Magnetic Particle Imaging: Current and Future Applications,Magnetic Nanoparticle Synthesis Methods and Safety Measures

Magnetic nanoparticles (MNPs) have a wide range of applications; an area of particular interest is magnetic particle imaging (MPI). MPI is an imaging modality that utilizes superparamagnetic iron oxide particles (SPIONs) as tracer particles to produce highly sensitive and specific images in a broad range of applications, including cardiovascular, neuroimaging, tumor imaging, magnetic hyperthermia and cellular tracking. While there are hurdles to overcome, including accessibility of products, and an understanding of safety and toxicity profiles, MPI has the potential to revolutionize research and clinical biomedical imaging. This review will explore a brief history of MPI, MNP synthesis methods, current and future applications, and safety concerns associated with this newly emerging imaging modality.     

Advances in hydrogen engine conversion technology

A Peugeot 505 automobile with a standard 2-1. gasoline engine has been converted to operate on hydrogen under a contract awarded to Billings by the Paris-based auto manufacturer. Research conducted at the Billings Research Laboratories has resulted in the development of a Direct Cylinder Injection (DCI) system which was tested and analyzed in the Peugeot 505 engine. Preliminary tests performed on the system demonstrated satisfactory engine performance operating on hydrogen as compared to gasoline. The DCI system takes greater advantage of the variable equivalence ratio combustion properties of hydrogen, and increased engine efficiency, while eliminating the tendency of hydrogen engines to backfire. This report presents an explanation of the project including DCI development, engine conversion, hydrogen fuel consumption and engine performance data.     

Feasibility study of structural damage detection using NARMAX modelling and Nonlinear Output Frequency Response Function based analysis

Nonlinear Output Frequency Response Functions (NOFRFs) are a series of one-dimensional functions of frequency recently proposed by the authors to facilitate the analysis of nonlinear systems in the frequency domain. The present study is concerned with a feasibility study of the application of the well-known Nonlinear Auto-Regressive Moving Average with eXogenous Inputs (NARMAX) modelling method and the NOFRFs-based analyses to the detection of damage in engineering structures. The new technique includes three steps. First, a NARX model is established by applying the NARMAX modelling method to input and output data collected from a test on an inspected structure. Then, the NOFRFs and an associated index for the inspected structure are determined from the established NARX model. Finally, structural damage detection is conducted by comparing the values of the NOFRF index of the inspected structure with the values of the index for a damage-free structure. An experimental application to the detection of damage in aluminium plates demonstrates the potential and effectiveness of the new damage detection technique.