-and silicon-faces of 4H-silicon carbides in a direct current chemical vapor deposition device.The nucleation density on the carbon-face is higher by 2-3 orders of magnitude compared to the silicon-face.Transmission electron microscopy verifies that there are high density diamond nuclei on the interface between the carbon-face and the diamond film,which is different from columnar diamond growth structure on the silicon-face.Transition state theory calculation reveals that the unprecedented distinction of the nucleation density between the carbon-face and the silicon-face is attributed to different desorption rates of the absorbed hydrocarbon radicals.In addition,kinetic model simulations demonstrate that it is more difficult to form CH2(s)-CH2(s)dimers on silicon-faces than carbon-faces,resulting in much lower nucleation densities on silicon-faces.