Engineering Applications Research Articles

Modal Parameter Identification of Jacket-Type Offshore Wind Turbines Under Operating Conditions

Operational modal analysis (OMA) is essential for long-term health monitoring of offshore wind turbines (OWTs), helping identifying changes in structural dynamic characteristics. OMA has been applied under parked or idle states for OWTs, assuming a linear and time-invariant dynamic system subjected to white noise excitations. The impact of complex operating environmental conditions on structural modal identification therefore requires systematic investigation. This paper studies the applicability of OMA based on covariance-driven stochastic subspace identification (SSI-COV) under various non-white noise excitations, using a DTU 10 MW jacket OWT model as a basis for a case study. Then, a scaled (1:75) 10 MW jacket OWT model test is used for the verification. For pure wave conditions, it is found that accurate identification for the first and second FA/SS modes can be achieved with significant wave energy. Under pure wind excitations, the unsteady servo control behavior leads to significant identification errors. The combined wind and wave actions further complicate the picture, leading to more scattered identification errors. The SSI-COV based modal identification method is suggested to be reliably applied for wind speeds larger than the rated speed and with sufficient wave energy. In addition, this method is found to perform better with larger misalignment of wind and wave directions. This study provides valuable insights in relation to the engineering applications of in situ modal identification techniques under operating conditions in real OWT projects.

Research on information leakage in time series prediction based on empirical mode decomposition.

Time series analysis predicts the future based on existing historical data and has a wide range of applications in finance, economics, meteorology, biology, engineering, and other fields. Although the combination of decomposition techniques and machine learning algorithms can effectively solve the problem of predicting nonstationary sequences, this kind of decomposition-integration-prediction strategy of the prediction method has serious defects. After the decomposition of the division of the training set and the test set, the information of the test set in the process of decomposition of the information leakage ultimately shows a high accuracy of the prediction of the illusionary. This paper proposes three improvement strategies for this type of "information leakage" problem: sliding window decomposition (SW-EMD), single training and multiple decomposition (STMP-EMD), and multiple training and multiple decomposition (MTMP-EMD). They are combined with a bidirectional multiscale temporal convolutional network (MSBTCN), bidirectional long- and short-term memory network (BiLSTM), and attention mechanism (DMAttention), which introduces a dependency matrix based on cosine similarity to be applied to water quality prediction. The experimental results show that the model achieves good performance in the prediction of three water quality indicators (pH, DO and KMnO4), and the accuracies of the three models proposed in this paper are improved by 1.958% and 0.853% in terms of the RMSE and MAPE, respectively, compared with those of the mainstream LSTM models. The key contributions of this study include the following: (1) three methods are proposed to improve the class EMD decomposition, which can effectively solve the problem of "information leakage" that exists in the current models via class EMD decomposition; (2) the CEEMDAN-MSBTCN-BiLSTM-DMAttention model structure is innovated by combining improved class EMD decomposition methods; and (3) the three improved decomposition methods proposed in this paper can effectively solve the problem of "information leakage" and optimize the prediction model at the same time. This study provides an effective experimental method for water quality prediction and can effectively address the problem of "overfitting" models via class EMD decompositions during model training and testing.

Application and prospects of interface engineering in energy storage and conversion of graphdiyne‐based materials

AbstractA new carbon allotrope, graphdiyne (GDY) has great promise for future use. Much interest was piqued when it was initially prepared in 2010. GDY is made up of sp‐ and sp2‐hybridized carbon atoms. It has a one‐atom thick two‐dimensional structure and many interesting and useful qualities, such as strong chemical bonds, super‐large π structures, the ability to change from an alkyne to an alkene, and can be grown on any surface. GDY has become one of the frontier hotspots in chemistry and materials science, with original research achievements in energy conversion and storage, catalysis, intelligent information, life sciences constantly emerging and so on, showing revolutionary performance. In electrochemical cells, the electrode interface content not only accounts for a small proportion in the entire electrode system but it also plays a crucial role, affecting the efficiency, lifespan, power performance, and safety performance of the battery. In view of this, the intrinsic properties of GDY have been thoroughly analyzed, and a new GDY‐based electrochemical interface has been proposed by combining the key problems of electrochemical interfaces in electrochemical energy storage and conversion. This has led to new understanding and insights to address many critical scientific issues. In this review, the structure, characteristics, and applications of GDY in interface engineering are presented. In particular, recent advances in GDY and its aggregates in energy storage and conversion are summarized and discussed.

