Curing Kinetics and Mechanical Properties of Epoxy-Cyanate Ester Composite Films for Microelectronic Applications.

In general, although abundant literature studies are available on epoxy resin systems, a complete description of the curing kinetics in epoxy-cyanate ester composites relevant to the microelectronics industry is still lacking. Herein, curing behaviors of Ajinomoto build-up films, which are epoxy/silica composites, were studied by the non-isothermal differential scanning calorimetry method, and then, three non-isothermal curing kinetics models and model-free curing methods were used to analyze curing behaviors. In addition, a copper layer was also deposited onto the surface of the build-up film, and its interfacial adhesion property was also analyzed at different pre-curing conditions. The results showed that the curing reaction of the build-up film contains two curing reaction processes, and the first curing process is suited for the autocatalytic curing model, while the other curing process is suited for the Kamal curing kinetics model. Three model-free curing methods were used to calculate the activating energy at different degrees of curing, which indicated that the activating energy is variable during the whole curing process. The interfacial adhesion strength between the build-up film and copper layer decreased with the increase in the degree of curing, which is attributed to the contribution of mechanical anchoring. This work will offer guidance in curing behaviors for improving interfacial bonding force and controlling warpage behavior for chip substrates in the future.

Automatic positioning and sensing microelectrode array (APSMEA) for multi-site electrophysiological recordings.

Technological improvement of measurements for the electrical recordings from individual neurons within network is essential in neuroscience today. Here, we present a novel automatic positioning and sensing microelectrode array (APSMEA), which simultaneously positioned desired number of neurons onto 48 recording microelectrodes automatically and scathelessly by use of negative dielectrophoretic (DEP) forces, and facilitated the measurement of the electrophysiological activities of neuronal populations after functional synaptic connections formed between neurons. The results of multi-site electrophysiological recordings during drug administration also demonstrated the application of APSMEA in bioassay with cultured rat cortical neurons. Therefore, this device should benefit the investigation of neuronal networks in vitro with more comprehensive electrophysiological experiments, and also promise the possibility of a modular device for both cell manipulation and cell-based biosensor on microchip.

Analysis of the sensitivity and frequency characteristics of coplanar electrical cell-substrate impedance sensors.

A PDMS-glass based micro-device was designed and fabricated with 12 coplanar impedance sensors integrated for electrical cell-substrate impedance sensing (ECIS). The sensitivity and frequency characteristics of the sensors were investigated both theoretically (equivalent circuit model) and experimentally for the commonly used micro-electrode dimension scale (20-80 microm). The experimental results matched well with the theoretical model analysis and revealed that, within this micro-electrode dimension scale, as the electrode width decreased or as the total electrode length decreased the sensitivity of sensor increased over the whole sensing frequency range, whilst electrode to electrode distance had no influence on sensitivity. Through our frequency characteristics analysis, the whole frequency range could be divided into four parts. New functions describing the dominant components in each frequency range were defined and validated experimentally, and could be used to explain the phenomenon of an ECIS sensing frequency window. The contribution to the impedance measurement of cells growing on the edges of the electrodes was determined for the first time. Finally, novel proposals for ECIS sensor design and ECIS measurements were presented.

Microelectrode array-based system for neuropharmacological applications with cortical neurons cultured in vitro.

Microelectrode arrays (MEAs) provide a means to investigate the electrophysiological behavior of neuronal systems through the measurements from neuronal culture preparations. Changes in activity patterns of neuronal networks are usually detected by applying neural chemicals. Because of the difficulties of fabricating the arrays, and the delicate and less reliable properties of cortical neurons, MEA-based systems with cortical neuronal networks for neurophamacological applications are technically difficult, therefore restricting their utility. Here, we report a new approach to the development of such MEA-based system with sensitive and durable MEAs conveniently fabricated and the culture conditions optimized. Upon growth differentiation, cortical neurons, cultured directly on MEAs, reach a developmentally stable and reliable activity state. With this system, we monitored the global spontaneous activities of neuronal networks and demonstrated the fine discrimination for specific substances and unique property of cortical neurons, which validated both the applicability and necessity of such system in pharmacological bioassay.

Real-time, label-free monitoring of the cell cycle with a cellular impedance sensing chip.

The cell cycle plays a crucial role in many cellular physiological processes and has drawn an increasing interest in past decades. In the current study, we have developed a bioelectronic chip-based system capable of performing real-time dynamic analysis of the cell cycle in live cells via non-invasive cellular impedance sensing. The cells were cultured on the cellular impedance sensing chip comprising microfabricated interdigitated electrode structures. HeLa cells were synchronized with double thymidine block and the cellular impedances were monitored in a time resolution of minutes during the whole 5 days' experiment. Our results show that real-time impedance sensing can clearly mirror the progression of the cell cycle-in G(1) phase and S phase, the cellular impedance increased with time, while in G(2) phase and M phase, the cellular impedance decreased. Correspondingly, the time-course impedance curves for the synchronized cells have marked "M-valleys" corresponding to the periods of mitosis of the cells. The cell cycle information revealed by the cellular impedance data was confirmed using flow cytometry and microscopy. This paper presents the first step towards in situ and label-free monitoring of the cell cycle of mammalian cells on chip in a real-time, non-invasive manner.

Negative dielectrophoretic force assisted construction of ordered neuronal networks on cell positioning bioelectronic chips.

Developing new methods and technologies in order to pattern neurons into regular networks is of utmost scientific interest in the field of neurological research. An efficient method here is developed for trapping neurons and constructing ordered neuronal networks on bioelectronic chips by using arrayed negative dielectrophoretic (DEP) forces. A special bioelectronic chip with well defined positioning electrode arrays was designed and fabricated on silicon substrate. When a high frequency AC signal was applied, the cell positioning bioelectronic chip (CPBC) is able to provide a well-defined non-uniform electric field, and thus generate negative DEP forces. The parameters, such as size of positioning electrode, conductivity of working solution, amplitude and frequency of power signal and cell concentration, were investigated to optimize the performance of the CPBC. When the neuron suspension was added onto the energized bioelectronic chip, the neurons were immediately trapped and quickly formed the predetermined pattern. Neurons may adhere and then be cultured directly on the CPBC, and show good neuron viability and neurite development. The formation of the ordered neuronal networks after two-week culture demonstrates that negative dielectrophoretic force assisted construction of ordered neuronal networks is effective, and it could be used to assist in monitoring functional activities of neuronal networks.