Advanced Engineering Materials最新文献

Periodic open cellular structures (POCS) are additively manufactured supports for heterogeneous catalysts in the field of chemical reaction engineering. Constructed from a repeated unit cell, POCS offer excellent heat transport characteristics due to heat conduction in the continuous solid matrix. However, when inserted into tubular reactors, a loose fit between structure and tube wall results. This considerably hinders heat transfer across the wall. The novel POCS concept presented in this work aims at an intensified wall heat transfer by utilizing a reentrant structure design to ensure auxetic behavior. If the POCS is made of shape memory alloy, it can recover its original shape. Combining these two effects with an initial radial oversize, an interference fit with the tube is established. This contribution comprises the geometric description of reentrant POCS and heat conduction simulations for characterization of the effective heat conductivity, yielding scaling correlations dependent on geometric parameters. Moreover, the effective radial heat conductivity of POCS in cylindrical shape is explicitly investigated. The influencing factor identified is the ratio of tube diameter and cell size: while the ratio increases, the effective radial heat conductivity decreases, but remains well above the effective heat conductivity of the unit cell.

Drop-Weight Impact Resistance

In article number 2400035, Douglas S. Galvao, Chandra S. Tiwary, and co-workers show that as the impactor (metallic tip) hits the complex 3D-printed porous structures, the impactor experiences multiple stress concentration regions throughout the porous structures; as a result, efficient stress concentrates around the pores, causing local deformation. During penetration of the impactor, the impact energy is absorbed in various events such as the tearing of layers, delamination, bulging, and densification of the structure.

Several studies focus on impact of residual stress in coatings, predominantly those synthesized by conventional physical vapor deposition (PVD) techniques like arc PVD and magnetron sputtering. High-speed PVD (HS-PVD) is based on hollow cathode gas flow sputtering, enabling the deposition of thick coatings s > 20 μm in contrast to the mentioned processes, where coating thickness is limited due to compressive residual stresses. Therefore, the effect of residual stresses on HS-PVD coatings and adhesion was analyzed for the first time. The aim is to evaluate the influence of diverse substrate materials, different coating systems, and process parameters on the residual stress states in HS-PVD coatings. Different coating systems like AlCrN and AlCrO are deposited at different reactive gas flows, coating times, and bias voltages. The residual stress of oxide coatings, deposited on cemented carbide and steel X40CrMoV5–1, is analyzed using X-ray diffraction (XRD) and the sin²ψ method. For AlCrN coatings, in addition to the XRD method, the residual stresses are measured by focused ion-beam-digital image correlation ring-core method to investigate different measuring methods. Both coating systems show higher adhesion strength with increasing thickness. Lower residual compressive stresses are unexpectedly observed at higher coating thickness using both analysis methods.

Direct Ink Writing

In article number 2400630, Yarjan Abdul Samad and co-workers use direct ink writing to fabricate an additively manufactured vision based tactile sensor, which cuts down the fabrication time, allows more control of the design, and reduces the feature complexities. The mechanical characteristics of the DIW sensor, robotic normality estimation, and finite element analysis are at par with those of molded Ecoflex, hence providing a fast, scaleable method to produce such sensors.

To propose a time-saving method for evaluating the fatigue strength of carburized steel, the fatigue behavior and fracture mechanism of carburized 14Cr14Co13Mo5 steels are studied by the rotary bending fatigue tests. It is found that the fatigue crack initiation site changes from surface to internal after carburizing due to the residual compressive stress and carbide cluster caused by the carburization. Besides, a notable correlation between the stress intensity of the cracked carbides at fatigue crack initiation site and fatigue life is observed in the carburized samples. This correlation allows for the estimation of fatigue strength at long conditional life based on samples tested at relatively high stress amplitudes with short lives, achieving a prediction error within 10% for the material studied. A significant time saving of ≈65% compared to the staircase method is achieved. The proposed method has significant implications for improving the efficiency fatigue strength evaluation in carburized steels containing carbides.

