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.

Electron shell contributions to gamma-ray spectra of positron annihilation in noble gases

Gamma-ray positron annihilation spectra of the noble gases are simulated using computational chemistry tools for the bound electron wavefunctions and plane-wave approximation for the low-energy positron. The present annihilation line shapes, i.e. the full width at half maximum, Delta epsilon, of the gamma-ray annihilation spectra for He and Ar (valence) agree well with available independent atomic calculations using a different algorithm. For other noble gases they achieve moderate agreement with the experimental measurements. It is found that the contributions of various atomic electron shells to the spectra depend significantly on their principal quantum number n and orbital angular momentum quantum number l. The present study further reveals that the outermost ns electrons of the noble gases exhibit spectral line shapes in close agreement with those measured, indicating (as expected) that the measurements are not due to a simple sum over the momentum densities for all atomic electrons. The robust nature of the present approach makes it possible for us to proceed to more complex molecular systems using the tools of modern computational chemistry.

The structural information content of chemical networks

We present an information-theoretic method to measure the structural information content of networks and apply it to chemical graphs. As a result, we find that our entropy measure is more general than classical information indices known in mathematical and computational chemistry. Further, we demonstrate that our measure reflects the essence of molecular branching meaningfully by determining the structural information content of some chemical graphs numerically.

Electronic states and spin-forbidden cooling transitions of AlH and AlF

The feasibility of laser cooling AlH and AlF is investigated using ab initio quantum chemistry. All the electronic states corresponding to the ground and lowest two excited states of the Al atom are calculated using multi-reference configuration interaction (MRCI) and the large AV6Z basis set for AlH. The smaller AVQZ basis set is used to calculate the valence electronic states of AlF. Theoretical Franck-Condon factors are determined for the A(1)Pi -> X(1)Sigma(+) transitions in both radicals and found to agree with the highly diagonal factors found experimentally, suggesting computational chemistry is an effective method for screening suitable laser cooling candidates. AlH does not appear to have a transition quite as diagonal as that in SrF (which has been laser cooled) but the A(1)Pi -> X(1)Sigma(+) transition transition of AlF is a strong candidate for cooling with just a single laser, though the cooling frequency is deep in the UV. Furthermore, the a (3)Pi -> X(1)Sigma(+) transitions are also strongly diagonal and in AlF is a practical method for obtaining very low final temperatures around 3 mu K.

STO and GTO field-induced polarization functions for H to Kr

Field-induced polarization (FIP) functions were proposed over two decades ago to improve the accuracy of calculated response properties, and the FIP functions in GTO form for H and C to F were tested on small molecules, with encouraging results. The concept of FIP,is now extended to all atoms up to Kr. New simplifying approximations for the description of asymptotic highest occupied atomic orbitals. (HOAOs) are introduced in this study. They provide the basis for STO and GTO exponents of a complete set of FIP functions from H to Kr, which are both listed for the convenience of the users. Tests on the polarizabilities of a series of atoms and molecules demonstrate that addition of the FIP basis functions to a series' of standard basis sets drastically improves the performance of all these basis sets compared to converged results. Moreover, the byproduct of this study (approximate asymptotic HOAOs) provides information for the construction of accurate basis sets for long-range ground state properties. (C) 2003 Wiley Periodicals, Inc.

Molecular Computational Elements Encode Large Populations of Small Objects

Since the introduction of molecular computation1, 2, experimental molecular computational elements have grown3, 4, 5 to encompass small-scale integration6, arithmetic7 and games8, among others. However, the need for a practical application has been pressing. Here we present molecular computational identification (MCID), a demonstration that molecular logic and computation can be applied to a widely relevant issue. Examples of populations that need encoding in the microscopic world are cells in diagnostics or beads in combinatorial chemistry (tags). Taking advantage of the small size9 (about 1 nm) and large 'on/off' output ratios of molecular logic gates and using the great variety of logic types, input chemical combinations, switching thresholds and even gate arrays in addition to colours, we produce unique identifiers for members of populations of small polymer beads (about 100 m) used for synthesis of combinatorial libraries10, 11. Many millions of distinguishable tags become available. This method should be extensible to far smaller objects, with the only requirement being a 'wash and watch' protocol12. Our focus on converting molecular science into technology concerning analog sensors13, 14, turns to digital logic devices in the present work.

Statistical Monitoring of Dynamic Multivariate Processes: Part I: Modeling Auto- and Cross-Correlation

The work in this paper is of particular significance since it considers the problem of modelling cross- and auto-correlation in statistical process monitoring. The presence of both types of correlation can lead to fault insensitivity or false alarms, although in published literature to date, only autocorrelation has been broadly considered. The proposed method, which uses a Kalman innovation model, effectively removes both correlations. The paper (and Part 2 [2]) has emerged from work supported by EPSRC grant GR/S84354/01 and is of direct relevance to problems in several application areas including chemical, electrical, and mechanical process monitoring.