Bond line thickness and die tilt inspection in die bonding process

This study focuses upon building an automated inspection system for the in-line measurement of bond-line thickness (BLT) and die tilt in die attachments in the semiconductor packaging process. A prototype of a visual system utilizing the line scan stereo vision technique via two linear CCD cameras has been developed for the die bonding quality inspection. A novel algorithm is proposed for the determination of the 3D coordinates of certain points on an object. The BLT and die tilt of a die attached chip of substrate height 800 μm and cross section 15 × 15 mm² were measured to be approximately 76.8 μm and 0.00094, respectively. The measurement can be completed within one second. Thus the in-line inspection of die bonding quality can be conducted efficiently using the proposed technique.     

A QoS-driven approach for service-oriented device anycasting in ubiquitous environments

The vision of pervasive computing is to let users enjoy ICT-enabled services in an “any time, anywhere, on any device” manner. It aims to supply ubiquitous services through communications among a set of devices deployed in a ubiquitous environment. Due to the diverse QoS needs of different kinds of ubiquitous services and users, it is a critical challenge to select an optimal set of devices with the objective of achieving service-specific QoS goals like low packet loss, short packet delay, and high energy efficiency. In this paper, the problem is first formulated as the service-oriented device anycasting problem (SDAP) and then proved as an NP-complete problem. By adopting a tree-based service representation model, Basu et al. proposed the dynamic task-embedding anycasting (DTA) approach. This approach effectively solves the SDAP in a distributed way. However, the service quality is likely sacrificed because the tree scheme does not sufficiently describe a ubiquitous service. In this paper, we propose a novel approach called the service-oriented device anycasting (SDA) approach that adopts a graph-based service representation model called the service profile (SP). By introducing a layered structure into the SP, the SDA approach can reach a compromise between service quality and computational complexity. In addition, the QoS-driven utility function is proposed to quantify service quality by matching the capabilities of heterogeneous devices to various QoS needs. Finally, the simulation results show that the SDA approach outperforms the DTA approach by saving roughly 20% of device energy and prolonging the network lifetime. Packet loss and packet delay are also improved by roughly 25% and 8%, respectively. The advantage of the SDA approach is more obvious in environments with highly mobile devices and multiple users.     

On a transistor-type hydrogen gas sensor prepared by an electrophoretic deposition (EPD) approach

A Pd/GaN/AlGaN heterostructure field-effect transistor (HFET)-type hydrogen gas sensor, based on an electrophoretic deposition (EPD) approach, is fabricated and studied. Due to the formation of good Schottky gate contact by an EPD approach, the studied HFET shows improved DC performance including the suppressed gate current and better thermal stabilities on current–voltage (I–V) characteristics. This is mainly attributed to the reduction of interface trap density and improved Pd morphology. The EPD-based Pd morphologies are examined by X-ray diffraction, energy dispersive spectroscopy, Auger electron spectroscopy, scanning electron microscopy, and atomic force microscopy. For the used gate-dimension of 1 μm × 100 μm, an EPD-based HFET shows low gate current of 2.9 nA, maximum drain saturation current of 490 mA/mm, and maximum extrinsic transconductance of 78.9 mS/mm at room temperature. Also, solid thermal stabilities on maximum drain saturation current (−0.46 mA/mm K) and maximum extrinsic transconductance (−0.08 mS/mm K) are found as the temperature is increased from 300 to 600 K. For hydrogen gas sensing application, at 370 K, the maximum hydrogen sensitivity of 600.1 μA/mm ppm H₂/air under a 5 ppm H₂/air ambiance and fast response time (30 s) and recovery time (47 s) under a 10,000 ppm H₂/air ambiance are obtained. The EPD approach also demonstrates advantages of low cost, simple apparatus, easy process, little restriction on the shaped substrate, composited deposition, and adjustable alloy grain size. Therefore, the proposed EPD approach gives the promise for fabricating high-performance HFET devices and hydrogen gas sensors.     

MEMS-based formaldehyde gas sensor integrated with a micro-hotplate

This paper presents a novel micro-fabricated formaldehyde gas sensor with enhanced sensitivity and detection resolution capabilities. The device comprises a quartz substrate with Pt heaters as a micro-hotplate and deposited formaldehyde-sensing layer on it. A sputtered NiO thin film is used as the formaldehyde-sensing layer. A specific orientation of NiO becomes more apparent as the substrate temperature increases in the sputtering process, which helps the formation of NiO material with a correct stoichiometric ratio. The gas sensor incorporates Pt heating resistors integrated with a micro-hotplate to provide a heating function and utilizes Au inter-digitated electrodes. When formaldehyde is present in the atmosphere, oxydation happens near the sensing layer with a high temperature caused by the micro-hotplate and causes a change in the electrical conductivity of the NiO film. Therefore, the measured resistance between the inter-digitated electrodes changes correspondingly. The application of a voltage to the Pt heaters causes the temperature of the micro-hotplate to increase, which in turn enhances the sensitivity of the sensor. The nanometer scale grain size of the sputtered oxide thin film is conducive to improving the sensitivity of the gas sensor. The experimental results indicate that the developed device has a high stability (0.23%), a low hysteresis value (0.18%), a quick response time (13.0 s), a high degree of sensitivity (0.14 Ω ppm⁻¹), and a detection capability of less than 1.2 ppm.

