Reduction Capability Research Articles

Surface Modification of 3D Biomimetic Shark Denticle Structures for Drag Reduction.

Shark skin features superhydrophilic and riblet-textured denticles that provide drag reduction, antifouling, and mechanical protection. The artificial riblet structures exhibit drag reduction capabilities in turbulent flow. However, the effects of the surface wettability of shark denticles and the cavity region underneath the denticle crown on drag reduction remain insufficiently explored. Here, 3D printing is utilized to fabricate realistic staggered and overlapped denticle arrays, modified to achieve superhydrophilic, superhydrophobic, and hybrid configurations, including external riblets hydrophilic/internal cavities hydrophobic (ELIB), and vice versa (EBIL). Denticles of varying heights are also fabricated. The results indicate that superhydrophobic, ELIB, and EBIL denticles outperform superhydrophilic ones in reducing drag, achieving a peak drag reduction rate of ≈20%. Notably, shorter denticles further improve drag reduction. Reduced vortex formation within the underneath cavity correlates with improved drag reduction. These vortices can function similarly to rolling bearings while facilitating momentum exchange and increasing skin friction drag. Superhydrophobic or partially superhydrophobic denticles (ELIBD/EBILD) mitigate this effect. This study suggests that sharks may secrete mucus on specific sections of their denticles to further reduce vorticity and drag, offering novel insights into the biomimetic design of shark denticles for optimized drag reduction.

A novel dynamic vibration absorber for vibration control of piping systems under multi-frequency harmonic excitations

To suppress the significant vibration line spectra of piping systems under multi-frequency harmonic excitations, a novel dynamic vibration absorber (NDVA) is designed. The NDVA integrates numerous independent resonant units within a finite space through an ingenious structural design and possesses rich frequency regulation characteristics. A vibration model of the piping system equipped with the NDVA is established, and the approximate equivalent parameters of both the piping and the resonant units are inverted based on the frequency response function (FRF) test results. These parameters can be substituted into the model to enhance the accuracy and validity of the theoretical calculations. Based on the relationship between the absorbing bandwidth of the NDVA and the intervals of multi-frequency excitation frequencies, a tailored regulation strategy for different densities of excitation frequencies is proposed. Subsequently, the multi-frequency vibration reduction capability of the NDVA is verified through an example involving dual-frequency harmonic excitations. When there is a notable difference in the intensities of the multi-frequency vibration line spectra, a genetic algorithm is utilized to optimize the mass allocation of the resonant units. Simulation and test results demonstrate that the maximum response amplitude of the optimized system is further reduced.

Optimizing stability and characteristics of a vibrating rigid body pendulum with energy harvesting device

The focus of this paper is on reducing vibrations and capturing energy from a three degrees-of-freedom (3DOF) dynamical system. The system consists of a damped spring-pendulum with an elliptical pivot path at a constant angular velocity and a connected rigid body experiencing external harmonic forces and moments. An independent electromagnetic energy harvesting system has been integrated into the structure, utilizing the motion of a magnet within a coil. The optimization efforts target both energy harvesting (EH) and vibration reduction capabilities. The second kind of Lagrange’s equations are used to formulate the governing kinematic equations, which are then solved asymptotically using the multiple-scales technique (MST), producing novel and precise results up to the third approximation. Various resonance cases are identified, with three examined concurrently. The time evolution of the solutions, as well as the modified phases and amplitudes, are analyzed through graphical representations, taking into account the influential parameters of the system. Graphical plots of phase portraits successfully depicted the system’s stable dynamics. The power output and current time profiles of the electromagnetic device are presented to demonstrate the impact of various parameters on system behavior. Analysis of stability and instability areas reveals that the system exhibits stable performance across a wide range of parameters. This model is gaining significance in contemporary applications, especially in control sensors used across various sectors such as industry, construction, automotive, transportation, and infrastructure.

