Design and coupled-effect simulations of CMOS micro gas-sensors built on SOI thin membranes

This paper describes coupled-effect simulations of smart micro gas-sensors based on standard BiCMOS technology. The smart sensor features very low power consumption, high sensitivity and potential low fabrication cost achieved through full CMOS integration. For the first time the micro heaters are made of active CMOS elements (i.e. MOSFET transistors) and embedded in a thin SOI membrane consisting of Si and SiO2 thin layers. Micro gas-sensors such as chemoresistive, microcalorimeteric and Pd/polymer gate FET sensors can be made using this technology. Full numerical analyses including 3D electro-thermo-mechanical simulations, in particular stress and deflection studies on the SOI membranes are presented. The transducer circuit design and the post-CMOS fabrication process, which includes single sided back-etching, are also reported.

Design and simulations of SOI CMOS micro-hotplate gas sensors

This paper describes a new generation of integrated solid-state gas-sensors embedded in SOI micro-hotplates. The micro-hotplates lie on a SOI membrane and consist of MOSFET heaters that elevate the operating temperature, through self-heating, of a gas sensitive material. These sensors are fully compatible with SOI CMOS or BiCMOS technologies, offer ultra-low power consumption (under 100 mW), high sensitivity, low noise, low unit cost, reproducibility and reliability through the use of on-chip integration. In addition, the new integrated sensors offer a nearly uniform temperature distribution over the active area at its operating temperatures at up to about 300-350°C. This makes SOI-based gas-sensing devices particularly attractive for use in handheld battery-operated gas monitors. This paper reports on the design of a chemo-resistive gas sensor and proposes for the first time an intelligent SOI membrane microcalorimeter using active micro-FET heaters and temperature sensors. A comprehensive set of numerical and analogue simulations is also presented including complex 2D and 3D electro-thermal numerical analyses. © 2001 Elsevier Science B.V. All rights reserved.

Using strong sustainability to optimize electricity generation fuel mixes

This work represents a contribution to the field of sustainable electricity system design by using an optimization tool to specify the final mix composition, subject to the constraints of: emissions that are within the biocapacity of the region; a diverse and robust electricity supply system; and supply that at least meets current demand. The 25-country European Union (EU-25) is used as a case study. All the goals, save diversity, can be met by re-structuring the current fuel mix, thus maintaining current consumption levels. The diversity target is only met when consumption is reduced by 10-15% and the constraint on maximum material throughput is relaxed. Re-structuring the mix and reducing consumption is insufficient to achieve a sustainable EU carbon footprint. However, the solution proposed singlehandedly allows the EU to meet its Kyoto emissions target as well as its 2007 policy of a reduction of 20% in greenhouse gas emissions by 2020. © 2007 Elsevier Ltd. All rights reserved.

Linking energy policy, electricity generation and transmission using strong sustainability and co-optimization

The design of a sustainable electricity generation and transmission system is based on the established science of anthropogenic climate change and the realization that depending on imported fossil-fuels is becoming a measure of energy insecurity of supply. A model is proposed which integrates generation fuel mix composition, assignment of plants and optimized power flow, using Portugal as a case study. The result of this co-optimized approach is an overall set of generator types/fuels which increases the diversity of Portuguese electricity supply, lowers its dependency on imported fuels by 14.62% and moves the country towards meeting its regional and international obligations of 31% energy from renewables by 2020 and a 27% reduction in greenhouse gas emissions by 2012, respectively. The quantity and composition of power generation at each bus is specified, with particular focus on quantifying the amount of distributed generation. Based on other works, the resultant, overall distributed capacity penetration of 19.02% of total installed generation is expected to yield positive network benefits. Thus, the model demonstrates that national energy policy and technical deployment can be linked through sustainability and, moreover, that the respective goals may be mutually achieved via holistic, integrated design. ©2009 IEEE.

Implications of local lifecycle analyses and low carbon fuel standard design on gasohol transportation fuels

State and regional policies, such as low carbon fuel standards (LCFSs), increasingly mandate that transportation fuels be examined according to their greenhouse gas (GHG) emissions. We investigate whether such policies benefit from determining fuel carbon intensities (FCIs) locally to account for variations in fuel production and to stimulate improvements in FCI. In this study, we examine the FCI of transportation fuels on a lifecycle basis within a specific state, Minnesota, and compare the results to FCIs using national averages. Using data compiled from 18 refineries over an 11-year period, we find that ethanol production is highly variable, resulting in a 42% difference between carbon intensities. Historical data suggests that lower FCIs are possible through incremental improvements in refining efficiency and the use of biomass for processing heat. Stochastic modeling of the corn ethanol FCI shows that gains in certainty due to knowledge of specific refinery inputs are overwhelmed by uncertainty in parameters external to the refiner, including impacts of fertilization and land use change. The LCA results are incorporated into multiple policy scenarios to demonstrate the effect of policy configurations on the use of alternative fuels. These results provide a contrast between volumetric mandates and LCFSs. © 2011 Elsevier Ltd.

