Densification mechanism and microstructure characteristics of nano- and micro- crystalline alumina by high-pressure and low temperature sintering

Fully dense ceramics with retarded grain growth can be attained effectively at relatively low temperatures using a high-pressure sintering method. However, there is a paucity of in-depth research on the densification mechanism, grain growth process, grain boundary characterization, and residual stress. Using a strong, reliable die made from a carbon-fiber-reinforced carbon (C_f/C) composite for spark plasma sintering, two kinds of commercially pure α-Al₂O₃ powders, with average particle sizes of 220 nm and 3 μm, were sintered at relatively low temperatures and under high pressures of up to 200 MPa. The sintering densification temperature and the starting threshold temperature of grain growth (T_sg) were determined by the applied pressure and the surface energy relative to grain size, as they were both observed to increase with grain size and to decrease with applied pressure. Densification with limited grain coarsening occurred under an applied pressure of 200 MPa at 1050 °C for the 220 nm Al₂O₃ powder and 1400 °C for the 3 μm Al₂O₃ powder. The grain boundary energy, residual stress, and dislocation density of the ceramics sintered under high pressure and low temperature were higher than those of the samples sintered without additional pressure. Plastic deformation occurring at the contact area of the adjacent particles was proved to be the dominant mechanism for sintering under high pressure, and a mathematical model based on the plasticity mechanics and close packing of equal spheres was established. Based on the mathematical model, the predicted relative density of an Al₂O₃ compact can reach ～80 % via the plastic deformation mechanism, which fits well with experimental observations. The densification kinetics were investigated from the sintering parameters, i.e., the holding temperature, dwell time, and applied pressure. Diffusion, grain boundary sliding, and dislocation motion were assistant mechanisms in the final stage of sintering, as indicated by the stress exponent and the microstructural evolution. During the sintering of the 220 nm alumina at 1125 °C and 100 MPa, the deformation tends to increase defects and vacancies generation, both of which accelerate lattice diffusion and thus enhance grain growth.     

Structural Aspects and Prediction of Calmodulin-Binding Proteins

Calmodulin (CaM) is an important intracellular protein that binds Ca²⁺ and functions as a critical second messenger involved in numerous biological activities through extensive interactions with proteins and peptides. CaM’s ability to adapt to binding targets with different structures is related to the flexible central helix separating the N- and C-terminal lobes, which allows for conformational changes between extended and collapsed forms of the protein. CaM-binding targets are most often identified using prediction algorithms that utilize sequence and structural data to predict regions of peptides and proteins that can interact with CaM. In this review, we provide an overview of different CaM-binding proteins, the motifs through which they interact with CaM, and shared properties that make them good binding partners for CaM. Additionally, we discuss the historical and current methods for predicting CaM binding, and the similarities and differences between these methods and their relative success at prediction. As new CaM-binding proteins are identified and classified, we will gain a broader understanding of the biological processes regulated through changes in Ca²⁺ concentration through interactions with CaM.     

An ultrasonic study on ternary xPbO–(45-x)CuO–55B2O3 glasses

A series of xPbO–(45-x)CuO–55B₂O₃ glasses (5 ≤ x ≥ 40 mol %) were prepared by the melt-quenching technique. The X-ray diffraction (XRD) patterns of the prepared glasses are found to have amorphous structure. An extensive ultrasonic study has been made to explore the structural role of PbO and CuO in the borate network. Various elastic properties were calculated from the measured data of density and ultrasonic velocity. Ultrasonic velocity and elastic moduli revealed broad humps at about 20 mol % PbO, which are attributed to the borate anomaly. Below 20 mol % PbO, all Pb²⁺ ions are considered to be entering the borate network as a glass modifier. This results in the transforms the borate network from an open structure to a denser three-dimensional structure due to BO₃ → BO₄ conversion. Beyond 20 mol, addition of PbO results in the formation of metaborate, pyroborate, and orthoborate units with NBOs. This weakness the glass structure and decrease both ultrasonic velocity and elastic moduli. The elastic properties were predicted and quantitatively analyzed by taking into account the effect of boron coordination number on the compositional and structural parameters involved in Makishima–Mackenzie's theory, ring deformation model and bond compression model. An excellent agreement between the computed theoretical and experimental elastic moduli, micro-harness and Poisson's ratio was achieved for majority of samples.     

In Silico Analysis of the Molecular-Level Impact of SMPD1 Variants on Niemann-Pick Disease Severity

Sphingomyelin phosphodiesterase (SMPD1) is a key enzyme in the sphingolipid metabolism. Genetic SMPD1 variants have been related to the Niemann-Pick lysosomal storage disorder, which has different degrees of phenotypic severity ranging from severe symptomatology involving the central nervous system (type A) to milder ones (type B). They have also been linked to neurodegenerative disorders such as Parkinson and Alzheimer. In this paper, we leveraged structural, evolutionary and stability information on SMPD1 to predict and analyze the impact of variants at the molecular level. We developed the SMPD1-ZooM algorithm, which is able to predict with good accuracy whether variants cause Niemann-Pick disease and its phenotypic severity; the predictor is freely available for download. We performed a large-scale analysis of all possible SMPD1 variants, which led us to identify protein regions that are either robust or fragile with respect to amino acid variations, and show the importance of aromatic-involving interactions in SMPD1 function and stability. Our study also revealed a good correlation between SMPD1-ZooM scores and in vitro loss of SMPD1 activity. The understanding of the molecular effects of SMPD1 variants is of crucial importance to improve genetic screening of SMPD1-related disorders and to develop personalized treatments that restore SMPD1 functionality.     