Bearing Fault Feature Extraction Method Based on Adaptive Time-Varying Filtering Empirical Mode Decomposition and Singular Value Decomposition Denoising

Aiming to address the difficulty in extracting the early weak fault features of bearings under complex operating conditions, a fault diagnosis method is proposed based on the adaptive fusion of time-varying filtering empirical mode decomposition (TVF-EMD) modal components and singular value decomposition (SVD) noise reduction. First, the snake optimization (SO) technique is used to optimize the TVF-EMD algorithm in order to determine the optimal parameters that match the input signal. Then, the bearing signal is divided into a number of intrinsic mode functions (IMFs) using TVF-EMD in order to reduce the nonlinearity and non-stationary characteristics of the fault signal. An index for the envelope fault information energy ratio (EFIER) is created to overcome the drawback of there being too many IMF components after TVF-EMD decomposition. The IMF components are ranked in descending order according to the EFIER, and they are fused according to the maximum principle of the energy ratio of envelope fault information until the optimal fusion component is determined. Finally, the fault feature is extracted when the optimal fusion component is denoised using SVD. Two measured bearing fault signals and simulation signals are used to validate the performance of the proposed method. The experimental findings demonstrate that the approach has good sensitive feature screening, fusion, and noise reduction capabilities. The proposed method can more precisely extract the early fault features of bearings and accurately identify fault types.

Diversity and physiology of abundant Rhodoferax species in global wastewater treatment systems.

Wastewater treatment plants rely on complex microbial communities for bioconversion and removal of pollutants, but many process-critical species are still poorly investigated. One of these genera is Rhodoferax, an abundant core genus in wastewater treatment plants across the world. The genus has been associated with many metabolic traits such as iron reduction and oxidation and denitrification. We used 16S rRNA gene amplicon data to uncover the diversity and abundance of Rhodoferax species in Danish and global treatment plants. Publicly available metagenome-assembled genomes were analyzed based on phylogenomics to delineate species and assign taxonomies based on the SeqCode. The phylogenetic analysis of "Rhodoferax" revealed that species previously assigned to Rhodoferax in wastewater treatment plants should be considered as at least eight different genera, with five representing previously undescribed genera. Genome annotation showed potential for several key-bioconversions in wastewater treatment, such as nitrate reduction, carbohydrate degradation, and accumulations of various storage compounds. Iron oxidation and reduction capabilities were not predicted for abundant species. Species-resolved FISH-Raman was performed to gain an overview of the morphology and ecophysiology of selected taxa to clarify their potential role in global wastewater treatment systems. Our study provides a first insight into the functional and ecological characteristics of several novel genera abundant in global wastewater treatment plants, previously assigned to the Rhodoferax genus.

The effects of orifice shape on the dominant jet frequency in crossflow

The jet in crossflow describes a unique flow characteristic, which involves the injection of a fluid jet into a turbulent boundary layer. This flow structure is significant for applications in vibration reduction, noise suppression, and cooling and heat transfer. In this study, a numerical model for jet-in-crossflow was established using Large Eddy Simulation, and the accuracy of simulation results was validated by comparison with experimental data. On the basis of maintaining the same jet exit flow rate, the study investigated the differences in fundamental flow characteristics, wall pressure fluctuations, and flow noise among jet-in-crossflow cases with circular, square, and elliptical orifices. The distribution of sound sources for the three cases was identified using vortex sound theory. The study shows that the elliptical orifice case did not develop a jet blockage effect similar to the other cases. All three orifice cases generated counter-rotating vortex pairs, although the vortex core positions varied. For the circular and square orifices, the root mean square pressure along the lower edge of the orifice exhibited a symmetric distribution, while the elliptical orifice case showed no clear symmetry. In the downstream region, spanning 2–10 orifice diameters, a stable dominant frequency was observed for all three cases, which is attributed to vortex transport. The elliptical orifice demonstrated significant noise reduction performance, with a noise reduction of 3–8 dB, mainly concentrated in the downstream region up to 10 orifice diameters. Using Proper Orthogonal Decomposition and Dynamic Mode Decomposition, the relationship between vortex transport and wall pressure fluctuations for the three cases was explained. The analysis revealed the fundamental reason behind the noise reduction capabilities of the elliptical orifice and the vortex structures responsible for generating the dominant frequency.

