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The element diffusion behavior, the interfacial evolution and mechanical properties of the joining of gallium arsenide (GaAs) with Sn3.5Ag4Ti(Ce,Ga) alloy filler at 250 °C in air were investigated. The interfacial microstructure, elemental diffusion and absorption, interface reaction and evolution were analyzed in detail. Titanium (Ti) and gallium (Ga) element were found to obviously take part in the active bonding between GaAs substrate and Sn3.5Ag4Ti(Ce,Ga) alloy filler. According to the transmission electron microscopy analysis, the titanium elements were observed to successively segregate at the interface, while some of the element Ga included in GaAs to dissolve into the molten alloy. In addition, there is a resultant formed discontiniously along the interface which was identified as Ga4Ti5, but no arsenic compounds were observed. The joining mechanisms related to the adsorption and reaction were discussed based on the thermodynamics theories, the molecular dynamic (MD) model and the reaction product controlled (RPC) model. The analysis results show that the RPC model was a special form of MD model, both the chemical reaction and the adsorption of active elements may control the reactive wetting of Sn3.5Ag4Ti(Ce,Ga) filler alloy on GaAs substrate together. In order to better understand the interfacial evolution of bonding, a simple interfacial evolution model between GaAs substrate and Sn3.5Ag4Ti(Ce, Ga) active solder was established. Finally, the effect of holding time on shear strength was investigated and the maximum shear strength of 23.32 MPa was obtained when soldered at 250 °C for 1 h. The interface separation could be caused by the mixed fracture mechanism.

Little is known about the transcriptomic plasticity and adaptive mechanisms of circulating tumor cells (CTCs) during hematogeneous dissemination. Here we interrogate the transcriptome of 113 single CTCs from 4 different vascular sites, including hepatic vein (HV), peripheral artery (PA), peripheral vein (PV) and portal vein (PoV) using single-cell full-length RNA sequencing in hepatocellular carcinoma (HCC) patients. We reveal that the transcriptional dynamics of CTCs were associated with stress response, cell cycle and immune-evasion signaling during hematogeneous transportation. Besides, we identify chemokine CCL5 as an important mediator for CTC immune evasion. Mechanistically, overexpression of CCL5 in CTCs is transcriptionally regulated by p38-MAX signaling, which recruites regulatory T cells (Tregs) to facilitate immune escape and metastatic seeding of CTCs. Collectively, our results reveal a previously unappreciated spatial heterogeneity and an immune-escape mechanism of CTC, which may aid in designing new anti-metastasis therapeutic strategies in HCC., Circulating tumour cells can be useful for monitoring disease progression but how they survive in the circulatory system is unclear. Here, the authors use single-cell sequencing of circulating tumour cells from multiple vascular sites in liver cancer patients and identify genes that may help the cells survive.

Cancer-associated fibroblasts (CAFs) play a role in response to cancer treatment and patient prognosis. CAFs show phenotypic and functional heterogeneity and differ widely in tumors of different tissue origin. Here, we use single-cell RNA sequencing of bladder cancer (BC) patient samples and report a CAF subpopulation characterized by overexpression of the urea transporter SLC14A1. This population is induced by interferon signaling and confers stemness to BC cells via the WNT5A paracrine pathway. Activation of cGAS-STING signaling in tumor cells drives interferon production, thereby revealing a link between cGAS-STING signaling and SLC14A1

Summary Pathological examination is the gold standard for cancer diagnosis, and breast tumor cells are often found in clusters. We report a case study on one triple-negative breast cancer (TNBC) patient, analyzing tumor development, metastasis, and prognosis with simultaneous DNA and RNA sequencing of pathologist-defined cell clusters from multiregional frozen sections. The cell clusters are isolated by laser capture microdissection (LCM) from primary tumor tissue, lymphatic vessels, and axillary lymph nodes. Data are reported for a total of 97 cell clusters. A combination of tumor cell-cluster clonality and phylogeny reveals 3 evolutionarily distinct pathways for this patient, each associated with a unique mRNA signature, and each correlated with disparate survival outcomes. Hub gene analysis indicates that extensive downregulation of ribosomal protein mRNA is a potential marker of poor prognosis in breast cancer., Graphical abstract, Highlights Pathologically diverse cell clusters share genomic and transcriptomic profiles Transcriptome-defined clones are more complex than genome-defined clones Three distinct pathways were inferred, each with disparate survival outcomes Lower expression of ribosomal proteins may be an indicator of poor prognosis, Zhu et al. reveal the complexity of tumor development, metastasis, and prognosis by simultaneous DNA and RNA sequencing of pathologist-defined cell clusters, excised through laser capture microdissection from multiregional frozen sections of a triple-negative breast cancer patient.