川中地区侏罗系沙溪庙组致密气处理和解释关键技术与应用

四川盆地蕴含丰富的致密砂岩气资源，近期利用高精度三维资料开展侏罗系沙溪庙组河道砂体勘探取得突出成效。沙溪庙组河道砂体具有横向变化快、储层非均质性强的特点，因此提高河道砂体的边界识别及其含气性预测精度是致密气地震勘探的关键。通过开展AVO特征低频保护的“六分法”（分类、分频、分时、分域、分步和分区）高保真叠前去噪、近地表Q补偿和OVT域叠前时间偏移等技术攻关，形成了一套针对川中地区侏罗系沙溪庙组致密气藏的“双高”（高保真、高分辨率）地震处理技术，并创新应用“双亮点”属性及多波、多分量砂体含气性地震预测等解释技术，提高了含气砂体预测精度。该技术系列在川中沙溪庙组致密气预测应用成果显著，地震数据频带得到了拓宽，低频信息更加丰富，资料信噪比明显提升，河道边界及其含气性预测的精度大幅提高，钻井成功率超过83%，应用成果有力地支撑了该地区沙溪庙组致密气的增储上产。     

FE-SEA方法在平台支持船噪声预报中的应用

平台支持船由于作业需要通常配备有动力定位系统,其在侧推工况下舱室噪声超标较为严重。针对这个问题采用计算流体力学(CFD)方法,得到侧推螺旋桨作用在导管上的脉动压力,并将时域计算结果转换成噪声计算的激励条件。采用有限元(FE)与统计能量分析(SEA)混合方法建立船体中频段FE-SEA耦合模型并建立船体高频段SEA模型,对某65 m AHTS船侧推工况下全频段(63 Hz~8000 Hz)舱室噪声进行预报,分析该船噪声分布规律及主要影响因素。并建立起全船的SEA模型,在中频段对比SEA与FE-SEA两种方法得到的舱室声压级频谱曲线,验证了使用混合模型的必要性。     

Learning shape and texture progression for young child face aging

Face aging (FA) for young faces refers to rendering the aging faces at target age for an individual, generally under 20s, which is an important topic of facial age analysis. Unlike traditional FA for adults, it is challenging to age children with one deep learning-based FA network, since there are deformations of facial shapes and variations of textural details. To alleviate the deficiency, a unified FA framework for young faces is proposed, which consists of two decoupled networks to apply aging image translation. It explicitly models transformations of geometry and appearance using two components: GD-GAN, which simulates the Geometric Deformation using Generative Adversarial Network; TV-GAN, which simulates the Textural Variations guided by the age-related saliency map. Extensive experiments demonstrate that our method has advantages over the state-of-the-art methods in terms of synthesizing visually plausible images for young faces, as well as preserving the personalized features.     

Effect of Bimodal Grain Size Distribution on the Strain Hardening Behavior of a Medium-Entropy Alloy

The evolution of strain hardening behavior of the Fe_(50)(CoCrMnNi)_(50) medium-entropy alloy as a function of the fraction of recrystallized microstructure and the grain size was studied using the Hollomon and Ludwigson equations.The specimens under study were partially recrystallized,fully recrystallized with ultrafine-grained microstructure,and fully recrystallized with coarse grains.The yield strength decreases steadily as the fraction of recry stallized micro structure and grain size increases due to the recovery process and the Hall-Petch effect.Interestingly,the bimodal grain distribution was found to have a significant impact on strain hardening during plastic deformation.For instance,the highest ultimate tensile strength was exhibited by a 0.97 μm specimen,which was observed to contain a bimodal grain distribution.Furthermore,using the Ludwigson equation,the effect of the bimodal grain distribution was established from the behavior of K_2 and n1 curves.These curves tend to show very high values in the specimens with a bimodal grain distribution compared to those that show a homogenous grain distribution.Additionally,the bimodal grain distribution contributes to the extensive L(u|")ders strain observed in the 0.97 μm specimen,which induces a significant deviation of the Hollomon equation at lower strains.     

防气窜固井技术研究

从气窜机理、气窜预测方法、提高水泥浆防气窜性能、防气窜固井工艺技术四个方面进行研究,为固井防气窜提供理论依据,进而提升防气窜固井技术。     

InSAR技术在矿区地表变形监测中的应用

以禹州市梁北矿为研究区，利用2018年11月—2020年6月间35景5 m×20 m分辨率Sentinel-1A数据，采用InSAR技术，利用SBAS（短基线集InSAR）雷达干涉测量方法对梁北矿进行地面沉降信息提取解译，并通过实地调查成果认为，采用InSAR技术适合在矿区开展地表变形监测。