Poly(norepinephrine)-Mediated Universal Surface Modification for Patterning Human Pluripotent Stem Cell Culture and Differentiation.

Maintaining undifferentiated states of human pluripotent stem cells (hPSCs) is key to accomplishing successful hPSC research. Specific culture conditions, including hPSC-compatible substrates, are required for the hPSC culture. Over the past two decades, substrates supporting hPSC self-renewal have evolved from undefined and xenogeneic protein components to chemically defined and xenogeneic-free materials. However, these synthetic substrates are often costly and complex to use, leading many laboratories to continue using simpler undefined extracellular matrix (ECM) protein mixtures. In this study, we present a method using poly(norepinephrine) (pNE) for surface modification to enhance the immobilization of ECM proteins on various substrates, including polydimethylsiloxane (PDMS) and ultralow attachment (ULA) hydrogels, thereby supporting hPSC culture and maintenance of pluripotency. The pNE-mediated surface modification enables spatial patterning of ECM proteins on nonadhesive ULA surfaces, facilitating tunable macroscopic cell patterning. This approach improves hPSC attachment and growth and allows for cell patterning to study the effects of anisotropic environments on the hPSC fate. Our findings demonstrate the versatility and simplicity of pNE-mediated surface modification for improving hPSC culture and spatially controlled differentiation into endothelial cells and cardiomyocytes on previously nonamenable substrates, providing a valuable tool for tissue engineering and regenerative medicine applications.

Comparative enhancement of H+ and OH− treatment on electromagnetic interference shielding in aligned and compact Ti3C2Tx MXene film

Abstract The pressing demand for ultrathin and flexible shields to counter electromagnetic interference (EMI) has sparked interest in Ti3C2Tx MXene materials due to their exceptional electrical conductivity, tunable surface chemistry, and layered structure. However, pure Ti3C2Tx MXene films often lack the mechanical properties required for practical engineering applications, and traditional reinforcement methods tend to reduce electrical conductivity. This work demonstrates an effective strategy to enhance the alignment and densely packed layered structure of Ti3C2Tx MXene films by regulating the acidity and alkalinity of Ti3C2Tx MXene aqueous solutions. This approach simultaneously improves mechanical strength and electromagnetic interference shielding effectiveness (EMI SE). Compared with original Ti3C2Tx MXene films, MXene films modified with ammonia solution (NH3·H2O) via OH− show a significant improvement in tensile strength (27.7 ± 1.9 MPa). Meanwhile, MXene films treated with hydrochloric acid (HCl) via H+ reach an even higher tensile strength of 39 ± 1.5 MPa. Moreover, the EMI SE values of the treated MXene films increase significantly, each reaching 66.2 and 58.4 dB. The maximum improvements in EMI SE values for the acid- and alkali-treated samples are 17.9% and 4%, respectively. In conclusion, the simultaneous enhancement of mechanical strength and EMI shielding efficacy highlights the potential of acid- and alkali-treated Ti3C2Tx MXene films for applications in ultrathin and flexible EMI shielding materials. Graphical abstract

Experimental study on the shear behaviour of high-strength lightweight concrete beams incorporating graphene oxide.