In this article, the shear properties of Sn–0.3Ag–0.7Cu-xCeO2 composite solder alloys were investigated at strain rates of 10−3s−1, 10−2s−1, and 10−1s−1 under three different temperatures of 25 °C, 75 °C, and 125 °C. Scanning electron microscope equipped with Energy-dispersive X-ray spectroscopy was used to observe the microstructural evolution and the fracture surface of the composite solder alloys. The results show that appropriate addition of CeO2 nanoparticles can improve the shear stress of the composite solder alloys. However, the excessive addition of CeO2 nanoparticles could degrade the mechanical properties. With an increase in strain rate or a decrease in test temperature, the shear stress of all solder alloys shows an increasing trend. A modified constitutive model was used to describe the effect of strain rate and temperature on shear stress. The optimum addition concentration of CeO2 nanoparticles in Sn–0.3Ag–0.7Cu-xCeO2 solder alloys is about 0.5 wt%, which possesses the highest shear stress.

Diffuse large B cell lymphoma (DLBCL) is one of the most common yet aggressive types of B cell lymphoma and remains incurable in 40% of patients. Herein, we profile the transcriptomes of 94,324 cells from 17 DLBCLs and 3 control samples using single-cell RNA sequencing. Altogether, 73 gene expression programs are identified in malignant cells, demonstrating high intra- and intertumor heterogeneity. Furthermore, 2,754 pairs of suggestive cell-cell interactions are predicted, indicating a complex and highly dynamic tumor microenvironment. Especially for B cell lymphomas, a strong costimulatory CD70-CD27 interaction is predicted between malignant and T cells. Furthermore, coinhibitory signals mediated by TIM3 or TIGIT seem to be the main driving force for T cell exhaustion. Finally, we find that chronic hepatitis B virus infection may have a significant impact on tumor cell survival and immune evasion in DLBCL. Our results provide insights into B cell lymphomagenesis and may facilitate the design of targeted immunotherapy strategies.

BackgroundColorectal cancer (CRC) is a major cancer type whose mechanism of metastasis remains elusive.MethodsIn this study, we characterised the evolutionary pattern of metastatic CRC (mCRC) by analysing bulk and single-cell exome sequencing data of primary and metastatic tumours from 7 CRC patients with liver metastases. Here, 7 CRC patients were analysed by bulk whole-exome sequencing (WES); 4 of these were also analysed using single-cell sequencing.ResultsDespite low genomic divergence between paired primary and metastatic cancers in the bulk data, single-cell WES (scWES) data revealed rare mutations and defined two separate cell populations, indicative of the diverse evolutionary trajectories between primary and metastatic tumour cells. We further identified 24 metastatic cell-specific-mutated genes and validated their functions in cell migration capacity.ConclusionsIn summary, scWES revealed rare mutations that failed to be detected by bulk WES. These rare mutations better define the distinct genomic profiles of primary and metastatic tumour cell clones.

