On-Chip ESD Protection Design: Optimized Clamps

The extensive use of Integrated Circuits (ICs) means complex working conditions for these tiny chips. To guarantee the ICs could work properly in various environments, some special protection strategies are required to improve the reliability of system. From all the possible reliability issues, the electrostatics discharge (ESD) might be the most common one. The peak current of electrostatics can be as high as tens of amperes and the peak voltage can be over thousand voltages. In contrast, the size of semiconductor device fabricated is continuing to scale down, making it even more vulnerable to high level overstress and current surge induced by ESD event. To protect the on-chip semiconductor from damage, some extra clamp cells are put together to consist a network. The network can redirect the superfluous current through the ESD network and clamp the voltage to a low level. In this dissertation, one design concept is introduced that uses the combination of some basic ESD devices to meet different requirements first, and then tries to establish parasitic current path among these devices to further increase the current handling capability. Some design cases are addressed to demonstrate this design concept is valid and efficient: 1. A combination of silicon-controlled-rectifier (SCR) and diode cluster is implemented to resolve the overshoot issue under fast ESD event. 2. A new SCR structure is introduced, which can be used as padding device to increase the clamping voltage without affecting other parameters. Based on this padding device, two design cases are introduced. 3. A controllable SCR clamp structure is presented, which has high current handling capability and can be controlled with by small signal. All these structures and topologies described in this dissertation are compatible with most of popular semiconductor fabrication process

Modeling relation paths for knowledge base completion via joint adversarial training

Knowledge Base Completion (KBC), which aims at determining the missing relations between entity pairs, has received increasing attention in recent years. Most existing KBC methods focus on either embedding the Knowledge Base (KB) into a specific semantic space or leveraging the joint probability of Random Walks (RWs) on multi-hop paths. Only a few unified models take both semantic and path-related features into consideration with adequacy. In this paper, we propose a novel method to explore the intrinsic relationship between the single relation (i.e. 1-hop path) and multi-hop paths between paired entities. We use Hierarchical Attention Networks (HANs) to select important relations in multi-hop paths and encode them into low-dimensional vectors. By treating relations and multi-hop paths as two different input sources, we use a feature extractor, which is shared by two downstream components (i.e. relation classifier and source discriminator), to capture shared/similar information between them. By joint adversarial training, we encourage our model to extract features from the multi-hop paths which are representative for relation completion. We apply the trained model (except for the source discriminator) to several large-scale KBs for relation completion. Experimental results show that our method outperforms existing path information-based approaches. Since each sub-module of our model can be well interpreted, our model can be applied to a large number of relation learning tasks.Comment: Accepted by Knowledge-Based System

Highly Accurate Quantum Chemical Property Prediction with Uni-Mol+

Recent developments in deep learning have made remarkable progress in speeding up the prediction of quantum chemical (QC) properties by removing the need for expensive electronic structure calculations like density functional theory. However, previous methods learned from 1D SMILES sequences or 2D molecular graphs failed to achieve high accuracy as QC properties primarily depend on the 3D equilibrium conformations optimized by electronic structure methods, far different from the sequence-type and graph-type data. In this paper, we propose a novel approach called Uni-Mol+ to tackle this challenge. Uni-Mol+ first generates a raw 3D molecule conformation from inexpensive methods such as RDKit. Then, the raw conformation is iteratively updated to its target DFT equilibrium conformation using neural networks, and the learned conformation will be used to predict the QC properties. To effectively learn this update process towards the equilibrium conformation, we introduce a two-track Transformer model backbone and train it with the QC property prediction task. We also design a novel approach to guide the model's training process. Our extensive benchmarking results demonstrate that the proposed Uni-Mol+ significantly improves the accuracy of QC property prediction in various datasets. We have made the code and model publicly available at \url{https://github.com/dptech-corp/Uni-Mol}

Theoretical Study on Relaxed Surrounding Rock Pressure on Shallow Bias Neighborhood Tunnels under Seismic Load