Graphene oxide (GO) has achieved significant progress in the material behaviour of cement-based materials. However, research on its structural behaviour in high-strength lightweight concrete (HSLWC) structures is limited, which restricts its engineering applications. This study focused on investigating the effects of low contents of GO on the shear behaviour of HSLWC beams. A total of four HSLWC beams with GO contents of 0, 0.01, 0.03 and 0.05% (by weight of cement) were designed to observe failure modes, load‒deformation curves, shear capacities, crack behaviour and load‒strain curves under four-point loading by a 300 kN servo loading device. The results revealed that all the beams exhibited shear compression failure. GO improved the shear capacity of the HSLWC beams, and this strengthening effect increased with increase in GO content. When the content of GO was 0.05%, the ultimate load of the beam reached a maximum, which was 39.2% greater than that of the control beam. GO can endow the HSLWC beams with a certain degree of ductility. In addition, a modified JGJ 12-2006 model was proposed to predict the shear capacity of HSLWC beams containing different GO contents on the basis of a comparison of typical models. This study can provide exploratory engineering practice for evaluating and designing GO-reinforced HSLWC structures.

Multi‐Material Gradient Printing Using Meniscus‐enabled Projection Stereolithography (MAPS)

AbstractLight‐based additive manufacturing methods are widely used to print high‐resolution 3D structures for applications in tissue engineering, soft robotics, photonics, and microfluidics, among others. Despite this progress, multi‐material printing with these methods remains challenging due to constraints associated with hardware modifications, control systems, cross‐contamination, waste, and resin properties. Here, a new printing platform coined Meniscus‐enabled Projection Stereolithography (MAPS) is reported, a vat‐free method that relies on generating and maintaining a resin meniscus between a crosslinked structure and bottom window to print lateral, vertical, discrete, or gradient multi‐material 3D structures with no waste and user‐defined mixing between layers. MAPS is compatible with a wide range of resins shown and can print complex multi‐material 3D structures without requiring specialized hardware, software, or complex washing protocols. MAPS's ability to print structures with microscale variations in mechanical stiffness, opacity, surface energy, cell densities, and magnetic properties provides a generic method to make advanced materials for a broad range of applications.

Revolutionizing dairy waste: emerging solutions in conjunction with microbial engineering.

The dairy industry is grappling with significant challenges in managing effluent due to environmental concerns and stringent regulatory demands, necessitating innovative solutions. The paper investigates how microbial engineering is transforming the treatment of dairy wastewater, offering advanced methods to minimize environmental impact and enhance sustainability. It delves into the current challenges faced by the dairy industry, such as regulatory compliance and the limitations of traditional treatment technologies, and introduces microbial engineering as a promising solution for effluent management. Microbial engineering leverages genetic engineering techniques and microorganisms to enhance the efficiency of treatment processes like bioaugmentation and bioremediation. The environmental and economic benefits of microbial engineering, highlighting its potential to reduce pollution and lower operational costs for the dairy industry. The specific figures can vary based on factors like farm size and location, studies suggest that microbial engineering can reduce wastewater pollution by up to 50% and nutrient runoff by 30%. It also identifies key challenges and there are still areas including strains for specific pollutants (drugs, hormones), enhance degradation pathways, and increase microbes' stability (stress tolerance, long-term viability) that require further innovation to maximize its benefits. Through case studies and success stories, the paper demonstrates practical applications of microbial engineering in managing dairy effluent, illustrating how it can revolutionize industrial practices for a more sustainable future.

Biocomposite Scaffolds for Tissue Engineering: Materials, Fabrication Techniques and Future Directions