Single cell approaches have increased our knowledge about the cell type composition of the non-human primate (NHP), but a detailed characterization of area-specific regulatory features remains outstanding. We generated single-cell chromatin accessibility (single-cell ATAC) and transcriptomic data of 358,237 cells from prefrontal cortex (PFC), primary motor cortex (M1) and primary visual cortex (V1) of adult cynomolgus monkey brain, and integrated this dataset with Stereo-seq (Spatio-Temporal Enhanced REsolution Omics-sequencing) of the corresponding cortical areas to assign topographic information to molecular states. We identified area-specific chromatin accessible sites and their targeted genes, including the cell type-specific transcriptional regulatory network associated with excitatory neurons heterogeneity. We reveal calcium ion transport and axon guidance genes related to specialized functions of PFC and M1, identified the similarities and differences between adult macaque and human oligodendrocyte trajectories, and mapped the genetic variants and gene perturbations of human diseases to NHP cortical cells. This resource establishes a transcriptomic and chromatin accessibility combinatory regulatory landscape at a single-cell and spatially resolved resolution in NHP cortex.

Resolving tumor heterogeneity is a crucial step in understanding cancer development and evolution but it is hampered by limits of all available data sources. Bulk sequencing has become the most common technology to assess the tumor heterogeneity but it has the limitation of mixing many genetically distinct cells in each sample which must then be computationally deconvolved. This genomic deconvolution generally has low resolution and high error rates in reconstructing clonal population structure. Recent technological developments in single-cell sequencing (SCS) provide the potential for providing high resolution, whole-genome reconstructions of clonal structure. However, the limitations of SCS – such as high noise, difficulty in scaling to large populations, various challenging technical artifacts, and the large data sets it produces – have so far made it impractical for applying to study cohorts of sufficient size to identify statistically robust features of tumor evolution. To address these problems, we have developed strategies to combine limited amounts of bulk and single-cell data to gain some advantages of single-cell resolution with much lower cost. We specifically focus on the problem of deconvolving copy number data from bulk samples assisted by information from small numbers of SCS sequences. We developed a mixed membership model for clonal deconvolution via Non-Negative Matrix Factorization (NMF) balancing deconvolution quality of the bulk data with similarity to single-cell samples and an associated efficient coordinate descent algorithm. We improve on that algorithm by integrating deconvolution with clonal phylogeny inference, using an integer linear programming (ILP) model to add a minimum evolution phylogenetic cost to the problem objective so as to bias deconvolution to favor inferred clones that are plausibly related to observed SCS data. We demonstrate the effectiveness of these methods on semi-simulated data of known ground truth, showing significantly enhanced deconvolution accuracy relative bulk data alone.

In the original publication of this article [1], Fig. 6 is wrong and the updated figure is shown below.

Lymphovascular invasion (LVI) is a critical step in the metastatic process but has received relatively little attention due to the technical challenges associated with their isolation. In this study, we used laser capture microdissection (LCM) to isolate 97 cancer cell clusters from pathological frozen sections within lymphatic vessels, primary tumor tissue, and axillary lymph nodes of a triple negative breast cancer (TNBC) patient. Simultaneous genome and transcriptome amplification and sequencing (G&T-seq) performed on these clusters permitted a comprehensive depiction of the genomic and transcriptional profiles of cancer cells associated with LVI. Combination phylogeny analysis pointed to three evolutionarily distinct pathways of tumor clone development and metastasis in this patient, each of which was associated with a unique mRNA signature, and correlated to disparate overall survival outcomes. Moreover, hub gene evaluation found extensive down regulation of ribosomal protein mRNA to be a potential marker of poor prognosis in breast cancer patients.

The aim of the present study was to identify the hub genes and provide insight into the tumorigenesis and development of breast cancer. To examine the hub genes in breast cancer, integrated bioinformatics analysis was performed. Gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database and the differentially expressed genes (DEGs) were identified using the ‘limma’ package in R. Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis was used to determine the functional annotations and potential pathways of the DEGs. Subsequently, a protein-protein interaction network analysis and weighted correlation network analysis (WGCNA) were conducted to identify hub genes. To confirm the reliability of the identified hub genes, RNA gene expression profiles were obtained from The Cancer Genome Atlas (TCGA)-breast cancer database, and WGCNA was used to screen for genes that were markedly correlated with breast cancer. By combining the results from the GEO and TCGA datasets, 15 hub genes were identified to be associated with breast cancer pathophysiology. Overall survival analysis was performed to examine the association between the expression of hub genes and the overall survival time of patients with breast cancer. Higher expression of all hub genes was associated with significantly shorter overall survival in patients with breast cancer compared with patients with lower levels of expression of the respective gene.

