Fabrication of buried microfluidic channels with observation windows using femtosecond laser photoablation and parylene-C coating

We developed an advanced method for fabricating microfluidic structures comprising channels and inputs/outputs buried within a silicon wafer based on single level lithography. We etched trenches into a silicon substrate, covered these trenches with parylene-C, and selectively opened their bottoms using femtosecond laser photoablation, forming channels and inputs/outputs by isotropic etching of silicon by xenon difluoride vapors. We subsequently sealed the channels with a second parylene-C layer. Unlike in previously published works, this entire process is conducted at ambient temperature to allow for integration with complementary metal oxide semiconductor devices for smart readout electronics. We also demonstrated a method of chip cryo-cleaving with parylene presence that allows for monitoring of the process development. We also created an observation window for in situ visualization inside the opaque silicon substrate by forming a hole in the parylene layer at the silicon backside and with local silicon removal by xenon difluoride vapor etching. We verified the microfluidic chip performance by forming a segmented flow of a fluorescein solution in an oil stream. This proposed technique provides opportunities for forming simple microfluidic systems with buried channels at ambient temperature.     

Logistics planning under uncertainty for disposition of radioactive wastes

The US Department of Energy (DOE) faces an enormous environmental remediation challenge involving highly radioactive wastes at former weapons production facilities. The purpose of this analysis is to focus on equipment acquisition and fleet sizing issues related to transportation of wastes from remediation sites to disposal sites. Planning for the transportation of these wastes must be done with recognition of important uncertainties related to overall quantities of waste to be moved, the rate at which the wastes will be prepared for transport, and the certification of suitable transportation containers for use in the effort. However, deadlines for completion of the effort have already been set by the political process, without much regard for these uncertainties. To address this fleet sizing problem, we have created a robust optimization model that focuses on equipment investment decisions. Through this robust optimization, we illustrate how modeling can be used to explore the effects of uncertainty on the equipment acquisition strategy. The disposition of radioactive wastes from DOE sites is an important illustration of a category of problems where equipment investments must be made under conditions of considerable uncertainty. The methodology illustrated in this paper can be applied to this general class of problems.     

Location model for CCA-treated wood waste remediation units using GIS and clustering methods

In the next decades, a significant increase is expected in the amounts of CCA-treated wood waste that annually need to be properly disposed. This waste should be recycled only after its remediation, so planning and optimisation of the remediation units location is of major importance.A location model for CCA-treated wood waste was implemented using Geographic Information Systems (ArcGIS 8.2), with geographic information, namely land use information and the results of a questionnaire sent to Portuguese wood preservation industries. Two different clustering methods (Self-Organizing Maps and K-means) were tested in different conditions to solve the multisource Weber problem using SOMToolbox for MATLAB.The solutions obtained with the data and with both clustering methods could be used to decide on the location of these plants. SOM provided more robust and reproducible results than K-means, with the disadvantage of longer computing times. The main advantage of K-means, compared to SOM, is the reduced computing time (considering an average of all the runs, the K-means computing time is half the SOM computing time) together with the fact that it allows to obtain the best solutions in the majority of the cases, in spite of bigger variances and more geographical dispersion.     

Detection of buried ancient walls using airborne thermal video radiometry

This study examined the feasibility of using a very sensitive thermal video radiometer to derive information about subsoil objects from the air. In this study we mounted a thermal sensor onboard a helicopter and acquired digital data from an altitude of 1333 m over an archaeological site on the Golan Heights, Israel. The site, namely, Leviah Enclosure, is an Early Bronze Age settlement that is covered by a thin layer of soil. The buried structures, made from basalt, could not be observed from the ground or in aerial photos. However, in the thermal images, the buried basalt structures were significantly enhanced because they have different thermal characteristics than the ground's surface. Based on the thermal images, it was possible to generate a map to use for future excavation activity. Referring to the thermal maps, a selected area was excavated, and verification on the ground, using traditional archaeological methods revealed a positive agreement between the thermal-based map and the actual location of the buried structures. The research highlights the fact that this technology can contribute additional and useful information to the field of archaeology. Based on these results, further study is planned in order to examine the capability of the sensor under different conditions and to further excavate the entire Leviah Enclosure.     