X-ray induced in-situ ferroptosis through the Fenton reaction of iron supplements for the cancer therapy

The potential of iron-based therapeutic agents in enhancing radiotherapy efficacy through catalyzing the Fenton reaction has garnered widespread interest. The inherent instability of ferrous ions requires the use of complex ligands for the ligand-dependent reduction from Fe3+ to Fe2+, thereby boosting ferroptosis through inducing the Fenton reaction. However, the reliance on complex redox systems and potential long-term toxicity have seriously limited the clinical application in cancer treatment. In this study, we propose an innovative approach that utilizes the reduction capabilities of hydrated electrons generated by X-ray to directly reduce both ferric ions (Fe3+) and Iron Proteinsuccinylate, a clinically used iron supplement. Our experiments showed that over 20 % of Fe3+, at a concentration of 23 μM, was reduced by X-ray without the need for ligand involvement. Furthermore, both in vitro and in vivo studies confirmed that Iron Proteinsuccinylate exhibited the highest tumor growth inhibition rate through the Fenton reaction and ferroptosis, offering a new and safer method for the in-situ reduction of Fe3+ and enhancing the efficacy of radiotherapy.

A recyclable T-ZIF-8/SnO2@PAN photocatalytic porous fibrous membrane used for CO2 reduction

The challenge of separating and recycling high-performance photocatalysts often results in resource wastage and secondary environmental contamination. Therefore, the advancement of recyclable photocatalysts has emerged as a frontier area of interest in the domain of photocatalytic CO2 reduction. In this work, T-ZIF-8/SnO2@PAN-PVP fibrous membranes were constructed with T-ZIF-8/SnO2 as a photocatalyst, polyacrylonitrile (PAN) as a matrix, polyvinylpyrrolidone (PVP) as a porogen utilizing electrospinning technique. By regulating the variable parameters, the effects of spinning solution concentration, conductive salt dosage, porogenic agent dosage and their effects on fiber microscopic morphology were investigated, and the process parameters were optimized to obtain the best microscopic morphology, and then the photocatalytic porous fibers were obtained through the water impregnation treatment. A comparative analysis of the CO2 reduction capability of photocatalytic powders, fibers, and porous fibers was performed, alongside an exploration of the potential reaction mechanism. The results indicate that the T-ZIF-8/SnO2@PAN-PVP porous fiber membrane irradiated by visible light for 4 h demonstrates excellent CO2 reduction efficiency, achieving CO, CH4, and H2 production rates of 14.3, 7.09, and 8.57 μmol·g−1·h−1, respectively. Durability tests through repetitive experiments have validated that the T-ZIF-8/SnO2@PAN/ZnCl2 porous fiber membrane retains over 90 % of its initial photocatalytic activity after four cycles, thereby facilitating the sustainable recycling and reuse of photocatalysts.

Benefits and Challenges of California Offshore Wind Electricity: An Updated Assessment

Offshore wind (OSW) technology has recently been included in California’s plans to achieve 100% carbon-free electricity by 2045. As an emerging technology, many features of OSW are changing more rapidly than established renewable options and are shaped by local circumstances in unique ways that limit transferrable experiences globally. This paper fills a gap in the literature by providing an updated technological assessment of OSW in California to determine its viability and competitiveness in the state’s electricity generation mix to achieve its near-term energy and environmental goals. Through a critical synthesis and extrapolation of technical, social, and economic analyses, we identify several major improvements in its potential. First, we note that while estimates of OSW’s costs per MWh of installed capacity have generally documented and projected a long-term decline, recent technical, microeconomic, and macroeconomic factors have caused significant backsliding of this momentum. Second, we project that the potential dollar value benefits of OSW’s greenhouse gas reduction capabilities have increased by one to two orders of magnitude, primarily due to major upward revisions of the social cost of carbon. Several co-benefits, including enhanced reliability, economic growth, and environmental justice, look to be increasingly promising due to a combination of technological advances and policy initiatives. Despite these advancements, OSW continues to face several engineering and broader challenges. We assess the current status of these challenges, as well as current and future strategies to address them. We conclude that OSW is now overall an even more attractive electricity-generating option than at the beginning of this decade.

DEVELOPMENT OF A WEBSITE-BASED FETAL MOVEMENT MONITORING TOOL

Background: The development of technology by utilizing sensors to record body bioelectricity is a challenge in the transformation of health in the pillar of biotechnology that can be used to detect fetal movement with a non-transmission and inexpensive system. Advances in sensor technology can be used for long-term fetal movement recording. This study discusses the development of a system that can be used by pregnant women to monitor fetal movement using an accelerometer that has a fairly high accuracy in detecting fetal movement. Mobile phone applications to monitor fetal movement using an accelerometer in areas with limited resources have a fairly high level of accuracy and can be used as a tool in monitoring fetal movement. Research on fetal movement recording devices can provide valuable information about the condition of the fetus and its health, and has developed into a reliable technology that can be used in clinical settings. Objective: to develop a website-based fetal recording device. Method: The research method used is the research and development (R&D) method, this method is used to develop certain products and test the effectiveness of the product. Results: The results displayed in the software are in the form of excel which will be processed into a logarithm of fetal movement recorded by the electrode and then an analysis of fetal movement signals will be carried out compared to the movement results from the mother's perception. Conclusion: The prototype demonstrates superior noise reduction capabilities but may require optimized preprocessing to preserve event-related signal variations.