The influence of the joint size on the growth of intermetallic compound (IMC) between Sn-3.0Ag-0.5Cu-0.1TiO 2 composite solder and Cu pad during isothermal aging at temperatures of 100 °C, 120 °C, and 150 °C has been investigated in this study. Scanning electron microscopy was used to observe the microstructural evolution of the solder joints and to measure the thickness of IMC layer. Results for micro-joints show that the size of the solder joints has a significant effect on the interfacial reaction. The IMC thickness and the growth rate increase, whereas the activation energy decreases with the increase in joint size for all aging temperatures. The size effect might be due to the difference in Cu concentration near the IMC interface. Finite-element model was applied to examine the thermo-mechanical stresses at the interface of the solder joint as thermo-mechanical stress can cause the formation of crystal defects in solder matrix and interfacial IMC layer. We assume that these crystal defects serve as fast diffusion paths for atomic diffusion and affect Cu distribution.

The active bonding between Sn3.5Ag4Ti(Ce, Ga) and silicon dioxide at low temperature has been investigated. The microstructure of the bonding interface, the distribution of Ti near the interface, and the formation of the interfacial reaction products have been explored. Experiment results show that there is obvious segregation of Ti at the SiO2/solder interface, and TiSi and TiO2 phases are formed at the interface. The mechanism of active bonding between Sn3.5Ag4Ti(Ce, Ga) and silicon dioxide has been analyzed based on the active adsorption and reaction thermodynamics theories. A soldering dynamic process model is established to better understand the soldering process. Both theoretical and experimental results suggest that the chemical adsorption of Ti on the silicon dioxide interface plays an important role in the initial bonding stage. The main bonding mechanism might be the reactant formation due to the interfacial reaction between Sn3.5Ag4Ti(Ce, Ga) solder and SiO2 substrate. The shear strength of SiO2/SiO2 joints is measured to be 11.15 MPa, 14.10 MPa, 16.37 MPa, and 17.91 MPa with soldering time of 1 min, 15 min, 30 min, and 60 min, respectively, which meets the requirements of SiO2 or glass substrates bonding application.

Based on the Zufiria theoretical model, a new model regarding the asymptotic bubble velocity for the Rayleigh-Taylor (RT) instability is presented by use of the complex velocity potential proposed by Sohn. The proposed model is an extension of the ordinary Zufiria model and can deal with non-ideal fluids. With the control variable method, the effect of the viscosity and surface tension on the bubble growth rate of the RT instability is studied. The result is consistent with Cao’s result if we only consider the viscous effect and with Xia’s result if we only consider the surface tension effect. The asymptotic bubble velocity predicted by the Zufiria model is smaller than that predicted by the Layzer model, and the result from the Zufiria model is much closer to White’s experimental data.

In this study, the effect of nano-TiO 2 particles additive on the growth of interfacial Cu 6 Sn 5 and Cu 3 Sn intermetallic compound (IMC) layers between Sn 3.0Ag 0.5Cu xTiO 2 solder and Cu substrate was investigated under different isothermal aging temperatures of 120 °C, 150 °C, and 190 °C. Scanning electron microscopy (SEM) was adopted to observe the morphological evolution of interfacial IMC layers. The composition and phase of the IMCs were identified by energy-dispersive X-ray spectroscopy (EDS) and X-ray diffraction (XRD), respectively. Results show that the morphology of the Cu 6 Sn 5 transformed from scalloped to plate-like after solid-state aging, while that of the Cu 3 Sn phase remains the layer-type. Nano-TiO 2 particles have a strong influence on the growth of both the Cu 6 Sn 5 and Cu 3 Sn IMC layers. The thickness of Cu 3 Sn layer increases promptly with aging temperature and time, while that of Cu 6 Sn 5 layer increases slowly. This might be due to the Cu 3 Sn grows at the expense of Cu 6 Sn 5 layer. The growth exponent value of the Cu 6 Sn 5 layer ranges from 0.52 to 0.8, while that of the Cu 3 Sn ranges from 0.45 to 0.64. The addition of nano-TiO 2 significantly affected the Cu 6 Sn 5 layer growth, but very little influence on the growth of Cu 3 Sn layer, especially at the low aging temperature. The activation energies for the Cu 6 Sn 5 and Cu 3 Sn layers are the range of 14.91 kJ/mol to 20.95 kJ/mol and 85.51 kJ/mol to 86.23 kJ/mol, respectively. Adding 0.1 wt% nano-TiO 2 to Sn 3.0Ag 0.5Cu solder exhibits the smallest growth rate for both the two IMC layers and gives the most prominent effect in suppressing IMC growth. Based on the theory of adsorption, grain boundary pinning is one of the most important mechanisms for regarding the Cu 6 Sn 5 and Cu 3 Sn growth when nano-TiO 2 is added.

