The Riesz space structure of an Abelian W*-algebra

Let M be an Abelian W*-algebra of operators on a Hilbert space H. Let M₀ be the set of all linear, closed, densely defined transformations in H which commute with every unitary operator in the commutant M’ of M. A well known result of R. Pallu de Barriere states that if ɸ is a normal positive linear functional on M, then ɸ is of the form T → (Tx, x) for some x in H, where T is in M. An elementary proof of this result is given, using only those properties which are consequences of the fact that ReM is a Dedekind complete Riesz space with plenty of normal integrals. The techniques used lead to a natural construction of the class M₀, and an elementary proof is given of the fact that a positive self-adjoint transformation in M₀ has a unique positive square root in M₀. It is then shown that when the algebraic operations are suitably defined, then M₀ becomes a commutative algebra. If ReM₀ denotes the set of all self-adjoint elements of M₀, then it is proved that ReM₀ is Dedekind complete, universally complete Riesz spaces which contains ReM as an order dense ideal. A generalization of the result of R. Pallu de la Barriere is obtained for the Riesz space ReM₀ which characterizes the normal integrals on the order dense ideals of ReM₀. It is then shown that ReM₀ may be identified with the extended order dual of ReM, and that ReM₀ is perfect in the extended sense.

Some secondary questions related to the Riesz space ReM are also studied. In particular it is shown that ReM is a perfect Riesz space, and that every integral is normal under the assumption that every decomposition of the identity operator has non-measurable cardinal. The presence of atoms in ReM is examined briefly, and it is shown that ReM is finite dimensional if and only if every order bounded linear functional on ReM is a normal integral.

Topology optimization of silicon anode structures for lithium-ion battery applications

This thesis presents a topology optimization methodology for the systematic design of optimal multifunctional silicon anode structures in lithium-ion batteries. In order to develop next generation high performance lithium-ion batteries, key design challenges relating to the silicon anode structure must be addressed, namely the lithiation-induced mechanical degradation and the low intrinsic electrical conductivity of silicon. As such, this work considers two design objectives of minimum compliance under design dependent volume expansion, and maximum electrical conduction through the structure, both of which are subject to a constraint on material volume. Density-based topology optimization methods are employed in conjunction with regularization techniques, a continuation scheme, and mathematical programming methods. The objectives are first considered individually, during which the iteration history, mesh independence, and influence of prescribed volume fraction and minimum length scale are investigated. The methodology is subsequently extended to a bi-objective formulation to simultaneously address both the compliance and conduction design criteria. A weighting method is used to derive the Pareto fronts, which demonstrate a clear trade-off between the competing design objectives. Furthermore, a systematic parameter study is undertaken to determine the influence of the prescribed volume fraction and minimum length scale on the optimal combined topologies. The developments presented in this work provide a foundation for the informed design and development of silicon anode structures for high performance lithium-ion batteries.

The impact of molecular biology on assessment of water quality: advantages and limitations of current techniques

The advent of molecular biology has had a dramatic impact on all aspects of biology, not least applied microbial ecology. Microbiological testing of water has traditionally depended largely on culture techniques. Growing understanding that only a small proportion of microbial species are culturable, and that many microorganisms may attain a viable but non-culturable state, has promoted the development of novel approaches to monitoring pathogens in the environment. This has been paralleled by an increased awareness of the surprising genetic diversity of natural microbial populations. By targeting gene sequences that are specific for particular microorganisms, for example genes that encode diagnostic enzymes, or species-specific domains of conserved genes such as 16S ribosomal RNA coding sequences (rrn genes), the problems of culture can be avoided. Technical developments, notably in the area of in vitro amplification of DNA using the polymerase chain reaction (PCR), now permit routine detection and identification of specific microorganisms, even when present in very low numbers. Although the techniques of molecular biology have provided some very powerful tools for environmental microbiology, it should not be forgotten that these have their own drawbacks and biases in sampling. For example, molecular techniques are dependent on efficient lysis and recovery of nucleic acids from both vegetative forms and spores of microbial species that may differ radically when growing in the laboratory compared with the natural environment. Furthermore, PCR amplification can introduce its own bias depending on the nature of the oligonucleotide primers utilised. However, despite these potential caveats, it seems likely that a molecular biological approach, particularly with its potential for automation, will provide the mainstay of diagnostic technology for the foreseeable future.