Phase constitution,microstructure and mechanical properties of a Ni-based superalloy specially designed for additive manufacturing

In this study, a kind of Ni-based superalloy specially designed for additive manufacturing (AM) was investigated. Thermo-Calc simulation and differential scanning calorimetry (DSC) analysis were used to determine phases and their transformation temperature. Experimental specimens were prepared by laser metal deposition (LMD) and traditional casting method. Microstructure, phase constitution and mechanical properties of the alloy were characterized by scanning electron microscopy (SEM), transmission scanning electron microscopy (TEM), X-ray diffraction (XRD) and tensile tests. The results show that this alloy contains two basic phases, γ/γ', in addition to these phases, at least two secondary phases may be present, such as MC carbides and Laves phases. Furthermore, the as-deposited alloy has finer dendrite, its mean primary dendrite arm space (PDAS) is about 30-45 μm, and the average size of γ' particles is 100-150 nm. However, the dendrite size of the as-cast alloy is much larger and its PDAS is 300-500 μm with secondary and even third dendrite arms. Correspondingly, the alloy displays different tensile behavior with different processing methods, and the as-deposited specimen shows better ultimate tensile stress (1,085.7±51.7 MPa), yield stress (697±19.5 MPa) and elongation (25.8%±2.2%) than that of the as-cast specimen. The differences in mechanical properties of the alloy are due to the different morphology and size of dendrites, γ', and Laves phase, and the segregation of elements, etc. Such important information would be helpful for alloy application as well as new alloy development.     

Designing Semipermeable Hydrogel Shells with Controlled Thickness through Internal Osmosis in Triple-Emulsion Droplets

Hydrogel shells that compartmentalize the water core from the aqueous surrounding provide molecular selectivity on size and charge in transmembrane transport. It is highly demanding to produce thin hydrogel shells to minimize diffusion length and maximize core volume. Here, internal osmosis in water-in-oil-in-water-in-oil (W/O/W/O) triple-emulsion droplets is used to produce thin hydrogel shells enclosing a large water core. The triple-emulsion droplets are prepared to have an ultrathin middle oil layer using a capillary microfluidic device. The innermost water droplet has a higher osmolarity than the outer water layer containing photopolymerizable hydrogel precursors, which pumps water from the outer layer to the core through the ultrathin oil layer by the osmosis. Therefore, the outer layer gets thinner and hydrogel precursors are enriched while the size of the triple-emulsion droplets remains unchanged. Through photopolymerization of precursors and phase transfer from oil to water, hydrogel shells enclosing water core are produced in the water environment; the oil layer is ruptured for molecular exchange through the shells. The thickness and composition of the hydrogel shells are precisely controllable by the osmotic conditions. The shells show a high permeation rate due to the thinness as well as controlled cut-off threshold of permeation for neutral and charged molecules.     

Nanovaccine-Mediated Cell Selective Delivery of Neoantigens Potentiating Adoptive Dendritic Cell Transfer for Personalized Immunization

Neoantigen vaccines and adoptive dendritic cell (DC) transfer are major clinical approaches to initiate personalized immunity in cancer patients. However, the immunization efficacy is largely limited by the in vivo trajectory including neoantigens’ access to resident DCs and DCs’ access to lymph nodes (LNs). Herein, an innovative strategy is proposed to improve personalized immunization through neoantigen-loaded nanovaccines synergized with adoptive DC transfer. It is found that it enables selective delivery of neoantigens to resident DCs and macrophages by coating cancer cell membranes onto neoantigen-loaded nanoparticles. In addition, the nanovaccines promote the secretion of chemokine C-C motif ligand 2 (CCL2), CCL3, and C-X-C motif ligand 10 from macrophages, thus potentiating the access of transferred DCs to LNs. This immunization strategy enables coordinated delivery of identified neoantigens and autologous tumor lysate-derived undefined antigens, leading to initiation of antitumor T cell immunity in a personalized manner. It significantly inhibits tumor growth in prophylactic and established mouse tumor models. The findings provide a new vision for potentiating adoptive cell transfer by nanovaccines, which may open the door to a transformative possibility for improving personalized immunization.     