The influence of joint size on the interfacial reaction in Sn-3.0Ag-0.5Cu-0.1TiO 2 solder joints was investigated in this study. The thickness and grain size of the intermetallic layer were characterized by scanning electron microscope (SEM). Results show that both the thickness and grain size of the intermetallic compound (IMC) increases with the increase in joint size. The growth exponents for both IMC layers and grains are determined by curve-fitting to study the growth kinetics of IMC in wetting reaction. Results reveal that the growth exponents for IMC layer and grains increase with increase in joint size. The size effect might be due to the difference of Cu concentration distribution near the IMC interface in the molten solder. A two dimensional finite element method was adopted to investigate the kinetics of the Cu diffusion behavior in solder joint during the reflow process. Results reveal that the diffusion of Cu atoms might be influenced by the coarsening of the scallop like grains.

In this work, a high-order numerical approach based on the immersed-boundary method to simulate viscous incompressible flows involving arbitrary boundaries is described. The idea is to combine compact finite difference schemes and a high-order direct forcing approach of the sharp-interface immersed-boundary method. In this approach, a particular challenge is to solve the pressure Poisson equation using the compact stencil. This issue is addressed by introducing an efficient approach based on high-order corrections to the right-hand side of the Poisson equation (that is, the source term) while retaining the second-order short stencil for the Laplace operator. The two-dimensional implementation is described, for which third-order global convergence is achieved when an immersed boundary is present.

Single-cell RNA sequencing examines the transcriptome of individual cells and reveals the inter-cell transcription heterogeneity, playing a critical role in both scientific research and clinical applications. Recently, droplet microfluidics-based platform for expression profiling has been shown as a powerful tool to capture of the transcriptional information on single cell level. Despite the breakthrough this platform brought about, it required the simultaneous encapsulation of single cell and single barcoded bead, the incidence of which was very low. Suboptimal capturing efficiency limited the throughput of the Drop-seq platform. In this work, we leveraged the advance in inertial microfluidics-based cell sorting and designed a microfluidic chip for high efficiency cell-bead co-encapsulation, increasing the capturing rate by more than four folds. Specifically, we adopted spiral and serpentine channels and ordered cells/beads before the encapsulation region. We characterized the effect of cell concentration on the capturing rate and achieved a cell-bead co-capturing rate up to 3%. We tested this platform by co-encapsulating barcoded beads and human-mouse cell mixtures. The sequencing data distinguished the majority of human and mice expressions, with the doublet rate being as low as 5.8%, indicating that the simultaneous capturing of two or more cells in one droplet was minimal even when using high cell concentration. This chip design showed great potential in improving the efficiency for future single cell expression profiling.

