Synthesis and characterization of copper foams through a powder metallurgy route using a compressible and lubricant space-holder material

In the present work,a compressible and lubricating space-holder material commonly known as "acrawax" was used to process Cu foams with various pore sizes and various porosities.The foams were processed without using binders to avoid contamination of their metal matrices.The lubricant space-holder material was found to facilitate more uniform flow and distribution of metal powder around the surface of the space holder.In addition,the use of acrawax as a space-holder material yielded considerably dense cell walls,which are an essential prerequisite for better material properties.The foams processed with a smaller-sized space holder were found to exhibit better electrical and mechanical properties than those processed with a coarser-sized space holder.The isotropic pore shape,uniform pore distribution throughout the metal matrix,and uniform cell wall thickness were found to enhance the properties pertaining to fine-pore foam samples.The processed foams exhibit properties similar to those of the foams processed through the lost-carbonate sintering process.

Active Learning Query Strategies for Classification,Regression,and Clustering:A Survey

Generally,data is available abundantly in unlabeled form,and its annotation requires some cost.The labeling,as well as learning cost,can be minimized by learning with the minimum labeled data instances.Active learning(AL),learns from a few labeled data instances with the additional facility of querying the labels of instances from an expert annotator or oracle.The active learner uses an instance selection strategy for selecting those critical query instances,which reduce the generalization error as fast as possible.This process results in a refined training dataset,which helps in minimizing the overall cost.The key to the success of AL is query strategies that select the candidate query instances and help the learner in learning a valid hypothesis.This survey reviews AL query strategies for classification,regression,and clustering under the pool-based AL scenario.The query strategies under classification are further divided into:informative-based,representative-based,informative-and representative-based,and others.Also,more advanced query strategies based on reinforcement learning and deep learning,along with query strategies under the realistic environment setting,are presented.After a rigorous mathematical analysis of AL strategies,this work presents a comparative analysis of these strategies.Finally,implementation guide,applications,and challenges of AL are discussed.

Fracture toughness of a rejuvenated β-Ti reinforced bulk metallic glass matrix composite

A β-Ti dendrite reinforced Zr-based bulk metallic glass composite(BMGC) was found to be brittle when cast in a large size. The reasons for the embrittlement and the effectiveness of the cryothermal cycling(CTC) treatment in restoring the mode I fracture toughness are examined. Plasticity in all the CTC treated BMGC is estimated from the distribution and occurrence of pop-ins in nanoindentation tests and by measuring the magnitude of enthalpy of relaxation(△H_(rel)) via differential scanning calorimetry(DSC). This is further validated by examining the strain-to-failure(ε_(f)) in compression tests. Mode I fracture behaviour of the as-cast embrittled BMGC and the CTC treated BMGC, which exhibits maximum plasticity, is examined. Results show that both BMGCs are equally brittle and exhibit 5 times lower notch toughness(K_(QJ))than their tougher counterpart. Post-facto imaging of the side surfaces reveals the absence of notch-tip plasticity in both BMGCs. The lack of notch tip plasticity of CTC treated BMGC, despite exhibiting signatures of plasticity in nanoindentation and higher △Hrelis rationalized by reassessing the origin of pop-ins in nanoindentation tests and describing the variations in chemical and topological short range ordering during CTC, respectively. Implications of these results in terms of improving the fracture toughness of structurally relaxed BMGCs via CTC are discussed.