     

Formation and magnetization reversal mechanisms of nano-size Fe arrays prepared on anodic aluminum oxide templates

Vertically aligned Fe arrays have been self-assembled on anodic aluminum oxide templates by evaporation. The rims of the pores, which act as obstacles to the stacking of atoms, prevent them from forming continuous films. By controlling the Fe nominal thicknesses (τ_n) from 400 to 5 nm, the morphology is changed from continuous film to isolated arrays, leading to the change of the predominant magnetization reversal from domain wall motion to spin rotation. For samples with τ_n < 59 nm, isolated, rather than interconnected, morphology is formed. In this range, the coercivity shows a spectacular change for τ_n = 47 nm, with an array diameter of about 52 nm, achieving a maximum of about 38 kA/m. The critical dimension of single-domain array is therefore determined. The magnetostatic and exchange interactions are reduced due to the thermal fluctuation, and the magnetization leaves from the in-plane direction to be randomly distributed in 3-D, for τ_n < 27 nm.     

Mechanical strength of Sn-3.5Ag-based solders and related bondings

The tensile strengths of bulk solders and joint couples of Sn-3.5Ag-0.5Cu, Sn-3.5Ag-0.07Ni, and Sn-3.5Ag-0.5Cu-0.07Ni-0.01Ge solders and the shear strengths of ball grid array (BGA) specimens, solder-ball-attached Cu/Ni/Au metallized substrates were investigated. The tensile strength of the bulk is degraded by thermal aging. The Ni-containing solder exhibits lower tensile strength than Sn-3.5Ag-0.5Cu after thermal aging. However, the Ni-containing solder joints show greater tensile strength than the Cu/Sn-3.5Ag-0.5Cu/Cu joint. Fracture of the solder joint occurs between the intermetallic compound (IMC) and the solder. The shear strength and fracture mechanism of BGA specimens are the same regardless of solder composition.     

Adaptive AR modeling in white Gaussian noise

Autoregressive (AR) modeling is widely used in signal processing. The coefficients of an AR model can be easily obtained with a least mean square (LMS) prediction error filter. However, it is known that this filter gives a biased solution when the input signal is corrupted by white Gaussian noise. Treichler (1979) suggested the γ-LMS algorithm to remedy this problem and proved that the mean weight vector can converge to the Wiener solution. In this paper, we develop a new algorithm that extends works of Vijayan et al. (1990), for adaptive AR modeling in the presence of white Gaussian noise. By theoretical analysis, we show that the performance of the new algorithm is superior to the γ-LMS filter. Simulations are also provided to support our theoretical results     

Hydrophilic UV-curable PU resins for PET micro-fiber applications

Hydrophilic UV-curable PU oligomers (UV-PU) were prepared by mixing either the toluene diisocyanates (TDI) with polyethylene glycol-1000, or the isophorone diisocyanate (IPDI) with polypropylene glycol-1000 and dimethylol propanic acid (DMPA), to produce the desired carboxylic acid bearing or non-ionic PU oligmer (NCO-PU), separately. The 2-hydroxyethyl methacrylate (HEMA) was then added into the NCO-PU oligomer to form acrylate-terminated (UV-curable) PU oligomer (UV-PU). The reactive diluents, such as 1,6-hexanediol diacrylate (HDDA), trimethylolpropane tricarylate (TMPTA) and others were used to adjust the viscosity of UV-PU and to control the concentration of acrylic group. The hydrophilic UV-curable PU system was formulated and applied on PET micro-fiber and then cured by an UV-radiation at ambient temperature. The physical, thermal, and mechanical properties, in particular, the hydrophilic properties of UV-curable PU treated PET micro-fibers will be discussed.     

Predicting Construction Contractor Default with Option-Based Credit Models—Models’ Performance and Comparison with Financial Ratio Models

Construction contractor evaluation is a critical issue in successfully completing a project. It is important for project owners and other stakeholders to identify potentially failing contractors and to avoid awarding them contracts. Previous studies developed construction contractor default prediction models incorporating managerial or economic variables into traditional financial ratio models to enhance predicting power. However, managerial variables are subjective and qualitative, and both economic variables and financial ratios are only available periodically and may not provide the necessary information in time. This study predicts contractor default by employing three option-based credit models (BSM, CB, and BS) based on stock market information, and the empirical results show that all of the models have strong discriminatory power in ranking contractors from riskiest to safest. The misclassification rates of the three models are BSM: 10%, CB: 10%, and BS: 12.7%, all of which are smaller than that of the enhanced ratio model developed by Russell and Zhai (22%), and two of which are smaller than that of the model developed by Severson and colleagues (12.5%). The results show that option-based credit models are good alternatives for construction contractor default prediction.     

Muscle Wasting in Chronic Kidney Disease: Mechanism and Clinical Implications—A Narrative Review

Muscle wasting, known to develop in patients with chronic kidney disease (CKD), is a deleterious consequence of numerous complications associated with deteriorated renal function. Muscle wasting in CKD mainly involves dysregulated muscle protein metabolism and impaired muscle cell regeneration. In this narrative review, we discuss the cardinal role of the insulin-like growth factor 1 and myostatin signaling pathways, which have been extensively investigated using animal and human studies, as well as the emerging concepts in microRNA- and gut microbiota-mediated regulation of muscle mass and myogenesis. To ameliorate muscle loss, therapeutic strategies, including nutritional support, exercise programs, pharmacological interventions, and physical modalities, are being increasingly developed based on advances in understanding its underlying pathophysiology.