Improved process flow for buried channel fabrication in silicon

The fabrication of microchannels using MEMS technology always attracted the attention of researchers and designers of microfluidic systems. Our group focused on realizing buried fluidic channels in silicon substrates involving deep reactive ion etching. To meet the demands of today’s complex microsystems, our aim was to create passive microfluidics in the bulk Si substrate well below the surface, while retaining planarity of the wafer. Therefore additional lithographic steps for e.g. integrating circuit elements are still possible on the chip surface. In this paper, a more economic process flow is applied which also contains a selective edge-masking method in order to eliminate under-etching phenomenon at the top of the trenches to be filled. The effect of Al protection on the subsequent etch steps is also discussed. Applying the proposed protection method, our group successfully fabricated sealed microchannels with excellent surface planarity above the filled trenches. Due to the concept, the integration of the technology in hollow silicon microprobes fabrication is now available.     

Ground water exploration in the Saurashtra peninsula

The fact that groundwater in hard-rock formations is generally confined to fissures, fractures, joints and weathered zones makes space imagery extremely useful when prospecting for groundwater in hard-rock areas. Keeping this in mind, multitemporal LANDSAT imagery of the Saurashtra region has been studied by employing visual/manual-interpretation techniques. Various hydrogeomorphological features, such as abandoned channels, buried channels, lineaments, water bodies, vegetation and floodplains, were mapped at a scale of 1:250 000. Using these maps, areas with groundwater potential were identified. Resistivity surveys were conducted in selected areas. Using these results, sites for exploratory drilling were chosen. The pumping-test results at most of the sites were quite encouraging. The present study therefore demonstrates the usefulness of remotely sensed data in groundwater exploration.     

Fabrication of Flexible Transducer Arrays With Through-Wafer Electrical Interconnects Based on Trench Refilling With PDMS

Flexible transducer arrays are desired to wrap around catheter tips for side-looking intravascular ultrasound imaging. We present a technique for constructing flexible capacitive micromachined ultrasonic transducer (CMUT) arrays by forming polymer-filled deep trenches in a silicon substrate. First, we etch deep trenches between the bottom electrodes of CMUT elements on a prime silicon wafer using deep reactive ion etching. Second, we fusion-bond a silicon-on-insulator (SOI) wafer to the prime silicon wafer. Once the silicon handle and buried oxide layers are removed from the back side of the SOI wafer, the remaining thin silicon device layer acts as a movable membrane and top electrode. Third, we fill the deep trenches with polydimethylsiloxane, and thin the wafer down from the back side. The 16 by 16 flexible 2-D arrays presented in this paper have a trench width that varies between 6 and 20 ; the trench depth is 150 ; the membrane thickness is 1.83 ; and the final substrate thickness is 150 . We demonstrate the flexibility of the substrate by wrapping it around a needle tip with a radius of 450 (less than catheter size of 3 French). Measurements in air validate the functionality of the arrays. The 250- by 250- transducer elements have a capacitance of 2.29 to 2.67 pF, and a resonant frequency of 5.0 to 4.3 MHz, for dc bias voltages ranging from 70 to 100 V.     

Estimating the depth of buried hot features from thermal IR remote sensing data: a conceptual approach

Estimating the depth of buried thermal features from remotely sensed data is a difficult problem. The theoretical basis discussed in this letter shows that if the time of initiation of the heat source is known, then utilizing two sets of thermal Infrared ( IR) data of different time instances for the same anomaly area, the depth of the buried heat source can be computed. However, if the thermal IR data are collected at time intervals close to the time of initiation of heat source, the knowledge of initial conditions of heat source is obviated. In this latter case, a double ratioing technique, utilizing three sets of thermal IR remote sensing data, acquired at different times for the same area, can be used for estimating the depth of buried heat source. Respective sample sets of characteristic curves designed for depth estimation are presented along with results of sensitivity analysis tests, performed on simulated data.     

Investigation of Structure – Biodegradability Relationships in Polychlorinated Biphenyls Using Self-Organising Maps

Polychlorinated biphenyls (PCBs) represent a significant, long-term environmental hazard. Persistent in the environment, accumulative in many species, and toxic, they are a serious pollutant at many industrial sites. The most common methods for environmental remediation – thermal or photochemical treatment – are often an unsatisfactory option if PCBs are present in chemically-contaminated sites, since these methods may convert PCBs into even more toxic chemicals such as dioxins. Microbial degradation offers a safer and more Environmentally-friendly alternative, but susceptibility to microbial degradation varies widely among members of the PCB family, and the relationship of structure to degradation rates is poorly understood. This paper discusses the use of a Self-Organising Map (SOM) to rationalise and predict degradation data for PCBs under the action of Aspergillus Niger. A SOM is shown to be able to predict biodegradability to within 25% of the experimental values for three quarters of a set of 44 PCBs. It appears that prediction of the biodegradability of dichloro-PCBs may be more difficult than prediction for other types of PCB.     