Background Currently, over 20 genes have been defined that can confer susceptibility for high-risk breast cancer. Although research has proved the utility of multiple-gene sequencing in the assessment of breast cancer risk, there is little data from China patients. Here, we use a multiple-gene sequencing panel to identify the variant spectrum in Chinese high-risk breast cancer subjects. Findings A total of 829 Chinese high-risk breast cancer patients participated in the research. The coding regions of 115 hereditary cancer susceptibility genes were captured and sequenced using a next generation sequencing platform from Complete Genomics and Illumina. Single Nucleotide Polymorphism and small Insertion/deletion variants were defined and analyzed. We developed a semi-automatic interpretation pipeline which enables accurate variants classification. In total, 193 pathogenic variants were identified in 45 genes from 177 patients. The pathogenic variant carrier rate is 21.4%: with 10.5% patients carrying a BRCA1 or BRCA2 mutation only, 10.0% of patients carried non-BRCA gene mutations only, while 1.0% of patients carried both a BRCA1/2 and a non-BRCA gene mutation. Variants of uncertain significance (VUS) totaling 2632 were identified in 115 genes from 787 of 829 patients: 82.5% patients carried more than one VUS, and only 5.1% patients did not carry any VUS. Families carrying pathogenic variants were tracked and adenoma was founded in three of them. Conclusions Our data provide a comprehensive analysis of potential susceptibility variations of high-risk for breast cancer in a Chinese population. This data will be useful for the comparison of the susceptibility variation spectrum between different populations and to discover potential pathogenic variants to improve the prevention and treatment of high-risk breast cancer.

Active retrotransposons play important roles during evolution and continue to shape our genomes today, especially in genetic polymorphisms underlying a diverse set of diseases. However, studies of human retrotransposon insertion polymorphisms (RIPs) based on whole-genome deep sequencing at the population level have not been sufficiently undertaken, despite the obvious need for a thorough characterization of RIPs in the general population. Herein, we present a novel and efficient computational tool called Specific Insertions Detector (SID) for the detection of non-reference RIPs. We demonstrate that SID is suitable for high-depth whole-genome sequencing data using paired-end reads obtained from simulated and real datasets. We construct a comprehensive RIP database using a large population of 90 Han Chinese individuals with a mean ×68 depth per individual. In total, we identify 9342 recent RIPs, and 8433 of these RIPs are novel compared with dbRIP, including 5826 Alu, 2169 long interspersed nuclear element 1 (L1), 383 SVA, and 55 long terminal repeats. Among the 9342 RIPs, 4828 were located in gene regions and 5 were located in protein-coding regions. We demonstrate that RIPs can, in principle, be an informative resource to perform population evolution and phylogenetic analyses. Taking the demographic effects into account, we identify a weak negative selection on SVA and L1 but an approximately neutral selection for Alu elements based on the frequency spectrum of RIPs. SID is a powerful open-source program for the detection of non-reference RIPs. We built a non-reference RIP dataset that greatly enhanced the diversity of RIPs detected in the general population, and it should be invaluable to researchers interested in many aspects of human evolution, genetics, and disease. As a proof of concept, we demonstrate that the RIPs can be used as biomarkers in a similar way as single nucleotide polymorphisms.

The aim of this study was to identify the hub genes in breast cancer and provide further insight into the tumorigenesis and development of breast cancer. To explore the hub genes in breast cancer, we performed an integrated bioinformatics analysis. Two gene expression profiles were downloaded from the GEO database. The differentially expressed genes (DEGs) were identified by using the “limma” package. Then, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to explore the functional annotation and potential pathways of the DEGs. Next, protein–protein interaction (PPI) network analysis and weighted gene coexpression network analysis (WGCNA) were conducted to screen for hub genes. To confirm the reliability of the identified hub genes, we obtained TCGA-BRCA data by using WGCNA to screen for genes that were strongly related to breast cancer. By combining the results from the GEO and TCGA datasets, we finally identified 15 real hub genes in breast cancer. Finally, we performed an overall survival analysis to explore the connection between the expression of hub genes and the overall survival time of breast cancer patients. We found that for all hub genes, higher expression was associated with significantly shorter overall survival times among breast cancer patients.

