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Damping alloys can dissipate vibration energy into thermal energy through defective motion with high mechanical properties and functional characteristics， which have a great significance in the development and research of aerospace and military fields. There are differences in microstucture between different alloy systems. The types of defects that play a dominant role in damping are different， and the properties of structureal defect （type， density， and movability） are the key factors affecting the damping performance of alloys. The types and characteristics of damping source for different damping alloys systems were summarized from the perspective of defects （plane defects， line defects， and point defects）. The relationship between damping capacity， mechanical properties， and functional properties （corrosion resistance， casting performance， etc.） was reviewed， the development status of various damping alloys was summarized， and then the development laws and differences of damping alloys were concluded. Finally， the research direction of damping alloys is prospected. The single type of damping source will seriously limit the improvement of the material damping capacity. While the design concepts of composite materials and high-entropy alloys allow for the coexistence of multiple damping sources， which produces the coupling effect of multiple damping mechanisms that can realize the two-dimensional expansion of damping capacity， and improve mechanical properties and functionalities. The design concepts will play a significant guide to enhance comprehensive performance of damping alloys.

The composition of high-damage-tolerance dual-phase TC21 (Ti-6Al-2Zr-2Sn-2Mo-2Nb-1.5Cr) were analyzed on the basis of the dual-cluster formula of Ti-6Al-4V, consisting of 13 α-Ti and 4 β-Ti unit. Its β-Ti unit is reduced from 5 to 4 compared with Ti-6Al-4V, while adding more β-stabilizing elements to enhance the strength and plasticity. Subsequently, the atoms of each β-stabilizing element within the β-Ti cluster formula of TC21 were proportioned equally to increase the mixing entropy, and more Zr content was increased to substantially enhance the β-phase stability, giving the cluster formula as α-{[Al-Ti12](AlTi2)}13+β-{[(Al-(Ti12Zr2)]Sn0.75Mo0.75Nb0.75Cr0.75}4(atom fraction), named as TC21Z2, with the corresponding mass fraction of Ti-5.9Al-5.4Zr-2.6Sn-2.1Mo-2.0Nb-1.1Cr. The samples were prepared by using vacuum copper mold pouring process and the as-cast microstructure and tensile mechanical properties of the alloy were studied.Results show that the as-cast microstructure of TC21Z2 is composed of α+α' martensite+ a small amount of β phases, and its ultimate tensile strength, yield strength and elongation are 1289, 1181 MPa and 1.4%, respectively. Its strength and plasticity are better than those of the TC21 at the same state.

As a new material system, the high entropy ceramics have become a hot research topic in the field of materials because of their unique and adjustable properties benefited by the huge component space, unique microstructure and large configuration entropy. The research of the high entropy ceramics is still in the initial stage at present, especially for the accurate composition design theory, preparation of high purity and high conversion powder, new sintering process and other aspects, which need to be further explored. Therefore, the five high entropy effects, new design theory, powder preparation methods, new sintering methods, comprehensive properties and practical applications of high entropy compounds ceramics were sorted and summarized, the composition design of high entropy ceramics (HEC) by the cluster-plus-glue-atom model (CPGA) was analyzed, and the relationship between the components, microstructure, and performance of HEC was explored deeply. The key development direction of future HEC will still be basic theoretical design, especially for the composition and structure of non oxide HEC. At the same time, the breakthroughs in interdisciplinary fields was sought, such as using artificial intelligence machine learning and 3D printing for sample preparation. Finally, the practical applications in structures, thermal barrier and corrosion resistant coatings, machinery, engineering optics, and magnetism were searched, and the strengthening and failure mechanisms were explored and analyzed in-depth under the investigated working environment.

Abstract Background Hematoma expansion is an independent predictor of patient outcome and mortality. The early diagnosis of hematoma expansion is crucial for selecting clinical treatment options. This study aims to explore the value of a deep learning algorithm for the prediction of hematoma expansion from non-contrast computed tomography (NCCT) scan through external validation. Methods 102 NCCT images of hypertensive intracerebral hemorrhage (HICH) patients diagnosed in our hospital were retrospectively reviewed. The initial computed tomography (CT) scan images were evaluated by a commercial Artificial Intelligence (AI) software using deep learning algorithm and radiologists respectively to predict hematoma expansion and the corresponding sensitivity, specificity and accuracy of the two groups were calculated and compared. Comparisons were also conducted among gold standard hematoma expansion diagnosis time, AI software diagnosis time and doctors’ reading time. Results Among 102 HICH patients, the sensitivity, specificity, and accuracy of hematoma expansion prediction in the AI group were higher than those in the doctor group(80.0% vs 66.7%, 73.6% vs 58.3%, 75.5% vs 60.8%), with statistically significant difference (p