An automated calibration tool for high performance wireless inertial measurement in professional sports

Traditional motion capture techniques, for instance, those employing optical technology, have long been used in the area of rehabilitation, sports medicine and performance analysis, where accurately capturing bio-mechanical data is of crucial importance. However their size, cost, complexity and lack of portability mean that their use is often impractical. Low cost MEMS inertial sensors when combined and assembled into a Wireless Inertial Measurement Unit (WIMU) present a possible solution for low cost and highly portable motion capture. However due to the large variability inherent to MEMS sensors, such a system would need extensive characterization to calibrate each sensor and ensure good quality data capture. A completely calibrated WIMU system would allow for motion capture in a wider range of real-world, non-laboratory based applications. Calibration can be a complex task, particularly for newer, multi-sensing range capable inertial sensors. As such we present an automated system for quickly and easily calibrating inertial sensors in a packaged WIMU, demonstrating some of the improvements in accuracy attainable.

Metacomputing on clusters augmented with reconfigurable hardware

Accepted Version

Precursor adsorption on copper surfaces as the first step during the deposition of copper: a density functional study with van der Waals correction

Copper dimethylamino-2-propoxide [Cu(dmap)2] is used as a precursor for low-temperature atomic layer deposition (ALD) of copper thin films. Chemisorption of the precursor is the necessary first step of ALD, but it is not known in this case whether there is selectivity for adsorption sites, defects, or islands on the substrate. Therefore, we study the adsorption of the Cu(dmap)2 molecule on the different sites on flat and rough Cu surfaces using PBE, PBE-D3, optB88-vdW, and vdW-DF2 methods. We found the relative order of adsorption energies for Cu(dmap)2 on Cu surfaces is Eads (PBE-D3) > Eads (optB88-vdW) > Eads (vdW-DF2) > Eads (PBE). The PBE and vdW-DF2 methods predict one chemisorption structure, while optB88-vdW predicts three chemisorption structures for Cu(dmap)2 adsorption among four possible adsorption configurations, whereas PBE-D3 predicts a chemisorbed structure for all the adsorption sites on Cu(111). All the methods with and without van der Waals corrections yield a chemisorbed molecule on the Cu(332) step and Cu(643) kink because of less steric hindrance on the vicinal surfaces. Strong distortion of the molecule and significant elongation of Cu–N bonds are predicted in the chemisorbed structures, indicating that the ligand–Cu bonds break during the ALD of Cu from Cu(dmap)2. The molecule loses its initial square-planar structure and gains linear O–Cu–O bonding as these atoms attach to the surface. As a result, the ligands become unstable and the precursor becomes more reactive to the coreagent. Charge redistribution mainly occurs between the adsorbate O–Cu–O bond and the surface. Bader charge analysis shows that electrons are donated from the surface to the molecule in the chemisorbed structures, so that the Cu center in the molecule is partially reduced.