Modeling supernovae: braving a bold new frontier

The death of a massive star, called a core collapse supernova, is among the most energetic events in the universe, exploding with so much force it can be compared to 10/sup 28/ individual megaton bombs exploding at once. Researchers need powerful supercomputers capable of generating and storing terabytes and petabytes of data to simulate complex models. The US Department of Energy created the TeraScale Supernova Initiative (TSI) to do just that. The $9 million program - made up of the ORNL and eight US universities - aims to discover exactly how a supernova occurs. The scientists' charge is to perform 3D simulations of the radiation of the enormous amounts of neutrino energy and the resulting turbulent fluid flow that propels elements into space. So far, the team has generated 2D simulations, made possible because of terascale computers. They have created some 3D models, but not to the realistic detail the team needs. The team is using some of the most powerful types of computers available, capable of handling many terabytes of data. With these computers, 4,000 to 5,000 processor hours take just days - as opposed to months with a one-processor supercomputer. The team's computers include Seaborg, located at the National Energy Research Scientific Computing Center, Cheetah, located at the Center for Computational Science at ORNL, and Eagle, also located at ORNL. Use of these three computers and others like it have led to new discoveries by enabling multidimensional simulations.     

Microwave remote sensing of physically buried objects in the Negev Desert: implications for environmental research

We report remote detections of physically buried specularly reflecting objects using microwave radar at two sites: Ashalim and Tseelim in the northern region of the Negev Desert, Israel. These detections provide confirmation that microwave subsurface remote sensing is a genuine phenomenon. At Ashalim, a scatterometer operating in the P-band (441 MHz, 68 cm) was mounted on a cherry picker truck at a height of 8 m and used to detect two triangular aluminum mesh reflectors (forming a 1-m square area reflector) buried down to a depth of 8 cm in dry sand. At Tseelim, the same scatterometer was mounted on an airplane flying at an altitude of 70 m and used to detect 1-m square aluminum reflectors (each one submerged at a different location along the airplane flight path) buried down to a depth of 20 cm. The experimental results compare favorably with a theoretical model that incorporates radar absorption effects arising in the sandy subsurface layer and radar interference effects arising from phase differences between reflections from the surface and buried reflector. The theoretical modeling also predicts the detection of a subsurface reflector down to a depth of about 4.4 m. This experiment and the associated modeling approach is the first of a series of planned experiments, which we outline for the detection and the theoretical evaluation of buried reflectors using remote microwave and VHF radar. We identify potential subject areas for environmental research.     

A method for the remote sensing identification of uncontrolled landfills: formulation and validation

The identification of uncontrolled landfills is a central environmental problem in all developed and developing countries, where several illegal waste deposits exist as a result of rapid industrial growth over the past century. Remote sensing can potentially provide crucial information for the identification of contaminated sites, but surprisingly there is a marked lack of rigorously validated approaches. In this paper we introduce and validate a method that uses remotely sensed information and a geographic information system (GIS) to identify unknown landfills over large areas. The method is applied to a study area located in NE Italy (part of the Venice lagoon watershed) using IKONOS satellite data. Soil contamination effects on the radiometric properties of vegetation, calibrated using spectral signatures of stressed vegetation from known illegal landfill sites, were used to define numerous candidate sites that are most likely to host waste materials. Distributed geographical information, such as the position of the road network, the population density, and historical aerial photographs, have then been used to select the most likely contaminated sites among the candidates identified through remote sensing. The importance of the integration of GIS and remote sensing is highlighted and represents a key instrument for environmental management and for the spatially distributed characterization of possible uncontrolled landfill sites.     