The tumor microenvironment is composed of numerous cell types, including tumor, immune and stromal cells. Cancer cells interact with the tumor microenvironment to suppress anticancer immunity. In this study, we molecularly dissected the tumor microenvironment of breast cancer by single-cell RNA-seq. We profiled the breast cancer tumor microenvironment by analyzing the single-cell transcriptomes of 52,163 cells from the tumor tissues of 15 breast cancer patients. The tumor cells and immune cells from individual patients were analyzed simultaneously at the single-cell level. This study explores the diversity of the cell types in the tumor microenvironment and provides information on the mechanisms of escape from clearance by immune cells in breast cancer.One Sentence SummaryLandscape of tumor cells and immune cells in breast cancer by single cell RNA-seq

The influence of titanium on the interfacial reaction and soldering strength between Sn3.5Ag4Ti(Ce,Ga) and silicon substrates has been studied. The microstructure, the distribution of the elements, and the new phases formed at the interface were investigated. It is observed that the Sn3.5Ag4Ti(Ce,Ga) solder can wet the silicon well under the agitation of external force. The titanium element could be found to obviously segregate at the silicon/solder interface by element mapping, and some discontinuous reaction products could be found at the silicon/solder interface by transmission electron microscopy (TEM). Theoretical analysis results suggest that there might be two soldering mechanisms coexisting in the soldering process, the chemical adsorption of Ti on the silicon surface and the interfacial reaction between Si substrate and Sn3.5Ag4Ti(Ce,Ga) solder. Both of them play important roles in realizing reliable bonding of silicon to silicon. The interfacial model between Si and Sn3.5Ag4Ti(Ce,Ga) active solder was established to explain the bonding mechanism. The shear strengths of the soldered silicon/silicon joints were measured and the effects of Ti on the bonding strength are discussed.

To reveal the effects of Titanium on active bonding between Sn3.5Ag4Ti(Ce,Ga) alloy filler and Silicon, the characteristics of the as-bonded Si/Si substrates and bonded Si/Si substrates aged at 190 °C for 720 h were investigated. The active element Ti is found to be segregated at the interface of Sn3.5Ag4Ti(Ce, Ga)/Si joint, and the TiSi and TiSi 2 phases are identified to be formed discontinuously along the interface. Experiment results reveal that active element Ti plays an important role for obtaining reliable bonding at low temperature, and shear strength of the Si/Si joints meets the requirements of die or wafer bonding application.

Changes in chromatin structure (chromatin remodeling) are essential regulatory processes for neuronal development, but the molecular mechanisms are unclear. The aim of the present study was to assess the effects of conditional knockout (Ko) of the Brahma-related gene-1 (Brg1) in the mouse central nervous system (CNS) on postnatal development. Brg1 was deleted in the CNS by crossing mice carrying the Brg1 conditional allele with a transgenic line expressing Cre under the control of the Nex 1 promoter. Brg1, PSD-95, NR2A and NR2B protein expressions were assessed using western blotting. Immunofluorescence, Nissl and TUNEL staining were used to assess cortical neuron viability. Hippocampal neurons were extracted from mouse embryos to observe the effects of neuronal degeneration associated with oxidative stress using Paraquat dichloride x-hydrate or 80% oxygen. Brg1(fx/fx);NEX-Cre mice were significantly smaller in both body size and brain size after P35 conditional Ko of Brg1 in mouse cortical progenitors. The amount of neurons and their dendritic branches were significantly reduced in Brg1 Ko cortexes during early postnatal development. Absence of Brg1 may result in increased number of astrocytes. Loss of Brg1 increased damaged and dying neurons associated with oxidative stress. Furthermore, loss of NR2A in the Brg1 Ko cortex during early postnatal development, and delayed the NR2B-NR2A switch. Therefore, Brg1 may play a critical role in neuronal growth by regulating the NR2B-NR2A switch. Our findings provide an insight in chromatin remodeling regulation in postnatal neuronal development.

Summary A moment-of-fluid method is presented for computing solutions to incompressible multiphase flows in which the number of materials can be greater than two. In this work, the multimaterial moment-of-fluid interface representation technique is applied to simulating surface tension effects at points where three materials meet. The advection terms are solved using a directionally split cell integrated semi-Lagrangian algorithm, and the projection method is used to evaluate the pressure gradient force term. The underlying computational grid is a dynamic block-structured adaptive grid. The new method is applied to multiphase problems illustrating contact-line dynamics, triple junctions, and encapsulation in order to demonstrate its capabilities. Examples are given in two-dimensional, three-dimensional axisymmetric (R–Z), and three-dimensional (X–Y–Z) coordinate systems. Copyright © 2015 John Wiley & Sons, Ltd.

