Nanostructuring of materials for device and sensor applications

The recent developments in nanotechnology are reviewed, with particular emphasis on its application in microsystem technology where increased reliability is achieved by integrating the sensor and the readout electronics on the same substrate. New applications may be possible using integrated micromechanical clips to connect optic fibers and components in integrated silicon systems. Some of the key developments in enabling technologies are also described, including the control of thin film deposition, nanostructuring to tailor the properties of thin film, silicon micromachining to make sensors, and microclips for the low-cost assembly of integrated optical microsystems.

Selection of materials for marine instruments

The paper describes the selection of materials for the reliable operation of oceanographic instruments. For selecting the material, raft immersion tests were carried out for one year. Results of the tests are presented. Comparisons between metals were discussed.

Encyclopedia of materials

... Damping of Acoustic Waves: High Damping Alloys and Inorganic Noise Absorbing Materials Machinery noise and vibration reduction can be achieved by using ...

Identification of Materials from Construction Site Images Using Content Based Image Retrieval Techniques

The capability to automatically identify shapes, objects and materials from the image content through direct and indirect methodologies has enabled the development of several civil engineering related applications that assist in the design, construction and maintenance of construction projects. Examples include surface cracks detection, assessment of fire-damaged mortar, fatigue evaluation of asphalt mixes, aggregate shape measurements, velocimentry, vehicles detection, pore size distribution in geotextiles, damage detection and others. This capability is a product of the technological breakthroughs in the area of Image and Video Processing that has allowed for the development of a large number of digital imaging applications in all industries ranging from the well established medical diagnostic tools (magnetic resonance imaging, spectroscopy and nuclear medical imaging) to image searching mechanisms (image matching, content based image retrieval). Content based image retrieval techniques can also assist in the automated recognition of materials in construction site images and thus enable the development of reliable methods for image classification and retrieval. The amount of original imaging information produced yearly in the construction industry during the last decade has experienced a tremendous growth. Digital cameras and image databases are gradually replacing traditional photography while owners demand complete site photograph logs and engineers store thousands of images for each project to use in a number of construction management tasks. However, construction companies tend to store images without following any standardized indexing protocols, thus making the manual searching and retrieval a tedious and time-consuming effort. Alternatively, material and object identification techniques can be used for the development of automated, content based, construction site image retrieval methodology. These methods can utilize automatic material or object based indexing to remove the user from the time-consuming and tedious manual classification process. In this paper, a novel material identification methodology is presented. This method utilizes content based image retrieval concepts to match known material samples with material clusters within the image content. The results demonstrate the suitability of this methodology for construction site image retrieval purposes and reveal the capability of existing image processing technologies to accurately identify a wealth of materials from construction site images.

Doping during low-temperature growth of materials for n-p-n Si/SiGe/Si heterojuction bipolar transistor by gas source molecular beam epitaxy

In situ doping for growth of n-p-n Si/SiGe/Si heterojuction bipolar transistor (HBT) structural materials in Si gas source molecular beam epitaxy is investigated. We studied high n-type doping kinetics in Si growth using disilane and phosphine, and p-type doping in SiGe growth using disilane, soild-Ge, and diborane with an emphasis on the effect of Ge on B incorporation. Based on these results, in situ growth of n-p-n Si/SiGe/Si HBT device structure is demonstrated with designed structural and carrier profiles, as verified from characterizations by X-ray diffraction, and spreading resistance profiling analysis. (C) 2000 Elsevier Science B.V. All rights reserved.

Development of a triple stage heat transformer for the recycling of low temperature heat energy

Absorption heat transformers are thermodynamic systems which are capable of recycling industrial waste heat energy by increasing its temperature. Triple stage heat transformers (TAHTs) can increase the temperature of this waste heat by up to approximately 145˚C. The principle factors influencing the thermodynamic performance of a TAHT and general points of operating optima were identified using a multivariate statistical analysis, prior to using heat exchange network modelling techniques to dissect the design of the TAHT and systematically reassemble it in order to minimise internal exergy destruction within the unit. This enabled first and second law efficiency improvements of up to 18.8% and 31.5% respectively to be achieved compared to conventional TAHT designs. The economic feasibility of such a thermodynamically optimised cycle was investigated by applying it to an oil refinery in Ireland, demonstrating that in general the capital cost of a TAHT makes it difficult to achieve acceptable rates of return. Decreasing the TAHT's capital cost may be achieved by redesigning its individual pieces of equipment and reducing their size. The potential benefits of using a bubble column absorber were therefore investigated in this thesis. An experimental bubble column was constructed and used to track the collapse of steam bubbles being absorbed into a hotter lithium bromide salt solution. Extremely high mass transfer coefficients of approximately 0.0012m/s were observed, showing significant improvements over previously investigated absorbers. Two separate models were developed, namely a combined heat and mass transfer model describing the rate of collapse of the bubbles, and a stochastic model describing the hydrodynamic motion of the collapsing vapour bubbles taking into consideration random fluctuations observed in the experimental data. Both models showed good agreement with the collected data, and demonstrated that the difference between the solution's temperature and its boiling temperature is the primary factor influencing the absorber's performance.

Modeling non-harmonic behavior of materials from experimental inelastic neutron scattering and thermal expansion measurements

Based on thermodynamic principles, we derive expressions quantifying the non-harmonic vibrational behavior of materials, which are rigorous yet easily evaluated from experimentally available data for the thermal expansion coefficient and the phonon density of states. These experimentally- derived quantities are valuable to benchmark first-principles theoretical predictions of harmonic and non-harmonic thermal behaviors using perturbation theory, ab initio molecular-dynamics, or Monte-Carlo simulations. We illustrate this analysis by computing the harmonic, dilational, and anharmonic contributions to the entropy, internal energy, and free energy of elemental aluminum and the ordered compound FeSi over a wide range of temperature. Results agree well with previous data in the literature and provide an efficient approach to estimate anharmonic effects in materials.

Computational issues in the modelling of materials-based manufacturing processes

The manufacture of materials products involves the control of a range of interacting physical phenomena. The material to be used is synthesised and then manipulated into some component form. The structure and properties of the final component are influenced by both interactions of continuum-scale phenomena and those at an atomistic-scale level. Moreover, during the processing phase there are some properties that cannot be measured (typically the liquid-solid phase change). However, it seems there is a potential to derive properties and other features from atomistic-scale simulations that are of key importance at the continuum scale. Some of the issues that need to be resolved in this context focus upon computational techniques and software tools facilitating: (i) the multiphysics modeling at continuum scale; (ii) the interaction and appropriate degrees of coupling between the atomistic through microstructure to continuum scale; and (iii) the exploitation of high-performance parallel computing power delivering simulation results in a practical time period. This paper discusses some of the attempts to address each of the above issues, particularly in the context of materials processing for manufacture.

Numerical modelling for electromagnetic processing of materials

Electromagnetic processing of materials (EPM) is one of the most widely practiced and fast growing applications of magnetic and electric forces to fluid flow. EPM is encountered in both industrial processes and laboratory investigations. Applications range in scale from nano-particle manipulation to tonnes of liquid metal treated in the presence of various configurations of magnetic fields. Some of these processes are specifically designed and made possible by the use of the electromagnetic force, like the magnetic levitation of liquid droplets, whilst others involve electric currents essential for electrothermal or electrochemical reasons, for instance, in electrolytic metal production and in induction melting. An insight for the range of established and novel EPM applications can be found in the review presented by Asai [1] in the EPM-2003 conference proceedings.