Multi-wall Carbon Nanotube Gas Sensor Fabricated

INTEREST in nano-materials has been growing rapidly for the past several years. Carbon nanotubes (CNTs) are especially promising as new materials for a variety of potential applications. Existing electrical sensor materials include semi conducting metal oxides, silicon devices, and carbon black-polymer composites. Semi conducting metal oxides have been widely used for NO and NH detection. These sensors operate at high temperatures (200 C to 600 C) to achieve enhanced chemical reactivity between molecules and the sensor materials for substantial sensitivity. Conducting polymers and organic phthalocyanine semiconductors have also been investigated for NO sensing. The former exhibits limited sensitivity, whereas the latter tends to have very high resistivity (sample resistance of -Ohms). Recently, CNT-based gas sensors have received considerable attraction because of their outstanding properties, such as faster response, higher sensitivity, lower operating temperature, and a wide variety of gases that may be detected compared with the other types of gas sensor. Up-to-date reported studies on possible applications of carbon nanotubes as gas sensors have been focused either on isolated single wall carbon nanotubes (SWCNTs) or on SWCNT mats. Theoretical studies have predicted significant changes in the electronic properties of carbon nanotubes because of gas adsorption. These results lead to the application of carbon nanotubes as gas sensors to detect sub-ppm concentrations of oxidizing gases like NO , and CO. However, it takes a long time for the CNT-based gas sensors fabricated to recover owing to the small diffusion barriers of gases on CNT surfaces. This letter reports on the fabrication of the sensor composed of a heater, a diaphragm, a contact electrode, and a directly grown MWCNT-sensing film on a thermally insulated dielectric diaphragm to improve recovery characteristics. Following a description of the integrated structure and the MWCNT deposition process, the characteristics of the sensor when exposed to NO are presented.

Applications of Nano-materials inside cells

The application of various types of Nano-materials inside cells are on the research path. Nanotechnology refers to the research and technology development at atomic, molecular, and macromolecular scales, which leads to the controlled manipulation and study of structures and devices with length scales in the range of 1—100 nanometers. In the last two decades, the research of nanotechnology has grown explosively with over three hundred thousands publications in the field of nano-science according to Web of Science. Among these spectacular developments, a new emerging field that combines nanotechnology and biotechnology — nano biotechnology — is receiving increased attentions.

Nano-scale structures and materials (e.g., nano-particles, Nano-wires, nano-fibers, and nano-tubes) have been explored in many biological applications (e.g., bio-sensing, biological separation, molecular imaging, and/or anticancer therapy) because their novel properties and functions differ drastically from their bulk counterparts. Particularly, their high volume/surface ratio, surface tailor ability, improved solubility, and multifunctional open many new possibilities for biomedicine. Moreover, the intrinsic optical, magnetic, and biological properties of nano-materials offer remarkable opportunities to study and regulate complex biological processes for biomedical applications in an unprecedented manner. Since life itself, fundamentally, is a collective of processes at nano-scale within cells, it is unavoidable and necessary to understand the impacts of the presence of nano-materials inside the cells when one explores the advantages and promises of nano-materials for biomedical applications.

Obviously, the successful applications of the nano-materials in biology and medicine sometimes require them to enter cells. The entry of the nano-materials into the cell has to cross a major barrier, that is, the cell membrane that consists of a nanometer-thin lipid bilayer with embedded or peripherally attached proteins. Although it is not a trivial matter, nano-materials can enter cells via several known processes, including (i) non-specific uptake by endocytosis, where the nano-materials often end up in endocytic compartments; (ii) direct microinjection of nano-liter of dispersion of nano-materials, which is a tedious procedure and only applicable to a limited number of cells; (iii) electroporation, which uses charges to physically ‘‘push’’ nano-materials across the membrane;
and (iv) mediated/targeted uptake based on the surface functionalization of nano-materials by using known biological interactions or promoters. Among these processes, the last one holds the great promises and offers convenient flexibility because nano-materials themselves normally need a compatible surface to interact with the cells before realizing their own functionalities. Usually, the nano-materials should be compatible with biological systems, in addition to the required good water solubility. Although there are several developed strategies to coat the nano-materials for conferring good water solubility and desired functions, an ideal surface coating should satisfy the following basic requirements: (i) preventing the nano-materials from unwanted aggregation during the long-term storage; (ii) maintaining good water solubility; (iii) retaining the functionalities of the nano-materials; and (iv) ensuring the biocompatibility before the nano-materials interact with their targeted subjects.

Computer-Aided Design Tools for Micro-electromechanical [MEMS] Systems

Simulation Tools for Micro-machined Device Design

Micro-machining technology has enabled the fabrication of several novel micro-sensors and micro-actuators. Because of the specialized processing involved, the cost of prototyping even simple micro-sensors, micro-valves, and micro-actuators is enormous. In order to reduce the number of prototype failures, designers of these devices need to make frequent use of simulation tools. To efficiently predict the performance of micro-electro-mechanical systems (MEMS) these simulation tools need to account for the interaction between electrical, mechanical, and fluidic forces. Simulating this coupled problem is made more difficult by the fact that most MEMS devices are innately three-dimensional and geometrically complicated. It is possible to simulate efficiently these devices using domain-specific solvers, provided the coupling between domains can be handled effectively. In this work recent development showed several new approaches and tools for efficient computer aided design and analysis of MEMS.

