Temperature-programmed GC using silicon microfabricated columns with integrated heaters and temperature sensors

Columns were fabricated in silicon substrates by deep reactive-ion etching. The channels were sealed with a glass wafer anodically bonded to the silicon surface. Heaters and temperature sensors were fabricated on the back side of each column chip. A microcontroller-based temperature controller was used with a PC for temperature programming. Temperature programming, with channel lengths of 3.0 and 0.25 m, is described. The 3.0-m-long channel was fabricated on a 3.2 cmx3.2 cm chip. Four columns were fabricated on a standard 4-in. silicon wafer. The 0.25-m-long channel was fabricated on a 1.1 cmx1.1 cm chip, and approximately 40 columns could be fabricated on a 4-in. wafer. All columns were coated with a nonpolar poly(dimethylsiloxanes) stationary phase. A static coating procedure was employed. The 3.0-m-long column generated about 12000 theoretical plates, and the 0.25-m-long channel generated about 1000 plates at optimal carrier gas velocity. Linear temperature ramps as high as 1000 degrees C/min when temperature programmed from 30 to 200 degrees C were obtained with the shorter column. With the 0.25-m-long column, normal alkanes from n-C5 through n-C15 were eluted in less than 12 s using a temperature ramp rate of 1000 degrees C/min. Temperature uniformity over the column chip surface was measured with infrared imaging. A variation of about 2 degrees C was obtained for the 3.0-m-long channel. Retention time reproducibility with temperature programming typically ranged from +/-0.15% to +/-1.5%. Design of the columns and the temperature controller are discussed. Performance data are presented for the different columns lengths.     

Behavior navigation system for harsh environments

Performing general human behavior by experts’ navigation is expected to be realized as wearable technologies and computing systems are further developed. We have proposed and developed the prototype of the advanced behavior navigation system (BNS) using augmented reality technology. Utilizing the BNS, an expert can guide a non-expert to perform a variety of tasks. The BNSs are useful in tasks to be performed in harsh and hazardous environments, such as factories, construction sites, and areas affected by natural disasters (e.g. earthquakes and tsunamis). In this paper, we present a BNS that is specifically designed to operate in harsh environments, with characteristics such as wet or dusty conditions. The implementation, experimental results, and evaluation of the BNS prototypes are presented.     

Statistical investigation of the cotton dyeing kinetics of CI Reactive Black 5 dye

In this study, the dyeing kinetics of CI Reactive Black 5 dye was statistically investigated. Cotton fabrics were dyed with this dye under different conditions by the exhaustion technique. Dye samples were taken from the dyebath from the start to the end of the process at 10 min intervals in order to determine the percentage dye exhaustion. The transmittance of the coloured dyebath samples was measured using a UV‐vis spectrophotometer. The results were investigated by statistical methods using analysis of variance and regression curves. The dye exhaustion of the cotton fabrics was found to change as a function of the dyeing parameters. Times of half‐dyeing were determined from the regression curves.     

Estimating Time Dependence of Edge Plasma Turbulence in IR-T1 Tokamak

Time dependence of edge plasma turbulence was investigated in the IR-T1 tokamak. Time dependence of fluctuation level and spectra were measured using Langmuir probe in the region r/a = 0.8–1. In all times of typical shot, the edge plasma was turbulently unstable, with a broad band fluctuation spectrum in the range of frequencies f = 10–1000 kHz. The relative fluctuation level as monitored by the ion saturation current J⁺ was very high, in the range ?0.1–0.6 all over the time, while the fluctuation power spectra were roughly invariant in shape.     

Biasing Effect on the Edge Plasma Electrical Fluctuations in IR-T1 Tokamak

The effect of biasing on the edge plasma electrical fluctuations and their control was investigated. Biasing was applied to both positive and negative polarity in the range of +380 to ?380 V. As soon as biasing was applied, the electrical fluctuations, fluctuations frequency and H_α emission reduced significantly and all of them showed the positive effect of biasing in the edge plasma electrical fluctuations reduction. Experiments also showed that positive biasing is more effective than negative biasing.     

Study on the effective process parameters influencing styrene and acrylonitrile grafting onto seeded polybutadiene latex

A series of experiments were designed and conducted to determine the significance of process parameters in the grafting of styrene and acrylonitrile onto polybutadiene seeds in a semicontinuous emulsion copolymerization system. The significances of the parameters were obtained by comparing the variance ratios, or F values, with F‐distributions. The significance level of each test (α‐value) was obtained by variance analysis. The important process parameters in industrial polymerization processes are usually monomer‐to‐polymer ratio, initiator type and concentration, chain‐transfer agent, and reaction temperature. The target responses were final monomer conversion, grafting degree, grafting efficiency, gel percent, and viscosity‐average molecular weight of free styrene‐acrylonitrile (SAN). The analysis of variance indicated that cumene hydroperoxide as the initiator and reaction temperature had strong effects on the graft structure. Moreover, free SAN molecular weight was significantly affected by the monomer/polymer ratio and cumene hydroperoxide and n‐dodecyl mercaptan as chain‐transfer agents. The raspberry‐like morphology of grafted acrylonitrile‐butadiene‐styrene (ABS) particles and phase separation within the particles were confirmed by transmission electron microscopy. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2011     

Collaborative multi-agent rock facies classification from wireline well log data

Gas and oil reservoirs have been the focus of modeling efforts for decades as an attempt to locate zones with high volumes. Certain subsurface layers and layer sequences, such as those containing shale, are known to be impermeable to gas and/or liquid. Oil and natural gas then become trapped by these layers, making it possible to drill wells to reach the supply, and extract for use. The drilling of these wells, however, is costly. In this paper, we utilize multi-agent machine learning and classifier combination to learn rock facies sequences from wireline well log data. The paper focuses on how to construct a successful set of classifiers, which periodically collaborate, to increase the classification accuracy. Utilizing multiple, heterogeneous collaborative learning agents is shown to be successful for this classification problem. Utilizing the Multi-Agent Collaborative Learning Architecture, 84.5% absolute accuracy was obtained, an improvement of about 6.5% over the best results achieved by the Kansas Geological Survey with the same data set. A number of heuristics are presented for constructing teams of multiple collaborative classifiers for predicting rock facies.     

On-Line Robotic Interception Planning Using a Rendezvous-Guidance Technique

A novel method for online, robotic interception of moving objects using visual feedback is proposed in this paper. No prior knowledge of the motion of the object is assumed. Since such objects might depart quickly from the workspace of the robot, fast interception is a critical issue. Thus, a novel time-optimal rendezvous-guidance technique that takes the dynamic limitations of the robot into account has been developed. In the proposed methodology, first, a parallel-navigation rule, originally introduced in the missile-guidance literature, is applied to generate a set of instantaneous task-space velocity commands, which, if executed, would keep the end-effector on a collision course with the object. Subsequently, a rendezvous-guidance method is utilized to reduce the original command set to one with velocity-matching capability. Finally, the fastest velocity command in the reduced set is chosen such that the dynamic limitations of the actuators of the robot are not violated. The proposed algorithm results in a fast and robust interception as shown by several simulation examples in 2D and 3D workspace.