Impact of EV interfacing on peak-shelving and frequency regulation in a microgrid

A vehicle-to-grid (V2G) technology enables bidirectional power exchange between electric vehicles (EVs) and the power grid, presenting enhanced grid stability and load management opportunities. This study investigates a comprehensive microgrid system integrating EVs with solar (8 MW), wind (4.5 MW), and diesel generation sources, focusing on peak load reduction and frequency regulation capabilities. Through MATLAB/Simulink simulations using a Phasor model, we analyze five distinct scenarios with varying EV fleet sizes (20–100 vehicles, 40 kW each). Results demonstrate that V2G integration effectively maintains grid frequency within 59.5–60.5 Hz across all test cases, achieving optimal performance using 100 EVs. Through strategic EV discharge scheduling, the system successfully reduces evening peak loads from 3000 to 2200 kW. Economic analysis reveals decreasing payback periods from 5.2 to 2.8 years as fleet size increases, with ROI improving from 12.5 to 23.1%. These findings establish quantitative benchmarks for V2G implementation in microgrids and demonstrate its viability for grid stability enhancement and load management applications.

AEGAN-Pathifier: a data augmentation method to improve cancer classification for imbalanced gene expression data

BackgroundCancer classification has consistently been a challenging problem, with the main difficulties being high-dimensional data and the collection of patient samples. Concretely, obtaining patient samples is a costly and resource-intensive process, and imbalances often exist between samples. Moreover, expression data is characterized by high dimensionality, small samples and high noise, which could easily lead to struggles such as dimensionality catastrophe and overfitting. Thus, we incorporate prior knowledge from the pathway and combine AutoEncoder and Generative Adversarial Network (GAN) to solve these difficulties.ResultsIn this study, we propose an effective and efficient deep learning method, named AEGAN, which combines the capabilities of AutoEncoder and GAN to generate synthetic samples of the minority class in imbalanced gene expression data. The proposed data balancing technique has been demonstrated to be useful for cancer classification and improving the performance of classifier models. Additionally, we integrate prior knowledge from the pathway and employ the pathifier algorithm to calculate pathway scores for each sample. This data augmentation approach, referred to as AEGAN-Pathifier, not only preserves the biological functionality of the data but also possesses dimensional reduction capabilities. Through validation with various classifiers, the experimental results show an improvement in classifier performance.ConclusionAEGAN-Pathifier shows improved performance on the imbalanced datasets GSE25066, GSE20194, BRCA and Liver24. Results from various classifiers indicate that AEGAN-Pathifier has good generalization capability.

Research on Dynamic Modeling and Vibration Characterization of Integrated Bearings

Integrated bearings, characterized by their unique structure, feature an inner ring that is seamlessly integrated with the shaft. This study is based on the theoretical framework of rolling bearing dynamics and considers bearing friction, lubrication, and Hertz elastic contact theory. A dynamic simulation model considering the interaction between the components of the rolling bearing is established. Additionally, a subroutine for calculating the interaction forces between the bearing components was written in C and compiled into a dynamic link library, which was then integrated with the dynamic simulation software. To solve and simulate the dynamics of the integrated bearing model, a sophisticated combination of a refined integration method and the predictor-corrector Adams–Bashforth–Moulton multistep technique was employed. The theoretical analysis offers insights into the vibration characteristics of the integrated bearings across different structural and operational parameters. Results indicate that a judicious selection of parameters, such as the curvature radius ratio of the inner and outer grooves and the gap of the cage pockets, can significantly enhance the bearings’ vibration and noise reduction capabilities. Furthermore, the application of an appropriate axial preload effectively reduces bearing vibrations, and there exists an optimal range of rotational speeds that minimizes these vibrations.