One of the recent efforts in this area has been in developing algorithms for coupled-domain mixed regime simulation. We developed a matrix-implicit multi-level Newton method for coupled domain simulation which has much more robust convergence properties than just iterating between domain-specific analysis programs, but still allows one to treat the domain analysis programs as black boxes. In addition, an another approach to accelerating coupled-domain simulation is by allowing physical simplifications where appropriate. This is referred to as mixed regime simulation. For example, self-consistent coupled electromechanical simulation of MEMS devices face a bottleneck in the finite element based nonlinear electrostatic solver. Replacing a stiff structural element by a rigid body approximation which has only 6 variables, all variables associated with the internal and surface nodes of the element are eliminated which is now a function of the rigid body parameters. Using this coupled domain approach has made it possible to perform coupled electromechanical analysis of an entire comb drive accelerometer in less than 15 minutes.

Analysis of the resonance behavior of micro-machined devices packaged in air or fluid requires that fluid damping be considered. Since the spatial scales are small and resonance analyzes are typically done assuming a small amplitude excitation, fluid velocities can often be analyzed by ignoring convective and inertial terms and then using the steady Stokes equation. For higher frequency applications, the convective

term may still be small, but the inertial term rises linearly with frequency. Therefore, analyzing higher frequency resonances requires the unsteady Stokes equations, though the small amplitudes involved make it possible to use frequency domain techniques. We have developed a fast Stokes solver, Fast Stokes,

based on the pre-corrected-FFT accelerated boundary-element techniques. The program can solve the steady Stokes equation or the frequency domain unsteady Stokes equation in extremely complicated geometries. For problems discretized using more than 50,000 unknowns, our accelerated solver is more than three orders of magnitude faster than direct methods.

Enhancing MEMS Design Using Statistical Process Information

Micro Electro-Mechanical Systems (MEMS) design is often done using circuit design rules for layout and complex synthesis or mechanical simulation for actual device structure. The problem with this approach is that devices that work well in simulation often have high sensitivity to process variation and therefore can have properties that differ substantially from projected values. These effects lead to both poor performances and lower yields.

Figure above shows a picture as well as a diagram of a comb-drive resonator. This device is ideal for process sensitivity analysis because its resonant frequency is a key system parameter that can be easily computed in simulation and is directly affected by the process and underlying geometries.As an example of the importance of process variation to device performance, Figure below compares a 50 K Hz resonator based on a 2 mm folded beam flexure to a 50Khz resonator using a 4 mm beam. The graph shows that for a 1 s manufacturing variation in beam width (taken from actual MEMS fabrication data), the 4 mm system experienced a 4.2 frequency variation compared to the 10 reduction in system variation (for frequency) would lead to higher yield and tighter system specifications.A methodology for enhancing MEMS designs was developed using the property shown in one of the figure. The comb-drive resonator was used as an example device. A tool for synthesizing resonators that is more robust to process variation was developed. One of the figures shows the results of synthesizing three resonators using the tool. The above figure shows a 50 K Hz resonator synthesized for area alone. Typical fabrication process variation would cause this device over 10variation, figure shows the same resonator optimized for less than 95process robustness.

MEMS-Based Reconfigurable and Evolvable Sensor Networks

Over the last decade wireless sensor networks (WSNs) have attracted much attention from both research and industries. The idea of wireless sensor network has significantly impacted on the traditional sensing systems due to its reliability, robustness, flexibility and redundancy. A wireless sensor network may consist of a large number of sensor nodes to aggregate and transmit data in Ad hoc networking. The autonomous, adaptable, and distributed nature of reconfigurable sensor networks will allow the sensor nodes to be deployed in a wide range of applications. However, most of wireless sensor networks are designed for terrestrial applications, such as environmental monitoring, surveillance, reconnaissance, targeting, tracking, risk assessment, and building automation, etc.

In future’s space missions the autonomous, miniaturized, intelligent and massively distributed networked systems will play important roles. Due to the flexibility, reliability, and low cost, the networked constellations with hundreds-to-thousands of very small satellites could eventually replace the functionality of traditional larger satellites. Thus, there has been an increasing need to develop flexible, reconfigurable, and intelligent space-based sensor networks to support this developmental trend. Technical advancements in Ad hoc networking, wireless communications, MEMS devices, low-power electronics, adaptive and reconfigurable hardware, micro-spacecraft, and micro-sensors will directly facilitate the development of such highly integrated space networking systems. The ESPACENET1 project is targeting the design of evolvable and reconfigurable sensor networks and distributed reconfigurable System-On-Chip (SoC) sensor nodes for aerospacebased monitoring and diagnostics. In designing such a space-based sensor network, multiple objectives or measures of performance are involved. These objectives are often essentially competing or in conflict with each other. For an Ad-hoc WSN, the performance is unavoidably related with its working environment and missions. So the decision variables for the whole networking system should be online determined at different levels and scales under multiple objectives. Thus, multiobjective optimal design is a particularly challenging issue. Multiobjective evolutionary algorithms (MOEAs) have received considerable attention in many engineering optimization problems. In recent years MOEAs have also been applied to the area of WSNs. It is highly desirable for MOEAs to provide enough automation and flexibility for an engineering system. However, in comparison to other applications, power constraints, hierarchical topology, hardware adaptability, and fault-tolerance requirements as well as other specific constraints pertinent to the aerospace domain make the multiobjective design with MOEAs even more challenging in the ESPACENET project. The main objective of this post is to present the multiobjective optimal design of MEMS-based reconfigurable and evolvable sensor networks.