Tissue engineering is an interdisciplinary field that combines materials, methods, and biological molecules to engineer newly formed tissues to replace or restore functional organs. Biomaterials-based scaffolds play a crucial role in developing new tissue by interacting with human cells. Tissue engineering scaffolds with ideal characteristics, namely, nontoxicity, biodegradability, and appropriate mechanical and surface properties, are vital for tissue regeneration applications. However, current biocomposite scaffolds face significant limitations, particularly in achieving structural durability, controlled degradation rates, and effective cellular integration. These qualities are essential for maintaining long-term functionality in vivo. Although commonly utilized biomaterials can provide physical and chemical properties needed for tissue regeneration, inadequate biomimetic properties, as well as insufficient interactions of cells-scaffolds interaction, still need to be improved for the application of tissue engineering in vivo. It is impossible to achieve some essential features using a single material, so combining two or more materials may accomplish the requirements. In order to achieve a proper scaffold design, a suitable fabrication technique and combination of biomaterials with controlled micro or nanostructures are needed to achieve the proper biological responses. This review emphasizes advancements in scaffold durability, biocompatibility, and cellular responsiveness. It focuses on natural and synthetic polymer combinations and innovative fabrication techniques. Developing stimulus-responsive 3D scaffolds is critical, as these scaffolds enhance cell adhesion and promote functional tissue formation while maintaining structural integrity over time. This review also highlights the natural polymers, smart materials, and recent advanced techniques currently used to create emerging scaffolds for tissue regeneration applications.

Optimizing superelastic shape-memory alloy fibers for enhancing the pullout performance in engineered cementitious composites

Abstract This study explores the effect of integrated superelastic shape-memory alloy fibers (SMAFs) on the mechanical performance of engineered cementitious composites (ECCs). Various SMAF configurations – linear-shaped SMAFs (LS-SMAFs), hook-shaped SMAFs (HS-SMAFs), and indented-shaped SMAFs (IS-SMAFs) – with diameters of 0.8 and 1.0 mm were incorporated into ECC matrices, and surface texturization was achieved through abrasive paper treatment. Their mechanical properties were assessed through single fiber pullout tests on ECC mixtures containing 1.5 and 2.0% polyvinyl alcohol (PVA), subjected to both monotonic and cyclic loading conditions. Qualitative analysis, employing scanning electron microscopy, demonstrated that the IS-SMAF configuration provided superior mechanical interlocking and fiber–matrix adhesion, with a distinct flag shape observed during tensile testing. Quantitative data indicated that IS-SMAFs significantly improved the tensile strength and pullout resistance, with slip distances of ≥5 mm and average pullout loads ranging from 263 to 403 N. LS-SMAFs demonstrated better performance compared to HS-SMAFs and LS-SMAFs in terms of tensile and pullout characteristics. Additionally, ECCs with increased PVA content exhibited enhanced withdrawal performance. Thermogravimetry analysis and X-ray diffraction provided insights into the high-temperature stability and crystalline structure of the composites. These results underscore the effectiveness of IS-SMAFs in enhancing ECC properties, offering significant implications for the development and optimization of high-performance composite materials in civil engineering applications.

B3AM: A beamforming toolbox for three-component ambient seismic noise analysis

We introduce the MATLAB toolbox B3AM for beamforming of three-component ambient noise array data. We explain the theory behind three-component beamforming and polarisation analysis in particular, provide an overview of the workflow, and discuss the output using a worked example. The strength of the presented code package is the analysis of multiple beam response maps from multiple time windows. Hence, it provides statistical information about the ambient noise wavefield recorded over a period of time, such as the ratio of surface to body waves, average dispersion velocities, or dominant propagation direction. It can be used to validate assumptions made about the ambient noise wavefield in a particular location, helping to interpret results from other techniques, such as the analysis of horizontal-to-vertical spectral ratios or ambient noise interferometry, and enabling more precise monitoring of specific wavefield components. While designed initially with seismic networks in mind, B3AM is applicable over a wide range of frequencies and array sizes and can thus be adapted also for laboratory settings or civil engineering applications.

