Polymer 4D printing: Advanced shape-change and beyond

4D printing is an exciting branch of additive manufacturing. It relies on established 3D printing techniques to fabricate objects in much the same way. However, structures which fall into the 4D printed category have the ability to change with time, hence the “extra dimension.” The common perception of 4D printed objects is that of macroscopic single-material structures limited to point-to-point shape change only, in response to either heat or water. However, in the area of polymer 4D printing, recent advancements challenge this understanding. A host of new polymeric materials have been designed which display a variety of wonderful effects brought about by unconventional stimuli, and advanced additive manufacturing techniques have been developed to accommodate them. As a result, the horizons of polymer 4D printing have been broadened beyond what was initially thought possible. In this review, we showcase the many studies which evolve the very definition of polymer 4D printing, and reveal emerging areas of research integral to its advancement.     

A convenient synthesis of 3-aryl-5-methylidene-2-thiohydantoins

3-Aryl-5-methylidene-2-thiohydantoins were constructed in one-pot reaction of aryl isothiocyanates and 3-morpholino- alanine in alkaline medium with the subsequent treatment with boiling hydrochloric acid.     

Highly diastereoselective multicomponent synthesis of polysubstituted 2-hydroxy-2-trifluoromethylpiperidineswith four and five stereogenic centers

The Michael–Mannich cascade cyclization of cyano olefins, ethyl 4,4,4-trifluoro-3-oxobutanoate, aromatic aldehydes and ammonium acetate provides convenient stereoselective formation of ethyl 5,5-dicyano-4,6-diaryl-2-hydroxy-2-(trifluoromethyl)piperidine-3-carboxylates with fourstereogenic centers and dialkyl 4,6-diaryl-5-cyano-2-hydroxy-2-(trifluoromethyl)piperidine-3,5-dicarboxylates with five stereogenic centers. Ammonium acetate plays dual role, acting as a base and as a nitrogen source.     

Periodicity of Two-Dimensional Bonding of Main Group Elements

In the periodic table the position of each atom follows the ‘aufbau’ principle of the individual electron shells. The resulting intrinsic periodicity of atomic properties determines the overall behavior of atoms in two-dimensional (2D) bonding and structure formation. Insight into the type and strength of bonding is the key in the discovery of innovative 2D materials. The primary features of 2D bonding and the ensuing monolayer structures of the main-group II–VI elements result from the number of valence electrons and the change of atom size, which determine the type of hybridization. The results reveal the tight connection between strength of bonding and bond length in 2D networks. The predictive power of the periodic table reveals general rules of bonding, the bonding-structure relationship, and allows an assessment of published data of 2D materials.     

No-Reference Video Quality Assessment using novel hybrid features and two-stage hybrid regression for score level fusion

This paper presents a novel No-Reference Video Quality Assessment (NR-VQA) model that utilizes proposed 3D steerable wavelet transform-based Natural Video Statistics (NVS) features as well as human perceptual features. Additionally, we proposed a novel two-stage regression scheme that significantly improves the overall performance of quality estimation. In the first stage, transform-based NVS and human perceptual features are separately passed through the proposed hybrid regression scheme: Support Vector Regression (SVR) followed by Polynomial curve fitting. The two visual quality scores predicted from the first stage are then used as features for the similar second stage. This predicts the final quality scores of distorted videos by achieving score level fusion. Extensive experiments were conducted using five authentic and four synthetic distortion databases. Experimental results demonstrate that the proposed method outperforms other published state-of-the-art benchmark methods on synthetic distortion databases and is among the top performers on authentic distortion databases. The source code is available at https://github.com/anishVNIT/two-stage-vqa.     

Lithiation MXene Derivative Skeletons for Wide-Temperature Lithium Metal Anodes

Lithium (Li) metal, as an appealing candidate for the next-generation of high-energy-density batteries, is plagued by its safety issue mainly caused by uncontrolled dendrite growth and infinite volume expansion. Developing new materials that can improve the performance of Li-metal anode is one of the urgent tasks. Herein, a new MXene derivative containing pure rutile TiO₂ and N-doped carbon prepared by heat-treating MXene under a mixing gas, exhibiting high chemical activity in molten Li, is reported. The lithiation MXene derivative with a hybrid of LiTiO₂-Li₃N-C and Li offers outstanding electrochemical properties. The symmetrical cell assembling lithiation MXene derivative hybrid anode exhibits an ultra-long cycle lifespan of 2000 h with an overpotential of ≈30 mV at 1 mA cm⁻², which overwhelms Li-based anodes reported so far. Additionally, long-term operations of 34, 350, and 500 h at 10 mA cm⁻² can be achieved in symmetrical cells at temperatures of −10, 25, and 50 °C, respectively. Both experimental tests and density functional theory calculations confirm that the LiTiO₂-Li₃N-C skeleton serves as a promising host for Li infusion by alleviating volume variation. Simultaneously, the superlithiophilic interphase of Li₃N guides Li deposition along the LiTiO₂-Li₃N-C skeleton to avoid dendrite growth.     

Epitaxial Growth of 2D Materials on High-Index Substrate Surfaces

Recently, the successful synthesis of wafer-scale single-crystal graphene, hexagonal boron nitride (hBN), and MoS₂ on transition metal surfaces with step edges boosted the research interests in synthesizing wafer-scale 2D single crystals on high-index substrate surfaces. Here, using hBN growth on high-index Cu surfaces as an example, a systematic theoretical study to understand the epitaxial growth of 2D materials on various high-index surfaces is performed. It is revealed that hBN orientation on a high-index surface is highly dependent on the alignment of the step edges of the surface as well as the surface roughness. On an ideal high-index surface, well-aligned hBN islands can be easily achieved, whereas curved step edges on a rough surface can lead to the alignment of hBN along with different directions. This study shows that high-index surfaces with a large step density are robust for templating the epitaxial growth of 2D single crystals due to their large tolerance for surface roughness and provides a general guideline for the epitaxial growth of various 2D single crystals.     

Determinants of the intention to use non-medical insertable digital devices: The case of Chile and Colombia

In the past, thinking of carrying electronic devices inside our bodies was only posed by non-real scenarios. The emergence of insertable devices has changed this. Since this technology is still in its initial development stages, few studies have investigated factors that influence its acceptance. This paper analyzes the predictors of the intention to use non-medical insertable devices in two Latin American contexts. We used partial least squares structural equation modeling to examine whether six constructs predicted intention to use insertable devices. A questionnaire was administered to undergraduate students located in Colombia and Chile (n = 672). We also examined whether these predictors influenced intention differently for both of them. Four common constructs significantly and positively influenced both Chilean and Colombian respondents to use insertable devices (hedonic motivation, habit, performance expectancy, and social influence). Also, the habit has a complementary mediating effect on the relationship between social influence and behavioral intention. By contrast, effort expectations were a positive and significant predictor, but only among Chilean respondents. Findings suggest that when technologies are emerging, well-known predictors of intention (e.g., performance and effort expectations) are less influential than predictors related to self-efficacy (e.g., habit and hedonic motivation). The use of insertable devices has a significant impact on society. Thus, a better understanding of what motivates their use has implications for both academia and industry.