Conformal Electronics

In article number 2400220, Shuo Zhang, Yuhang Li, and co-workers introduce a facile approach to print completely conformal liquid metal circuits on arbitrary curved surfaces by a conformally attached 3D-printed customized conformal mask (CCM). Via CCM, conformal liquid metal circuits can be printed on the complex surfaces of aircraft, serving as intelligent skin. This work offers fabrication strategy for arbitrary curved surface conformal electronics in aeronautics and wearable devices.

Acoustic Emission

In article number 2400317, Abdulkadir Gulsen and co-workers present a novel ensemble feature selection methodology to rank features relevant to damage modes on AE signals in CFRP sandwich composites. Subsequently, ranked features are utilized in unsupervised clustering models to identify damage modes. The comparative results demonstrate that, in addition to the commonly used features, other features, like partial powers, have a robust correlation with damage modes.

The difficult determination of morphological properties in metal foams stands behind the reasons why metal foams are not widely used in industry, since quality control of the batches produced is limited to destructive methods. To approach this challenge, a new method of analysis of morphological properties based on 2D X-Ray radiograms and the employment of a new Convolutional Neural Network architecture is proposed. The training of this model is based on a combined approach of simulating simplified foams as pretraining data and the acquisition of real experimental data, extracted from X-Ray computer tomographies. The network is trained successfully with 41 foams to obtain predictions for cell size distribution between 0.3 and 5 mm, as well as sphericities in ranges from 0.4 to 1. In addition, tests are carried out to get an insight into the robustness of the model when confronted with similar data that are not included in the training process. It is found that the effectiveness of the neural network increases with a larger number of cells in the observed volume where above 500 cells per volume 92.5% of sphericity predictions and 99.4% of cell size predictions passed the Kolmogorov-Smirnov test.

Enhancing carbon dioxide (CO₂) detection is crucial for improving indoor air quality and environmental surveillance. Traditional CO₂ sensors face drawbacks like high costs, large sizes, environmental impact, and reliance on external power, limiting their practicality for continuous indoor monitoring. In this research, an innovative indoor CO₂-sensing system using a self-powered bio-solar cell (BSC) platform is introduced. Utilizing cyanobacteria as a sensitive biocatalyst and sustainable power source, the system offers a cost-effective, eco-friendly, and maintenance-free alternative to conventional sensors. It operates by monitoring electron-transfer processes in cyanobacteria during photosynthesis, converting CO₂ and water into oxygen and chemical energy, enabling accurate CO₂ level monitoring. The system responds to CO₂ fluctuations and issues alerts when levels are outside the recommended range of 500–1000 ppm for human health and productivity. A self-sustaining configuration of eight BSCs—one for sensing and others for power generation—ensures continuous operation without external power. An integrated energy-harvesting board efficiently manages power distribution to a microcontroller and display system for real-time data visualization, with the array producing up to 400 μW. Additionally, a machine-learning model interprets BSC outputs to accurately quantify CO₂ levels, enhancing the sensor's adaptive performance.

Pneumatic manipulation has the advantages of low cost, lightweight design, fast response, and ease of integration. However, its application in the field of phononic crystals remains limited. Inspired by pneumatic soft robots, this article proposes a pneumatic soft phononic crystal arranged in a square lattice, incorporating four pneumatic actuators within the scatterer. By manipulating air pressure, the bandgap can be effectively opened and closed. The finite element analysis is employed to examine the deformation and bandgaps of the pneumatic soft phononic crystal under varying air pressures. Moreover, the effect of the scatterer's rotation angle on the bandgap evolution in the phononic crystal is parametrically investigated. The results show that varying both the volume and the rotation angle of the scatterer can achieve bandgap opening, closing, and tuning. The proposed phononic crystal presents obvious practical applications and provides important insights for the design of soft-tunable acoustic devices.