A normally closed in-channel micro check valve

We present here the first surface-micromachined, normally closed, in-channel, Parylene check valve. This device is fabricated monolithically on a silicon substrate using a five-layer Parylene process. The operating structure of the check valve is a circular sealing plate on top of a ring-shaped valve seat. The sealing plate is center-anchored on top of a chamber diaphragm that is vacuum-collapsed to the bottom of the chamber in order to achieve a normally closed position. A thin gold layer on the roughened valve seat surface is used to reduce stiction between the sealing plate and the valve seat. We have achieved an in-channel check valve with a cracking (opening) pressure of 20/spl sim/40 kPa under forward bias and no measurable leakage under reverse bias up to 270 kPa. Using this design, this valve performs well in two-phase microfluidic systems (i.e. microchannel flows containing gas, liquid, or gas/liquid mixture)

Tunable Frequency Comb Generation from a Microring with a Thermal Heater

We demonstrate a novel comb tuning method for microresonator-based Kerr comb generators. Continuously tunable, low-noise, and coherent comb generation is achieved in a CMOS-compatible silicon nitride microring resonator.Comment: submitted to CLEO201

A check-valved silicone diaphragm pump

Two generations of check-valved silicone rubber diaphragm pumps are presented. Significant improvements have been made from pump to pump including the design and fabrication of a double-sided check valve, a bossed silicone membrane, and silicone gaskets. Water flow rates of up to 13 ml/min and a maximum back pressure of 5.9 kPa were achieved through pneumatic operation with an external compressed air source. Using a custom designed solenoid actuator, flow rates of up to 4.5 ml/min and a maximum back pressure of 2.1 kPa have been demonstrated

Subgraph Networks Based Contrastive Learning

Graph contrastive learning (GCL), as a self-supervised learning method, can solve the problem of annotated data scarcity. It mines explicit features in unannotated graphs to generate favorable graph representations for downstream tasks. Most existing GCL methods focus on the design of graph augmentation strategies and mutual information estimation operations. Graph augmentation produces augmented views by graph perturbations. These views preserve a locally similar structure and exploit explicit features. However, these methods have not considered the interaction existing in subgraphs. To explore the impact of substructure interactions on graph representations, we propose a novel framework called subgraph network-based contrastive learning (SGNCL). SGNCL applies a subgraph network generation strategy to produce augmented views. This strategy converts the original graph into an Edge-to-Node mapping network with both topological and attribute features. The single-shot augmented view is a first-order subgraph network that mines the interaction between nodes, node-edge, and edges. In addition, we also investigate the impact of the second-order subgraph augmentation on mining graph structure interactions, and further, propose a contrastive objective that fuses the first-order and second-order subgraph information. We compare SGNCL with classical and state-of-the-art graph contrastive learning methods on multiple benchmark datasets of different domains. Extensive experiments show that SGNCL achieves competitive or better performance (top three) on all datasets in unsupervised learning settings. Furthermore, SGNCL achieves the best average gain of 6.9\% in transfer learning compared to the best method. Finally, experiments also demonstrate that mining substructure interactions have positive implications for graph contrastive learning.Comment: 12 pages, 6 figure

Gas-phase Silicon Etching With Bromine Trifluoride

We report the first study of gas phase silicon micromachining using pure bromine trifluoride (BrF/sub 3/) gas at room temperature. This work includes both the design of a new apparatus and etching characterization. Consistent etching results and high molecular etching efficiency (80%) have been achieved by performing the etching in a controlled pulse mode. This pure gaseous BrF/sub 3/ etching process is isotropic and has a high etch rate with superb selectivity over silicon dioxide (3000:1), silicon nitride (400-800:1) and photoresist (1000:1). Moreover, gaseous BrF/sub 3/ etching has also been demonstrated in surface micromachining process, where silicon nitride channels and membranes using polysilicon as the sacrificial layer have been successfully fabricated