To study the distribution of relaxed surrounding rock pressure on the shallow bias neighborhood tunnels under the combined action of horizontal and vertical earthquake force, finite element software was used for failure mode analysis. Moreover, with the pseudo-static method, the calculation formula for the relaxed pressure on the shallow bias neighborhood tunnels was derived and used to analyze the variation of the rupture angle of these tunnels under the action of the seismic force. The study shows that: shallow bias neighborhood tunnels basically follow a “W” failure pattern under the combined action of horizontal and vertical seismic force, and the failure scope of the surrounding rock is controlled by four rupture angles. Rupture angles β2 and β3 between the deep and shallow tunnels of the shallow bias neighborhood tunnels are not affected by the surface slope. For tunnels with the same grade of the surrounding rock, the greater the seismic intensity, the smaller the value of β2, and the greater the value of β3. While at the same seismic intensity, the higher the grade of the surrounding rock, the smaller the β2 and β3. Ruptures angles β1 and β4 are influenced by the surface slope, seismic intensity and surrounding rock grades. A steeper surface slope leads to a smaller β1 and a greater β4; β1 increase and β4 decrease with increasing seismic intensity; while, β1 and β4 both show a decreasing trend with an increasing rock grade

Experimental analysis on physical and mechanical properties of thermal shock damage of granite

The purpose of this study was to explore the changes of mechanical and physical properties of granite under different thermal loading effects. Uniaxial compression experiments studying the rules of the influence of temperature load on mechanical properties of granite were carried out. After high-temperature heating at above 600 °C, granite tended to have stronger ductility and plasticity as well as declined peak stress and compressive strength. Thermogravimetry - differential scanning calorimetry (TG-DSC) analysis results showed that, thermal load at different temperatures induced reactions such as water loss, oxidation and crystallization in the microstructure of granite, which led to physical changes of granite. Hence it is concluded that, heating can significantly weaken the mechanical performance of granite, which provides an important support for the optimization of heating assisted processing of granite. It also reveals that, heating assisted cutting technique can effectively lower energy consumption and improve processing efficiency

Characterization of a Weak Allele of Zebrafish cloche Mutant

Hematopoiesis is a complicated and dynamic process about which the molecular mechanisms remain poorly understood. Danio rerio (zebrafish) is an excellent vertebrate system for studying hematopoiesis and developmental mechanisms. In the previous study, we isolated and identified a cloche172 (clo172) mutant, a novel allele compared to the original cloche (clo) mutant, through using complementation test and initial mapping. Here, according to whole mount in-situ hybridization, we report that the endothelial cells in clo172 mutant embryos, although initially developed, failed to form the functional vascular system eventually. In addition, further characterization indicates that the clo172 mutant exhibited weaker defects instead of completely lost in primitive erythroid cells and definitive hematopoietic cells compared with the clos5 mutant. In contrast, primitive myeloid cells were totally lost in clo172 mutant. Furthermore, these reappeared definitive myeloid cells were demonstrated to initiate from the remaining hematopoietic stem cells (HSCs) in clo172 mutant, confirmed by the dramatic decrease of lyc in clo172runx1w84x double mutant. Collectively, the clo172 mutant is a weak allele compared to the clos5 mutant, therefore providing a model for studying the early development of hematopoietic and vascular system, as well as an opportunity to further understand the function of the cloche gene

Molecular Control of Follicular Helper T cell Development and Differentiation

Follicular helper T cells (Tfh) are specialized helper T cells that are predominantly located in germinal centers and provide help to B cells. The development and differentiation of Tfh cells has been shown to be regulated by transcription factors, such as B-cell lymphoma 6 protein (Bcl-6), signal transducer and activator of transcription 3 (STAT3) and B lymphocyte-induced maturation protein-1 (Blimp-1). In addition, cytokines, including IL-21, have been found to be important for Tfh cell development. Moreover, several epigenetic modifications have also been reported to be involved in the determination of Tfh cell fate. The regulatory network is complicated, and the number of novel molecules demonstrated to control the fate of Tfh cells is increasing. Therefore, this review aims to summarize the current knowledge regarding the molecular regulation of Tfh cell development and differentiation at the protein level and at the epigenetic level to elucidate Tfh cell biology and provide potential targets for clinical interventions in the future