Autonomous hazardous waste drum inspection vehicle

Hundreds of thousands of hazardous, radioactive, and mixed waste drums are being stored throughout the world, and the anticipated decommissioning of facilities will generate many more drums. Currently, in compliance with federal regulations, waste storage facilities at U.S. Department of Energy (DOE) sites are inspected manually for degradation and to verify inventories. An Intelligent Mobile Sensing System (IMSS) has been developed for the automated inspection of radioactive and hazardous waste storage containers in warehouse facilities at DOE sites. The IMSS will reduce the risk of exposure to personnel and create accurate, high-quality inspection reports to ensure regulatory compliance. The IMSS includes an autonomous robotic device with enhanced intelligence and maneuverability, capable of conducting routine multisensor inspection of stored waste drums     

An intelligent decision support system for management of petroleum-contaminated sites

Groundwater and soil contamination resulted from LNAPLs (light nonaqueous phase liquids) spills and leakage in petroleum industry is currently one of the major environmental concerns in North America. Numerous site remediation technologies have been developed and implemented in the last two decades. They are classified as ex-situ and in-situ remediation techniques. One of the problems associated with ex-situ remediation is the cost of operation. In recent years, in-situ techniques have acquired popularity. However, the selection of the optimal techniques is difficult and insufficient expertise in the process may result in large inflation of expenses. This study presents an expert system (ES) for the management of petroleum contaminated sites in which a variety of artificial intelligence (AI) techniques were used to construct a support tool for site remediation decision-making. This paper presents the knowledge engineering processes of knowledge acquisition, conceptual design, and system implementation. The results from some case studies indicate that the expert system can generate cost-effective remediation alternatives to assist decision-makers.     

Microcomputer-aided design analysis of evaporating liquid waste from the Melton Valley Storage Tanks (MVSTS)

A microcomputer software package, SFWS (Software for Water Sparging) Version 1.10, has been developed to analyze the sparging of water from the Melton Valley Storage Tanks (MVSTs) located at Oak Ridge National Laboratory (ORNL). SFWS is a menu-driven, user-friendly software package and does not require any previous experience with computer operating systems. The main menu is divided into four submenus consisting of: (a) evaporation of MVSTs, using thermodynamics analysis, (b) evaporation of MVSTs, using heat- and mass-transfer analyses, (c) comparison of the accuracy of this software against the experimental setup at ORNL, and (d) exit. The analysis is carried out based on the mathematical modeling of bubble formation, velocity of rise, and the Nusselt and Sherwood correlation obtained and used for heat- and mass-transfer analysis of gas/liquid two-phase flow (Perry & Green, 1984). The software is developed for the IBM or IBM compatible personal computer and is written in the GW-BASIC language.     

多模态深度神经网络的固废对象分割

目的 对城市发展过程中产生的建筑固废进行处理,并将之转换为资源和能源,是极佳的保护环境的经济发展模式。然而人工分拣处理存在效率低、污染严重、对人身危害大等问题。目前工业界在探索一种有效的基于机械臂自动抓取的建筑固废自动分拣系统,其中图像分割技术是非常必要的一个环节。但是工业现场的环境因素造成固废对象的颜色严重退化,会影响最终的固废对象分割。本文针对建筑固废图像分割难度大的现状,提出一种基于多模态深度神经网络的方法来解决固废对象分割问题。方法 首先, 在颜色退化严重的场景下,把RGB图像和深度图一起作为深度卷积神经网络的输入,利用深度卷积神经网络进行高维特征学习,通过softmax分类器获得每个像素的标签分配概率。其次,基于新的能量函数建立全连接条件随机场,通过最小化能量函数寻找全局最优解来分割图像,从而为每一类固废对象产生一个独立的分割块。最后,利用局部轮廓信息计算深度梯度,实现同一类别的不同实例的固废对象精确分割。结果 在固废图像测试集上,该方法取得了90.02%均像素精度和89.03%均交并比（MIOU）。此外,与目前一些优秀的语义分割算法相比,也表现出了优越性。结论 本文方法能够对每一个固废对象同时进行有效的分割和分类,为建筑垃圾自动分拣系统提供准确的固废对象轮廓和类别信息,从而方便实现机械臂的自动抓取。     

High aspect-ratio combined poly and single-crystal silicon (HARPSS)MEMS technology