Model Test on Thermomechanical Behavior of Deeply Buried Pipe Energy Pile Under Different Temperature Loads and Mechanical Loads

Deeply buried pipe energy pile (DBP-EP) offers the capability to harness geothermal energy from significantly deeper subterranean layers than those available inside buried pipe energy pile (IBP-EP). Despite its potential, there is a notable scarcity of research on the thermomechanical behavior of DBP-EP. This study meticulously observed the thermal variations in the soil surrounding the DBP-EP, the mechanical response of the pile itself, the earth pressure at the pile toe, and the displacement occurring at the pile’s top during the heating phase across various operational conditions. The findings show that for every 1 °C increase in inlet temperature, the temperature difference between the inlet and outlet increases by about 0.27 °C. The method of load application at the pile top during heating markedly influences the frictional resistance along the pile’s sides. Furthermore, When the pile top load rises from 0.26 kN to 0.78 kN, the observed vertical load at the pile foot decreases by 2.2–8.51%. This indicates that the increase in the pile top load reduces the downdrag effect on the sandy soil near the pile toe. This reduction subsequently diminishes the impact of vertical loads on the pile toe. Notably, after continuous operation for 8 h, the rate of increase in pile top displacement for DBP-EP shows a decline. Additionally, for every 1 °C rise in the inlet water temperature, the final displacement at the pile top diminishes by approximately 0.03‰D. This research endeavors to furnish a robust theoretical foundation for the structural design and practical engineering applications for DBP-EP.

A Hardware Chaotic Neural Network With Gap Junction Models

ABSTRACTWe aim at the engineering applications of reservoir computing using hardware chaotic neural networks, including associative memory recall. The reservoir layer used in reservoir computing is networked and constructed using pulse‐type hardware chaos neuron models (P‐HCNMs). The structure of the reservoir layer is simple, which is advantageous for hardware implementation. By inducing chaos in the reservoir layer, it is possible to use the “chaotic edge” where the reservoir reaches its highest efficiency. It has also been reported that incorporating self‐correction within the reservoir layer increases the efficiency of the task. In this paper, we constructed a hardware small‐world neural network using a synaptic model with spike timing‐dependent synaptic plasticity (STDP) and a gap junction model. As a result, it is clarified that all cell body models with synaptic model connections show chaotic firing by simulation at the same time, and that the STDP model enables learning while keeping the chaotic phenomena. In addition, comparison with the firing of cell body models coupled only with synaptic models suggested that the gap junction model works significantly in inducing chaos in neural networks.

Study on Bandgap of Two‐Dimensional Square Lattice Acoustic Metamaterial with Multiembedded Cores

Acoustic metamaterials have been widely studied for their excellent ability of vibration isolation. In this article, a 2D square lattice acoustic metamaterial structure with multiembedded cores is proposed. Based on Bloch's theorem and finite element method, the band structures and bandgap properties of the structure are calculated and analyzed, and the vibration isolation ability of the structure is investigated. The effects of structural parameters on the bandgap property are analyzed. Thus, the anisotropy of the structure is also analyzed by the contours of phased velocity and group velocity. The results show that the structure has significant bandgap properties and vibration isolation. The second‐order similarity ratio has significant effects on the bandgap property. Via increasing the second‐order similarity ratio, the total bandgap width and low‐frequency bandgap width are widened. In addition, the structure has significant anisotropy, and the energy of elastic wave propagates at the direction of 45° and 135°. The research in this article supplements the design and research of 2D lattice acoustic metamaterials and makes a beneficial exploration for future engineering applications.

Comparative study of fibers extracted from the stems and roots of the Cameroonian pennissetum purpureum for their applications in compressed earth brick reinforcement and textile engineering

