Dong Lin

High-purity copper features excellent electrical conductivity but generally low mechanical properties. Adding a three-dimensional graphene network as reinforcement to make a copper–graphene metal matrix composite is promising for a wide range of applications with better mechanical performance and functional capabilities. However, direct application in a metal matrix is difficult due to unfavorable wetting, which causes poor dispersion and weak interfacial bonding in the graphene–metal system. Here, the powder metallurgy method was used to construct a three-dimensional continuous graphene network in the copper matrix combined with high-pressure torsion. Optimized deformation/thermomechanical treatment enhanced the microstructural development processed by the severe plastic deformation method of high-pressure torsion. The primary advantage of this hybrid process is that it enables us to achieve grains with a size in the ultra-fine or even nanoscale. A homogeneous equiaxed nanostructure without segregation was observed during microstructural characterization, with a grain size of ~300 nm. This study investigated structural development during progressive deformation, and the samples were evaluated from the viewpoint of grain size and grain boundaries. The process significantly increased the microhardness of the copper–graphene composite. The tensile strength reached ~500 MPa at room temperature. The interpenetrating structural feature of graphene promoted interfacial shear stress to a high level, whereas plastic deformation increased the dislocation density and grain boundaries, thus resulting in significantly enhanced load transfer strengthening and crack-bridging toughness simultaneously.

Introducing magnetic properties to aerogels not only opens new application areas but also enhances their performance in various applications. Herein, we report a novel 3D magnetic agar nanocomposite aerogel (3D-MANCA) with outstanding characteristics such as high porosity, magnetic property, rapid swelling behavior, and a unique stimuli-driven electrical conductivity. Agar and nanocellulose mixture were selected as the matrix material, while magnetic Fe ₃ O ₄ nanoparticles, CuO nanoparticles, and graphene nanopowder were incorporated as functional additives. 3D-MANCA obtained after a uni-directional freeze casting process exhibited a highly-ordered microporosity. It showed excellent magnetic properties and methylene-blue adsorption capability and a great performance as humidity sensor.

Developing advanced nuclear fuel technologies is critical for high-performance applications such as nuclear thermal propulsion (NTP). This study explores the feasibility of direct ink writing (DIW) for fabricating ceramic pellets for potential nuclear applications. Zirconium carbide (ZrC) is used as a matrix material and vanadium carbide (VC) is used as a surrogate for uranium carbide (UC) in this study. A series of ink formulations were developed with varying concentrations of VC and nanocrystalline cellulose (NCC) to optimize the rheological properties for DIW processing. Post-sintering analysis revealed that conventionally sintered samples at 1750 °C exhibited high porosity (>60%), significantly reducing the compressive strength compared to dense ZrC ceramics. However, increasing VC content improved densification and mechanical properties, albeit at the cost of increased shrinkage and ink flow challenges. Spark plasma sintering (SPS) achieved near-theoretical density (~97%) but introduced geometric distortions and microcracking. Despite these challenges, this study demonstrates that DIW offers a viable route for fabricating ZrC-based ceramic structures, provided that sintering strategies and ink rheology are further optimized. These findings establish a baseline for DIW of ZrC-based materials and offer valuable insights into the porosity control, mechanical stability, and processing limitations of DIW for future nuclear fuel applications.

This research advances the field of additive manufacturing (AM) of silicon carbide (SiC) ceramics by integrating spark plasma sintering (SPS) to enhance material density, mechanical strength, and thermal properties. Traditional AM techniques struggle to achieve the high‐density SiC required for demanding applications, such as aerospace engineering, where high thermal conductivity and mechanical strength are paramount. Our study addresses these challenges by incorporating SPS as a post‐processing step, achieving near‐theoretical maximum densities and significantly reducing porosity, thereby resulting in outstanding thermal conductivity in SiC ceramics. We developed a specialized SiC ink optimized for 3D printing, ensuring structural integrity after deposition through tailored rheological properties. The application of SPS facilitates rapid, uniform sintering, essential for attaining superior density, mechanical properties, and thermal performance. Our experimental results, confirmed through scanning electron microscopy analysis, demonstrate significant microstructural properties, mechanical strength, and thermal conductivity, showcasing the effectiveness of integrating SPS in AM processes. This innovative approach not only expands the capabilities of AM in producing complex, high‐density ceramic structures but also broadens the potential applications of SiC in demanding environments.

The 3D freeze printing (3DFP) of nanocellulose aerogels are demonstrated with large‐scale aligned pore orientations as a sustainable alternative to current acoustical materials. In contrast with the unidirectional pore network orientations obtained from current 3DFP techniques, a bidirectional orientation is achieved by using an inhomogeneous printing substrate to alter the thermal gradient within the print volume. The microstructural morphology shows that bidirectional printing results in a 2D pore orientation, with comparatively thinner pore walls and larger pore widths. Acoustic measurements reveal that altering the pore network characteristics significantly affects the acoustical behavior of the printed CNC aerogels; the wider pores allow the bidirectional CNC aerogels to provide higher sound absorption performance at lower frequencies than the unidirectional samples. Notably, both 3D Freeze printed CNC aerogels provide substantially higher sound transmission loss performance as compared to current acoustical materials. The unidirectional pore structure results in CNC aerogels with higher stiffness and improved energy absorption performance, with both 3D freeze printed CNC aerogels outperforming other CNC aerogel materials in their stiffness‐to‐density ratios. The ability to simultaneously control their pore orientation and macrostructural geometry paves the way for printing complex shaped CNC aerogel structures for multifunctional noise control applications.

The comprehensive properties of high-entropy alloys (HEAs) are highly-dependent on their phases. Although a large number of machine learning (ML) algorithms has been successfully applied to the phase prediction of HEAs, the accuracies among different ML algorithms based on the same dataset vary significantly. Therefore, selection of an efficient ML algorithm would significantly reduce the number and cost of the experiments. In this work, phase prediction of HEAs (PPH) is proposed by integrating criterion and machine learning recommendation method (MLRM). First, a meta-knowledge table based on characteristics of HEAs and performance of candidate algorithms is established, and meta-learning based on the meta-knowledge table is adopted to recommend an algorithm with desirable accuracy. Secondly, an MLRM based on improved meta-learning is engineered to recommend a more desirable algorithm for phase prediction. Finally, considering poor interpretability and generalization of single ML algorithms, a PPH combining the advantages of MLRM and criterion is proposed to improve the accuracy of phase prediction. The PPH is validated by 902 samples from 12 datasets, including 405 quinary HEAs, 359 senary HEAs, and 138 septenary HEAs. The experimental results shows that the PPH achieves performance than the traditional meta-learning method. The average prediction accuracy of PPH in all, quinary, senary, and septenary HEAs is 91.6%, 94.3%, 93.1%, and 95.8%, respectively.

Three dimensional freeze printing (3DFP) combines the advantages of freeze casting and additive manufacturing to fabricate multifunctional aerogels. Freeze casting is a cost-effective, efficient, and versatile method capable of fabricating micro-scale porous structures inside the aerogels for many different applications. The 3DFP provided the capability of fabricating highly customized geometries with controlled microporous structures as well. However, there are still many unexplained phenomena and features because of the complexity of post-processes and indirect observation methods. This study demonstrates the design and construction of the in situ imaging systems, which use the x-ray synchrotron radiography to observe freeze casting and 3DFP processes. With the advantages provided by the in situ x-ray imaging techniques, the ice crystal growth with its unique lamellar structures can be observed during the freeze casting process. The movement of freeze front, material deposition, and growth of ice crystals can also be visualized during the inkjet-based 3DFP process.