This paper presents a single-wafer high aspect-ratio micromachining technology capable of simultaneously producing tens to hundreds of micrometers thick electrically isolated poly and single-crystal silicon microstructures. High aspect-ratio polysilicon structures are created by refilling hundreds of micrometers deep trenches with polysilicon deposited over a sacrificial oxide layer. Thick single-crystal silicon structures are released from the substrate through the front side of the wafer by means of a combined directional and isotropic silicon dry etch and are protected on the sides by refilled trenches. This process is capable of producing electrically isolated polysilicon and silicon electrodes as tall as the main body structure with various size capacitive air gaps ranging from submicrometer to tens of micrometers. Using bent-beam strain sensors, residual stress in 80-μm-thick 4-μm-wide trench-refilled vertical polysilicon beams fabricated in this technology has been measured to be virtually zero. 300-μm-long 80-μm-thick polysilicon clamped-clamped beam micromechanical resonators have shown quality factors as high as 85 000 in vacuum. The all-silicon feature of this technology improves long-term stability and temperature sensitivity, while fabrication of large-area vertical pickoff electrodes with submicrometer gap spacing will increase the sensitivity of micro-electromechanical devices by orders of magnitude     

Plan-N-Scan: A Robotic System for Collision-Free Autonomous Exploration and Workspace Mapping

This paper presents a sensor-based robotic system, called Plan-N-Scan, for collision-free, autonomous exploration and workspace mapping, using a wrist-mounted laser range camera. This system involves gaze planning with collision-free sensor positioning in a static environment, resulting in a 3-D map suitable for real-time collision detection. This work was initially motivated by the great demand for autonomous exploration systems in the remediation of buried but leaking tanks containing hazardous nuclear waste. Plan-N-Scan uses two types of representations: a spherical model of the manipulator and a weighted voxel map of the workspace. In addition to providing efficient collision detection, the voxel map allows the incorporation of different types of spatial occupancy information. The mapping of unknown sections of the workspace is achieved by either target or volume scanning. Target scanning incorporates a powerful A*-based search, along with a viewing position selection strategy, to incrementally acquire scans of the scene and use them to capture targets, even if they are not immediately viewable by the range camera. Volume scanning is implemented as an iterative process which automatically selects scan targets, then employs the target scanning process to scan these targets and explore the selected workspace volume. The performance and reliability of the system was demonstrated through simulation and a number of experiments involving a real robot system. The ability of the Plan-N-Scan system to incrementally acquire range information and successfully scan both targets and workspace volumes was demonstrated.     

Numerical models for 2D free boundary analysis of groundwater in slopes stabilized by drain trenches

A numerical model for 2D free boundary analysis of groundwater in slopes stabilized by drain trenches has been developed. It consists of a front-tracking method (based on an original way of adapting the space derivatives), very effective in saving calculation time respect to classical fix-grid methods. The method analyses the trenches effect inside slopes in which the soils above the water table are partially saturated, for which a boundary can be recognized between the saturated domain (water table) and the unsaturated one (above the water table). In this case pore pressure lowering, due to trenches, can be analyzed considering the progressively reduction of the saturated domain. This approach efficiently solves the problem of fixing hydraulic boundary conditions on the sides of the trenches. Results have been compared with those obtained by a fix-grid method, observing difference less than 0.14%. Applying the method, the capability of drain trenches to control the effect of heavy rainfalls has been investigated, calculating (during the transient process of water table lowering) limit values of water recharge for which water table keeps on constant.     

BASSUM: A Bayesian semi-supervised method for classification feature selection

Feature selection is an important preprocessing step for building efficient, generalizable and interpretable classifiers on high dimensional data sets. Given the assumption on the sufficient labelled samples, the Markov Blanket provides a complete and sound solution to the selection of optimal features, by exploring the conditional independence relationships among the features. In real-world applications, unfortunately, it is usually easy to get unlabelled samples, but expensive to obtain the corresponding accurate labels on the samples. This leads to the potential waste of valuable classification information buried in unlabelled samples.In this paper, we propose a new BAyesian Semi-SUpervised Method, or BASSUM in short, to exploit the values of unlabelled samples on classification feature selection problem. Generally speaking, the inclusion of unlabelled samples helps the feature selection algorithm on (1) pinpointing more specific conditional independence tests involving fewer variable features and (2) improving the robustness of individual conditional independence tests with additional statistical information. Our experimental results show that BASSUM enhances the efficiency of traditional feature selection methods and overcomes the difficulties on redundant features in existing semi-supervised solutions.