Single element differentiation of chemical vapors using an array
We present a heterosensor array that exploits the collective recognition ability of a set of different gas sensors to identify individual chemical vapors. In contrast to the conventional sensing approach based on the "lock-and-key" design, the heterosensor array rely on the response patterns produced over the collection of different sensors. Diverse sensors with different operating principles are employed to provide as much chemical diversity as possible. We demonstrate that this platform provides a highly discriminative tool with single element precision.
Limits of recognition for simple vapor mixtures determined with a microsensor array.
The "limit of recognition" (LOR) has been defined as the minimum concentration at which reliable individual vapor recognition can be achieved with a multisensor array, and methodology for determining the LORs of individual vapors probabilistically on the basis of sensor array response patterns has been reported. This article explores the problems of defining and evaluating LORs for vapor mixtures in terms of the absolute and relative component vapor concentrations, where the mixture must be discriminated from those component vapors and from the subset of possible lower-order component mixtures. Monte Carlo simulations and principal components regression analyses of an extant database of calibrated responses to a set of 16 vapors from an array of 6 diverse polymer-coated surface acoustic wave sensors are used to illustrate the approach and to examine trends in LOR values among the 120 possible binary mixtures and 560 possible ternary mixtures in the data set. At concentrations exceeding the LOD, 89% of the binary mixtures could be reliably recognized (<5% error) over some composite concentration range, while only 3% of the ternary mixtures could be recognized. Most binary mixtures could be recognized only if the constituent vapor relative concentration ratio, defined in terms of multiples of the LOD for each vapor, was < or =20. Correlations with the Euclidean distance(s) separating the normalized constituent vapor response vectors allow reasonably accurate predictions of the limiting recognizable mixture composition ranges for binary and ternary cases. Results are considered in the context of using microsensor arrays for vapor detection and recognition in microanalytical systems.
Seismic and Sequence Analysis of Middle to Late Miocene Deposits of Northeast Java Basin
DOI: 10.17014/ijog.2.2.101- 110 This study is focused on Middle to Late Miocene sediments. As depicted in the regional geology of Indonesia, the area of study is part of Northeast Java Basin. There are three phases of tectonism in the basin: extensional tectonics at Eocene-Oligocene time, compressional tectonics at Middle Miocene, and compressional tectonics at Miocene-Pliocene time. The result of the study shows three sequences were developing during Middle to Late Miocene, those are: (1) Middle Miocene sequence-1 (MM-1 sequence) consisting of a Lowstand Tract System deposition in Middle Miocene-1 (LST MM-1), Transgressive System Tract deposition in Middle Miocene-1 (TST MM-1), and Highstand System Tract deposition in Middle Miocene-1 (HST MT-2); (2) Middle Miocene sequence-2 (MT-2 sequence), comprising Transgressive System Tract Middle Miocene-1 (TST MM-2), and Highstand System Tract deposition in Middle Miocene-1 (HST MM-2); (3) Late Miocene sequence-1 (LM-1 sequence), composed of a Lowstand Tract System deposition in Late Miocene -1 (LST LM-1) and a Transgressive System Tract deposition in Late Miocene-1 (TST LM-1).