Heating reduction with shock control for a V-shaped blunt leading edge

This study investigates the heating issue associated with a V-shaped blunt leading edge (VBLE) in a hypersonic flow. The heat flux generation on the VBLE is highly correlated with the shock interaction configurations in the crotch region, determined by the relative position of the triple point T and the curved shock (CS). The primary Mach reflection (MR), accompanied by a series of secondary shock–shock interactions and shock wave–boundary layer interactions, can produce extremely high heating peaks on the crotch. To configure the shock wave structures and reduce the heat flux, a shock-controllable design approach is developed based on the simplified continuity method. The strategy involves the inverse design of the crotch sweep path, according to the location of the triple point and the contour of the CS. The comparisons between the pre-designed shock configurations and the numerical results demonstrate the reliability of the design approach across various free stream Mach numbers ranging from 6 to 10. A VBLE model designed with the shock configuration of regular reflection from the same family (sRR) at a free stream Mach number of 8 is examined. Under the design conditions, the outermost heat flux peak is reduced by 80 % compared with the baseline case. The heating reduction capabilities of the model under varying free stream Mach numbers and sideslip angles are also evaluated, confirming its robustness under undesigned operating scenarios.

Highly Compressible Micro/Nanofibrous Sponges with Thin-Walled Cavity Structures Enable Low-Frequency Noise Reduction.

Increasing noise pollution has generated a tremendous threat to human health and incurred great economic losses. However, most existing noise-absorbing materials present a significant challenge in achieving lightweight, robust mechanical stability, and efficient low-frequency (<1000 Hz) noise reduction. Herein, we create highly compressible micro/nanofibrous sponges with thin-walled cavity structures for efficient noise reduction through electrospinning and dispersion casting. Manipulating the phase separation driven by solution/water interaction in jets enables formation of fluffy fibrous frameworks, on which the deformation of casting dispersion is controlled to develop thin-walled cavity structures consisting of semiopened cells and entangled networks. The resultant sponges exhibit lightweight characteristics (2.2 mg cm-3) and mechanical robustness, integrated with remarkable low-frequency noise reduction capability (absorption coefficient up to 0.98) benefiting from vibration and viscous friction effects of cavity-structured skeletons. This work may offer new horizons for designing advanced fibrous acoustical materials, inspiring next-generation noise-reducing devices in aerospace and transportation.

Impact of Power Tiller Noise on the Occupational Health of Indian Farmers: A Case Study of Jammu and Kashmir

Power tillers have significantly improved the efficiency of agricultural operations in India. However, their noise emissions pose considerable health risks to operators. This study investigates the impact of power tiller noise on occupational health, and evaluates the effectiveness of various noise protection devices. Noise levels were recorded at different engine speeds, revealing that without protection, noise could reach 103.14 dB(A), surpassing the recommended safe occupational limit of 85 dB(A). Noise reduction capabilities of ear muffs, ear plugs, and moist cotton were assessed. Ear muffs provided highest noise reduction, lowering noise by 40.50%, followed by ear plugs (32.70%) and moist cotton (26.80%). The physiological impact of noise on operators was also measured, showing that ear muffs led to the most significant reductions in elevated blood pressure (both systolic and diastolic blood pressure) as well as increased heart rate. The findings underscore the urgent need for effective noise mitigation strategies in power tiller operations and recommend ear muffs as the most effective protective device for safeguarding operators’ health.

Impact of tree growth form on temporal and spatial patterns of particulate matter with various particle sizes in urban street canyons

ContextTrees play a vital role in reducing street-level particulate matter (PM) pollution in metropolitan areas. However, the optimal tree growth type for maximizing the retention of various sizes of PM remains uncertain.ObjectivesThis study assessed the PM reduction capabilities of evergreen and deciduous broadleaf street trees, focusing on how leaf phenology influences the dispersion of pollutants across particle sizes.MethodsWe collected data on six PM size fractions from 72 sites along streets lined with either evergreen or deciduous broadleaf trees in Wuhan, China, during the summer and winter of 2017–2018.ResultsEvergreen trees demonstrated superior PM reduction capabilities compared to deciduous trees, with evergreen street canyons showing 27.2% and 12.6% lower PM2.5 and PM10 concentrations in summer, and 13% and 5.5% lower concentrations in winter. During summer, evergreen streets predominantly contained fine particles (PM1, PM2.5), posing potential health risk due to their ability to infiltrate the human respiratory system. In contrast, deciduous streets primarily harbored coarser particles (PM4, PM7, PM10, and total suspended particulate [TSP]). During winter, larger particles were dominant, regardless of the tree growth form.ConclusionsEvergreen trees showed superior PM reduction capabilities compared to deciduous trees due to their year-round leaf retention, enhanced surface properties, and denser canopies that maximize PM capture. We recommend prioritizing evergreen broadleaf trees as the primary street trees while interspersing deciduous trees at appropriate intervals. This approach will ensure that urban greenery provides maximum ecological benefits while reducing the PM concentration.

