Effect of solder volume on joint shape with variable chip-to-board contact pad ratio

The objective of this paper is to investigate the effect of the pad size ratio between the chip and board end of a solder joint on the shape of that solder joint in combination with the solder volume available. The shape of the solder joint is correlated to its reliability and thus of importance. For low density chip bond pad applications Flip Chip (FC) manufacturing costs can be kept down by using larger size board pads suitable for solder application. By using “Surface Evolver” software package the solder joint shapes associated with different size/shape solder preforms and chip/board pad ratios are predicted. In this case a so called Flip-Chip Over Hole (FCOH) assembly format has been used. Assembly trials involved the deposition of lead-free 99.3Sn0.7Cu solder on the board side, followed by reflow, an underfill process and back die encapsulation. During the assembly work pad off-sets occurred that have been taken into account for the Surface Evolver solder joint shape prediction and accurately matched the real assembly. Overall, good correlation was found between the simulated solder joint shape and the actual fabricated solder joint shapes. Solder preforms were found to exhibit better control over the solder volume. Reflow simulation of commercially available solder preform volumes suggests that for a fixed stand-off height and chip-board pad ratio, the solder volume value and the surface tension determines the shape of the joint.

Comparison of deterministic, stochastic and fuzzy logic uncertainty modelling for capacity extension projects of DI/WFI pharmaceutical plant utilities with variable/dynamic demand

The last 30 years have seen Fuzzy Logic (FL) emerging as a method either complementing or challenging stochastic methods as the traditional method of modelling uncertainty. But the circumstances under which FL or stochastic methods should be used are shrouded in disagreement, because the areas of application of statistical and FL methods are overlapping with differences in opinion as to when which method should be used. Lacking are practically relevant case studies comparing these two methods. This work compares stochastic and FL methods for the assessment of spare capacity on the example of pharmaceutical high purity water (HPW) utility systems. The goal of this study was to find the most appropriate method modelling uncertainty in industrial scale HPW systems. The results provide evidence which suggests that stochastic methods are superior to the methods of FL in simulating uncertainty in chemical plant utilities including HPW systems in typical cases whereby extreme events, for example peaks in demand, or day-to-day variation rather than average values are of interest. The average production output or other statistical measures may, for instance, be of interest in the assessment of workshops. Furthermore the results indicate that the stochastic model should be used only if found necessary by a deterministic simulation. Consequently, this thesis concludes that either deterministic or stochastic methods should be used to simulate uncertainty in chemical plant utility systems and by extension some process system because extreme events or the modelling of day-to-day variation are important in capacity extension projects. Other reasons supporting the suggestion that stochastic HPW models are preferred to FL HPW models include: 1. The computer code for stochastic models is typically less complex than a FL models, thus reducing code maintenance and validation issues. 2. In many respects FL models are similar to deterministic models. Thus the need for a FL model over a deterministic model is questionable in the case of industrial scale HPW systems as presented here (as well as other similar systems) since the latter requires simpler models. 3. A FL model may be difficult to "sell" to an end-user as its results represent "approximate reasoning" a definition of which is, however, lacking. 4. Stochastic models may be applied with some relatively minor modifications on other systems, whereas FL models may not. For instance, the stochastic HPW system could be used to model municipal drinking water systems, whereas the FL HPW model should or could not be used on such systems. This is because the FL and stochastic model philosophies of a HPW system are fundamentally different. The stochastic model sees schedule and volume uncertainties as random phenomena described by statistical distributions based on either estimated or historical data. The FL model, on the other hand, simulates schedule uncertainties based on estimated operator behaviour e.g. tiredness of the operators and their working schedule. But in a municipal drinking water distribution system the notion of "operator" breaks down. 5. Stochastic methods can account for uncertainties that are difficult to model with FL. The FL HPW system model does not account for dispensed volume uncertainty, as there appears to be no reasonable method to account for it with FL whereas the stochastic model includes volume uncertainty.

Nanostructured ferroelectric materials

Nanostructured materials are central to the evolution of future electronics and information technologies. Ferroelectrics have already been established as a dominant branch in the electronics sector because of their diverse application range such as ferroelectric memories, ferroelectric tunnel junctions, etc. The on-going dimensional downscaling of materials to allow packing of increased numbers of components onto integrated circuits provides the momentum for the evolution of nanostructured ferroelectric materials and devices. Nanoscaling of ferroelectric materials can result in a modification of their functionality, such as phase transition temperature or Curie temperature (TC), domain dynamics, dielectric constant, coercive field, spontaneous polarisation and piezoelectric response. Furthermore, nanoscaling can be used to form high density arrays of monodomain ferroelectric nanostructures, which is desirable for the miniaturisation of memory devices. This thesis details the use of various types of nanostructuring approaches to fabricate arrays of ferroelectric nanostructures, particularly non-oxide based systems. The introductory chapter reviews some exemplary research breakthroughs in the synthesis, characterisation and applications of nanoscale ferroelectric materials over the last decade, with priority given to novel synthetic strategies. Chapter 2 provides an overview of the experimental methods and characterisation tools used to produce and probe the properties of nanostructured antimony sulphide (Sb2S3), antimony sulpho iodide (SbSI) and lead titanate zirconate (PZT). In particular, Chapter 2 details the general principles of piezoresponse microscopy (PFM). Chapter 3 highlights the fabrication of arrays of Sb2S3 nanowires with variable diameters using newly developed solventless template-based approach. A detailed account of domain imaging and polarisation switching of these nanowire arrays is also provided. Chapter 4 details the preparation of vertically aligned arrays of SbSI nanorods and nanowires using a surface-roughness assisted vapour-phase deposition method. The qualitative and quantitative nanoscale ferroelectric properties of these nanostructures are also discussed. Chapter 5 highlights the fabrication of highly ordered arrays of PZT nanodots using block copolymer self-assembled templates and their ferroelectric characterisation using PFM. Chapter 6 summarises the conclusions drawn from the results reported in chapters 3, 4 and 5 and the future work.

