The Application of Computational Chemistry and Chemometrics to Developing a Method for Online Monitoring of Polymer Degradation in the Manufacture of Bioresorbable Medical Implants

Bioresorbable polymers such as PLA have an important role to play in the development of temporary implantable medical devices with significant benefits over traditional therapies. However, development of new devices is hindered by high manufacturing costs associated with difficulties in processing the material. A major problem is the lack of insight on material degradation during processing. In this work, a method of quantifying degradation of PLA using IR spectroscopy coupled with computational chemistry and chemometric modeling is examined. It is shown that the method can predict the quantity of degradation products in solid-state samples with reasonably good accuracy, indicating the potential to adapt the method to developing an on-line sensor for monitoring PLA degradation in real-time during processing.

Variation in stable carbon isotope fractionation during aerobic degradation of phenol and benzoate by contaminant degrading bacteria

Variation in the natural abundance stable carbon isotope composition of respired CO2 and biomass has been measured for two types of aerobic bacteria found in contaminated land sites. Pseudomonas putida strain NCIMB 10015 was cultured on phenol and benzoate and Rhodococcus sp. I-1 was cultured on phenol. Results indicate that aerobic isotope fractionations of differing magnitudes occur during aerobic biodegradation of these substrates with an isotopic depletion in the CO2 (Delta(13)C(phenol-CO2)) as much as 3.7 parts per thousand and 5.6 parts per thousand for Pseudomonas putida and Rhodococcus sp. I-1 respectively. This observation has significant implications for the use of a stable isotope mass balance approach in monitoring degradation processes that rely on indigenous bacterial populations. The effects of the metabolic pathway utilised in degradation and inter-species variation on the magnitude of isotope fractionation are discussed. Possible explanations for the observed isotope fractionation include differences in the metabolic pathways utilised by the organisms and differences in specific growth rates and physiology. (C) 1999 Elsevier Science Ltd. All rights reserved.

Micro-Environmental monitoring of temperature and moisture changes in building stone

The monitoring of temperature and moisture changes in response to different micro-environment of building stones is essential to understand the material behaviour and the degradation mechanisms. From a practical point of view, having a continuous and detailed understanding of micro-environmental changes in building stones helps to assist in their maintenance and repair strategies. Temperature within the stone is usually monitored by means of thermistors, whereas wide ranges of techniques are available for monitoring the moisture. In the case of concrete an electrical resistance method has previously been used as an inexpensive tool for monitoring moisture changes. This paper describes the adaptation of this technique and describes its further development for monitoring moisture movement in building stones.
In this study a block of limestone was subjected to intermittent infrared radiation with programmed cycles of ambient temperature, rainfall and wind conditions in an automated climatic chamber. The temperature and moisture changes at different depths within the stone were monitored by means of bead thermistors and electrical resistance sensors. This experiment has helped to understand the thermal conductivity and moisture transport from surface into deeper parts of the stone at different simulated extreme climatic conditions. Results indicated that variations in external ambient conditions could substantially affect the moisture transport and temperature profile within the micro-environment of building stones and hence they could have a significant impact on stone decay.

In-situ Monitoring of Solid Oxide Electrolysis Cells

High temperature co-electrolysis of steam and carbon dioxide using a solid oxide cell (SOC) has been shown to be an efficient route to produce syngas (CO + H-2), which can then be converted to synthetic fuel. Optimization of co-electrolysis requires detailed understanding of the complex reactions, transport processes and degradation mechanisms occurring in the SOC during operation. Thermal imaging, Raman spectroscopy and Diffuse Reflectance Infrared Fourier Transform Spectroscopy are being developed to probe in-situ both the reactions occurring during operation and any associated changes within the structure of the electrodes and electrolyte. Here we discuss the challenges in designing experimental apparatus suitable for high temperature operation with optical spectroscopic access to the areas of the SOC that are of interest. In particular, issues with sealing, temperature gradients, signal strength and cell configuration are discussed and final designs are presented. Preliminary results obtained during co-electrolysis operation are also presented.

Monitoring Bridge Dynamic Behaviour using an Instrumented Two Axle Vehicle

Highway structures such as bridges are subject to continuous degradation primarily due to ageing, loading and environmental factors. A rational transport policy must monitor and provide adequate maintenance to this infrastructure to guarantee the required levels of transport service and safety. Increasingly in recent years, bridges are being instrumented and monitored on an ongoing basis due to the implementation of Bridge Management Systems. This is very effective and provides a high level of protection to the public and early warning if the bridge becomes unsafe. However, the process can be expensive and time consuming, requiring the installation of sensors and data acquisition electronics on the bridge. This paper investigates the use of an instrumented 2-axle vehicle fitted with accelerometers to monitor the dynamic behaviour of a bridge network in a simple and cost-effective manner. A simplified half car-beam interaction model is used to simulate the passage of a vehicle over a bridge. This investigation involves the frequency domain analysis of the axle accelerations as the vehicle crosses the bridge. The spectrum of the acceleration record contains noise, vehicle, bridge and road frequency components. Therefore, the bridge dynamic behaviour is monitored in simulations for both smooth and rough road surfaces. The vehicle mass and axle spacing are varied in simulations along with bridge structural damping in order to analyse the sensitivity of the vehicle accelerations to a change in bridge properties. These vehicle accelerations can be obtained for different periods of time and serve as a useful tool to monitor the variation of bridge frequency and damping with time.

Multivariate analysis of regional-scale geochemical data for environmental monitoring

A compositional multivariate approach is used to analyse regional scale soil geochemical data obtained as part of the Tellus Project generated by the Geological Survey Northern Ireland (GSNI). The multi-element total concentration data presented comprise XRF analyses of 6862 rural soil samples collected at 20cm depths on a non-aligned grid at one site per 2 km2. Censored data were imputed using published detection limits. Using these imputed values for 46 elements (including LOI), each soil sample site was assigned to the regional geology map provided by GSNI initially using the dominant lithology for the map polygon. Northern Ireland includes a diversity of geology representing a stratigraphic record from the Mesoproterozoic, up to and including the Palaeogene. However, the advance of ice sheets and their meltwaters over the last 100,000 years has left at least 80% of the bedrock covered by superficial deposits, including glacial till and post-glacial alluvium and peat. The question is to what extent the soil geochemistry reflects the underlying geology or superficial deposits. To address this, the geochemical data were transformed using centered log ratios (clr) to observe the requirements of compositional data analysis and avoid closure issues. Following this, compositional multivariate techniques including compositional Principal Component Analysis (PCA) and minimum/maximum autocorrelation factor (MAF) analysis method were used to determine the influence of underlying geology on the soil geochemistry signature. PCA showed that 72% of the variation was determined by the first four principal components (PC’s) implying “significant” structure in the data. Analysis of variance showed that only 10 PC’s were necessary to classify the soil geochemical data. To consider an improvement over PCA that uses the spatial relationships of the data, a classification based on MAF analysis was undertaken using the first 6 dominant factors. Understanding the relationship between soil geochemistry and superficial deposits is important for environmental monitoring of fragile ecosystems such as peat. To explore whether peat cover could be predicted from the classification, the lithology designation was adapted to include the presence of peat, based on GSNI superficial deposit polygons and linear discriminant analysis (LDA) undertaken. Prediction accuracy for LDA classification improved from 60.98% based on PCA using 10 principal components to 64.73% using MAF based on the 6 most dominant factors. The misclassification of peat may reflect degradation of peat covered areas since the creation of superficial deposit classification. Further work will examine the influence of underlying lithologies on elemental concentrations in peat composition and the effect of this in classification analysis.