First-Principle Calculations on O-Doped Hexagonal Boron Nitride (H-BN) for Carbon Dioxide (CO2) Reduction into C1 Products.

With the rapid growth of the world population and economy, the greenhouse effect caused by CO2 emissions is becoming more and more serious. To achieve the "two-carbon" goal as soon as possible, the carbon dioxide reduction reaction is one of the most promising strategies due to its economic and environmental friendliness. As an analog of graphene, monolayer h-BN is considered to be a potential catalyst. To systematically and theoretically study the effect of O doping on the CO2 reduction catalytic properties of monolayer h-BN, we have perform a series of first-principle calculations in this paper. The structural analysis demonstrates that O preferentially replaces N, leading to decreasing VBM of monolayer h-BN, which is conducive to improving its capability for CO2 reduction. The preferential CO2 adsorption sites on monolayer h-BN before and after O doping are the N-t site and B-t site, respectively. O doping increases the adsorption strength of CO2, which is favorable in the further hydrogenation of CO2. During the conversion of CO2 into CO and HCOOH via a two-electron pathway and CH3OH and CH4 via a six-electron pathway, O doping can reduce the energy barrier of the rate determining step (RDS) and change the key steps from uphill reactions to downhill reactions, thus increasing the probability of CO2 reduction. In conclusion, O(N)-doped h-BN exhibits the excellent CO2 reduction performance and has the potential to be a promising catalyst.

Vibro-acoustic behavior of partially submerged composite sandwich plates with negative Poisson’s ratio grids

Composite sandwich structures demonstrate significant potential for applications in Marine structures due to their corrosion resistance, high specific strength, and lightweight characteristics. This paper explores the underwater vibro-acoustic characteristics of composite sandwich plates featuring negative Poisson’s ratio grids. The composite sandwich plate comprises orthotropic carbon fiber and glass fiber laminates, along with a periodic grating structure. The fundamental units of the grating structure are star grids, chiral grids, and concave hexagonal grids, respectively. The vibration and noise reduction performance of the negative Poisson ratio composite sandwich plate is affirmed through comparison with the traditional regular hexagonal composite sandwich plate. The chiral and concave hexagonal grids demonstrate outstanding noise reduction capabilities, achieving up to 25 dB, though their vibration damping performance is poor. In contrast, the star grid still exhibits high acoustic response peaks but maintains a relatively stable vibration damping performance of around 5 dB. Finally, the paper explores the effects of different parameters on the vibro-acoustic behavior of composite sandwich plates with negative Poisson ratio grids, including cell equivalent Poisson ratio, panel layup angle, and plate curvature.

Laser-induced adhesives with excellent adhesion enhancement and reduction capabilities for transfer printing of microchips.

Transfer printing based on tunable and reversible adhesive that enables the heterogeneous integration of materials is essential for developing envisioned electronic systems. An adhesive with both adhesion enhancement and reduction capabilities in a rapid and selective manner is challenging. Here, we report a laser-induced adhesive, featuring a geometrically simple shape memory polymer layer on a glass backing, with excellent adhesion modulation capability for programmable pickup and noncontact printing of microchips. Selective and rapid laser heating substantially enhances the adhesive's adhesion strength from kilopascal to megapascal within 10 ms due to the shape fixing effect, allowing for precise and programmable pickup. Conversely, the enhanced adhesion can be quickly reduced and eliminated within 3 ms through the shape recovery effect, enabling noncontact printing. Demonstrations of transfer printing microlight-emitting diodes (LEDs) and mini-LEDs onto various low-adhesive flat, rough, and curved surfaces highlight the unusual capabilities of this adhesive for deterministic assembly.