This work focuses on the extraction and experimental characterization of pennisetum purpureum fibers extracted from stems and roots, harvested in the Batié Kingdom, in the West Region of Cameroon. After extracting fibers using the boiling water technique, they are chemically treated to improve their properties and performance and to facilitate their incorporation into various composite materials. For the physical characterizations, it is measured: the absolute and apparent densities, the linear mass, the water absorption rate, and the diameter via the microscope. The mean values of the diameters and the measure of their frequency distributions are calculated, followed by the statistical analysis using the maximum entropy principle, in order to find the most probable diameter necessary for technological applications. For the mechanical properties, only the tensile tests are performed, with the determination of the young modulus of both the stems and roots. The results thus obtained showed that the fibers of the stems have an absolute density of (1.35 g/cm3), a linear mass of (54.6 tex), an apparent density of (0.45 g/cm3), a water content of (12.73%), an absorption rate of (142.46%), a porosity of (65.91%), a mean diameter of (7 mm), an elastic modulus of (3.98 GPa), a tensile strength of value of (1186.59 MPa) and an elongation of 16.17%, while the root fibers have an absolute density of (1.34 g/cm3), a linear mass (16.76 tex), an apparent density of (0.37845 g/cm3), a water content of (12.25%), an absorption rate of (193.16%), a porosity of (71.92%), a diameter of (4 mm), an elastic modulus of (1.55 GPa), a tensile strength of a value of (1960.35 MPa) and an elongation of 60.6%. Thus, the fibers of the stems have good mechanical properties, which make them an appropriate material in several applications, such as the reinforcement of composite materials.

Genetic Engineering in Bacteria, Fungi, and Oomycetes, Taking Advantage of CRISPR

Genetic engineering has revolutionized our ability to modify microorganisms for various applications in agriculture, medicine, and industry. This review examines recent advances in genetic engineering techniques for bacteria, fungi, and oomycetes, with a focus on CRISPR-Cas systems. In bacteria, CRISPR-Cas9 has enabled precise genome editing, enhancing applications in antibiotic production and metabolic engineering. For fungi, despite challenges associated with their complex cell structures, CRISPR/Cas9 has advanced the production of enzymes and secondary metabolites. In oomycetes, significant plant pathogens, modified Agrobacterium-mediated transformation, and CRISPR/Cas12a have contributed to developing disease-resistant crops. This review provides a comparative analysis of genetic engineering efficiencies across these microorganisms and addresses ethical and regulatory considerations. Future research directions include refining genetic tools to improve efficiency and expand applicability in non-model organisms. This comprehensive overview highlights the transformative potential of genetic engineering in microbiology and its implications for addressing global challenges in agriculture, medicine, and biotechnology.

Polyurethane foam adhesive with fly ash as a sustainable stabilizer

ABSTRACT This experimental research work investigates the role of polyurethane foam adhesive (PFA) in evaluating the unconfined compressive strength (UCS) of three different types of sands with varying maximum particle sizes (Dmax = 4.00 mm, 2.00 mm, and 0.63 mm) mixed with different proportions of fly ash (FA = 0%, 5%, 10%, and 15%). Moreover, this study includes the influence of the polymer percentages (PFc = 2%, 4%, 6%, and 8%) and particle size characteristics on the UCS of the tested materials. The obtained results indicate a significant increase in the UCS and ductility at a particular fly ash content (FA = 5%), where the increment of the polyurethane foam content from PFc = 2% to 8% induces an increasing of the UCS from 1.64 MPa to 5.28 MPa (a 3.2% increase). It is found that higher values of PFc = 8% and FA = 15% exhibit noticeable improvements and stabilization of the strength properties in the tested mixtures. Additionally, the UCS of the enhanced mixtures can be predicted using a newly introduced parameter called the polymer factor index (IPF), which considers the porosity and PFA content properties. The PFA-enhanced sand-fly ash mixtures offer a promising and innovative solution in many geotechnical engineering applications due to their reliable mechanical performances.

Multiscale understanding of structural effect on explosive dispersal of granular media