A knowledge management system to optimise comfort throughout the building life-cycle

Comfort is, in essence, satisfaction with the environment, and with respect to the indoor environment it is primarily satisfaction with the thermal conditions and air quality. Improving comfort has social, health and economic benefits, and is more financially significant than any other building cost. Despite this, comfort is not strictly managed throughout the building lifecycle. This is mainly due to the lack of an appropriate system to adequately manage comfort knowledge through the construction process into operation. Previous proposals to improve knowledge management have not been successfully adopted by the construction industry. To address this, the BabySteps approach was devised. BabySteps is an approach, proposed by this research, which states that for an innovation to be adopted into the industry it must be implementable through a number of small changes. This research proposes that improving the management of comfort knowledge will improve comfort. ComMet is a new methodology proposed by this research that manages comfort knowledge. It enables comfort knowledge to be captured, stored and accessed throughout the building life-cycle and so allowing it to be re-used in future stages of the building project and in future projects. It does this using the following: Comfort Performances – These are simplified numerical representations of the comfort of the indoor environment. Comfort Performances quantify the comfort at each stage of the building life-cycle using standard comfort metrics. Comfort Ratings - These are a means of classifying the comfort conditions of the indoor environment according to an appropriate standard. Comfort Ratings are generated by comparing different Comfort Performances. Comfort Ratings provide additional information relating to the comfort conditions of the indoor environment, which is not readily determined from the individual Comfort Performances. Comfort History – This is a continuous descriptive record of the comfort throughout the project, with a focus on documenting the items and activities, proposed and implemented, which could potentially affect comfort. Each aspect of the Comfort History is linked to the relevant comfort entity it references. These three components create a comprehensive record of the comfort throughout the building lifecycle. They are then stored and made available in a common format in a central location which allows them to be re-used ad infinitum. The LCMS System was developed to implement the ComMet methodology. It uses current and emerging technologies to capture, store and allow easy access to comfort knowledge as specified by ComMet. LCMS is an IT system that is a combination of the following six components: Building Standards; Modelling & Simulation; Physical Measurement through the specially developed Egg-Whisk (Wireless Sensor) Network; Data Manipulation; Information Recording; Knowledge Storage and Access.Results from a test case application of the LCMS system - an existing office room at a research facility - highlighted that while some aspects of comfort were being maintained, the building’s environment was not in compliance with the acceptable levels as stipulated by the relevant building standards. The implementation of ComMet, through LCMS, demonstrates how comfort, typically only considered during early design, can be measured and managed appropriately through systematic application of the methodology as means of ensuring a healthy internal environment in the building.

The effect of positive psychological interventions on psychological and physical well-being during pregnancy

Prenatal well-being can have significant effects on the mother and developing foetus. Positive psychological interventions, including gratitude and mindfulness, consistently demonstrate benefits for well-being in diverse populations. No research has been conducted on gratitude during pregnancy; the few studies of prenatal mindfulness interventions have demonstrated well-being benefits. The current study examined the effects of gratitude and mindfulness interventions on prenatal maternal well-being, cortisol and birth outcomes. Five studies were conducted. Study 1 was a systematic review of mindfulness intervention effects on cortisol; this highlighted potential benefits of mindfulness but the need for rigorous protocols in future research. In Study 2 a gratitude and a mindfulness intervention were developed and evaluated; findings indicate usefulness of two 3 week interventions. Study 3 examined the effects of these interventions in a randomised controlled trial (RCT) of non-pregnant women, before examining a pregnant group. No significant intervention effects were found in this study, potentially due to insufficient power and poor protocol adherence. Changes in expected directions were observed for most outcomes and the potential utility of a combined gratitude and mindfulness intervention was noted. In Study 4 a gratitude during pregnancy (GDP) scale was developed and the reliability of an existing mindfulness measure (MAAS) was examined in a pregnant group. Both scales were found to be suitable and reliable measures in pregnancy. Study 5 incorporated the findings of the previous four studies to examine of the effect of a combined mindfulness and gratitude intervention with a group of pregnant women. Forty-six participants took part in a 5-week RCT that examined intervention effects on prenatal gratitude, mindfulness, happiness, satisfaction with life, social support, prenatal stress, depression and sleep. Findings indicated that the intervention improved sleep quality and that effects for prenatal distress were approaching significance. Issues of attrition and non-compliance to study protocols were problematic and are discussed. In summary, the current thesis highlights the need for robust measurement, and intervention and cortisol sampling protocols in future research, particularly with pregnant groups. Findings also demonstrate tentative benefits of a gratitude and mindfulness intervention during pregnancy.