Phrase-based statistical language generation using graphical models and active learning

Most previous work on trainable language generation has focused on two paradigms: (a) using a statistical model to rank a set of generated utterances, or (b) using statistics to inform the generation decision process. Both approaches rely on the existence of a handcrafted generator, which limits their scalability to new domains. This paper presents BAGEL, a statistical language generator which uses dynamic Bayesian networks to learn from semantically-aligned data produced by 42 untrained annotators. A human evaluation shows that BAGEL can generate natural and informative utterances from unseen inputs in the information presentation domain. Additionally, generation performance on sparse datasets is improved significantly by using certainty-based active learning, yielding ratings close to the human gold standard with a fraction of the data. © 2010 Association for Computational Linguistics.

Embodied energy and gas emission of geotechnical infrastructure

Construction of geotechnical structures produces various environmental impacts. These include depletion of limited natural resources, generation of wastes and harmful substances during material productions and construction, ineffective usage of energy during processing of raw materials into construction materials, and emissions of unwanted gasses during transportation of materials and usage of equipments. With increasing interests in sustainability at the global scale, there is a need to develop a methodology that can assess environmental impacts at such scale for geotechnical construction. Using embodied energy and gas emission, quantitative measures of environmental impact are evaluated using a case study of a new high speed railway line construction in the UK. Based on the results, the keys to energy savings are (a) to optimise the usage of materials with high embodied energy intensity value (b) to optimise the transportation network and logistics for processes using primarily low embodied energy intensity materials and (c) to reuse as much materials on-site as possible to minimise the quantity of spoils or distance to disposal sites. The evaluated embodied energy and embodied carbon values are compared to those of other types of structures and of other activities and carbon tax values. Such comparisons can be used to discuss among various interested parties (clients, contractors, consultants, policy makers, etc) to make the construction industry more energy efficient. © Springer Science+Business Media B.V. 2011.

Effects of ethanol on vehicle energy efficiency and implications on ethanol life-cycle greenhouse gas analysis.

Bioethanol is the world's largest-produced alternative to petroleum-derived transportation fuels due to its compatibility within existing spark-ignition engines and its relatively mature production technology. Despite its success, questions remain over the greenhouse gas (GHG) implications of fuel ethanol use with many studies showing significant impacts of differences in land use, feedstock, and refinery operation. While most efforts to quantify life-cycle GHG impacts have focused on the production stage, a few recent studies have acknowledged the effect of ethanol on engine performance and incorporated these effects into the fuel life cycle. These studies have broadly asserted that vehicle efficiency increases with ethanol use to justify reducing the GHG impact of ethanol. These results seem to conflict with the general notion that ethanol decreases the fuel efficiency (or increases the fuel consumption) of vehicles due to the lower volumetric energy content of ethanol when compared to gasoline. Here we argue that due to the increased emphasis on alternative fuels with drastically differing energy densities, vehicle efficiency should be evaluated based on energy rather than volume. When done so, we show that efficiency of existing vehicles can be affected by ethanol content, but these impacts can serve to have both positive and negative effects and are highly uncertain (ranging from -15% to +24%). As a result, uncertainties in the net GHG effect of ethanol, particularly when used in a low-level blend with gasoline, are considerably larger than previously estimated (standard deviations increase by >10% and >200% when used in high and low blends, respectively). Technical options exist to improve vehicle efficiency through smarter use of ethanol though changes to the vehicle fleets and fuel infrastructure would be required. Future biofuel policies should promote synergies between the vehicle and fuel industries in order to maximize the society-wise benefits or minimize the risks of adverse impacts of ethanol.

PCB-integrated optical waveguide sensors: An ammonia gas sensor

This paper presents a novel platform for the formation of cost-effective PCB-integrated optical waveguide sensors. The sensor design relies on the use of multimode polymer waveguides that can be formed directly on standard PCBs and commercially-available chemical dyes, enabling the integration of all essential sensor components (electronic, photonic, chemical) on low-cost substrates. Moreover, it enables the detection of multiple analytes from a single device by employing waveguide arrays functionalised with different chemical dyes. The devices can be manufactured with conventional methods of the PCB industry, such as solder-reflow processes and pick-and-place assembly techniques. As a proof of principle, a PCB-integrated ammonia gas sensor is fabricated on a FR4 substrate. The sensor operation relies on the change of the optical transmission characteristics of chemically functionalised optical waveguides in the presence of ammonia molecules. The fabrication and assembly of the sensor unit, as well as fundamental simulation and characterisation studies, are presented. The device achieves a sensitivity of approximately 30 ppm and a linear response up to 600 ppm at room temperature. Finally, the potential to detect multiple analytes from a single device is demonstrated using principal-component analysis. © 1983-2012 IEEE.

Fast response CO2 sensor for automotive exhaust gas analysis

A fast response sensor for measuring carbon dioxide concentration has been developed for laboratory research and tested on a spark ignition engine. The sensor uses the well known infra-red absorption technique with a miniaturized detection system and short capillary sampling tubes, giving a time constant of approximately 5 milliseconds; this is sufficiently fast to observe changes in CO2 levels on a cycle-by-cycle basis under normal operating conditions. The sensor is easily located in the exhaust system and operates continuously. The sensor was tested on a standard production four cylinder spark-ignition engine to observe changes in CO2 concentration in exhaust gas under steady state and transient operating conditions. The processed sensor signal was compared to a standard air-to-fuel ratio (AFR) sensor in the exhaust stream and the results are presented here. The high frequency response CO2 measurements give new insights into both engine and catalyst transient operation. Copyright © 1999 Society of Automotive Engineers, Inc.