Enhanced thermal shrinkage behavior of phenolic-derived carbon aerogel-reinforced by HNTs with superior compressive strength performance

A novel carbon/m-HNTs composite aerogel was synthesized by introducing the modified halloysite nanotubes (m-HNTs) into phenolic (PR) aerogels through chemical grafting, followed with carbonization treatment. In order to explore the best proportion of HNTs to phenolic, the micromorphology of PR/m-HNTs were investigated by SEM before carbonization, confirming 10 wt% of m-HNTs is most beneficial to the porous network of aerogels. The interaction between PR and HNTs was studied by FTIR spectra, and microstructure evolution of the target product-carbon/m-HNTs composite aerogel were illustrated by SEM and TEM techniques. SEM patterns indicated that the carbon/m-HNTs aerogels maintain a stable porous structure at 1000 °C (carbonization temperature), while a ~20 nm carbon layer was formed around m-HNTs generating an integral unit through TEM analysis. Specific surface area and pore size distribution of composite aerogels were analyzed based on mercury intrusion porosimetry and N₂ adsorption–desorption method, the obtained results stayed around 500 m²g^?1 and 1.00 cm³g^?1 (pore volume) without significant discrepancy, compared with pure aerogel, showing the uniformity of pore size. The weight loss rate (26.76%) decreased greatly compared with pure aerogel, at the same time, the best volumetric shrinkage rate was only 30.83%, contributed by the existence of HNTs supporting the neighbor structure to avoid over-shrinking. The highest compressive strength reached to 4.43 MPa, while the data of pure aerogel was only 1.52 MPa, demonstrating the excellent mechanical property of carbon/m-HNTs aerogels.     

Research on Crop Irrigation Schedules Under Deficit Irrigation—A Meta-analysis

Water Resources Management - Increasing water consumption in agriculture due to global climate change has posed considerable challenges to food security, thus improving the efficiency of water...     

An Enhanced Beetle Antennae Search Algorithm Based Comprehensive Water Quality Index for Urban River Water Quality Assessment

Water Resources Management - Urban river not only has the important function in urban hydrological environment, but also is an area for entertainment. Water quality assessment is the core technique...     

A Novel LRRK2 Variant p.G2294R in the WD40 Domain Identified in Familial Parkinson’s Disease Affects LRRK2 Protein Levels

Leucine-rich repeat kinase 2 (LRRK2) is a major causative gene of late-onset familial Parkinson’s disease (PD). The suppression of kinase activity is believed to confer neuroprotection, as most pathogenic variants of LRRK2 associated with PD exhibit increased kinase activity. We herein report a novel LRRK2 variant—p.G2294R—located in the WD40 domain, detected through targeted gene-panel screening in a patient with familial PD. The proband showed late-onset Parkinsonism with dysautonomia and a good response to levodopa, without cognitive decline or psychosis. Cultured cell experiments revealed that p.G2294R is highly destabilized at the protein level. The LRRK2 p.G2294R protein expression was upregulated in the patient’s peripheral blood lymphocytes. However, macrophages differentiated from the same peripheral blood showed decreased LRRK2 protein levels. Moreover, our experiment indicated reduced phagocytic activity in the pathogenic yeasts and α-synuclein fibrils. This PD case presents an example wherein the decrease in LRRK2 activity did not act in a neuroprotective manner. Further investigations are needed in order to elucidate the relationship between LRRK2 expression in the central nervous system and the pathogenesis caused by altered LRRK2 activity.     

基于大数据深度学习的输电塔结构抗风易损性评估

为了有效预测输电网系统在强风作用下的响应，并开展高效精准的性能评估，文章提出了基于深度学习模型的风致易损性评估框架。以某具备健康监测系统的输电塔结构为例，首先对监测数据进行清洗和重构，通过大数据深度学习建立荷载输入和响应输出的等效映射模型，然后通过数值模拟生成灾害强度均匀的风场数据并由深度学习模型预测输电塔关键杆件响应，计算不同性能水准的易损性曲线。研究结果表明，经训练的深度学习模型可以涵盖实际工程中存在的各类不确定性因素，有效映射复杂风环境下输电塔结构的动力响应。提出的框架方法可以避免单纯通过数值模型制备大量动态响应数据，更高效地进行输电网系统风致易损性评估。     

基于有限元的区域分解方法在永磁聚焦系统仿真中的应用

随着计算机技术以及并行求解技术的发展,区域分解方法越来越多地应用于计算电磁学的各个领域.针对微波管中的永磁聚焦系统仿真,该文提出一种基于有限元的非重叠区域分解方法,其引入一种新型传输条件,并采用内罚的方式推导出有限元弱形式.该区域分解法的最大优势是不需要引入多余的未知量,并且最终集成的有限元矩阵满足对称正定性,适合采用预处理共轭梯度法进行矩阵方程的求解.该文仿真了多个微波管永磁聚焦系统,并与商业软件Maxwell进行了详细的对比,结果表明所提出的区域分解方法和Maxwell精度相当,却拥有着更加优越的计算性能.