The role of active element titanium for the bonding alumina substrates using Sn3.5Ag4Ti(Ce,Ga) alloy filler at 250 °C in air was studied. The influence of soldering time on the microstructure and element distribution was investigated. It was observed that the Sn3.5Ag4Ti(Ce,Ga) solder could wet the alumina well under the agitation of external force. No continuous reaction products could be detected at the alumina/solder interface by using scanning electron microscopy and X-ray diffractometer. It might be inferred that the joining could be accomplished by chemical adsorption of Ti on the alumina/solder interface, regardless of whether or not an interfacial reaction layer is formed. The theoretical analysis of the Ti element adsorption at the alumina/solder interface was tried. Results can further explain the adsorption phenomenon of Ti at the interface prior to bond formation. In the case of environmental temperature has yet to meet the chemical reaction conditions, the chemical adsorption between active elements and alumina can get good bond as well. The shear strengths of the soldered Al2O3/Al2O3 substrates with the soldering time of 15 min, 30 min, and 1 h were measured to be 15.46, 16.15, and 17.39 MPa respectively.

The creep behavior of 95.8Sn–3.5Ag–0.7Cu shear-lap solder joints was investigated at different shear stresses ranging from 2–26 MPa and test temperatures of 25, 75, and 125°C. The stress exponent can be clearly defined in the low-stress (τ 15 MPa) ranges. The stress exponent is larger in the high-stress range, and decreases with increasing temperature in both low and high-stress ranges. The average modulus compensated shear stress transition point and the average activation energy were determined to be 1.08 × 10−3 and 90.59 kJ/mol, respectively. A creep constitutive model with internal stress incorporated into the Garofalo hyperbolic sine law model was used to describe the creep behavior of 95.8Sn–3.5Ag–0.7Cu shear-lap solder joints. In this model, the relationship between creep strain rate and shear stress was determined by introducing internal stress that is a function of the shear stress in the low-stress range and a function of particle size and volume fraction of intermetallic particles in the high-stress range. The internal stress was calculated on the basis of the different creep mechanisms in the low and high-stress ranges. Results showed that the modified creep constitutive model was consistent with experimental data, which indicates that the model can be used to predict the creep behavior of 95.8Sn–3.5Ag–0.7Cu shear-lap solder joints.

The growth kinetics of the interfacial intermetallic compounds (IMCs) between Sn–3.0Ag–0.5Cu–xTiO2 composite solder and Cu substrate during reflow process has been investigated in this work. Scanning electron microscope was adopted to observe the microstructure evolution of solder joints and measure the thickness of the interfacial IMC layer. The IMC phases were identified by energy-dispersive X-ray spectroscopy and X-ray diffractometry. Results show that both the reflow time and nano-TiO2 addition affects the microstructural morphology of IMCs. The thickness of Cu6Sn5 IMC was observed to increase with an increase in the reflow time, decrease with nano-TiO2 addition, and has a significant drop with the nano-TiO2 proportion of about 0.1 wt%. The growth of IMC layer was found to deviate the classical Fick’s diffusion law at the early stages of the IMC growth and then to approach the parabolic law. To explore the interfacial IMC growth kinetics, a diffusion wave model was proposed for predicting the IMC growth. Results show that the theoretical model was well consistent with the experimental data, which shows the feasibility of the model to predict the interfacial IMC growth for Sn–3.0Ag–0.5Cu–xTiO2 solder joints in the reflow process.

The adjoint optimization method has been well developed and applied in the field of aviation. In this paper, the adjoint method is used to optimize the head shape of a simplified high-speed train, and the feasibility of this method in aerodynamic shape optimization of high speed-trains is discussed. The optimization results show that the aerodynamic drag coefficient of the optimized train is 0.9% lower than that of the original one, while the main feature of the head shape is not changed significantly. The adjoint method has important engineering application value in the aerodynamic optimization of high-speed trains.