Explosive dispersal of granular media widely occurs in nature across various length scales, enabling engineering applications ranging from commercial or military explosive systems to the loss prevention industry. However, the correlation between the explosive dispersal behaviour and the structure of dispersal system is far from completely understood, thereby compromising the prediction of the explosive dispersal outcome resulting from a specific dispersal system. Here, we investigate the dispersal behaviours of densely packed particle rings driven by the enclosed pressurized gases using coarse-grained computational fluid dynamics–discrete parcel method. Distinct dispersal modes emerge from the dispersal systems with vastly varying sets of the macro- and micro-scale structural parameters in terms of the dispersal completeness and the spatial uniformity of the dispersed mass. Further investigation reveals the variation in the dispersal modes arises from the collective effects of multiscale gas–particle coupling relationships. Specifically, the macroscale coupling dictates the cyclic momentum/energy transfer between gases and particle ring as an entirety. The mesoscale coupling relates to the inter-pore gas filtration through the thickness of the particle ring, leading to the mass/energy reduction of the explosive source. The microscale coupling involves the individual particle dynamics influenced by the local flow parameters. A persistent macroscale coupling results in an incomplete dispersal which takes the form of an aggregated annular band, whereas the meso- and micro-scale couplings alter the macroscale coupling to a different extent. By incorporating the effects of the variety of structural parameters on the multiscale gas–particle coupling relationships, a non-dimensional parameter referred to as the modified mass ratio is constructed, which shows an explicit correlation with the dispersal mode. We proceed to establish a dispersal ring model in the continuum frame which accounts for the macro and meso-scale coupling effects. This model proves to be capable of successfully predicting the ideal and validated failed dispersal modes.

Influence of micro-milling machining parameters on residual stresses in alumina bioceramics-a three-dimensional finite element simulation study.

The formation and distribution of residual stress during the micro-milling process significantly affect the crack resistance and service life of alumina bioceramics. This study aims to optimize the surface residual stress distribution by adjusting machining parameters, thereby improving the machining quality of alumina ceramics. A three-dimensional finite element model of alumina bioceramics was developed, and numerical simulations were conducted to analyze the effects of feed per tooth, cutting depth, and spindle speed on temperature and residual stress. The study further explores the patterns of residual stress variation. The results show that both surface temperature and residual tensile stress exhibit systematic trends with parameter changes. Specifically, surface residual tensile stress increases with cutting depth initially but decreases sharply once the cutting depth exceeds 25 μm. Residual tensile stress increases with spindle speed, reaching its peak at 21,000 r/min before stabilizing. Additionally, the residual tensile stress rises with feed per tooth at first but gradually declines when the value exceeds 25 μm/z. This research reveals the mechanisms by which micro-milling parameters influence surface temperature and residual stress in alumina bioceramics, providing theoretical guidance for optimizing micro-milling processes. The findings can also be extended to the micro-milling of other hard-to-machine materials, offering broad engineering application potential.

Harnessing Extreme Internal Damping in Polyrotaxane‐Incorporated Liquid Crystal Elastomers for Pressure‐Sensitive Adhesives

AbstractLiquid crystal elastomers (LCEs) exhibit extraordinary energy dissipation due to their unique viscoelastic response, resulting from the rotation of mesogens under mechanical stress. While recent studies demonstrate the LCE‐based pressure‐sensitive adhesives (PSAs) by exploiting the enhanced damping, all previous studies have focused on LCEs with covalent crosslinks. Here, a new class of PSAs is developed by integrating movable polyrotaxane crosslinkers into an LCE matrix (PRx‐LCEs). Dynamic viscoelastic measurements reveal that PRx‐LCE exhibits a remarkably high energy dissipation, as indicated by a large tan δ. Interestingly, the secondary tan δ peak associated with LCE damping is more pronounced than the primary peak of the glass transition. The exceptional energy dissipation in PRx‐LCE results in superior adhesion strength (≈1864 N m−1), which is 3.5 times higher than conventional LCEs and 13 times higher than commercial PSAs in the peel test. Additionally, PRx‐LCEs demonstrate thermally reversible adhesion, enabling clean removal at elevated temperatures. Furthermore, the sliding effect in PRx‐LCE enhances both deformability and stress relaxation under load, resulting in deeper indentation, and superior adhesion during the probe tack test. The combination of LCE and slidable crosslinks provides robust and switchable adhesion, making them promising for applications in biomedical engineering, display, and semiconductor industries.